GPX4 and FSP1, key ferroptosis regulators, are critical for T cell functions and CAR-T antitumor activity

GPX4 and FSP1, key ferroptosis regulators, are critical for T cell functions and CAR-T antitumor activity | 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 Article GPX4 and FSP1, key ferroptosis regulators, are critical for T cell functions and CAR-T antitumor activity Malgorzata Bajor, Marta Kłopotowska, Iwona Baranowska, Szymon Hajduk, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5280443/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Induction of ferroptosis, an iron-dependent form of regulated cell death, holds promise as a strategy to overcome tumor resistance to conventional therapies and enhance immunotherapy responses. However, while the susceptibility of tumor cells to ferroptosis is extensively studied, limited data exists on the vulnerability of immune cells to disturbed iron balance and lipid peroxidation. Here, we found that T cell stimulation rewires iron and redox homeostasis and by increasing levels of reactive oxygen species and labile iron promotes lipid peroxidation and T cells’ ferroptosis. Upon stimulation, we detected substantial changes in the balance of ferroptosis-suppressive proteins, including GPX4 decrease and increase of FSP1, a phenomenon never described before. Subsequently, we identified GPX4 as a master regulator orchestrating T/CAR-T cells’ sensitivity to ferroptosis and demonstrated that GPX4 inhibitors impair T/CAR-T cells’ functions. Surprisingly, we observed that FSP1 regulates T cell antitumor activity independently of its ferroptosis-suppressive function. Specifically, FSP1 inhibition decreased oxidative phosphorylation and mitochondrial ATP production, reduced the amount of perforin and cytokines produced by T cells, and suppressed their proliferation. Altogether, our study for the first time indicates that GPX4 and FSP1, key regulators of ferroptosis, are critical for the antitumor cytotoxic potential of T/CAR-T cells. From our study FSP1 also emerges as a novel metabolic regulator in T cells, which inhibition profoundly affects T cells’ oxidative phosphorylation. Our findings are not only significant to understand metabolic vulnerabilities of T cells but may also hold particular significance from the standpoint of therapeutic development. In the context of our results, future anticancer therapies should be carefully designed to selectively induce ferroptosis of tumor cells without impeding cytotoxic cells’ antitumor efficacy. Biological sciences/Immunology/Cell death and immune response Biological sciences/Cancer/Cancer microenvironment Biological sciences/Immunology/Lymphocytes/T cells ferroptosis T cells chimeric antigen receptor GPX4 FSP1 lipid metabolism immunotherapy Figures Figure 1 Figure 2 Figure 3 Introduction Ferroptosis has gathered increased attention as a promising anticancer strategy [1–4]. It has been shown that manipulating lipid metabolism or redox balance can induce ferroptosis in various cancer types, including both solid tumors and hematological malignancies [5–8]. Ferroptosis is a free radical-mediated process that results in iron-dependent excessive oxidation and subsequent degradation of lipids containing polyunsaturated fatty acids (PUFA) [9]. In addition to an increased peroxidation of lipids in the cell membrane and an accumulation of labile iron pool inside the cell, ferroptosis is characterized by changes in the redox state, leading to increased production of reactive oxygen species (ROS) and a concomitant impairment of the cell's antioxidant defense systems [10]. To prevent excessive ferroptosis induction cells activate cyst(e)ine–glutathione (GSH)–glutathione peroxidase 4 (GPX4) axis as a key defense system. Recently however, ferroptosis suppressor protein 1 (FSP1)/coenzyme Q10 (CoQ10) has been identified as the second ferroptosis-suppressing system, which efficiently prevents lipid peroxidation independently of GPX4 [11]. While ferroptosis of tumor cells is widely studied, the effects of ferroptosis on immune cells, particularly in the tumor microenvironment (TME), still remain poorly understood. Recent evidence suggests that neutrophils within tumors can undergo spontaneous ferroptosis, suppressing T cell activity [12], while those at metastatic sites upregulate of ferroptosis-related genes, potentially indicating a defensive mechanism against ferroptosis. Notably, T cells are more prone to ferroptosis than neutrophils, as evidenced by lipidomic studies [13]. It has been also reported that T cells lacking GPX4 fail to expand and function upon activation and undergo ferroptosis [14]. GPX4 has been shown to control lipid oxidation to support T cell responses during viral infections [14]. Furthermore, in the TME, cystine consumption by tumor cells disrupts the cystine/glutamate exchange in CD8 + T cells, leading to increased CD36 expression, fatty acids uptake, lipid accumulation, abnormal ROS production, and ultimately T cell exhaustion and ferroptosis [15–17]. Consistently, blocking CD36-induced ferroptosis, in combination with immune checkpoint inhibitors, has been shown to enhance CD8 + T cell anticancer activity [16]. On the other hand, CD8 + T cells have been shown to promote ferroptosis in tumor cells by secreting interferon-γ (IFNγ) [18]. While T cells are critical for mounting the antitumor response, the metabolic requirements for maintenance and execution of effector functions are less well studied. These may be particularly important in the context of their antitumor activity, where T cells are first stimulated before interacting with cancer cells within the tumor niche [19]. Therefore, we addressed this issue and demonstrated that T cell stimulation affects the balance between processes that promote and protect against ferroptosis, thereby disrupting T cell homeostasis. Specifically, we observed a significant decrease in GPX4 expression and a corresponding increase in FSP1 protein levels following T cell stimulation. Our findings revealed that both T cells and CAR-T cells are susceptible to ferroptosis, with GPX4 inhibition reducing their antitumor responses. Although very effective in hematological malignancies, CAR-T therapy still faces several obstacles in eliminating solid tumors. One reason for this is the hostile, immunosuppressive tumor microenvironment (TME), characterized by chronic oxidative stress, that contributes to mitochondrial dysfunction, lipid peroxidation, and impaired antioxidant defense systems, all of which are metabolic features characteristic of ferroptosis. In this context, we show that inhibition of ferroptosis with liproxstatin 1 (Lip-1) protects CAR-T cells and improves the effective eradication of cancer cells, both in vitro and in vivo . One of our unexpected results was the identification of FSP1 as a novel regulator of T cell and CAR-T cell metabolism, proliferation, and antitumor efficacy, operating independently of its role in ferroptosis suppression. Overall, our findings unveil a novel role for the ferroptosis-related proteins GPX4 and FSP1 in enhancing the cytotoxic potential of T cells against tumors. These mechanisms can operate through ferroptosis-dependent and -independent pathways, underscoring the complexity of ferroptosis regulation in cytotoxic cells. Materials and methods Cell lines Raji and MCF7 cell lines were purchased from ATCC or the European Collection of Cell Cultures (Wiltshire, UK). The cells were cultured in RPMI-1640 medium (Sigma-Aldrich, St Louis, MO, USA) supplemented with 10% fetal bovine serum (FBS) (Sigma-Aldrich), 2 mM L-glutamine (Sigma-Aldrich) and 1% antibiotics – penicillin/streptomycin (Sigma-Aldrich) (referred as full RPMI medium) in a humidified atmosphere containing 5% CO 2 . All the cell lines were maintained through continuous passaging and were confirmed to be free of contamination with Mycoplasma spp. For luciferase-based assays cell lines (Raji and MCF7) were modified with plasmid pLenti7.3/V5 TOPO-RedLuc encoding the red luciferase gene and green fluorescent protein, as described previously [20]. Reagents All tested compounds GPX4 inhibitors: RSL3 (Selleckchem, S8155) and ML162 (Merck, SML2561), iFSP1 (Selleckchem, S9663), liproxstatin-1 (Merck, SML1414), liproxstatin-1 for in vivo experiments (Chem-Norm, TBW04068), Z-VAD-FMK (Selleckchem, S7023), necrostatin-1 (Sigma, N9037) were dissolved in DMSO to obtain 10 mM stock solutions and kept at -20 or -80°C according to manufacturer’s recommendations. Further dilutions were performed in culture medium, directly before each experiment. Deferoxamine (Desferal, Novartis leftovers donated by patients) was dissolved in dH 2 O and was kept at -20°C. T cell isolation and stimulation Human primary T cells were isolated from buffy coats of healthy donors obtained from the Regional Blood Center in Warsaw, Poland, with the knowledge of the Bioethics Committee at the Central Clinical Hospital of the Ministry of Interior and Administration in Warsaw (approved on 12/10/2022). Initially, mononuclear cells were isolated by density gradient centrifugation using Lymphoprep (STEMCELL Technologies Canada, Inc.). Subsequently, T cells were magnetically separated from mononuclear cells with negative selection using EasySep™ Human T Cell Isolation Kit (STEMCELL Technologies Canada, Inc.). T cells were stimulated with the magnetic beads coated with monoclonal antibodies against CD3 and CD28 molecules (Dynabeads Human T-Activator CD3/CD28, Thermo Fisher Scientific) and were cultured in full RPMI medium supplemented with 100 U/mL of IL-2 (Peprotech). After 5 days the beads were removed and T cells were further cultured in the presence of IL-2 only. T cell viability assays Unstimulated T cells, stimulated T cells or CAR-T cells were treated with tested compounds for an indicated time, 24 or 48 h. Subsequently, the viability of the cells was assessed by propidium iodide (PI, 1 µg/mL, Sigma-Aldrich) staining, followed by flow cytometry analysis BD FACSCantoII and HTS sampler. T cell proliferation assay Human primary T cells were resuspended in PBS (1 × 10 6 /ml) and stained with Cell Trace Violet (CTV) dye (Thermo Fisher Scientific) for 20 min at 37°C at a final CTV concentration of 2.5 µM. Subsequently, T cells were washed and seeded onto a 96-round-bottom plate (2 × 10 4 cells per well) in full RPMI medium in the presence of IL-2 (100 U/mL), Dynabeads Human T-Activator CD3/CD28 (beads to cell ratio 2:1) and increasing concentrations of iFSP1 or RSL3 with or without Lip-1. After 3 and 6 days of incubation, the T cells were stained with DRAQ7 viability stain (BioLegend) and analyzed on BD FACSCantoII and HTS sampler. Flow cytometry staining Extracellular staining for surface antigen was performed in a staining buffer (PBS supplemented with 1mM EDTA and 2% FBS) for 20 min at room temperature onto a 96-round-bottom plate. For intracellular staining, the cells were fixed with BD Cytofix buffer, permeabilized with BD Perm/Wash buffer and stained at 4°C for 30 min. Next, cells were washed in Perm/Wash buffer, resuspended in staining buffer and analyzed with BD FACSCantoII and HTS sampler. Antibodies used for staining are listed in Table 1 . Table 1 Flow cytometry antibodies Antibody Fluorochrome Catalog number Company CD71 (transferrin receptor) antibody APC 17-0719-42 Invitrogen Ferroportin/SLC40A1 antibody PE NBP1-21502PE Novus Biologicals CD340 (erbB2/HER-2) antibody APC 324408 BioLegend goat anti-human IgG, Fcγ fragment specific antibody AF647 109-606-098 Jackson ImmunoResearch Labs Lipid peroxidation assay Lipid peroxidation was evaluated in T cells either at a steady state or following RSL3 treatment using the fluorescent lipid peroxidation sensor named BODIPY 581/591 C11 (ThermoFisher). Briefly, T cells were seeded onto a 96-round-bottom plate at cell density 1 × 10 6 /ml and incubated with increasing concentrations of RSL3 in the presence or absence of Lip-1 for 20 h. The next day, T cells were centrifuged and resuspended in full RPMI medium containing 0.5 µM BODIPY 581/591 C11 reagent (100 µl/well) and incubated at 37°C for 30 min. Subsequently, the cells were washed three times and analyzed on BD FACSCantoII and HTS sampler. The level of lipid ROS was assessed as an increase in oxidized C11-BODIPY (green fluorescence). Labile iron pool detection Intracellular Fe 2+ level was evaluated with the fluorescent probe FerroOrange (Dojindo). The cells were seeded onto a 96-round-bottom plate at cell number 2 × 10 5 /well, washed three times with PBS, and then resuspended in HBSS buffer. In experiments with deferoxamine pretreatment, the cells were preincubated with 1 mM or 2 mM deferoxamine and incubated for 30 min at 37°C. Subsequently, 2 times concentrated FerroOrange probe was added to the wells at a final concentration of 1 µM and incubated for 30 min at 37°C. After incubation, cells were analyzed without washing on a BD LSRFortessa X20 instrument (BD Biosciences) and PE channel. Intracellular ROS detection Intracellular ROS were determined with fluorescent probes CellROX Deep Red and CellROX Green (Thermo Fisher Scientific). Briefly, T cells were seeded onto a 96-round-bottom plate at the density of 5 × 10 5 cells/mL and incubated with the CellROX Deep Red or CellROX Green reagent at 37°C, 5% CO 2 for 30 minutes. After washing, the cells were analyzed on a BD FACSCantoII flow cytometer (BD Biosciences). GSH detection To determine GSH level in T cells the Intracellular glutathione (GSH) Detection Assay Kit (ab112132) was applied. Briefly, T cells were seeded onto a 96-round-bottom plate at cell density 1 × 10 6 /ml and incubated with Thiol Green fluorescent probe (diluted 1:10000) for 30 min at 37°C. After incubation, the cells were washed and analyzed using flow cytometry and green fluorescence. CAR constructs and lentiviral T cell modification In this study, we utilized two CD19 CAR (FMC63 clone) constructs, generously provided by M. Pule from UCL, UK. The first construct includes the CD8 hinge and transmembrane domain, the 41BB costimulatory domain, the CD3ζ signaling domain, and the rituximab recognized-RQR8 epitope for CAR detection. The second CD19 CAR construct consists of the IgG1 half-hinge, the CD28 transmembrane and co-stimulatory domain, and CD3ζ. PD-L1-targeting CAR consists of an atezolizumab-based scFv sequence following an IgG1 half-hinge, CD28 transmembrane region, CD28 costimulatory domain, and CD3ζ signaling domain. HER2 CAR construct consists of a trastuzumab-based scFv sequence following a CD8 hinge and transmembrane domain and a 4-1BB-CD3ζ signaling tail. All constructs were subcloned into the lentiviral pSEW plasmid. T cells were modified with the CAR constructs using a lentiviral transduction system as described previously [21]. The CAR expression on the surface of the T cells was evaluated by flow cytometry 48–72 h after transduction as described in [21]. RTCA-based killing assay The HER2 CAR-mediated killing of T cells was monitored with a real-time cell analysis (RTCA) assay. Adherent target MCF7 cells (3 × 10 4 cells/well) were seeded onto 16-well E-Plate (ACEA Biosciences) in 150 µl of a full RPMI medium. The proliferation of MCF7 cells was monitored in the incubator at 37°C (5% CO 2 , 95% humidity) for 24 h with the xCELLigence impedance-based RTCA system (ACEA Biosciences). The next day, 100 µl of the medium was aspirated and replaced with the full RPMI medium containing effector cells (control unmodified T cells or HER2 CAR-T cells) at effector to target ratio E:T 2:1. T cells and CAR-T cells were pretreated with increasing concentrations of RSL3 for 5 h and transferred onto target cells without washing out the RSL3-containing medium. The CAR-mediated killing of target cells was monitored for the next 12 h. Analysis was performed using RTCA Software Pro (ACEA Biosciences). The impedance changes (cell index) were normalized to the end value of the target cells' proliferation and plotted over time as normalized cell index. Luciferase-based cytotoxicity assay Cell lines previously modified to express the luciferase reporter gene (Red-Luc), were seeded onto the 96-well black plates with a clear bottom (Perkin Elmer) at a cell density of 3 × 10 4 per well in 100 µl of full RPMI in three or four technical replicates. MCF-7 cells were allowed to adhere for 24 h while suspension Raji cells were directly used in the experimental procedures. For cytotoxicity assays, increasing concentrations of RSL3 or iFSP1 were added to the wells and the cells were incubated for 48 h. For luciferase-based killing assays, effector CAR-T cells and control unmodified T cells were added to the wells at different E:T ratios and were cocultured for the next 18 h. For bioluminescence readout Bright-Glo™ Luciferase Assay System (E2610, Promega) was used. The plate was incubated for 5 min in darkness at room temperature and luminescence was measured using Tecan INFINITE M1000 (TECAN). Flow cytometry-based killing assay PD-L1 CAR-T cells were pretreated with or without 20 µM iFSP1 for 48 h. For cytotoxicity assay, a target (Raji PD-L1) cells were stained with Cell Trace Violet (CTV) and seeded onto the 96-well plate at a cell density of 1 × 10 5 per well in 100 µl of full RPMI in two technical replicates. Next, PD-L1 CAR-T cells were added for 24 h at E:T ratios 0.25:1, 0.5:1 and 1:1. Propidium iodide (PI) was used to discriminate live/dead cells. Cytotoxicity of effector cells was evaluated as an increase in a percentage of violet-CTV positive, PI positive target cell population. Degranulation and cytokine production assay Before degranulation and cytokine production assay CAR-T cells were preincubated with either RSL3 for 16 h or iFSP1 for 24 h. The next day, tumor cells expressing recognized antigen on the surface were added to appropriate wells at E:T (effector to target) ratio 0.25:1 and 1:1. CD19 CAR-T cells were incubated with Burkitt’s lymphoma cell line Raji (CD19 + ), HER2 CAR-T cells with breast cancer cell line MCF7 (low HER2 + ) and PD-L1 CAR-T cells with Raji cells, genetically modified to overexpress PD-L1 molecule [21]. Subsequently, Golgi Stop (BD Biosciences, dilution 1:250), Golgi Plug (BD Biosciences, dilution 1:200) and anti-CD107a-PE antibody (BD Biosciences, dilution 1:40) were added and the assay plate was incubated for 4 h at 37°C and 5% CO 2 . After incubation, the cells were stained with anti-CD3-BV421 antibody and Fixable viability stain 510 (BD Biosciences, dilution 1:200) followed by fixation and permeabilization procedures. Eventually, the cells were stained for cytokines with anti-IFNy-APC (BD Biosciences, dilution 1:100) and anti-TNFα-PECy7 (BD Biosciences, dilution 1:100) antibodies. Degranulation and cytokine production by effector cells was assessed using flow cytometry. Seahorse analysis Cell metabolism was measured using Seahorse XF HS Mini Analyzer (Agilent). Seahorse analysis was performed on T cells and CAR-T cells pretreated with iFSP1. Stimulated T cells or CAR T cells were seeded onto a 24-well plate with 20 µM of iFSP1 and incubated for 48 h. iFSP pretreated T/CAR T cells were subsequently resuspended in Agilent Seahorse XF RPMI medium, pH 7.4 supplemented with Agilent Seahorse XF glucose (10 mM) and glutamine (2 mM) solutions and seeded at 2 × 10 5 cells/well onto Agilent Seahorse XFp PDL Cell Culture Miniplates. Metabolic parameters were measured under basal conditions upon treatment with oligomycin A (1.5 µM), BAM15 (2.5 µM) and rotenone/antimycin A (0.5 µM each) (Seahorse XF T Cell Metabolic Profiling Kit, Agilent). All steps were performed following the manufacturer’s recommendations. Western Blotting For Western blotting, cells were lysed with RIPA lysis buffer (Tris-HCL pH 7.4, NaCl 150 mM, NP-40 1% (v/v), sodium deoxycholate 1% (v/v), SDS 0.1% (v/v)) supplemented with Complete Protease Inhibitor Cocktail and Phosphatase Inhibitor Cocktail (Roche Diagnostics). Protein concentration was measured using the Pierce™ Rapid Gold BCA Protein Assay Kit (Thermo Fisher Scientific) according to the manufacturer's instructions with minor modifications on the TECAN Infinite M1000 Pro microplate reader. 20 µg of cell lysates were separated in 10, 12 or 15% (v/v) (depending on the molecular weight of detected protein) reducing SDS-polyacrylamide gel, then transferred onto nitrocellulose membranes and blocked with either 5% (w/v) nonfat milk or 5% Bovine Serum Albumin (w/v) (Kenilworth) in TBST (Tris-buffered saline, pH 7.4 and 0.05% (v/v) Tween-20) and then incubated with the following primary antibodies: anti-GPX4 (Cell Signaling cat. 52455S, dilution 1:1000), anti-FSP1 (Abcam cat. ab302673, dilution 1:1000), anti-ACSL4 (Santa Cruz cat. sc-271800, dilution 1:1000), anti-LOX15 (Abclonal cat. A6864, dilution 1:1000), anti-LC3 (Cell Signaling cat. 4108, dilution 1:1000), anti-perforin (MABTECH cat. Pf-344, dilution 1:1000), and anti-β-actin-HRP (A222, Sigma-Aldrich; dilution 1:50,000). For detection of primary protein bands HRP-conjugated secondary antibodies were used. The blots were exposed to the Super Signal chemiluminescent substrates (Thermo Fisher Scientific). The signal was detected using the ChemiDoc Imaging System (Bio-Rad ChemiDoc MP Imaging System). Animal studies All in vivo experiments were performed with 8–12-week old male NSG (NOD.Cg- Prkdc scid Il2rg tm1Wjl /SzJ) mice obtained from Charles River Laboratories, which were bred at the Animal Facility of the Mossakowski Medical Research Institute, Polish Academy of Sciences. All experiments were performed in accordance with the guidelines and approved by The Second Local Ethics Committee for the Animal Experimentation, Warsaw University of Life Sciences (number: WAW2/100/2023, WAW2/027/2024). The experiments were carried out in an SPF animal facility with IVC systems. To avoid confounders, all mice were labeled and kept in tagged cages. The cages had an assigned, unchanging place in the rack. Results obtained from individual mice according to the treatment method are presented. The blinding was not applied. The distribution of mice to the experimental groups was random and no animals were excluded during the experiment. The sample size was determined based on the assumed increase in tumor diameter. The experimental group size was calculated by power analysis (for assumed test power 80%) or resource equation approach as described in [22]. In vivo experiment Mice were inoculated subcutaneously with 2 × 10 6 Raji cells in 50% Matrigel Growth Factor Reduced (Corning) on day 0 of the experiment. Subsequently, on days 4, 7, 10, and 13, 5 × 10 6 CD19 CAR-T cells were administrated intravenously. Liproxstatin-1 (Chem-Norm) was injected intraperitoneally with 10 mg/kg every day or every other day for 2 consecutive weeks. Control mice received medium or solvent respectively. Tumor growth was monitored three times per week with caliper starting from day 7 of the experiment. Tumor volume was calculated according to the formula volume (mm 3 )= (width 2 [mm] × length [mm])/2. Mice were sacrificed when the tumor diameter reached 15 mm in at least one dimension. Total number of mice used within this study was 37. RNAseq and bioinformatics analysis RNAseq analysis was done using the dataset - GSE 59846, which comprises expression data for two cell types - CD4 + naïve and CD4 + memory T-cells, each derived from 3 individuals. Each cell type was additionally stimulated for 48 h using beads coated with monoclonal antibodies against the CD3 and CD28. Thus, 12 RNA-seq experiments were carried out; however, due to possible mislabeling of two runs - SRR1531315 and SRR1531316, we excluded them from the downstream analysis. Initially, we assessed library quality with FastQC [23] (v. 0.11.9). Next, trimmomatic [24] (v. 0.39) was used to trim fragments of reads from the 3’ and 5’ ends if their average quality fall below 30. Additionally, reads shorter than 40 bp were excluded at this stage. Processed reads were mapped to the human genome (GRCh38) using the align function available from the Rsubread package [25] (v. 2.12.3). Samtools [26] (v. 1.10) was used to remove unmapped reads. The number of reads associated with human genes, as defined in the Gencode GTF annotation file V40, was calculated using the featureCounts function from the Rsubread package and converted to counts per million (in log2 scale). The differential gene expression analysis was carried out using the limma program [27] (v. 3.54.2) for samples divided into two groups ‘stimulated’ or ‘unstimulated’ (Table 2 ). P-values were adjusted for multiple tests with the Benjamini–Hochberg procedure. All analyses were carried out in R (v. 4.2.2). Results of the statical test are shown as * for p-value ≤ 0.1, ** p-value ≤ 0.05; ***, p-value < 0.01. Table 2 Sample labelling in RNAseq reanalysis Sample ID Source name Activation Donor Final label SRR1531325 Memory CD4 T cell 48 h 5134 stimulated SRR1531324 Memory CD4 T cell 48 h 5009 stimulated SRR1531323 Memory CD4 T cell 0 h 5134 unstimulated SRR1531322 Memory CD4 T cell 0 h 5009 unstimulated SRR1531321 Naive CD4 T cell 48 h 5134 stimulated SRR1531320 Naive CD4 T cell 48 h 5009 stimulated SRR1531319 Naive CD4 T cell 0 h 5134 unstimulated SRR1531318 Naive CD4 T cell 0 h 5009 unstimulated SRR1531317 Memory CD4 T cell 48 h 5053 stimulated SRR1531314 Naive CD4 T cell 0 h 5053 unstimulated Statistical analysis Statistical analysis was performed with GraphPad Prism 9 (GraphPad Software). To determine data distribution, the Shapiro-Wilk normality test was performed. If data passed the normality test, parametric statistics were used. In all analyses, the tests were two-tailed. For comparison between 2 groups either unpaired or paired t-test was performed, depending on data sets. For the differences between three or more independent groups one-way ANOVA was applied, followed by multiple comparisons tests. For comparison differences between groups with two independent variables, twoway ANOVA with post hoc analysis was performed. All statistically significant differences (p-value < 0.05) and their p-values were marked on the graphs. Non-significant differences with p-value ≥ 0.05 were marked as ns. Data are represented as means with standard deviation. Each dot on the graphs represents the average of 2 technical replicates for a particular donor. Results T cell stimulation rewires iron and redox homeostasis of T cells To understand the metabolic consequences of T cells’ stimulation, we assessed iron homeostasis and the expression of iron homeostasis regulators, including transferrin receptor (CD71) as an iron importer and ferroportin (FPN1), a protein responsible for exporting Fe 2+ from the cell. Following stimulation, CD71 protein expression level increased significantly and remained elevated in stimulated T cells compared to unstimulated ones (Fig. 1 a). This effect was accompanied by an increase in FPN1 protein level, likely serving as a protective mechanism against toxic iron overload (Fig. 1 b). Over time of culture, the level of both CD71 and FPN1 noticeably dropped, but remained elevated as compared with unstimulated T cells. In consequence, following T cell stimulation we observed an increased level of the intracellular labile iron pool (Fig. 1 c) that remained elevated even for long-term culture and was only decreased upon deferoxamine treatment, a Fe 2+ chelator (Suppl. Figure 1a). Another observed consequence of T cell stimulation was redox homeostasis disturbance. To analyze it thoroughly, we assessed ROS levels with the CellROX Deep Red probe, for preferential detection of cytoplasmic and mitochondrial ROS (Fig. 1 d), and the CellROX Green reagent (Suppl. Figure 1b) to detect primarily nuclear-localized ROS. Upon stimulation, we observed an increase in ROS levels in stimulated T cells, although there was no widespread accumulation of ROS. Since ROS are short-lived molecules, the transcriptional activation of antioxidant enzymes can serve as a marker of defense against elevated intracellular ROS levels. Therefore, we reanalyzed RNAseq data in activated CD4 + T cells and observed, in comparison to unstimulated counterparts, an increased expression of transcripts encoding antioxidant defense enzymes, including members of the peroxiredoxin and thioredoxin families (Suppl. Figure 1c). Besides enzymatic antioxidant defense, the increased production of ROS is also balanced by reduced glutathione (GSH), the most abundant nonprotein thiol in mammalian cells. Therefore, we examined intracellular GSH levels and observed that stimulated T cells exhibited higher GSH levels compared to their unstimulated counterparts (Fig. 1 e). We also found that GSH- and glutathione peroxidases (GPXs)related genes, described as associated with ferroptosis [28], were up-regulated in stimulated T cells including transcripts for GSS, CHAC1, GPX4 (Suppl. Figure 1d). Since GSH synthesis depends on the availability of cysteine that in the cell is derived from the reduction of cellular cystine imported into the cells through the xc- system, a cystine-glutamate exchanger [29], we subsequently examined the expression of components of the xc- system and found upregulated expression of transcripts for SLC3A2 and SLC7A11 in stimulated CD4 + T cells (Suppl. Figure 1e), altogether supporting that stimulation of T cells induces ROS and antioxidant defense systems. T cell stimulation promotes lipid peroxidation Given that ferrous iron (Fe 2+ ) and hydrogen peroxide (H 2 O 2 ) can react in a process known as the Fenton reaction and generate peroxidized lipids [10], we subsequently assessed their levels in cell membranes. Upon stimulation, we observed a significant increase in the accumulation of peroxidized lipids in T cell membranes (Fig. 1 f) that remained elevated over the prolonged culture, as determined by C11-BODIPY™ 581/591 staining. Since lipid peroxidation is a marker of ferroptotic death, in the next steps we assessed the main pathways involved in the regulation of ferroptosis. The ACSL4–LPCAT3–LOX signaling axis is an intracellular pathway known to promote lipid peroxidation of membrane phospholipids (PLs) containing PUFAs and has been identified as one of the components crucial for ferroptosis execution [30–32]. We examined the expression of ACSL4 and observed its elevation in stimulated T cells both at mRNA (Suppl. Figure 1f) and protein (Fig. 1 g) levels. Also, the mRNA expression for LPCAT3 transcript significantly increased upon T cell stimulation (Suppl. Figure 1f). Furthermore, we assessed by Western blotting the protein level of LOX15 that acts as a key ferroptosis-promoting factor by directly oxidizing arachidonoyl (AA) and adrenoyl (AdA) phospholipids (PE) into lipid hydroperoxides [33]. While we observed a decrease of LOX15 in T cells after stimulation, in long-term culture LOX15 levels were reversed to some extent (Fig. 1 g). Finally, we examined the expression of two master ferroptosis suppressors, GPX4 and FSP1. In accordance with the accumulation of lipid peroxides upon TCR stimulation, a significant decrease of GPX4, as assessed by Western blotting was detected in subsequent days after stimulation (Fig. 1 h, Suppl. Figure 1g). Surprisingly, however, FSP1 expression was significantly increased upon stimulation of T cells (Fig. 1 h, Suppl. Figure 1g). In summary, our findings at this step demonstrate that stimulation of T cells substantially disturbs lipid, iron and redox homeostasis that is evidenced by an increased load of labile iron pool, as well as elevated ROS and lipid peroxidation levels. Moreover, T cells upon stimulation downregulate GPX4 and upregulate ACSL4 that are both ferroptosis-promoting effects. At the same time, stimulation of T cells activates the program that confers protection against ferroptosis and includes LOX15 decrease and increase of FSP1. Given these disturbances, we hypothesized that stimulation of T cells changes the balance of ferroptosis-promoting and protecting events and can therefore impair T cell homeostasis. To verify this hypothesis, we employed several inhibitors of GPX4 and FSP1, as two primary regulators protecting cells from ferroptosis and subsequently determined their influence on T cells’ viability, functions and metabolism. GPX4 orchestrates T cells and CAR-T cells' sensitivity to ferroptosis While unstimulated T cells remained relatively resistant to GPX4 inhibitors (RSL3 or ML162), as demonstrated by their viability (Fig. 2 a, Suppl. Figure 2a) and lipid peroxidation (Fig. 2 b), T cells after stimulation acquired sensitivity to inhibition of GPX4 (Fig. 2 c, Suppl. Figure 2b). Decreased viability of stimulated T cells was reversible with Lip-1, a ferroptosis-specific inhibitor, as determined by propidium iodide staining followed by flow cytometry analysis (Fig. 2 c, Suppl. Figure 2b). Consistently with the sensitivity of T cells to ferroptosis, a significant increase in lipid peroxidation measured by C11-BODIPY™ 581/591 staining, reversible by Lip-1, was observed in stimulated T cells, particularly when exposed to higher concentrations of RSL3 (Fig. 2 d). In contrast, even if some toxicity of GPX4 inhibitors was observed in higher doses in unstimulated T cells, it was not abrogated by Lip-1 (Fig. 2 a, Suppl. Figure 2a). Additionally, we noticed that stimulated T cells up to 2 weeks after stimulation were relatively insensitive to ferroptosis (Suppl. Figure 2c, d) and increasing concentrations of RSL3 did not trigger their lipid peroxidation (Suppl. Figure 2e). To check whether other types of cell death are induced in T cells by inhibiting GPX4 activity, we employed the pan-caspase apoptosis inhibitor Z-VAD-fmk (Z-VAD), and necroptosis inhibitor necrostatin-1 (Nec-1). They both did not confer protective effects on stimulated T cells incubated with a toxic dose of RSL3 (Suppl. Figure 2f). We also conducted a Western blot analysis to evaluate the LC3 protein, recognized as an indicator of autophagy. This was prompted by research suggesting that the initiation of autophagy could potentially influence the onset of ferroptosis [34]. Up to a week following T cell stimulation, we detected increased LC3 protein levels in T cells’ lysates, which was in line with previous research demonstrating that TCR activation triggers autophagy in T cells [35]. However, there was a noticeable decrease in LC3 protein levels in subsequent days of T cell culture, suggesting a lack of involvement of autophagy in mediating the ferroptosis of T cells (Suppl. Figure 2g). We also checked the influence of GPX4 inhibition on the proliferation potential of T cells upon stimulation. To this end, T cells were stimulated with anti-CD3/CD28 antibodies in the presence of increasing concentrations of RSL3. After 3 days of stimulation, in the highest tested RSL3 doses we observed some shifts in the peaks corresponding to the inhibition of the proliferation. However, these changes were not reversible by Lip-1 and were further mitigated by day 6 of the culture (Suppl. Figure 2h). Altogether, our results at this step show that GPX4 inhibition sensitizes T cells and CAR-T cells to ferroptosis in a manner reversible by Lip-1. Nevertheless, although stimulated T cells are initially resistant to ferroptosis, they acquire over time the sensitivity to ferroptosis-inducing agents, a phenomenon accompanied by GPX4 downregulation, ACSL4 upregulation and re-expression of LOX15. Moreover, CD19 CAR-modified T cells and their unmodified counterparts were highly sensitive to RSL3 (Fig. 2 e). Their decreased viability was almost completely reversible by Lip-1 further confirming that GPX4 inhibition also sensitizes CAR-T cells to ferroptosis. GPX4 inhibitors impair T cell functions in vitro and in vivo To understand the functional consequences of increased sensitivity of T cells to ferroptosis, we assessed the influence of GPX4 inhibitors on CAR-T cells’ cytotoxic activity. To this end, the ability of HER2 CAR-T cells to kill target MCF7 tumor cells was assessed in the presence of increasing concentrations of RSL3 by RTCA, an impedance-based technology used for label-free and real-time monitoring of cytotoxicity. For these experiments, we selected RSL3 concentrations that were non-toxic to CAR-T cells and only CAR-T cells with at least 80% viability were included in the RTCA analysis (Suppl. Figure 3a, left panel). We observed that the killing ability of RSL3-pretreated HER2 CART cells against the MCF7 cell line was impaired compared to the untreated control (Fig. 2 f) and unmodified T cells (Suppl. Figure 3b) and was further reversed by 24-hour pretreatment of CAR-T cells with Lip-1 (Fig. 2 f) that preserved CAR-T cell viability (Suppl. Figure 3a, right panel). Moreover, we confirmed that the viability of MCF7 cells alone in the presence of RSL3 or combination with Lip-1 was unaffected (Suppl. Figure 3c). In addition, to exclude the target antigen loss on cancer cells in response to RSL3 treatment, we also verified that the HER2 antigen expression on MCF7 cells remained unchanged following the RSL3 treatment (Suppl. Figure 3d). We further evaluated the influence of RSL3 on the degranulation of CAR-T cells (CD107a staining), as well as the cytokine production. In these experiments, CAR-T cells targeting CD19, PD-L1 or HER-2 were cultured with cancer cells expressing the corresponding antigens, in the presence of RSL3 at concentrations not toxic to cancer cell lines (Suppl. Figure 3e). Our findings demonstrated that pretreatment of CAR-T cells with RSL3 reduced their ability to degranulate in response to cognate target cells (Fig. 2 g) and to produce IFNγ and TNFα (Fig. 2 h). Finally, we sought to determine the role of ferroptosis in vivo and its influence on the efficacy of CAR-T immunotherapy (Fig. 2 i). To this end, CD19 CAR-T cells generated from two healthy donors’ T cells (referred to as donor 4 and donor 5) were intravenously injected into the mouse tail vein in the human-to-mouse Raji xenograft model. Before in vivo experiments, the percentage of T cell modification with CAR construct (Suppl. Figure 3f) and cytotoxic activity of CD19 CAR-T cells against Raji cells were assessed in vitro (Suppl. Figure 3g). While CD19 CAR-T cells from both donors efficiently and comparably killed tumor cells in vitro , they differed in the potential to eradicate tumors in vivo . In particular, donor 5-derived CD19 CAR-T cells significantly inhibited Raji tumor growth (Suppl. Figure 3h) and prolonged mouse survival (as assessed by reaching the predefined tumor volume) (Suppl. Figure 3i). Simultaneously, donor 4-derived CD19 CAR-T cells failed to do so, as compared with controls (Fig. 2 k). Interestingly, tumor eradication by donor 4 CD19 CAR-T cells was potentiated by Lip-1, as assessed by tumor volume (Fig. 2 k) and mouse survival (Fig. 2 l). Importantly, Lip-1 alone did not affect tumor cell growth compared to untreated control mice (Fig. 2 j). Taken together, our findings provide compelling evidence that ferroptosis, induced either by pharmacological inactivation of GPX4 in vitro or occurring naturally within the TME in vivo , significantly influences the functionality and cytotoxic activity of CAR-T cells. Furthermore, we also demonstrated that inhibiting ferroptosis using its specific inhibitor, Lip-1, can effectively protect CAR-T cells and enable the effective eradication of cancer cells. FSP1 regulates T cell antitumor activity independently of ferroptosis-suppressive function To understand more globally the role of ferroptosis in the modulation of T cell function, we further investigated the FSP1 pathway as a key component of a nonmitochondrial CoQ antioxidant system that acts in parallel to the canonical glutathione-based GPX4 pathway. To this end, we employed iFSP1, an inhibitor that regulates the human FSP1 protein by binding to residue F360 within it [36]. We observed that iFSP1 further potentiated ferroptosis of T cells induced by GPX4 inhibition (Fig. 3 a). Simultaneously, both T cells and CAR-T cells remained completely insensitive to single treatment with iFSP1, as determined by propidium iodide staining followed by flow cytometry analysis (Fig. 3 b). To our surprise, however, inhibition of FSP1, although not toxic to T cells, significantly affected the cytotoxic potential of CAR-T cells (both CD19- and PD-L1 CAR-T cells) and their ability to kill target tumor cells (Raji and Raji cells overexpressing PD-L1, respectively). This impairment was visible over the tested range of iFSP1 concentrations (2.5–40 µM), for different E:T ratios and when assessed by either luminescence assay (Fig. 3 c) or by flow cytometry (Suppl. Figure 3j). Interestingly, the inhibitory effect iFSP1 was nor reversible by Lip-1, suggesting that FSP1 plays a regulatory role in T cells independently of its ferroptosis-suppressive function (Fig. 3 c). To better understand the functional consequences of FSP1 inhibition in T cells, we further evaluated their degranulation, as well as production of cytotoxic molecules (perforin) and cytokines (IFNγ and TNFα) in the presence of increasing concentrations of iFSP1. While degranulation, measured by CD107a staining, was not affected by iFSP1 (Fig. 3 d, left panel), perforin levels (assessed by Western blotting, Fig. 3 e) and cytokine amounts (determined by flow cytometry, Fig. 3 e, middle and right panels) were substantially reduced. At this step, we concluded that FSP1 is a novel regulator of T cells and CAR-T cells function needed for their antitumor activity. We observed that FSP1 is strongly upregulated in T cells upon stimulation (Fig. 1 h), and its inhibition has a profound suppressive effect on their cytotoxic potential, correlated with decreased perforin levels and cytokine production. FSP1 inhibition changes T cell metabolism and suppresses proliferation Given that IFNγ and perforin production by T cells are strongly dependent on their metabolic state, we further explored the metabolic fitness of CAR-T cells following iFSP1 treatment. The oxygen consumption rate (OCR) for mitochondrial respiration and the extracellular acidification rate (ECAR) for glycolysis were detected by the Seahorse XF analyzer. Our findings demonstrated a substantial decrease in OCR (Fig. 3 f, left) and decreased mitochondrial ATP production (Fig. 3 g, left) after 24 hours of iFSP1 treatment when compared to untreated control cells. Surprisingly, upon treatment with iFSP1, neither ECAR (Fig. 3 f, right) nor the glycolytic pool of ATP (Fig. 3 g, right) were affected. Similar metabolic changes were observed in iFSP1-treated T cells, as seen in CAR-T cells (Suppl. Figure 3k, l). Although much of the attention on metabolic reprogramming in activated T cells has focused on the engagement of aerobic glycolysis, recent research has revealed the importance of mitochondrial-driven activities in this process [37–39]. In addition to energy production, the electron transport chain is a major source of ROS, which are important for T cell responses and proliferation. Therefore, given the observed changes in OCR and mito ATP pool upon iFSP1 treatment, we subsequently investigated the influence of iFSP1 on the proliferation of T cells. To this end, T cells isolated from healthy donor buffy coats were stained with CTV, stimulated with anti-CD3/CD28 antibodies, treated with iFSP1 and monitored for the proliferation capacity by flow cytometry. After 3 days of stimulation, only higher concentrations of iFSP1 (10–40 µM) delayed the proliferation (Fig. 3 h, left), while after 6 days of stimulation, the impaired proliferation was easily observed over the tested range of iFSP1 concentrations (2.5–40 µM), as compared to control cells (Fig. 3 h, right). Interestingly, this antiproliferative activity of iFSP1 was not reversible by Lip-1, further confirming that FSP1 in T cells plays a non-canonical role independently of its ferroptosis-suppressor function. In summary, we concluded from these experiments that FSP1 is a novel, so far not described, regulator of T cell metabolism and proliferation. Inhibition of FSP1 results in decreased mitochondrial ATP production in T cells that in consequence leads to the impairment of their proliferation and decreased antitumor cytotoxic potential. Discussion Ferroptosis has recently emerged as an iron-dependent form of regulated cell death that can be induced to overcome the resistance of the tumor cells to existing conventional therapies. An important role in the susceptibility of cancer cells to ferroptosis is played by TME, a multifaceted ecosystem composed of tumor cells, stroma cells and various immune cells. It has been shown that various cellular components of TME (neutrophils, T cells), as well as secreted cytokines (IFNγ, TGFβ1) and metabolic changes (acidosis), have a ferroptosis-promoting role. On the other hand, while the sensitivity of tumor cells to ferroptosis is widely studied, limited data is available for the immune cells. Therefore, in this study, we have addressed this issue by comprehensively characterizing ferroptosis markers in T cells. We demonstrated that stimulated, but not unstimulated T cells, showed hallmarks of ferroptosis [40]. These included an elevated intracellular labile iron pool, increased expression of the iron importer CD71, and an increase of ROS levels [41, 42]. In consequence, in stimulated T cells we observed an increased accumulation of peroxidized lipids, that was mitigated specifically by Lip-1, but not inhibitors of other cell death types, further confirming the ferroptotic type of death. While several studies have demonstrated that T cells are relatively resistant to ferroptosis, other research has found T cells to be vulnerable to this form of cell death. Our results are in accordance with other reports, where it has been shown that CD8 + tumor-infiltrating lymphocytes (TILs) displayed significant amounts of lipid peroxidation [43]. It has been also demonstrated that CD8 + T cells can undergo ferroptosis, particularly through mechanisms involving CD36-associated fatty acid intake leading to lipid peroxidation [16, 17]. It was also shown that sensitivity to ferroptosis differs across T cells’ subsets. For example, follicular helper CD4 + T cells were demonstrated to be highly susceptible to ferroptosis due to altered mitochondrial morphology and excessive lipid ROS [44]. Moreover, the deficiency of GPX4 leads to the elimination of a significant portion of memory CD4 + T cells, indicating their susceptibility to ferroptosis [14]. In contrast, Tregs show limited lipid peroxidation compared to tumor-specific CD8 + T cells and induction of GPX4 expression upon TCR triggering protects them from ferroptosis [43]. However, GPX4 deletion in Tregs can activate ferroptosis, promote IL-1β production, and enhance Th17 cell responses, thereby enhancing antitumor immunity and inhibiting tumor growth [45]. Moreover, Wang et al. demonstrated that RSL3 and erastin treatment did not affect the survival of naive and shortly stimulated T cells, irrespectively of the presence of a ferroptosis inhibitor, whereas they have shown that immunotherapy-activated CD8 + T cells induce ferroptosis in tumor cells [18]. The sensitivity of T cells to ferroptosis can have important therapeutic consequences. We demonstrated that GPX4 is essential for the activity of CAR-T cells, as shown by impaired degranulation, cytokine production and killing potential upon RSL3-evoked GPX4 inhibition. This phenomenon was mitigated in the presence of Lip-1 and remained in accordance with a report by Drijvers et al.. They reported that the inhibition of GPX4 impaired the OT-1 T cells' antigen-specific killing of cancer cells, and this effect was rescued by ferroptosis inhibitors, vitamin E and ferrostatin-1. We observed that in contrast to T cells in which sensitivity changed in the course of time, CAR-T cells were susceptible to ferroptosis already shortly after CAR modification. It is probably related to the CAR-T cell preparation process itself which requires twofold stimulation: firstly, associated with preparing the cells to introduce the plasmid encoding the CAR receptor, and secondly, subsequent stimulation with CD3/CD28 beads for their expansion. It is worth noting that the repeated antigen stimulation of CAR-T cells can trigger activation-induced cell death (AICD), which can subsequently reduce the persistence of CAR-T cells and may impact their ability to eliminate tumor cells [46]. Here, we hypothesize that activation-induced ferroptosis is one of the mechanisms regulating T cells’ fate, maintaining T cell homeostasis and therefore contributing to the termination of cellular immune responses. Accordingly, the induction of ferroptosis in stimulated T/CAR-T cells may occur as part of the contraction phase of an immune response, resulting in the elimination of the effector T cell population while sparing those transformed into long-lived memory cells [47, 48]. As a novel observation not described before, we noticed a significant decrease in the expression level of GPX4 protein and increase of FSP1 following TCR stimulation. While GPX4 serves as a pivotal regulator in the intricate process of ferroptosis by playing a crucial role in protecting cells from lipid peroxidation-induced damage, FSP1 has been identified as the second ferroptosis-suppressing system. FSP1 efficiently prevents lipid peroxidation independently of the cyst(e)ine–glutathione (GSH)–glutathione peroxidase 4 (GPX4) axis [11]. Interestingly, we observed that FSP1 inhibition neither affected the viability of T cells nor CAR-T cells. However, it significantly potentiated the ferroptosis of T cells induced by inhibition of GPX4. This observation remains in accordance with the role of FSP1 complementing GPX4 in tumor cells, as already described elsewhere [11]. Surprisingly, iFSP, although not toxic to CAR-T cells, significantly inhibited their ability to kill target tumor cells, produce cytokines and perforin, and proliferate. Moreover, we also observed that iFSP1 had profound effects on T cells metabolism by inhibiting OCR and mito ATP production. Given these results, we hypothesize that FSP1 is a novel regulator involved in the control of mitochondrial oxidative phosphorylation in T cells. Importantly, beyond its anti-ferroptotic role, FSP1 has already been reported by others to regulate cellular metabolism. For instance, in brown adipose tissue, FSP1 promotes glycolysis during thermogenesis, and in skeletal muscles, it is induced during exercise to enhance glucose utilization and maintain exercise capacity [49, 50]. It has also been demonstrated that overexpression of FSP1 enhances the NAD+/NADH ratio to drive higher glycolytic rates essential for cell proliferation and promotes invasion and migration in human glioma cells [51]. FSP1, also known as AIFM2/AMID belongs to the apoptosis inducing factor (AIF) family. Apoptosis-inducing factors were initially identified as factors that can trigger a unique, caspase-independent apoptotic program [52]. However, AIFM2 and its more ubiquitously expressed homolog AIFM1 presumably play a so far poorly analyzed physiological role in metabolism in many cells [52]. Beyond being a part of a system that reduces the risk of phospholipid peroxidation and ferroptosis, FSP1 is referred to as a special isoform of an NADH dehydrogenase speeding up electron flow through the respiratory chain and promoting the functionality of mitochondrial respiration [52]. Interestingly, it was proposed that both AIF and AMID (FSP1) are previously unidentified mammalian NADH:ubiquinone (UQ) oxidoreductase enzymes, whose bioenergetic function could be a supplemental NADH oxidation in cells [53]. Importantly, it was demonstrated that both AIF and AMID (FSP1) can be associated with the matrix side of the inner membrane of submitochondrial part and integrated as members of the host respiratory chain, with UQ being the physiological electron acceptor for both of them [53]. It was also reported that AIF deficiency in Harlequin mice strain (characterized by hypomorphic mutation of AIF) compromises oxidative phosphorylation and results in complex I defects [54]. Our results are in accordance with these observations; however it should be underlined that FSP1 has never been described earlier as a metabolic regulator of OXPHOS in T cells. Therefore, further studies are needed to better understand the role of FSP1 in determining T cells’ fate. It is possible that FSP1 serves as conserved redox switch which measures T cells’ metabolic conditions on the mitochondrial surface and translate it into a binary life/death decision. Finally, our in vivo study demonstrates that the efficacy of CAR-T cell therapy can be enhanced through the inhibition of ferroptosis by Lip-1, thus indirectly providing support for the presence of ferroptosis within the TME, as was previously described by Kim et al. [12]. Indeed, we observed that the diminished cytotoxic potential of CAR-T cells may only become apparent in vivo with donor-to-donor variability, despite similar CAR-T cells efficacy in vitro . Our results indicate that even repeated administration of well-proliferating CAR-T cells is not sufficient when their cytotoxic activity is impaired. Our findings might also have significant implications for optimizing CAR-T cell therapy outcomes. The condition of T cells in adoptive therapies is multifactorial. An important factor influencing the efficacy of CAR-T therapy is the quality of T cells isolated from patients for CAR modification. Additionally, the generation time of CAR-T cells, from leukapheresis to infusion into the patient, spans several weeks [55] potentially increasing the vulnerability of CAR-T cells to ferroptosis. Moreover, post-infusion, the cytotoxic potential of CAR-T cells against tumors is largely constrained by the immunosuppressive TME characterized by oxidative stress, lipid accumulation, and competition for scarce energy resources, rendering immune cells susceptible to ferroptosis [56, 57]. On the other hand, the induction of ferroptosis is developed as one of the therapeutic approaches in cancer treatment, particularly for solid tumors. Our results indicate that induction of ferroptosis can be a double-edged sword, that apart from eliminating cancer cells can also significantly impairs CAR-T cell-mediated antitumor activity. As mentioned earlier, both GPX4 and FSP1 plays an important role in regulation of cytotoxic functions of CAR-T cells. In light of this, future anticancer therapies should be carefully designed to selectively induce ferroptosis of tumor cells without impeding cytotoxic cells’ antitumor efficacy. Declarations Acknowledgements: The authors would like to acknowledge Mrs Ewa Pieta for peripheral blood mononuclear cells (PBMC) preparation. The work was supported by the National Science Centre, Poland (2019/33/B/NZ6/02503 to MB), European Research Council (805038/STIMUNO/ERC-2018-STG to MW) and Medical University of Warsaw (1/M/MG/N/24 to SH). ML, DP were partially funded by Warsaw University of Technology within the Excellence Initiative: Research University (IDUB) programme. Bioinformatics computations were performed thanks to the Laboratory of Bioinformatics and Computational Genomics, Faculty of Mathematics and Information Science, Warsaw University of Technology using Artificial Intelligence HPC platform financed by Polish Ministry of Science and Higher Education (decision no. 7054/IA/SP/2020 of 2020-08-28). Contributions: M.Kł. conducted most in vitro experiments, analyzed the data, performed a statistical analysis, wrote manuscript and prepared figures. I.B. designed, coordinated, and conducted in vivo experiments. S.H., N.L., and A.J. contributed to some in vitro flow cytometry and Western blotting experiments. M.G. conducted experiments related to the assessment of the labile iron pool by flow cytometry and performed RTCA tests. M.Ł. performed the bioinformatics analyses of RNAseq data and prepared figures. M.Kr. performed a statistical analysis. M.D. performed HER2 antigen staining by flow cytometry. A.G. and R.Z. provided critical feedback and edited the manuscript. D.P. supervised the bioinformatics analyses. M.W. conceived and supervised the study, provided funding and resources, and supervised and edited the manuscript. M.B. conceived, designed, supervised and performed the study, provided funding and resources, and supervised and wrote the manuscript. All authors provided critical feedback and reviewed and approved the final manuscript. A conflict of interest disclosure statement: The authors declare no potential conflicts of interest. References Koeberle, S.C., et al., Ferroptosis-modulating small molecules for targeting drug-resistant cancer: Challenges and opportunities in manipulating redox signaling. Med Res Rev, 2023. 43 (3): p. 614-682. Zhang, C., et al., Ferroptosis in cancer therapy: a novel approach to reversing drug resistance. Mol Cancer, 2022. 21 (1): p. 47. 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Nakamaru-Ogiso, Apoptosis-inducing Factor (AIF) and Its Family Member Protein, AMID, Are Rotenone-sensitive NADH:Ubiquinone Oxidoreductases (NDH-2). J Biol Chem, 2015. 290 (34): p. 20815-20826. Vahsen, N., et al., AIF deficiency compromises oxidative phosphorylation. EMBO J, 2004. 23 (23): p. 4679-89. Blache, U., et al., Potential solutions for manufacture of CAR T cells in cancer immunotherapy. Nat Commun, 2022. 13 (1): p. 5225. Curvello, R., et al., Recreating metabolic interactions of the tumour microenvironment. Trends Endocrinol Metab, 2024. Nanjireddy, P.M., S.H. Olejniczak, and N.P. Buxbaum, Targeting of chimeric antigen receptor T cell metabolism to improve therapeutic outcomes. Front Immunol, 2023. 14 : p. 1121565. Additional Declarations There is no duality of interest Supplementary Files UncroppedwesternblotsGPX4FSP1combo.docx Suppl. Fig. 1. Stimulation of T cells alters the expression levels of transcripts encoding proteins that regulate ferroptosis. a.FerroOrange staining of labile iron pool in unstimulated T cells and stimulated with anti-CD3/anti-CD28 Dynabeads and IL2 for 3 days. The cells were washed 3 times and resuspended in HBSS buffer in the presence or absence of 1 mM or 2 mM deferoxamine for 30 min before FerroOrange staining. b. Intracellular ROS detection using fluorescent probe CellROX Green and flow cytometry analysis. Statistical analysis was done with Brown-Forsythe and Welch ANOVA tests with Dunnett; T3 multiple comparisons test, with individual variances computed for each comparison. c. RNAseq analysis of transcripts for peroxiredoxin/thioredoxin-related genes: PRDX1-6 (peroxiredoxins 1-6), TXN 1, 2 (thioredoxins 1, 2) and thioredoxin reductase TXNRD1 in unstimulated CD4+ T cells and stimulated with CD3/CD28 antibodies for 48 h (GEO accession number: GSE 59846); * p ≤ 0.05; ** p ≤ 0.01; *** p ≤ 0.001; ns: not significant. d. RNAseq analysis of transcripts of glutathione and glutathione peroxidases related genes glutathione synthetase (GSS), glutathione-specific gamma-glutamylcyclotransferase 1 (CHAC1) and glutathione peroxidase 4 (GPX4) in unstimulated CD4+ T cells and stimulated with CD3/CD28 antibodies for 48 h (GEO accession number: GSE 59846); * p ≤ 0.05; ** p ≤ 0.01. e. RNAseq analysis of xc- related transcripts: amino acid transporter heavy chain (SLC3A2), cystine/glutamate transporter (SLC7A11) in unstimulated CD4+ T cells and stimulated with CD3/CD28 antibodies for 48 h; *** p ≤ 0.001. f. RNAseq analysis of lipid peroxidation-related transcripts named Long-chain-fatty-acid--CoA ligase 4 (ACSL4) and lysophosphatidylcholine acyltransferase 3 (LPCAT3), in unstimulated CD4+ T cells and stimulated with CD3/CD28 antibodies for 48 h; * p ≤ 0.05; ** p ≤ 0.01. g. Western blotting analysis of GPX4 and FSP1 protein levels in unstimulated and stimulated T cells at different days upon stimulation. Data show results from another representative donor. β-actin was used as a loading control. Suppl. Fig.2. GPX4 inhibition neither induces ferroptosis in unstimulated and shortly stimulated T cells nor affects T cell proliferation. a. Sensitivity of unstimulated T cells to GPX4 inhibitor ML162. Resting T cells isolated from PBMC were seeded with ML162 in the presence or absence of Lip-1 for 48 h. Viability was evaluated with standard propidium iodide staining and flow cytometry analysis. b. Sensitivity of stimulated T cells to ML162. Human primary T cells were stimulated with (CD3/CD28 beads) and IL-2 (100 U/ml). Subsequently, T cells were cultured for at least 14 days and were seeded with ML162 for 48 h in the presence or absence of Lip-1 (0.5 µM). Data are presented as means +/- sd. c, d. T cells 1-2 weeks after stimulation with CD3/CD28 beads and IL-2 (100 U/ml) were tested for their sensitivity to RSL3 (c) and ML162 (d) after 48 h incubation with GPX4 inhibitors in the presence or absence of Lip-1 (0.5 µM). Cell survival was evaluated with propidium iodide and flow cytometry. Each data point represents an average of 2 technical replicates for one donor. e. C11-BODIPY 581/591 staining of T cells 1-2 weeks after stimulation with CD3/CD28 beads and IL-2 (100 U/ml) after 24 h-incubation with RSL3 in the presence or absence of Lip-1 (0.5 µM). Data are presented as means +/- sd. Each data point represents an average of 2 technical replicates for one donor. Statistical analysis was done with ordinary two-way ANOVA with Dunnett's multiple comparisons test; ns: not significant. f. Survival of unstimulated (left panel) and stimulated (right panel) T cells in the presence or absence of RSL3 (2.5 µM) in combination with an inhibitor of apoptosis (Z-VAD, 10 µM), necroptosis (Nec-1, 10 µM) and ferroptosis (Lip-1, 0.5 µM). The statistic was calculated with one-way ANOVA with repeated measures and Geisser-Greenhouse correction with Sidak’s multiple comparisons test; ns: not significant. g. Western blotting evaluation of LC3 protein level in unstimulated and stimulated T cells at different days upon stimulation. Data show results from 1 representative donor. β-actin was used as a loading control. h.Proliferation of T cells stimulated with CD3/CD28 beads and IL-2 in the presence of increasing concentrations of RSL3 (blue histograms) or RSL3 and Lip-1 (pink histograms). Proliferation was evaluated upon Cell Trace Violet staining and flow cytometry analysis. Data are presented from 3 donors after 3 days of stimulation (left panel) and 6 days of stimulation (right panel). Unstained control was marked as light grey histogram, CTV-positive unstimulated (non-proliferating) control (dark grey). Suppl. Fig. 3. Evaluation of survival, cytotoxicity, and metabolic activity in effector cells under GPX4 or FSP1 inhibition. a. Viability of T cells and CAR-HER2 T cells treated with RSL3 (with or without Lip-1) for 5 h and 24 h, evaluated with propidium iodide staining and flow cytometry analysis. b. Supplementary data for the main figure 2f showing results of real-time cell analysis of control unmodified T cell killing of MCF7 targets. T cells were pretreated with RSL3 for 5 h then the cells were added to MCF7 targets and assay was monitored for the next 12 hours. Experiment was repeated at least 3 times, data represent mean and standard deviation of 2 technical replicates from one representative experiment. c. RTCA results of the impact of RSL3 on MCF7 cells proliferation. d.Expression of HER2 antigen on MCF7 target cells preincubated with RSL3. MCF7 cells were seeded onto a 12-well plate and allowed to adhere overnight. The next day RSL3 was added to appropriate wells, and after 24 h MCF7 cells were trypsinized, stained with viability stain and anti-HER2 antibody and analyzed on a flow cytometer. e. Raji and MCF7 cells, previously modified to express the luciferase reporter gene (red-luc), were seeded with RSL3 for 48 h in the presence or absence of Lip-1 (0.5 µM). After incubation, Bright-Glo™ Luciferase Assay System was used for bioluminescence readout. f. Dot plots from flow cytometry analysis showing CD19 CAR expression in modified CAR-T cells. g. CD19 CAR-T cell-mediated killing of Raji red-luc cells evaluated with luminescence-based assay. Data are presented as averages from 4 technical replicates +/- sd. h, i. Raji cells were inoculated into NSG (NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ) mice treated with CD19 CAR-T cells with or without Lip-1 i.p. injections. Tumor volume measurements are presented for each mouse (h). Event-free survival is presented on the Kaplan–Meier survival plot (i). j. PD-L1 CAR-T cell-mediated killing of Raji cells overexpressing PD-L1 molecule upon iFSP1 pretreatment. CAR-T cells were pretreated with iFSP1 (20 µM) for 48 h then washed and seeded for 18 h with target cells at different E:T ratios. The graph presents data from one donor. k, l. Seahorse analysis of control and iFSP1 (20 µM) pretreated T cells (48 h) using Seahorse XF T Cell Metabolic Profiling kit. k.Kinetic graphs represent oxygen consumption rate (OCR) levels and extracellular acidification rate (ECAR) profiles of control and iFSP1-treated CAR-T cells. Data are presented as mean +/- sd of measurements performed on 2 donors. l. Bar graphs from Seahorse analysis representing mitochondrial (left panel) and glycolysis (right panel) ATP production levels in stimulated T cells pretreated with iFSP1 for 48 h. Cite Share Download PDF Status: Posted Version 1 posted 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. 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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-5280443","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":369003874,"identity":"933637fe-06f3-4696-a250-6006a9607c82","order_by":0,"name":"Malgorzata 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Warsaw","correspondingAuthor":false,"prefix":"","firstName":"Magdalena","middleName":"","lastName":"Winiarska","suffix":""}],"badges":[],"createdAt":"2024-10-17 07:12:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5280443/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5280443/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":67830872,"identity":"58acb936-813e-4140-9008-dbff95c0e01d","added_by":"auto","created_at":"2024-10-30 07:15:44","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1105020,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eT cells stimulation substantially disturbs lipid, iron, and redox homeostasis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCenter of the figure: \u003c/strong\u003eSchematic presentation of proteins involved in the ferroptosis pathway. Anti-ferroptotic proteins are marked in green, and pro-ferroptotic proteins are marked in red. Inhibitors used in the experiments are marked in squares. Red square – ferroptosis inducing agents, green squares – ferroptosis inhibitors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea-f.\u003c/strong\u003e Analysis of ferroptosis-related markers in unstimulated (unst) and stimulated T cells cultured for different times after stimulation 1-2 weeks (short) and 3-5 weeks (long). Data points represent individual donors. Statistical analysis was done with Brown-Forsythe and Welch ANOVA tests with Dunnett; T3 multiple comparisons test, with individual variances computed for each comparison; ns: not significant. All experiments were analyzed using flow cytometry. \u003cstrong\u003ea. \u003c/strong\u003eExtracellular staining of CD71 (transferrin receptor) on T cells. \u003cstrong\u003eb.\u003c/strong\u003e Intracellular staining of FPN1 (ferroportin) on T cells. \u003cstrong\u003ec.\u003c/strong\u003e Labile iron pool in T cells was detected with fluorescent probe FerroOrange. \u003cstrong\u003ed.\u003c/strong\u003e Intracellular ROS detection using fluorescent probe CellROX DeepRed.\u003cstrong\u003e e.\u003c/strong\u003e Glutathione level in T cells determined with fluorescent probe Thiol Green. \u003cstrong\u003ef.\u003c/strong\u003e Lipid peroxidation evaluated with C11-BODIPY 581/591 sensor. \u003cstrong\u003eg-h. \u003c/strong\u003eWestern blotting evaluation of\u003cstrong\u003e g\u003c/strong\u003e. ACSL4 and LOX15 or \u003cstrong\u003eh.\u003c/strong\u003e GPX4 and FSP1 protein levels in unstimulated and stimulated T cells at different days upon stimulation with CD3/CD28 beads and IL-2 (100 U/ml). Data show results from representative donors. β-actin was used as a loading control.\u003c/p\u003e","description":"","filename":"Figures13mainmanuscript1.png","url":"https://assets-eu.researchsquare.com/files/rs-5280443/v1/3e466ae51a162b72944cfea2.png"},{"id":67830871,"identity":"8442d0c1-89f1-443a-bf62-a466fe40b6e5","added_by":"auto","created_at":"2024-10-30 07:15:44","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":800575,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGPX4 inhibition sensitizes T cells and CAR-T cells to ferroptosis and leads to impaired function and reduced antitumor efficacy, which can be restored by Lip-1.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea. \u003c/strong\u003eSensitivity of unstimulated T cells to GPX4 inhibition. Human primary T cells were isolated from PBMC and incubated with RSL3 for 48h +/- Lip-1 (0.5 µM). Cell viability was evaluated with flow cytometry and propidium iodide staining. Each data point represents an average of 2 technical replicates for one donor.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eb.\u003c/strong\u003e Lipid peroxidation of unstimulated T cells upon 24 h incubation with RSL3 evaluated with C11-BODIPY 581/591 staining. Each data point represents averages of 2 technical replicates for one donor. Statistical analysis was done with ordinary two-way ANOVA with Dunnett's multiple comparisons test; ns: not significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ec. \u003c/strong\u003eSensitivity of stimulated T cells to RSL3. Human primary T cells were stimulated with (CD3/CD28 beads) and IL-2 (100 U/ml). Subsequently, T cells were cultured for at least 14 days and were seeded with RSL3 for 48 h in the presence or absence of Lip-1 (0.5 µM). Data are presented as means +/- sd.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ed.\u003c/strong\u003e Lipid peroxidation of stimulated T cells upon 24 h RSL3 treatment evaluated with C11-BODIPY 581/591 staining. Each data point represents averages of 2 technical replicates for one donor. Statistical analysis was done with ordinary two-way ANOVA with Dunnett's multiple comparisons test; ns: not significant. Statistically significant p-values were marked on the graph.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ee.\u003c/strong\u003eSensitivity of CD19 CAR-T cells to GPX4 inhibition. CD19 CAR-T cells and control unmodified T cells were incubated with RSL3 for 48 h in the presence or absence of Lip-1 (0.5 µM). The viability of cells was evaluated using propidium iodide staining followed by flow cytometry analysis. Each data point represents an average of 2 technical replicates for one donor.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ef.\u003c/strong\u003e Real-time cell analysis of CAR-HER2-mediated killing of MCF7 targets. CAR-T cells were pretreated with RSL3 for 5 h then the cells were added to MCF7 targets and the killing was monitored for the next 12 hours. The experiment was done at least 3 times. Representative data from one experiment are presented on the graph. Data represent mean +/- sd of 2 technical replicates.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eg-h.\u003c/strong\u003e Degranulation (\u003cstrong\u003eg\u003c/strong\u003e) and cytokine production (\u003cstrong\u003eh\u003c/strong\u003e) IFNy and TNFα of control unmodified T cells and CAR-T cells in the presence of cancer cells expressing recognized antigen (CD19 CAR-T cells were cocultured with CD19+ Raji cells, CAR HER2 T cells with HER2+ MCF7 and PDL1 CAR-T cells with Raji cells overexpressing PDL1. Effector cells (T cells /CAR-T cells) were pretreated with RSL3 (2.5 µM) for 18 h and subsequently, the cells were tested in a 4 h functional assay. Each data point represents an average of 2 technical replicates for one donor. The statistic was calculated using a paired t-test.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ei.\u003c/strong\u003e Scheme of the treatment procedures used for \u003cem\u003ein vivo\u003c/em\u003e experiments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ej-l. \u003c/strong\u003e\u003cem\u003eIn vivo\u003c/em\u003e results of Lip-1 effect on tumor growth of Raji cells treated with CD19 CAR-T cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ej.\u003c/strong\u003e Tumor growth of Raji cells in control mice or control mice administrated i.p. with Lip-1 (10 mg/kg). \u003cstrong\u003ek.\u003c/strong\u003e Tumor growth of Raji cells treated with CD19 CAR-T cells (donor 4) or CD19 CAR-T cells (donor 4) in combination with Lip-1 (10 mg/kg) i.p. injections. \u003cstrong\u003el.\u003c/strong\u003eSurvival rate of mice in four groups: mice inoculated with Raji cells (control), mice inoculated with Raji cells and injected with Lip-1 (control + Lip-1), mice inoculated with Raji cells treated with CD19 CAR-T cells from donor 4 (CAR CD19 donor 4) and mice inoculated with Raji cells treated with CD19 CAR-T cells from donor 4 and injected with Lip- 1 (CAR CD19 donor 4 + Lip-1). Each line represents individual mice.\u003c/p\u003e","description":"","filename":"Figures13mainmanuscript2.png","url":"https://assets-eu.researchsquare.com/files/rs-5280443/v1/abc401abfb4fb6f9b90a4675.png"},{"id":67829810,"identity":"51d4ad07-e7e3-448b-8a6d-cb939cfd945d","added_by":"auto","created_at":"2024-10-30 07:07:44","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":602173,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFSP1 inhibition affects T cell and CAR T cell antitumor activity and metabolism.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea.\u003c/strong\u003e Viability of stimulated T cells incubated with or without iFSP1 (1.25 µM) in combination with RSL3 (2.5-5 µM). The statistic was calculated using a paired t-test.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eb.\u003c/strong\u003e Viability of unstimulated (blue) and stimulated (pink) T cells after 48h incubation with iFSP1. Cell survival was evaluated with flow cytometry upon propidium iodide staining.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ec.\u003c/strong\u003eLuciferase-based killing of CD19 CAR-T cells against target cells Raji cells (CD19+) overexpressing red luciferase (red-luc). Effector (E) CD19 CAR-T cells were preincubated with increasing concentrations of iFSP1 for 24 h and subsequently added onto Raji red-luc targets (T) at different E:T ratio 0.25:1 (left graph) and 1:1 (right graph). The statistic was calculated with RM two-way ANOVA. Multiple comparisons were performed only for the iFSP1 concentration factor (p=0.0001) with Dunnett’s multiple comparisons test.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ed.\u003c/strong\u003e Degranulation (left graph) and cytokine production (right graphs) IFNy and TNFα of CD19 CAR-T cells in the presence of CD19+ Raji cells. Effector to target ratio 1:1. Effector cells were pretreated with increasing concentrations of iFSP1 for 24 h, subsequently seeded with Raji cells in for 4 h functional assay. Data were calculated and presented as a % of control. Each data point represents an average of 2 technical replicates for one donor, lines represent mean +/- sd. The statistic was calculated using one-way ANOVA.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ee. \u003c/strong\u003eWestern blotting evaluation of perforin in stimulated T cells upon iFSP1 treatment for 48 h. Data show results from 3 representative donors. β-actin was used as a loading control.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ef.\u003c/strong\u003e Seahorse analysis of control and iFSP1 (20 µM) pretreated CAR-T cells (48 h) using Seahorse XF T Cell Metabolic Profiling kit. Kinetic graphs represent oxygen consumption rate (OCR) levels and extracellular acidification rate (ECAR) profiles of control and iFSP1-treated CAR-T cells. Data are presented as mean +/- sd of measurements performed on 4 donors. p-value of repeated measures two-way ANOVA is presented on the kinetic graphs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eg.\u003c/strong\u003e Bar graphs from Seahorse analysis representing mitochondrial (left panel) and glycolysis (right panel) ATP production levels. The statistic was calculated with paired t test; ns: not significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eh. \u003c/strong\u003eProliferation of T cells stimulated with CD3/CD28 beads and IL-2 in the presence of increasing concentrations of iFSP1 (violet histograms) or iFSP1 and Lip-1 (pink histograms). Proliferation was evaluated upon Cell Trace Violet staining after 3 and 6 days with flow cytometry. Histograms present data from one representative donor. Experiments were done on 12 donors. Unstained control was marked as light grey histogram, CTV-positive unstimulated (non-proliferating) control (dark grey).\u003c/p\u003e","description":"","filename":"Figures13mainmanuscript3.png","url":"https://assets-eu.researchsquare.com/files/rs-5280443/v1/2b95cf8f8f5d90062e7423ae.png"},{"id":80551914,"identity":"8452cc85-cca8-4957-89d0-5166663c7196","added_by":"auto","created_at":"2025-04-14 14:59:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3993242,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5280443/v1/7f4debe0-7afb-4768-a08a-5e3b4e4a8085.pdf"},{"id":67829812,"identity":"c8021e8e-407d-4342-93f5-4b39f09d4325","added_by":"auto","created_at":"2024-10-30 07:07:44","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2389203,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSuppl. Fig. 1. Stimulation of T cells alters the expression levels of transcripts encoding proteins that regulate ferroptosis.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea.\u003c/strong\u003eFerroOrange staining of labile iron pool in unstimulated T cells and stimulated with anti-CD3/anti-CD28 Dynabeads and IL2 for 3 days. The cells were washed 3 times and resuspended in HBSS buffer in the presence or absence of 1 mM or 2 mM deferoxamine for 30 min before FerroOrange staining.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eb.\u003c/strong\u003e Intracellular ROS detection using fluorescent probe CellROX Green and flow cytometry analysis. Statistical analysis was done with Brown-Forsythe and Welch ANOVA tests with Dunnett; T3 multiple comparisons test, with individual variances computed for each comparison.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ec.\u003c/strong\u003e RNAseq analysis of transcripts for peroxiredoxin/thioredoxin-related genes: PRDX1-6 (peroxiredoxins 1-6), TXN 1, 2 (thioredoxins 1, 2) and thioredoxin reductase TXNRD1 in unstimulated CD4+ T cells and stimulated with CD3/CD28 antibodies for 48 h (GEO accession number: GSE 59846); * p ≤ 0.05; ** p ≤ 0.01; *** p ≤ 0.001; ns: not significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ed.\u003c/strong\u003e RNAseq analysis of transcripts of glutathione and glutathione peroxidases related genes glutathione synthetase (GSS), glutathione-specific gamma-glutamylcyclotransferase 1 (CHAC1) and glutathione peroxidase 4 (GPX4) in unstimulated CD4+ T cells and stimulated with CD3/CD28 antibodies for 48 h (GEO accession number: GSE 59846); * p ≤ 0.05; ** p ≤ 0.01.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ee.\u003c/strong\u003e RNAseq analysis of xc- related transcripts: amino acid transporter heavy chain (SLC3A2), cystine/glutamate transporter (SLC7A11) in unstimulated CD4+ T cells and stimulated with CD3/CD28 antibodies for 48 h; *** p ≤ 0.001.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ef.\u003c/strong\u003e RNAseq analysis of lipid peroxidation-related transcripts named Long-chain-fatty-acid--CoA ligase 4 (ACSL4) and lysophosphatidylcholine acyltransferase 3 (LPCAT3), in unstimulated CD4+ T cells and stimulated with CD3/CD28 antibodies for 48 h; * p ≤ 0.05; ** p ≤ 0.01.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eg.\u003c/strong\u003e Western blotting analysis of GPX4 and FSP1 protein levels in unstimulated and stimulated T cells at different days upon stimulation. Data show results from another representative donor. β-actin was used as a loading control.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSuppl. Fig.2. GPX4 inhibition neither induces ferroptosis in unstimulated and shortly stimulated T cells nor affects T cell proliferation.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea. \u003c/strong\u003eSensitivity of unstimulated T cells to GPX4 inhibitor ML162. Resting T cells isolated from PBMC were seeded with ML162 in the presence or absence of Lip-1 for 48 h. Viability was evaluated with standard propidium iodide staining and flow cytometry analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eb.\u003c/strong\u003e Sensitivity of stimulated T cells to ML162. Human primary T cells were stimulated with (CD3/CD28 beads) and IL-2 (100 U/ml). Subsequently, T cells were cultured for at least 14 days and were seeded with ML162 for 48 h in the presence or absence of Lip-1 (0.5 µM). Data are presented as means +/- sd.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ec, d.\u003c/strong\u003e T cells 1-2 weeks after stimulation with CD3/CD28 beads and IL-2 (100 U/ml) were tested for their sensitivity to RSL3 (c) and ML162 (d) after 48 h incubation with GPX4 inhibitors in the presence or absence of Lip-1 (0.5 µM). Cell survival was evaluated with propidium iodide and flow cytometry. Each data point represents an average of 2 technical replicates for one donor.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ee.\u003c/strong\u003e C11-BODIPY 581/591 staining of T cells 1-2 weeks after stimulation with CD3/CD28 beads and IL-2 (100 U/ml) \u0026nbsp;after 24 h-incubation with RSL3 in the presence or absence of Lip-1 (0.5 µM). Data are presented as means +/- sd. Each data point represents an average of 2 technical replicates for one donor. Statistical analysis was done with ordinary two-way ANOVA with Dunnett's multiple comparisons test; ns: not significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ef.\u003c/strong\u003e Survival of unstimulated (left panel) and stimulated (right panel) T cells in the presence or absence of RSL3 (2.5 µM) in combination with an inhibitor of apoptosis (Z-VAD, 10 µM), necroptosis (Nec-1, 10 µM) and ferroptosis (Lip-1, 0.5 µM). The statistic was calculated with one-way ANOVA with repeated measures and Geisser-Greenhouse correction with Sidak’s multiple comparisons test; ns: not significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eg.\u003c/strong\u003e Western blotting evaluation of LC3 protein level in unstimulated and stimulated T cells at different days upon stimulation. Data show results from 1 representative donor. β-actin was used as a loading control.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eh.\u003c/strong\u003eProliferation of T cells stimulated with CD3/CD28 beads and IL-2 in the presence of increasing concentrations of RSL3 (blue histograms) or RSL3 and Lip-1 (pink histograms). Proliferation was evaluated upon Cell Trace Violet staining and flow cytometry analysis. Data are presented from 3 donors after 3 days of stimulation (left panel) and 6 days of stimulation (right panel). Unstained control was marked as light grey histogram, CTV-positive unstimulated (non-proliferating) control (dark grey).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSuppl. Fig. 3. Evaluation of survival, cytotoxicity, and metabolic activity in effector cells under GPX4 or FSP1 inhibition.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea.\u003c/strong\u003e Viability of T cells and CAR-HER2 T cells treated with RSL3 (with or without Lip-1) for 5 h and 24 h, evaluated with propidium iodide staining and flow cytometry analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eb.\u003c/strong\u003e Supplementary data for the main figure 2f showing results of real-time cell analysis of control unmodified T cell killing of MCF7 targets. T cells were pretreated with RSL3 for 5 h then the cells were added to MCF7 targets and assay was monitored for the next 12 hours. Experiment was repeated at least 3 times, data represent mean and standard deviation of 2 technical replicates from one representative experiment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ec.\u003c/strong\u003e RTCA results of the impact of RSL3 on MCF7 cells proliferation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ed.\u003c/strong\u003eExpression of HER2 antigen on MCF7 target cells preincubated with RSL3. MCF7 cells were seeded onto a 12-well plate and allowed to adhere overnight. The next day RSL3 was added to appropriate wells, and after 24 h MCF7 cells were trypsinized, stained with viability stain and anti-HER2 antibody and analyzed on a flow cytometer.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ee.\u003c/strong\u003e Raji and MCF7 cells, previously modified to express the luciferase reporter gene (red-luc), were seeded with RSL3 for 48 h in the presence or absence of Lip-1 (0.5 µM). After incubation, Bright-Glo™ Luciferase Assay System was used for bioluminescence readout.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ef.\u003c/strong\u003e Dot plots from flow cytometry analysis showing CD19 CAR expression in modified CAR-T cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eg.\u003c/strong\u003e CD19 CAR-T cell-mediated killing of Raji red-luc cells evaluated with luminescence-based assay. Data are presented as averages from 4 technical replicates +/- sd.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eh, i.\u003c/strong\u003e Raji cells were inoculated into NSG (NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ) mice treated with CD19 CAR-T cells with or without Lip-1 i.p. injections. Tumor volume measurements are presented for each mouse (h). Event-free survival is presented on the Kaplan–Meier survival plot (i).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ej. \u003c/strong\u003ePD-L1 CAR-T cell-mediated killing of Raji cells overexpressing PD-L1 molecule upon iFSP1 pretreatment. CAR-T cells were pretreated with iFSP1 (20 µM) for 48 h then washed and seeded for 18 h with target cells at different E:T ratios. The graph presents data from one donor.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ek, l.\u003c/strong\u003e Seahorse analysis of control and iFSP1 (20 µM) pretreated T cells (48 h) using Seahorse XF T Cell Metabolic Profiling kit. \u003cstrong\u003ek.\u003c/strong\u003eKinetic graphs represent oxygen consumption rate (OCR) levels and extracellular acidification rate (ECAR) profiles of control and iFSP1-treated CAR-T cells. Data are presented as mean +/- sd of measurements performed on 2 donors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003el.\u003c/strong\u003e Bar graphs from Seahorse analysis representing mitochondrial (left panel) and glycolysis (right panel) ATP production levels in stimulated T cells pretreated with iFSP1 for 48 h.\u003c/p\u003e","description":"","filename":"UncroppedwesternblotsGPX4FSP1combo.docx","url":"https://assets-eu.researchsquare.com/files/rs-5280443/v1/ce3f1ba55f31fb47756d1572.docx"}],"financialInterests":"There is no duality of interest","formattedTitle":"GPX4 and FSP1, key ferroptosis regulators, are critical for T cell functions and CAR-T antitumor activity","fulltext":[{"header":"Introduction","content":"\u003cp\u003eFerroptosis has gathered increased attention as a promising anticancer strategy [1\u0026ndash;4]. It has been shown that manipulating lipid metabolism or redox balance can induce ferroptosis in various cancer types, including both solid tumors and hematological malignancies [5\u0026ndash;8].\u003c/p\u003e \u003cp\u003eFerroptosis is a free radical-mediated process that results in iron-dependent excessive oxidation and subsequent degradation of lipids containing polyunsaturated fatty acids (PUFA) [9]. In addition to an increased peroxidation of lipids in the cell membrane and an accumulation of labile iron pool inside the cell, ferroptosis is characterized by changes in the redox state, leading to increased production of reactive oxygen species (ROS) and a concomitant impairment of the cell's antioxidant defense systems [10]. To prevent excessive ferroptosis induction cells activate cyst(e)ine\u0026ndash;glutathione (GSH)\u0026ndash;glutathione peroxidase 4 (GPX4) axis as a key defense system. Recently however, ferroptosis suppressor protein 1 (FSP1)/coenzyme Q10 (CoQ10) has been identified as the second ferroptosis-suppressing system, which efficiently prevents lipid peroxidation independently of GPX4 [11].\u003c/p\u003e \u003cp\u003eWhile ferroptosis of tumor cells is widely studied, the effects of ferroptosis on immune cells, particularly in the tumor microenvironment (TME), still remain poorly understood. Recent evidence suggests that neutrophils within tumors can undergo spontaneous ferroptosis, suppressing T cell activity [12], while those at metastatic sites upregulate of ferroptosis-related genes, potentially indicating a defensive mechanism against ferroptosis. Notably, T cells are more prone to ferroptosis than neutrophils, as evidenced by lipidomic studies [13]. It has been also reported that T cells lacking GPX4 fail to expand and function upon activation and undergo ferroptosis [14].\u003c/p\u003e \u003cp\u003eGPX4 has been shown to control lipid oxidation to support T cell responses during viral infections [14]. Furthermore, in the TME, cystine consumption by tumor cells disrupts the cystine/glutamate exchange in CD8\u003csup\u003e+\u003c/sup\u003e T cells, leading to increased CD36 expression, fatty acids uptake, lipid accumulation, abnormal ROS production, and ultimately T cell exhaustion and ferroptosis [15\u0026ndash;17]. Consistently, blocking CD36-induced ferroptosis, in combination with immune checkpoint inhibitors, has been shown to enhance CD8\u003csup\u003e+\u003c/sup\u003e T cell anticancer activity [16]. On the other hand, CD8\u003csup\u003e+\u003c/sup\u003e T cells have been shown to promote ferroptosis in tumor cells by secreting interferon-γ (IFNγ) [18]. While T cells are critical for mounting the antitumor response, the metabolic requirements for maintenance and execution of effector functions are less well studied. These may be particularly important in the context of their antitumor activity, where T cells are first stimulated before interacting with cancer cells within the tumor niche [19].\u003c/p\u003e \u003cp\u003eTherefore, we addressed this issue and demonstrated that T cell stimulation affects the balance between processes that promote and protect against ferroptosis, thereby disrupting T cell homeostasis. Specifically, we observed a significant decrease in GPX4 expression and a corresponding increase in FSP1 protein levels following T cell stimulation. Our findings revealed that both T cells and CAR-T cells are susceptible to ferroptosis, with GPX4 inhibition reducing their antitumor responses. Although very effective in hematological malignancies, CAR-T therapy still faces several obstacles in eliminating solid tumors. One reason for this is the hostile, immunosuppressive tumor microenvironment (TME), characterized by chronic oxidative stress, that contributes to mitochondrial dysfunction, lipid peroxidation, and impaired antioxidant defense systems, all of which are metabolic features characteristic of ferroptosis. In this context, we show that inhibition of ferroptosis with liproxstatin 1 (Lip-1) protects CAR-T cells and improves the effective eradication of cancer cells, both \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e. One of our unexpected results was the identification of FSP1 as a novel regulator of T cell and CAR-T cell metabolism, proliferation, and antitumor efficacy, operating independently of its role in ferroptosis suppression.\u003c/p\u003e \u003cp\u003eOverall, our findings unveil a novel role for the ferroptosis-related proteins GPX4 and FSP1 in enhancing the cytotoxic potential of T cells against tumors. These mechanisms can operate through ferroptosis-dependent and -independent pathways, underscoring the complexity of ferroptosis regulation in cytotoxic cells.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCell lines\u003c/h2\u003e \u003cp\u003eRaji and MCF7 cell lines were purchased from ATCC or the European Collection of Cell Cultures (Wiltshire, UK). The cells were cultured in RPMI-1640 medium (Sigma-Aldrich, St Louis, MO, USA) supplemented with 10% fetal bovine serum (FBS) (Sigma-Aldrich), 2 mM L-glutamine (Sigma-Aldrich) and 1% antibiotics \u0026ndash; penicillin/streptomycin (Sigma-Aldrich) (referred as full RPMI medium) in a humidified atmosphere containing 5% CO\u003csub\u003e2\u003c/sub\u003e. All the cell lines were maintained through continuous passaging and were confirmed to be free of contamination with Mycoplasma spp. For luciferase-based assays cell lines (Raji and MCF7) were modified with plasmid pLenti7.3/V5 TOPO-RedLuc encoding the red luciferase gene and green fluorescent protein, as described previously [20].\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eReagents\u003c/h3\u003e\n\u003cp\u003eAll tested compounds GPX4 inhibitors: RSL3 (Selleckchem, S8155) and ML162 (Merck, SML2561), iFSP1 (Selleckchem, S9663), liproxstatin-1 (Merck, SML1414), liproxstatin-1 for \u003cem\u003ein vivo\u003c/em\u003e experiments (Chem-Norm, TBW04068), Z-VAD-FMK (Selleckchem, S7023), necrostatin-1 (Sigma, N9037) were dissolved in DMSO to obtain 10 mM stock solutions and kept at -20 or -80\u0026deg;C according to manufacturer\u0026rsquo;s recommendations. Further dilutions were performed in culture medium, directly before each experiment. Deferoxamine (Desferal, Novartis leftovers donated by patients) was dissolved in dH\u003csub\u003e2\u003c/sub\u003eO and was kept at -20\u0026deg;C.\u003c/p\u003e\n\u003ch3\u003eT cell isolation and stimulation\u003c/h3\u003e\n\u003cp\u003eHuman primary T cells were isolated from buffy coats of healthy donors obtained from the Regional Blood Center in Warsaw, Poland, with the knowledge of the Bioethics Committee at the Central Clinical Hospital of the Ministry of Interior and Administration in Warsaw (approved on 12/10/2022). Initially, mononuclear cells were isolated by density gradient centrifugation using Lymphoprep (STEMCELL Technologies Canada, Inc.). Subsequently, T cells were magnetically separated from mononuclear cells with negative selection using EasySep\u0026trade; Human T Cell Isolation Kit (STEMCELL Technologies Canada, Inc.). T cells were stimulated with the magnetic beads coated with monoclonal antibodies against CD3 and CD28 molecules (Dynabeads Human T-Activator CD3/CD28, Thermo Fisher Scientific) and were cultured in full RPMI medium supplemented with 100 U/mL of IL-2 (Peprotech). After 5 days the beads were removed and T cells were further cultured in the presence of IL-2 only.\u003c/p\u003e\n\u003ch3\u003eT cell viability assays\u003c/h3\u003e\n\u003cp\u003eUnstimulated T cells, stimulated T cells or CAR-T cells were treated with tested compounds for an indicated time, 24 or 48 h. Subsequently, the viability of the cells was assessed by propidium iodide (PI, 1 \u0026micro;g/mL, Sigma-Aldrich) staining, followed by flow cytometry analysis BD FACSCantoII and HTS sampler.\u003c/p\u003e\n\u003ch3\u003eT cell proliferation assay\u003c/h3\u003e\n\u003cp\u003eHuman primary T cells were resuspended in PBS (1 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e/ml) and stained with Cell Trace Violet (CTV) dye (Thermo Fisher Scientific) for 20 min at 37\u0026deg;C at a final CTV concentration of 2.5 \u0026micro;M. Subsequently, T cells were washed and seeded onto a 96-round-bottom plate (2 \u0026times; 10\u003csup\u003e4\u003c/sup\u003e cells per well) in full RPMI medium in the presence of IL-2 (100 U/mL), Dynabeads Human T-Activator CD3/CD28 (beads to cell ratio 2:1) and increasing concentrations of iFSP1 or RSL3 with or without Lip-1. After 3 and 6 days of incubation, the T cells were stained with DRAQ7 viability stain (BioLegend) and analyzed on BD FACSCantoII and HTS sampler.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eFlow cytometry staining\u003c/h2\u003e \u003cp\u003eExtracellular staining for surface antigen was performed in a staining buffer (PBS supplemented with 1mM EDTA and 2% FBS) for 20 min at room temperature onto a 96-round-bottom plate. For intracellular staining, the cells were fixed with BD Cytofix buffer, permeabilized with BD Perm/Wash buffer and stained at 4\u0026deg;C for 30 min. Next, cells were washed in Perm/Wash buffer, resuspended in staining buffer and analyzed with BD FACSCantoII and HTS sampler. Antibodies used for staining are listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFlow cytometry antibodies\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntibody\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFluorochrome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCatalog number\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCompany\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD71 (transferrin receptor) antibody\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAPC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17-0719-42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInvitrogen\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFerroportin/SLC40A1 antibody\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNBP1-21502PE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNovus Biologicals\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD340 (erbB2/HER-2) antibody\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAPC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e324408\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBioLegend\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003egoat anti-human IgG, Fcγ fragment specific antibody\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAF647\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e109-606-098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eJackson ImmunoResearch Labs\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eLipid peroxidation assay\u003c/h3\u003e\n\u003cp\u003eLipid peroxidation was evaluated in T cells either at a steady state or following RSL3 treatment using the fluorescent lipid peroxidation sensor named BODIPY 581/591 C11 (ThermoFisher). Briefly, T cells were seeded onto a 96-round-bottom plate at cell density 1 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e/ml and incubated with increasing concentrations of RSL3 in the presence or absence of Lip-1 for 20 h. The next day, T cells were centrifuged and resuspended in full RPMI medium containing 0.5 \u0026micro;M BODIPY 581/591 C11 reagent (100 \u0026micro;l/well) and incubated at 37\u0026deg;C for 30 min. Subsequently, the cells were washed three times and analyzed on BD FACSCantoII and HTS sampler. The level of lipid ROS was assessed as an increase in oxidized C11-BODIPY (green fluorescence).\u003c/p\u003e\n\u003ch3\u003eLabile iron pool detection\u003c/h3\u003e\n\u003cp\u003eIntracellular Fe\u003csup\u003e2+\u003c/sup\u003e level was evaluated with the fluorescent probe FerroOrange (Dojindo). The cells were seeded onto a 96-round-bottom plate at cell number 2 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e/well, washed three times with PBS, and then resuspended in HBSS buffer. In experiments with deferoxamine pretreatment, the cells were preincubated with 1 mM or 2 mM deferoxamine and incubated for 30 min at 37\u0026deg;C. Subsequently, 2 times concentrated FerroOrange probe was added to the wells at a final concentration of 1 \u0026micro;M and incubated for 30 min at 37\u0026deg;C. After incubation, cells were analyzed without washing on a BD LSRFortessa X20 instrument (BD Biosciences) and PE channel.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eIntracellular ROS detection\u003c/h2\u003e \u003cp\u003eIntracellular ROS were determined with fluorescent probes CellROX Deep Red and CellROX Green (Thermo Fisher Scientific). Briefly, T cells were seeded onto a 96-round-bottom plate at the density of 5 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e cells/mL and incubated with the CellROX Deep Red or CellROX Green reagent at 37\u0026deg;C, 5% CO\u003csub\u003e2\u003c/sub\u003e for 30 minutes. After washing, the cells were analyzed on a BD FACSCantoII flow cytometer (BD Biosciences).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eGSH detection\u003c/h2\u003e \u003cp\u003eTo determine GSH level in T cells the Intracellular glutathione (GSH) Detection Assay Kit (ab112132) was applied. Briefly, T cells were seeded onto a 96-round-bottom plate at cell density 1 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e/ml and incubated with Thiol Green fluorescent probe (diluted 1:10000) for 30 min at 37\u0026deg;C. After incubation, the cells were washed and analyzed using flow cytometry and green fluorescence.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eCAR constructs and lentiviral T cell modification\u003c/h2\u003e \u003cp\u003eIn this study, we utilized two CD19 CAR (FMC63 clone) constructs, generously provided by M. Pule from UCL, UK. The first construct includes the CD8 hinge and transmembrane domain, the 41BB costimulatory domain, the CD3ζ signaling domain, and the rituximab recognized-RQR8 epitope for CAR detection. The second CD19 CAR construct consists of the IgG1 half-hinge, the CD28 transmembrane and co-stimulatory domain, and CD3ζ. PD-L1-targeting CAR consists of an atezolizumab-based scFv sequence following an IgG1 half-hinge, CD28 transmembrane region, CD28 costimulatory domain, and CD3ζ signaling domain. HER2 CAR construct consists of a trastuzumab-based scFv sequence following a CD8 hinge and transmembrane domain and a 4-1BB-CD3ζ signaling tail. All constructs were subcloned into the lentiviral pSEW plasmid. T cells were modified with the CAR constructs using a lentiviral transduction system as described previously [21]. The CAR expression on the surface of the T cells was evaluated by flow cytometry 48\u0026ndash;72 h after transduction as described in [21].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eRTCA-based killing assay\u003c/h2\u003e \u003cp\u003eThe HER2 CAR-mediated killing of T cells was monitored with a real-time cell analysis (RTCA) assay. Adherent target MCF7 cells (3 \u0026times; 10\u003csup\u003e4\u003c/sup\u003e cells/well) were seeded onto 16-well E-Plate (ACEA Biosciences) in 150 \u0026micro;l of a full RPMI medium. The proliferation of MCF7 cells was monitored in the incubator at 37\u0026deg;C (5% CO\u003csub\u003e2\u003c/sub\u003e, 95% humidity) for 24 h with the xCELLigence impedance-based RTCA system (ACEA Biosciences). The next day, 100 \u0026micro;l of the medium was aspirated and replaced with the full RPMI medium containing effector cells (control unmodified T cells or HER2 CAR-T cells) at effector to target ratio E:T 2:1. T cells and CAR-T cells were pretreated with increasing concentrations of RSL3 for 5 h and transferred onto target cells without washing out the RSL3-containing medium. The CAR-mediated killing of target cells was monitored for the next 12 h. Analysis was performed using RTCA Software Pro (ACEA Biosciences). The impedance changes (cell index) were normalized to the end value of the target cells' proliferation and plotted over time as normalized cell index.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eLuciferase-based cytotoxicity assay\u003c/h2\u003e \u003cp\u003eCell lines previously modified to express the luciferase reporter gene (Red-Luc), were seeded onto the 96-well black plates with a clear bottom (Perkin Elmer) at a cell density of 3 \u0026times; 10\u003csup\u003e4\u003c/sup\u003e per well in 100 \u0026micro;l of full RPMI in three or four technical replicates. MCF-7 cells were allowed to adhere for 24 h while suspension Raji cells were directly used in the experimental procedures. For cytotoxicity assays, increasing concentrations of RSL3 or iFSP1 were added to the wells and the cells were incubated for 48 h. For luciferase-based killing assays, effector CAR-T cells and control unmodified T cells were added to the wells at different E:T ratios and were cocultured for the next 18 h. For bioluminescence readout Bright-Glo\u0026trade; Luciferase Assay System (E2610, Promega) was used. The plate was incubated for 5 min in darkness at room temperature and luminescence was measured using Tecan INFINITE M1000 (TECAN).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eFlow cytometry-based killing assay\u003c/h2\u003e \u003cp\u003ePD-L1 CAR-T cells were pretreated with or without 20 \u0026micro;M iFSP1 for 48 h. For cytotoxicity assay, a target (Raji PD-L1) cells were stained with Cell Trace Violet (CTV) and seeded onto the 96-well plate at a cell density of 1 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e per well in 100 \u0026micro;l of full RPMI in two technical replicates. Next, PD-L1 CAR-T cells were added for 24 h at E:T ratios 0.25:1, 0.5:1 and 1:1. Propidium iodide (PI) was used to discriminate live/dead cells. Cytotoxicity of effector cells was evaluated as an increase in a percentage of violet-CTV positive, PI positive target cell population.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eDegranulation and cytokine production assay\u003c/h2\u003e \u003cp\u003eBefore degranulation and cytokine production assay CAR-T cells were preincubated with either RSL3 for 16 h or iFSP1 for 24 h. The next day, tumor cells expressing recognized antigen on the surface were added to appropriate wells at E:T (effector to target) ratio 0.25:1 and 1:1. CD19 CAR-T cells were incubated with Burkitt\u0026rsquo;s lymphoma cell line Raji (CD19\u003csup\u003e+\u003c/sup\u003e), HER2 CAR-T cells with breast cancer cell line MCF7 (low HER2\u003csup\u003e+\u003c/sup\u003e) and PD-L1 CAR-T cells with Raji cells, genetically modified to overexpress PD-L1 molecule [21]. Subsequently, Golgi Stop (BD Biosciences, dilution 1:250), Golgi Plug (BD Biosciences, dilution 1:200) and anti-CD107a-PE antibody (BD Biosciences, dilution 1:40) were added and the assay plate was incubated for 4 h at 37\u0026deg;C and 5% CO\u003csub\u003e2\u003c/sub\u003e. After incubation, the cells were stained with anti-CD3-BV421 antibody and Fixable viability stain 510 (BD Biosciences, dilution 1:200) followed by fixation and permeabilization procedures. Eventually, the cells were stained for cytokines with anti-IFNy-APC (BD Biosciences, dilution 1:100) and anti-TNFα-PECy7 (BD Biosciences, dilution 1:100) antibodies. Degranulation and cytokine production by effector cells was assessed using flow cytometry.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eSeahorse analysis\u003c/h2\u003e \u003cp\u003eCell metabolism was measured using Seahorse XF HS Mini Analyzer (Agilent). Seahorse analysis was performed on T cells and CAR-T cells pretreated with iFSP1. Stimulated T cells or CAR T cells were seeded onto a 24-well plate with 20 \u0026micro;M of iFSP1 and incubated for 48 h. iFSP pretreated T/CAR T cells were subsequently resuspended in Agilent Seahorse XF RPMI medium, pH 7.4 supplemented with Agilent Seahorse XF glucose (10 mM) and glutamine (2 mM) solutions and seeded at 2 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e cells/well onto Agilent Seahorse XFp PDL Cell Culture Miniplates. Metabolic parameters were measured under basal conditions upon treatment with oligomycin A (1.5 \u0026micro;M), BAM15 (2.5 \u0026micro;M) and rotenone/antimycin A (0.5 \u0026micro;M each) (Seahorse XF T Cell Metabolic Profiling Kit, Agilent). All steps were performed following the manufacturer\u0026rsquo;s recommendations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eWestern Blotting\u003c/h2\u003e \u003cp\u003eFor Western blotting, cells were lysed with RIPA lysis buffer (Tris-HCL pH 7.4, NaCl 150 mM, NP-40 1% (v/v), sodium deoxycholate 1% (v/v), SDS 0.1% (v/v)) supplemented with Complete Protease Inhibitor Cocktail and Phosphatase Inhibitor Cocktail (Roche Diagnostics). Protein concentration was measured using the Pierce\u0026trade; Rapid Gold BCA Protein Assay Kit (Thermo Fisher Scientific) according to the manufacturer's instructions with minor modifications on the TECAN Infinite M1000 Pro microplate reader. 20 \u0026micro;g of cell lysates were separated in 10, 12 or 15% (v/v) (depending on the molecular weight of detected protein) reducing SDS-polyacrylamide gel, then transferred onto nitrocellulose membranes and blocked with either 5% (w/v) nonfat milk or 5% Bovine Serum Albumin (w/v) (Kenilworth) in TBST (Tris-buffered saline, pH 7.4 and 0.05% (v/v) Tween-20) and then incubated with the following primary antibodies: anti-GPX4 (Cell Signaling cat. 52455S, dilution 1:1000), anti-FSP1 (Abcam cat. ab302673, dilution 1:1000), anti-ACSL4 (Santa Cruz cat. sc-271800, dilution 1:1000), anti-LOX15 (Abclonal cat. A6864, dilution 1:1000), anti-LC3 (Cell Signaling cat. 4108, dilution 1:1000), anti-perforin (MABTECH cat. Pf-344, dilution 1:1000), and anti-β-actin-HRP (A222, Sigma-Aldrich; dilution 1:50,000). For detection of primary protein bands HRP-conjugated secondary antibodies were used. The blots were exposed to the Super Signal chemiluminescent substrates (Thermo Fisher Scientific). The signal was detected using the ChemiDoc Imaging System (Bio-Rad ChemiDoc MP Imaging System).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eAnimal studies\u003c/h2\u003e \u003cp\u003eAll \u003cem\u003ein vivo\u003c/em\u003e experiments were performed with 8\u0026ndash;12-week old male NSG (NOD.Cg-\u003cem\u003ePrkdc\u003c/em\u003e\u003csup\u003e\u003cem\u003escid\u003c/em\u003e\u003c/sup\u003e\u003cem\u003eIl2rg\u003c/em\u003e\u003csup\u003e\u003cem\u003etm1Wjl\u003c/em\u003e\u003c/sup\u003e/SzJ) mice obtained from Charles River Laboratories, which were bred at the Animal Facility of the Mossakowski Medical Research Institute, Polish Academy of Sciences. All experiments were performed in accordance with the guidelines and approved by The Second Local Ethics Committee for the Animal Experimentation, Warsaw University of Life Sciences (number: WAW2/100/2023, WAW2/027/2024). The experiments were carried out in an SPF animal facility with IVC systems. To avoid confounders, all mice were labeled and kept in tagged cages. The cages had an assigned, unchanging place in the rack. Results obtained from individual mice according to the treatment method are presented. The blinding was not applied. The distribution of mice to the experimental groups was random and no animals were excluded during the experiment. The sample size was determined based on the assumed increase in tumor diameter. The experimental group size was calculated by power analysis (for assumed test power 80%) or resource equation approach as described in [22].\u003c/p\u003e \u003cp\u003e \u003cb\u003eIn vivo\u003c/b\u003e \u003cb\u003eexperiment\u003c/b\u003e\u003c/p\u003e \u003cp\u003eMice were inoculated subcutaneously with 2 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e Raji cells in 50% Matrigel Growth Factor Reduced (Corning) on day 0 of the experiment. Subsequently, on days 4, 7, 10, and 13, 5 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e CD19 CAR-T cells were administrated intravenously. Liproxstatin-1 (Chem-Norm) was injected intraperitoneally with 10 mg/kg every day or every other day for 2 consecutive weeks. Control mice received medium or solvent respectively. Tumor growth was monitored three times per week with caliper starting from day 7 of the experiment. Tumor volume was calculated according to the formula volume (mm\u003csup\u003e3\u003c/sup\u003e)= (width\u003csup\u003e2\u003c/sup\u003e [mm] \u0026times; length [mm])/2. Mice were sacrificed when the tumor diameter reached 15 mm in at least one dimension. Total number of mice used within this study was 37.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eRNAseq and bioinformatics analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eRNAseq analysis was done using the dataset - GSE 59846, which comprises expression data for two cell types - CD4\u003csup\u003e+\u003c/sup\u003e na\u0026iuml;ve and CD4\u003csup\u003e+\u003c/sup\u003e memory T-cells, each derived from 3 individuals. Each cell type was additionally stimulated for 48 h using beads coated with monoclonal antibodies against the CD3 and CD28. Thus, 12 RNA-seq experiments were carried out; however, due to possible mislabeling of two runs - SRR1531315 and SRR1531316, we excluded them from the downstream analysis. Initially, we assessed library quality with FastQC [23] (v. 0.11.9). Next, trimmomatic [24] (v. 0.39) was used to trim fragments of reads from the 3\u0026rsquo; and 5\u0026rsquo; ends if their average quality fall below 30. Additionally, reads shorter than 40 bp were excluded at this stage. Processed reads were mapped to the human genome (GRCh38) using the align function available from the Rsubread package [25] (v. 2.12.3). Samtools [26] (v. 1.10) was used to remove unmapped reads. The number of reads associated with human genes, as defined in the Gencode GTF annotation file V40, was calculated using the featureCounts function from the Rsubread package and converted to counts per million (in log2 scale). The differential gene expression analysis was carried out using the limma program [27] (v. 3.54.2) for samples divided into two groups \u0026lsquo;stimulated\u0026rsquo; or \u0026lsquo;unstimulated\u0026rsquo; (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). P-values were adjusted for multiple tests with the Benjamini\u0026ndash;Hochberg procedure. All analyses were carried out in R (v. 4.2.2). Results of the statical test are shown as * for p-value\u0026thinsp;\u0026le;\u0026thinsp;0.1, ** p-value\u0026thinsp;\u0026le;\u0026thinsp;0.05; ***, p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.01.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSample labelling in RNAseq reanalysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSource name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eActivation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDonor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFinal label\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSRR1531325\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMemory CD4 T cell\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003estimulated\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSRR1531324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMemory CD4 T cell\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003estimulated\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSRR1531323\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMemory CD4 T cell\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eunstimulated\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSRR1531322\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMemory CD4 T cell\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eunstimulated\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSRR1531321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNaive CD4 T cell\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003estimulated\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSRR1531320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNaive CD4 T cell\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003estimulated\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSRR1531319\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNaive CD4 T cell\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eunstimulated\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSRR1531318\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNaive CD4 T cell\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eunstimulated\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSRR1531317\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMemory CD4 T cell\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003estimulated\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSRR1531314\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNaive CD4 T cell\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eunstimulated\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eStatistical analysis was performed with GraphPad Prism 9 (GraphPad Software). To determine data distribution, the Shapiro-Wilk normality test was performed. If data passed the normality test, parametric statistics were used. In all analyses, the tests were two-tailed. For comparison between 2 groups either unpaired or paired t-test was performed, depending on data sets. For the differences between three or more independent groups one-way ANOVA was applied, followed by multiple comparisons tests. For comparison differences between groups with two independent variables, twoway ANOVA with post hoc analysis was performed. All statistically significant differences (p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and their p-values were marked on the graphs. Non-significant differences with p-value\u0026thinsp;\u0026ge;\u0026thinsp;0.05 were marked as ns. Data are represented as means with standard deviation. Each dot on the graphs represents the average of 2 technical replicates for a particular donor.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eT cell stimulation rewires iron and redox homeostasis of T cells\u003c/h2\u003e \u003cp\u003eTo understand the metabolic consequences of T cells\u0026rsquo; stimulation, we assessed iron homeostasis and the expression of iron homeostasis regulators, including transferrin receptor (CD71) as an iron importer and ferroportin (FPN1), a protein responsible for exporting Fe\u003csup\u003e2+\u003c/sup\u003e from the cell. Following stimulation, CD71 protein expression level increased significantly and remained elevated in stimulated T cells compared to unstimulated ones (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). This effect was accompanied by an increase in FPN1 protein level, likely serving as a protective mechanism against toxic iron overload (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). Over time of culture, the level of both CD71 and FPN1 noticeably dropped, but remained elevated as compared with unstimulated T cells. In consequence, following T cell stimulation we observed an increased level of the intracellular labile iron pool (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec) that remained elevated even for long-term culture and was only decreased upon deferoxamine treatment, a Fe\u003csup\u003e2+\u003c/sup\u003e chelator (Suppl. Figure\u0026nbsp;1a).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAnother observed consequence of T cell stimulation was redox homeostasis disturbance. To analyze it thoroughly, we assessed ROS levels with the CellROX Deep Red probe, for preferential detection of cytoplasmic and mitochondrial ROS (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed), and the CellROX Green reagent (Suppl. Figure\u0026nbsp;1b) to detect primarily nuclear-localized ROS. Upon stimulation, we observed an increase in ROS levels in stimulated T cells, although there was no widespread accumulation of ROS. Since ROS are short-lived molecules, the transcriptional activation of antioxidant enzymes can serve as a marker of defense against elevated intracellular ROS levels. Therefore, we reanalyzed RNAseq data in activated CD4\u003csup\u003e+\u003c/sup\u003e T cells and observed, in comparison to unstimulated counterparts, an increased expression of transcripts encoding antioxidant defense enzymes, including members of the peroxiredoxin and thioredoxin families (Suppl. Figure\u0026nbsp;1c). Besides enzymatic antioxidant defense, the increased production of ROS is also balanced by reduced glutathione (GSH), the most abundant nonprotein thiol in mammalian cells. Therefore, we examined intracellular GSH levels and observed that stimulated T cells exhibited higher GSH levels compared to their unstimulated counterparts (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee). We also found that GSH- and glutathione peroxidases (GPXs)related genes, described as associated with ferroptosis [28], were up-regulated in stimulated T cells including transcripts for GSS, CHAC1, GPX4 (Suppl. Figure\u0026nbsp;1d). Since GSH synthesis depends on the availability of cysteine that in the cell is derived from the reduction of cellular cystine imported into the cells through the xc- system, a cystine-glutamate exchanger [29], we subsequently examined the expression of components of the xc- system and found upregulated expression of transcripts for SLC3A2 and SLC7A11 in stimulated CD4\u003csup\u003e+\u003c/sup\u003e T cells (Suppl. Figure\u0026nbsp;1e), altogether supporting that stimulation of T cells induces ROS and antioxidant defense systems.\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eT cell stimulation promotes lipid peroxidation\u003c/h2\u003e \u003cp\u003eGiven that ferrous iron (Fe\u003csup\u003e2+\u003c/sup\u003e) and hydrogen peroxide (H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e) can react in a process known as the Fenton reaction and generate peroxidized lipids [10], we subsequently assessed their levels in cell membranes. Upon stimulation, we observed a significant increase in the accumulation of peroxidized lipids in T cell membranes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ef) that remained elevated over the prolonged culture, as determined by C11-BODIPY\u0026trade; 581/591 staining. Since lipid peroxidation is a marker of ferroptotic death, in the next steps we assessed the main pathways involved in the regulation of ferroptosis. The ACSL4\u0026ndash;LPCAT3\u0026ndash;LOX signaling axis is an intracellular pathway known to promote lipid peroxidation of membrane phospholipids (PLs) containing PUFAs and has been identified as one of the components crucial for ferroptosis execution [30\u0026ndash;32]. We examined the expression of ACSL4 and observed its elevation in stimulated T cells both at mRNA (Suppl. Figure\u0026nbsp;1f) and protein (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eg) levels. Also, the mRNA expression for LPCAT3 transcript significantly increased upon T cell stimulation (Suppl. Figure\u0026nbsp;1f). Furthermore, we assessed by Western blotting the protein level of LOX15 that acts as a key ferroptosis-promoting factor by directly oxidizing arachidonoyl (AA) and adrenoyl (AdA) phospholipids (PE) into lipid hydroperoxides [33]. While we observed a decrease of LOX15 in T cells after stimulation, in long-term culture LOX15 levels were reversed to some extent (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eg). Finally, we examined the expression of two master ferroptosis suppressors, GPX4 and FSP1. In accordance with the accumulation of lipid peroxides upon TCR stimulation, a significant decrease of GPX4, as assessed by Western blotting was detected in subsequent days after stimulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eh, Suppl. Figure\u0026nbsp;1g). Surprisingly, however, FSP1 expression was significantly increased upon stimulation of T cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eh, Suppl. Figure\u0026nbsp;1g).\u003c/p\u003e \u003cp\u003eIn summary, our findings at this step demonstrate that stimulation of T cells substantially disturbs lipid, iron and redox homeostasis that is evidenced by an increased load of labile iron pool, as well as elevated ROS and lipid peroxidation levels. Moreover, T cells upon stimulation downregulate GPX4 and upregulate ACSL4 that are both ferroptosis-promoting effects. At the same time, stimulation of T cells activates the program that confers protection against ferroptosis and includes LOX15 decrease and increase of FSP1. Given these disturbances, we hypothesized that stimulation of T cells changes the balance of ferroptosis-promoting and protecting events and can therefore impair T cell homeostasis. To verify this hypothesis, we employed several inhibitors of GPX4 and FSP1, as two primary regulators protecting cells from ferroptosis and subsequently determined their influence on T cells\u0026rsquo; viability, functions and metabolism.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eGPX4 orchestrates T cells and CAR-T cells' sensitivity to ferroptosis\u003c/h2\u003e \u003cp\u003eWhile unstimulated T cells remained relatively resistant to GPX4 inhibitors (RSL3 or ML162), as demonstrated by their viability (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea, Suppl. Figure\u0026nbsp;2a) and lipid peroxidation (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb), T cells after stimulation acquired sensitivity to inhibition of GPX4 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec, Suppl. Figure\u0026nbsp;2b). Decreased viability of stimulated T cells was reversible with Lip-1, a ferroptosis-specific inhibitor, as determined by propidium iodide staining followed by flow cytometry analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec, Suppl. Figure\u0026nbsp;2b). Consistently with the sensitivity of T cells to ferroptosis, a significant increase in lipid peroxidation measured by C11-BODIPY\u0026trade; 581/591 staining, reversible by Lip-1, was observed in stimulated T cells, particularly when exposed to higher concentrations of RSL3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed). In contrast, even if some toxicity of GPX4 inhibitors was observed in higher doses in unstimulated T cells, it was not abrogated by Lip-1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea, Suppl. Figure\u0026nbsp;2a). Additionally, we noticed that stimulated T cells up to 2 weeks after stimulation were relatively insensitive to ferroptosis (Suppl. Figure\u0026nbsp;2c, d) and increasing concentrations of RSL3 did not trigger their lipid peroxidation (Suppl. Figure\u0026nbsp;2e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo check whether other types of cell death are induced in T cells by inhibiting GPX4 activity, we employed the pan-caspase apoptosis inhibitor Z-VAD-fmk (Z-VAD), and necroptosis inhibitor necrostatin-1 (Nec-1). They both did not confer protective effects on stimulated T cells incubated with a toxic dose of RSL3 (Suppl. Figure\u0026nbsp;2f). We also conducted a Western blot analysis to evaluate the LC3 protein, recognized as an indicator of autophagy. This was prompted by research suggesting that the initiation of autophagy could potentially influence the onset of ferroptosis [34]. Up to a week following T cell stimulation, we detected increased LC3 protein levels in T cells\u0026rsquo; lysates, which was in line with previous research demonstrating that TCR activation triggers autophagy in T cells [35]. However, there was a noticeable decrease in LC3 protein levels in subsequent days of T cell culture, suggesting a lack of involvement of autophagy in mediating the ferroptosis of T cells (Suppl. Figure\u0026nbsp;2g).\u003c/p\u003e \u003cp\u003eWe also checked the influence of GPX4 inhibition on the proliferation potential of T cells upon stimulation. To this end, T cells were stimulated with anti-CD3/CD28 antibodies in the presence of increasing concentrations of RSL3. After 3 days of stimulation, in the highest tested RSL3 doses we observed some shifts in the peaks corresponding to the inhibition of the proliferation. However, these changes were not reversible by Lip-1 and were further mitigated by day 6 of the culture (Suppl. Figure\u0026nbsp;2h).\u003c/p\u003e \u003cp\u003eAltogether, our results at this step show that GPX4 inhibition sensitizes T cells and CAR-T cells to ferroptosis in a manner reversible by Lip-1. Nevertheless, although stimulated T cells are initially resistant to ferroptosis, they acquire over time the sensitivity to ferroptosis-inducing agents, a phenomenon accompanied by GPX4 downregulation, ACSL4 upregulation and re-expression of LOX15.\u003c/p\u003e \u003cp\u003eMoreover, CD19 CAR-modified T cells and their unmodified counterparts were highly sensitive to RSL3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee). Their decreased viability was almost completely reversible by Lip-1 further confirming that GPX4 inhibition also sensitizes CAR-T cells to ferroptosis.\u003c/p\u003e \u003cp\u003e \u003cb\u003eGPX4 inhibitors impair T cell functions\u003c/b\u003e \u003cb\u003ein vitro\u003c/b\u003e \u003cb\u003eand\u003c/b\u003e \u003cb\u003ein vivo\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo understand the functional consequences of increased sensitivity of T cells to ferroptosis, we assessed the influence of GPX4 inhibitors on CAR-T cells\u0026rsquo; cytotoxic activity. To this end, the ability of HER2 CAR-T cells to kill target MCF7 tumor cells was assessed in the presence of increasing concentrations of RSL3 by RTCA, an impedance-based technology used for label-free and real-time monitoring of cytotoxicity. For these experiments, we selected RSL3 concentrations that were non-toxic to CAR-T cells and only CAR-T cells with at least 80% viability were included in the RTCA analysis (Suppl. Figure\u0026nbsp;3a, left panel). We observed that the killing ability of RSL3-pretreated HER2 CART cells against the MCF7 cell line was impaired compared to the untreated control (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef) and unmodified T cells (Suppl. Figure\u0026nbsp;3b) and was further reversed by 24-hour pretreatment of CAR-T cells with Lip-1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef) that preserved CAR-T cell viability (Suppl. Figure\u0026nbsp;3a, right panel). Moreover, we confirmed that the viability of MCF7 cells alone in the presence of RSL3 or combination with Lip-1 was unaffected (Suppl. Figure\u0026nbsp;3c). In addition, to exclude the target antigen loss on cancer cells in response to RSL3 treatment, we also verified that the HER2 antigen expression on MCF7 cells remained unchanged following the RSL3 treatment (Suppl. Figure\u0026nbsp;3d).\u003c/p\u003e \u003cp\u003eWe further evaluated the influence of RSL3 on the degranulation of CAR-T cells (CD107a staining), as well as the cytokine production. In these experiments, CAR-T cells targeting CD19, PD-L1 or HER-2 were cultured with cancer cells expressing the corresponding antigens, in the presence of RSL3 at concentrations not toxic to cancer cell lines (Suppl. Figure\u0026nbsp;3e). Our findings demonstrated that pretreatment of CAR-T cells with RSL3 reduced their ability to degranulate in response to cognate target cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eg) and to produce IFNγ and TNFα (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eh).\u003c/p\u003e \u003cp\u003eFinally, we sought to determine the role of ferroptosis \u003cem\u003ein vivo\u003c/em\u003e and its influence on the efficacy of CAR-T immunotherapy (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ei). To this end, CD19 CAR-T cells generated from two healthy donors\u0026rsquo; T cells (referred to as donor 4 and donor 5) were intravenously injected into the mouse tail vein in the human-to-mouse Raji xenograft model. Before \u003cem\u003ein vivo\u003c/em\u003e experiments, the percentage of T cell modification with CAR construct (Suppl. Figure\u0026nbsp;3f) and cytotoxic activity of CD19 CAR-T cells against Raji cells were assessed \u003cem\u003ein vitro\u003c/em\u003e (Suppl. Figure\u0026nbsp;3g). While CD19 CAR-T cells from both donors efficiently and comparably killed tumor cells \u003cem\u003ein vitro\u003c/em\u003e, they differed in the potential to eradicate tumors \u003cem\u003ein vivo\u003c/em\u003e. In particular, donor 5-derived CD19 CAR-T cells significantly inhibited Raji tumor growth (Suppl. Figure\u0026nbsp;3h) and prolonged mouse survival (as assessed by reaching the predefined tumor volume) (Suppl. Figure\u0026nbsp;3i). Simultaneously, donor 4-derived CD19 CAR-T cells failed to do so, as compared with controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ek). Interestingly, tumor eradication by donor 4 CD19 CAR-T cells was potentiated by Lip-1, as assessed by tumor volume (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ek) and mouse survival (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003el). Importantly, Lip-1 alone did not affect tumor cell growth compared to untreated control mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ej).\u003c/p\u003e \u003cp\u003eTaken together, our findings provide compelling evidence that ferroptosis, induced either by pharmacological inactivation of GPX4 \u003cem\u003ein vitro\u003c/em\u003e or occurring naturally within the TME \u003cem\u003ein vivo\u003c/em\u003e, significantly influences the functionality and cytotoxic activity of CAR-T cells. Furthermore, we also demonstrated that inhibiting ferroptosis using its specific inhibitor, Lip-1, can effectively protect CAR-T cells and enable the effective eradication of cancer cells.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003ch2\u003eFSP1 regulates T cell antitumor activity independently of ferroptosis-suppressive function\u003c/h2\u003e \u003cp\u003eTo understand more globally the role of ferroptosis in the modulation of T cell function, we further investigated the FSP1 pathway as a key component of a nonmitochondrial CoQ antioxidant system that acts in parallel to the canonical glutathione-based GPX4 pathway. To this end, we employed iFSP1, an inhibitor that regulates the human FSP1 protein by binding to residue F360 within it [36]. We observed that iFSP1 further potentiated ferroptosis of T cells induced by GPX4 inhibition (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). Simultaneously, both T cells and CAR-T cells remained completely insensitive to single treatment with iFSP1, as determined by propidium iodide staining followed by flow cytometry analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). To our surprise, however, inhibition of FSP1, although not toxic to T cells, significantly affected the cytotoxic potential of CAR-T cells (both CD19- and PD-L1 CAR-T cells) and their ability to kill target tumor cells (Raji and Raji cells overexpressing PD-L1, respectively). This impairment was visible over the tested range of iFSP1 concentrations (2.5\u0026ndash;40 \u0026micro;M), for different E:T ratios and when assessed by either luminescence assay (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec) or by flow cytometry (Suppl. Figure\u0026nbsp;3j). Interestingly, the inhibitory effect iFSP1 was nor reversible by Lip-1, suggesting that FSP1 plays a regulatory role in T cells independently of its ferroptosis-suppressive function (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec). To better understand the functional consequences of FSP1 inhibition in T cells, we further evaluated their degranulation, as well as production of cytotoxic molecules (perforin) and cytokines (IFNγ and TNFα) in the presence of increasing concentrations of iFSP1. While degranulation, measured by CD107a staining, was not affected by iFSP1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed, left panel), perforin levels (assessed by Western blotting, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee) and cytokine amounts (determined by flow cytometry, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee, middle and right panels) were substantially reduced.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAt this step, we concluded that FSP1 is a novel regulator of T cells and CAR-T cells function needed for their antitumor activity. We observed that FSP1 is strongly upregulated in T cells upon stimulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eh), and its inhibition has a profound suppressive effect on their cytotoxic potential, correlated with decreased perforin levels and cytokine production.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003eFSP1 inhibition changes T cell metabolism and suppresses proliferation\u003c/h2\u003e \u003cp\u003eGiven that IFNγ and perforin production by T cells are strongly dependent on their metabolic state, we further explored the metabolic fitness of CAR-T cells following iFSP1 treatment. The oxygen consumption rate (OCR) for mitochondrial respiration and the extracellular acidification rate (ECAR) for glycolysis were detected by the Seahorse XF analyzer. Our findings demonstrated a substantial decrease in OCR (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ef, left) and decreased mitochondrial ATP production (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eg, left) after 24 hours of iFSP1 treatment when compared to untreated control cells. Surprisingly, upon treatment with iFSP1, neither ECAR (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ef, right) nor the glycolytic pool of ATP (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eg, right) were affected. Similar metabolic changes were observed in iFSP1-treated T cells, as seen in CAR-T cells (Suppl. Figure\u0026nbsp;3k, l).\u003c/p\u003e \u003cp\u003eAlthough much of the attention on metabolic reprogramming in activated T cells has focused on the engagement of aerobic glycolysis, recent research has revealed the importance of mitochondrial-driven activities in this process [37\u0026ndash;39]. In addition to energy production, the electron transport chain is a major source of ROS, which are important for T cell responses and proliferation. Therefore, given the observed changes in OCR and mito ATP pool upon iFSP1 treatment, we subsequently investigated the influence of iFSP1 on the proliferation of T cells. To this end, T cells isolated from healthy donor buffy coats were stained with CTV, stimulated with anti-CD3/CD28 antibodies, treated with iFSP1 and monitored for the proliferation capacity by flow cytometry. After 3 days of stimulation, only higher concentrations of iFSP1 (10\u0026ndash;40 \u0026micro;M) delayed the proliferation (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eh, left), while after 6 days of stimulation, the impaired proliferation was easily observed over the tested range of iFSP1 concentrations (2.5\u0026ndash;40 \u0026micro;M), as compared to control cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eh, right). Interestingly, this antiproliferative activity of iFSP1 was not reversible by Lip-1, further confirming that FSP1 in T cells plays a non-canonical role independently of its ferroptosis-suppressor function.\u003c/p\u003e \u003cp\u003eIn summary, we concluded from these experiments that FSP1 is a novel, so far not described, regulator of T cell metabolism and proliferation. Inhibition of FSP1 results in decreased mitochondrial ATP production in T cells that in consequence leads to the impairment of their proliferation and decreased antitumor cytotoxic potential.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eFerroptosis has recently emerged as an iron-dependent form of regulated cell death that can be induced to overcome the resistance of the tumor cells to existing conventional therapies. An important role in the susceptibility of cancer cells to ferroptosis is played by TME, a multifaceted ecosystem composed of tumor cells, stroma cells and various immune cells. It has been shown that various cellular components of TME (neutrophils, T cells), as well as secreted cytokines (IFNγ, TGFβ1) and metabolic changes (acidosis), have a ferroptosis-promoting role. On the other hand, while the sensitivity of tumor cells to ferroptosis is widely studied, limited data is available for the immune cells. Therefore, in this study, we have addressed this issue by comprehensively characterizing ferroptosis markers in T cells. We demonstrated that stimulated, but not unstimulated T cells, showed hallmarks of ferroptosis [40]. These included an elevated intracellular labile iron pool, increased expression of the iron importer CD71, and an increase of ROS levels [41, 42]. In consequence, in stimulated T cells we observed an increased accumulation of peroxidized lipids, that was mitigated specifically by Lip-1, but not inhibitors of other cell death types, further confirming the ferroptotic type of death. While several studies have demonstrated that T cells are relatively resistant to ferroptosis, other research has found T cells to be vulnerable to this form of cell death. Our results are in accordance with other reports, where it has been shown that CD8\u003csup\u003e+\u003c/sup\u003e tumor-infiltrating lymphocytes (TILs) displayed significant amounts of lipid peroxidation [43]. It has been also demonstrated that CD8\u003csup\u003e+\u003c/sup\u003e T cells can undergo ferroptosis, particularly through mechanisms involving CD36-associated fatty acid intake leading to lipid peroxidation [16, 17]. It was also shown that sensitivity to ferroptosis differs across T cells\u0026rsquo; subsets. For example, follicular helper CD4\u003csup\u003e+\u003c/sup\u003eT cells were demonstrated to be highly susceptible to ferroptosis due to altered mitochondrial morphology and excessive lipid ROS [44]. Moreover, the deficiency of GPX4 leads to the elimination of a significant portion of memory CD4\u003csup\u003e+\u003c/sup\u003e T cells, indicating their susceptibility to ferroptosis [14]. In contrast, Tregs show limited lipid peroxidation compared to tumor-specific CD8\u003csup\u003e+\u003c/sup\u003e T cells and induction of GPX4 expression upon TCR triggering protects them from ferroptosis [43]. However, GPX4 deletion in Tregs can activate ferroptosis, promote IL-1β production, and enhance Th17 cell responses, thereby enhancing antitumor immunity and inhibiting tumor growth [45]. Moreover, Wang et al. demonstrated that RSL3 and erastin treatment did not affect the survival of naive and shortly stimulated T cells, irrespectively of the presence of a ferroptosis inhibitor, whereas they have shown that immunotherapy-activated CD8\u003csup\u003e+\u003c/sup\u003e T cells induce ferroptosis in tumor cells [18].\u003c/p\u003e \u003cp\u003eThe sensitivity of T cells to ferroptosis can have important therapeutic consequences. We demonstrated that GPX4 is essential for the activity of CAR-T cells, as shown by impaired degranulation, cytokine production and killing potential upon RSL3-evoked GPX4 inhibition. This phenomenon was mitigated in the presence of Lip-1 and remained in accordance with a report by Drijvers et al.. They reported that the inhibition of GPX4 impaired the OT-1 T cells' antigen-specific killing of cancer cells, and this effect was rescued by ferroptosis inhibitors, vitamin E and ferrostatin-1. We observed that in contrast to T cells in which sensitivity changed in the course of time, CAR-T cells were susceptible to ferroptosis already shortly after CAR modification. It is probably related to the CAR-T cell preparation process itself which requires twofold stimulation: firstly, associated with preparing the cells to introduce the plasmid encoding the CAR receptor, and secondly, subsequent stimulation with CD3/CD28 beads for their expansion. It is worth noting that the repeated antigen stimulation of CAR-T cells can trigger activation-induced cell death (AICD), which can subsequently reduce the persistence of CAR-T cells and may impact their ability to eliminate tumor cells [46]. Here, we hypothesize that activation-induced ferroptosis is one of the mechanisms regulating T cells\u0026rsquo; fate, maintaining T cell homeostasis and therefore contributing to the termination of cellular immune responses. Accordingly, the induction of ferroptosis in stimulated T/CAR-T cells may occur as part of the contraction phase of an immune response, resulting in the elimination of the effector T cell population while sparing those transformed into long-lived memory cells [47, 48].\u003c/p\u003e \u003cp\u003eAs a novel observation not described before, we noticed a significant decrease in the expression level of GPX4 protein and increase of FSP1 following TCR stimulation. While GPX4 serves as a pivotal regulator in the intricate process of ferroptosis by playing a crucial role in protecting cells from lipid peroxidation-induced damage, FSP1 has been identified as the second ferroptosis-suppressing system. FSP1 efficiently prevents lipid peroxidation independently of the cyst(e)ine\u0026ndash;glutathione (GSH)\u0026ndash;glutathione peroxidase 4 (GPX4) axis [11]. Interestingly, we observed that FSP1 inhibition neither affected the viability of T cells nor CAR-T cells. However, it significantly potentiated the ferroptosis of T cells induced by inhibition of GPX4. This observation remains in accordance with the role of FSP1 complementing GPX4 in tumor cells, as already described elsewhere [11]. Surprisingly, iFSP, although not toxic to CAR-T cells, significantly inhibited their ability to kill target tumor cells, produce cytokines and perforin, and proliferate. Moreover, we also observed that iFSP1 had profound effects on T cells metabolism by inhibiting OCR and mito ATP production. Given these results, we hypothesize that FSP1 is a novel regulator involved in the control of mitochondrial oxidative phosphorylation in T cells. Importantly, beyond its anti-ferroptotic role, FSP1 has already been reported by others to regulate cellular metabolism. For instance, in brown adipose tissue, FSP1 promotes glycolysis during thermogenesis, and in skeletal muscles, it is induced during exercise to enhance glucose utilization and maintain exercise capacity [49, 50]. It has also been demonstrated that overexpression of FSP1 enhances the NAD+/NADH ratio to drive higher glycolytic rates essential for cell proliferation and promotes invasion and migration in human glioma cells [51]. FSP1, also known as AIFM2/AMID belongs to the apoptosis inducing factor (AIF) family. Apoptosis-inducing factors were initially identified as factors that can trigger a unique, caspase-independent apoptotic program [52]. However, AIFM2 and its more ubiquitously expressed homolog AIFM1 presumably play a so far poorly analyzed physiological role in metabolism in many cells [52]. Beyond being a part of a system that reduces the risk of phospholipid peroxidation and ferroptosis, FSP1 is referred to as a special isoform of an NADH dehydrogenase speeding up electron flow through the respiratory chain and promoting the functionality of mitochondrial respiration [52]. Interestingly, it was proposed that both AIF and AMID (FSP1) are previously unidentified mammalian NADH:ubiquinone (UQ) oxidoreductase enzymes, whose bioenergetic function could be a supplemental NADH oxidation in cells [53]. Importantly, it was demonstrated that both AIF and AMID (FSP1) can be associated with the matrix side of the inner membrane of submitochondrial part and integrated as members of the host respiratory chain, with UQ being the physiological electron acceptor for both of them [53]. It was also reported that AIF deficiency in Harlequin mice strain (characterized by hypomorphic mutation of AIF) compromises oxidative phosphorylation and results in complex I defects [54]. Our results are in accordance with these observations; however it should be underlined that FSP1 has never been described earlier as a metabolic regulator of OXPHOS in T cells. Therefore, further studies are needed to better understand the role of FSP1 in determining T cells\u0026rsquo; fate. It is possible that FSP1 serves as conserved redox switch which measures T cells\u0026rsquo; metabolic conditions on the mitochondrial surface and translate it into a binary life/death decision.\u003c/p\u003e \u003cp\u003eFinally, our \u003cem\u003ein vivo\u003c/em\u003e study demonstrates that the efficacy of CAR-T cell therapy can be enhanced through the inhibition of ferroptosis by Lip-1, thus indirectly providing support for the presence of ferroptosis within the TME, as was previously described by Kim et al. [12]. Indeed, we observed that the diminished cytotoxic potential of CAR-T cells may only become apparent \u003cem\u003ein vivo\u003c/em\u003e with donor-to-donor variability, despite similar CAR-T cells efficacy \u003cem\u003ein vitro\u003c/em\u003e. Our results indicate that even repeated administration of well-proliferating CAR-T cells is not sufficient when their cytotoxic activity is impaired. Our findings might also have significant implications for optimizing CAR-T cell therapy outcomes. The condition of T cells in adoptive therapies is multifactorial. An important factor influencing the efficacy of CAR-T therapy is the quality of T cells isolated from patients for CAR modification. Additionally, the generation time of CAR-T cells, from leukapheresis to infusion into the patient, spans several weeks [55] potentially increasing the vulnerability of CAR-T cells to ferroptosis. Moreover, post-infusion, the cytotoxic potential of CAR-T cells against tumors is largely constrained by the immunosuppressive TME characterized by oxidative stress, lipid accumulation, and competition for scarce energy resources, rendering immune cells susceptible to ferroptosis [56, 57]. On the other hand, the induction of ferroptosis is developed as one of the therapeutic approaches in cancer treatment, particularly for solid tumors. Our results indicate that induction of ferroptosis can be a double-edged sword, that apart from eliminating cancer cells can also significantly impairs CAR-T cell-mediated antitumor activity. As mentioned earlier, both GPX4 and FSP1 plays an important role in regulation of cytotoxic functions of CAR-T cells. In light of this, future anticancer therapies should be carefully designed to selectively induce ferroptosis of tumor cells without impeding cytotoxic cells\u0026rsquo; antitumor efficacy.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to acknowledge Mrs Ewa Pieta for peripheral blood mononuclear cells (PBMC) preparation. The work was supported by the National Science Centre, Poland (2019/33/B/NZ6/02503 to MB), European Research Council (805038/STIMUNO/ERC-2018-STG to MW) and Medical University of Warsaw (1/M/MG/N/24 to SH). ML, DP were partially funded by Warsaw University of Technology within the Excellence Initiative: Research University (IDUB) programme. Bioinformatics computations were performed thanks to the Laboratory of Bioinformatics and Computational Genomics, Faculty of Mathematics and Information Science, Warsaw University of Technology using Artificial Intelligence HPC platform financed by Polish Ministry of Science and Higher Education (decision no. 7054/IA/SP/2020 of 2020-08-28).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eM.Kł. conducted most \u003cem\u003ein vitro\u003c/em\u003e experiments, analyzed the data, performed a statistical analysis, wrote manuscript and prepared figures. I.B. designed, coordinated, and conducted \u003cem\u003ein vivo\u0026nbsp;\u003c/em\u003eexperiments. S.H., N.L., and A.J. contributed to some \u003cem\u003ein vitro\u0026nbsp;\u003c/em\u003eflow cytometry and Western blotting experiments. M.G. conducted experiments related to the assessment of the labile iron pool by flow cytometry and performed RTCA tests. M.Ł. performed the bioinformatics analyses of RNAseq data and prepared figures. M.Kr. performed a statistical analysis. M.D. performed HER2 antigen staining by flow cytometry. A.G. and R.Z. provided critical feedback and edited the manuscript. D.P. supervised the bioinformatics analyses. M.W. conceived and supervised the study, provided funding and resources, and supervised and edited the manuscript. M.B. conceived, designed, supervised and performed the study, provided funding and resources, and supervised and wrote the manuscript. All authors provided critical feedback and reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA conflict of interest disclosure statement: \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no potential conflicts of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKoeberle, S.C., et al., \u003cem\u003eFerroptosis-modulating small molecules for targeting drug-resistant cancer: Challenges and opportunities in manipulating redox signaling.\u003c/em\u003e Med Res Rev, 2023. \u003cstrong\u003e43\u003c/strong\u003e(3): p. 614-682.\u003c/li\u003e\n\u003cli\u003eZhang, C., et al., \u003cem\u003eFerroptosis in cancer therapy: a novel approach to reversing drug resistance.\u003c/em\u003e Mol Cancer, 2022. \u003cstrong\u003e21\u003c/strong\u003e(1): p. 47.\u003c/li\u003e\n\u003cli\u003eYin, L., et al., \u003cem\u003eFerroptosis-related small-molecule compounds in cancer therapy: Strategies and applications.\u003c/em\u003e Eur J Med Chem, 2022. \u003cstrong\u003e244\u003c/strong\u003e: p. 114861.\u003c/li\u003e\n\u003cli\u003eLi, Z., et al., \u003cem\u003eTargeting ferroptosis in breast cancer.\u003c/em\u003e Biomark Res, 2020. \u003cstrong\u003e8\u003c/strong\u003e(1): p. 58.\u003c/li\u003e\n\u003cli\u003eYang, F., et al., \u003cem\u003eFerroptosis heterogeneity in triple-negative breast cancer reveals an innovative immunotherapy combination strategy.\u003c/em\u003e Cell Metab, 2023. \u003cstrong\u003e35\u003c/strong\u003e(1): p. 84-100 e8.\u003c/li\u003e\n\u003cli\u003eCai, Y., et al., \u003cem\u003ealpha-KG inhibits tumor growth of diffuse large B-cell lymphoma by inducing ROS and TP53-mediated ferroptosis.\u003c/em\u003e Cell Death Discov, 2023. \u003cstrong\u003e9\u003c/strong\u003e(1): p. 182.\u003c/li\u003e\n\u003cli\u003eLi, Y., et al., \u003cem\u003eTargeting fatty acid synthase modulates sensitivity of hepatocellular carcinoma to sorafenib via ferroptosis.\u003c/em\u003e J Exp Clin Cancer Res, 2023. \u003cstrong\u003e42\u003c/strong\u003e(1): p. 6.\u003c/li\u003e\n\u003cli\u003eWeigand, I., et al., \u003cem\u003eActive steroid hormone synthesis renders adrenocortical cells highly susceptible to type II ferroptosis induction.\u003c/em\u003e Cell Death Dis, 2020. \u003cstrong\u003e11\u003c/strong\u003e(3): p. 192.\u003c/li\u003e\n\u003cli\u003eDixon, S.J., et al., \u003cem\u003eFerroptosis: an iron-dependent form of nonapoptotic cell death.\u003c/em\u003e Cell, 2012. \u003cstrong\u003e149\u003c/strong\u003e(5): p. 1060-72.\u003c/li\u003e\n\u003cli\u003eDixon, S.J. and B.R. 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Buxbaum, \u003cem\u003eTargeting of chimeric antigen receptor T cell metabolism to improve therapeutic outcomes.\u003c/em\u003e Front Immunol, 2023. \u003cstrong\u003e14\u003c/strong\u003e: p. 1121565.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"ferroptosis, T cells, chimeric antigen receptor, GPX4, FSP1, lipid metabolism, immunotherapy","lastPublishedDoi":"10.21203/rs.3.rs-5280443/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5280443/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eInduction of ferroptosis, an iron-dependent form of regulated cell death, holds promise as a strategy to overcome tumor resistance to conventional therapies and enhance immunotherapy responses. However, while the susceptibility of tumor cells to ferroptosis is extensively studied, limited data exists on the vulnerability of immune cells to disturbed iron balance and lipid peroxidation. Here, we found that T cell stimulation rewires iron and redox homeostasis and by increasing levels of reactive oxygen species and labile iron promotes lipid peroxidation and T cells\u0026rsquo; ferroptosis. Upon stimulation, we detected substantial changes in the balance of ferroptosis-suppressive proteins, including GPX4 decrease and increase of FSP1, a phenomenon never described before. Subsequently, we identified GPX4 as a master regulator orchestrating T/CAR-T cells\u0026rsquo; sensitivity to ferroptosis and demonstrated that GPX4 inhibitors impair T/CAR-T cells\u0026rsquo; functions. Surprisingly, we observed that FSP1 regulates T cell antitumor activity independently of its ferroptosis-suppressive function. Specifically, FSP1 inhibition decreased oxidative phosphorylation and mitochondrial ATP production, reduced the amount of perforin and cytokines produced by T cells, and suppressed their proliferation. Altogether, our study for the first time indicates that GPX4 and FSP1, key regulators of ferroptosis, are critical for the antitumor cytotoxic potential of T/CAR-T cells. From our study FSP1 also emerges as a novel metabolic regulator in T cells, which inhibition profoundly affects T cells\u0026rsquo; oxidative phosphorylation. Our findings are not only significant to understand metabolic vulnerabilities of T cells but may also hold particular significance from the standpoint of therapeutic development. In the context of our results, future anticancer therapies should be carefully designed to selectively induce ferroptosis of tumor cells without impeding cytotoxic cells\u0026rsquo; antitumor efficacy.\u003c/p\u003e","manuscriptTitle":"GPX4 and FSP1, key ferroptosis regulators, are critical for T cell functions and CAR-T antitumor activity","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-30 07:07:39","doi":"10.21203/rs.3.rs-5280443/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e196ccf0-76d5-40fc-8c19-39be2ce1db91","owner":[],"postedDate":"October 30th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":39264329,"name":"Biological sciences/Immunology/Cell death and immune response"},{"id":39264330,"name":"Biological sciences/Cancer/Cancer microenvironment"},{"id":39264331,"name":"Biological sciences/Immunology/Lymphocytes/T cells"}],"tags":[],"updatedAt":"2025-04-14T14:51:17+00:00","versionOfRecord":[],"versionCreatedAt":"2024-10-30 07:07:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5280443","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5280443","identity":"rs-5280443","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}