Essential role of NLRC5 in cancer immune surveillance and cancer immunoediting

Essential role of NLRC5 in cancer immune surveillance and cancer immunoediting | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (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];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Essential role of NLRC5 in cancer immune surveillance and cancer immunoediting Akhil Shukla , Anny Armas Cayarga , Jean-François Lucier , Madanraj Appiya Santharam , Dominique Lévesque , View ORCID Profile François-Michel Boisvert , Sheela Ramanathan , View ORCID Profile Subburaj Ilangumaran doi: https://doi.org/10.1101/2025.02.03.636144 Akhil Shukla 1 Department of Immunology and Cell Biology, Faculty of Medicine and Health Sciences, Université de Sherbrooke , Sherbrooke, QC J1H 5N4, Canada Find this author on Google Scholar Find this author on PubMed Search for this author on this site Anny Armas Cayarga 1 Department of Immunology and Cell Biology, Faculty of Medicine and Health Sciences, Université de Sherbrooke , Sherbrooke, QC J1H 5N4, Canada Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jean-François Lucier 2 Department of Biology, Université de Sherbrooke , Sherbrooke, QC J1K 2R1, Canada Find this author on Google Scholar Find this author on PubMed Search for this author on this site Madanraj Appiya Santharam 1 Department of Immunology and Cell Biology, Faculty of Medicine and Health Sciences, Université de Sherbrooke , Sherbrooke, QC J1H 5N4, Canada Find this author on Google Scholar Find this author on PubMed Search for this author on this site Dominique Lévesque 1 Department of Immunology and Cell Biology, Faculty of Medicine and Health Sciences, Université de Sherbrooke , Sherbrooke, QC J1H 5N4, Canada Find this author on Google Scholar Find this author on PubMed Search for this author on this site François-Michel Boisvert 1 Department of Immunology and Cell Biology, Faculty of Medicine and Health Sciences, Université de Sherbrooke , Sherbrooke, QC J1H 5N4, Canada Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for François-Michel Boisvert Sheela Ramanathan 1 Department of Immunology and Cell Biology, Faculty of Medicine and Health Sciences, Université de Sherbrooke , Sherbrooke, QC J1H 5N4, Canada 3 Centre de Recherche, Centre Hospitalier Universitaire de Sherbrooke , Sherbrooke, QC J1H 5N4, Canada Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: Subburaj.Ilangumaran{at}USherbrooke.ca Sheela.Ramanathan{at}USherbrooke.ca Subburaj Ilangumaran 1 Department of Immunology and Cell Biology, Faculty of Medicine and Health Sciences, Université de Sherbrooke , Sherbrooke, QC J1H 5N4, Canada Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Subburaj Ilangumaran For correspondence: Subburaj.Ilangumaran{at}USherbrooke.ca Sheela.Ramanathan{at}USherbrooke.ca Abstract Full Text Info/History Metrics Preview PDF Abstract A key mechanism of immune escape from CD8 + T cell-mediated tumor control occurs via downregulation of NLRC5, the IFNγ-induced transcriptional activator of MHC class-I. As NLRC5 deficiency does not abrogate CD8 + T cell development, we investigated whether NLRC5-dependent antitumor immune mechanisms are required for immune surveillance. Development of 3-methylcholanthrene (MCA)-induced endogenous fibrosarcoma was studied in Nlrc5 -/- mice with Nlrc5 +/+ and Rag1 -/- mice serving as controls. Nlrc5 -/- and Rag1 -/- mice showed increased propensity to develop MCA-induced tumors with elevated growth rate compared to Nlrc5 +/+ mice, and displayed significantly reduced survival. Tumors from Nlrc5 +/+ and Nlrc5 -/- mice, but not from Rag1 -/- mice, contained necrotic areas and displayed T cell infiltration. Tumor cell lines established from MCA- induced tumors were evaluated for their sensitivity to immune-mediated growth control following implantation into immunocompetent C57BL/6 and immunodeficient Rag1 -/- hosts. Tumors formed by Nlrc5 +/+ tumor cell lines progressed unhindered in C57BL/6 hosts that reflected their immunoedited status, whereas cell lines from Nlrc5 -/- and Rag1 -/- tumors were efficiently controlled, indicating their non-immunoedited status. Proteomic analysis by mass spectrometry followed by pathway analysis revealed enrichment of granzyme-mediated cytolytic pathway in Nlrc5 +/+ tumors that were absent in Nlrc5 -/- tumors, which showed enrichment of humoral and innate immune pathways. Overall, our findings show that NLRC5 is required for robust tumor immune surveillance and tumor immunoediting and that compensatory humoral and innate immune mechanisms activated by the loss of NLRC5 are insufficient for cancer immune surveillance and cancer immunoediting. Introduction Immune evasion is a hallmark of cancer [ 1 ]. A key mechanism underlying the ability of cancer cells to evade killing by the adaptive immune system is the downmodulation of major histocompatibility class-I (MHC-I) molecules that present tumor antigenic peptides to CD8 + cytotoxic T lymphocytes (CTL) [ 2 – 5 ]. Reduced MHC-I expression often correlates with high tumor grading, disease progression, reduced patient survival and failure of CTL-based immunotherapies [ 4 , 6 – 9 ]. Loss of MHC-I can arise from deletions or mutations that give rise to hard/irreversible lesions, or from epigenetic repression that results in soft/reversible lesions [ 3 , 10 – 12 ]. The MHC-I antigen presentation pathway is linked to proteasomal cleavage of aged and misfolded proteins [ 13 – 15 ]. The peptides are transported across the endoplasmic reticulum by TAP1/TAP2 proteins, loaded on to MHC-I by TAPBP, and stable MHC-I:peptide complexes presented on the cell surface [ 16 – 18 ]. Thus, defective expression of any key component of the MHC-I antigen processing machinery (APM) can also result in impaired MHC-I expression [ 2 , 9 , 19 – 23 ]. The MHC-I:peptide complexes expressed on all nucleated cells are constantly scanned by CD8 + T lymphocytes, which detect and kill potentially neoplastic cells displaying tumor antigenic peptides, as a key mechanism of cancer immune surveillance. Cancer cells overcome this immune surveillance through immunoediting, which they achieve by downmodulating or mutating dominant tumor antigens and by reducing MHC-I expression [ 24 , 25 ]. NOD-Like Receptor CARD domain containing 5 (NLRC5) is a member of the NLR family proteins, which function as innate immune sensors of pathogen- or danger- associated molecular patterns [ 26 , 27 ]. NLRC5 attenuates LPS-induced NF-κB activation and reduces the induction of TNFα, IL-6 and IL-1β genes [ 28 – 32 ]. Similarities between NLRC5 and NLRA led to the discovery that NLRC5 transactivates MHC-I and APM genes [ 33 , 34 ]. These gene promoters contain cis- regulatory elements that bind transcription factors with which NLRC5 interacts and assembles a transcriptional enhanceosome [ 34 – 37 ]. NLRC5 is strongly induced by IFNγ [ 34 ]. Despite NLRC5 being the key transcriptional activator of MHC-I and the loss of β2M or MHC-I impairs CD8 + T cell development, NLRC5-deficient mice show only marginal reduction in CD8 + T cell numbers, possibly due to high basal MHC-I expression in thymic epithelial cells [ 38 – 45 ]. TCGA data from diverse cancers revealed that loss of NLRC5 expression is the most prevalent defect among MHC-I-related genes and correlates with reduced CTL infiltration, poor patient survival and unresponsiveness to immune checkpoint blockade therapy [ 46 , 47 ]. We and others have shown that stable expression of NLRC5 in MHC-I low cancer cells upregulates MHC-I and APM genes and promotes tumor antigen presentation and tumor control by CTLs [ 48 , 49 ]. Based on the above findings, NLRC5 is postulated to promote cancer immune surveillance [ 50 ], but this has not yet been experimentally validated. In this study we investigated whether NLRC5 is critical or dispensable for cancer immune surveillance and cancer immunoediting using mouse genetic models. Materials and Methods Mice Nlrc5 -/- mice and control Nlrc5 +/+ in C57BL/6J (Jax Strain #:000664) background have been previously described [ 51 ]. Functional impact of NLRC5 deficiency was confirmed by impaired upregulation of MHC-I and APM genes in splenocytes following IFNγ stimulation ( Supplementary Figure S1 ). Rag1 -/- mice in C57BL/6J background were purchased from the Jackson laboratory (B6.129S7- Rag1 tm1Mom /J; Strain #:002216). All strains of mice were housed in the same breeding and experimentation rooms of the Université de Sherbrooke specific pathogen-free animal facility. Mice were housed in ventilated cages with 14/10 hours day/night cycle and fed with normal chow ad libitum . All experiments on mice were carried out during daytime with the approval of the Université de Sherbrooke Ethics Committee for Animal Care and Use (Protocol ID 2023-4043). Flow cytometry Spleens from Nlrc5 -/- and Nlrc5 +/+ mice were collected into sterile PBS containing 2% fetal calf serum in Petri dishes and crushed between glass slides to obtain single cell suspension. Red-blood cells were removed by incubating the cell pellet in 2 mL erythrocyte lysis buffer (150mM NH 4 Cl, 10mM KHCO 3 , 0.1mM Na 2 EDTA, pH 7.2-7.4) for 2 minutes and washed in PBS-FCS. Aliquots of cells were incubated with mouse IFNγ (20 ng mL −1 ) for 8 h and 24 h. Control and IFNγ stimulated cells were labelled for flow cytometry using fluorochrome conjugated antibodies listed in Table S1 as previously described {Kandhi, 2022 #675}. Cells were analyzed using CytoFLEX (Beckman Coulter, CA USA) flow cytometer and data analyzed using Flowjo software (BD Bioscience, OR, USA, version 10.9.0). MHC-I expression was evaluated using an antibody that detects H-2K b /D b on CD45 gated CD3+CD4+, CD3+CD8+ and CD3-B220+ cells (Table S1) and expressed as mean fluorescence intensity. RT-qPCR RNA was extracted from aliquots of control and IFNγ stimulated splenocytes using RNeasy® Plus Mini Kit (Qiagen, Hilden, Germany, Cat #74134) following manufacturers’ instructions. cDNA was synthetized from 1µg of purified RNA using QuantiTect® reverse transcription kit (Qiagen, Toronto, Ontario, Canada). Quantitative RT-PCR reactions were carried out in CFX Connect Real-Time PCR Detection System (Bio-Rad, Canada) using SYBR Green Supermix (Bio-Rad, Mississauga, Ontario, Canada). The expression of indicated genes was measured using primers listed in Table S2. Each primer for qRT-PCR was validated by analyzing its standard curve and melt curve. Data was normalized to the expression of a housekeeping gene β-actin in unstimulated cells from Nlrc5 +/+ mice to calculate the relative gene-expression. Induction of Fibrosarcoma To test the role of NLRC5 in cancer immune surveillance, endogenous fibrosarcoma was induced by subcutaneous administration of 3-methylcholanthrene (MCA; Sigma-Aldrich, Cat # 212942) in the flanks of Nlrc5 -/- , Nlrc5 +/+ and Rag1 -/- mice following published methods [ 24 , 52 ]. As the effective MCA dose varies among mouse colonies even for the same genetic strain [ 52 , 53 ], 100, 200 and 400 μg of MCA in 100 μL corn oil. Both male and female mice were used, as no significant difference was observed in tumor incidence between them. Tumor development was initially monitored visually once week and, after palpable tumor development, by using digital vernier calipers until the endpoint of 20 mm diameter in any direction or tumor skin ulceration, at which point the mice were euthanized. Tumor incidence, growth and endpoints were recorded for statistical analyses. Tumor tissues were collected, and tissue pieces were fixed in buffered formalin for paraffin embedding, snap frozen in liquid nitrogen for proteomic analysis and cultured to establish cancer cell lines. Histology and immunohistochemistry Formalin fixed paraffin embedded (FFPE) tumor sections were deparaffinized, rehydrated, and stained with hematoxylin and eosin (H&E). For immunohistochemical detection of CD3, rehydrated tumor sections were immersed in citrate buffer (pH 6.0) and given intermittent microwave treatment to retrieve antigenic epitopes. Following incubation in 3% hydrogen peroxide for 10 min to inhibit endogenous peroxidase activity, sections were blocked with 5% BSA in Tris-buffered saline (TBS) containing 20% Tween-20 (TBS-T). Slides were incubated overnight at 4°C with a rat monoclonal antibody against mouse CD3 (ThermoFisher scientific, Cat #14-0032-81) diluted in blocking buffer, washed and then incubated with horseradish peroxidase (HRP)-conjugated secondary Ab for 1 h. After thorough washing, slides were incubated in 30-40 µL of signal stain boost (SignalStain ® Boost, Cell Signaling Technology, Cat # 8125) for 30 minutes at room temperature. After washing. a substrate solution containing 3,3’-diaminobenzidine (DAB; Sigma-Aldrich; 30 μL chromogen diluted in 1 mL of DAB liquid buffer) was added for 10 min. The sections were counterstained with hematoxylin and mounted with a coverslip. Images of the stained sections, digitized using the NanoZoomer Slide Scanner (Hamamatsu Photonics, Japan), were analyzed by the NanoZoomer Digital Pathology software NDPview2.0. Necrotic areas in H&E-stained sections were quantified using the NIH ImageJ software (version 1.53e) and CD3 positive cells were counted in NanoZoomer images. Assay for cancer immunoediting Tumor tissues collected aseptically from individual tumors were minced in sterile PBS, digested with 1 mg/mL collagenase (type II, Cat #LS004176, Worthington, NJ, USA) and 40 μg/mL DNase I (Roche, Cat #10104159001) at 37°C for 60 mins. Clumps were removed by filtering through 70 µm membrane filter and cells were by centrifugation for 5 mins at 400 g . Cells were resuspended in RPMI-1640 cell culture medium containing 10% fetal bovine serum, plated in adherent culture plates and passed through several passages over three months prior to using them for immunoediting experiments or freezing in liquid nitrogen. Each independent tumor derived cell line established from Nlrc5 −/− , Nlrc5 +/+ and Rag1 −/− mice was injected simultaneously into batches of Rag1 −/− and C57BL/6 hosts. The cells (2 x 10 5 cells in 50 μL PBS) were injected subcutaneously in the flanks. Tumor growth was monitored until the end point. Statistical Analysis Data analysis and graphic plotting were carried out using the GraphPad Prism (San Diego, CA, USA; version 10.4.1). Log-rank test was used to calculate survival probability. For other comparisons between groups, one-way ANOVA was used. p values are represented by asterisks: * <0.05, ** <0.01, *** <0.001, **** <0.001. Mass spectrometry Protein preparation and protease digestion Snap frozen tumor tissues (20-50 mg) were resuspended in 1 mL of lysis buffer (8 M Urea, 1 M NH 4 HCO 3 and 10 mM HEPES-KOH pH7.5) in a 2 mL low protein binding tubes (Axygen). Tissues were homogenized using steel beads in a mixer mill tissue lyser (MM 400, Retsch, Haan, Germany). Tissue lysates were transferred to fresh tubes and sonicated on ice (12 cycles, 20-25% intensity, 5 sec PULSE/ 5 sec OFF) and centrifuged at 16,000 g for 10 min at 4°C. Supernatants were transferred to fresh and proteins quantified using DC Protein Assay Kit (Bio-Rad, #5000113, #5000114, #5000115) following the manufacturer’s instructions. One hundred µg of protein was transferred to new tubes, volumes adjusted to 50 µL with urea solution (8 M Urea, 10 mM HEPES, pH 8) and 1 µL of 255 mM dithiothreitol was added to achieve 5 mM final concentration. The tubes were vortexed and boiled at 95°C for 2 min and allowed to cool at room temperature for 30 min. After adding 1.5 µL of photosensitive 262.5 mM chloroacetamide to achieve 7.5 mM final concentration, the samples were vortexed and incubated in dark at room temperature for 20 min before adding 150 µL of 50 mM NH 4 HCO 3 to bring the urea concentration down to 2 M. Proteins were digested by adding 1 µg of Pierce TM Trypsin Protease (Thermo Scientific, cat# 90058) and overnight incubation at 30°C. Proteolysis was stopped by adding 0.5 µL of 100% Trifluoroacetic acid (TFA) and the digested peptides were cleaned using Pierce TM C18 tips (Thermo Scientific, cat# 87784). The solvents were then removed using Vacufuge Plus centrifuge concentrator (Eppendorf) and the peptides diluted in 1% Formic Acid (FA) were quantified using NanoDrop 2000/2000c spectrophotometer (Thermo Fisher scientific). Liquid chromatography-tandem mass spectrometry (LC-MS/MS) Concentrated peptides (250 ng) were separated on a nanoHPLC system (nanoElute, Bruker Daltonics). The samples were loaded onto an Acclaim PepMap100 C18 Trap Column (0.3 mm id x 5 mm, Dionex Corporation) at 4 µL/min consistent flow and peptides were eluted onto a PepMap C18 analytical nanocolumn (1.9 µm beads size, 75 µm x 25 cm, PepSep) heated at 50°C. Peptides were eluted with solvent B (100% ACN & 0.1% FA) in a 5-37% linear gradient with a flowrate of 400 nL/min for ∼2 h. The HPLC system was coupled to an TimsTOF Pro ion mobility mass spectrometer containing Captive Spray nano electrospray source (Bruker Daltonics). Data acquisition was done using diaPASEF mode. For each individual Trapped Ion Mobility Spectrometry (TIMS) measurement in diaPASEF mode, a single mobility window consisting of 27 mass steps (with m/z ranging from 114 to 1414 and a mass width of 50 Da) was employed per cycle, which had a 1.27-second duty cycle. This process involves scanning the diagonal line in the m/z-ion mobility plane for +2 and +3 charged peptides. Protein identification Peptide mass spectra were analyzed using the DIA-NN, an open-source software [ 54 ] suite for DIA / SWATH data processing ( https://github.com/vdemichev/DiaNN , version 1.8.1), installed in an Apptainer container ( https://apptainer.org/ , version 1.3.5) using docker image provided on the docker hub [ 55 ]. Analysis was performed using default parameters except for these options: 2 missed - cleavages was allowed; trypsin digestion was performed for K/R; protein N-term methionine excision as variable modification for the in-silico digest. The Mus musculus reference proteome UP000000589 was downloaded from the Uniprot website ( https://www.uniprot.org/proteomes/UP000000589 ). The reference proteome contained a total of 63367 proteins. For the FASTA search, DIA-NN was instructed to perform an in-silico digest of the sequence database. A mass tolerance accuracy of MS1 and MS2 of 20 ppm was used for precursor and fragment ions, respectively. Minimum and maximum were set for peptide length (7-30 amino acids), and precursor charge (1-5), precursor m/z (100-1700) and fragmentation m/z (100-1500) for in silico library generation or library-free search. For the reanalysis, MBR (match between run) was enabled and chosen the smart profiling when creating a spectral library from DIA data. Carboxyamidomethylation (unimod4), and oxidation (M) (unimod35) were set as fixed modifications and N-terminal protein acetylation was set as a variable modification. DIANN protein group matrix was filtered using custom Perl script to extract protein groups with a single protein. This new matrix was used as input to the R package FragPipeAnalystR [ 56 ] to get QC metrics and differential protein expression profiles. Proteomic data visualization Significantly modulated proteins with cut-off values of log2-fold change 1 and p -Value <0.05 in the FragPipeAnalystR pipeline output were sorted using Microsoft Excel (Office 365). GraphPad Prism version 10.0.3 (GraphPad, Boston, MA) was used to generate volcano plots and pie charts. Venn diagrams were generated using the jvenn https://jvenn.toulouse.inrae.fr/app/index.html ; accessed in Dec 2024) online tool [ 57 ]. The SRplot server ( http://www.bioinformatics.com.cn/srplot ; accessed in Dec 2024) was used for pathway and Gene Ontology (GO) analyses and to generate pathway enrichment plots and heatmaps. Gene set enrichment analysis (GSEA) based on GO and Kyoto Encyclopedia of Genes and Genomes (KEGG) was conducted using HTSanalyzeR2 ( https://github.com/CityUHK-CompBio/HTSanalyzeR2 ) [ 58 ]. Results Increased incidence of MCA-induced fibrosarcoma and reduced survival in Nlrc5 −/− mice To elucidate the role of NLRC5 in tumor immunosurveillance, we injected 3-methylcholanthrene (MCA) into Nlrc5 −/− mice, using Nlrc5 +/+ and Rag1 −/− mice as controls. All mice are in C57BL/6 background. Different doses of MCA (100μg, 200μg, and 400μg) were used because susceptibility of the same genetic strain to MCA-induced tumors can vary from one animal facility to another [ 52 ]. At 100μg MCA, 7 out of 8 Nlrc5 −/− mice developed tumors compared to six out of nine Nlrc5 +/+ mice, with Nlrc5 −/− mice with higher tumor-related mortality (87.5% versus 70.5%) ( Figure 1A, B ). Seven out of eight Nlrc5 −/− mice developed tumors, compared to four out of nine Nlrc5 +/+ mice at 200μg MCA, again with significantly higher mortality than in Nlrc5 +/+ mice (87.5% versus 55.5%) ( Figure 1C, D ). At 400μg MCA, all Nlrc5 −/− mice and three out of five Nlrc5 +/+ mice developed tumors (mortality 100% versus 60%) ( Figure 1E, F ). Rag1 −/− mice developed tumors at all doses of MCA tested. Pooled data from all three doses of MCA showed that 91.3% of Nlrc5 −/− mice developed tumors compared to the 56.5% observed in Nlrc5 +/+ mice, with significantly elevated mortality (91.3% versus 69%) ( Figure 1G, H ). These findings indicate that NLRC5 expression is required for efficient control of endogenously arising tumors and underscore the key role of NLRC5 in cancer immunosurveillance. Download figure Open in new tab Figure 1. NLRC5 deficiency increases susceptibility to MCA-induced fibrosarcoma. Nlrc5 −/− , Nlrc5 +/+ and Rag1 −/− mice were injected the chemical carcinogen 3-methylcholanthrene (3-MCA) at different doses of 100 μg (A, B), 200 μg (C, D), 400 μg (E, F) subcutaneously. Development of fibrosarcoma was monitored visually and by using a digital vernier caliper until the endpoint (tumor diameter of 20 mm in any direction, or ulceration at any diameter), when the animals were euthanized. Days to endpoint are plotted in the left panels (A, C, E) and survival probability in the right panels (B, D, F). Pooled data are shown in G and H. Numbers in parenthesis in A, C, E and G indicate the number of mice that developed tumors over total number for each genotype. B, D, F, H: Log-rank (Mantel-Cox) test. * p ≤0.05, *** p ≤0.001. Histological features of MCA-induced fibrosarcoma in Nlrc5 −/− and control mice Histological examination of tumor tissues revealed the distinctive feature of fibrosarcoma that is characterized by spindle-shaped fibroblast-like cells arranged in a herringbone or chevron-like pattern ( Figure 2A ). Notably, tumors arising in Nlrc5 +/+ and Nlrc5 −/− mice displayed large areas of tumor necrosis that did not occur in Rag1 −/− tumors ( Figure 2A, B ), suggesting cell death mediated by the immune system rather than spontaneous death caused, for example, by hypoxia or reduced nutrient supply. This notion is supported by significant infiltration by CD3+ T lymphocytes in tumors from Nlrc5 +/+ and Nlrc5 −/− mice but not in Rag1 −/− hosts ( Figure 2C, D ). Download figure Open in new tab Figure 2. MCA-induced tumors in Nlrc5 −/− mice show areas of necrosis and T cell infiltration as in Nlrc5 +/+ mice. (A) H&E staining of MCA-induced tumors from Nlrc5 +/+ , Nlrc5 −/− and Rag1 −/− mice at lower and higher magnification, the latter revealing the Herringbone pattern. Tumors from Nlrc5 +/+ and Nlrc5 −/− mice display pale staining areas of necrosis that are not observed in Rag1 −/− tumors. Representative data from three mice in each genotype. (B) The proportion of necrotic area in random fields of three tumors per genotype was measured using ImageJ. (C) Immunohistochemical staining of MCA-induced tumors for CD3 + T cells (brown-stained cells indicated by circles). Representative data from 3 mice in each group. (D) The number of CD3 + T cells were counted and pooled from 3 random fields per tumor. Mean + SEM; One-way ANOVA ** p ≤0.05, *** p ≤0.001, **** p ≤0.0001. NLRC5 is required for cancer immunoediting To investigate the immunoedited status of MCA tumors, cancer cell lines were established from the MCA-induced tumors ( Figure 1 ). Independent cell lines from Nlrc5 +/+ , Nlrc5 −/− and Rag1 −/− tumors were implanted into immunocompetent C57BL/6 and immunocompromised Rag1 −/− mice, and their growth was assessed. Cell lines from Rag1 −/− tumors serve as controls for non-immunoedited status, whereas cell lines from Nlrc5 +/+ tumors represented immunoedited status as shown by Shankaran et al., [ 24 ]. As expected, the two Rag1 −/− tumor cell lines showed unhindered growth when implanted into a new batch of Rag1 −/− hosts ( Figure 3A ). However, when implanted into C57BL/6 hosts, the same tumor cell lines were efficiently controlled because they had not previously been controlled by the adaptive immune system, i.e., not immunoedited ( Figure 3A ). On the other hand, five distinct MCA cancer cell lines originating from the MCA-induced tumors of Nlrc5 +/+ hosts showed unhindered growth in fresh cohorts of C57BL/6 mice (25 out of 26 mice; only three cell lines are shown in Figure 3B ), indicating their immunoedited status that was previously established in Nlrc5 +/+ hosts. Notably, for reasons that remain unclear, Nlrc5 +/+ tumor cell lines frequently ulcerated in Rag1 −/− hosts, contributing to their earlier endpoints ( Figure 3B ). Download figure Open in new tab Figure 3. Impaired immunoediting of MCA tumors in Nlrc5 −/− mice. Cancer cell lines established from MCA-induced fibrosarcoma were implanted into immunocompetent C57BL/6 (black circles) and immunocompromised Rag1 −/− (red circles) hosts (200,000 cells in 50 µl 1xPBS, subcutaneous route). Tumor growth was monitored every 2 days. The final data points indicate the endpoint. (A) Tumors developing in Rag1 −/− mice were not immunoedited. Rag1 −/− tumor cell lines arising from 100 or 200 µg MCA are indicated as R-KO_100-1 and R-KO_200-1. (B) Tumors developing in Nlrc5 +/+ hosts were immunoedited. Three of the five cell lines established from MCA-induced fibrosarcoma of Nlrc5 +/+ hosts injected with 100 or 200 µg MCA are indicated as N_200-1, N_200-3 and N_400-1. (C) Impaired immunoediting of MCA tumors in Nlrc5 −/− mice. Three of the four Nlrc5 −/− tumor cell lines arising from 100 or 200 µg MCA-induced tumors are indicated as N-KO_100-1, N-KO_200-1 and N-KO_200-3. Evaluation of the immunoedited status in MCA tumors arising in Nlrc5 −/− mice using four different cancer cell lines showed that the majority of Nlrc5 −/− tumor cell lines were effectively controlled in C57BL/6 hosts with only a small proportion of mice developing tumors (5 out of 15) (only three cell lines are shown in Figure 3C ). Most of these cell lines grew uninhibited in Rag1 −/− hosts, with all 15 mice developing tumors. These data show that unlike tumors arising in Nlrc5 +/+ mice that are immunoedited, most tumors arising in Nlrc5 −/− mice were non-immunoedited. These findings also suggest that the NLRC5-dependent tumor growth mechanisms are the key contributors to cancer immunoediting. Impact of NLRC5 deficiency on the tumor proteome NLRC5 deficiency compromised tumor growth control and tumor immunoediting to a level comparable to Rag1 −/− mice ( Figures 1 , 3 ), indicating that NLRC5-dependent adaptive antitumor immune mechanisms are critical for tumor growth control. To gain deeper understanding of these control mechanisms, we carried out mass spectrometry analysis of the proteomes from three independent MCA tumors for each of the three genotypes. A total of 6373 individual proteins were identified in these samples, and quality control measures showed a random missing protein profile ( Figure 4A, B ). Even though Pearson’s correlation coefficient revealed high degree of similarity among the nine tumors, presumably because they all represent fibrosarcoma ( Figure 4C ). PCA plot showed that the tumors did not tightly cluster according to the three genotypes ( Figure 4D ), possibly reflecting the randomness of the oncogenic pathways activated in these tumors by the chemical carcinogen MCA. Download figure Open in new tab Figure 4. Quality control for mass spectrometry data on tumor proteomes. Three independent MCA tumors (biological triplicates) from each of the Nlrc5 +/+ , Nlrc5 −/− and Rag1 −/− mice were subjected to shotgun proteomics by LC-MS/MS. (A) Number of individual proteins identified in each tumor by more than peptide. (B) Missing value pattern across samples. (C) Pearson correlation between samples. (D) Principal component analysis (PCA) plot. Pairwise comparison of protein expression profiles using Volcano plots identified only 239 differentially expressed proteins (DEPs) between tumors arising in Nlrc5 +/+ mice and Nlrc5 −/− mice (out of 6373 proteins), with 140 upregulated proteins (green) and 99 downregulated proteins (red) in Nlrc5 +/+ tumors ( Figure 5A ). Similar comparison between Nlrc5 +/+ and Rag1 −/− tumors revealed 171 DEPs with 82 upregulated and 89 downregulated proteins in Nlrc5 +/+ tumors ( Figure 5B ). Nlrc5 −/− and Rag1 −/− tumors showed an elevated number of DEPs (357), with 116 upregulated and 241 downregulated proteins in Nlrc5 −/− tumors ( Figure 5C ), suggesting that Nlrc5 −/− tumors are more disparate from Rag1 −/− tumors than from Nlrc5 +/+ tumors. To further understand these differences, the degree of overlap between differentially modulated proteins was analyzed using a Venn diagram ( Figure 5D ). The three groups of DEPs shared only 6 proteins (CPS1, RABEPK, ARHGEF5, TNC, TPM1, AND MUP3), indicating that fibrosarcoma arising in Nlrc5 +/+ , Nlrc5 −/− and Rag1 −/− mice display a subset of distinct proteins that may be associated with genotype-specific host response toward the tumor rather than with inter-tumor heterogeneity. Among the 239 DEPs between Nlrc5 +/+ versus Nlrc5 −/− tumors, only 33 were shared with the DEPs of Nlrc5 +/+ versus Rag1 −/− tumors ( Figure 5D ), suggesting that loss of NLRC5 or RAG1 differentially impact the MCA tumor proteome. This notion is further supported by 81 out of 357 DEPs between Nlrc5 −/− versus Rag1 −/− tumors being shared with the DEPs of Nlrc5 +/+ versus Nlrc5 −/− tumors, compared to 45 shared with the DEPs of Nlrc5 +/+ versus Rag1 −/− tumors ( Figure 5D ). Notably, 225 DEPs between Nlrc5 −/− versus Rag1 −/− tumors were unique compared to 119 unique DEPs for Nlrc5 +/+ versus Nlrc5 −/− tumors and 83 unique DEPs for Nlrc5 −/− versus Rag1 −/− tumors, suggesting that NLRC5 deficiency differentially impacts the host response to endogenously arising tumors. Download figure Open in new tab Figure 5. Differential protein expression in MCA tumors. (A-C) Volcano plots showing significantly modulated proteins between Nlrc5 +/+ and Nlrc5 −/− tumors (A), Nlrc5 +/+ and Rag1 −/− tumors (B) Nlrc5 −/− and Rag1 −/− tumors (C); vs, versus. Differentially expressed proteins (DEPs; fold change >1.5 fold; p <0.05) are indicated in green (upregulated) or red (downregulated). Total number of significantly upregulated and downregulated proteins are shown in the pie chart. (D) Venn diagram showing unique and shared DEPs modulated by the loss of NLRC5 or RAG1 in the host. Enrichment of CTL-mediated cell death pathways in Nlrc5 +/+ tumors To elucidate the functional significance of proteins modulated by NLRC5 deficiency in MCA tumors, we carried out Gene ontology (GO) analysis of DEPs for potential impact on biological processes (BP), cellular compartments (CC), and molecular functions (MF) ( Figure 6 ). DEPs upregulated in Nlrc5 +/+ tumors in comparison to Rag1 −/− tumors showed enrichment of BP terms such as granzyme-mediated apoptotic signaling pathway, positive regulation of inflammatory response and antigen processing and presentation, as well as the MF terms CD8 receptor binding and T cell antigen receptor binding ( Figure 6A ). The BP term granzyme-mediated apoptotic signaling pathway and the MF term NF-κB binding were enriched among the DEPs upregulated in Nlrc5 +/+ tumors in comparison to Nlrc5 -/- tumors ( Figure 6B ), in line with the known functions of NLRC5 in MHC-I-dependent CD8 T cell activation and regulation of NF-κB activity [ 31 , 59 ]. None of these terms were represented among those enriched within the upregulated DEPs of Nlrc5 -/- tumors in comparison to Rag1 −/− tumors ( Figure 6C ). Heatmap plot of proteins involved in ‘granzyme-mediated apoptotic signaling pathway’, ‘granzyme-mediated programmed cell death signaling pathway’ and ‘cytolysis’ showed upregulation of several murine granzymes (D, E, F, G) that play a crucial role in CTL-mediated cytotoxicity [ 60 ] in Nlrc5 +/+ tumors compared to Nlrc5 −/− and Rag1 −/− tumors ( Figure 7A ). Corroborating with this data, gene set enrichment analysis (GSEA) of DEPs showed that Nlrc5 +/+ tumors displayed high enrichment score (0.795) for proteins involved in CD8 receptor binding (GO: 0042610) that included classical (H-2D1, H2-K1) and non-classical (H2-Q4, H2-Q7) MHC-I molecules ( Figure 7B, C ). Notably, this group of CD8 receptor binding proteins included FYN, which is downregulated in Nlrc5 +/+ tumors compared to Nlrc5 −/− and Rag1 −/− tumors ( Figure 7C ). Collectively, these results indicate that CTL-mediated cytotoxic pathway is the key mediator of NLRC5-dependent control of endogenously arising tumors. Download figure Open in new tab Figure 6. Gene ontology analysis of DEPs in MCA tumors. Gene ontology (GO) analysis of upregulated and downregulated genes in Nlrc5 +/+ versus Rag1 −/− tumors (A), Nlrc5 +/+ versus Nlrc5 −/− tumors (B), and Nlrc5 −/− versus Rag1 −/− tumors (C); vs, versus. GO terms in Biological Processes (BP, orange bars), Cellular Compartments (CC, green bars), and Molecular Functions (MF, blue bars) are indicated with corresponding enrichment scores. GO terms related to tumor control by cytolytic immune cell function are indicated in blue color fonts, and terms related to innate immune response in red color font. Download figure Open in new tab Figure 7. Expression level of proteins identified within the key ontology terms upregulated in Nlrc5 +/+ tumors. (A) Heatmap analysis shows the expression level of proteins within the BP terms granzyme mediated elimination and cytolysis. (B, C) GSEA plot (B) and corresponding heatmap (C) for proteins identified within the MF term CD8 receptor binding. (A, C) Normalised abundance values (calculated using complete-linkage clustering and Euclidean distance method) are color coded on a scale with green and red representing upregulation and downregulation, respectively. Upregulation of innate immune pathways in NLRC5 deficient tumors Even though cytolytic immune response pathways were not enriched in Nlrc5 −/− tumors, they displayed areas of necrosis that are not found in Rag1 −/− tumors, suggesting activation of other cytolytic immune cell functions. Among the DEPs downregulated in Nlrc5 +/+ tumors in comparison with Nlrc5 -/- tumors, but not in Rag1 −/− tumors ( Figure 6C ), humoral immune response and innate immune response pathways were notably enriched. GSEA of DEPs in Nlrc5 −/− versus Rag1 −/− tumors revealed enrichment in immune-related pathways, particularly innate immune response in Nlrc5 −/− tumors (GO: 0006695, 0002376, 0045087; Figure 8A , B, C). A heatmap analysis of 118 genes associated with these immune response pathways confirmed that Nlrc5 −/− tumors displayed elevated expression of innate immune response proteins that surpassed their expression levels in Nlrc5 +/+ tumors ( Figure 8D ). In fact, Nlrc5 −/− tumors showed high enrichment of immunoglobulin-mediated immune response (GO:0016064) against both Rag1 −/− tumors (enrichment score 0.752) and Nlrc5 +/+ tumors (enrichment score 0.709) and ( Figure 9A ). Heatmap analysis revealed that multiple immunoglobulin heavy chain variable region (IGHV)-derived peptides were upregulated in Nlrc5 −/− tumors ( Figure 9B ), suggesting upregulation of antibody-mediated tumor resistance mechanisms to compensate for the impaired CTL- mediated immune surveillance functions caused by the loss of NLRC5 or RAG1. Download figure Open in new tab Figure 8. Upregulation of innate immune response pathways in Nlrc5 −/− tumors: (A, B, C) GSEA of DEPs in Nlrc5 −/− versus Rag1 −/− tumors showing enrichment of immune response pathways. (D) Heatmap plot showing differential expression of proteins identified within these pathways in Nlrc5 +/+ , Nlrc5 −/− and Rag1 −/− tumors. Normalised abundance values (calculated using complete-linkage clustering and Euclidean distance method) are color coded on a scale with green and red representing upregulation and downregulation, respectively. Download figure Open in new tab Figure 9. Enrichment of immunoglobulin-mediated immune responses in Nlrc5 −/− tumors. (A) GSEA of DEPs in Nlrc5 −/− tumors versus Nlrc5 +/+ or Rag1 −/− tumors showing enrichment of proteins related to immunoglobulin-mediated immune response (GO:0016064). (B) Expression levels of proteins visualized using a heatmap. Normalised abundance values (calculated using complete-linkage clustering and Euclidean distance method) are color coded on a scale with green and red representing upregulation and downregulation, respectively. DEPs upregulated in Nlrc5 -/- tumors when compared to Rag1 −/− tumors were also enriched for the GO terms regulation of peptidase activity, antigen processing and proteasome complex ( Figure 6C ), suggesting compensatory upregulation of pathways related to antigen processing and presentation. Furthermore, DEPs upregulated in Nlrc5 -/- tumors in comparison to Rag1 −/− tumors showed enrichment of the GO terms protein targeting (BP), trans-golgi network (CC) and ubiquitin-protease transferase activity (MF), suggesting that loss of NLRC5 may also trigger antigen presentation pathways outside of the proteasome machinery in an attempt to restore impaired CTL functions. Discussion Using mouse genetic models, we have shown in this study that NLRC5 is required to reduce the incidence of endogenous tumors and to attenuate tumor progression. We have also shown that the tumors that arose in the absence of NLRC5 were not immunoedited similar to those arising in RAG1- deficient mice, underscoring the importance of NLRC5-dependent adaptive immune responses in delaying the progression of NLRC5 expressing tumors. Most of the NLRC5-dependent cancer immune surveillance and cancer immunoediting functions are likely mediated by the already demonstrated role of NLRC5 in transcriptional upregulation of MHC-I and key proteins involved in antigen processing and presentation to CD8 + T cells [ 33 , 48 , 49 , 61 ]. However, slightly faster tumor progression in Nlrc5 -/- mice than in Rag1 -/- mice, and notable differences in the proteomes of tumors arising in Nlrc5 -/- mice compared to those of Nlrc5 +/+ and Rag1 -/- tumors suggest that NLRC5 may also promote additional antitumor immune functions and possibly regulate potentially tumor-promoting immune responses. A key step in the cancer immunity cycle [ 62 , 63 ], which involves activation of antitumor T lymphocytes and killing of tumor cells by CTLs in iterating cycles to achieve tumor growth control, is the presentation of tumor antigenic peptides to naïve CD8 + T cells. This process requires cross-presentation of tumor antigens acquired from dead tumor cells by dendritic cells (DC), which present the tumor antigenic peptides along with costimulatory ligands in tumor draining lymph nodes [ 64 , 65 ]. DCs can also acquire MHC-I:peptide complexes directly from live tumor cells via trogocytosis, and recent studies show that such cross-dressing of DCs with tumor cell-derived MHC-I:peptide complexes is important for initiating antitumor CTL responses [ 66 – 68 ]. DCs from Nlrc5 -/- mice also show reduced MHC-I expression and are less efficient in activating CD8 + T cells [ 39 , 40 , 69 ]. As we have used in our studies whole body NLRC5 knockout mice, the aggressive growth of MCA-induced tumors in these mice could result from impaired tumor antigen presentation via cross-dressing, cross-presentation or both processes. Addressing this question will require studying the growth of NLRC5-deficient and NLRC5-sufficient isogenic tumor cell lines in Nlrc5 -/- and Nlrc5 +/+ hosts, or in mice lacking NLRC5 specifically in DCs. Activated CD8 + T cells proliferate and differentiate into effector CTLs, enter circulation, traffic to the tumor, recognize tumor antigenic peptide:MHC-I complexes on cancer cells, and release cytolytic granules [ 62 ]. In addition to CD8 + T cells, natural killer (NK) cells also play a role in tumor immune surveillance, although they are not sufficient to control MCA-induced spontaneous tumors in Rag1 -/- mice [ 70 – 72 ]. NK cells recognize cancer cells that lose the expression of classical MHC-Ia molecules, which engage NK cell inhibitory receptors, and cancer cells that express NK cell activating ligands, which include non-classical MHC-Ib molecules [ 73 – 77 ]. Tumors from Nlrc5 -/- mice showed reduced expression of classical (H2-K1, H2-D1) and non-classical (H2-Q7, H-2-Q4) MHC-I molecules ( Figure 7C ). Earlier studies have shown that NLRC5 transactivated both MHC-Ia and MHC-Ib molecules [ 38 , 40 , 44 , 69 ], indicating a role for NLRC5 in activating both CTL and NK cell responses against tumors. A similar expression pattern of MHC-Ia and MHC-Ib molecules in Nlrc5 -/- and Rag -/- tumors ( Figure 7C ) suggests their induction by ongoing immune responses, presumably via IFNγ and downstream induction of NLRC5. Granzymes are a key arsenal of cytolytic granules of CTLs and NK cells in killing cancer cells, of which GZMB is plays a major role [ 60 , 78 , 79 ]. Notably, GZMB expression that was markedly downregulated in Rag -/- tumors was only moderately reduced in Nlrc5 -/- tumors ( Figure 7A ), suggesting its expression in other immune cells that may be activated in an NLRC5-independent fashion. Another notable difference related to CD8 receptor binding is the very low expression of FYN in Nlrc5 -/- tumors. As FYN has been reported to attenuate T cell activation and commitment to effector cell differentiation [ 80 , 81 ], it raises the possibility that NLRC5 may have a role in alleviating this negative regulatory mechanism in CD8 + T cells. Besides CTLs and NK cells, γδ T cells may also contribute to elevated cytolytic responses in Nlrc5 +/+ tumors, as NLRC5 has been shown to promote killing by γδ T cells via induction of butyrophilin (BTN) family proteins BTN3A1-3 [ 82 – 84 ]. BTN proteins bound to altered self-proteins such as phospho-Ags in stressed and cancer cells are recognized by the γδ TCR in an MHC-independent manner [ 82 ]. Analysis of differentially expressed proteins in tumors from Nlrc5 −/− , Nlrc5 +/+ and Rag -/- tumors revealed not only the enrichment of cytolytic immune cell responses in Nlrc5 +/+ tumors but also revealed suppression of humoral and innate immune responses, which are enriched in Nlrc5 −/− tumors. This enrichment is particularly associated with IGHV peptides derived from antibodies, suggesting a skewed antigen reactivity of the tumor-associated B cell antibody repertoire. Tumor-associated B lymphocytes also actively participate in antitumor immune responses, however they are heterogeneous and may exert either anti-tumor or pro-tumor functions, and antibodies can cause aberrant autoimmune-like reactions in tumor microenvironment [ 85 – 87 ]. Nlrc5 −/− tumors also displayed enrichment of GO terms related to proteolytic pathways, suggesting that loss of NLRC5-dependent classical MHC-I antigen processing pathway could trigger alternate antigen processing pathways [ 88 ]. The enrichment of distinct antibody responses and proteolytic pathways likely represent adaptations to compensate for the loss of NLRC5-dependent cytolytic immune effector cell functions. These adaptations may contribute to T cell infiltration and other immune effector cells giving rise to the necrotic areas in Nlrc5 -/- tumors that were not present in Rag1 −/− tumors. Evidently, these adaptations were insufficient to control tumor growth in Nlrc5 -/- mice as their tumor incidence and survival were not significantly different from Rag1 −/− mice. Our findings show that NLRC5 is needed for robust immune surveillance against endogenously arising tumors. NLRC5 expression in tumors promote enrichment of proteins involved in activation of antigen processing and presentation, CD8 T cell receptor binding and granzyme-mediated cytolytic immune effector cell pathways. NLRC5 plays an indispensable role in tumor immunoediting. The loss of NLRC5-dependent adaptive tumor immune surveillance mechanisms promotes compensatory activation of innate and humoral immune response pathways, however, these pathways are not sufficient for cancer immune surveillance and cancer immunoediting. Figure Legends Download figure Open in new tab Supplementary Figure S1. Validation of Nlrc5 −/− mice. (A) Flow cytometry evaluation of MHC-I expression in CD45 gated B cells, CD4+ T cells and CD8+ T cells with and without and IFNγ stimulation (20 ng mL −1 ) for the indicated periods. (B, C) NLRC5 deficiency impairs the induction of MHC-I (B) and antigen processing machinery genes (C). Freshly isolated and IFNγ-stimulated (20ng/ml) splenocytes from Nlrc5 -/- and Nlrc5 +/+ mice were evaluated for the expression of Nlrc5, B2m , H2-K and H2-D genes (B), and genes coding for LMP2 ( Psmb9 ), LMP7 ( Psmb8 ), TAP1 ( Tap1 ) and Tapasin ( Tapbp ) (C) by RT-qPCR. 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Share Essential role of NLRC5 in cancer immune surveillance and cancer immunoediting Akhil Shukla , Anny Armas Cayarga , Jean-François Lucier , Madanraj Appiya Santharam , Dominique Lévesque , François-Michel Boisvert , Sheela Ramanathan , Subburaj Ilangumaran bioRxiv 2025.02.03.636144; doi: https://doi.org/10.1101/2025.02.03.636144 Share This Article: Copy Citation Tools Essential role of NLRC5 in cancer immune surveillance and cancer immunoediting Akhil Shukla , Anny Armas Cayarga , Jean-François Lucier , Madanraj Appiya Santharam , Dominique Lévesque , François-Michel Boisvert , Sheela Ramanathan , Subburaj Ilangumaran bioRxiv 2025.02.03.636144; doi: https://doi.org/10.1101/2025.02.03.636144 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Immunology Subject Areas All Articles Animal Behavior and Cognition (7622) Biochemistry (17650) Bioengineering (13871) Bioinformatics (41881) Biophysics (21424) Cancer Biology (18566) Cell Biology (25461) Clinical Trials (138) Developmental Biology (13365) Ecology (19866) Epidemiology (2067) Evolutionary Biology (24290) Genetics (15590) Genomics (22476) Immunology (17713) Microbiology (40331) Molecular Biology (17148) Neuroscience (88473) Paleontology (666) Pathology (2827) Pharmacology and Toxicology (4816) Physiology (7635) Plant Biology (15114) Scientific Communication and Education (2044) Synthetic Biology (4286) Systems Biology (9815) Zoology (2268)