Development of a Gene Editing Platform to Enhance CAR-T Therapy Through Inducible IL-15 Expression at the PD-1 Locus

Development of a Gene Editing Platform to Enhance CAR-T Therapy Through Inducible IL-15 Expression at the PD-1 Locus | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Development of a Gene Editing Platform to Enhance CAR-T Therapy Through Inducible IL-15 Expression at the PD-1 Locus M. Cortijo-Gutiérrez¹, N. Maldonado-Pérez, M. Tristán-Manzano¹, and 11 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7012598/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 9 You are reading this latest preprint version Abstract Background Adoptive cell therapy (ACT) with genetically engineered T cells expressing chimeric antigen receptors (CARs) has emerged as a promising treatment option for patients with refractory leukaemia or lymphoma. Despite its success in type B malignancies, CAR-T cell therapy still faces some challenges such as toxicity, functional suppression by the tumour microenvironment (TME), and poor persistence in treated patients. Methods This study employed a second-generation CD19-targeting CAR construct to generate engineered CAR-T cells with enhanced functionality through precise genome editing. Using CRISPR/Cas9 technology, the PDCD1 gene was to mitigate T cell exhaustion, and in a parallel knock-in strategy, an IL-15 transgene was inserted at the PDCD1 locus. Gene editing was performed via electroporation of RNP complexes, with AAV6 vectors used for homology-directed IL-15 integration. Editing efficiency and off-target activity were assessed by flow cytometry, Sanger sequencing, ICE, and CAST-Seq. Functional characterization included bulk RNA sequencing, metabolic profiling using Seahorse technology, and cytotoxicity assays against CD19 + target cells. Results We initially demonstrated that αCD19 CAR-T cells lacking PD-1 expression (PD-1 KO) exhibited reduced expansion capacity and overall fitness compared to control CAR-T cells but showed a superior cytotoxicity against PDL1 + target cells. To address the impaired fitness of PD-1 KO CAR-T cells, we generated PD-1KIL-15 CAR-T cells, which combine PD-1 KO with the expression of IL-15 under the control of the PD-1 endogenous promoter. Compared to CAR T PD-1 KO cells, PD-1KIL-15 CAR-T cells displayed improved phenotype, viability, and metabolism. More importantly, they also demonstrated enhanced cytolytic capacity of PDL1 + CD19 + target cells, which correlated with increased resistance to apoptosis and improved cell fitness. Conclusions In summary, we present a next 4th generation CAR-T cells platform (TRUCKs) that integrates PD-1 deletion with the inducible expression of IL-15 upon T cell activation and/or exhaustion. This strategy addresses the limitations associated with knocking-out PD-1 and those associated with sustained IL-15 cytokine expression. The same platform can be used to generate PD-1 KO TRUCKs targeting different antigens and expressing different cytokines under the control of the PD-1 locus. CAR-T PD-1 PD-1KIL-15 IL-15 Gene editing AAV6 CRISPR/Cas9 inducible expression TME TRUCKs physiological expression safe harbour Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background In the last decade, significant progress has been achieved in the development of immunotherapies to fight a wide range of malignancies [ 1 ]. One notable advancement involves the use of adoptive cell therapies (ACTs), particularly the application of genetically engineered T cells equipped with chimeric antigen receptors (CARs) called CAR-T cells. This innovative approach has demonstrated remarkable efficacy, leading to complete remissions in thousands of patients with refractory type B leukemia or lymphoma, demonstrating substantial disease-modifying potential [ 2 – 4 ]. Currently, there are seven FDA-approved CAR T cell products indicated for the treatment of eight distinct malignancies, including Lymphoma, Leukaemia and Multiple Myeloma and with more than 900 ongoing clinical trials worldwide together with CAR-T product ARI-0001, the first CAR-T therapy authorized by the Spanish Agency for Medicines and Medical Devices (AEMPS) under the Hospital Exemption pathway [ 5 ]. This approval allows its use for the treatment of patients over 25 years of age with relapsed or refractory B-cell acute lymphoblastic leukaemia (R/R B-ALL). While the field of CAR-T therapy has experienced significant advancements, its broader application faces a range of clinical and technical challenges. These challenges encompass the emergence of severe, life-threatening side effects following CAR-T cell infusion, tumour cells evading recognition by CAR-T cells, immune rejection of therapeutic cells, and the intricacies of the challenging tumour microenvironment (TME), which blocks T cell activation and contributes to the limited persistence of CAR-T cells [ 6 , 7 ]. Major players of these blocking effects include CTLA-4/CD80, CD86, PD-1/PD-L1, and PD-L2 ligand-receptor pairs, which act as regulators of activated T cells [ 8 ]. Among the immune checkpoint receptors, programmed cell death protein-1 (PD-1), mediates immunosuppression when engaged by its ligand (PD-L1), which is highly expressed in the TME [ 9 , 10 ]. Numerous studies have shown that targeting the PD-1/PD-L1 pathway through various approach leads to remarkable therapeutic effectiveness in cancer patients [ 11 , 12 ]. Notably, PD1 gene editing in CAR-T cell therapy has displayed promising outcomes [ 13 – 20 ], this approach has emerged as a promising strategy to enhance T cell function by overcoming exhaustion and improving antitumor responses. Although there is a consensus regarding the benefits of PD-1 knock-out in T cells, there is still debate about how PD-1 ablation affects the functionality of T cells. From a metabolic standpoint, PD-1 signals were found to be essential for maintaining the delicate equilibrium between mTOR-dependent anabolic glycolysis and fatty acid oxidation programs, which are crucial for meeting the bioenergetic demands of quiescent CD8 T cell memory [ 21 , 22 ]. Other studies have demonstrated that PD-1 plays a role in preserving exhausted T cell populations by preventing excessive proliferation and terminal differentiation [ 23 ]. Thus, PD-1 plays a dual role in T lymphocytes. A second approach to enhancing the therapeutic effectiveness of CAR-T cells involves implementing an armouring strategy with cytokines/chemokines and/or their receptors called T cells redirected for universal cytokine-mediated killing (TRUCKs) or fourth generation CARs. In this regard, it is noteworthy that IL-15 has demonstrated the ability to enhance the antitumour activity of human CAR-T cells when directed against multiple antigens in both blood and solid xenograft tumour models [ 24 – 26 ]. Recognizing the clinical potential of IL-15, this cytokine has been studied as an immunotherapeutic agent against different tumours, and several ongoing clinical trials involving CAR-T cell therapy are underway. These include Phase I studies targeting relapsed/refractory neuroblastoma and osteosarcoma with GD2-specific CAR-T cells expressing IL-15 and a safety switch (NCT03721068), as well as trials examining IL-15-armored Glypican-3-specific CAR-T cells for paediatric solid tumours (NCT04377932, NCT04715191, NCT05103631). Other trials investigate GD2-specific CAR-NKT cells for neuroblastoma (NCT03294954), IL-7/IL-15 pre-treated CD19 CAR-T cells for chemotherapy-resistant B cell lymphoma (NCT02992834), and CAR-T therapies for liver cancer (NCT04093648). However, higher base line or peak serum IL-15 levels, associated with a constitutive expression, are also related to severe toxicity, such as cytokine release syndrome (CRS), graft-versus-host disease (GVHD) and neurotoxicity [ 27 ]. For this reason, we and others have proposed the strategy of an inducible-selected expression to regulate the expression of several molecules including IL-15 [ 28 – 30 ]. Alternatively, knock-in of a large gene cassette coding for a specific protein to re-write cell programs has proven feasible for next-generation T cell therapies. This approach aims to counteract suppressive signals and increase therapeutic efficacy [ 31 ]. Zhang et al. demonstrated an enhanced capacity for eradicating tumour cells in animal models by integrating anti-CD19 CAR-T cells into the PDCD1 locus [ 32 ]. This innovative technique was employed in adoptive therapy for relapsed/refractory aggressive B cell non-Hodgkin lymphoma resulting in an impressive 87.5% success rate in achieving complete remission among treated patients, with sustained responses and no significant adverse effects observed, with a median follow-up of 19.2 months (NCT04213469). Preclinical and clinical studies have consistently demonstrated that IL-15 alone is insufficient to achieve robust therapeutic effects, highlighting the necessity of combining it with other therapeutic agents to maximize its potential [ 33 ]. In particular, the combination of IL-15 with immune checkpoint inhibitors and monoclonal antibodies has shown significantly enhanced efficacy compared to IL-15 monotherapy. Similarly, therapies targeting PD-1 alone have also been found inadequate for inducing strong immune responses and improving clinical outcomes [ 34 ]. Given these limitations, the strategic incorporation of additional combinatorial approaches (especially those activating key metabolic pathways) has been proposed to further strengthen therapeutic responses [ 33 ]. IL-15 emerges as a critical enhancer when used in combination given its pivotal role in regulating essential metabolic and survival pathways in immune cells [ 35 , 36 ]. Moreover, while IL-15 monotherapy has shown limited effectiveness, its combination with checkpoint inhibitor-based approaches has been widely recommended to enhance therapeutic efficacy [ 33 ]. Building on these findings, we developed a strategy to address the limitations of PD-1 KO CAR-T cells while simultaneously enhancing the therapeutic potential of IL-15. Our approach involves a gene-editing strategy that integrates the IL-15 gene into the PD-1 safe harbour locus, creating CD19-specific "armoured" CAR-T cells. This modification not only mitigates the limitations of the PD-1/PD-L1 axis but also enables precise, dosage-dependent regulation of IL-15 expression. By optimizing the controlled administration of IL-15, we enhanced CAR-T cell efficacy while minimizing the adverse effects associated with uncontrolled cytokine expression. Methods Cell lines Namalwa (Burkitt’s lymphoma, ATCC® CRL-1432) and Jurkat (acute T-cell leukemia) cell lines were cultured in RPMI-1640 medium (Biowest) supplemented with 10% fetal bovine serum (FBS, Biowest) and 1% Penicillin/Streptomycin (P/S, Biowest), in an environment with 37°C and 5% CO2. The Namalwa-GFP- Nluc [ 37 ] and Namalwa-PDL1+ (generated in the present work) cell lines were cultured following the same procedure. HEK-293T cell line (human embryonic kidney cells derived from human embryonic kidney, ATCC® CRL-11268) was cultured in DMEM medium (Biowest) with 10% FBS and 1% P/S at 37°C in a 10% CO2 atmosphere. The cells were maintained without exceeding 90% confluence using TryPLE (Gibco) 0.4% after a prior wash with PBS. All cell lines were maintained at the recommended cell density according to ATCC instructions and were regularly tested for the presence of mycoplasma using the MycoAlert Mycoplasma Detection Kit (Lonza). Human primary T cells Primary T cells were obtained from mononuclear cells derived from peripheral blood (PBMCs) of healthy donors, acquired with informed consent at the Reina Sofía Hospital (Córdoba) as well as from the Biobank of the public healthcare system of Andalusia (San Cecilio University Hospital, Granada). The study was conducted in accordance with the ethical committee guidelines, meeting the quality and safety requirements for the donation, collection, storage, distribution, and preservation of human cells and tissues under Spanish regulations (Royal Decree-Law 9/2014). Blood was diluted in a 1:2 to 1:4 ratio with PBS, depending on the cell density. Subsequently, cell separation was carried out using Ficoll (Lymphosep, Biowest), with 1/3 Ficoll and 2/3 diluted blood, through centrifugation without brake or acceleration at 1800rpm for 20 minutes. The mononuclear cell fraction (PBMCs) was collected with a Pasteur pipette and washed twice at 200g for 10 minutes to remove platelets. Afterward, PBMCs were cultured in TexMACS medium (a serum-free medium designed for T cell culture, containing human serum albumin, stable glutamine, and phenol red; Miltenyi Biotec) supplemented with 20 ng/mL IL-2 (Miltenyi Biotec), 5% human AB serum (Biowest), and 1% P/S (Biowest) at a density of 2x10 6 cells/mL, at 37°C with 5% CO2. The following day, the cells were activated with T cell TransAct (an α-CD3/CD28 nanomatrix, 1:100; Miltenyi Biotec). After activation, cells were passaged every 2 or 3 days, maintaining a cell density of 1x10 6 cells/mL. Lentiviral and adeno-associated vectors Lentiviral vectors ARI-0001 vector: a third-generation, self-inactivating lentiviral vector expresses the second-generation anti-CD19 CAR ARI-0001 (A3B1/4-1BB/CD3ζ) under the control of the EF1α promoter. The plasmid was generously provided by Dr. Manel Juan and Dr. María Castella from the Hospital Clínic in Barcelona [ 38 ]. SPDL1 vector: This third-generation, self-inactivating vector, designed using the VectorBuilder database, expresses the PD-L1 protein under the lentiviral SFFV promoter and has been used to generate the Namalwa cell line. Adeno-associated vectors (AAV) Vector v6_IL-15PDCD1 vector, generated by production the VectorBuilder company ( https://en.vectorbuilder.com/products-services/service/aav-packaging.html ), expresses the cDNA of the human cytokine IL-15, followed by a polyA tail and flanked by two 150 bp homology arms, each corresponding to the 3’ and 5’ sequences on either side of the cutting site of guide 3 for the PDCD1 locus, between the two viral ITRs. This construct lacks a promoter, allowing for expression of the transgene under the endogenous promoter. Production of lentiviral particles and titration Maxi-production and plasmids For large-scale plasmid production, transformations were performed in competent E. coli Stbl3 (Life Technologies), and a single colony was selected. A mini-preparation was performed using the Wizard® Plus SV Minipreps DNA Purification System (Promega), followed by a digestion with HindIII to verify correct plasmid amplification. Subsequently, a large-scale bacterial culture was performed, typically 300 mL, shaking at 220 rpm and at 37°C overnight. From this culture, a maxi-preparation of the plasmid was carried out using the NucleoBond Xtra Maxi EF kit (Macherey-Nagel) for the final step with guaranteed sterility. The plasmid yield was quantified using the NanoDrop® ND-1000 (Thermo Fisher), and the 260:280 and 260:230 nm absorbance ratios were evaluated to ensure the absence of cross-contamination. Confirmation of the plasmid maxi-production was performed by enzymatic digestion with HindIII (New England Biolabs) as well as Sanger sequencing. Aliquots were prepared at a concentration of 1 µg/µL (1λ) and stored at -20°C for future use. This procedure ensures the generation of significant amounts of high-quality plasmid and the preservation of samples for subsequent applications. Production of viral particles For lentiviral vector (LV) production, HEK-293T packaging cells or their modified variants were used. In brief, packaging cells were seeded to reach 80% confluence. They were then cotransfected with the transfer plasmid, the HIV-1 packaging plasmid (pCMVΔR8.9), available at https://www.addgene.org/Didier_Trono/ , and the VSV-G envelope plasmid (pMD2.G), also available at https://www.addgene.org/Didier_Trono/ . The transfection ratio was 10:7:3, using polyethyleneimine (PEI) (Alfa Aesar) as the transfection reagent. This process was carried out in DMEM (Biowest) without serum for 20 minutes, after which the mixture was added dropwise to the cells. After 5 hours, the medium was replaced with DMEM supplemented with 10% FBS (Biowest), and the viral supernatant was collected at 48 and 72 hours and stored at -80°C. If necessary, the LV particles were concentrated by ultracentrifugation using the SW32 Ti rotor (Beckman) at 23.000 rpm for 2 hours at 4°C. Viral titration The calculation of the functional viral titer (transducing units per mL, TU/mL) was performed by transducing Jurkat cells. Three serial dilutions of lentiviral supernatant were performed to ensure process linearity. Five days after transduction, the expression of the protein of interest was evaluated by flow cytometry (FACS Canto II, BD Biosciences). The viral titer was calculated at conditions where the expression percentage did not exceed 30%. This threshold was established because below 30%, it is considered that a single DNA copy has been integrated, while above this threshold, the linearity is lost due to the insertion of multiple viral DNA copies. The formula used to estimate the viral titer was as follows: Additionally, from the viral titer, the multiplicity of infection (MOI) was calculated using the formula: \(\:\text{M}\text{O}\text{I}=\frac{\:\text{T}\text{i}\text{t}\text{e}\text{r}\:\left(\frac{\text{T}\text{U}}{\text{m}\text{l}}\right)*volume\:LVs\:\left(ml\right)}{N\text{º}\:transduced\:cells}\) Genetic modification Cell transduction Primary T cells, previously activated with T Cell TransAct (Miltenyi Biotec), were transduced with ARI-0001 lentiviral vector (LVs) at a multiplicity of infection (MOI) of 10 using spinoculation (800g for 60 minutes at 32°C). After 5 hours of incubation in the presence of the LVs, the cells were washed with PBS (300g, 10 minutes) and seeded at a density of 10 6 cells/mL in supplemented TexMACS medium. The percentage of transduced cells was determined by flow cytometry at least 72 hours after transduction. For the transduction of suspension cell lines, 10 5 cells were incubated in a well of a 48-well plate with different lentiviral vectors (LVs) in a maximum volume of 300 µL. In all cases, after 5 hours of incubation, the cells were washed with PBS for 5 minutes at 300g and cultured as described earlier, seeded according to the density recommended by ATCC. The percentage of transduced cells was determined by flow cytometry at least 72 hours after transduction. Genome editing For the Knock-out (KO) technique in PDCD1 locus were edited. A comparison was made between two gRNAs: gRNA1 (CGUCUGGGCGGUGCUACAAC UCCAGGCAUGCAGAUCCCAC, GenScript, 100 µM) and gRNA2 (UCCAGGCAUGCAGAUCCCAC, GenScript, 100 µM) to optimize the knock-out of PD-1 expression. For generating PD-1 KO T cells or CAR-T PD-1 KO cells, PBMCs were activated for 24 hours and transduced with lentiviral vectors to express the CAR. 48 hours post-transduction, the genomic editing of these CAR-T WT cells was performed. In the case of CAR-T PD-1 KO cells, the cells were modified using the CRISPR/Cas9 endonuclease system. First, ribonucleoprotein (RNP) complexes were formed by incubating 3.3 µM Cas9 protein (IDT, 61 µM) with 10 µM of the gRNA targeting the first exon of the PD-1 locus (gRNA2 PD-1: UCCAGGCAUGCAGAUCCCAC, GenScript, 100 µM) in a 1:3 ratio for 20 minutes at 37°C. During this period, the cell density and the required cell number were determined. The cells were washed with PBS, followed by an electroporation buffer (Opti-MEM medium, ThermoFisher). All centrifugations were performed at 300g for 5 minutes at room temperature. The cells were suspended in the solution containing the RNPs, and Opti-MEM was added to reach the final volume of the nucleofection cuvette (20 or 100 µL, Lonza). The mixture was electroporated using the 4D-Nucleofector (Lonza) and the EH-115 program. Afterward, the cells were recovered in TexMACS medium without supplements at 37°C and seeded at a concentration of 2x10 6 cells/mL, considering that the viability post-electroporation was 50%. After 5 hours, the cells were diluted to 1x10 6 cells/mL by adding supplemented TexMACS medium (2X). After 48 to 72 hours, the cells were washed as needed and cultured at 1x10 6 cells/mL in complete medium. Five to seven days after transduction, the percentage of transduced and edited cells was determined, along with phenotypic characterization by flow cytometry. The editing efficiency was confirmed by Sanger sequencing (details below). For performing the knock-in (KI) and generating PD-1KIL-15 CAR-T cells, the procedure was exactly the same, except that 5x10 4 GC/mL of the AAV6 v6_IL-15PDCD1 was added twenty minutes after the membrane pores and DNA breaks were generated. Analysis of the generated gene editing On target gene editing Wild-type (WT) and genetically modified cells (PD-1 KO, PD-1KIL-15 CAR-T) were lysed five to seven days after editing, and genomic DNA was extracted using the QIAamp genomic DNA kit from Qiagen. DNA amplification was performed using KAPA2G Fast Hot Start Ready Mix from Sigma-Aldrich, utilizing 10 ng of DNA and the oligonucleotide primers (Ontarget Guide1 Fw: TCACTCTCGCCCACGTGGA; Ontarget Guide1 Rev: GCCTCCCCCACGGATGGTCT). All reactions were performed in duplicate using the Veriti thermocycler (ThermoFisher) with the following program: 1x (95ºC, 5 min); 40x (94ºC, 45 sec / 60ºC, 20 sec / 72ºC, 30 sec); 1x (72ºC, 10 min). For Sanger sequencing, PCR products were purified using the QIAquick PCR Purification Kit from Qiagen. The resulting sequences were analysed using the ICE (Inference of CRISPR Editing) program ( https://ice.synthego.com/ ), which provides information on editing efficiency and the distribution of insertions/deletions (INDELs). Off-target gene editing The CHOPCHOP tool (available at https://chopchop.cbu.uib.no ) was used to predict in silico potential off-target effects of the gRNA2 PD-1. Five possible off-target sites were selected, and these were subsequently analysed in the DNA of edited and non-edited cells using Sanger sequencing and the ICE program. The sequences of the oligonucleotides used are detailed in ( Supplementary table 1 ). CAST-Seq analysis CAST-Seq analysis was performed, as previously described [ 39 ], on genomic DNA extracted from cells three days after editing with Cas9/gRNA2, with untreated cells serving as a negative control. Several modifications were made to the original workflow to improve specificity: average fragmentation size of the DNA was aimed at an average length of 500 bp [ 40 ]. Library sequencing was conducted on a NovaSeq 6000 system using 2x150 bp paired-end sequencing (GENEWIZ, Azenta Life Sciences). The bioinformatic pipeline included the following changes: sites under investigation were classified as OMT if the p-value was below the threshold of 0.005. Annotation for barcode hopping was incorporated into the CAST-Seq algorithm, and coverage analysis was optimized to reduce execution time by aligning the spacer sequence only to the most covered regions for each site. Biological replicates from three different donors were used in the CAST-seq analysis. Only sites that were significant in at least two of the replicates were considered as putative events ( Supplementary table 2). RNA extraction and quantitative PCR (qPCR) Messenger RNA was extracted from approximately 7x10⁵ edited and non-edited T cells using the RNeasy Plus Mini Kit from Qiagen. Subsequently, reverse transcription (RT-PCR) was performed to generate complementary DNA (cDNA) using the High-Capacity cDNA Reverse Transcription Kit from ThermoFisher, following the manufacturer’s protocol. The same amount of mRNA was used for all samples, and the following program was applied on a ThermoFisher Veriti thermal cycler: 1x (95°C, 15 minutes); 40x (95°C, 15 seconds / 60°C, 30 seconds / 72°C, 30 seconds); 1x (95°C, 1 minute / 55°C, 30 seconds / 95°C, 30 seconds). After obtaining the cDNA, real-time PCR (qPCR) was conducted in duplicate for all samples. The oligonucleotide pairs described in Table 1 were used to analyse the expression of various genes. The amplification program used was: 1x (95°C, 15 minutes); 40x (95°C, 15 seconds / 60°C, 30 seconds / 72°C, 30 seconds); 1x (95°C, 1 minute / 55°C, 30 seconds / 95°C, 30 seconds). The KAPA SYBR FAST qPCR Master Mix (2X) from Kapa Biosystems was used, ensuring that the same amount of cDNA was maintained across all samples. Ultrapure water from Invitrogen was used as the negative control for the PCR. Results were normalized relative to GAPDH cDNA ( Table 1 ). Data analysis was performed using the MxPro software from Agilent, calculating relative gene expression changes with the 2 ΔΔCt method [ 41 ] Table 1. Oligonucleotide sequences used in the genomic editing analysis of KI to generate PD-1KIIL-15 CAR-T cells. PRIMER NAME 5’ – 3’ SEQUENCE 3' IL-15 On Target G_3 Fw TGGGGATGCGGTGGGCTCTA 3' IL-15 On Targe t G_3 Rev CAGAGCTGGGGGCCAAGGCT cDNA IL-15 Fw ACTTGTGTTTACTTCTAAACAGTC cDNA IL-15 Rev TTTGCAACTGGGGTGAACATCA cDNA IL-15 Fw 3.0 CAGTTTGTCTTCTAATGGGAAT GFP Rev 3 CGTCCAGCTCGACCAGGAT BIM Fw CCCTCCTETTCTECCAATETE BIM Rev TCTATCCCTACTCCTTCCCCCT Bcl-xL Fw TCCAAGGCTOTAGGTOGTCA Bcl-xL Rev GGGCATTCAGTGACCTGACA GAPDH Fw GGCCTCCAAGGAGTAAGACC GAPDH Rev TGGTACATGACAAGGTGCGG Allele Editing frequencies using ddPCR The integration of the v6_IL15PDCD1 transgene into the PDCD1 locus was assessed using a duplex digital droplet PCR (ddPCR) assay. Genomic DNA from the edited cells was mixed with two sets of primers/probes ( Table 2 ): a reference set (Ref Fw and Rev) with its probe (HEX) and a set targeting the upstream region of the right homology arm (PDCD1_Rev outside 3’ HA) along with the primer and probe (FAM) located at the PolyA tail (ROB79). Droplets were generated using a Bio-Rad automated droplet generator (Bio-Rad, Hercules, CA, USA), amplified by PCR using a Bio-Rad thermal cycler, and analysed with a Bio-Rad QX200 droplet reader. Integration frequencies were calculated as the ratio of double-positive droplets to all positive reference droplets using the QuantaSoft™ Analysis Pro software. Table 2. Oligonucleotide and probe sequences used in specific integration analysis in PDCD1 transgene. PRIMER NAME 5’ – 3’ SEQUENCE Ref Fw AAGCTATGCAGGTGACAG Ref Rev AGGTAGTTTCTGAACTTCTCC Probe Ref ATGCAGCAGTGCGTCATCCC-HEX-ZEN-IBFQ ROB79 Fw GGGAGGATTGGGAAGACA PDCD1 _Rev outside 3’HA GTTTGGGGTTCTGGCCAGCC Probe Smpl CCCACTGACGGGCACCGGA-FAM-ZEN-IBFQ Flow cytometry CAR detection Expression of the α-CD19 CAR was determined using a goat IgG1 antibody specific to the murine Fab region, conjugated to biotin (Jackson Immunoresearch, 115-065-072, Philadelphia, USA) [ 2 ], followed by incubation with streptavidin-APC (Thermo Fisher) as a secondary antibody. Approximately 50,000 cells were washed with a flow cytometry (FC) wash buffer (PBS + 3% BSA + 2 mM EDTA) and incubated with the anti-murine Fab antibody (1:100) for 20 minutes on ice. After washing, streptavidin-APC (1:330) was added. Fifteen minutes later, extracellular staining for phenotypic and additional markers was performed for another 15 minutes. Cells were washed twice with PBS before acquisition using FACSCantoII or FACS Verse cytometers (Beckton Dickison Biosciences). Detection of hIL-15 Approximately 100,000 cells were washed and stained with desired surface markers. Fixation and permeabilization were performed using the Fix & Perm kit from Nordic MUbio. Briefly, 80 µL of Fixation Reagent A was added for 20 minutes at room temperature. After washing, cells were permeabilized with 80 µL of Permeabilization Reagent B for 10 minutes at room temperature. Without additional washes, anti-hIL-15 APC antibody (MA5-23627, 1:20, ThermoFisher) was added for 30 minutes at room temperature. Two PBS washes were performed before data acquisition on the aforementioned flow cytometers. Phenotype and exhaustion analysis of edited cells Various monoclonal antibodies were used for T-cell phenotypic characterization, including hCD62L-PE-Cy7/APC-Cy7 (1:200), hCD45RA-FITC/Pacific Blue (1:200), hCD3-PerCP-Cy5.5/APC-780/BV711 (1:200), hTIM3-APC-Cy7/PE-CF594 (1:100), hLAG3-PE/eFluor506/AlexaFluor700 (1:100), hPD-L1-APC (1:100), and hPD1-APC/PE (1:100) from ThermoFisher and Biolegend. Extracellular staining was generally performed for 30 minutes on ice and in the dark. Analysis strategies included singlet selection and dead cell exclusion using 4',6-diamidino-2-phenylindole (DAPI, Thermo Fisher) during acquisition, provided violet laser channels were available and cellular permeabilization was absent. Data analysis was performed using FlowJo V10 software (TreeStar). RNA sequencing For bulk RNA-seq sample preparation total RNA from edited and unedited CAR T cells was extracted after three days post αCD3-αCD28 activation with the High Pure RNA Isolation Kit (Roche) according to the manufacturer’s recommendation and later purified and concentrated with the RNA Cleanup Kit (Monarch). The RNA quantity and purity (A260/ A280) ratio were measured on a Nanodrop spectrophotometer (Thermo Fisher Scientific), and the RNA integrity number (RIN) was determined using a 2100 Bioanalyzer with an Agilent RNA 6000 Pico kit (Agilent). mRNA-Sequencing was carried out by Novogene (UK) Company Ltd. Sample quality control, including RIN, was assessed with an Agilent 5400. Subsequently, strand-specific library preparation, including polyA-enrichment, was performed according to their standard protocols and 30M paired-end reads were sequenced on an Illumina NovaSeq X Plus sequencer, using paired-end 150-bp sequencing strategy. The tools used in the quality control of the raw expression FASTQ files where fastQC and MultiQC [ 42 ], adapters and artifacts were trimmed via cutadapt. Reads were aligned to the GRCh38 reference genome for subsequent gene quantification using RSEM [ 43 ] in conjunction with STAR [ 44 ] aligner, thus obtaining the expression matrix for the 9 samples considered in the study. As the interest of the analysis was differential expression, the 3 possible comparisons between the 3 groups were considered (Ctrl-KO, Ctrl-KI, KO-KI), therefore, filtration and normalization was applied for each of the 3 cases separately. For filtration, genes that appeared less than 10 times individually in a minimum of 4 of the 6 samples in the comparison where removed. For normalization, data was normalized with the voom function from limma [ 45 ] R package, and the statistic used in the differential expression analysis was the moderated t test statistic from the same package, taking into account a design matrix that enabled paired sample testing. Genes were sorted based on the moderated t-statistic for GSEA. Gene sets were derived from the Hallmark and C2 Human Collections in MsigDB [ 46 , 47 ] while the analysis tool used was fgsea R package. Functional Studies Cellular activation and exhaustion Among 1.5 × 10⁶ and 2 × 10⁶ cells were plated in duplicate wells of a 48-well plate. One duplicate was activated with TransAct (1:100, Miltenyi Biotec). After three days, the supernatant from both activated and non-activated wells was collected for IL-15 secretion assays and the analysis of pro- and anti-inflammatory cytokine expression. Cell pellets from each well were also collected for RNA or genomic DNA extraction to conduct further studies. hIL-15 Secretion To assess human IL-15 secretion into the medium, we used the ELISA MAX™ Deluxe Set Human IL-15 Kit (Biolegend). Supernatants from WT, PD-1 KO, and PD-1KIL-15 CAR-T cells were collected after three days of continuous activation. IL-15 concentrations in the medium were determined by extrapolating against the standard curve provided in the kit, following the manufacturer's instructions. Cytotoxicity assays The cytotoxic capacity of αCD19 CAR-T cells was evaluated through sequential co-culture with CD19⁺ tumour cells. The assay employed Namalwa cell lines derived from Burkitt's lymphoma (CD19⁺), which constitutively express eGFP-Nanoluciferase (NLuc) (100% eGFP⁺) for in vitro and in vivo monitoring. Specifically, this included Namalwa eGFP-NLuc WT and Namalwa PD-L1⁺ cells (a PD-L1⁺ overexpressing line generated for this study via lentiviral transduction of Namalwa eGFP-NLuc). CAR-T cells and target cells were co-cultured in multiple replicates at an effector-to-target ratio of 12.5:1 in non-supplemented RPMI medium. The assay used 2.5 × 10⁴ Namalwa cells in U-bottom 96-well plates along with 1 × 10⁴ T cells, approximately 20% of which expressed CAR (~ 2 × 10 3 total CAR + cells). As a control, tumour cells were co-cultured with non-transduced (NT) T cells (2 × 10 3 cells). After 48 hours, the absolute counts of target and effector cells were measured using Count Absolute Bright (ThermoFisher), and the phenotype of the T cells was assessed by flow cytometry. When > 80% of the tumour cells were lysed, additional Namalwa cells were added to each replicate (R, re-encounter). The percentage of lysis of CD19⁺ target cells was determined via flow cytometry by measuring the loss of GFP compared to the initial percentage of Namalwa cells in the culture at time 0. $$\:Percentage\:of\:Lysis=1-\left(\:\frac{\%\:Namalwa\:cells\:at\:the\:end\:of\:time}{\%\:Namalwa\:cells\:at\:early\:time}\:\right)\:x\:100$$ Metabolic characterization After 3 days of continuous stimulation with α-CD3/CD28, mitochondrial function of WT, PD-1 KO, and PD-1KIL-15 CAR-T cells was assessed using the Agilent Seahorse XF HS Mini Analyzer and the Cell Metabolic Profiling Kit (Agilent Technologies). CAR-T cells were washed, counted, and suspended in XF RPMI medium containing 10 mM glucose, 2 mM L-glutamine, and 1 mM sodium pyruvate. A total of 1 × 10⁵ cells** were seeded per well on XFP PDL mini plates. During calibration, cells were maintained at 37°C in a non-CO₂ incubator. The oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) were measured under basal conditions and after treatment with: − 1.5 µM oligomycin A (ATP synthase inhibitor) − 2.5 µM BAM15 (mitochondrial uncoupler) − 0.5 µM rotenone + 0.5 µM antimycin A (mitochondrial inhibitors) Mitochondrial energetic and respiratory capacities, such as the spare respiratory capacity (SRC), proton release, and ATP generation, were also analysed. Results were processed using the Seahorse Analytics software available online at [Seahorse Analytics] ( https://seahorseanalytics.agilent.com/ ). Statistical analysis Statistical analyses were conducted using GraphPad Prism 9 (GraphPad Software Inc.). Specific statistical tests are detailed in the legends of each figure. Data are presented as mean ± standard error of the mean (SEM). Comparisons between two groups were performed using either the T-test or the Wilcoxon Mann-Whitney test, depending on the distribution of the data. Results Generation and characterization of PD-1 knock-out αCD19 CAR-T cells. As previously mentioned, while there is broad consensus on the benefits of PD-1 knock-out in CAR-T cells, debate remains regarding its overall impact on their functionality. Therefore, we aimed to investigate the potential effects (both beneficial and detrimental) of PD-1 knock-out on αCD19 CAR-T cells. We first optimized the strategy to knock-out (KO) the PDCD1 locus in T cells. We followed our previously described protocols that use electroporation of gRNA/Cas9 ribonucleoproteins (RNPs) [ 48 – 50 ]. Briefly, T cells were isolated from healthy donors, activated through the CD3/CD28 pathway and electroporated with the RNP complexes. 3 to 5 days later, genome editing efficacy was monitored by flow cytometry and Inference of CRISPR Edits (ICE) analysis (Fig. 1 A, Supplementary Fig. 1) (see M&M for details). Based on previous data in our laboratory, we evaluated two different guide RNAs (gRNAs) designed to target exon 1 of PDCD1 (gRNA1 and gRNA2). Our data showed that gRNA2 outperformed gRNA1, reducing PD-1 expression to undetectable levels by flow cytometry ( Supplementary Fig. 1A) and, consistent with this data, generating over 80% insertion or deletions (INDELs) on ICE analysis (Fig. 1 B ). Additionally, gRNA2 preferentially generated deletions of 1 or 2 nucleotides ( Supplementary Fig. 1B) , both resulting in premature stop codons in the PDCD1 gene. Finally, biased analysis of potential off-target of both gRNAs found no generation of potential off-target in any of them ( Supplementary Table 1) . We therefore selected gRNA2 to investigate in more details the potential genotoxic effects of PD-1 disruption. With this purpose, we used CAST-Seq, a method capable of detecting on- and off-target activity through the identification of structural genomic aberrations. On-target coverage plots derived from the CAST-Seq data revealed expected genomic rearrangements around the target site, including large deletions and inversions, resulting from the PDCD1 locus cleavage (Fig. 1 C and Supplementary Fig. 1C ). Importantly, no significant evidence of off-target mediated translocations (OMTs) was detected in the cells treated with the RNPs (Fig. 1 C). Once established the best protocol for PD-1 KO, we generated PD-1 KO αCD19 cells as described on workflow in Fig. 1 D. The CAR construction used in this study is ARI-0001, chosen due to its potential in clinical application and thanks to collaboration with Dr. Manel Juan's group at Hospital Clinic. This is a second-generation CAR, with 4-1BB and CD3ζ as intracellular signalling domains, designed to target CD19 and expressed under the EF1-α promoter. T cells were transduced with lentiviral vectors (LVs) expressing the ARI-0001 CAR, using a MOI of 10 and two days later electroporated with the RNP (Cas9 + gRNA2). As observed in previous analysis carried out with T cells, ICE analysis revealed around 80% INDELs with an average KO score of 70% (Fig. 1 E, left graph ), which correlates with PD-1 downregulation at the surface of CAR-T cells (Fig. 1 E, right graph and Supplementary Fig. 1D ). Importantly, our analysis also shows that PD-1 editing does not affect CAR expression ( Supplementary Fig. 1E). Next, we investigated potential effects of PD-1 KO on proliferation and phenotype of the αCD19 CAR-T cells. As has been previosly described (Odorizzi, Pauken et al. 2015), we observed a reduction in the expansion capacity of PD-1 KO CAR-T cells after CD3/CD28 estimulation compared to control CAR-T cells (Fig. 1 F ) . Thus, this suggests that the reduced expansion capacity is intrinsically linked to the loss of PD-1. Another key aspect of PD-1 editing is its potential to promote a less exhausted phenotype and enrichement in memory T cells [ 51 ]. In this direction, although our initial phenotype characterization reveal no significative differences in TIM-3 or LAG-3 (Fig. 1 G). We also study the phenotype of this T cells in terms of CD45RA and CD62L expression (T CM (central memory), T SCM (stem cell memory), T EM (effector memory), and T EF (effector)). Activated PD-1 KO CAR-T cells showed a tendency to induce T CM (WT = 44.4% ±6.83 to KO = 54% ±5.04) and T SCM (WT = 21.1% ±5.26 to KO = 32.5% ±5.98) populations, while T EF population decreases from an average of 20.4% ± 7.94 in WT CAR-T cells to 5.21% ±4.69 in PD-1 KO CAR-T cells ( Fig. 1 H, I ) . PD-1 KO CAR-T cells exhibit superior lytic capability against PD-L1 + Namalwa cells but reduced metabolic fitness. We assessed the lytic capability against tumor target cells expressing the PD-L1 generated in our laboratory through lentiviral vector transduction ( Supplementary Fig. 2A and 2B ), as detailed in M&M. Different lytic conditions were tested in order to observe differential killing between Namalwa WT and Namalwa PD-L1⁺ target cells. To reveal functional differences between ARI and ARI PD-1 KO CAR-T cells, we ultimately had to push the system to its limiting conditions. This was achieved by minimizing both the number of T cells and target cells, and by using RPMI medium instead of T cells specific TexMACs medium, thereby creating a more stringent environment to uncover the effects of PD-1 deletion. Once we achieved the exact lysis conditions, three lysis experiments were conducted using T cells obtained from three different healthy donors, transduced with a MOI of 10 to with ARI-0001 CAR LVs and edited for the PDCD1 locus . These cells were co-cultured with Namalwa PD-L1 + target cells at a 12.5:1 ratio (tumoral cell:effector CAR-T cell; T:E_CAR), with Namalwa PD-L1 + target cells, in RPMI media. To further stress the system, we designed a repeated stimulation experiment in which CAR-T cells were exposed every 48 hours to new Namalwa PD-L1 + target cells at the same initial ratio (12.5:1) for a total of four encounters (rechallenge or reencounter) (Fig. 2 A). Monitoring of relative target cells in co-culture is shown in Fig. 2 B, with FACS evaluations every 48 hours. PD-1 KO CAR-T cells exhibited enhanced lytic capacity against Namalwa PD-L1 + cells compared to WT CAR-T cells after three encounters with target cells, with clear tumour escape observed in all three donors after day 2. However, no siginificant differences were detected in terms of exhaustion markers expression ( Supplementary Fig. 2D) , nor phenotype (Fig. 2 C). As expected, and contrary to WT CAR-T cells, repetead encounters of PD-1KO CAR-T cells with PD-L1 positive target cells lead to an increase in both the total number of CAR + T cells after 8 days ( Supplementary Fig. 2E) and the proportion of T CM population (Fig. 2 C). The results observed with PD-1 KO CAR-T cells in terms of proliferation, phenotype, and lytic activity indicate that, although there are clearly positive effects in the presence of PD-L1⁺ target cells, certain alterations may also impair their cytotoxic potential. To further clarify this observation, we performed a comparative metabolic analysis between PD-1 KO CAR-T cells and control CAR-T cells. Our initial analysis showed that PD-1 CAR-T cells had a reduction in the extracellular acidification rate (ECAR)(Fig. 2 D), indicating that they produce less energy through glycolysis. This is consistent with the findings showing that PD-1 KO enhances a memory phenotype, since memory T cells produce less energy through glycolisis compared to effector T cells. Interestingly, and contrary to what is expected for memory CAR-T cells, PD-1 KO CAR-T cells exhibited a reduced oxygen consumption rate (OCR)(Fig. 2 E, left) and spare respiratory capacity (SRC)(Fig. 2 E, right), which assess mitochondrial function and capacity for energy production, respectively, indicating decreased oxidative phosphorylation efficiency in PD-1 KO CAR-T cells. To corroborate this finding, we examinated the cells ability to generate energy (ATP) through glycolysis (glycoATP) and mitochondria (mitoATP). In line with the obtained OCR and SRC parameters, PD-1 KO CAR-T cells showed a five-fold reduction in mitochondrial energy production and about three times less glycolytic energy production compared to WT CAR-T cells (Fig. 2 F). These findings suggest that PD-1 KO CAR-T cells have lower overall metabolic activity and energy production resulting in reduced overall cellular fitness. This would explain the lower proliferative potential of PD-1 KO CAR- T cells as well as the lower lytic activity of these cells when encountering PD-1L negative targets. Engineering CAR-T cells to express IL-15 under the PD-1 promoter (PD-1KIL-15 CAR-Ts) improve proliferation and survival of PD-1-KO CAR-T cells Our previous results show that PD-1 KO CAR-T cells enhance their lytic capacity against PD-L1 + tumor cells and improved memory subpopulation frequencies. However, they exhibit lower lytic capacity against PD-L1 negative targets, along with reduced proliferative capacity and metabolic fitness. To address this issue, we investigated whether controlled expression of the cytokine IL-15 could enhance the potency of PD-1KO CAR-T cells due to the role of this cytokine regulating T cell bioenergetics. We designed a knock-in (KI) genome editing platform to simultaneously knock-out PD-1 and express IL-15 through the PD-1 promoter by inserting a IL-15 complementary DNA (cDNA) into the exon 1 of PD-1 exon 1 (Fig. 3 A, top). With the aim of monitoring IL-15 expression driven through the inserted cassette and to avoid residual PD-1 expression, we desingned a DNA donor that included a eGFP cDNA after the 2A peptide and a polyadenilation signal ( Fig. 3 A, middle). The DNA donor was included in a AAV6 vector, which is highly efficient in human T cells. With this construct once inserted in the target location, the genome edited T cells will lack PD-1 and express IL-15 and eGFP only under T cell activation and/or T cells exhaustion ( Fig. 3 A bottom). To achieved high T cells KI efficiency we used a previously established procedure that combine RNP electroporation with AAV6 transduction [ 52 ] and compared most used MOI 10 4 versus 5x10 4 GC/mL ( Supplementary Fig. 3A ). We next analysed IL-15 (Fig. 3 B left ) and PD-1 (Fig. 3 B right ) expression levels in control CAR-T cells (WT) versus PD-1KIL-15 CAR-T cells at baseline and after activation. As expected, PD-1 expression was significantly reduced. Importantly, the expression pattern of exogenous IL-15 (Fig. 3 C, botton ) mimicked that of PD-1 (Fig. 3 C, top ) in the PD-1KIL-15 CAR-T cells edited population (80% editing efficiency), with both increasing upon T cell activation. This data was in agreement with the IL-15 controlled expression by the PD-1 gene promoter. To further confim this, we measured total secreted IL-15 by ELISA. At baseline, control and PD-1KIL-15 CAR-T cells express similar IL-15 levels (around 17ng/ml). However, upon activation, only PD-1KIL-15 cells increased IL-15 levels to over 24ng/ml (Fig. 3 D), which confirmed that PD-1KIL-15 CAR-T cells not only express intracellular IL-15, but also secrete it. Finally, we analysed by RT-PCR, the levels of endogenous IL-15 versus IL-15 expressed through the integrated DNA donor using specific set of primers for each (See M&M and Supplementary Fig. 3B ). As expected, most of the IL-15 expressed by PD-1KIL-15 cells comes from the integrated DNA donor (Fig. 3 E). Since IL-15 has a major role on promoting T cells cell survival and proliferation, we next compared both parameters in control, PD-1 and PD-1KIL-15 CAR-T cells. First, we studied the proliferative capacity of these cells generated from three donors. Our data showed that PD-1KIL-15 CAR-T cells regained their proliferative capacity in all donors, even compared to unedited CAR-T cells (FIG. 3 F). Next, we analysed the expression levels of BIM (pro-apototic) and Bcl-xl (anti-apoptotic) proteins, which are known to be downregulated and upregulated, respectively, by IL-15. We observed an increase of both proteins compared to WT unactivated cells, upon activation in WT CAR-T cells (Fig. 3 G, dark blue bars ) that was not present in PD-1 CAR-T cells (Fig. 3 G, dark and bright purple bars ). In addition, the activated PD-1 KO CAR-T cells showed a strong reduction of the anti-apoptotic Bcl-xL gene, from 1 in unactivated WT cells to 0.422, that could account in part for it low proliferation capabilities. Expression of BIM and Bcl-xL related to the effects of IL-15 could explain the increased proliferative capacity of PD-1KIL-15 CAR-T cells. These expression data showed that BIM expression decreased from 0.96 in CAR-T WT cells to 0.458 in PD-1KIL-15 CAR-T cells. Similarly, Bcl-xL expression increased from an average of 1 in CAR-T WT cells to 1.98 in PD-1KIL-15 CAR-T cells (Fig. 3 G, dark and bright grey bars). Finally, we also evaluated the immunophenotype of edited CAR-T cells using CD45RA and CD62L markers to determine T cell subpopulation distribution. After three days of activation, IL-15 expression did not significantly affect memory population distribution compared to CAR-T PD-1 KO cells, except for a reduction of T EM cells (Fig. 3 H). PD-1IKL-15 CAR-T cells exhibit enhanced glycolytic and mitochondrial ATP production compared to PD-1 KO CAR-T cells The enhanced proliferative potential observed in PD-1KIL-15 CAR-T cells, likely due to increased IL-15 secretion (Fig. 3 ), prompted us to investigate whether the metabolic impairment caused by PD-1 knock-out was also reversed. As shown in Fig. 4 A and consistent with previous analyses, ECAR, a marker of anaerobic metabolism, was higher in P D-1KIL-15 CAR-T cells (34.42 mpH/min/cells) compared to PD-1 KO CAR-T cells (18.88 mpH/min/cells), although it did not reach the glycolytic levels observed in CAR-T WT cells (51.05 mpH/min/cells). As done previously with PD-1 KO CAR-T cells, we also analysed oxidative metabolism by measuring OCR and SRC. Similar patterns were observed in the OCR analysis (Fig. 4 B, left ), where IL-15-expressing cells showed increased oxygen consumption rates compared to PD-1 KO CAR-T cells. Furthermore, PD-1KIL-15 CAR-T cells exhibited a higher SRC than PD-1 KO CAR-T cells, effectively reversing the mitochondrial metabolic deficiency induced by PD-1 knock-out and indicating a more robust energetic profile (Fig. 4 B, right ), completely restoring these mitochondrial metabolic characteristics in PD-1 edited cells. ATP production analysis revealed a pronounced enhancement in the bioenergetic profile of PD-1KIL-15 CAR-T cells (Fig. 4 C). Specifically, glycolytic ATP production (glycoATP) was increased by approximately 1.8-fold compared to PD-1 KO CAR-T cells, indicating improved efficiency in anaerobic energy generation. More strikingly, mitochondrial ATP production (mitoATP) exhibited an almost six-fold increase in PD-1KIL-15 CAR-T cells compared to PD-1 KO CAR-T cells, highlighting a profound restoration of mitochondrial function. This This enhancement of mitochondrial activity suggests a reactivation of the oxidative phosphorylation pathways, likely facilitated by IL-15-induced signaling events that promote mitochondrial biogenesis, respiratory chain efficiency, or both. The elevated mitoATP levels indicate not only a higher basal energy output but also an enhanced capacity to meet energy demands during activation and proliferation (critical features for the sustained functionality and persistence of CAR-T cells in therapeutic settings). This metabolic reprogramming toward a more oxidative and efficient energy profile underscores the potential of IL-15 expression to overcome the metabolic exhaustion typically associated with PD-1 disruption. We also proved that PD-1KIL-15 CAR-T cells displayed higher OCR when compared with PD-1 KO CAR-T cells, reaching the same levels as WT cells ( Fig. 4 D ). As OCR is a strong indicator of the phenotype and fitness of immune cells, in effector terms, we could conclude that PD-1KIL-15 CAR-T cells predominantly present a memory phenotype in addition to having a greater antitumour capacity. Once PD-1KIL-15 CAR-T cells where characterized, we proceeded to analyse their antitumour activity against PD-L1 + target cells. WT CAR-T cells, PD-1 KO CAR-T cells, and PD-1KIL-15 CAR-T cells generated from three different healthy donors were subjected to four encounters with Namalwa PD-L1 + target cells (Fig. 4 E). Target cells persistence is significantly compromised when co-cultured with PD-1KIL-15 CAR-T cells, in comparison with those co-cultured with CAR-T WT cells (Fig. 4 F). Lytic activity was evaluated every 24 hours for the first two days, and every 48 hours from day 2 onward. At the end of the experiment (day 8), phenotype and persistence of the different CAR-T cells were analysed. PD-1KIL-15 CAR-T cells were able to maintain a higher lysis capacity compared to CAR-T WT cells (Fig. 4 F, day 2 ). The exhaustion markers TIM-3 and LAG-3 are expressed similarly in both WT CAR-T and PD-1 KO CAR-T cells. However, both markers are reduced in PD-1KIL-15 CAR-T cells, with a significant reduction observed in the case of LAG3 (Fig. 4 G). At end point, PD-1 KO CAR-T cells increased in number up to two-fold compared to baseline, whereas PD-1KIL-15 CAR-T cells exhibited a three-fold increase ( Fig. 4 H ) , suggesting improved persistence capacity. This data is consistent with the enhanced lysis efficiency of PD-1KIL-15 CAR-T cells ( Fig. 4 F ). Finally, subpopulations analysis by flow cytometry (based on the expression of CD45RA and CD62L markers) after different encounters with PD-L1 + target cells showed that PD-1KIL-15 CAR-T cells exhibited a significant increase in T CM cells compared to WT CAR-T cells (77.3% ± 7.82 vs. 64.6% ±0.47) and a significant decrease in T SCM cells compared to WT CAR-T cells (9.16% ± 2.64 vs. 18.5% ±4.07. These variations in memory populations align with the observed lytic capacity, as T SCM cells have high proliferative potential but lower effector capacities compared to T EM and T CM cells (Fig. 4 I). RNA sequencing analysis confirms integration and expression of IL-15 and its benefits on CAR-T cells in contrast to PD-1 KO CAR-T cells To gain further insight into the molecular mechanisms underlying our PD-1KIL-15 CAR-T cells, we performed RNA sequencing (RNA-seq) followed by gene set enrichment analysis (GSEA) to identify differentially regulated pathways. RNA-seq was conducted on the three CAR-T cell populations from three different donors three days after activation to assess how the knock-in strategies affected CAR-T cell function. This approach enabled us to compare, at transcriptomic level, the effects of PD-1 ablation and/or the addition and expression of the IL-15 cytokine under the control of the endogenous PD-1 promoter. The analysis was performed on bulk populations, and no significant differences were observed in CAR expression, PD-1 expression, or IL-15 integration across donors or conditions, ensuring that the comparisons were not biased by variability in transgene expression or editing efficiency. Conversely, PD-1 KO CAR-T cells displayed enrichment of pathways linked to cellular stress, serum deprivation-induced apoptosis, and mitochondrial dysfunction (Fig. 5 A), consistent with their reduced glycolytic and mitochondrial ATP production (Fig. 2 D-F) and lower cytotoxic efficacy over repeated tumour encounters ( Supplementary Fig. 2C and Fig. 4 F). This is also reflected in the increased LAG-3 expression ( Supplementary Fig. 2D and Fig. 4 G), their reduced ability to maintain T cell expansion under chronic stimulation (Fig. 4 H), and their apoptotic protein expression profile (Fig. 3 G) indicating functional exhaustion. As shown in FIG. 5 , in contrast with PD-1 KO transcriptomic profile, PD-1KIIL-15 CAR-T cells displayed a unique transcriptional profile characterized by an increase in enrichment in mitochondrial respiration, oxidative phosphorylation, fatty acid metabolism, and electron transport chain-related pathways compared to both PD-1 KO CAR-T and WT CAR-T cells (FIG. 5 A and 5 B). These transcriptomic features are consistent with the enhanced mitochondrial function observed in the Agilent Seahorse assay (FIG. 4 B–D), including increased OCR, SRC, and mitochondrial ATP production. This elevated mitochondrial gene expression in Fig. 5 aligns with early phenotypic observations observed in Fig. 3 H, where PD-1KIL-15 CAR-T cells showed higher frequencies in T SCM populations shortly after activation, suggesting an early shift toward a long-lived metabolic program. These features are further maintained and expanded upon in Fig. 4 , where PD-1KIL-15 CAR-T cells exhibit lower exhaustion marker expression (Fig. 4 G), and a higher frequency of T CM cells at later time points, supporting the hypothesis of superior persistence and stemness-like qualities, probably as a result of IL-15 expression (Fig. 4 I). In addition to metabolic rewiring, Fig. 5 A reveals significant enrichment of mTOR and KRAS signalling pathways in PD-1KIL-15 CAR-T cells, hallmarks of T cell proliferation, activation, and survival. These findings support the increased CAR-T cell expansion observed in the co-culture assays (Fig. 3 F and 4 H), and stand in line with the transcriptional signatures observed in Fig. 5 , where PD-1KIL-15 CAR-T cells show upregulation of gene modules related to cell growth, proliferation, and cytokine signalling. Together, this data integrates phenotypic, functional, and transcriptional evidence to show that PD-1KIL-15 CAR-T cells outperform PD-1 KO and WT CAR-T cells through coordinated mitochondrial reprogramming, reduced exhaustion, and enhanced memory formation. The targeted insertion of IL-15 into the PDCD1 locus not only preserves T cell fitness but also actively promotes long-term metabolic and functional advantages, which are crucial for sustained antitumour responses in adoptive cell therapies. Discusion CAR-T therapy combines adoptive cell therapy, immunotherapy and gene therapy, and has achieved significant success in treating haematological malignancies such as B-cell leukaemia, lymphomas and multiple myeloma. However, 50–70% of patients relapse post-treatment, with higher relapse rates in specific lymphoma and myeloma subtypes [ 53 , 54 ]. These setbacks are often attributed to insufficient cell persistence, antigen escape, and tumour-induced immunosuppressive microenvironments, particularly in solid tumours [ 55 ]. To address these challenges, immune checkpoint inhibitors (ICIs)—particularly those targeting the PD-1/PD-L1 axis—have been incorporated into therapeutic regimens to enhance CAR-T efficacy [ 56 , 57 ], and are now being used in combination with CAR-T cells to enhance their efficacy [ 58 – 60 ]. In parallel, gene editing approaches to disrupt PD-1 and other inhibitory receptors (as LAG-3 or TIM-3) have emerged as promising strategies. Although PD-1 knock-out (KO) has been proven to improve CAR-T cell function and antitumour responses, contrasting findings also highlight risks such as premature T cell exhaustion and reduced persistence, which appear to be highly dependent on the CAR construct design, target antigen, and experimental conditions [ 61 – 63 ]. Building upon these findings, our study investigated the functional and metabolic consequences of PD-1 ablation in CAR-T cells, while also introducing a novel knock-in strategy that leverages the endogenous PD-1 promoter to dynamically regulate IL-15 expression. Our PD-1 KO model aimed to block PD-1/PD-L1 signalling [ 64 ] using Cas9/gRNA electroporation, reflecting mechanisms similar to FDA (and EMA) approved monoclonal antibody therapies [ 65 ]. Consistent with previous works, PD-1 KO led to altered T cell activation kinetics and metabolic profiles. We observed that, contrary to several reports [ 15 , 16 , 32 , 66 ], PD-1 KO CAR-T cells showed reduced expansion, particularly in the absence of PD-L1 stimulation. Our αCD3/αCD28 stimulation model demonstrated that CAR-T WT cells outperformed PD-1 KO counterparts in proliferation, supporting the idea that PD-1 deletion may disrupt activation thresholds and homeostatic control, leading to overactivation and terminal differentiation [ 23 , 62 ] Interestingly, RNA-seq analysis of PD-1 KO CAR-T cells revealed upregulation of gene signatures associated with cell proliferation, although these transcriptional changes did not translate into enhanced proliferation in our ex vivo models. This was corroborated by Seahorse metabolic analysis analysis and RNA-seq data, which showed a marked reduction in both glycolytic and mitochondrial ATP production (GlycoATP and MitoATP), highlighting the role of PD-1 in balancing glycolysis with FAO/OXPHOS metabolic pathways [ 21 , 67 ]. Additionally, the elevated expression of apoptotic pathways, likely compromises their ability to maintain the proliferative program. Therefore, even though the pathways related to proliferation are transcriptionally active, the lack of metabolic fitness prevents their functional realization. This emphasizes the importance of coupling transcriptional reprogramming with metabolic support to achieve effective cellular function. One possible explanation for this phenomenon is that the activation of proliferation-associated genes, such as MYC , E2F , and cyclin family members, can initiate a cell cycle entry program, but the continuation of this program requires robust ATP generation and maintenance of redox balance. PD-1 KO cells, due to their impaired mitochondrial capacity and insufficient glycolytic flexibility, may experience energetic stress that leads to the activation of cellular checkpoints such as AMPK or p53, ultimately halting cell cycle progression [ 68 – 72 ]. Additionally, high intracellular stress and reactive oxygen species (ROS) levels may further compromise survival pathways, shifting the balance toward apoptosis rather than sustained proliferation. This hypothesis is further supported by our observation of increased expression of apoptotic markers in PD-1 KO CAR-T cells. Expression evaluation together with transcriptomic analysis indicated elevated levels of pro-apoptotic molecules such as BIM, PUMA, and caspase-related genes, while anti-apoptotic regulators like Bcl-2 and Bcl-xL were comparatively underexpressed [ 73 , 74 ]. These findings suggest that, in the absence of PD-1, the imbalance between metabolic stress and survival signaling primes CAR-T cells for apoptosis, thereby limiting their proliferative capacity and functional persistence. Taken together, these findings demonstrate that transcriptomic signatures alone do not fully predict functional outcomes. In the case of PD-1 KO CAR-T cells, a superficial increase in proliferation-related gene expression masks an underlying fragility rooted in metabolic insufficiency. This has important implications for the design and interpretation of gene editing strategies in CAR-T cells: interventions must consider not only the removal of inhibitory signals but also the preservation (or enhancement) of cellular fitness. Our data underscore the essential role of metabolic support in enabling CAR-T cells to fully execute their transcriptional programs. While PD-1 ablation effectively removes inhibitory checkpoints, it simultaneously disrupts metabolic homeostasis, highlighting an unintended trade-off between cellular activation and long-term functionality. In the absence of sufficient mitochondrial capacity and glycolytic adaptability, CAR-T cells are unable to sustain their activated state, leading instead to metabolic exhaustion, increased apoptosis, and impaired persistence. These findings suggest that immune checkpoint disruption must be accompanied by strategies that preserve or enhance metabolic fitness to ensure durable antitumour responses. To address this limitation, we explored a targeted knock-in strategy to couple IL-15 expression to the endogenous PDCD1 promoter. This approach aimed to simultaneously block PD-1 signaling and provide metabolic and survival support through localized IL-15 production during T cell activation. Our design enables IL-15 expression upon T cell activation, mimicking physiological demand and avoiding systemic IL-15 toxicity [ 75 , 76 ]. We validated site-specific insertion by qPCR and ELISA, showing 8-fold increase in IL-15 mRNA in activated cells. PD-1KIL-15 CAR-T cells provides a compelling illustration of how metabolic and functional deficiencies can be mitigated by coupling immunoregulatory gene edits with cytokine support. IL-15 expression under the PD-1 promoter not only aligns cytokine delivery with T cell activation but also promotes mitochondrial biogenesis, enhances oxidative metabolism, and stabilizes the expression of anti-apoptotic proteins [ 77 – 80 ]. These effects collectively restore the capacity for sustained proliferation and cytotoxic activity, particularly under conditions of chronic antigen stimulation. Moreover, the coordinated regulation of IL-15 ensures that its expression remains tightly linked to cellular activation status, preventing toxicity while maximizing functional benefit. Functionally, PD-1-KIL-15 CAR-T cells demonstrated markedly improved expansion capacity and metabolic performance, characterized by enhanced mitochondrial respiration, increased mitochondrial ATP production, and elevated spare respiratory capacity (all hallmarks of metabolically fit, long-lived T cells). These functional gains were consistent with transcriptomic signatures enriched for oxidative phosphorylation, fatty acid oxidation, and adipogenesis pathways, which are typically associated with memory-like T cell phenotypes and long-term persistence. Importantly, the metabolic advantage conferred by IL-15 expression appears to translate into improved survival capacity, as evidenced by the upregulation of anti-apoptotic genes such as Bcl-xL and the downregulation of pro-apoptotic genes like BIM , observed through both qPCR and RNA-seq analyses [ 73 , 77 , 81 , 82 ] Altogether, this data suggests that controlled IL-15 expression under the PDCD1 promoter not only compensates for the metabolic stress induced by PD-1 ablation but also enhances the persistence and survival of CAR-T cells by reprogramming their bioenergetic and apoptotic profiles. The superiority of PD-1KIL-15 CAR-T cells was also reflected in their immunophenotypic profile. These cells exhibited increased central memory and stem-like subpopulations, with reduced expression of the exhaustion markers LAG-3 and TIM-3. These features are closely tied to long-term persistence and have been associated with improved clinical outcomes in CAR-T therapies [ 83 ] [ 84 ]. Additionally, PD-1KIL-15 CAR-T cells demonstrated superior cytotoxicity over multiple rounds of antigen exposure, confirming their resilience and functional competence in stress-inducing environments. In summary, our study highlights the dual challenge of overcoming immune suppression while preserving CAR-T cell fitness. While PD-1 knock-out offers initial benefits, its long-term effects may be detrimental unless counterbalanced by supportive cytokine signalling. By integrating IL-15 expression under endogenous PD-1 control, pdTRUCKIL-15 cells achieve enhanced persistence, metabolism, and cytotoxicity, offering a promising next-generation CAR-T design for durable antitumour immunity. Conclusions In summary, this study provides a comprehensive evaluation of the PD-1/PD-L1 axis in the context of CAR-T cell therapy. We investigated the functional consequences of PD-1 ablation in CAR-T cells, observing distinct changes in PD-1 expression kinetics in both PD-1 KO and unmodified T cells upon activation, thereby highlighting the importance of PD-1 in the tumour immune landscape. Our research further explored the metabolic impact of PD-1 knock-out , revealing significant reductions in ATP production and alterations in metabolic pathways, which may affect T cell functionality and expansion. To enhance the therapeutic potential of PD-1 KO CAR-T cells, we incorporated controlled IL-15 expression within the PDCD1 locus, resulting in improved cell expansion, enhanced fitness, and a memory-like phenotype. Notably, PD-1 KO CAR-T cells, especially those expressing IL-15, demonstrated superior lysis capabilities and reduced exhaustion marker expression, underscoring their promise as effective therapeutic agents. However, while PD-1 ablation enhances antitumour potential, it also induces metabolic stress that can limit CAR-T cell persistence and expansion. By coupling IL-15 expression to the endogenous PDCD1 locus, we restored metabolic fitness and promoted a memory-like, apoptosis-resistant phenotype. These findings highlight the importance of balancing immune activation with metabolic support and demonstrate the potential of combinatorial gene editing strategies to improve CAR-T cell efficacy, particularly against PD-L1–expressing tumours. Future in vivo studies using animal models will be conducted to validate and further characterize these findings in a physiological context Declarations Funding This publication is based upon work from COST Action Gene Editing for the Treatment of Human Diseases, CA21113 ( https://www.genehumdi.eu ) and is supported by the COST. The study was also supported by the Consejería de Universidad, Investigación e Innovación under Plan Andaluz de Investigación, Desarrollo e Innovación (PAIDI 2020) ( ProyExcel_00875 ) de la junta de Andalucía. And PI-0216-2024 uCARAML-Nano , and PECART-0027-2020 ,funded by la Consejería de Salud y Consumo de la Junta de Andalucía. This project was funded by Spanish ISCIII Health Research Fund and the European Regional Development Fund (FEDER) through research grants PI18/01016 (CH), PI18/00330 (KB), PI21/00298 and PI24/00888 (FM). ISCIII– NextGenerationEU funds - actions of the Recovery and Resilience Mechanism: Red TerAv RD21/0017/0004 and TerAv + RD24/0014/0005 (FM). Ministerio de Ciencia e innovación (MICIN). Plan de Recuperación, transformación y resilencia, Centro para el Desarrollo Tecnológico Industrial (CDTI) and European Union-Next Generation EU: Research grants 00123009/SNEO-20191072 (FM), PMPTA22/00060 (FM) Consejería de Salud y Familias (CSyF) -Junta de Andalucía - FEDER/European Cohesion Fund (FSE) for Andalucía: Grants: 2 016000073332-TRA, CARTPI-0001-201, PECART-0031-2020 y PI-0236-2024 (FM). Ministerio de Ciencia e innovación (MICIN) – líneas estratégicas: Grant PLEC2021-008094 (FM). European Union’s Horizon research and innovation program — Grant agreement no. 101057438 (geneTIGA) for C.F, R.O.B and T.C. K.B. held a Nicolas Monardes contract from Consejería de Salud y Consumo de la Junta de de Andalucía, MTM is funded by a Postdoctoral Contract RHJ-0106-2024 Consejería de Salud y Consumo Junta de Andalucía (Spain). Y.L. is supported by the the Novo Nordisk Foundation ( NNF21OC0072031, NNF21OC0068988 ) and the Lundbeck Foundation ( R396-2022-350 ). Author Contribution Author Contributions•M.C.-G. (M. Cortijo-Gutiérrez): Contributed to the conception and design of the study, performed experiments, and drafted the manuscript.•K.B. (K. Benabdellah): Contributed to study conception and supervision, performed data interpretation, and drafted and revised the manuscript and secured project funding. •N.M.-P. (N. Maldonado-Pérez): Participated in data acquisition and experimental procedures.•M.T.-M. (M. Tristán-Manzano): Contributed to data acquisition and figure preparation.•K.P. (K. Pavlovic): Assisted in experimental design and data collection.•P.J.-L. (P. Justicia-Lirio): Performed data analysis •C.F.-G. (C. Fuster-García): Contributed to bioinformatics analyses and data interpretation.•P.C.-S. (P. Carmona-Sáez): Supervised bioinformatics analysis and contributed to data interpretation.•T.C. (T. Cathomen): critically revised the manuscript.•R.O.B. (R. O. Bak): Contributed to experimental strategy for gene editing and data interpretation.•P.P.J.-B. (P. P. Jurado-Bascón): Contributed to interpretation of RNAseq l data.•I.C.H. (I. C. Herrera): Provided clinical insights and contributed to data interpretation.•Y.L. (Yonglun Luo): Contributed to gene editing methodology.•F.M. (F. Martín): Supervised the project and substantially revised the manuscript.All authors have read and approved the final manuscript and agree to be accountable for all aspects of the work. Acknowledgement WE would like to thanks, Geoffroy Andrieux (from the Institute of Medical Bioinformatics and Systems Medicine, Medical Center-University of Freiburg) for his help with the bioinformatic part in the CAST-Seq pipeline Data Availability Data is provided within the manuscript or supplementary information files References Zhang M, Liu C, Tu J, Tang M, Ashrafizadeh M, Nabavi N, Sethi G, Zhao P, Liu S: Advances in cancer immunotherapy: historical perspectives, current developments, and future directions. Molecular cancer 2025, 24:136. Pasvolsky O, Kebriaei P, Shah BD, Jabbour E, Jain N: Chimeric antigen receptor T-cell therapy for adult B-cell acute lymphoblastic leukemia: state-of-the-(C)ART and the road ahead. Blood advances 2023, 7:3350–3360. Brudno JN, Maus MV, Hinrichs CS: CAR T Cells and T-Cell Therapies for Cancer: A Translational Science Review. JAMA 2024, 332:1924–1935. Patel KK, Tariveranmoshabad M, Kadu S, Shobaki N, June C: From concept to cure: The evolution of CAR-T cell therapy. Molecular therapy: the journal of the American Society of Gene Therapy 2025, 33:2123–2140. Martinez-Cibrian N, Ortiz-Maldonado V, Espanol-Rego M, Blazquez A, Cid J, Lozano M, Magnano L, Gine E, Correa JG, Mozas P, et al: The academic point-of-care anti-CD19 chimeric antigen receptor T-cell product varnimcabtagene autoleucel (ARI-0001 cells) shows efficacy and safety in the treatment of relapsed/refractory B-cell non-Hodgkin lymphoma. British journal of haematology 2024, 204:525–533. Khan AN, Asija S, Pendhari J, Purwar R: CAR-T cell therapy in hematological malignancies: Where are we now and where are we heading for? European journal of haematology 2023. Mucha SR, Rajendram P: Management and Prevention of Cellular-Therapy-Related Toxicity: Early and Late Complications. Current oncology 2023, 30:5003–5023. Wang Q, Shao X, Zhang Y, Zhu M, Wang FXC, Mu J, Li J, Yao H, Chen K: Role of tumor microenvironment in cancer progression and therapeutic strategy. Cancer medicine 2023, 12:11149–11165. Yamaguchi H, Hsu JM, Yang WH, Hung MC: Mechanisms regulating PD-L1 expression in cancers and associated opportunities for novel small-molecule therapeutics. Nature reviews Clinical oncology 2022, 19:287–305. Li Y, Sharma A, Schmidt-Wolf IGH: Evolving insights into the improvement of adoptive T-cell immunotherapy through PD-1/PD-L1 blockade in the clinical spectrum of lung cancer. Molecular cancer 2024, 23:80. Kraehenbuehl L, Weng CH, Eghbali S, Wolchok JD, Merghoub T: Enhancing immunotherapy in cancer by targeting emerging immunomodulatory pathways. Nature reviews Clinical oncology 2022, 19:37–50. Lin X, Kang K, Chen P, Zeng Z, Li G, Xiong W, Yi M, Xiang B: Regulatory mechanisms of PD-1/PD-L1 in cancers. Molecular cancer 2024, 23:108. Lah S, Kim S, Kang I, Kim H, Hupperetz C, Jung H, Choi HR, Lee YH, Jang HK, Bae S, Kim CH: Engineering second-generation TCR-T cells by site-specific integration of TRAF-binding motifs into the CD247 locus. Journal for immunotherapy of cancer 2023, 11. Yang Z, Wu H, Lin Q, Wang X, Kang S: Lymphopenic condition enhanced the antitumor immunity of PD-1-knockout T cells mediated by CRISPR/Cas9 system in malignant melanoma. Immunology letters 2022, 250:15–22. Wang Z, Li N, Feng K, Chen M, Zhang Y, Liu Y, Yang Q, Nie J, Tang N, Zhang X, et al: Phase I study of CAR-T cells with PD-1 and TCR disruption in mesothelin-positive solid tumors. Cellular & molecular immunology 2021, 18:2188–2198. Nakazawa T, Natsume A, Nishimura F, Morimoto T, Matsuda R, Nakamura M, Yamada S, Nakagawa I, Motoyama Y, Park YS, et al: Effect of CRISPR/Cas9-Mediated PD-1-Disrupted Primary Human Third-Generation CAR-T Cells Targeting EGFRvIII on In Vitro Human Glioblastoma Cell Growth. Cells 2020, 9. Hu W, Zi Z, Jin Y, Li G, Shao K, Cai Q, Ma X, Wei F: CRISPR/Cas9-mediated PD-1 disruption enhances human mesothelin-targeted CAR T cell effector functions. Cancer immunology, immunotherapy: CII 2019, 68:365–377. Choi BD, Yu X, Castano AP, Darr H, Henderson DB, Bouffard AA, Larson RC, Scarfo I, Bailey SR, Gerhard GM, et al: CRISPR-Cas9 disruption of PD-1 enhances activity of universal EGFRvIII CAR T cells in a preclinical model of human glioblastoma. Journal for immunotherapy of cancer 2019, 7:304. Guo X, Jiang H, Shi B, Zhou M, Zhang H, Shi Z, Du G, Luo H, Wu X, Wang Y, et al: Disruption of PD-1 Enhanced the Anti-tumor Activity of Chimeric Antigen Receptor T Cells Against Hepatocellular Carcinoma. Frontiers in pharmacology 2018, 9:1118. Rupp LJ, Schumann K, Roybal KT, Gate RE, Ye CJ, Lim WA, Marson A: CRISPR/Cas9-mediated PD-1 disruption enhances anti-tumor efficacy of human chimeric antigen receptor T cells. Scientific reports 2017, 7:737. Kalia V, Yuzefpolskiy Y, Vegaraju A, Xiao H, Baumann F, Jatav S, Church C, Prlic M, Jha A, Nghiem P, et al: Metabolic regulation by PD-1 signaling promotes long-lived quiescent CD8 T cell memory in mice. Science translational medicine 2021, 13:eaba6006. Zhou Y, Zhao W, Zhu Y, Liu H, Sun Y, Gong Z, Li X, Liu Z, Wen K, Wang Y, et al: CXCL13 Expression Promotes CAR T Cell Antitumor Activity and Potentiates Response to PD-1 Blockade. Advanced science 2025:e08095. Odorizzi PM, Pauken KE, Paley MA, Sharpe A, Wherry EJ: Genetic absence of PD-1 promotes accumulation of terminally differentiated exhausted CD8 + T cells. The Journal of experimental medicine 2015, 212:1125–1137. Chen Y, Sun C, Landoni E, Metelitsa L, Dotti G, Savoldo B: Eradication of Neuroblastoma by T Cells Redirected with an Optimized GD2-Specific Chimeric Antigen Receptor and Interleukin-15. Clinical cancer research: an official journal of the American Association for Cancer Research 2019, 25:2915–2924. Krenciute G, Prinzing BL, Yi Z, Wu MF, Liu H, Dotti G, Balyasnikova IV, Gottschalk S: Transgenic Expression of IL15 Improves Antiglioma Activity of IL13Ralpha2-CAR T Cells but Results in Antigen Loss Variants. Cancer immunology research 2017, 5:571–581. Batra SA, Rathi P, Guo L, Courtney AN, Fleurence J, Balzeau J, Shaik RS, Nguyen TP, Wu MF, Bulsara S, et al: Glypican-3-Specific CAR T Cells Coexpressing IL15 and IL21 Have Superior Expansion and Antitumor Activity against Hepatocellular Carcinoma. Cancer immunology research 2020, 8:309–320. Sindaco P, Pandey H, Isabelle C, Chakravarti N, Brammer JE, Porcu P, Mishra A: The role of interleukin-15 in the development and treatment of hematological malignancies. Frontiers in immunology 2023, 14:1141208. Zhao B, Wang Y, Tan X, Zheng X, Wang F, Ke K, Zhang C, Liao N, Dang Y, Shi Y, et al: An Optogenetic Controllable T Cell System for Hepatocellular Carcinoma Immunotherapy. Theranostics 2019, 9:1837–1850. Smole A, Benton A, Poussin MA, Eiva MA, Mezzanotte C, Camisa B, Greco B, Sharma P, Minutolo NG, Gray F, et al: Expression of inducible factors reprograms CAR-T cells for enhanced function and safety. Cancer cell 2022, 40:1470–1487 e1477. Tristan-Manzano M, Maldonado-Perez N, Justicia-Lirio P, Cortijo-Gutierrez M, Tristan-Ramos P, Blanco-Benitez C, Pavlovic K, Aguilar-Gonzalez A, Munoz P, Molina-Estevez FJ, et al: Lentiviral vectors for inducible, transactivator-free advanced therapy medicinal products: Application to CAR-T cells. Molecular therapy Nucleic acids 2023, 32:322–339. Sachdeva M, Busser BW, Temburni S, Jahangiri B, Gautron AS, Marechal A, Juillerat A, Williams A, Depil S, Duchateau P, et al: Repurposing endogenous immune pathways to tailor and control chimeric antigen receptor T cell functionality. Nature communications 2019, 10:5100. Zhang J, Hu Y, Yang J, Li W, Zhang M, Wang Q, Zhang L, Wei G, Tian Y, Zhao K, et al: Non-viral, specifically targeted CAR-T cells achieve high safety and efficacy in B-NHL. Nature 2022, 609:369–374. Waldmann TA, Dubois S, Miljkovic MD, Conlon KC: IL-15 in the Combination Immunotherapy of Cancer. Frontiers in immunology 2020, 11:868. Sharpe AH, Pauken KE: The diverse functions of the PD1 inhibitory pathway. Nature reviews Immunology 2018, 18:153–167. Watkinson F, Nayar SK, Rani A, Sakellariou CA, Elhage O, Papaevangelou E, Dasgupta P, Galustian C: IL-15 Upregulates Telomerase Expression and Potently Increases Proliferative Capacity of NK, NKT-Like, and CD8 T Cells. Frontiers in immunology 2020, 11:594620. Briukhovetska D, Dorr J, Endres S, Libby P, Dinarello CA, Kobold S: Interleukins in cancer: from biology to therapy. Nature reviews Cancer 2021, 21:481–499. Tristan-Manzano M, Maldonado-Perez N, Justicia-Lirio P, Munoz P, Cortijo-Gutierrez M, Pavlovic K, Jimenez-Moreno R, Nogueras S, Carmona MD, Sanchez-Hernandez S, et al: Physiological lentiviral vectors for the generation of improved CAR-T cells. Molecular therapy oncolytics 2022, 25:335–349. Castella M, Caballero-Banos M, Ortiz-Maldonado V, Gonzalez-Navarro EA, Sune G, Antonana-Vidosola A, Boronat A, Marzal B, Millan L, Martin-Antonio B, et al: Point-Of-Care CAR T-Cell Production (ARI-0001) Using a Closed Semi-automatic Bioreactor: Experience From an Academic Phase I Clinical Trial. Frontiers in immunology 2020, 11:482. Turchiano G, Andrieux G, Klermund J, Blattner G, Pennucci V, El Gaz M, Monaco G, Poddar S, Mussolino C, Cornu TI, et al: Quantitative evaluation of chromosomal rearrangements in gene-edited human stem cells by CAST-Seq. Cell stem cell 2021, 28:1136–1147 e1135. Rhiel M, Geiger K, Andrieux G, Rositzka J, Boerries M, Cathomen T, Cornu TI: T-CAST: An optimized CAST-Seq pipeline for TALEN confirms superior safety and efficacy of obligate-heterodimeric scaffolds. Frontiers in genome editing 2023, 5:1130736. Livak KJ, Schmittgen TD: Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods 2001, 25:402–408. Ewels P, Magnusson M, Lundin S, Kaller M: MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics 2016, 32:3047–3048. Li B, Dewey CN: RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC bioinformatics 2011, 12:323. Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M, Gingeras TR: STAR: ultrafast universal RNA-seq aligner. Bioinformatics 2013, 29:15–21. Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, Smyth GK: limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic acids research 2015, 43:e47. Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES, Mesirov JP: Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proceedings of the National Academy of Sciences of the United States of America 2005, 102:15545–15550. Liberzon A, Birger C, Thorvaldsdottir H, Ghandi M, Mesirov JP, Tamayo P: The Molecular Signatures Database (MSigDB) hallmark gene set collection. Cell systems 2015, 1:417–425. Cortijo-Gutierrez M, Sanchez-Hernandez S, Tristan-Manzano M, Maldonado-Perez N, Lopez-Onieva L, Real PJ, Herrera C, Marchal JA, Martin F, Benabdellah K: Improved Functionality of Integration-Deficient Lentiviral Vectors (IDLVs) by the Inclusion of IS(2) Protein Docks. Pharmaceutics 2021, 13. Maldonado-Perez N, Tristan-Manzano M, Justicia-Lirio P, Martinez-Planes E, Munoz P, Pavlovic K, Cortijo-Gutierrez M, Blanco-Benitez C, Castella M, Juan M, et al: Efficacy and safety of universal (TCRKO) ARI-0001 CAR-T cells for the treatment of B-cell lymphoma. Frontiers in immunology 2022, 13:1011858. Pavlovic K, Carmona-Luque M, Corsi GI, Maldonado-Perez N, Molina-Estevez FJ, Peralbo-Santaella E, Cortijo-Gutierrez M, Justicia-Lirio P, Tristan-Manzano M, Ronco-Diaz V, et al: Generating universal anti-CD19 CAR T cells with a defined memory phenotype by CRISPR/Cas9 editing and safety evaluation of the transcriptome. Frontiers in immunology 2024, 15:1401683. Dolina JS, Van Braeckel-Budimir N, Thomas GD, Salek-Ardakani S: CD8(+) T Cell Exhaustion in Cancer. Frontiers in immunology 2021, 12:715234. Eyquem J, Mansilla-Soto J, Giavridis T, van der Stegen SJ, Hamieh M, Cunanan KM, Odak A, Gonen M, Sadelain M: Targeting a CAR to the TRAC locus with CRISPR/Cas9 enhances tumour rejection. Nature 2017, 543:113–117. Ding H, Wu Y: CAR-T Therapy in Relapsed Refractory Multiple Myeloma. Current medicinal chemistry 2024, 31:4362–4382. Aparicio-Perez C, Carmona M, Benabdellah K, Herrera C: Failure of ALL recognition by CAR T cells: a review of CD 19-negative relapses after anti-CD 19 CAR-T treatment in B-ALL. Frontiers in immunology 2023, 14:1165870. Maalej KM, Merhi M, Inchakalody VP, Mestiri S, Alam M, Maccalli C, Cherif H, Uddin S, Steinhoff M, Marincola FM, Dermime S: CAR-cell therapy in the era of solid tumor treatment: current challenges and emerging therapeutic advances. Molecular cancer 2023, 22:20. Yin S, Chen Z, Chen D, Yan D: Strategies targeting PD-L1 expression and associated opportunities for cancer combination therapy. Theranostics 2023, 13:1520–1544. Zou W, Luo X, Gao M, Yu C, Wan X, Yu S, Wu Y, Wang A, Fenical W, Wei Z, et al: Optimization of cancer immunotherapy on the basis of programmed death ligand-1 distribution and function. British journal of pharmacology 2023. Chong EA, Melenhorst JJ, Lacey SF, Ambrose DE, Gonzalez V, Levine BL, June CH, Schuster SJ: PD-1 blockade modulates chimeric antigen receptor (CAR)-modified T cells: refueling the CAR. Blood 2017, 129:1039–1041. Rafiq S, Yeku OO, Jackson HJ, Purdon TJ, van Leeuwen DG, Drakes DJ, Song M, Miele MM, Li Z, Wang P, et al: Targeted delivery of a PD-1-blocking scFv by CAR-T cells enhances anti-tumor efficacy in vivo. Nature biotechnology 2018, 36:847–856. Sailer CJ, Hong Y, Dahal A, Ryan AT, Mir S, Gerber SA, Reagan PM, Kim M: PD-1(Hi) CAR-T cells provide superior protection against solid tumors. Frontiers in immunology 2023, 14:1187850. Andreu-Saumell I, Rodriguez-Garcia A, Muhlgrabner V, Gimenez-Alejandre M, Marzal B, Castellsague J, Braso-Maristany F, Calderon H, Angelats L, Colell S, et al: CAR affinity modulates the sensitivity of CAR-T cells to PD-1/PD-L1-mediated inhibition. Nature communications 2024, 15:3552. Kalinin RS, Ukrainskaya VM, Chumakov SP, Moysenovich AM, Tereshchuk VM, Volkov DV, Pershin DS, Maksimov EG, Zhang H, Maschan MA, et al: Engineered Removal of PD-1 From the Surface of CD19 CAR-T Cells Results in Increased Activation and Diminished Survival. Frontiers in molecular biosciences 2021, 8:745286. Wei SC, Anang NAS, Sharma R, Andrews MC, Reuben A, Levine JH, Cogdill AP, Mancuso JJ, Wargo JA, Pe'er D, Allison JP: Combination anti-CTLA-4 plus anti-PD-1 checkpoint blockade utilizes cellular mechanisms partially distinct from monotherapies. Proceedings of the National Academy of Sciences of the United States of America 2019, 116:22699–22709. Jiang X, Wang J, Deng X, Xiong F, Ge J, Xiang B, Wu X, Ma J, Zhou M, Li X, et al: Role of the tumor microenvironment in PD-L1/PD-1-mediated tumor immune escape. Molecular cancer 2019, 18:10. Markham A, Keam SJ: Camrelizumab: First Global Approval. Drugs 2019, 79:1355–1361. Chamberlain CA, Bennett EP, Kverneland AH, Svane IM, Donia M, Met O: Highly efficient PD-1-targeted CRISPR-Cas9 for tumor-infiltrating lymphocyte-based adoptive T cell therapy. Molecular therapy oncolytics 2022, 24:417–428. Wartewig T, Daniels J, Schulz M, Hameister E, Joshi A, Park J, Morrish E, Venkatasubramani AV, Cernilogar FM, van Heijster FHA, et al: PD-1 instructs a tumor-suppressive metabolic program that restricts glycolysis and restrains AP-1 activity in T cell lymphoma. Nature cancer 2023. Chamoto K, Chowdhury PS, Kumar A, Sonomura K, Matsuda F, Fagarasan S, Honjo T: Mitochondrial activation chemicals synergize with surface receptor PD-1 blockade for T cell-dependent antitumor activity. Proceedings of the National Academy of Sciences of the United States of America 2017, 114:E761-E770. Chowdhury PS, Chamoto K, Kumar A, Honjo T: PPAR-Induced Fatty Acid Oxidation in T Cells Increases the Number of Tumor-Reactive CD8(+) T Cells and Facilitates Anti-PD-1 Therapy. Cancer immunology research 2018, 6:1375–1387. Flati I, Di Vito Nolfi M, Dall'Aglio F, Vecchiotti D, Verzella D, Alesse E, Capece D, Zazzeroni F: Molecular Mechanisms Underpinning Immunometabolic Reprogramming: How the Wind Changes during Cancer Progression. Genes 2023, 14. Jung JG, Le A: Targeting Metabolic Cross Talk Between Cancer Cells and Cancer-Associated Fibroblasts. Advances in experimental medicine and biology 2021, 1311:205–214. Jung JG, Le A: Metabolism of Immune Cells in the Tumor Microenvironment. Advances in experimental medicine and biology 2021, 1311:173–185. Ma S, Han J, Li Z, Xiao S, Zhang J, Yan J, Tang T, Barr T, Kraft AS, Caligiuri MA, Yu J: An XBP1s-PIM-2 positive feedback loop controls IL-15-mediated survival of natural killer cells. Science immunology 2023, 8:eabn7993. Wang Y, Zhang Y, Yi P, Dong W, Nalin AP, Zhang J, Zhu Z, Chen L, Benson DM, Mundy-Bosse BL, et al: The IL-15-AKT-XBP1s signaling pathway contributes to effector functions and survival in human NK cells. Nature immunology 2019, 20:10–17. Waldmann TA, Miljkovic MD, Conlon KC: Interleukin-15 (dys)regulation of lymphoid homeostasis: Implications for therapy of autoimmunity and cancer. The Journal of experimental medicine 2020, 217. Ataca Atilla P, McKenna MK, Tashiro H, Srinivasan M, Mo F, Watanabe N, Simons BW, McLean Stevens A, Redell MS, Heslop HE, et al: Modulating TNFalpha activity allows transgenic IL15-Expressing CLL-1 CAR T cells to safely eliminate acute myeloid leukemia. Journal for immunotherapy of cancer 2020, 8. Xu A, Bhanumathy KK, Wu J, Ye Z, Freywald A, Leary SC, Li R, Xiang J: IL-15 signaling promotes adoptive effector T-cell survival and memory formation in irradiation-induced lymphopenia. Cell & bioscience 2016, 6:30. Ye J, Liu Q, He Y, Song Z, Lin B, Hu Z, Hu J, Ning Y, Cai C, Li Y: Combined therapy of CAR-IL-15/IL-15Ralpha-T cells and GLIPR1 knockdown in cancer cells enhanced anti-tumor effect against gastric cancer. Journal of translational medicine 2024, 22:171. Goswami R, Kaplan MH: STAT Transcription Factors in T Cell Control of Health and Disease. International review of cell and molecular biology 2017, 331:123–180. Skariah N, James OJ, Swamy M: Signalling mechanisms driving homeostatic and inflammatory effects of interleukin-15 on tissue lymphocytes. Discovery immunology 2024, 3:kyae002. Zhang S, Zhao J, Bai X, Handley M, Shan F: Biological effects of IL-15 on immune cells and its potential for the treatment of cancer. International immunopharmacology 2021, 91:107318. Guo Y, Luan L, Patil NK, Sherwood ER: Immunobiology of the IL-15/IL-15Ralpha complex as an antitumor and antiviral agent. Cytokine & growth factor reviews 2017, 38:10–21. Alizadeh D, Wong RA, Yang X, Wang D, Pecoraro JR, Kuo CF, Aguilar B, Qi Y, Ann DK, Starr R, et al: IL15 Enhances CAR-T Cell Antitumor Activity by Reducing mTORC1 Activity and Preserving Their Stem Cell Memory Phenotype. Cancer immunology research 2019, 7:759–772. Mollavelioglu B, Cetin Aktas E, Cabioglu N, Abbasov A, Onder S, Emiroglu S, Tukenmez M, Muslumanoglu M, Igci A, Deniz G, Ozmen V: High co-expression of immune checkpoint receptors PD-1, CTLA-4, LAG-3, TIM-3, and TIGIT on tumor-infiltrating lymphocytes in early-stage breast cancer. World journal of surgical oncology 2022, 20:349. Additional Declarations No competing interests reported. Supplementary Files Supplementary.docx Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 31 Oct, 2025 Reviews received at journal 06 Sep, 2025 Reviewers agreed at journal 09 Aug, 2025 Reviews received at journal 02 Aug, 2025 Reviewers agreed at journal 21 Jul, 2025 Reviewers invited by journal 16 Jul, 2025 Editor assigned by journal 09 Jul, 2025 Submission checks completed at journal 01 Jul, 2025 First submitted to journal 30 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7012598","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":486570373,"identity":"dc874319-8560-47ec-bfd5-a76394188d5f","order_by":0,"name":"M. Cortijo-Gutiérrez¹","email":"","orcid":"","institution":"Pfizer-University of Granada-Junta de Andalucía Centre for Genomics and Oncological Research","correspondingAuthor":false,"prefix":"","firstName":"M.","middleName":"","lastName":"Cortijo-Gutiérrez¹","suffix":""},{"id":486570374,"identity":"f66b4513-8343-46d1-80e7-83485fcad96e","order_by":1,"name":"N. Maldonado-Pérez","email":"","orcid":"","institution":"University of Geneva","correspondingAuthor":false,"prefix":"","firstName":"N.","middleName":"","lastName":"Maldonado-Pérez","suffix":""},{"id":486570375,"identity":"5618cba2-3619-41e1-8ccc-e27f9db0cd03","order_by":2,"name":"M. Tristán-Manzano¹","email":"","orcid":"","institution":"Pfizer-University of Granada-Junta de Andalucía Centre for Genomics and Oncological Research","correspondingAuthor":false,"prefix":"","firstName":"M.","middleName":"","lastName":"Tristán-Manzano¹","suffix":""},{"id":486570376,"identity":"326c2c59-6e70-457b-91b4-6e9e2a96ae5d","order_by":3,"name":"K. Pavlovic¹","email":"","orcid":"","institution":"Pfizer-University of Granada-Junta de Andalucía Centre for Genomics and Oncological Research","correspondingAuthor":false,"prefix":"","firstName":"K.","middleName":"","lastName":"Pavlovic¹","suffix":""},{"id":486570377,"identity":"aa6fb56c-991c-4cee-a524-0d226329a9a8","order_by":4,"name":"P. Justicia-Lirio⁵","email":"","orcid":"","institution":"Universidad de Navarra (CCUN), Navarra Institute for Health Research (IdiSNA)","correspondingAuthor":false,"prefix":"","firstName":"P.","middleName":"","lastName":"Justicia-Lirio⁵","suffix":""},{"id":486570378,"identity":"7d6a45d5-b48f-450c-a934-24f4bc57bca5","order_by":5,"name":"C. Fuster-García⁶","email":"","orcid":"","institution":"University of Freiburg","correspondingAuthor":false,"prefix":"","firstName":"C.","middleName":"","lastName":"Fuster-García⁶","suffix":""},{"id":486570379,"identity":"d55a0a4b-49d0-42c1-913c-6adf2a92214a","order_by":6,"name":"T. Cathomen⁶","email":"","orcid":"","institution":"University of Freiburg","correspondingAuthor":false,"prefix":"","firstName":"T.","middleName":"","lastName":"Cathomen⁶","suffix":""},{"id":486570380,"identity":"0a78e71a-d76e-4fd9-8f54-4094f4705817","order_by":7,"name":"R. O. Bak⁷","email":"","orcid":"","institution":"University of Freiburg","correspondingAuthor":false,"prefix":"","firstName":"R.","middleName":"O.","lastName":"Bak⁷","suffix":""},{"id":486570381,"identity":"d0af3bbf-a4a1-4a7e-a7f8-40ed036896f3","order_by":8,"name":"P. P. Jurado-Bascón¹","email":"","orcid":"","institution":"University of Granada, Andalusian Regional Government PTS Granada","correspondingAuthor":false,"prefix":"","firstName":"P.","middleName":"P.","lastName":"Jurado-Bascón¹","suffix":""},{"id":486570382,"identity":"a8a78d3f-a91a-47b7-afe9-d1c9ff27b975","order_by":9,"name":"P. Carmona-Sáez¹","email":"","orcid":"","institution":"Pfizer-University of Granada-Junta de Andalucía Centre for Genomics and Oncological Research","correspondingAuthor":false,"prefix":"","firstName":"P.","middleName":"","lastName":"Carmona-Sáez¹","suffix":""},{"id":486570383,"identity":"b55422ee-0631-4f0d-9b99-7f4deead9275","order_by":10,"name":"I. C. Herrera⁹","email":"","orcid":"","institution":"9.\tDepartment of Hematology and Cell Therapy Unit, IMIBIC, Hospital Universitario Reina Sofía","correspondingAuthor":false,"prefix":"","firstName":"I.","middleName":"C.","lastName":"Herrera⁹","suffix":""},{"id":486570384,"identity":"b8041292-8ae1-47e5-827d-d6b2b77c602e","order_by":11,"name":"Yonglun Luo⁷","email":"","orcid":"","institution":"Aarhus University","correspondingAuthor":false,"prefix":"","firstName":"Yonglun","middleName":"","lastName":"Luo⁷","suffix":""},{"id":486570385,"identity":"2be55cf3-6627-405f-a3c5-d4e7f7af57f6","order_by":12,"name":"F. Martín","email":"","orcid":"","institution":"Pfizer-University of Granada-Junta de Andalucía Centre for Genomics and Oncological Research","correspondingAuthor":false,"prefix":"","firstName":"F.","middleName":"","lastName":"Martín","suffix":""},{"id":486570386,"identity":"39eeec2e-a1ab-41b8-96b3-069cb8906666","order_by":13,"name":"K. Benabdellah","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+0lEQVRIiWNgGAWjYBACCSA+AEYMPEBOgQ3JWgzSiNPCgKTlMGEtku1nHx66wXBHzpz97MEbHwzO2/VL9xg+YKiow6lFmifd4HAOwzNjy568ZMsZBreTZ845Y2zAcAa3dXIMaQxALYcTNxzIMZPmAWoxuJFjJsHYdgC3Fv5nYC31G86/MZP+Y3Au2R6s5R8eh0lAbEkAGS7NYHDAzkACpKWBGbf3Z4BsMXhmuOHGu2TLHoPkBIkbacUGCcdw+0XifBrz55yKO/IG53MP3vhRYWfPPyN544MPNbgdBgEGCGZiAwOHAUMCAQ0owJ6Bgf0BKRpGwSgYBaNg+AMAFphYJnpKxK0AAAAASUVORK5CYII=","orcid":"","institution":"Pfizer-University of Granada-Junta de Andalucía Centre for Genomics and Oncological Research","correspondingAuthor":true,"prefix":"","firstName":"K.","middleName":"","lastName":"Benabdellah","suffix":""}],"badges":[],"createdAt":"2025-06-30 16:08:33","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7012598/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7012598/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87377922,"identity":"daddc325-55ff-45e3-99d5-8ee52d915a23","added_by":"auto","created_at":"2025-07-23 08:17:09","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":287559,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCRISPR-Mediated PD-1 \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eKnock-out\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e in CAR-T Cells: workflow, validation and functional analysis. A)\u003c/strong\u003e Schematic diagram of the workflow for generating PD-1 KO T cells. \u003cstrong\u003eB)\u003c/strong\u003e Representative graph showing the percentage of INDEL generation at the \u003cem\u003ePDCD1 locus\u003c/em\u003e with both study guides. gRNA2 shows significantly higher efficiency than gRNA1 (n≥5)\u003cstrong\u003e. C)\u003c/strong\u003e Circos plot representing structural variations induced by Cas9/gRNA2 targeting \u003cem\u003ePDCD1\u003c/em\u003e. The green arc represents genomic aberrations at the on-target site, red lines off-target mediated translocation (not detected). \u003cstrong\u003eD)\u003c/strong\u003e Schematic representation of the protocol used to generate the PD-1 KO CAR-T cell product. \u003cstrong\u003eE)\u003c/strong\u003e Assessment of the percentage of INDELs and the \u003cem\u003eknock-out\u003c/em\u003e score (\u003cstrong\u003eleft panel\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003egenerated by using RNP (CRISPR/Cas9-gRNA2) in WT and PD-1 KO CAR-T cells (n=14). Data were obtained through the Synthego platform. \u003cstrong\u003eRight panel\u003c/strong\u003e shows reduction in PD-1 expression in PD-1 KO CAR-T cells compared to WT CAR-T cells after three days of activation with the αCD3-αCD28 nanomatrix. Graphs show the mean ± SEM. Statistical analysis was performed using a one-tailed paired t-test.\u003cstrong\u003e F)\u003c/strong\u003e Graph showing the expansion capacity of CAR-T cells edited or not for the \u003cem\u003ePDCD1\u003c/em\u003e gene from three independent donors (n=3, (p-value = 0.2832). \u003cstrong\u003eG)\u003c/strong\u003e Analysis of exhaustion markers in PD-1 KO CAR-T cells versus WT CAR-T cells (n=6).\u003cstrong\u003e H, I)\u003c/strong\u003e Immunophenotypic analysis of WT CAR-T and PD-1 KO CAR-T cells. Phenotypic subpopulations are separated based on the expression of surface markers CD62L and CD45RA. \u003cstrong\u003eH)\u003c/strong\u003e Representative flow cytometry plots showing the variation in T cell subpopulations. \u003cstrong\u003eI)\u003c/strong\u003e Graph showing T cell subpopulations distribution, (T\u003csub\u003eCM\u003c/sub\u003e, T\u003csub\u003eSCM\u003c/sub\u003e, T\u003csub\u003eEF\u003c/sub\u003e and T\u003csub\u003eEM\u003c/sub\u003e) after αCD3-αCD28 stimulation (n=5). Graphs show mean ± SEM. Statistical analysis was performed using a one-tailed paired t-test. * = p value ≤ 0.05; ** = p value ≤ 0.005; *** = p value ≤ 0.0005; **** = p value ≤0.0001\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7012598/v1/8c50f52e0e07a8014e2eeebb.jpg"},{"id":87379218,"identity":"888ea548-e804-4829-a161-5343debd26a7","added_by":"auto","created_at":"2025-07-23 08:25:09","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":216036,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFunctional and Metabolic Characterization of WT and PD-1 \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eKnock-out\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e CAR-T Cells.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA)\u003c/strong\u003e Schematic diagram of the cytotoxicity assay workflow. A co-culture was established using 25,000 PD-L1⁺ Namalwa cells and 10,000 T cells (WT or PD-1 KO), each expressing ~20% CAR (around 2,000 CAR-T cells). The resulting effector-to-target CAR ratio (T:E_CAR) was 12.5:1, representing 12.5 PD-L1⁺ cells per CAR-expressing cell. Serial re-stimulations (R) were performed on days 2, 4, 6, and 8.\u003cstrong\u003e B) \u003c/strong\u003eGraph showing\u003cstrong\u003e \u003c/strong\u003ecytotoxic activity of WT and PD-1 KO CAR-T cells against PD-L1⁺ targets across four sequential re-encounters (T:E_CAR = 12.5:1) (n=4).\u003cstrong\u003e C)\u003c/strong\u003e Graph showing T cell subpopulations distribution, (T\u003csub\u003eCM\u003c/sub\u003e, T\u003csub\u003eSCM\u003c/sub\u003e, T\u003csub\u003eEF\u003c/sub\u003e and T\u003csub\u003eEM\u003c/sub\u003e) based on CD62L and CD45RA expression (n=3). \u003cstrong\u003eD)\u003c/strong\u003e Glycolytic activity assessed via extracellular acidification rate (ECAR), showing reduced glycolysis in PD-1 KO CAR-T cells compared to WT (n=4).\u003cstrong\u003e E)\u003c/strong\u003e Mitochondrial function analysis via oxygen consumption rate (OCR) (\u003cstrong\u003eleft\u003c/strong\u003e), and spare respiratory capacity (SRC) variation (\u003cstrong\u003eright\u003c/strong\u003e) (n=3).\u003cstrong\u003e F)\u003c/strong\u003e ATP production rates comparing mitochondrial (mitoATP, orange) and glycolytic (glycoATP, black) sources in PD-1 KO CAR-T cells (n=4). Experiments from D to F were mesured three days after T cell stimulation. All graphs represent mean ± SEM. Statistical analysis was performed using a one-tailed paired \u003cem\u003et\u003c/em\u003e-test. * = p value ≤ 0.05; ** = p value ≤ 0.005; *** = p value ≤ 0.0005; **** = p value ≤0.0001\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7012598/v1/c837ada43b6113cbb36e090c.jpg"},{"id":87377909,"identity":"9da96831-9578-4d51-b3cf-a42fd63354fa","added_by":"auto","created_at":"2025-07-23 08:17:09","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":374054,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTargeted IL-15 \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eKnock-In\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e at \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ePDCD1\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eenhances CAR-T cell activation, expansion, and survival\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA)\u003c/strong\u003e Schematic representation of the IL-15 \u003cem\u003eknock-in\u003c/em\u003e strategy at exon 1 of the \u003cem\u003ePDCD1\u003c/em\u003e locus. The gRNA2 target site and PAM sequence are indicated. Homology-directed repair is mediated by 150 bp homology arms flanking the Cas9-induced double-strand break (DSB), facilitating IL-15 insertion under the control of the \u003cem\u003ePDCD1\u003c/em\u003eendogenous promoter.\u003cstrong\u003e B)\u003c/strong\u003e Graphs showing kinetics of intracellular IL-15 (left) and PD-1 surface expression (right) in CAR-T WT (blue line) and IL-15 \u003cem\u003eknock-in cells\u003c/em\u003e (grey line) (n=3). \u003cstrong\u003eC)\u003c/strong\u003e Representative flow cytometry plots showing PD-1 and IL-15 expression in WT, PD-1 KO, and PD-1KIL-15 CAR-T cells before and after activation.\u003cstrong\u003e D)\u003c/strong\u003e Quantification of IL-15 secretion after three days activation evaluated with an ELISA assay (n=3).\u003cstrong\u003e E)\u003c/strong\u003e mRNA analysis of IL-15 expression in CAR-T cells after three days of activation. Exogenous IL-15 transcripts are compared to endogenous IL-15 and unactivated conditions (n=4).\u003cstrong\u003e F)\u003c/strong\u003e Proliferation of WT, PD-1 KO, and PD-1KIL-15 CAR-T cells from three independent donors.\u003cstrong\u003e G)\u003c/strong\u003e qPCR analysis of apoptosis-related gene expression in non-activated and three days post-activation PD-1KIL-15 CAR-T cells compared to WT and PD-1 KO CAR-T cells (n=4).\u003cstrong\u003e H)\u003c/strong\u003e Relative proportions of T cell subpopulations three days post-activation (n=3). All data are presented as mean ± SEM. Statistical analysis was performed using appropriate paired \u003cem\u003et\u003c/em\u003e-tests. * = p value ≤ 0.05; ** = p value ≤ 0.005; *** = p value ≤ 0.0005; **** = p value ≤0.0001\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7012598/v1/acea0de874d1f54725d60350.jpg"},{"id":87383061,"identity":"d023bab5-42d8-48f7-abd2-48f411bf5b75","added_by":"auto","created_at":"2025-07-23 08:41:09","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":305869,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMetabolic Enhancement and Superior Cytotoxic Function of PD-1KIL-15 CAR-T cells.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA)\u003c/strong\u003e Graph showing glycolytic activity assessed via extracellular acidification rate (ECAR) of WT, PD-1 KO, and PD-1KOKIL-15 CAR-T cells, measured three days after T cell activation (n=3).\u003cstrong\u003e B)\u003c/strong\u003e Mitochondrial respiration analysis of WT, PD-1 KO and PD-1KOKIL-15 CAR-T cells showing oxygen consumption rate (OCR, left graph) and spare respiratory capacity (SRC, right graph) (n=3). \u003cstrong\u003eC)\u003c/strong\u003e Graph showing mitochondrial (\u003cstrong\u003emitoATP, orange\u003c/strong\u003e) and glycolytic (\u003cstrong\u003eglycoATP, black\u003c/strong\u003e) ATP production rates three days post T cell activation (n=3).\u003cstrong\u003e D)\u003c/strong\u003e Seahorse XF assay profiling of OCR over time three days post T cell activation of WT, PD-1 KO and PD-1KOKIL-15 CAR-T cells. Arrows indicate sequential injection of oligomycin, FCCP, and rotenone/antimycin A (n=3). \u003cstrong\u003eE)\u003c/strong\u003e Schematic representation of the cytotoxicity assay. 25,000 Namalwa PD-L1⁺ cells were co-cultured with 10,000 WT, PD-1 KO, or PD-1KIL-15 CAR- T cells (expressing ~20% CAR⁺ à ~2,000 CAR⁺). Four rounds of re-stimulations (R) were performed every two days (n=3).\u003cstrong\u003e F)\u003c/strong\u003e Target cell killing over time. Relative increase expansion of Namalwa target cells related to Day 0 (n=3).\u003cstrong\u003e G)\u003c/strong\u003e Quantification of the percentage of cells expressing exhaustion markers TIM-3 and LAG-3 at day 8 post-activation (n=3). \u003cstrong\u003eH)\u003c/strong\u003e Assessment of CAR-T cell persistence, represented by fold increase in T cell number at endpoint (n=3). \u003cstrong\u003eI)\u003c/strong\u003e Distribution of T cell subsets at endpoint, classified by CD45RA and CD62L (T\u003csub\u003eCM\u003c/sub\u003e), (T\u003csub\u003eSCM\u003c/sub\u003e, T\u003csub\u003eEM\u003c/sub\u003e, T\u003csub\u003eEF\u003c/sub\u003e) populations (n=3). Data are represented as mean ± SEM. Statistical analyses were performed using paired one-tailed \u003cem\u003et\u003c/em\u003e-tests. * = p value ≤ 0.05; ** = p value ≤ 0.005; *** = p value ≤ 0.0005; **** = p value ≤0.0001\u003c/p\u003e","description":"","filename":"Picture4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7012598/v1/9a313180eefe21a7aa763a59.jpg"},{"id":87379222,"identity":"58ebbfc7-48b0-41a0-83d5-2d4e543e7bc6","added_by":"auto","created_at":"2025-07-23 08:25:09","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":308049,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTranscriptomic profiling reveals enhanced metabolic and pro-survival signatures in PD-1KIL-15 CAR-T cells.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA)\u003c/strong\u003e Gene Set Enrichment Analysis (GSEA) comparing transcriptomic representative profiles of PD-1 KO CAR-T vs. WT \u003cstrong\u003eleft\u003c/strong\u003e) and PD-1KIL-15 CAR-T vs. WT (\u003cstrong\u003eright\u003c/strong\u003e) cells from three different donors. Dot plot displays significantly enriched hallmark and pathway gene sets grouped by functional categories such as mitochondrial respiration, energy capacity, proliferation, and apoptosis. Dot size indicates the –log₁₀ (p-value) and colour indicates normalized enrichment score (NES). PD-1KIL-15 CAR-T cells show enrichment for metabolic and survival-related pathways, including oxidative phosphorylation, fatty acid metabolism, mTOR signaling, and IL-15 response.\u003cstrong\u003e B) \u003c/strong\u003eRepresentative GSEA enrichment plots of key pathways across the three CAR-T populations. REACTOME_MITOCHONDRIAL_PROTEIN_IMPORT, GRAESSMANN_APOPTOSIS_BY_SERUM_DEPRIVATION_UP, HALLMARK_KRAS_SIGNALING_UP, REACTOME_RESPIRATORY_ELECTRON_TRANSPORT_ATP_SYNTHESIS_BY_CHEMIOSMOTIC_\u003c/p\u003e\n\u003cp\u003eCOUPLING_AND_HEAT_PRODUCTION_BY_UNCOUPLING_PROTEINS. IWANAGA_CARCINOGENESIS_BY_KRAS_PTEN_UP. and PARENT_MTOR_SIGNALING_UP are represented.\u003c/p\u003e","description":"","filename":"Picture5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7012598/v1/37a4b64574756558d47340c6.jpg"},{"id":87467083,"identity":"c8ddf9d7-51d6-4d47-a86e-1d3278d4f9be","added_by":"auto","created_at":"2025-07-24 07:58:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3432076,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7012598/v1/8ba17d8f-e984-497a-b53e-b0a7eaa540f1.pdf"},{"id":87377914,"identity":"9297aae1-08ec-4b88-983f-454bdc29614c","added_by":"auto","created_at":"2025-07-23 08:17:09","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":648675,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary.docx","url":"https://assets-eu.researchsquare.com/files/rs-7012598/v1/56523375dd5e30529a8c3101.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Development of a Gene Editing Platform to Enhance CAR-T Therapy Through Inducible IL-15 Expression at the PD-1 Locus","fulltext":[{"header":"Background","content":"\u003cp\u003eIn the last decade, significant progress has been achieved in the development of immunotherapies to fight a wide range of malignancies [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. One notable advancement involves the use of adoptive cell therapies (ACTs), particularly the application of genetically engineered T cells equipped with chimeric antigen receptors (CARs) called CAR-T cells. This innovative approach has demonstrated remarkable efficacy, leading to complete remissions in thousands of patients with refractory type B leukemia or lymphoma, demonstrating substantial disease-modifying potential [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Currently, there are seven FDA-approved CAR T cell products indicated for the treatment of eight distinct malignancies, including Lymphoma, Leukaemia and Multiple Myeloma and with more than 900 ongoing clinical trials worldwide together with CAR-T product ARI-0001, the first CAR-T therapy authorized by the Spanish Agency for Medicines and Medical Devices (AEMPS) under the Hospital Exemption pathway [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This approval allows its use for the treatment of patients over 25 years of age with relapsed or refractory B-cell acute lymphoblastic leukaemia (R/R B-ALL). While the field of CAR-T therapy has experienced significant advancements, its broader application faces a range of clinical and technical challenges. These challenges encompass the emergence of severe, life-threatening side effects following CAR-T cell infusion, tumour cells evading recognition by CAR-T cells, immune rejection of therapeutic cells, and the intricacies of the challenging tumour microenvironment (TME), which blocks T cell activation and contributes to the limited persistence of CAR-T cells [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Major players of these blocking effects include CTLA-4/CD80, CD86, PD-1/PD-L1, and PD-L2 ligand-receptor pairs, which act as regulators of activated T cells [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Among the immune checkpoint receptors, programmed cell death protein-1 (PD-1), mediates immunosuppression when engaged by its ligand (PD-L1), which is highly expressed in the TME [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Numerous studies have shown that targeting the PD-1/PD-L1 pathway through various approach leads to remarkable therapeutic effectiveness in cancer patients [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Notably, PD1 gene editing in CAR-T cell therapy has displayed promising outcomes [\u003cspan additionalcitationids=\"CR14 CR15 CR16 CR17 CR18 CR19\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], this approach has emerged as a promising strategy to enhance T cell function by overcoming exhaustion and improving antitumor responses. Although there is a consensus regarding the benefits of PD-1 \u003cem\u003eknock-out\u003c/em\u003e in T cells, there is still debate about how PD-1 ablation affects the functionality of T cells. From a metabolic standpoint, PD-1 signals were found to be essential for maintaining the delicate equilibrium between mTOR-dependent anabolic glycolysis and fatty acid oxidation programs, which are crucial for meeting the bioenergetic demands of quiescent CD8 T cell memory [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Other studies have demonstrated that PD-1 plays a role in preserving exhausted T cell populations by preventing excessive proliferation and terminal differentiation [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Thus, PD-1 plays a dual role in T lymphocytes.\u003c/p\u003e\u003cp\u003eA second approach to enhancing the therapeutic effectiveness of CAR-T cells involves implementing an armouring strategy with cytokines/chemokines and/or their receptors called T cells redirected for universal cytokine-mediated killing (TRUCKs) or fourth generation CARs. In this regard, it is noteworthy that IL-15 has demonstrated the ability to enhance the antitumour activity of human CAR-T cells when directed against multiple antigens in both blood and solid xenograft tumour models [\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Recognizing the clinical potential of IL-15, this cytokine has been studied as an immunotherapeutic agent against different tumours, and several ongoing clinical trials involving CAR-T cell therapy are underway. These include Phase I studies targeting relapsed/refractory neuroblastoma and osteosarcoma with GD2-specific CAR-T cells expressing IL-15 and a safety switch (NCT03721068), as well as trials examining IL-15-armored Glypican-3-specific CAR-T cells for paediatric solid tumours (NCT04377932, NCT04715191, NCT05103631). Other trials investigate GD2-specific CAR-NKT cells for neuroblastoma (NCT03294954), IL-7/IL-15 pre-treated CD19 CAR-T cells for chemotherapy-resistant B cell lymphoma (NCT02992834), and CAR-T therapies for liver cancer (NCT04093648).\u003c/p\u003e\u003cp\u003eHowever, higher base line or peak serum IL-15 levels, associated with a constitutive expression, are also related to severe toxicity, such as cytokine release syndrome (CRS), graft-versus-host disease (GVHD) and neurotoxicity [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. For this reason, we and others have proposed the strategy of an inducible-selected expression to regulate the expression of several molecules including IL-15 [\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Alternatively, \u003cem\u003eknock-in\u003c/em\u003e of a large gene cassette coding for a specific protein to re-write cell programs has proven feasible for next-generation T cell therapies. This approach aims to counteract suppressive signals and increase therapeutic efficacy [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Zhang et al. demonstrated an enhanced capacity for eradicating tumour cells in animal models by integrating anti-CD19 CAR-T cells into the \u003cem\u003ePDCD1\u003c/em\u003e locus [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. This innovative technique was employed in adoptive therapy for relapsed/refractory aggressive B cell non-Hodgkin lymphoma resulting in an impressive 87.5% success rate in achieving complete remission among treated patients, with sustained responses and no significant adverse effects observed, with a median follow-up of 19.2 months (NCT04213469).\u003c/p\u003e\u003cp\u003ePreclinical and clinical studies have consistently demonstrated that IL-15 alone is insufficient to achieve robust therapeutic effects, highlighting the necessity of combining it with other therapeutic agents to maximize its potential [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. In particular, the combination of IL-15 with immune checkpoint inhibitors and monoclonal antibodies has shown significantly enhanced efficacy compared to IL-15 monotherapy. Similarly, therapies targeting PD-1 alone have also been found inadequate for inducing strong immune responses and improving clinical outcomes [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Given these limitations, the strategic incorporation of additional combinatorial approaches (especially those activating key metabolic pathways) has been proposed to further strengthen therapeutic responses [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. IL-15 emerges as a critical enhancer when used in combination given its pivotal role in regulating essential metabolic and survival pathways in immune cells [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Moreover, while IL-15 monotherapy has shown limited effectiveness, its combination with checkpoint inhibitor-based approaches has been widely recommended to enhance therapeutic efficacy [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Building on these findings, we developed a strategy to address the limitations of PD-1 KO CAR-T cells while simultaneously enhancing the therapeutic potential of IL-15. Our approach involves a gene-editing strategy that integrates the IL-15 gene into the PD-1 safe harbour locus, creating CD19-specific \"armoured\" CAR-T cells. This modification not only mitigates the limitations of the PD-1/PD-L1 axis but also enables precise, dosage-dependent regulation of IL-15 expression. By optimizing the controlled administration of IL-15, we enhanced CAR-T cell efficacy while minimizing the adverse effects associated with uncontrolled cytokine expression.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eCell lines\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNamalwa (Burkitt\u0026rsquo;s lymphoma, ATCC\u0026reg; CRL-1432) and Jurkat (acute T-cell leukemia) cell lines were cultured in RPMI-1640 medium (Biowest) supplemented with 10% fetal bovine serum (FBS, Biowest) and 1% Penicillin/Streptomycin (P/S, Biowest), in an environment with 37\u0026deg;C and 5% CO2. The Namalwa-GFP- Nluc [\u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e] and Namalwa-PDL1+ (generated in the present work) cell lines were cultured following the same procedure. HEK-293T cell line (human embryonic kidney cells derived from human embryonic kidney, ATCC\u0026reg; CRL-11268) was cultured in DMEM medium (Biowest) with 10% FBS and 1% P/S at 37\u0026deg;C in a 10% CO2 atmosphere. The cells were maintained without exceeding 90% confluence using TryPLE (Gibco) 0.4% after a prior wash with PBS. All cell lines were maintained at the recommended cell density according to ATCC instructions and were regularly tested for the presence of mycoplasma using the MycoAlert Mycoplasma Detection Kit (Lonza).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHuman primary T cells\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePrimary T cells were obtained from mononuclear cells derived from peripheral blood (PBMCs) of healthy donors, acquired with informed consent at the Reina Sof\u0026iacute;a Hospital (C\u0026oacute;rdoba) as well as from the Biobank of the public healthcare system of Andalusia (San Cecilio University Hospital, Granada). The study was conducted in accordance with the ethical committee guidelines, meeting the quality and safety requirements for the donation, collection, storage, distribution, and preservation of human cells and tissues under Spanish regulations (Royal Decree-Law 9/2014).\u003c/p\u003e\n\u003cp\u003eBlood was diluted in a 1:2 to 1:4 ratio with PBS, depending on the cell density. Subsequently, cell separation was carried out using Ficoll (Lymphosep, Biowest), with 1/3 Ficoll and 2/3 diluted blood, through centrifugation without brake or acceleration at 1800rpm for 20 minutes. The mononuclear cell fraction (PBMCs) was collected with a Pasteur pipette and washed twice at 200g for 10 minutes to remove platelets. Afterward, PBMCs were cultured in TexMACS medium (a serum-free medium designed for T cell culture, containing human serum albumin, stable glutamine, and phenol red; Miltenyi Biotec) supplemented with 20 ng/mL IL-2 (Miltenyi Biotec), 5% human AB serum (Biowest), and 1% P/S (Biowest) at a density of 2x10\u003csup\u003e6\u003c/sup\u003e cells/mL, at 37\u0026deg;C with 5% CO2. The following day, the cells were activated with T cell TransAct (an \u0026alpha;-CD3/CD28 nanomatrix, 1:100; Miltenyi Biotec). After activation, cells were passaged every 2 or 3 days, maintaining a cell density of 1x10\u003csup\u003e6\u003c/sup\u003e cells/mL.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLentiviral and adeno-associated vectors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLentiviral vectors\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eARI-0001 vector: a third-generation, self-inactivating lentiviral vector expresses the second-generation anti-CD19 CAR ARI-0001 (A3B1/4-1BB/CD3\u0026zeta;) under the control of the EF1\u0026alpha; promoter. The plasmid was generously provided by Dr. Manel Juan and Dr. Mar\u0026iacute;a Castella from the Hospital Cl\u0026iacute;nic in Barcelona [\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eSPDL1 vector: This third-generation, self-inactivating vector, designed using the VectorBuilder database, expresses the PD-L1 protein under the lentiviral SFFV promoter and has been used to generate the Namalwa cell line.\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eAdeno-associated vectors (AAV)\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eVector v6_IL-15PDCD1 vector, generated by production the VectorBuilder company (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://en.vectorbuilder.com/products-services/service/aav-packaging.html\u003c/span\u003e\u003c/span\u003e), expresses the cDNA of the human cytokine IL-15, followed by a polyA tail and flanked by two 150 bp homology arms, each corresponding to the 3\u0026rsquo; and 5\u0026rsquo; sequences on either side of the cutting site of guide 3 for the \u003cem\u003ePDCD1\u003c/em\u003e locus, between the two viral ITRs. This construct lacks a promoter, allowing for expression of the transgene under the endogenous promoter.\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eProduction of lentiviral particles and titration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaxi-production and plasmids\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor large-scale plasmid production, transformations were performed in competent E. coli Stbl3 (Life Technologies), and a single colony was selected. A mini-preparation was performed using the Wizard\u0026reg; Plus SV Minipreps DNA Purification System (Promega), followed by a digestion with HindIII to verify correct plasmid amplification. Subsequently, a large-scale bacterial culture was performed, typically 300 mL, shaking at 220 rpm and at 37\u0026deg;C overnight.\u003c/p\u003e\n\u003cp\u003eFrom this culture, a maxi-preparation of the plasmid was carried out using the NucleoBond Xtra Maxi EF kit (Macherey-Nagel) for the final step with guaranteed sterility. The plasmid yield was quantified using the NanoDrop\u0026reg; ND-1000 (Thermo Fisher), and the 260:280 and 260:230 nm absorbance ratios were evaluated to ensure the absence of cross-contamination. Confirmation of the plasmid maxi-production was performed by enzymatic digestion with HindIII (New England Biolabs) as well as Sanger sequencing.\u003c/p\u003e\n\u003cp\u003eAliquots were prepared at a concentration of 1 \u0026micro;g/\u0026micro;L (1\u0026lambda;) and stored at -20\u0026deg;C for future use. This procedure ensures the generation of significant amounts of high-quality plasmid and the preservation of samples for subsequent applications.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProduction of viral particles\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor lentiviral vector (LV) production, HEK-293T packaging cells or their modified variants were used. In brief, packaging cells were seeded to reach 80% confluence. They were then cotransfected with the transfer plasmid, the HIV-1 packaging plasmid (pCMV\u0026Delta;R8.9), available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.addgene.org/Didier_Trono/\u003c/span\u003e\u003c/span\u003e, and the VSV-G envelope plasmid (pMD2.G), also available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.addgene.org/Didier_Trono/\u003c/span\u003e\u003c/span\u003e. The transfection ratio was 10:7:3, using polyethyleneimine (PEI) (Alfa Aesar) as the transfection reagent. This process was carried out in DMEM (Biowest) without serum for 20 minutes, after which the mixture was added dropwise to the cells. After 5 hours, the medium was replaced with DMEM supplemented with 10% FBS (Biowest), and the viral supernatant was collected at 48 and 72 hours and stored at -80\u0026deg;C.\u003c/p\u003e\n\u003cp\u003eIf necessary, the LV particles were concentrated by ultracentrifugation using the SW32 Ti rotor (Beckman) at 23.000 rpm for 2 hours at 4\u0026deg;C.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eViral titration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe calculation of the functional viral titer (transducing units per mL, TU/mL) was performed by transducing Jurkat cells. Three serial dilutions of lentiviral supernatant were performed to ensure process linearity. Five days after transduction, the expression of the protein of interest was evaluated by flow cytometry (FACS Canto II, BD Biosciences). The viral titer was calculated at conditions where the expression percentage did not exceed 30%. This threshold was established because below 30%, it is considered that a single DNA copy has been integrated, while above this threshold, the linearity is lost due to the insertion of multiple viral DNA copies. The formula used to estimate the viral titer was as follows:\u003c/p\u003e\n\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\u003cimg src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAf8AAABeCAYAAAAtxh1BAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAAFiUAABYlAUlSJPAAABwNSURBVHhe7d3vixvH/Qfwt77Pm2RPz0op4fYe1DTGEK/qklwfXKBZ1Q1HIU2llFIMDklOgTxJenfo3AelxI7ktIZQ7gfUYEJT6YpLS0DizgYfRIpJfJcgQUIKvRWmhD5aWYnzB0wfRJ/5zo5mV9KddJZOnxccxjur/TG7O5/d2ZnZmBBCgDHGGGMT4//0CYwxxhg73jj4M8YYYxOGgz9jjDE2YTj4M8YYYxOGgz9jjDE2YTj4M8YYYxOGgz9jjDE2YTj4M8YYYxOGgz9jjDE2YTj4M8YYYxOGgz9jjDE2YTj4M8YYYxOGgz9jjDE2YTj4M8YYYxOGgz9jjDE2YTj4M8YYYxOGgz9jjDE2YTj4M8YYYxOGgz9jjDE2YTj4M8YYYxOGgz9jjDE2YTj4M8YYYxOGgz9jjDE2YTj4M8YYYxOGgz9jjDE2YTj4M8YYYxOGgz9jjDE2YTj4MzYAmUwGsVhM/o2barUa2P5isRhIz+fzgfRGoxFIZ2zSdbtG1LRMJhNIexA4+LOxsbKyEhmgYLgAV1ZWZFqz2UQ+n8fU1BRisRhmZmaQz+cDvz+o1dVVrK+vAwBc19WTR97s7Cw8z5P/P3HiRCB9cXERhUIBAGBZFqanpwPpx0Gz2cTKyoo8PxKJBOr1uj6b1Gw2MTU1hXQ6rSexCdTtGvF9H47jAABOnToVSHsgBGNjJJVKCQACgEilUnqyEEKIhYUFAUAsLCwEpqdSKWFZlqhUKkIIIdbX1wUAkc1mA/MdVKlUGujyHgQAwrIsfbIQQohKpRKZ7+Mum80Ky7KE53nC933huq78vwmdT2Hp48r3fXmNHYbjOAKAvN4mQbdrxHVdAUDUajU96cjxkz8bK48//jhc14Vt29jc3ESz2dRnwaOPPgoAeP311+W0RqOBzc1NLCwsYHZ2FgDw0ksvwXEcrK2tyfkO49NPPwUAPPnkk3rSWKCn3B/84Ad6EgDgs88+A9rH4LhpNBq4ePEilpeXMT09jXg8jgsXLqDVauH69ev67KhWq9jc3MSlS5c6nvDG3c2bNwEAqVRKTwIAFItFxGIxlMtlPUlqNBrY29uDZVnyepsE3a6RO3fuACPy5M/Bn42VW7du4fTp03j66acBpaBS3b17t6Pa7b///S8A4OGHH1bmBBKJBFqtVmDaQd26dQsA8L3vfU9PGgsffvghAOCpp57SkwAAOzs7AIAnnnhCTxqaTCZjfL2jq9frSCaTxpvBXlChrO4bBS06rqpz587BcRy89NJLetLYS6fTEEKE5vu1a9eALuf59PQ0hBC4d++ennSsRV0j9XodrVZrZF4LcvBnY+XOnTs4efIknnnmGQDAP//5T30W7O7uypuDo3Tnzh3Ytj22T4L05G8quABgb28PUILisDUaDRSLRTz//POhgQjt7Z6bm8OdO3fwxRdf6Mk9+c9//qNPCpXP5+F5Hq5cuaInHXsbGxvY3t7uuLlm34i6Rj7//HMg4ub6qHHwZ2OD7pxPnDiBM2fOAEBH1X+z2cTe3h7m5uaUXwLf+ta3AABfffVVYPru7i5s2w5M66ZeryOdTgcaDq6srKDVaskGPSbU4DCRSMgGiclkMrJRmUm1Wg2sP6pxWqPRQCaTwczMTKClsekJ+caNG4ChsR/ay/E8L3T/9DyhfEmn0x2tnns1PT2NnZ0dWJYVegNAgR/tp65hV6c2Gg28+eabgddH/aLjF4vFMDU1JY9btVpFMpmUeRdVrV4sFgPn0czMDDY2NvTZJP28o3NP/Y3aWHZqairwe+oN8vLLLwMAWq1WYFnVajUwH/3p5ySdJ7QO9dxQ9z+RSAR+R/Rzf2pq6kCNdovFolyXmh8mva6z2zXy/vvvAwAee+wxPQkAUC6XO7YpkUgMr2eA3giAsVFFDfQINf4rFApyGjW4MTUyogZceoO/9fV1fdZQhUJBABCO48hGO7TOqGXVajVhWZZwHKdj/WGNg0yy2axAuzEjNTSjfNAbntG2plKpjnn17aRGXrZtB6YTasyoN6IUQgjP8+S+0Xo8z5MNvvTt6hflnX6sabplWYduQJXL5YznDQDhuq78PzXy830/MF+vKpWKcF1XeJ4n8zSXy4lCoSCy2azwfV/UajWBdsNLfT2+7wvHcYRlWfIY+r4vG7nqx1Uo54yaRueefjxpXnWfVZRPpvUQ2i9o4aVUKslzhBq+0XIozfd9uQ36saB9zOVywvd94fu+sG1boI8GdNSQk9atLsd07vezzqhrRCgNIE3Xg/pbOuaVSkVYlmXcrkHg4M/GxsLCQqBQUoMbocLJhApJCiS2bUcWYjoK8lRIqaJaNquBX/0dLS+soNWFFdi5XK6jhT7ljWleKsxU3QouKpDV4EtomaVSKTC9VCoNrODSbwAGGfiFcizU88HzvMA0yiP6f61Wk4HEsqxAwd0LWp7ruh35TsvV85Sm68eBttWU32ifszrHcTqWE3Z+kF5aq4ed1xQ8hbIcul7UNNoGNS8pCOvbqy+nG9MDg2gvR78J73edUdeI3+Xmmpapnz/ZbLbj3BgUcynJ2AiybTtQKNEFpV40rut2FDqDQnf8+kWvppmEFRYUzMMKWhU9XZueBnW+74fOS4Wfvi2mp0MV3dyYCn0qrPXCc9DUG4BBBn5CT39qELKUrn+2bctzi44HFcwU8PopqCnfTIGZzhn13FBrnUzoWtDR9F7yKuz8IGHrUPVyXoc9PYv2NqjnUtTNhG3bxvPcRL3Z6uYg64y6RmjdYdcIHe+w628Yoo8iYyOCnmz0JyH9Th5D6mdPhYHpzp1uQvSCQrQDlppG1b30VOG6bkchYhL21G+iF761Wk0UCgVZwJjyh9JMBZfo0v+fAiHtj6lac1AoAKr7Nyh0c2Hbtqxap/OKAjXlD90smZ5Oe91/ynP9nA5L0891FV0fMARm2lZLeVUQho6jSVhA1HW7gRARNxF046r+Vl9epVIR6+vrMgib8sMkKv90B1kn5bEJnT9h+U83B2hfn72UCYfVmfuMjSAq9PWLgqanUikZaE2FKRVcYX/d0MVrCpx04ZrS6Hf0Z1mWcF1XZLPZyMJRZwoGYWhe+qMn1lwuFxqYovKhl0K/VqvJJx8MITAL7R0/BSlTIXxYlUolcGwosKrH13XdjhtBOta9HlfaDxPaP/VmjPLWdAzpHAyrFVDPQ0dpr6Ki/Qxbhn5TGYae6vVrldB1alpPLpfrOM9ou9XtT6VSYr39zr5X9PteftPvOrtdI3RNRp0bpVJJHnfLsnq61g/DfLUzNmKy2WxHYSu0qn8qnEwX52HRxWsKNmHvBkWPF30vDlJw9apbwUWBo1uhL9o3Y1SA9TJ/r9TAX6vV5P/D8n2Q3HZDUTXvTflFN6K9FNoUAE3VwJSmnu80Ley40jlougElnufJJ1p9f4Sy/WHLoN9G7V+3GwgRUf3ueZ6wbTtwc9Pt3OwVLSdqu8hB1tntGok6dirf9wM3aoctN6JwVz82Fm7cuGHsQhOPx+VIZJcvX4Zt24jH4/psA/Od73wn8P96vS5HCAwbGW+QhrFvNCrZ6dOn9SQAwCeffAJEdFFSpdNpvPfee0DI4DgHYerOd+rUqUA3QOpqNmjlchnb29tYXV3tmvcPPfRQ4N8oNKCSaSQ46n734osvymlff/01EPLdiGazKbtBnj9/Xk+WpqenUSwW4bouWq2W7HdOqCvayZMnA9MJdQWNGtyHBksK66oHZSRMtb97s9lEKpXC22+/PdTxA7odw4OKukaou6Op/NLF43EsLi4il8sBAG7fvq3PMjAc/NnIo777poISAH72s58BADzPG9rgPo888ggABAaRaTabuHTpkryoTYUWTbt//76ehGKxGPjwUBQai0Dvn08j26nC5kV7xDy9/ziNfRBW6H/55ZdASKGv99VGyDgBB2UK/ES9AZifn+/oU35YzWYTv/rVr+C6bsfHexzHwf7+fmAaBbVehG0r3Uw6joPFxUU5nfKUgqvq6tWraLVayGazgXNwY2PD2Ec87CaPjmPY8aORMNV1rKysBI4/DZbUz3gLzWYTr7zyCl577TWcPXs2kPbtb39bzqNrNptIJpMd559J1HL06zBq3rB1Rl0jdONmuiGq1+uYmZnRJxtvIgZOrwpgbNRQgyVTFakwVP0Pg9q2wPd94bX7KqvVz77vi0KhYGyp7Ch94Gu1mkilUqHvXk2oKpAa/NG6bNvuqIZV56Wq3VK7HzVtv2n+QqEg90utbqRXF57niUqlIpx2l0W16pr2zfM8WQWtb1e/9Kr+ML3O1y8670zv2Gkf1bxcaHcj1fPXhN6LU14K5ZWJeq6oaHuoalmtIjY1BDVV09N7ZVP1t36cXa0xKm1zqVQSfrvbrL5e/VxKpVIdVddqFTmtJ+pcoe2ia5vOfcuyQqvZTfRXd57niVwuZ7wO+12nnnfqcaUygK7HbDYrl6G2o6D5a+32M9aQPxrFwZ+NNPX9l1rw6aig0y/iQaLCV72QhbKNVkhfbwq89FvHcQ50k5Jrdz1T1xVWOORyOVlYox2gwwrYWq0WCEZ6Ya2+x1cDfa1WEwsLC4F967aufvjtAVl6Oaa1dp97Pe8Pim5sws43tUAXyg1I2PwqT3kvTjcMaL/jV4OAiX5cXdcNbfOwvr4u3HZ7BZrftu3Q1uT6cdbzvVKpyHXbtm1cr34umc4DT+m2GnUOE7rR0M99ffu6oeWoeRGW3/2uU887dZ/oPKZ1qtd+qVQSqVQqcEy7rWtQYuKbxgiMMcbakskk9vf38dFHH4W+Jy6Xy3j11VfheR4sy8Ly8nKgqj5MuVzGT3/6U+RyuZ7mZ2wY+J3/mKjX64i1x2UfhmKxGBj/nbFJtrW1hf39/dDADwBnz57F/v4+RPvrdb0G8g8++AA4qve6jIXoO/irH3/o9U9tiUsfLjB9GGEUHGb/9I8y6A2xGo1G4OMaU1NTxo+VmFAL4GF9QjSdTsvWvIyx4fn444+BkMZhjB2VvoM/cV0Xvu9DCIFKpSKnt9sRoFarwbKswG/GyUH2b2trS3bFcRwHW1tbgfTp6enAV+T+8pe/dLQiNqGuPI7j9NWKtl+m1uqMscHa3t4GADz88MN6EmNH5sDBv1u/11OnTmF1dVWfjFwuh0qlgp///Od6knxyHgUH3T/quxr1W+ra0Ut/YAC4efMmWq0WXnjhBT2JMTZG9FpQvcsYY0flQMHfcZyenhJ//OMf65Nw6tQpzM7OGn9Pd8QP2mH2bxiuXbsGAMYbJsbY+JidnZW1h7u7uz2VM4wNQ9/Bf3FxEbu7u/pko3g8DiEEZmdn9aQOwxqhq1/D2r+DajQa2N7exsLCQmRtAmOMMdarvoP/YaiN3dQGf8ViEfPz8/L/UY3misViYDmJRKKj8WC5XO5ouU4joanTxsHVq1cBAM8880xgerFYxNTUVGB/qtWqzJuZmZlAY8J8Pi/nTyQSoSOMMcYYO/6ONPjv7u7KcdhVJ06ckOOBA0ClUpF/NMYx2kOTPv/883jhhRcghIDv+0gkElhaWgoMz3j27Fn8/e9/B9pV+DRE6Ki8VujH2toabNvuGPYynU5jZ2cHaDdOLBaLOHfuHJ577jmkUil4nifHPE8mk7h79y6Wl5dh2zb29vbw7LPPBpZ3UNVqNXCz1s/fqNT2MMbYxNFH/TkIGu2ql8XRaGimkbCilkFfgtKHkxTK5y/1kaJoRCV11DIa4akfB9m/qC9C0WhP+khqOtpnU14R2i49X2gd0L565itD4ZrW3+t+MsYYG19H+uR/GO+88w4A4Je//KWeJL+mZvrohed5uHLlinwvv7q6im9i3Oijfe6lod/vf//7wP+p14H+UZJ4PG78Mtio0msL+I//+I//JvVvkMYm+G9ubgIAfvSjH3VkCFXn0xeldMNskDcsjUYDm5ubcF23pxbBYY0B1c9mMsYYYxin4E+om4zpr9fhNcfBzZs3AQDnzp3TkyaKfoz5j//4j/8m9W+Qxi74H6dGYvTdaJPLly/DsqyeRgB8kLjBH2OMjZ+xCf6O4wAAvvjiCz1ppPQyZOedO3dgWVZodX61WoXneSMf+KENWtLv3zi+jmGMseNgJIO/+kRIw18+99xzAIALFy6g2WzKdDIqT5E06t/29nbodrZarcjA/te//hUY4kd8GGOMTbaBBH/1abzbWNW3bt0CAHz11Vd6khwDYH5+Hvl8Hul0Wk47f/48HMeB53k4c+YMVlZWkM/nkclkMDMzg/n5+UCwVW8GTEG4H/3s3/T0tBybIJlMBrajXC5jfn4ejuN0tM4n/XzEJ2ofKX8pv1U0r16Lou5bt/1kjDE2xvS+f/2ifu30Z1mWKJVK+mxCCCGy2WxgXr3/uu/7sn+6ZVliYWFB+L4fSM/lcsK2bbkMx3FELpcLzFer1QLz2LZt7NPei372T1UqlQJ97cO2VVcoFAQAsb6+ricFmPaRxjnI5XJy7AMAIpVKyd+p22RZlhwDwLS8Wq0mf8cYUc9pfXwJNnoqlYpIpVKBcmAY1PFQoIwvsr6+LhzHCYw3wh68Qwd/NliO4wgAkTcIjD1Ivu/L87TbTepxQPuq3hib6A8KMAykpT8Q4PDPX5Gy2aywLKvrQ8egeJ4n90t9eCgUCsK2beG67pFsB+tuuGce6wtdOPw0xUYdBbFJqB3yfV/Witm2HRq8fN8XqVRKBj9TDaG6LMuyhpp/rusOfR0mtG86umm0LCs0D9nRGcg7fzYYYR/xYWzU0Gia3dqlHAfxeBwzMzMAgN/85jehA2rF43H8+te/lv/Xv8cBbVnvvffe0PJvZWUF29vbQ12HCX0wjEZdVcXjcWxtbQHt9lDsweLgP0LCPuLD2Cip1+totVpjNUz0YdHNzg9/+EM9KeChhx7SJwWon+geVlfXRqOBixcvwnXdoa0jzIcffghEjCwaj8exvLyMvb29wFdH2dHj4D8iyuUyWq0WXnzxRT2JsZHy+eefAxEF/HHTaDTQarVgWdahn6LfeustWJYV2ttnEN566y0AwKuvvqonDR09+T/xxBN6knT+/Hmg3W2bPTgc/EfE2bNnIY7ZEMXs6OTzeczMzCAWiwU+b91sNpHP5zE1NYVYLIZyuRz4HdrBLZPJyHlisRjS6XRod8/3338fAPDYY4/JafoyTE91xWJRLpuE/a7RaCCdTsvtoX3S9yeZTHZ0c1XR8ilvYrEYMplM5G909NRvqsrWnThxQp8k1et1rK2t4dKlS6GvDtA+lolEIjAaZjKZxMbGhj6rUbFYhGVZoTWIw8zzGzduAF3yIR6Py8+O080CewD0RgCMsfHiOI5YX1+XXa3UxlbUxYo+5ax/apq6lrquK7uKVioVYVlWaOM2av1O81NDrkqlItdjahFPXX2ph4Dpd67rilqtJhYWFoTnecLzPNlttVKpCNd1ZQt6alwX1uOA9i2VSslt7fYbE/oMuN41OQxCWvG7riscx9EnB+h5JNpd5dBjQ2A6B/TjTIaZ51HHXhf1aXd2NDrPUMbYWFGDtl7wU5poB6VsNiv/T/M7jtMR5Cng6X2zuxXw1GPFlE43DabW57Rcx3E6Ahf1LNBbrkcFEAr8esCM+k0Y2m69214YGII/bU+3ZVAe6Ogmrpt+9m/QeV4qlYx5bmI6V9nR4mp/xsYcfSOCRmx85JFHOtKoevUXv/iFTKMvRv7ud7/rqIZ+9NFHAcNnsj/66CNA+daG7l//+hcQkr63tweE9BCgdgSe52F1dTWQtr+/DwBYXl4O/JZGsdS/p9FsNpHJZIzv1j/55BOgyztpVbPZlNsdVZUdpdls4sKFCz038tvb2+uoDt/d3Y0cEvwgBpnnAPDBBx8AIceXjR4O/owdExSoH3/8cT0J29vbcF1XFsz1eh2e54X2Lrl7964+CQDw6aefAgDm5ub0JEAJAHo6DUUd1kPg9u3bAICFhYXAB6+azSY8z4NlWR3tYej9st4C//r162i1WlheXkY8Hke9XkexWEQymcTm5iay2WxPQRhKgHQcp+MGKQzd+NA+X716Fffu3eu4ETHJZrNAO/96fcd/UIPMcwD4+OOPQ9PY6OHgz9gxQU+1akM8tAvzN998M9C6ent7GwDw9NNPK3P+v93dXcCwLPpWxPe///3AdBIWHD777DMgoocALfcnP/lJYDrVNOhPvfREbmqB/49//AMAsLS0hFgshmeffRbXrl3DU089Bc/z8MYbbwTmj0IBMiyfTNSbhEajgaWlpa6N/Mgbb7yBXC6HVquFl19+GYlEoqMWYFAGmedQzilTGhs9HPwZOyY8zwMMfc3/+Mc/dlQ5040CVe+rGo2GrOo+c+ZMII0KeNOTc1Rw+POf/wxEVLeHLTesKpkClCko07Lo09H7+/vY2trC4uJi6Ge0w1CAPHnypJ7Uk2w2C8dx+vpC5+LiIjzPQyqVwt7eHubm5kJb1x/GIPO8W80OGz0c/Bk7Jihgq4V5sVjEjRs3Op52v/zySyAkGF+/fh1oVwerT6v0BGp6nw8lOOhd4srlcuR7c1quKXCEVSWHvV4YtKhufo1GA7FYLLRL5O3bt7G5uYkrV67oSV1NT0+jWCzCdV20Wi35+qFXpq+mqgad51Szc/r0aT3J6P79+/okdsQ4+DN2TJXLZVy7dk0OqaqiQpoKbUKvCCzLwuuvvx5I+/rrrwEAiUQiMJ1QewC1ar9er+Ptt9+G4ziwbdtY9U2jwpkCR1hVMgUo0+sH27YBw2euASCTyRjHOjChkQwtyzLWGNBTvZ5G+7G0tNRR4xJmY2MDmUxGn2zMkyh0M0f5E2bQeU43G73WkJjOFXa0OPgzdszQoCzvvPMO3n33XWPAPX/+PCzLwuXLl+WTa7ValWOu7+zsdAQ1VbPZxMrKCvL5vJz23e9+F1CqyqvVKpaWlvDuu+/KJ3+0A536PnlnZwcA8OSTT8pp6LEq+f79+3K7KdjTKJm//e1v5bRyuYxEIoF79+51vMoI87e//Q0wVHNTb4LNzc2ONCgt4U29DcLs7OxgbW0tcGNSLpextrYGx3F6uoFAu9bHsiwZwMMMOs9VjUYDyWRSLsuEzpGo9bAh0/v+McbGEw0Q02uf8FqtFvgKnW3bcqAXE9/3Zf9v27aNA73Q+ACWZYlsNivHD6Dptm13fF6WvnKnr5cGt1HHJiClUkkORJNKpTrGDsjlcnK5NI/pK3thTJ/nNf3p61V/a8qfMOvr6/IrfLRs27YDedgryuuo/R10ntdqNblMGkQoTLexItjRiIlvBpZgjDF2DDQaDdi2Ddd1ja98HrR8Po+lpSUUCoWOHgXs6HDwZ4yxY2ZlZQUXL15EqVQyjuPwoDQaDdn+g7qTsgeDgz9jjB1DiUQCnudhZ2eno/Heg9BsNpFMJuF5Hvb29iLblLDh4wZ/jDF2DNGQwHNzc8jn88bGeUelWCzKhpb//ve/OfCPAH7yZ4yxY6xareJPf/oTpqamOsbwPwrFYhF/+MMf8Nprr/E7/hHCwZ8xxhibMFztzxhjjE0YDv6MMcbYhOHgzxhjjE0YDv6MMcbYhOHgzxhjjE0YDv6MMcbYhOHgzxhjjE0YDv6MMcbYhOHgzxhjjE2Y/wFTqLVqnfotsgAAAABJRU5ErkJggg==\"\u003e\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003eAdditionally, from the viral titer, the multiplicity of infection (MOI) was calculated using the formula:\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{M}\\text{O}\\text{I}=\\frac{\\:\\text{T}\\text{i}\\text{t}\\text{e}\\text{r}\\:\\left(\\frac{\\text{T}\\text{U}}{\\text{m}\\text{l}}\\right)*volume\\:LVs\\:\\left(ml\\right)}{N\\text{\u0026ordm;}\\:transduced\\:cells}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGenetic modification\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCell transduction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePrimary T cells, previously activated with T Cell TransAct (Miltenyi Biotec), were transduced with ARI-0001 lentiviral vector (LVs) at a multiplicity of infection (MOI) of 10 using spinoculation (800g for 60 minutes at 32\u0026deg;C). After 5 hours of incubation in the presence of the LVs, the cells were washed with PBS (300g, 10 minutes) and seeded at a density of 10\u003csup\u003e6\u003c/sup\u003e cells/mL in supplemented TexMACS medium. The percentage of transduced cells was determined by flow cytometry at least 72 hours after transduction.\u003c/p\u003e\n\u003cp\u003eFor the transduction of suspension cell lines, 10\u003csup\u003e5\u003c/sup\u003e cells were incubated in a well of a 48-well plate with different lentiviral vectors (LVs) in a maximum volume of 300 \u0026micro;L. In all cases, after 5 hours of incubation, the cells were washed with PBS for 5 minutes at 300g and cultured as described earlier, seeded according to the density recommended by ATCC. The percentage of transduced cells was determined by flow cytometry at least 72 hours after transduction.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGenome editing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor the \u003cem\u003eKnock-out\u003c/em\u003e (KO) technique in \u003cem\u003ePDCD1\u003c/em\u003e locus were edited. A comparison was made between two gRNAs: gRNA1 (CGUCUGGGCGGUGCUACAAC UCCAGGCAUGCAGAUCCCAC, GenScript, 100 \u0026micro;M) and gRNA2 (UCCAGGCAUGCAGAUCCCAC, GenScript, 100 \u0026micro;M) to optimize the \u003cem\u003eknock-out\u003c/em\u003e of PD-1 expression.\u003c/p\u003e\n\u003cp\u003eFor generating PD-1 KO T cells or CAR-T PD-1 KO cells, PBMCs were activated for 24 hours and transduced with lentiviral vectors to express the CAR. 48 hours post-transduction, the genomic editing of these CAR-T WT cells was performed. In the case of CAR-T PD-1 KO cells, the cells were modified using the CRISPR/Cas9 endonuclease system. First, ribonucleoprotein (RNP) complexes were formed by incubating 3.3 \u0026micro;M Cas9 protein (IDT, 61 \u0026micro;M) with 10 \u0026micro;M of the gRNA targeting the first exon of the PD-1 locus (gRNA2 PD-1: UCCAGGCAUGCAGAUCCCAC, GenScript, 100 \u0026micro;M) in a 1:3 ratio for 20 minutes at 37\u0026deg;C. During this period, the cell density and the required cell number were determined. The cells were washed with PBS, followed by an electroporation buffer (Opti-MEM medium, ThermoFisher). All centrifugations were performed at 300g for 5 minutes at room temperature. The cells were suspended in the solution containing the RNPs, and Opti-MEM was added to reach the final volume of the nucleofection cuvette (20 or 100 \u0026micro;L, Lonza). The mixture was electroporated using the 4D-Nucleofector (Lonza) and the EH-115 program. Afterward, the cells were recovered in TexMACS medium without supplements at 37\u0026deg;C and seeded at a concentration of 2x10\u003csup\u003e6\u003c/sup\u003e cells/mL, considering that the viability post-electroporation was 50%. After 5 hours, the cells were diluted to 1x10\u003csup\u003e6\u003c/sup\u003e cells/mL by adding supplemented TexMACS medium (2X). After 48 to 72 hours, the cells were washed as needed and cultured at 1x10\u003csup\u003e6\u003c/sup\u003e cells/mL in complete medium. Five to seven days after transduction, the percentage of transduced and edited cells was determined, along with phenotypic characterization by flow cytometry. The editing efficiency was confirmed by Sanger sequencing (details below).\u003c/p\u003e\n\u003cp\u003eFor performing the \u003cem\u003eknock-in\u003c/em\u003e (KI) and generating PD-1KIL-15 CAR-T cells, the procedure was exactly the same, except that 5x10\u003csup\u003e4\u003c/sup\u003e GC/mL of the AAV6 v6_IL-15PDCD1 was added twenty minutes after the membrane pores and DNA breaks were generated.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis of the generated gene editing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOn target gene editing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWild-type (WT) and genetically modified cells (PD-1 KO, PD-1KIL-15 CAR-T) were lysed five to seven days after editing, and genomic DNA was extracted using the QIAamp genomic DNA kit from Qiagen. DNA amplification was performed using KAPA2G Fast Hot Start Ready Mix from Sigma-Aldrich, utilizing 10 ng of DNA and the oligonucleotide primers (Ontarget Guide1 Fw: TCACTCTCGCCCACGTGGA; Ontarget Guide1 Rev: GCCTCCCCCACGGATGGTCT). All reactions were performed in duplicate using the Veriti thermocycler (ThermoFisher) with the following program: 1x (95\u0026ordm;C, 5 min); 40x (94\u0026ordm;C, 45 sec / 60\u0026ordm;C, 20 sec / 72\u0026ordm;C, 30 sec); 1x (72\u0026ordm;C, 10 min). For Sanger sequencing, PCR products were purified using the QIAquick PCR Purification Kit from Qiagen. The resulting sequences were analysed using the ICE (Inference of CRISPR Editing) program (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://ice.synthego.com/\u003c/span\u003e\u003c/span\u003e), which provides information on editing efficiency and the distribution of insertions/deletions (INDELs).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOff-target gene editing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe CHOPCHOP tool (available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://chopchop.cbu.uib.no\u003c/span\u003e\u003c/span\u003e) was used to predict in silico potential off-target effects of the gRNA2 PD-1. Five possible off-target sites were selected, and these were subsequently analysed in the DNA of edited and non-edited cells using Sanger sequencing and the ICE program. The sequences of the oligonucleotides used are detailed in (\u003cstrong\u003eSupplementary table 1\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCAST-Seq analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCAST-Seq analysis was performed, as previously described [\u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e], on genomic DNA extracted from cells three days after editing with Cas9/gRNA2, with untreated cells serving as a negative control. Several modifications were made to the original workflow to improve specificity: average fragmentation size of the DNA was aimed at an average length of 500 bp [\u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e]. Library sequencing was conducted on a NovaSeq 6000 system using 2x150 bp paired-end sequencing (GENEWIZ, Azenta Life Sciences). The bioinformatic pipeline included the following changes: sites under investigation were classified as OMT if the p-value was below the threshold of 0.005. Annotation for barcode hopping was incorporated into the CAST-Seq algorithm, and coverage analysis was optimized to reduce execution time by aligning the spacer sequence only to the most covered regions for each site. Biological replicates from three different donors were used in the CAST-seq analysis. Only sites that were significant in at least two of the replicates were considered as putative events (\u003cstrong\u003eSupplementary table 2).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRNA extraction and quantitative PCR (qPCR)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMessenger RNA was extracted from approximately 7x10⁵ edited and non-edited T cells using the RNeasy Plus Mini Kit from Qiagen. Subsequently, reverse transcription (RT-PCR) was performed to generate complementary DNA (cDNA) using the High-Capacity cDNA Reverse Transcription Kit from ThermoFisher, following the manufacturer\u0026rsquo;s protocol. The same amount of mRNA was used for all samples, and the following program was applied on a ThermoFisher Veriti thermal cycler:\u003c/p\u003e\n\u003cp\u003e1x (95\u0026deg;C, 15 minutes); 40x (95\u0026deg;C, 15 seconds / 60\u0026deg;C, 30 seconds / 72\u0026deg;C, 30 seconds); 1x (95\u0026deg;C, 1 minute / 55\u0026deg;C, 30 seconds / 95\u0026deg;C, 30 seconds).\u003c/p\u003e\n\u003cp\u003eAfter obtaining the cDNA, real-time PCR (qPCR) was conducted in duplicate for all samples. The oligonucleotide pairs described in \u003cstrong\u003eTable\u0026nbsp;1\u003c/strong\u003e were used to analyse the expression of various genes. The amplification program used was:\u003c/p\u003e\n\u003cp\u003e1x (95\u0026deg;C, 15 minutes); 40x (95\u0026deg;C, 15 seconds / 60\u0026deg;C, 30 seconds / 72\u0026deg;C, 30 seconds); 1x (95\u0026deg;C, 1 minute / 55\u0026deg;C, 30 seconds / 95\u0026deg;C, 30 seconds).\u003c/p\u003e\n\u003cp\u003eThe KAPA SYBR FAST qPCR Master Mix (2X) from Kapa Biosystems was used, ensuring that the same amount of cDNA was maintained across all samples. Ultrapure water from Invitrogen was used as the negative control for the PCR. Results were normalized relative to GAPDH cDNA (\u003cstrong\u003eTable\u0026nbsp;1\u003c/strong\u003e). Data analysis was performed using the MxPro software from Agilent, calculating relative gene expression changes with the 2\u003csup\u003e\u0026Delta;\u0026Delta;Ct\u003c/sup\u003e method [\u003cspan class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eOligonucleotide sequences used in the genomic editing analysis of KI to generate PD-1KIIL-15 CAR-T cells.\u003c/p\u003e\n \u003ctable id=\"Taba\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePRIMER NAME\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e5\u0026rsquo; \u0026ndash; 3\u0026rsquo; SEQUENCE\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u0026apos; IL-15 \u003cem\u003eOn Target\u003c/em\u003e G_3 Fw\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTGGGGATGCGGTGGGCTCTA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u0026apos; IL-15 \u003cem\u003eOn Targe\u003c/em\u003et G_3 Rev\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCAGAGCTGGGGGCCAAGGCT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecDNA IL-15 Fw\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eACTTGTGTTTACTTCTAAACAGTC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecDNA IL-15 Rev\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTTTGCAACTGGGGTGAACATCA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecDNA IL-15 Fw 3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCAGTTTGTCTTCTAATGGGAAT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGFP Rev 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCGTCCAGCTCGACCAGGAT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBIM Fw\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCCCTCCTETTCTECCAATETE\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBIM Rev\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTCTATCCCTACTCCTTCCCCCT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBcl-xL Fw\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTCCAAGGCTOTAGGTOGTCA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBcl-xL Rev\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGGGCATTCAGTGACCTGACA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGAPDH Fw\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGGCCTCCAAGGAGTAAGACC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGAPDH Rev\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTGGTACATGACAAGGTGCGG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eAllele Editing frequencies using ddPCR\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe integration of the v6_IL15PDCD1 transgene into the \u003cem\u003ePDCD1\u003c/em\u003e locus was assessed using a duplex digital droplet PCR (ddPCR) assay. Genomic DNA from the edited cells was mixed with two sets of primers/probes (\u003cstrong\u003eTable\u0026nbsp;2\u003c/strong\u003e): a reference set (Ref Fw and Rev) with its probe (HEX) and a set targeting the upstream region of the right homology arm (PDCD1_Rev outside 3\u0026rsquo; HA) along with the primer and probe (FAM) located at the PolyA tail (ROB79).\u003c/p\u003e\n\u003cp\u003eDroplets were generated using a Bio-Rad automated droplet generator (Bio-Rad, Hercules, CA, USA), amplified by PCR using a Bio-Rad thermal cycler, and analysed with a Bio-Rad QX200 droplet reader. Integration frequencies were calculated as the ratio of double-positive droplets to all positive reference droplets using the QuantaSoft\u0026trade; Analysis Pro software.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\"\u003eTable 2. Oligonucleotide and probe sequences used in specific integration analysis in \u003cem\u003ePDCD1\u003c/em\u003e transgene.\u003c/div\u003e\n \u003ctable id=\"Tabb\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePRIMER NAME\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e5\u0026rsquo; \u0026ndash; 3\u0026rsquo; SEQUENCE\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRef Fw\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAAGCTATGCAGGTGACAG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRef Rev\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAGGTAGTTTCTGAACTTCTCC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProbe Ref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eATGCAGCAGTGCGTCATCCC-HEX-ZEN-IBFQ\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eROB79 Fw\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGGGAGGATTGGGAAGACA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePDCD1\u003c/em\u003e _Rev outside 3\u0026rsquo;HA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGTTTGGGGTTCTGGCCAGCC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProbe Smpl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCCCACTGACGGGCACCGGA-FAM-ZEN-IBFQ\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eFlow cytometry\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCAR detection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eExpression of the \u0026alpha;-CD19 CAR was determined using a goat IgG1 antibody specific to the murine Fab region, conjugated to biotin (Jackson Immunoresearch, 115-065-072, Philadelphia, USA) [\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e], followed by incubation with streptavidin-APC (Thermo Fisher) as a secondary antibody. Approximately 50,000 cells were washed with a flow cytometry (FC) wash buffer (PBS\u0026thinsp;+\u0026thinsp;3% BSA\u0026thinsp;+\u0026thinsp;2 mM EDTA) and incubated with the anti-murine Fab antibody (1:100) for 20 minutes on ice. After washing, streptavidin-APC (1:330) was added. Fifteen minutes later, extracellular staining for phenotypic and additional markers was performed for another 15 minutes. Cells were washed twice with PBS before acquisition using FACSCantoII or FACS Verse cytometers (Beckton Dickison Biosciences).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDetection of hIL-15\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eApproximately 100,000 cells were washed and stained with desired surface markers. Fixation and permeabilization were performed using the Fix \u0026amp; Perm kit from Nordic MUbio. Briefly, 80 \u0026micro;L of Fixation Reagent A was added for 20 minutes at room temperature. After washing, cells were permeabilized with 80 \u0026micro;L of Permeabilization Reagent B for 10 minutes at room temperature. Without additional washes, anti-hIL-15 APC antibody (MA5-23627, 1:20, ThermoFisher) was added for 30 minutes at room temperature. Two PBS washes were performed before data acquisition on the aforementioned flow cytometers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePhenotype and exhaustion analysis of edited cells\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eVarious monoclonal antibodies were used for T-cell phenotypic characterization, including hCD62L-PE-Cy7/APC-Cy7 (1:200), hCD45RA-FITC/Pacific Blue (1:200), hCD3-PerCP-Cy5.5/APC-780/BV711 (1:200), hTIM3-APC-Cy7/PE-CF594 (1:100), hLAG3-PE/eFluor506/AlexaFluor700 (1:100), hPD-L1-APC (1:100), and hPD1-APC/PE (1:100) from ThermoFisher and Biolegend. Extracellular staining was generally performed for 30 minutes on ice and in the dark.\u003c/p\u003e\n\u003cp\u003eAnalysis strategies included singlet selection and dead cell exclusion using 4\u0026apos;,6-diamidino-2-phenylindole (DAPI, Thermo Fisher) during acquisition, provided violet laser channels were available and cellular permeabilization was absent. Data analysis was performed using FlowJo V10 software (TreeStar).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRNA sequencing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor bulk RNA-seq sample preparation total RNA from edited and unedited CAR T cells was extracted after three days post \u0026alpha;CD3-\u0026alpha;CD28 activation with the High Pure RNA Isolation Kit (Roche) according to the manufacturer\u0026rsquo;s recommendation and later purified and concentrated with the RNA Cleanup Kit (Monarch). The RNA quantity and purity (A260/ A280) ratio were measured on a Nanodrop spectrophotometer (Thermo Fisher Scientific), and the RNA integrity number (RIN) was determined using a 2100 Bioanalyzer with an Agilent RNA 6000 Pico kit (Agilent). mRNA-Sequencing was carried out by Novogene (UK) Company Ltd. Sample quality control, including RIN, was assessed with an Agilent 5400. Subsequently, strand-specific library preparation, including polyA-enrichment, was performed according to their standard protocols and 30M paired-end reads were sequenced on an Illumina NovaSeq X Plus sequencer, using paired-end 150-bp sequencing strategy. The tools used in the quality control of the raw expression FASTQ files where fastQC and MultiQC [\u003cspan class=\"CitationRef\"\u003e42\u003c/span\u003e], adapters and artifacts were trimmed via cutadapt. Reads were aligned to the GRCh38 reference genome for subsequent gene quantification using RSEM [\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e] in conjunction with STAR [\u003cspan class=\"CitationRef\"\u003e44\u003c/span\u003e] aligner, thus obtaining the expression matrix for the 9 samples considered in the study. As the interest of the analysis was differential expression, the 3 possible comparisons between the 3 groups were considered (Ctrl-KO, Ctrl-KI, KO-KI), therefore, filtration and normalization was applied for each of the 3 cases separately. For filtration, genes that appeared less than 10 times individually in a minimum of 4 of the 6 samples in the comparison where removed. For normalization, data was normalized with the voom function from limma [\u003cspan class=\"CitationRef\"\u003e45\u003c/span\u003e] R package, and the statistic used in the differential expression analysis was the moderated t test statistic from the same package, taking into account a design matrix that enabled paired sample testing. Genes were sorted based on the moderated t-statistic for GSEA. Gene sets were derived from the Hallmark and C2 Human Collections in MsigDB [\u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e47\u003c/span\u003e] while the analysis tool used was fgsea R package.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunctional Studies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCellular activation and exhaustion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong 1.5 \u0026times; 10⁶ and 2 \u0026times; 10⁶ cells were plated in duplicate wells of a 48-well plate. One duplicate was activated with TransAct (1:100, Miltenyi Biotec). After three days, the supernatant from both activated and non-activated wells was collected for IL-15 secretion assays and the analysis of pro- and anti-inflammatory cytokine expression. Cell pellets from each well were also collected for RNA or genomic DNA extraction to conduct further studies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ehIL-15 Secretion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo assess human IL-15 secretion into the medium, we used the ELISA MAX\u0026trade; Deluxe Set Human IL-15 Kit (Biolegend). Supernatants from WT, PD-1 KO, and PD-1KIL-15 CAR-T cells were collected after three days of continuous activation. IL-15 concentrations in the medium were determined by extrapolating against the standard curve provided in the kit, following the manufacturer\u0026apos;s instructions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCytotoxicity assays\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe cytotoxic capacity of \u0026alpha;CD19 CAR-T cells was evaluated through sequential co-culture with CD19⁺ tumour cells. The assay employed Namalwa cell lines derived from Burkitt\u0026apos;s lymphoma (CD19⁺), which constitutively express eGFP-Nanoluciferase (NLuc) (100% eGFP⁺) for in vitro and in vivo monitoring. Specifically, this included Namalwa eGFP-NLuc WT and Namalwa PD-L1⁺ cells (a PD-L1⁺ overexpressing line generated for this study via lentiviral transduction of Namalwa eGFP-NLuc). CAR-T cells and target cells were co-cultured in multiple replicates at an effector-to-target ratio of 12.5:1 in non-supplemented RPMI medium. The assay used 2.5 \u0026times; 10⁴ Namalwa cells in U-bottom 96-well plates along with 1 \u0026times; 10⁴ T cells, approximately 20% of which expressed CAR (~\u0026thinsp;2 \u0026times; 10\u003csup\u003e3\u003c/sup\u003e total CAR\u003csup\u003e+\u003c/sup\u003e cells). As a control, tumour cells were co-cultured with non-transduced (NT) T cells (2 \u0026times; 10\u003csup\u003e3\u003c/sup\u003e cells). After 48 hours, the absolute counts of target and effector cells were measured using Count Absolute Bright (ThermoFisher), and the phenotype of the T cells was assessed by flow cytometry. When \u0026gt;\u0026thinsp;80% of the tumour cells were lysed, additional Namalwa cells were added to each replicate (R, re-encounter).\u003c/p\u003e\n\u003cp\u003eThe percentage of lysis of CD19⁺ target cells was determined via flow cytometry by measuring the loss of GFP compared to the initial percentage of Namalwa cells in the culture at time 0.\u003c/p\u003e\n\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e$$\\:Percentage\\:of\\:Lysis=1-\\left(\\:\\frac{\\%\\:Namalwa\\:cells\\:at\\:the\\:end\\:of\\:time}{\\%\\:Namalwa\\:cells\\:at\\:early\\:time}\\:\\right)\\:x\\:100$$\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eMetabolic characterization\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter 3 days of continuous stimulation with \u0026alpha;-CD3/CD28, mitochondrial function of WT, PD-1 KO, and PD-1KIL-15 CAR-T cells was assessed using the Agilent Seahorse XF HS Mini Analyzer and the Cell Metabolic Profiling Kit (Agilent Technologies). CAR-T cells were washed, counted, and suspended in XF RPMI medium containing 10 mM glucose, 2 mM L-glutamine, and 1 mM sodium pyruvate. A total of 1 \u0026times; 10⁵ cells** were seeded per well on XFP PDL mini plates. During calibration, cells were maintained at 37\u0026deg;C in a non-CO₂ incubator.\u003c/p\u003e\n\u003cp\u003eThe oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) were measured under basal conditions and after treatment with:\u003c/p\u003e\n\u003cp\u003e\u0026minus;\u0026thinsp;1.5 \u0026micro;M oligomycin A (ATP synthase inhibitor)\u003c/p\u003e\n\u003cp\u003e\u0026minus;\u0026thinsp;2.5 \u0026micro;M BAM15 (mitochondrial uncoupler)\u003c/p\u003e\n\u003cp\u003e\u0026minus;\u0026thinsp;0.5 \u0026micro;M rotenone\u0026thinsp;+\u0026thinsp;0.5 \u0026micro;M antimycin A (mitochondrial inhibitors)\u003c/p\u003e\n\u003cp\u003eMitochondrial energetic and respiratory capacities, such as the spare respiratory capacity (SRC), proton release, and ATP generation, were also analysed. Results were processed using the Seahorse Analytics software available online at [Seahorse Analytics] (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://seahorseanalytics.agilent.com/\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\n \u003ch2\u003eStatistical analysis\u003c/h2\u003e\n \u003cp\u003eStatistical analyses were conducted using GraphPad Prism 9 (GraphPad Software Inc.). Specific statistical tests are detailed in the legends of each figure. Data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error of the mean (SEM). Comparisons between two groups were performed using either the T-test or the Wilcoxon Mann-Whitney test, depending on the distribution of the data.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eGeneration and characterization of PD-1 knock-out \u0026alpha;CD19 CAR-T cells.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs previously mentioned, while there is broad consensus on the benefits of PD-1 \u003cem\u003eknock-out\u003c/em\u003e in CAR-T cells, debate remains regarding its overall impact on their functionality. Therefore, we aimed to investigate the potential effects (both beneficial and detrimental) of PD-1 \u003cem\u003eknock-out\u003c/em\u003e on \u0026alpha;CD19 CAR-T cells. We first optimized the strategy to \u003cem\u003eknock-out\u003c/em\u003e (KO) the \u003cem\u003ePDCD1\u003c/em\u003e locus in T cells. We followed our previously described protocols that use electroporation of gRNA/Cas9 ribonucleoproteins (RNPs) [\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e50\u003c/span\u003e]. Briefly, T cells were isolated from healthy donors, activated through the CD3/CD28 pathway and electroporated with the RNP complexes. 3 to 5 days later, genome editing efficacy was monitored by flow cytometry and Inference of CRISPR Edits (ICE) analysis (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eA, \u003cstrong\u003eSupplementary Fig.\u0026nbsp;1) (see M\u0026amp;M for details).\u003c/strong\u003e Based on previous data in our laboratory, we evaluated two different guide RNAs (gRNAs) designed to target exon 1 of \u003cem\u003ePDCD1\u003c/em\u003e (gRNA1 and gRNA2). Our data showed that gRNA2 outperformed gRNA1, reducing PD-1 expression to undetectable levels by flow cytometry (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;1A)\u003c/strong\u003e and, consistent with this data, generating over 80% insertion or deletions (INDELs) on ICE analysis (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eB\u003cstrong\u003e).\u003c/strong\u003e Additionally, gRNA2 preferentially generated deletions of 1 or 2 nucleotides (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;1B)\u003c/strong\u003e, both resulting in premature stop codons in the \u003cem\u003ePDCD1\u003c/em\u003e gene. Finally, biased analysis of potential \u003cem\u003eoff-target\u003c/em\u003e of both gRNAs found no generation of potential \u003cem\u003eoff-target\u003c/em\u003e in any of them (\u003cstrong\u003eSupplementary Table\u0026nbsp;1)\u003c/strong\u003e. We therefore selected gRNA2 to investigate in more details the potential genotoxic effects of PD-1 disruption. With this purpose, we used CAST-Seq, a method capable of detecting on- and off-target activity through the identification of structural genomic aberrations. On-target coverage plots derived from the CAST-Seq data revealed expected genomic rearrangements around the target site, including large deletions and inversions, resulting from the \u003cem\u003ePDCD1\u003c/em\u003e locus cleavage (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eC \u003cstrong\u003eand Supplementary Fig.\u0026nbsp;1C\u003c/strong\u003e). Importantly, no significant evidence of off-target mediated translocations (OMTs) was detected in the cells treated with the RNPs (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eC).\u003c/p\u003e\n\u003cp\u003eOnce established the best protocol for PD-1 KO, we generated PD-1 KO \u0026alpha;CD19 cells as described on workflow in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eD. The CAR construction used in this study is ARI-0001, chosen due to its potential in clinical application and thanks to collaboration with Dr. Manel Juan\u0026apos;s group at Hospital Clinic. This is a second-generation CAR, with 4-1BB and CD3\u0026zeta; as intracellular signalling domains, designed to target CD19 and expressed under the EF1-\u0026alpha; promoter. T cells were transduced with lentiviral vectors (LVs) expressing the ARI-0001 CAR, using a MOI of 10 and two days later electroporated with the RNP (Cas9\u0026thinsp;+\u0026thinsp;gRNA2). As observed in previous analysis carried out with T cells, ICE analysis revealed around 80% INDELs with an average KO score of 70% (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eE, \u003cstrong\u003eleft graph\u003c/strong\u003e), which correlates with PD-1 downregulation at the surface of CAR-T cells (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eE, right graph and \u003cstrong\u003eSupplementary Fig.\u0026nbsp;1D\u003c/strong\u003e). Importantly, our analysis also shows that PD-1 editing does not affect CAR expression (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;1E).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNext, we investigated potential effects of PD-1 KO on proliferation and phenotype of the \u0026alpha;CD19 CAR-T cells. As has been previosly described (Odorizzi, Pauken et al. 2015), we observed a reduction in the expansion capacity of PD-1 KO CAR-T cells after CD3/CD28 estimulation compared to control CAR-T cells (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eF\u003cstrong\u003e)\u003c/strong\u003e. Thus, this suggests that the reduced expansion capacity is intrinsically linked to the loss of PD-1. Another key aspect of PD-1 editing is its potential to promote a less exhausted phenotype and enrichement in memory T cells [\u003cspan class=\"CitationRef\"\u003e51\u003c/span\u003e]. In this direction, although our initial phenotype characterization reveal no significative differences in TIM-3 or LAG-3 (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eG). We also study the phenotype of this T cells in terms of CD45RA and CD62L expression (T\u003csub\u003eCM\u003c/sub\u003e (central memory), T\u003csub\u003eSCM\u003c/sub\u003e (stem cell memory), T\u003csub\u003eEM\u003c/sub\u003e (effector memory), and T\u003csub\u003eEF\u003c/sub\u003e (effector)). Activated PD-1 KO CAR-T cells showed a tendency to induce T\u003csub\u003eCM\u003c/sub\u003e (WT\u0026thinsp;=\u0026thinsp;44.4% \u0026plusmn;6.83 to KO\u0026thinsp;=\u0026thinsp;54% \u0026plusmn;5.04) and T\u003csub\u003eSCM\u003c/sub\u003e (WT\u0026thinsp;=\u0026thinsp;21.1% \u0026plusmn;5.26 to KO\u0026thinsp;=\u0026thinsp;32.5% \u0026plusmn;5.98) populations, while T\u003csub\u003eEF\u003c/sub\u003e population decreases from an average of 20.4% \u0026plusmn; 7.94 in WT CAR-T cells to 5.21% \u0026plusmn;4.69 in PD-1 KO CAR-T cells \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eH, I\u003cstrong\u003e)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePD-1 KO CAR-T cells exhibit superior lytic capability against PD-L1\u0026thinsp;+\u0026thinsp;Namalwa cells but reduced metabolic fitness.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe assessed the lytic capability against tumor target cells expressing the PD-L1 generated in our laboratory through lentiviral vector transduction (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;2A and 2B\u003c/strong\u003e), as detailed in M\u0026amp;M. Different lytic conditions were tested in order to observe differential killing between Namalwa WT and Namalwa PD-L1⁺ target cells. To reveal functional differences between ARI and ARI PD-1 KO CAR-T cells, we ultimately had to push the system to its limiting conditions. This was achieved by minimizing both the number of T cells and target cells, and by using RPMI medium instead of T cells specific TexMACs medium, thereby creating a more stringent environment to uncover the effects of PD-1 deletion. Once we achieved the exact lysis conditions, three lysis experiments were conducted using T cells obtained from three different healthy donors, transduced with a MOI of 10 to with ARI-0001 CAR LVs and edited for the \u003cem\u003ePDCD1 locus\u003c/em\u003e. These cells were co-cultured with Namalwa PD-L1\u0026thinsp;+\u0026thinsp;target cells at a 12.5:1 ratio (tumoral cell:effector CAR-T cell; T:E_CAR), with Namalwa PD-L1\u0026thinsp;+\u0026thinsp;target cells, in RPMI media. To further stress the system, we designed a repeated stimulation experiment in which CAR-T cells were exposed every 48 hours to new Namalwa PD-L1\u0026thinsp;+\u0026thinsp;target cells at the same initial ratio (12.5:1) for a total of four encounters (rechallenge or reencounter) (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA). Monitoring of relative target cells in co-culture is shown in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eB, with FACS evaluations every 48 hours. PD-1 KO CAR-T cells exhibited enhanced lytic capacity against Namalwa PD-L1\u0026thinsp;+\u0026thinsp;cells compared to WT CAR-T cells after three encounters with target cells, with clear tumour escape observed in all three donors after day 2. However, no siginificant differences were detected in terms of exhaustion markers expression (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;2D)\u003c/strong\u003e, nor phenotype (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eC). As expected, and contrary to WT CAR-T cells, repetead encounters of PD-1KO CAR-T cells with PD-L1 positive target cells lead to an increase in both the total number of CAR\u003csup\u003e+\u003c/sup\u003e T cells after 8 days (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;2E)\u003c/strong\u003e and the proportion of T\u003csub\u003eCM\u003c/sub\u003e population (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eC).\u003c/p\u003e\n\u003cp\u003eThe results observed with PD-1 KO CAR-T cells in terms of proliferation, phenotype, and lytic activity indicate that, although there are clearly positive effects in the presence of PD-L1⁺ target cells, certain alterations may also impair their cytotoxic potential. To further clarify this observation, we performed a comparative metabolic analysis between PD-1 KO CAR-T cells and control CAR-T cells. Our initial analysis showed that PD-1 CAR-T cells had a reduction in the extracellular acidification rate (ECAR)(Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eD), indicating that they produce less energy through glycolysis. This is consistent with the findings showing that PD-1 KO enhances a memory phenotype, since memory T cells produce less energy through glycolisis compared to effector T cells. Interestingly, and contrary to what is expected for memory CAR-T cells, PD-1 KO CAR-T cells exhibited a reduced oxygen consumption rate (OCR)(Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eE, left) and spare respiratory capacity (SRC)(Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eE, right), which assess mitochondrial function and capacity for energy production, respectively, indicating decreased oxidative phosphorylation efficiency in PD-1 KO CAR-T cells. To corroborate this finding, we examinated the cells ability to generate energy (ATP) through glycolysis (glycoATP) and mitochondria (mitoATP). In line with the obtained OCR and SRC parameters, PD-1 KO CAR-T cells showed a five-fold reduction in mitochondrial energy production and about three times less glycolytic energy production compared to WT CAR-T cells (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eF). These findings suggest that PD-1 KO CAR-T cells have lower overall metabolic activity and energy production resulting in reduced overall cellular fitness. This would explain the lower proliferative potential of PD-1 KO CAR- T cells as well as the lower lytic activity of these cells when encountering PD-1L negative targets.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEngineering CAR-T cells to express IL-15 under the PD-1 promoter (PD-1KIL-15 CAR-Ts) improve proliferation and survival of PD-1-KO CAR-T cells\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003eOur previous results show that PD-1 KO CAR-T cells enhance their lytic capacity against PD-L1\u0026thinsp;+\u0026thinsp;tumor cells and improved memory subpopulation frequencies. However, they exhibit lower lytic capacity against PD-L1 negative targets, along with reduced proliferative capacity and metabolic fitness. To address this issue, we investigated whether controlled expression of the cytokine IL-15 could enhance the potency of PD-1KO CAR-T cells due to the role of this cytokine regulating T cell bioenergetics. We designed a \u003cem\u003eknock-in\u003c/em\u003e (KI) genome editing platform to simultaneously \u003cem\u003eknock-out\u003c/em\u003e PD-1 and express IL-15 through the PD-1 promoter by inserting a IL-15 complementary DNA (cDNA) into the exon 1 of PD-1 exon 1 (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA, \u003cstrong\u003etop).\u003c/strong\u003e With the aim of monitoring IL-15 expression driven through the inserted cassette and to avoid residual PD-1 expression, we desingned a DNA donor that included a eGFP cDNA after the 2A peptide and a polyadenilation signal \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA, \u003cstrong\u003emiddle).\u003c/strong\u003e The DNA donor was included in a AAV6 vector, which is highly efficient in human T cells. With this construct once inserted in the target location, the genome edited T cells will lack PD-1 and express IL-15 and eGFP only under T cell activation and/or T cells exhaustion \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA \u003cstrong\u003ebottom).\u003c/strong\u003e To achieved high T cells KI efficiency we used a previously established procedure that combine RNP electroporation with AAV6 transduction [\u003cspan class=\"CitationRef\"\u003e52\u003c/span\u003e] and compared most used MOI 10\u003csup\u003e4\u003c/sup\u003e versus 5x10\u003csup\u003e4\u003c/sup\u003e GC/mL (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;3A\u003c/strong\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003eWe next analysed IL-15 (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eB \u003cstrong\u003eleft\u003c/strong\u003e) and PD-1 (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eB \u003cstrong\u003eright\u003c/strong\u003e) expression levels in control CAR-T cells (WT) versus PD-1KIL-15 CAR-T cells at baseline and after activation. As expected, PD-1 expression was significantly reduced. Importantly, the expression pattern of exogenous IL-15 (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eC, \u003cstrong\u003ebotton\u003c/strong\u003e) mimicked that of PD-1 (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eC, \u003cstrong\u003etop\u003c/strong\u003e) in the PD-1KIL-15 CAR-T cells edited population (80% editing efficiency), with both increasing upon T cell activation. This data was in agreement with the IL-15 controlled expression by the PD-1 gene promoter. To further confim this, we measured total secreted IL-15 by ELISA. At baseline, control and PD-1KIL-15 CAR-T cells express similar IL-15 levels (around 17ng/ml). However, upon activation, only PD-1KIL-15 cells increased IL-15 levels to over 24ng/ml (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eD), which confirmed that PD-1KIL-15 CAR-T cells not only express intracellular IL-15, but also secrete it. Finally, we analysed by RT-PCR, the levels of endogenous IL-15 versus IL-15 expressed through the integrated DNA donor using specific set of primers for each (See M\u0026amp;M and \u003cstrong\u003eSupplementary Fig.\u0026nbsp;3B\u003c/strong\u003e). As expected, most of the IL-15 expressed by PD-1KIL-15 cells comes from the integrated DNA donor (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eE).\u003c/p\u003e\n\u003c/div\u003e\n\u003cp\u003eSince IL-15 has a major role on promoting T cells cell survival and proliferation, we next compared both parameters in control, PD-1 and PD-1KIL-15 CAR-T cells. First, we studied the proliferative capacity of these cells generated from three donors. Our data showed that PD-1KIL-15 CAR-T cells regained their proliferative capacity in all donors, even compared to unedited CAR-T cells (FIG. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eF).\u003c/p\u003e\n\u003cp\u003eNext, we analysed the expression levels of BIM (pro-apototic) and Bcl-xl (anti-apoptotic) proteins, which are known to be downregulated and upregulated, respectively, by IL-15. We observed an increase of both proteins compared to WT unactivated cells, upon activation in WT CAR-T cells (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eG, \u003cstrong\u003edark blue bars\u003c/strong\u003e) that was not present in PD-1 CAR-T cells (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eG, \u003cstrong\u003edark and bright purple bars\u003c/strong\u003e). In addition, the activated PD-1 KO CAR-T cells showed a strong reduction of the anti-apoptotic Bcl-xL gene, from 1 in unactivated WT cells to 0.422, that could account in part for it low proliferation capabilities. Expression of BIM and Bcl-xL related to the effects of IL-15 could explain the increased proliferative capacity of PD-1KIL-15 CAR-T cells. These expression data showed that BIM expression decreased from 0.96 in CAR-T WT cells to 0.458 in PD-1KIL-15 CAR-T cells. Similarly, Bcl-xL expression increased from an average of 1 in CAR-T WT cells to 1.98 in PD-1KIL-15 CAR-T cells (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eG, dark and bright grey bars). Finally, we also evaluated the immunophenotype of edited CAR-T cells using CD45RA and CD62L markers to determine T cell subpopulation distribution. After three days of activation, IL-15 expression did not significantly affect memory population distribution compared to CAR-T PD-1 KO cells, except for a reduction of T\u003csub\u003eEM\u003c/sub\u003e cells (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eH).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePD-1IKL-15 CAR-T cells exhibit enhanced glycolytic and mitochondrial ATP production compared to PD-1 KO CAR-T cells\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe enhanced proliferative potential observed in PD-1KIL-15 CAR-T cells, likely due to increased IL-15 secretion (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e), prompted us to investigate whether the metabolic impairment caused by PD-1 \u003cem\u003eknock-out\u003c/em\u003e was also reversed. As shown in Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eA and consistent with previous analyses, ECAR, a marker of anaerobic metabolism, was higher in P D-1KIL-15 CAR-T cells (34.42 mpH/min/cells) compared to PD-1 KO CAR-T cells (18.88 mpH/min/cells), although it did not reach the glycolytic levels observed in CAR-T WT cells (51.05 mpH/min/cells). As done previously with PD-1 KO CAR-T cells, we also analysed oxidative metabolism by measuring OCR and SRC. Similar patterns were observed in the OCR analysis (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eB, \u003cstrong\u003eleft\u003c/strong\u003e), where IL-15-expressing cells showed increased oxygen consumption rates compared to PD-1 KO CAR-T cells. Furthermore, PD-1KIL-15 CAR-T cells exhibited a higher SRC than PD-1 KO CAR-T cells, effectively reversing the mitochondrial metabolic deficiency induced by PD-1 \u003cem\u003eknock-out\u003c/em\u003e and indicating a more robust energetic profile (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eB, \u003cstrong\u003eright\u003c/strong\u003e), completely restoring these mitochondrial metabolic characteristics in PD-1 edited cells.\u003c/p\u003e\n\u003cp\u003eATP production analysis revealed a pronounced enhancement in the bioenergetic profile of PD-1KIL-15 CAR-T cells (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eC). Specifically, glycolytic ATP production (glycoATP) was increased by approximately 1.8-fold compared to PD-1 KO CAR-T cells, indicating improved efficiency in anaerobic energy generation. More strikingly, mitochondrial ATP production (mitoATP) exhibited an almost six-fold increase in PD-1KIL-15 CAR-T cells compared to PD-1 KO CAR-T cells, highlighting a profound restoration of mitochondrial function. This This enhancement of mitochondrial activity suggests a reactivation of the oxidative phosphorylation pathways, likely facilitated by IL-15-induced signaling events that promote mitochondrial biogenesis, respiratory chain efficiency, or both. The elevated mitoATP levels indicate not only a higher basal energy output but also an enhanced capacity to meet energy demands during activation and proliferation (critical features for the sustained functionality and persistence of CAR-T cells in therapeutic settings). This metabolic reprogramming toward a more oxidative and efficient energy profile underscores the potential of IL-15 expression to overcome the metabolic exhaustion typically associated with PD-1 disruption.\u003c/p\u003e\n\u003cp\u003eWe also proved that PD-1KIL-15 CAR-T cells displayed higher OCR when compared with PD-1 KO CAR-T cells, reaching the same levels as WT cells \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eD\u003cstrong\u003e).\u003c/strong\u003e As OCR is a strong indicator of the phenotype and fitness of immune cells, in effector terms, we could conclude that PD-1KIL-15 CAR-T cells predominantly present a memory phenotype in addition to having a greater antitumour capacity.\u003c/p\u003e\n\u003cp\u003eOnce PD-1KIL-15 CAR-T cells where characterized, we proceeded to analyse their antitumour activity against PD-L1\u0026thinsp;+\u0026thinsp;target cells. WT CAR-T cells, PD-1 KO CAR-T cells, and PD-1KIL-15 CAR-T cells generated from three different healthy donors were subjected to four encounters with Namalwa PD-L1\u0026thinsp;+\u0026thinsp;target cells (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eE). Target cells persistence is significantly compromised when co-cultured with PD-1KIL-15 CAR-T cells, in comparison with those co-cultured with CAR-T WT cells (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eF). Lytic activity was evaluated every 24 hours for the first two days, and every 48 hours from day 2 onward. At the end of the experiment (day 8), phenotype and persistence of the different CAR-T cells were analysed. PD-1KIL-15 CAR-T cells were able to maintain a higher lysis capacity compared to CAR-T WT cells (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eF, \u003cstrong\u003eday 2\u003c/strong\u003e). The exhaustion markers TIM-3 and LAG-3 are expressed similarly in both WT CAR-T and PD-1 KO CAR-T cells. However, both markers are reduced in PD-1KIL-15 CAR-T cells, with a significant reduction observed in the case of LAG3 (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eG). At end point, PD-1 KO CAR-T cells increased in number up to two-fold compared to baseline, whereas PD-1KIL-15 CAR-T cells exhibited a three-fold increase \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eH\u003cstrong\u003e)\u003c/strong\u003e, suggesting improved persistence capacity. This data is consistent with the enhanced lysis efficiency of PD-1KIL-15 CAR-T cells \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eF\u003cstrong\u003e).\u003c/strong\u003e Finally, subpopulations analysis by flow cytometry (based on the expression of CD45RA and CD62L markers) after different encounters with PD-L1\u0026thinsp;+\u0026thinsp;target cells showed that PD-1KIL-15 CAR-T cells exhibited a significant increase in T\u003csub\u003eCM\u003c/sub\u003e cells compared to WT CAR-T cells (77.3% \u0026plusmn; 7.82 vs. 64.6% \u0026plusmn;0.47) and a significant decrease in T\u003csub\u003eSCM\u003c/sub\u003e cells compared to WT CAR-T cells (9.16% \u0026plusmn; 2.64 vs. 18.5% \u0026plusmn;4.07. These variations in memory populations align with the observed lytic capacity, as T\u003csub\u003eSCM\u003c/sub\u003e cells have high proliferative potential but lower effector capacities compared to T\u003csub\u003eEM\u003c/sub\u003e and T\u003csub\u003eCM\u003c/sub\u003e cells (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eI).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRNA sequencing analysis confirms integration and expression of IL-15 and its benefits on CAR-T cells in contrast to PD-1 KO CAR-T cells\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo gain further insight into the molecular mechanisms underlying our PD-1KIL-15 CAR-T cells, we performed RNA sequencing (RNA-seq) followed by gene set enrichment analysis (GSEA) to identify differentially regulated pathways. RNA-seq was conducted on the three CAR-T cell populations from three different donors three days after activation to assess how the \u003cem\u003eknock-in\u003c/em\u003e strategies affected CAR-T cell function. This approach enabled us to compare, at transcriptomic level, the effects of PD-1 ablation and/or the addition and expression of the IL-15 cytokine under the control of the endogenous PD-1 promoter. The analysis was performed on bulk populations, and no significant differences were observed in CAR expression, PD-1 expression, or IL-15 integration across donors or conditions, ensuring that the comparisons were not biased by variability in transgene expression or editing efficiency. Conversely, PD-1 KO CAR-T cells displayed enrichment of pathways linked to cellular stress, serum deprivation-induced apoptosis, and mitochondrial dysfunction (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eA), consistent with their reduced glycolytic and mitochondrial ATP production (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eD-F) and lower cytotoxic efficacy over repeated tumour encounters (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;2C and\u003c/strong\u003e Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eF). This is also reflected in the increased LAG-3 expression (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;2D and\u003c/strong\u003e Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eG), their reduced ability to maintain T cell expansion under chronic stimulation (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eH), and their apoptotic protein expression profile (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eG) indicating functional exhaustion.\u003c/p\u003e\n\u003cp\u003eAs shown in FIG. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e, in contrast with PD-1 KO transcriptomic profile, PD-1KIIL-15 CAR-T cells displayed a unique transcriptional profile characterized by an increase in enrichment in mitochondrial respiration, oxidative phosphorylation, fatty acid metabolism, and electron transport chain-related pathways compared to both PD-1 KO CAR-T and WT CAR-T cells (FIG. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eA and \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eB). These transcriptomic features are consistent with the enhanced mitochondrial function observed in the Agilent Seahorse assay (FIG. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eB\u0026ndash;D), including increased OCR, SRC, and mitochondrial ATP production.\u003c/p\u003e\n\u003cp\u003eThis elevated mitochondrial gene expression in Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e aligns with early phenotypic observations observed in Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eH, where PD-1KIL-15 CAR-T cells showed higher frequencies in T\u003csub\u003eSCM\u003c/sub\u003e populations shortly after activation, suggesting an early shift toward a long-lived metabolic program. These features are further maintained and expanded upon in Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e, where PD-1KIL-15 CAR-T cells exhibit lower exhaustion marker expression (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eG), and a higher frequency of T\u003csub\u003eCM\u003c/sub\u003e cells at later time points, supporting the hypothesis of superior persistence and stemness-like qualities, probably as a result of IL-15 expression (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eI).\u003c/p\u003e\n\u003cp\u003eIn addition to metabolic rewiring, Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eA reveals significant enrichment of mTOR and KRAS signalling pathways in PD-1KIL-15 CAR-T cells, hallmarks of T cell proliferation, activation, and survival. These findings support the increased CAR-T cell expansion observed in the co-culture assays (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eF and \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eH), and stand in line with the transcriptional signatures observed in Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e, where PD-1KIL-15 CAR-T cells show upregulation of gene modules related to cell growth, proliferation, and cytokine signalling.\u003c/p\u003e\n\u003cp\u003eTogether, this data integrates phenotypic, functional, and transcriptional evidence to show that PD-1KIL-15 CAR-T cells outperform PD-1 KO and WT CAR-T cells through coordinated mitochondrial reprogramming, reduced exhaustion, and enhanced memory formation. The targeted insertion of IL-15 into the \u003cem\u003ePDCD1\u003c/em\u003e locus not only preserves T cell fitness but also actively promotes long-term metabolic and functional advantages, which are crucial for sustained antitumour responses in adoptive cell therapies.\u003c/p\u003e"},{"header":"Discusion","content":"\u003cp\u003eCAR-T therapy combines adoptive cell therapy, immunotherapy and gene therapy, and has achieved significant success in treating haematological malignancies such as B-cell leukaemia, lymphomas and multiple myeloma. However, 50\u0026ndash;70% of patients relapse post-treatment, with higher relapse rates in specific lymphoma and myeloma subtypes [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. These setbacks are often attributed to insufficient cell persistence, antigen escape, and tumour-induced immunosuppressive microenvironments, particularly in solid tumours [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. To address these challenges, immune checkpoint inhibitors (ICIs)\u0026mdash;particularly those targeting the PD-1/PD-L1 axis\u0026mdash;have been incorporated into therapeutic regimens to enhance CAR-T efficacy [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e], and are now being used in combination with CAR-T cells to enhance their efficacy [\u003cspan additionalcitationids=\"CR59\" citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. In parallel, gene editing approaches to disrupt PD-1 and other inhibitory receptors (as LAG-3 or TIM-3) have emerged as promising strategies. Although PD-1 \u003cem\u003eknock-out\u003c/em\u003e (KO) has been proven to improve CAR-T cell function and antitumour responses, contrasting findings also highlight risks such as premature T cell exhaustion and reduced persistence, which appear to be highly dependent on the CAR construct design, target antigen, and experimental conditions [\u003cspan additionalcitationids=\"CR62\" citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eBuilding upon these findings, our study investigated the functional and metabolic consequences of PD-1 ablation in CAR-T cells, while also introducing a novel \u003cem\u003eknock-in\u003c/em\u003e strategy that leverages the endogenous PD-1 promoter to dynamically regulate IL-15 expression. Our PD-1 KO model aimed to block PD-1/PD-L1 signalling [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e] using Cas9/gRNA electroporation, reflecting mechanisms similar to FDA (and EMA) approved monoclonal antibody therapies [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. Consistent with previous works, PD-1 KO led to altered T cell activation kinetics and metabolic profiles.\u003c/p\u003e\u003cp\u003eWe observed that, contrary to several reports [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e], PD-1 KO CAR-T cells showed reduced expansion, particularly in the absence of PD-L1 stimulation. Our αCD3/αCD28 stimulation model demonstrated that CAR-T WT cells outperformed PD-1 KO counterparts in proliferation, supporting the idea that PD-1 deletion may disrupt activation thresholds and homeostatic control, leading to overactivation and terminal differentiation [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]\u003c/p\u003e\u003cp\u003eInterestingly, RNA-seq analysis of PD-1 KO CAR-T cells revealed upregulation of gene signatures associated with cell proliferation, although these transcriptional changes did not translate into enhanced proliferation in our \u003cem\u003eex vivo\u003c/em\u003e models. This was corroborated by Seahorse metabolic analysis analysis and RNA-seq data, which showed a marked reduction in both glycolytic and mitochondrial ATP production (GlycoATP and MitoATP), highlighting the role of PD-1 in balancing glycolysis with FAO/OXPHOS metabolic pathways [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. Additionally, the elevated expression of apoptotic pathways, likely compromises their ability to maintain the proliferative program. Therefore, even though the pathways related to proliferation are transcriptionally active, the lack of metabolic fitness prevents their functional realization. This emphasizes the importance of coupling transcriptional reprogramming with metabolic support to achieve effective cellular function.\u003c/p\u003e\u003cp\u003eOne possible explanation for this phenomenon is that the activation of proliferation-associated genes, such as \u003cem\u003eMYC\u003c/em\u003e, \u003cem\u003eE2F\u003c/em\u003e, and cyclin family members, can initiate a cell cycle entry program, but the continuation of this program requires robust ATP generation and maintenance of redox balance. PD-1 KO cells, due to their impaired mitochondrial capacity and insufficient glycolytic flexibility, may experience energetic stress that leads to the activation of cellular checkpoints such as AMPK or p53, ultimately halting cell cycle progression [\u003cspan additionalcitationids=\"CR69 CR70 CR71\" citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. Additionally, high intracellular stress and reactive oxygen species (ROS) levels may further compromise survival pathways, shifting the balance toward apoptosis rather than sustained proliferation.\u003c/p\u003e\u003cp\u003eThis hypothesis is further supported by our observation of increased expression of apoptotic markers in PD-1 KO CAR-T cells. Expression evaluation together with transcriptomic analysis indicated elevated levels of pro-apoptotic molecules such as BIM, PUMA, and caspase-related genes, while anti-apoptotic regulators like \u003cem\u003eBcl-2\u003c/em\u003e and \u003cem\u003eBcl-xL\u003c/em\u003e were comparatively underexpressed [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]. These findings suggest that, in the absence of PD-1, the imbalance between metabolic stress and survival signaling primes CAR-T cells for apoptosis, thereby limiting their proliferative capacity and functional persistence.\u003c/p\u003e\u003cp\u003eTaken together, these findings demonstrate that transcriptomic signatures alone do not fully predict functional outcomes. In the case of PD-1 KO CAR-T cells, a superficial increase in proliferation-related gene expression masks an underlying fragility rooted in metabolic insufficiency. This has important implications for the design and interpretation of gene editing strategies in CAR-T cells: interventions must consider not only the removal of inhibitory signals but also the preservation (or enhancement) of cellular fitness.\u003c/p\u003e\u003cp\u003eOur data underscore the essential role of metabolic support in enabling CAR-T cells to fully execute their transcriptional programs. While PD-1 ablation effectively removes inhibitory checkpoints, it simultaneously disrupts metabolic homeostasis, highlighting an unintended trade-off between cellular activation and long-term functionality. In the absence of sufficient mitochondrial capacity and glycolytic adaptability, CAR-T cells are unable to sustain their activated state, leading instead to metabolic exhaustion, increased apoptosis, and impaired persistence. These findings suggest that immune checkpoint disruption must be accompanied by strategies that preserve or enhance metabolic fitness to ensure durable antitumour responses. To address this limitation, we explored a targeted \u003cem\u003eknock-in\u003c/em\u003e strategy to couple IL-15 expression to the endogenous \u003cem\u003ePDCD1\u003c/em\u003e promoter. This approach aimed to simultaneously block PD-1 signaling and provide metabolic and survival support through localized IL-15 production during T cell activation. Our design enables IL-15 expression upon T cell activation, mimicking physiological demand and avoiding systemic IL-15 toxicity [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e]. We validated site-specific insertion by qPCR and ELISA, showing 8-fold increase in IL-15 mRNA in activated cells. PD-1KIL-15 CAR-T cells provides a compelling illustration of how metabolic and functional deficiencies can be mitigated by coupling immunoregulatory gene edits with cytokine support. IL-15 expression under the PD-1 promoter not only aligns cytokine delivery with T cell activation but also promotes mitochondrial biogenesis, enhances oxidative metabolism, and stabilizes the expression of anti-apoptotic proteins [\u003cspan additionalcitationids=\"CR78 CR79\" citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e]. These effects collectively restore the capacity for sustained proliferation and cytotoxic activity, particularly under conditions of chronic antigen stimulation. Moreover, the coordinated regulation of IL-15 ensures that its expression remains tightly linked to cellular activation status, preventing toxicity while maximizing functional benefit.\u003c/p\u003e\u003cp\u003eFunctionally, PD-1-KIL-15 CAR-T cells demonstrated markedly improved expansion capacity and metabolic performance, characterized by enhanced mitochondrial respiration, increased mitochondrial ATP production, and elevated spare respiratory capacity (all hallmarks of metabolically fit, long-lived T cells). These functional gains were consistent with transcriptomic signatures enriched for oxidative phosphorylation, fatty acid oxidation, and adipogenesis pathways, which are typically associated with memory-like T cell phenotypes and long-term persistence. Importantly, the metabolic advantage conferred by IL-15 expression appears to translate into improved survival capacity, as evidenced by the upregulation of anti-apoptotic genes such as \u003cem\u003eBcl-xL\u003c/em\u003e and the downregulation of pro-apoptotic genes like \u003cem\u003eBIM\u003c/em\u003e, observed through both qPCR and RNA-seq analyses [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e] Altogether, this data suggests that controlled IL-15 expression under the \u003cem\u003ePDCD1\u003c/em\u003e promoter not only compensates for the metabolic stress induced by PD-1 ablation but also enhances the persistence and survival of CAR-T cells by reprogramming their bioenergetic and apoptotic profiles.\u003c/p\u003e\u003cp\u003eThe superiority of PD-1KIL-15 CAR-T cells was also reflected in their immunophenotypic profile. These cells exhibited increased central memory and stem-like subpopulations, with reduced expression of the exhaustion markers LAG-3 and TIM-3. These features are closely tied to long-term persistence and have been associated with improved clinical outcomes in CAR-T therapies [\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e] [\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e]. Additionally, PD-1KIL-15 CAR-T cells demonstrated superior cytotoxicity over multiple rounds of antigen exposure, confirming their resilience and functional competence in stress-inducing environments.\u003c/p\u003e\u003cp\u003eIn summary, our study highlights the dual challenge of overcoming immune suppression while preserving CAR-T cell fitness. While PD-1 \u003cem\u003eknock-out\u003c/em\u003e offers initial benefits, its long-term effects may be detrimental unless counterbalanced by supportive cytokine signalling. By integrating IL-15 expression under endogenous PD-1 control, pdTRUCKIL-15 cells achieve enhanced persistence, metabolism, and cytotoxicity, offering a promising next-generation CAR-T design for durable antitumour immunity.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn summary, this study provides a comprehensive evaluation of the PD-1/PD-L1 axis in the context of CAR-T cell therapy. We investigated the functional consequences of PD-1 ablation in CAR-T cells, observing distinct changes in PD-1 expression kinetics in both PD-1 KO and unmodified T cells upon activation, thereby highlighting the importance of PD-1 in the tumour immune landscape. Our research further explored the metabolic impact of PD-1 \u003cem\u003eknock-out\u003c/em\u003e, revealing significant reductions in ATP production and alterations in metabolic pathways, which may affect T cell functionality and expansion.\u003c/p\u003e\u003cp\u003eTo enhance the therapeutic potential of PD-1 KO CAR-T cells, we incorporated controlled IL-15 expression within the \u003cem\u003ePDCD1\u003c/em\u003e locus, resulting in improved cell expansion, enhanced fitness, and a memory-like phenotype. Notably, PD-1 KO CAR-T cells, especially those expressing IL-15, demonstrated superior lysis capabilities and reduced exhaustion marker expression, underscoring their promise as effective therapeutic agents. However, while PD-1 ablation enhances antitumour potential, it also induces metabolic stress that can limit CAR-T cell persistence and expansion. By coupling IL-15 expression to the endogenous \u003cem\u003ePDCD1\u003c/em\u003e locus, we restored metabolic fitness and promoted a memory-like, apoptosis-resistant phenotype.\u003c/p\u003e\u003cp\u003eThese findings highlight the importance of balancing immune activation with metabolic support and demonstrate the potential of combinatorial gene editing strategies to improve CAR-T cell efficacy, particularly against PD-L1\u0026ndash;expressing tumours. Future in vivo studies using animal models will be conducted to validate and further characterize these findings in a physiological context\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis publication is based upon work from COST Action Gene Editing for the Treatment of Human Diseases, CA21113 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.genehumdi.eu\u003c/span\u003e\u003cspan address=\"https://www.genehumdi.eu\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and is supported by the COST. The study was also supported by the Consejer\u0026iacute;a de Universidad, Investigaci\u0026oacute;n e Innovaci\u0026oacute;n under Plan Andaluz de Investigaci\u0026oacute;n, Desarrollo e Innovaci\u0026oacute;n (PAIDI 2020) (\u003cb\u003eProyExcel_00875\u003c/b\u003e) de la junta de Andaluc\u0026iacute;a. And \u003cb\u003ePI-0216-2024 uCARAML-Nano\u003c/b\u003e, and \u003cb\u003ePECART-0027-2020\u003c/b\u003e,funded by la Consejer\u0026iacute;a de Salud y Consumo de la Junta de Andaluc\u0026iacute;a. This project was funded by Spanish ISCIII Health Research Fund and the European Regional Development Fund (FEDER) through research grants \u003cb\u003ePI18/01016\u003c/b\u003e (CH), \u003cb\u003ePI18/00330\u003c/b\u003e (KB), \u003cb\u003ePI21/00298\u003c/b\u003e and \u003cb\u003ePI24/00888\u003c/b\u003e (FM). ISCIII\u0026ndash; NextGenerationEU funds - actions of the Recovery and Resilience Mechanism: \u003cb\u003eRed TerAv RD21/0017/0004\u003c/b\u003e and \u003cb\u003eTerAv\u0026thinsp;+\u0026thinsp;RD24/0014/0005\u003c/b\u003e (FM). Ministerio de Ciencia e innovaci\u0026oacute;n (MICIN). Plan de Recuperaci\u0026oacute;n, transformaci\u0026oacute;n y resilencia, Centro para el Desarrollo Tecnol\u0026oacute;gico Industrial (CDTI) and European Union-Next Generation EU: Research grants \u003cb\u003e00123009/SNEO-20191072\u003c/b\u003e (FM), \u003cb\u003ePMPTA22/00060\u003c/b\u003e (FM) Consejer\u0026iacute;a de Salud y Familias (CSyF) -Junta de Andaluc\u0026iacute;a - FEDER/European Cohesion Fund (FSE) for Andaluc\u0026iacute;a: Grants: 2\u003cb\u003e016000073332-TRA, CARTPI-0001-201, PECART-0031-2020 y PI-0236-2024\u003c/b\u003e (FM). Ministerio de Ciencia e innovaci\u0026oacute;n (MICIN) \u0026ndash; l\u0026iacute;neas estrat\u0026eacute;gicas: Grant \u003cb\u003ePLEC2021-008094\u003c/b\u003e (FM). European Union\u0026rsquo;s Horizon research and innovation program \u0026mdash; Grant agreement no. \u003cb\u003e101057438\u003c/b\u003e (geneTIGA) for C.F, R.O.B and T.C. K.B. held a Nicolas Monardes contract from Consejer\u0026iacute;a de Salud y Consumo de la Junta de de Andaluc\u0026iacute;a, MTM is funded by a Postdoctoral Contract RHJ-0106-2024 Consejer\u0026iacute;a de Salud y Consumo Junta de Andaluc\u0026iacute;a (Spain). Y.L. is supported by the the Novo Nordisk Foundation (\u003cb\u003eNNF21OC0072031, NNF21OC0068988\u003c/b\u003e) and the Lundbeck Foundation (\u003cb\u003eR396-2022-350\u003c/b\u003e).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAuthor Contributions\u0026bull;M.C.-G. (M. Cortijo-Guti\u0026eacute;rrez): Contributed to the conception and design of the study, performed experiments, and drafted the manuscript.\u0026bull;K.B. (K. Benabdellah): Contributed to study conception and supervision, performed data interpretation, and drafted and revised the manuscript and secured project funding. \u0026bull;N.M.-P. (N. Maldonado-P\u0026eacute;rez): Participated in data acquisition and experimental procedures.\u0026bull;M.T.-M. (M. Trist\u0026aacute;n-Manzano): Contributed to data acquisition and figure preparation.\u0026bull;K.P. (K. Pavlovic): Assisted in experimental design and data collection.\u0026bull;P.J.-L. (P. Justicia-Lirio): Performed data analysis \u0026bull;C.F.-G. (C. Fuster-Garc\u0026iacute;a): Contributed to bioinformatics analyses and data interpretation.\u0026bull;P.C.-S. (P. Carmona-S\u0026aacute;ez): Supervised bioinformatics analysis and contributed to data interpretation.\u0026bull;T.C. (T. Cathomen): critically revised the manuscript.\u0026bull;R.O.B. (R. O. Bak): Contributed to experimental strategy for gene editing and data interpretation.\u0026bull;P.P.J.-B. (P. P. Jurado-Basc\u0026oacute;n): Contributed to interpretation of RNAseq l data.\u0026bull;I.C.H. (I. C. Herrera): Provided clinical insights and contributed to data interpretation.\u0026bull;Y.L. (Yonglun Luo): Contributed to gene editing methodology.\u0026bull;F.M. (F. Mart\u0026iacute;n): Supervised the project and substantially revised the manuscript.All authors have read and approved the final manuscript and agree to be accountable for all aspects of the work.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWE would like to thanks, Geoffroy Andrieux (from the Institute of Medical Bioinformatics and Systems Medicine, Medical Center-University of Freiburg) for his help with the bioinformatic part in the CAST-Seq pipeline\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData is provided within the manuscript or supplementary information files\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eZhang M, Liu C, Tu J, Tang M, Ashrafizadeh M, Nabavi N, Sethi G, Zhao P, Liu S: Advances in cancer immunotherapy: historical perspectives, current developments, and future directions. \u003cem\u003eMolecular cancer\u003c/em\u003e 2025, 24:136.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePasvolsky O, Kebriaei P, Shah BD, Jabbour E, Jain N: Chimeric antigen receptor T-cell therapy for adult B-cell acute lymphoblastic leukemia: state-of-the-(C)ART and the road ahead. \u003cem\u003eBlood advances\u003c/em\u003e 2023, 7:3350\u0026ndash;3360.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBrudno JN, Maus MV, Hinrichs CS: CAR T Cells and T-Cell Therapies for Cancer: A Translational Science Review. \u003cem\u003eJAMA\u003c/em\u003e 2024, 332:1924\u0026ndash;1935.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePatel KK, Tariveranmoshabad M, Kadu S, Shobaki N, June C: From concept to cure: The evolution of CAR-T cell therapy. \u003cem\u003eMolecular therapy: the journal of the American Society of Gene Therapy\u003c/em\u003e 2025, 33:2123\u0026ndash;2140.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMartinez-Cibrian N, Ortiz-Maldonado V, Espanol-Rego M, Blazquez A, Cid J, Lozano M, Magnano L, Gine E, Correa JG, Mozas P, et al: The academic point-of-care anti-CD19 chimeric antigen receptor T-cell product varnimcabtagene autoleucel (ARI-0001 cells) shows efficacy and safety in the treatment of relapsed/refractory B-cell non-Hodgkin lymphoma. \u003cem\u003eBritish journal of haematology\u003c/em\u003e 2024, 204:525\u0026ndash;533.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKhan AN, Asija S, Pendhari J, Purwar R: CAR-T cell therapy in hematological malignancies: Where are we now and where are we heading for? \u003cem\u003eEuropean journal of haematology\u003c/em\u003e 2023.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMucha SR, Rajendram P: Management and Prevention of Cellular-Therapy-Related Toxicity: Early and Late Complications. \u003cem\u003eCurrent oncology\u003c/em\u003e 2023, 30:5003\u0026ndash;5023.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang Q, Shao X, Zhang Y, Zhu M, Wang FXC, Mu J, Li J, Yao H, Chen K: Role of tumor microenvironment in cancer progression and therapeutic strategy. \u003cem\u003eCancer medicine\u003c/em\u003e 2023, 12:11149\u0026ndash;11165.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYamaguchi H, Hsu JM, Yang WH, Hung MC: Mechanisms regulating PD-L1 expression in cancers and associated opportunities for novel small-molecule therapeutics. \u003cem\u003eNature reviews Clinical oncology\u003c/em\u003e 2022, 19:287\u0026ndash;305.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi Y, Sharma A, Schmidt-Wolf IGH: Evolving insights into the improvement of adoptive T-cell immunotherapy through PD-1/PD-L1 blockade in the clinical spectrum of lung cancer. \u003cem\u003eMolecular cancer\u003c/em\u003e 2024, 23:80.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKraehenbuehl L, Weng CH, Eghbali S, Wolchok JD, Merghoub T: Enhancing immunotherapy in cancer by targeting emerging immunomodulatory pathways. \u003cem\u003eNature reviews Clinical oncology\u003c/em\u003e 2022, 19:37\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLin X, Kang K, Chen P, Zeng Z, Li G, Xiong W, Yi M, Xiang B: Regulatory mechanisms of PD-1/PD-L1 in cancers. \u003cem\u003eMolecular cancer\u003c/em\u003e 2024, 23:108.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLah S, Kim S, Kang I, Kim H, Hupperetz C, Jung H, Choi HR, Lee YH, Jang HK, Bae S, Kim CH: Engineering second-generation TCR-T cells by site-specific integration of TRAF-binding motifs into the CD247 locus. \u003cem\u003eJournal for immunotherapy of cancer\u003c/em\u003e 2023, 11.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYang Z, Wu H, Lin Q, Wang X, Kang S: Lymphopenic condition enhanced the antitumor immunity of PD-1-knockout T cells mediated by CRISPR/Cas9 system in malignant melanoma. \u003cem\u003eImmunology letters\u003c/em\u003e 2022, 250:15\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang Z, Li N, Feng K, Chen M, Zhang Y, Liu Y, Yang Q, Nie J, Tang N, Zhang X, et al: Phase I study of CAR-T cells with PD-1 and TCR disruption in mesothelin-positive solid tumors. \u003cem\u003eCellular \u0026amp; molecular immunology\u003c/em\u003e 2021, 18:2188\u0026ndash;2198.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNakazawa T, Natsume A, Nishimura F, Morimoto T, Matsuda R, Nakamura M, Yamada S, Nakagawa I, Motoyama Y, Park YS, et al: Effect of CRISPR/Cas9-Mediated PD-1-Disrupted Primary Human Third-Generation CAR-T Cells Targeting EGFRvIII on In Vitro Human Glioblastoma Cell Growth. \u003cem\u003eCells\u003c/em\u003e 2020, 9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHu W, Zi Z, Jin Y, Li G, Shao K, Cai Q, Ma X, Wei F: CRISPR/Cas9-mediated PD-1 disruption enhances human mesothelin-targeted CAR T cell effector functions. \u003cem\u003eCancer immunology, immunotherapy: CII\u003c/em\u003e 2019, 68:365\u0026ndash;377.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChoi BD, Yu X, Castano AP, Darr H, Henderson DB, Bouffard AA, Larson RC, Scarfo I, Bailey SR, Gerhard GM, et al: CRISPR-Cas9 disruption of PD-1 enhances activity of universal EGFRvIII CAR T cells in a preclinical model of human glioblastoma. \u003cem\u003eJournal for immunotherapy of cancer\u003c/em\u003e 2019, 7:304.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGuo X, Jiang H, Shi B, Zhou M, Zhang H, Shi Z, Du G, Luo H, Wu X, Wang Y, et al: Disruption of PD-1 Enhanced the Anti-tumor Activity of Chimeric Antigen Receptor T Cells Against Hepatocellular Carcinoma. \u003cem\u003eFrontiers in pharmacology\u003c/em\u003e 2018, 9:1118.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRupp LJ, Schumann K, Roybal KT, Gate RE, Ye CJ, Lim WA, Marson A: CRISPR/Cas9-mediated PD-1 disruption enhances anti-tumor efficacy of human chimeric antigen receptor T cells. \u003cem\u003eScientific reports\u003c/em\u003e 2017, 7:737.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKalia V, Yuzefpolskiy Y, Vegaraju A, Xiao H, Baumann F, Jatav S, Church C, Prlic M, Jha A, Nghiem P, et al: Metabolic regulation by PD-1 signaling promotes long-lived quiescent CD8 T cell memory in mice. \u003cem\u003eScience translational medicine\u003c/em\u003e 2021, 13:eaba6006.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhou Y, Zhao W, Zhu Y, Liu H, Sun Y, Gong Z, Li X, Liu Z, Wen K, Wang Y, et al: CXCL13 Expression Promotes CAR T Cell Antitumor Activity and Potentiates Response to PD-1 Blockade. \u003cem\u003eAdvanced science\u003c/em\u003e 2025:e08095.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOdorizzi PM, Pauken KE, Paley MA, Sharpe A, Wherry EJ: Genetic absence of PD-1 promotes accumulation of terminally differentiated exhausted CD8\u0026thinsp;+\u0026thinsp;T cells. \u003cem\u003eThe Journal of experimental medicine\u003c/em\u003e 2015, 212:1125\u0026ndash;1137.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChen Y, Sun C, Landoni E, Metelitsa L, Dotti G, Savoldo B: Eradication of Neuroblastoma by T Cells Redirected with an Optimized GD2-Specific Chimeric Antigen Receptor and Interleukin-15. \u003cem\u003eClinical cancer research: an official journal of the American Association for Cancer Research\u003c/em\u003e 2019, 25:2915\u0026ndash;2924.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKrenciute G, Prinzing BL, Yi Z, Wu MF, Liu H, Dotti G, Balyasnikova IV, Gottschalk S: Transgenic Expression of IL15 Improves Antiglioma Activity of IL13Ralpha2-CAR T Cells but Results in Antigen Loss Variants. \u003cem\u003eCancer immunology research\u003c/em\u003e 2017, 5:571\u0026ndash;581.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBatra SA, Rathi P, Guo L, Courtney AN, Fleurence J, Balzeau J, Shaik RS, Nguyen TP, Wu MF, Bulsara S, et al: Glypican-3-Specific CAR T Cells Coexpressing IL15 and IL21 Have Superior Expansion and Antitumor Activity against Hepatocellular Carcinoma. \u003cem\u003eCancer immunology research\u003c/em\u003e 2020, 8:309\u0026ndash;320.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSindaco P, Pandey H, Isabelle C, Chakravarti N, Brammer JE, Porcu P, Mishra A: The role of interleukin-15 in the development and treatment of hematological malignancies. \u003cem\u003eFrontiers in immunology\u003c/em\u003e 2023, 14:1141208.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhao B, Wang Y, Tan X, Zheng X, Wang F, Ke K, Zhang C, Liao N, Dang Y, Shi Y, et al: An Optogenetic Controllable T Cell System for Hepatocellular Carcinoma Immunotherapy. \u003cem\u003eTheranostics\u003c/em\u003e 2019, 9:1837\u0026ndash;1850.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSmole A, Benton A, Poussin MA, Eiva MA, Mezzanotte C, Camisa B, Greco B, Sharma P, Minutolo NG, Gray F, et al: Expression of inducible factors reprograms CAR-T cells for enhanced function and safety. \u003cem\u003eCancer cell\u003c/em\u003e 2022, 40:1470\u0026ndash;1487 e1477.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTristan-Manzano M, Maldonado-Perez N, Justicia-Lirio P, Cortijo-Gutierrez M, Tristan-Ramos P, Blanco-Benitez C, Pavlovic K, Aguilar-Gonzalez A, Munoz P, Molina-Estevez FJ, et al: Lentiviral vectors for inducible, transactivator-free advanced therapy medicinal products: Application to CAR-T cells. \u003cem\u003eMolecular therapy Nucleic acids\u003c/em\u003e 2023, 32:322\u0026ndash;339.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSachdeva M, Busser BW, Temburni S, Jahangiri B, Gautron AS, Marechal A, Juillerat A, Williams A, Depil S, Duchateau P, et al: Repurposing endogenous immune pathways to tailor and control chimeric antigen receptor T cell functionality. \u003cem\u003eNature communications\u003c/em\u003e 2019, 10:5100.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang J, Hu Y, Yang J, Li W, Zhang M, Wang Q, Zhang L, Wei G, Tian Y, Zhao K, et al: Non-viral, specifically targeted CAR-T cells achieve high safety and efficacy in B-NHL. \u003cem\u003eNature\u003c/em\u003e 2022, 609:369\u0026ndash;374.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWaldmann TA, Dubois S, Miljkovic MD, Conlon KC: IL-15 in the Combination Immunotherapy of Cancer. \u003cem\u003eFrontiers in immunology\u003c/em\u003e 2020, 11:868.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSharpe AH, Pauken KE: The diverse functions of the PD1 inhibitory pathway. \u003cem\u003eNature reviews Immunology\u003c/em\u003e 2018, 18:153\u0026ndash;167.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWatkinson F, Nayar SK, Rani A, Sakellariou CA, Elhage O, Papaevangelou E, Dasgupta P, Galustian C: IL-15 Upregulates Telomerase Expression and Potently Increases Proliferative Capacity of NK, NKT-Like, and CD8 T Cells. \u003cem\u003eFrontiers in immunology\u003c/em\u003e 2020, 11:594620.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBriukhovetska D, Dorr J, Endres S, Libby P, Dinarello CA, Kobold S: Interleukins in cancer: from biology to therapy. \u003cem\u003eNature reviews Cancer\u003c/em\u003e 2021, 21:481\u0026ndash;499.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTristan-Manzano M, Maldonado-Perez N, Justicia-Lirio P, Munoz P, Cortijo-Gutierrez M, Pavlovic K, Jimenez-Moreno R, Nogueras S, Carmona MD, Sanchez-Hernandez S, et al: Physiological lentiviral vectors for the generation of improved CAR-T cells. \u003cem\u003eMolecular therapy oncolytics\u003c/em\u003e 2022, 25:335\u0026ndash;349.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCastella M, Caballero-Banos M, Ortiz-Maldonado V, Gonzalez-Navarro EA, Sune G, Antonana-Vidosola A, Boronat A, Marzal B, Millan L, Martin-Antonio B, et al: Point-Of-Care CAR T-Cell Production (ARI-0001) Using a Closed Semi-automatic Bioreactor: Experience From an Academic Phase I Clinical Trial. \u003cem\u003eFrontiers in immunology\u003c/em\u003e 2020, 11:482.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTurchiano G, Andrieux G, Klermund J, Blattner G, Pennucci V, El Gaz M, Monaco G, Poddar S, Mussolino C, Cornu TI, et al: Quantitative evaluation of chromosomal rearrangements in gene-edited human stem cells by CAST-Seq. \u003cem\u003eCell stem cell\u003c/em\u003e 2021, 28:1136\u0026ndash;1147 e1135.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRhiel M, Geiger K, Andrieux G, Rositzka J, Boerries M, Cathomen T, Cornu TI: T-CAST: An optimized CAST-Seq pipeline for TALEN confirms superior safety and efficacy of obligate-heterodimeric scaffolds. \u003cem\u003eFrontiers in genome editing\u003c/em\u003e 2023, 5:1130736.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLivak KJ, Schmittgen TD: Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. \u003cem\u003eMethods\u003c/em\u003e 2001, 25:402\u0026ndash;408.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEwels P, Magnusson M, Lundin S, Kaller M: MultiQC: summarize analysis results for multiple tools and samples in a single report. \u003cem\u003eBioinformatics\u003c/em\u003e 2016, 32:3047\u0026ndash;3048.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi B, Dewey CN: RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. \u003cem\u003eBMC bioinformatics\u003c/em\u003e 2011, 12:323.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M, Gingeras TR: STAR: ultrafast universal RNA-seq aligner. \u003cem\u003eBioinformatics\u003c/em\u003e 2013, 29:15\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRitchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, Smyth GK: limma powers differential expression analyses for RNA-sequencing and microarray studies. \u003cem\u003eNucleic acids research\u003c/em\u003e 2015, 43:e47.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSubramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES, Mesirov JP: Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. \u003cem\u003eProceedings of the National Academy of Sciences of the United States of America\u003c/em\u003e 2005, 102:15545\u0026ndash;15550.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiberzon A, Birger C, Thorvaldsdottir H, Ghandi M, Mesirov JP, Tamayo P: The Molecular Signatures Database (MSigDB) hallmark gene set collection. \u003cem\u003eCell systems\u003c/em\u003e 2015, 1:417\u0026ndash;425.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCortijo-Gutierrez M, Sanchez-Hernandez S, Tristan-Manzano M, Maldonado-Perez N, Lopez-Onieva L, Real PJ, Herrera C, Marchal JA, Martin F, Benabdellah K: Improved Functionality of Integration-Deficient Lentiviral Vectors (IDLVs) by the Inclusion of IS(2) Protein Docks. \u003cem\u003ePharmaceutics\u003c/em\u003e 2021, 13.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMaldonado-Perez N, Tristan-Manzano M, Justicia-Lirio P, Martinez-Planes E, Munoz P, Pavlovic K, Cortijo-Gutierrez M, Blanco-Benitez C, Castella M, Juan M, et al: Efficacy and safety of universal (TCRKO) ARI-0001 CAR-T cells for the treatment of B-cell lymphoma. \u003cem\u003eFrontiers in immunology\u003c/em\u003e 2022, 13:1011858.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePavlovic K, Carmona-Luque M, Corsi GI, Maldonado-Perez N, Molina-Estevez FJ, Peralbo-Santaella E, Cortijo-Gutierrez M, Justicia-Lirio P, Tristan-Manzano M, Ronco-Diaz V, et al: Generating universal anti-CD19 CAR T cells with a defined memory phenotype by CRISPR/Cas9 editing and safety evaluation of the transcriptome. \u003cem\u003eFrontiers in immunology\u003c/em\u003e 2024, 15:1401683.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDolina JS, Van Braeckel-Budimir N, Thomas GD, Salek-Ardakani S: CD8(+) T Cell Exhaustion in Cancer. \u003cem\u003eFrontiers in immunology\u003c/em\u003e 2021, 12:715234.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEyquem J, Mansilla-Soto J, Giavridis T, van der Stegen SJ, Hamieh M, Cunanan KM, Odak A, Gonen M, Sadelain M: Targeting a CAR to the TRAC locus with CRISPR/Cas9 enhances tumour rejection. \u003cem\u003eNature\u003c/em\u003e 2017, 543:113\u0026ndash;117.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDing H, Wu Y: CAR-T Therapy in Relapsed Refractory Multiple Myeloma. \u003cem\u003eCurrent medicinal chemistry\u003c/em\u003e 2024, 31:4362\u0026ndash;4382.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAparicio-Perez C, Carmona M, Benabdellah K, Herrera C: Failure of ALL recognition by CAR T cells: a review of CD 19-negative relapses after anti-CD 19 CAR-T treatment in B-ALL. \u003cem\u003eFrontiers in immunology\u003c/em\u003e 2023, 14:1165870.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMaalej KM, Merhi M, Inchakalody VP, Mestiri S, Alam M, Maccalli C, Cherif H, Uddin S, Steinhoff M, Marincola FM, Dermime S: CAR-cell therapy in the era of solid tumor treatment: current challenges and emerging therapeutic advances. \u003cem\u003eMolecular cancer\u003c/em\u003e 2023, 22:20.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYin S, Chen Z, Chen D, Yan D: Strategies targeting PD-L1 expression and associated opportunities for cancer combination therapy. \u003cem\u003eTheranostics\u003c/em\u003e 2023, 13:1520\u0026ndash;1544.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZou W, Luo X, Gao M, Yu C, Wan X, Yu S, Wu Y, Wang A, Fenical W, Wei Z, et al: Optimization of cancer immunotherapy on the basis of programmed death ligand-1 distribution and function. \u003cem\u003eBritish journal of pharmacology\u003c/em\u003e 2023.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChong EA, Melenhorst JJ, Lacey SF, Ambrose DE, Gonzalez V, Levine BL, June CH, Schuster SJ: PD-1 blockade modulates chimeric antigen receptor (CAR)-modified T cells: refueling the CAR. \u003cem\u003eBlood\u003c/em\u003e 2017, 129:1039\u0026ndash;1041.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRafiq S, Yeku OO, Jackson HJ, Purdon TJ, van Leeuwen DG, Drakes DJ, Song M, Miele MM, Li Z, Wang P, et al: Targeted delivery of a PD-1-blocking scFv by CAR-T cells enhances anti-tumor efficacy in vivo. \u003cem\u003eNature biotechnology\u003c/em\u003e 2018, 36:847\u0026ndash;856.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSailer CJ, Hong Y, Dahal A, Ryan AT, Mir S, Gerber SA, Reagan PM, Kim M: PD-1(Hi) CAR-T cells provide superior protection against solid tumors. \u003cem\u003eFrontiers in immunology\u003c/em\u003e 2023, 14:1187850.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAndreu-Saumell I, Rodriguez-Garcia A, Muhlgrabner V, Gimenez-Alejandre M, Marzal B, Castellsague J, Braso-Maristany F, Calderon H, Angelats L, Colell S, et al: CAR affinity modulates the sensitivity of CAR-T cells to PD-1/PD-L1-mediated inhibition. \u003cem\u003eNature communications\u003c/em\u003e 2024, 15:3552.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKalinin RS, Ukrainskaya VM, Chumakov SP, Moysenovich AM, Tereshchuk VM, Volkov DV, Pershin DS, Maksimov EG, Zhang H, Maschan MA, et al: Engineered Removal of PD-1 From the Surface of CD19 CAR-T Cells Results in Increased Activation and Diminished Survival. \u003cem\u003eFrontiers in molecular biosciences\u003c/em\u003e 2021, 8:745286.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWei SC, Anang NAS, Sharma R, Andrews MC, Reuben A, Levine JH, Cogdill AP, Mancuso JJ, Wargo JA, Pe'er D, Allison JP: Combination anti-CTLA-4 plus anti-PD-1 checkpoint blockade utilizes cellular mechanisms partially distinct from monotherapies. \u003cem\u003eProceedings of the National Academy of Sciences of the United States of America\u003c/em\u003e 2019, 116:22699\u0026ndash;22709.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJiang X, Wang J, Deng X, Xiong F, Ge J, Xiang B, Wu X, Ma J, Zhou M, Li X, et al: Role of the tumor microenvironment in PD-L1/PD-1-mediated tumor immune escape. \u003cem\u003eMolecular cancer\u003c/em\u003e 2019, 18:10.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMarkham A, Keam SJ: Camrelizumab: First Global Approval. \u003cem\u003eDrugs\u003c/em\u003e 2019, 79:1355\u0026ndash;1361.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChamberlain CA, Bennett EP, Kverneland AH, Svane IM, Donia M, Met O: Highly efficient PD-1-targeted CRISPR-Cas9 for tumor-infiltrating lymphocyte-based adoptive T cell therapy. \u003cem\u003eMolecular therapy oncolytics\u003c/em\u003e 2022, 24:417\u0026ndash;428.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWartewig T, Daniels J, Schulz M, Hameister E, Joshi A, Park J, Morrish E, Venkatasubramani AV, Cernilogar FM, van Heijster FHA, et al: PD-1 instructs a tumor-suppressive metabolic program that restricts glycolysis and restrains AP-1 activity in T cell lymphoma. \u003cem\u003eNature cancer\u003c/em\u003e 2023.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChamoto K, Chowdhury PS, Kumar A, Sonomura K, Matsuda F, Fagarasan S, Honjo T: Mitochondrial activation chemicals synergize with surface receptor PD-1 blockade for T cell-dependent antitumor activity. \u003cem\u003eProceedings of the National Academy of Sciences of the United States of America\u003c/em\u003e 2017, 114:E761-E770.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChowdhury PS, Chamoto K, Kumar A, Honjo T: PPAR-Induced Fatty Acid Oxidation in T Cells Increases the Number of Tumor-Reactive CD8(+) T Cells and Facilitates Anti-PD-1 Therapy. \u003cem\u003eCancer immunology research\u003c/em\u003e 2018, 6:1375\u0026ndash;1387.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFlati I, Di Vito Nolfi M, Dall'Aglio F, Vecchiotti D, Verzella D, Alesse E, Capece D, Zazzeroni F: Molecular Mechanisms Underpinning Immunometabolic Reprogramming: How the Wind Changes during Cancer Progression. \u003cem\u003eGenes\u003c/em\u003e 2023, 14.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJung JG, Le A: Targeting Metabolic Cross Talk Between Cancer Cells and Cancer-Associated Fibroblasts. \u003cem\u003eAdvances in experimental medicine and biology\u003c/em\u003e 2021, 1311:205\u0026ndash;214.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJung JG, Le A: Metabolism of Immune Cells in the Tumor Microenvironment. \u003cem\u003eAdvances in experimental medicine and biology\u003c/em\u003e 2021, 1311:173\u0026ndash;185.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMa S, Han J, Li Z, Xiao S, Zhang J, Yan J, Tang T, Barr T, Kraft AS, Caligiuri MA, Yu J: An XBP1s-PIM-2 positive feedback loop controls IL-15-mediated survival of natural killer cells. \u003cem\u003eScience immunology\u003c/em\u003e 2023, 8:eabn7993.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang Y, Zhang Y, Yi P, Dong W, Nalin AP, Zhang J, Zhu Z, Chen L, Benson DM, Mundy-Bosse BL, et al: The IL-15-AKT-XBP1s signaling pathway contributes to effector functions and survival in human NK cells. \u003cem\u003eNature immunology\u003c/em\u003e 2019, 20:10\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWaldmann TA, Miljkovic MD, Conlon KC: Interleukin-15 (dys)regulation of lymphoid homeostasis: Implications for therapy of autoimmunity and cancer. \u003cem\u003eThe Journal of experimental medicine\u003c/em\u003e 2020, 217.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAtaca Atilla P, McKenna MK, Tashiro H, Srinivasan M, Mo F, Watanabe N, Simons BW, McLean Stevens A, Redell MS, Heslop HE, et al: Modulating TNFalpha activity allows transgenic IL15-Expressing CLL-1 CAR T cells to safely eliminate acute myeloid leukemia. \u003cem\u003eJournal for immunotherapy of cancer\u003c/em\u003e 2020, 8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXu A, Bhanumathy KK, Wu J, Ye Z, Freywald A, Leary SC, Li R, Xiang J: IL-15 signaling promotes adoptive effector T-cell survival and memory formation in irradiation-induced lymphopenia. \u003cem\u003eCell \u0026amp; bioscience\u003c/em\u003e 2016, 6:30.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYe J, Liu Q, He Y, Song Z, Lin B, Hu Z, Hu J, Ning Y, Cai C, Li Y: Combined therapy of CAR-IL-15/IL-15Ralpha-T cells and GLIPR1 knockdown in cancer cells enhanced anti-tumor effect against gastric cancer. \u003cem\u003eJournal of translational medicine\u003c/em\u003e 2024, 22:171.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGoswami R, Kaplan MH: STAT Transcription Factors in T Cell Control of Health and Disease. \u003cem\u003eInternational review of cell and molecular biology\u003c/em\u003e 2017, 331:123\u0026ndash;180.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSkariah N, James OJ, Swamy M: Signalling mechanisms driving homeostatic and inflammatory effects of interleukin-15 on tissue lymphocytes. \u003cem\u003eDiscovery immunology\u003c/em\u003e 2024, 3:kyae002.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang S, Zhao J, Bai X, Handley M, Shan F: Biological effects of IL-15 on immune cells and its potential for the treatment of cancer. \u003cem\u003eInternational immunopharmacology\u003c/em\u003e 2021, 91:107318.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGuo Y, Luan L, Patil NK, Sherwood ER: Immunobiology of the IL-15/IL-15Ralpha complex as an antitumor and antiviral agent. \u003cem\u003eCytokine \u0026amp; growth factor reviews\u003c/em\u003e 2017, 38:10\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAlizadeh D, Wong RA, Yang X, Wang D, Pecoraro JR, Kuo CF, Aguilar B, Qi Y, Ann DK, Starr R, et al: IL15 Enhances CAR-T Cell Antitumor Activity by Reducing mTORC1 Activity and Preserving Their Stem Cell Memory Phenotype. \u003cem\u003eCancer immunology research\u003c/em\u003e 2019, 7:759\u0026ndash;772.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMollavelioglu B, Cetin Aktas E, Cabioglu N, Abbasov A, Onder S, Emiroglu S, Tukenmez M, Muslumanoglu M, Igci A, Deniz G, Ozmen V: High co-expression of immune checkpoint receptors PD-1, CTLA-4, LAG-3, TIM-3, and TIGIT on tumor-infiltrating lymphocytes in early-stage breast cancer. \u003cem\u003eWorld journal of surgical oncology\u003c/em\u003e 2022, 20:349.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"genome-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Genome Medicine](https://genomemedicine.biomedcentral.com/)","snPcode":"13073","submissionUrl":"https://submission.springernature.com/new-submission/13073/3","title":"Genome Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"CAR-T, PD-1, PD-1KIL-15, IL-15, Gene editing, AAV6, CRISPR/Cas9, inducible expression, TME, TRUCKs, physiological expression, safe harbour","lastPublishedDoi":"10.21203/rs.3.rs-7012598/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7012598/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAdoptive cell therapy (ACT) with genetically engineered T cells expressing chimeric antigen receptors (CARs) has emerged as a promising treatment option for patients with refractory leukaemia or lymphoma. Despite its success in type B malignancies, CAR-T cell therapy still faces some challenges such as toxicity, functional suppression by the tumour microenvironment (TME), and poor persistence in treated patients.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study employed a second-generation CD19-targeting CAR construct to generate engineered CAR-T cells with enhanced functionality through precise genome editing. Using CRISPR/Cas9 technology, the PDCD1 gene was to mitigate T cell exhaustion, and in a parallel knock-in strategy, an IL-15 transgene was inserted at the PDCD1 locus. Gene editing was performed via electroporation of RNP complexes, with AAV6 vectors used for homology-directed IL-15 integration. Editing efficiency and off-target activity were assessed by flow cytometry, Sanger sequencing, ICE, and CAST-Seq.\u0026nbsp;Functional characterization included bulk RNA sequencing, metabolic profiling using Seahorse technology, and cytotoxicity assays against CD19\u003csup\u003e+\u003c/sup\u003e target cells.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe initially demonstrated that αCD19 CAR-T cells lacking PD-1 expression (PD-1 KO) exhibited reduced expansion capacity and overall fitness compared to control CAR-T cells but showed a superior cytotoxicity against PDL1\u003csup\u003e+\u003c/sup\u003e target cells. To address the impaired fitness of PD-1 KO CAR-T cells, we generated PD-1KIL-15 CAR-T cells, which combine PD-1 KO with the expression of IL-15 under the control of the PD-1 endogenous promoter. Compared to CAR T PD-1 KO cells, PD-1KIL-15 CAR-T cells displayed improved phenotype, viability, and metabolism. More importantly, they also demonstrated enhanced cytolytic capacity of PDL1\u003csup\u003e+\u003c/sup\u003e CD19\u0026thinsp;+\u0026thinsp;target cells, which correlated with increased resistance to apoptosis and improved cell fitness.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn summary, we present a next 4th generation CAR-T cells platform (TRUCKs) that integrates PD-1 deletion with the inducible expression of IL-15 upon T cell activation and/or exhaustion. This strategy addresses the limitations associated with \u003cem\u003eknocking-out\u003c/em\u003e PD-1 and those associated with sustained IL-15 cytokine expression. The same platform can be used to generate PD-1 KO TRUCKs targeting different antigens and expressing different cytokines under the control of the PD-1 locus.\u003c/p\u003e","manuscriptTitle":"Development of a Gene Editing Platform to Enhance CAR-T Therapy Through Inducible IL-15 Expression at the PD-1 Locus","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-23 08:17:04","doi":"10.21203/rs.3.rs-7012598/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-31T20:20:40+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-06T15:49:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"154385305965230698058736790555913170414","date":"2025-08-09T15:10:54+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-02T20:46:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"197943146130719344111786814656590103002","date":"2025-07-21T18:18:02+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-16T19:59:46+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-09T13:27:59+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-01T06:36:46+00:00","index":"","fulltext":""},{"type":"submitted","content":"Genome Medicine","date":"2025-06-30T16:04:10+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"genome-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Genome Medicine](https://genomemedicine.biomedcentral.com/)","snPcode":"13073","submissionUrl":"https://submission.springernature.com/new-submission/13073/3","title":"Genome Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3a30e41f-93b5-42c0-9c3f-bcf266e9146d","owner":[],"postedDate":"July 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2025-10-31T20:23:25+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-23 08:17:04","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7012598","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7012598","identity":"rs-7012598","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}