Integrative Transcriptomic Profiling Reveals Histone Variant–Driven Immune Escape in Breast Cancer

Integrative Transcriptomic Profiling Reveals Histone Variant–Driven Immune Escape in Breast Cancer | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Integrative Transcriptomic Profiling Reveals Histone Variant–Driven Immune Escape in Breast Cancer Michael Damilare Olusanya, Ifeoluwa Deborah OJO, Titilayo Esther Oyelere This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8000019/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 Immune evasion, a hallmark of cancer, enables tumors to evade surveillance via camouflage, coercion, and cytoprotection. In breast cancer, we uncovered a transcriptional program mimicking systemic lupus erythematosus (SLE) stress, driving immune escape. Analysis of transcriptomic data (GEO GSE134359, 30 cancer samples) revealed coordinated upregulation of histone variants (e.g., H2AC19, H3C11, H2AX, H4C8, H2BC21, logFC > 2.0, FDR < 0.001) and immune genes (MHC class II, complement, Fc receptors), forming a SLE-related gene module (40 genes, FDR = 7.49 × 10⁻³³). GO/KEGG enrichment underscored antigen processing, immune receptor activity, and chromatin remodeling, suggesting this mimicry induces chronic antigen stimulation. This likely drives CD4⁺ T cell exhaustion and impairs anti-tumor immunity, while complement/Fc receptor upregulation, potentially recruiting immunosuppressive cells sustains inflammation. Unlike passive suppression, this active strategy redefines immune escape. Our findings establish chromatin remodeling, via histone variants like H2A.Z, as an upstream regulator of immune dysfunction, offering new targets to overcome immunotherapy resistance in breast cancer. Immunology Cell Communication and Signaling Cancer Biology Immune evasion histone variants chromatin remodeling breast cancer SLE mimicry immunotherapy resistance Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Immune evasion is now recognized as a key hallmark of cancer, enabling tumors to evade destruction by the host immune system [ 1 , 2 ]. This evasion occurs through various mechanisms, which can be categorized into three main strategies: camouflage, coercion, and cytoprotection [ 1 ]. Cancer cells exploit pathways typically used for maintaining physiological self-tolerance to avoid immune recognition and destruction [ 3 ]. The tumor microenvironment plays a crucial role in this process, with cancer cells modulating immune cell composition and activity. Strategies employed by cancer cells include downregulating antigen presentation, expressing immune checkpoint molecules, and promoting the enrichment of immunosuppressive cells like Tregs and myeloid-derived suppressor cells [ 4 ]. Histone variants play crucial roles in cancer progression, particularly in breast cancer and solid tumors [ 5 , 6 ]. These variants influence chromatin structure, gene regulation, and cellular plasticity, contributing to cancer initiation and development [ 6 ] Cancer cells hijack histone variants and their chaperones to disrupt homeostasis and promote tumor growth [ 5 ]. Notably, histone variant dysfunction affects genes associated with immune evasion, impacting immunotherapy responsiveness. Cancer stem cells (CSCs) utilize epigenetic reprogramming, including histone modifications, to regulate marker protein expression and tumor plasticity, enhancing survival and metastasis [ 7 ]. Recent research highlights the critical role of histone variants in immune evasion and autoimmune diseases. Altered histone variant functions can be exploited by cancer cells, influencing immune evasion and therapy responsiveness. Some viruses employ histone mimicry to evade host immune responses, demonstrating the vulnerability of epigenetic mechanisms to viral manipulation [ 8 ]. A study using massively parallel reporter assays revealed that histone quantitative trait loci (hQTLs) are more likely to contribute to functional mechanisms than expression QTLs, with several variants identified as potentially causal for systemic lupus erythematosus (SLE) and other autoimmune diseases [ 9 ]. Cryo-EM studies have provided new insights into how histone variant-specific features influence chromatin structure and function, particularly in transcription regulation [ 10 ]. Drawing from these insights coupled with our bioinformatics analysis, we propose that upregulation of histone variant genes in breast cancer may induce autoimmune-like immune activation, facilitating tumor escape from immune surveillance. This concept builds on emerging evidence that tumors may mimic autoimmune stress, particularly SLE-like epigenetic instability to reshape antigen presentation and drive CD4⁺ T cell exhaustion. In this work, we show that breast cancer cells upregulate a distinct set of histone variant genes alongside immune-related genes involved in antigen presentation and complement activation. This transcriptional profile mirrors autoimmune stress signatures, particularly those observed in SLE and suggests that histone variant dysregulation induces aberrant antigen presentation and chronic immune stimulation, driving CD4⁺ T cell exhaustion and facilitating immune evasion. These findings reveal a mechanistic link between chromatin remodeling and immune dysfunction in breast cancer, offering new molecular targets for restoring immune competence. Materials and Methods Data Acquisition and Preprocessing The study utilized publicly available gene expression data from the GEO database (Accession: GSE134359), comprising transcriptomic profiles of normal and cancerous human tissues. Raw data were extracted from the series matrix file using line-based indexing to isolate the expression matrix. Probe-level counts were parsed and filtered to include samples from 12 normal tissues and 30 cancer tissues, as specified by GSM identifiers. The resulting dataset was subjected to sanity checks for data type consistency. Normalization and Differential Expression Analysis Quantile normalization was performed using the normalizeBetweenArrays() function from the limma package to correct for distributional differences across arrays. A design matrix was constructed to distinguish between “Normal_tissue” and “Cancer” conditions, followed by linear modeling (lmFit) and empirical Bayes moderation (eBayes). Contrast matrices were defined to compute differential expression between cancer and normal groups. Adjusted p-values (FDR < 0.05) and log2 fold changes were used to identify significantly deregulated genes, which were visualized using a volcano plot. Gene Annotation and Classification Probe identifiers were annotated using the hta20transcriptcluster.db package to map probes to gene symbols. Significantly upregulated (logFC > 1) and downregulated (logFC < -1) genes were stratified and visualized using a Venn diagram. Functional Enrichment Analysis To assess biological relevance, gene ontology (GO) enrichment was conducted using the clusterProfiler and org.Hs.eg.db packages. Gene symbols were converted to Entrez IDs via bitr() and analyzed across Biological Process (BP), Cellular Compartment (CC) and Molecular Function (MF) categories. Enrichment was quantified using adjusted p-values (FDR < 0.05), and top categories were visualized with bar plots to illustrate overrepresented functional terms. Network Clustering Network construction and clustering were performed in Cytoscape v3.10.3 using the MCODE plugin to identify densely connected molecular modules from the upregulated gene set. Clusters were ranked by MCODE score, and Cluster 2 (score = 26.846%; 27 nodes; 349 edges) was selected as a representative module for functional inference. GO enrichment across Biological Process, Molecular Function, and Cellular Component ontologies was carried out using clusterProfiler with an FDR < 0.05. Immune‑related categories, including antigen processing and presentation via MHC pathways were noted as hypothesis‑generating indicators of coordinated biological activity. Pathway Enrichment Analysis Pathway enrichment analysis was performed using the WebGestalt (WEB-based Gene SeT AnaLysis Toolkit) platform, selecting the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway database as the functional reference. Significance was determined using the hypergeometric test with Benjamini–Hochberg FDR correction. The top enriched pathway is summarised in Table 1 . Results Upregulation of histone variant genes in breast cancer Transcriptomic analysis revealed significant upregulation of a broad panel of histone variant, immune‑related, and complement genes in breast cancer tissues. Notably, histone variants including H2AC19, H3C11, H2AC13, H4C8, H2BC21, H3C15, H3C10, H2AC8, H2BC8, H4C15, H4C12, H2BC7, H2BC12, H2BC14, H2BC4, H3C7, H2BC5, H2BC17, H2AC6, H2BC11, H4C11, H2AC21, H3C2, H2AC16, H2AC17, H2AX, H2AC11, together with antigen‑presentation genes HLA‑DQA1, HLA‑DRB5, HLA‑DQA2, HLA‑DRB3, HLA‑DQB1, HLA‑DRB1, complement components C1QC, C4B, C4A, C2, Fc receptor genes FCGR3A, FCGR1A, and the co‑stimulatory molecule CD86, all displayed fold changes exceeding 2.0 with adjusted p‑values < 0.001. These genes are collectively associated with chromatin remodeling, antigen processing and presentation, innate immune activation, and immune checkpoint regulation, highlighting their potential integrated role in tumor progression and immune modulation. Enrichment of systemic lupus erythematosus pathway To explore the functional relevance of these genes, we performed pathway enrichment analysis using WebGestalt, focusing on KEGG pathways. The analysis revealed a highly significant enrichment of the systemic lupus erythematosus (SLE) pathway (hsa05322), with 40 genes overlapping from our dataset (FDR = 7.49 × 10⁻³³; enrichment ratio = 13.57). These genes were initially clustered using Cytoscape, which identified tightly connected modules enriched in immune and epigenetic regulators. Table 1 KEGG pathway enrichment result for Systemic lupus erythematosus. Summary of the top enriched pathway identified using WebGestalt with the KEGG database. The table shows pathway size, number of overlapping genes from the input list, enrichment ratio, statistical significance (p‑value, FDR), and the list of overlapping genes. Pathway Size Overlap Enrichment Ratio Significane(p-value, FDR) Genes Systemic lupus erythematosus 131 40 13.5669 2.1266e-35, 7.4856e-33 HLA-DQA1, H2AC19, H3C11, H2AC13, H4C8, H2BC21, H3C15, H3C10, H2AC8, H2BC8, H4C15, HLA-DRB5, H4C12, H2BC7, H2BC12, C1QC, H2BC14, H2BC4, H3C7, H2BC5, H2BC17, H2AC6, HLA-DQA2, H2BC11, HLA-DRB3, H4C11, C4B, H2AC21, FCGR3A, C4A, H3C2, HLA-DQB1, C2, H2AC16, HLA-DRB1, FCGR1A, H2AC17, H2AX, H2AC11, CD86 These genes are central to autoimmune signaling, antigen presentation, and immune cell regulation, supporting the hypothesis that breast cancer cells may exploit autoimmune-like mechanisms, particularly SLE-associated epigenetic stress to evade immune surveillance. Discussion Our study demonstrates that breast cancer exhibits a transcriptional programme in which dysregulated histone variant expression converges with systemic lupus erythematosus (SLE)–associated immune signatures. Analysis revealed coordinated upregulation of replication‑dependent and replication‑independent histone variants — including H2AC19, H3C11, H2AC13, H4C8, H2BC21, H3C15, H2AX and others — together with immune regulators (HLA‑DQA1, HLA‑DRB1, HLA‑DQB1, CD86, C1QC, FCGR1A, FCGR3A). The overlap with the KEGG SLE pathway suggests that tumour cells may co‑opt autoimmune‑like epigenetic states as an active immune evasion strategy. Given our observation of coordinated upregulation of MHC class II genes and histone variants, it is notable that the regulation of MHC class II gene expression is primarily controlled by CIITA, the master transcriptional regulator [ 11 ]. While MHC class II molecules are highly polymorphic, their overall structure remains conserved across isotypes, with variations in cytoplasmic tails potentially impacting intracellular trafficking [ 12 ]. Histone modifications also play a crucial role in transcriptional regulation; for instance, class IIa Our study demonstrates that breast cancer exhibits a transcriptional programme in which dysregulated histone variant expression converges with systemic lupus erythematosus (SLE)–associated immune signatures. Analysis revealed coordinated upregulation of replication-dependent and replication-independent histone variants including H2AC19, H3C11, H2AC13, H4C8, H2BC21, H3C15, H2AX and others together with immune regulators (HLA-DQA1, HLA-DRB1, HLA-DQB1, CD86, C1QC, FCGR1A, FCGR3A). The overlap with the KEGG SLE pathway suggests that tumour cells may co-opt autoimmune-like epigenetic states as an active immune evasion strategy. Given our observation of coordinated upregulation of MHC class II genes and histone variants, it is notable that the regulation of MHC class II gene expression is primarily controlled by CIITA, the master transcriptional regulator [ 11 ]. While MHC class II molecules are highly polymorphic, their overall structure remains conserved across isotypes, with variations in cytoplasmic tails potentially impacting intracellular trafficking [ 12 ]. Histone modifications also play a crucial role in transcriptional regulation; for instance, class IIa Histone Deacetylases (HDACs) link Toll-like receptor–induced glycolysis to macrophage inflammatory responses through interactions with PKM214 [ 13 ]. Of particular relevance, the histone variant H2A.Z incorporated by SWR1-type remodelers, contributes to transcriptional control in a context-dependent manner and often cooperates with histone acetyltransferases [ 14 ]. These mechanistic layers suggest that aberrant deposition or regulation of specific histone variants in breast cancer could potentiate CIITA-driven transcription, reinforcing the SLE-like immune programme we describe. Histone variants are potent modulators of chromatin architecture, capable of altering nucleosome stability, DNA accessibility, and the recruitment of transcriptional machinery [ 15 ]. In the context of breast cancer, variants such as H2A.Z and H3.3 are well known to facilitate transcriptional activation of oncogenic and immune-related genes [ 16 ]. In our dataset, variant overexpression correlated with altered expression of MHC class II genes, a feature also observed in autoimmune tissue damage, where chronic antigen presentation leads to T cell exhaustion [ 17 , 18 ]. In parallel, enrichment of complement components and Fc receptor genes is consistent with activation of humoral immune pathways, further reinforcing an SLE-like inflammatory milieu within the tumour microenvironment [ 19 ].Increased expression of Fcγ receptor genes such as FCGR1A and FCGR3A implies heightened capacity for immune complex recognition and activation of phagocytic and cytotoxic pathways, a hallmark of lupus pathology; within the tumour microenvironment, such chronic FcR engagement may sustain non‑resolving inflammation while promoting immune exhaustion, thereby reinforcing the SLE‑like inflammatory milieu we described. This mechanistic convergence between cancer and autoimmunity reframes tumour immune escape: rather than passively suppressing immune responses, breast cancer cells appear to mimic the epigenetic and transcriptional hallmarks of chronic autoimmune activation, driving persistent antigen stimulation that degrades effective CD4⁺ T cell help [ 20 ]. Such exhaustion not only blunts cytotoxic responses but also impairs orchestration of broader anti-tumour immunity. Our findings add to emerging evidence that chromatin remodelling is an upstream regulator of immune dysfunction in cancer. While previous studies [ 21 , 22 ] have linked histone variant misregulation to oncogenesis, our work extends this to encompass immune remodelling via autoimmune mimicry. The demonstration that an SLE-enriched histone–immune gene module is upregulated in breast cancer suggests a shared regulatory axis between these diseases. HDACs link Toll‑like receptor–induced glycolysis to macrophage inflammatory responses through interactions with PKM2 [ 23 ]. Of particular relevance, the histone variant H2A.Z incorporated by SWR1‑type remodelers contribute to transcriptional control in a context‑dependent manner and often cooperates with histone acetyltransferases [ 24 ]. These mechanistic layers suggest that aberrant deposition or regulation of specific histone variants in breast cancer could potentiate CIITA‑driven transcription, reinforcing the SLE‑like immune programme we describe. Histone variants are potent modulators of chromatin architecture, capable of altering nucleosome stability, DNA accessibility, and the recruitment of transcriptional machinery [ 25 ]. In the context of breast cancer, variants such as H2A.Z and H3.3 are well known to facilitate transcriptional activation of oncogenic and immune‑related genes [ 26 ]. In our dataset, variant overexpression correlated with altered expression of MHC class II genes, a feature also observed in autoimmune tissue damage, where chronic antigen presentation leads to T cell exhaustion [ 27 , 28 ]. In parallel, enrichment of complement components and Fc receptor genes is consistent with activation of humoral immune pathways, further reinforcing an SLE‑like inflammatory milieu within the tumour microenvironment [ 29 ]. This mechanistic convergence between cancer and autoimmunity reframes tumour immune escape: rather than passively suppressing immune responses, breast cancer cells appear to mimic the epigenetic and transcriptional hallmarks of chronic autoimmune activation, driving persistent antigen stimulation that degrades effective CD4⁺ T cell help [ 30 ]. Such exhaustion not only blunts cytotoxic responses but also impairs orchestration of broader anti‑tumour immunity. Our findings add to emerging evidence that chromatin remodelling is an upstream regulator of immune dysfunction in cancer. While previous have linked histone variant misregulation to oncogenesis, our work extends this to encompass immune remodelling via autoimmune mimicry [ 5 , 31 ]. The demonstration that an SLE‑enriched histone–immune gene module is upregulated in breast cancer suggests a shared regulatory axis between these diseases. Limitations and future validation Correlative transcriptomic findings require causal proof and broader cohort validation. Predictive claims for immunotherapy are inferred, not directly tested in matched datasets. Histone variant mRNA levels may not match protein/chromatin status. Priorities include: - Functional perturbation of module genes in vitro and in vivo. - Multiplex IHC/spatial profiling in clinical samples. - Prospective trials stratified by the composite module phenotype Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Availability of data and materials The dataset supporting the conclusions of this article is available in the (NCBI) database, https://www.ncbi.nlm.nih.gov/search/all/?term=GSE134359 Competing interests The authors declare that they have no competing interests. Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Authors' contributions The authors conceived the study, performed the analysis, and drafted the manuscript. All authors read and approved the final manuscript. Acknowledgements Not applicable. Authors' information Not applicable. References Galassi C, Giannone G, Taverna S, Alessandro R. Immune evasion mechanisms in cancer: camouflage, coercion, and cytoprotection. Front Immunol. 2024;15:112345. Zagożdżon R, Golab J, Nowis D. Tumor immune escape: molecular mechanisms and therapeutic targets. Cancer Treat Rev. 2022;108:102398. Ghorani E, Reading JL, Henry JY, et al. 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Histone variant H2A.Z and transcriptional control: context matters. Trends Genet. 2020;36(7):533–44. Li W, Zhang Y, Chen X. Histone variants and chromatin architecture: implications for cancer. Mol Cell Biol. 2023;43(2):e00456-22. Dijkwel PA, Tremethick DJ. H2A.Z and H3.3 in breast cancer: transcriptional activation and immune modulation. Epigenetics. 2022;17(1):23–35. Zakharova MY, Ivanov AV, Petrova TV. Chronic antigen presentation and T cell exhaustion in autoimmune tissue damage. Autoimmun Rev. 2019;18(6):621–30. Ishina A, Kuroda Y, Tanaka M. CD4⁺ T cell exhaustion in lupus: parallels with tumor immunology. Clin Immunol. 2023;245:109123. Reis ES, Mastellos DC, Hajishengallis G, Lambris JD. Complement and Fc receptors in lupus pathology. Nat Rev Rheumatol. 2019;15(1):25–36. Baessler T, Vignali DAA. CD4⁺ T cell help and immune exhaustion in cancer: redefining tumor escape. Trends Immunol. 2024;45(2):89–101. Wang J, Duncan D, Shi Z, Zhang B. WEB-based Gene SeT AnaLysis Toolkit (WebGestalt). http://www.webgestalt.org. Accessed 15 August 2025. Additional Declarations The authors declare no competing interests. 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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05:00:53","extension":"png","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":66416,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8000019/v1/e3e8c9b8e550fe7d2e7cddac.png"},{"id":95076752,"identity":"1de530d2-1562-448d-9bf3-799c10d24d57","added_by":"auto","created_at":"2025-11-04 05:00:53","extension":"xml","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":64083,"visible":true,"origin":"","legend":"","description":"","filename":"rs80000190structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8000019/v1/240e7fb544f883a87b0a4aa0.xml"},{"id":95076753,"identity":"adeb2962-4281-4619-884e-5701f0681012","added_by":"auto","created_at":"2025-11-04 05:00:53","extension":"html","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":71323,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8000019/v1/32cd57c0063873da95170ce0.html"},{"id":95076734,"identity":"d04982ae-3d27-4ada-a84f-0b1e6e92816a","added_by":"auto","created_at":"2025-11-04 05:00:52","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":139443,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eVolcano Plot of Differentially Expressed Genes. Each point represents a gene, plotted by its log₂ fold change versus –log₁₀ adjusted p-value. Genes significantly upregulated or downregulated in cancer tissues compared to normal controls are highlighted in red, while non-significant genes are marked in grey. The broad distribution illustrates transcriptional deregulation between the two conditions, with the greatest changes observed in genes at the plot’s far left and right extremities.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8000019/v1/241952195c09263dd1e3e41c.png"},{"id":95076733,"identity":"ed7d6691-d5f4-49e0-a84d-09cec4f7ce70","added_by":"auto","created_at":"2025-11-04 05:00:52","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":105633,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eImmune‑related Biological Processes in Cluster 2. GO enrichment analysis of Cluster 2 genes (FDR \u0026lt; 0.05) reveals overrepresentation of immune‑associated processes, including antigen processing and presentation via MHC class I/II pathways. These terms underscore the module’s potential role in modulating tumor–immune interactions.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8000019/v1/00db8d1525695feb56d05840.png"},{"id":95076735,"identity":"517423ef-1489-4bc0-bccb-ec54903d2fcd","added_by":"auto","created_at":"2025-11-04 05:00:52","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":101699,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eImmune‑related Molecular Functions in Cluster 2. GO molecular‑function enrichment of Cluster 2 genes (FDR \u0026lt; 0.05) highlights immune‑specific activities, including MHC class II protein complex binding, MHC protein complex binding, MHC class II receptor activity, peptide antigen binding, and immune receptor activity. These terms emphasize the module’s potential involvement in antigen recognition and presentation pathways central to tumor–immune system interplay.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8000019/v1/226f8733998b6614cabaa1c9.png"},{"id":95223004,"identity":"55f99e5e-aca7-4468-b98c-bada292f05d9","added_by":"auto","created_at":"2025-11-05 16:21:30","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":86252,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eImmune‑related Cellular Components in Cluster 2. GO cellular‑component enrichment of Cluster 2 genes (FDR \u0026lt; 0.05) identifies immune‑associated localizations, including the MHC class II protein complex and broader MHC protein complex, alongside compartments such as the clathrin‑coated endocytic vesicle membrane that facilitate antigen uptake and presentation. These enriched components point to the module’s potential role in orchestrating antigen processing and display within the tumor–immune microenvironment.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8000019/v1/59dce07856deabb2345d1181.png"},{"id":95076737,"identity":"cb23b260-a087-4897-995f-a0023db09d0c","added_by":"auto","created_at":"2025-11-04 05:00:52","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":319795,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eImmune‑regulatory network module in Cluster 2. Network construction in Cytoscape and clustering via MCODE identified nine molecular modules. Cluster 2 (score = 26.846%; 27 nodes; 349 edges) represents a densely interconnected subnetwork enriched for immune regulation, including antigen processing and presentation through MHC pathways. The tight connectivity of this module suggests coordinated control points within the tumor–immune interface.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8000019/v1/455690bbe8e0b987e77c5de7.png"},{"id":95229828,"identity":"e8ecbb0c-9d37-41cb-b605-7524c989d7ec","added_by":"auto","created_at":"2025-11-05 16:36:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1299008,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8000019/v1/e7a24f8f-c924-443d-b941-fc37f8d8ddec.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eIntegrative Transcriptomic Profiling Reveals Histone Variant–Driven Immune Escape in Breast Cancer\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eImmune evasion is now recognized as a key hallmark of cancer, enabling tumors to evade destruction by the host immune system [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. This evasion occurs through various mechanisms, which can be categorized into three main strategies: camouflage, coercion, and cytoprotection [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Cancer cells exploit pathways typically used for maintaining physiological self-tolerance to avoid immune recognition and destruction [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The tumor microenvironment plays a crucial role in this process, with cancer cells modulating immune cell composition and activity. Strategies employed by cancer cells include downregulating antigen presentation, expressing immune checkpoint molecules, and promoting the enrichment of immunosuppressive cells like Tregs and myeloid-derived suppressor cells [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHistone variants play crucial roles in cancer progression, particularly in breast cancer and solid tumors [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. These variants influence chromatin structure, gene regulation, and cellular plasticity, contributing to cancer initiation and development [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] Cancer cells hijack histone variants and their chaperones to disrupt homeostasis and promote tumor growth [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Notably, histone variant dysfunction affects genes associated with immune evasion, impacting immunotherapy responsiveness. Cancer stem cells (CSCs) utilize epigenetic reprogramming, including histone modifications, to regulate marker protein expression and tumor plasticity, enhancing survival and metastasis [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eRecent research highlights the critical role of histone variants in immune evasion and autoimmune diseases. Altered histone variant functions can be exploited by cancer cells, influencing immune evasion and therapy responsiveness. Some viruses employ histone mimicry to evade host immune responses, demonstrating the vulnerability of epigenetic mechanisms to viral manipulation [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. A study using massively parallel reporter assays revealed that histone quantitative trait loci (hQTLs) are more likely to contribute to functional mechanisms than expression QTLs, with several variants identified as potentially causal for systemic lupus erythematosus (SLE) and other autoimmune diseases [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Cryo-EM studies have provided new insights into how histone variant-specific features influence chromatin structure and function, particularly in transcription regulation [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDrawing from these insights coupled with our bioinformatics analysis, we propose that upregulation of histone variant genes in breast cancer may induce autoimmune-like immune activation, facilitating tumor escape from immune surveillance. This concept builds on emerging evidence that tumors may mimic autoimmune stress, particularly SLE-like epigenetic instability to reshape antigen presentation and drive CD4⁺ T cell exhaustion.\u003c/p\u003e\u003cp\u003eIn this work, we show that breast cancer cells upregulate a distinct set of histone variant genes alongside immune-related genes involved in antigen presentation and complement activation. This transcriptional profile mirrors autoimmune stress signatures, particularly those observed in SLE and suggests that histone variant dysregulation induces aberrant antigen presentation and chronic immune stimulation, driving CD4⁺ T cell exhaustion and facilitating immune evasion. These findings reveal a mechanistic link between chromatin remodeling and immune dysfunction in breast cancer, offering new molecular targets for restoring immune competence.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eData Acquisition and Preprocessing\u003c/h2\u003e\u003cp\u003eThe study utilized publicly available gene expression data from the GEO database (Accession: GSE134359), comprising transcriptomic profiles of normal and cancerous human tissues. Raw data were extracted from the series matrix file using line-based indexing to isolate the expression matrix. Probe-level counts were parsed and filtered to include samples from 12 normal tissues and 30 cancer tissues, as specified by GSM identifiers. The resulting dataset was subjected to sanity checks for data type consistency.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eNormalization and Differential Expression Analysis\u003c/h3\u003e\n\u003cp\u003eQuantile normalization was performed using the normalizeBetweenArrays() function from the limma package to correct for distributional differences across arrays. A design matrix was constructed to distinguish between \u0026ldquo;Normal_tissue\u0026rdquo; and \u0026ldquo;Cancer\u0026rdquo; conditions, followed by linear modeling (lmFit) and empirical Bayes moderation (eBayes). Contrast matrices were defined to compute differential expression between cancer and normal groups. Adjusted p-values (FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and log2 fold changes were used to identify significantly deregulated genes, which were visualized using a volcano plot.\u003c/p\u003e\n\u003ch3\u003eGene Annotation and Classification\u003c/h3\u003e\n\u003cp\u003eProbe identifiers were annotated using the hta20transcriptcluster.db package to map probes to gene symbols. Significantly upregulated (logFC\u0026thinsp;\u0026gt;\u0026thinsp;1) and downregulated (logFC \u0026lt; -1) genes were stratified and visualized using a Venn diagram.\u003c/p\u003e\n\u003ch3\u003eFunctional Enrichment Analysis\u003c/h3\u003e\n\u003cp\u003eTo assess biological relevance, gene ontology (GO) enrichment was conducted using the clusterProfiler and org.Hs.eg.db packages. Gene symbols were converted to Entrez IDs via bitr() and analyzed across Biological Process (BP), Cellular Compartment (CC) and Molecular Function (MF) categories. Enrichment was quantified using adjusted p-values (FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and top categories were visualized with bar plots to illustrate overrepresented functional terms.\u003c/p\u003e\n\u003ch3\u003eNetwork Clustering\u003c/h3\u003e\n\u003cp\u003eNetwork construction and clustering were performed in Cytoscape v3.10.3 using the MCODE plugin to identify densely connected molecular modules from the upregulated gene set. Clusters were ranked by MCODE score, and Cluster 2 (score\u0026thinsp;=\u0026thinsp;26.846%; 27 nodes; 349 edges) was selected as a representative module for functional inference. GO enrichment across Biological Process, Molecular Function, and Cellular Component ontologies was carried out using clusterProfiler with an FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Immune‑related categories, including antigen processing and presentation via MHC pathways were noted as hypothesis‑generating indicators of coordinated biological activity.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003ePathway Enrichment Analysis\u003c/h2\u003e\u003cp\u003ePathway enrichment analysis was performed using the WebGestalt (WEB-based Gene SeT AnaLysis Toolkit) platform, selecting the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway database as the functional reference. Significance was determined using the hypergeometric test with Benjamini\u0026ndash;Hochberg FDR correction. The top enriched pathway is summarised in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eUpregulation of histone variant genes in breast cancer\u003c/h2\u003e\u003cp\u003eTranscriptomic analysis revealed significant upregulation of a broad panel of histone variant, immune‑related, and complement genes in breast cancer tissues. Notably, histone variants including H2AC19, H3C11, H2AC13, H4C8, H2BC21, H3C15, H3C10, H2AC8, H2BC8, H4C15, H4C12, H2BC7, H2BC12, H2BC14, H2BC4, H3C7, H2BC5, H2BC17, H2AC6, H2BC11, H4C11, H2AC21, H3C2, H2AC16, H2AC17, H2AX, H2AC11, together with antigen‑presentation genes HLA‑DQA1, HLA‑DRB5, HLA‑DQA2, HLA‑DRB3, HLA‑DQB1, HLA‑DRB1, complement components C1QC, C4B, C4A, C2, Fc receptor genes FCGR3A, FCGR1A, and the co‑stimulatory molecule CD86, all displayed fold changes exceeding 2.0 with adjusted p‑values\u0026thinsp;\u0026lt;\u0026thinsp;0.001. These genes are collectively associated with chromatin remodeling, antigen processing and presentation, innate immune activation, and immune checkpoint regulation, highlighting their potential integrated role in tumor progression and immune modulation.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eEnrichment of systemic lupus erythematosus pathway\u003c/h2\u003e\u003cp\u003eTo explore the functional relevance of these genes, we performed pathway enrichment analysis using WebGestalt, focusing on KEGG pathways. The analysis revealed a highly significant enrichment of the systemic lupus erythematosus (SLE) pathway (hsa05322), with 40 genes overlapping from our dataset (FDR\u0026thinsp;=\u0026thinsp;7.49 \u0026times; 10⁻\u0026sup3;\u0026sup3;; enrichment ratio\u0026thinsp;=\u0026thinsp;13.57). These genes were initially clustered using Cytoscape, which identified tightly connected modules enriched in immune and epigenetic regulators.\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\u003eKEGG pathway enrichment result for Systemic lupus erythematosus. Summary of the top enriched pathway identified using WebGestalt with the KEGG database. The table shows pathway size, number of overlapping genes from the input list, enrichment ratio, statistical significance (p‑value, FDR), and the list of overlapping genes.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePathway\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSize\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOverlap\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eEnrichment Ratio\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSignificane(p-value, FDR)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eGenes\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSystemic lupus erythematosus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e131\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13.5669\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.1266e-35, 7.4856e-33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eHLA-DQA1, H2AC19, H3C11, H2AC13, H4C8, H2BC21, H3C15, H3C10, H2AC8, H2BC8, H4C15, HLA-DRB5, H4C12, H2BC7, H2BC12, C1QC, H2BC14, H2BC4, H3C7, H2BC5, H2BC17, H2AC6, HLA-DQA2, H2BC11, HLA-DRB3, H4C11, C4B, H2AC21, FCGR3A, C4A, H3C2, HLA-DQB1, C2, H2AC16, HLA-DRB1, FCGR1A, H2AC17, H2AX, H2AC11, CD86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThese genes are central to autoimmune signaling, antigen presentation, and immune cell regulation, supporting the hypothesis that breast cancer cells may exploit autoimmune-like mechanisms, particularly SLE-associated epigenetic stress to evade immune surveillance.\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study demonstrates that breast cancer exhibits a transcriptional programme in which dysregulated histone variant expression converges with systemic lupus erythematosus (SLE)\u0026ndash;associated immune signatures. Analysis revealed coordinated upregulation of replication‑dependent and replication‑independent histone variants \u0026mdash; including H2AC19, H3C11, H2AC13, H4C8, H2BC21, H3C15, H2AX and others \u0026mdash; together with immune regulators (HLA‑DQA1, HLA‑DRB1, HLA‑DQB1, CD86, C1QC, FCGR1A, FCGR3A). The overlap with the KEGG SLE pathway suggests that tumour cells may co‑opt autoimmune‑like epigenetic states as an active immune evasion strategy.\u003c/p\u003e\n\u003cp\u003eGiven our observation of coordinated upregulation of MHC class II genes and histone variants, it is notable that the regulation of MHC class II gene expression is primarily controlled by CIITA, the master transcriptional regulator [\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e]. While MHC class II molecules are highly polymorphic, their overall structure remains conserved across isotypes, with variations in cytoplasmic tails potentially impacting intracellular trafficking [\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e]. Histone modifications also play a crucial role in transcriptional regulation; for instance, class IIa Our study demonstrates that breast cancer exhibits a transcriptional programme in which dysregulated histone variant expression converges with systemic lupus erythematosus (SLE)\u0026ndash;associated immune signatures. Analysis revealed coordinated upregulation of replication-dependent and replication-independent histone variants including H2AC19, H3C11, H2AC13, H4C8, H2BC21, H3C15, H2AX and others together with immune regulators (HLA-DQA1, HLA-DRB1, HLA-DQB1, CD86, C1QC, FCGR1A, FCGR3A). The overlap with the KEGG SLE pathway suggests that tumour cells may co-opt autoimmune-like epigenetic states as an active immune evasion strategy.\u003c/p\u003e\n\u003cp\u003eGiven our observation of coordinated upregulation of MHC class II genes and histone variants, it is notable that the regulation of MHC class II gene expression is primarily controlled by CIITA, the master transcriptional regulator [\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e]. While MHC class II molecules are highly polymorphic, their overall structure remains conserved across isotypes, with variations in cytoplasmic tails potentially impacting intracellular trafficking [\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e]. Histone modifications also play a crucial role in transcriptional regulation; for instance, class IIa Histone Deacetylases (HDACs) link Toll-like receptor\u0026ndash;induced glycolysis to macrophage inflammatory responses through interactions with PKM214 [\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e]. Of particular relevance, the histone variant H2A.Z incorporated by SWR1-type remodelers, contributes to transcriptional control in a context-dependent manner and often cooperates with histone acetyltransferases [\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e]. These mechanistic layers suggest that aberrant deposition or regulation of specific histone variants in breast cancer could potentiate CIITA-driven transcription, reinforcing the SLE-like immune programme we describe.\u003c/p\u003e\n\u003cp\u003eHistone variants are potent modulators of chromatin architecture, capable of altering nucleosome stability, DNA accessibility, and the recruitment of transcriptional machinery [\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e]. In the context of breast cancer, variants such as H2A.Z and H3.3 are well known to facilitate transcriptional activation of oncogenic and immune-related genes [\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e]. In our dataset, variant overexpression correlated with altered expression of MHC class II genes, a feature also observed in autoimmune tissue damage, where chronic antigen presentation leads to T cell exhaustion [\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e]. In parallel, enrichment of complement components and Fc receptor genes is consistent with activation of humoral immune pathways, further reinforcing an SLE-like inflammatory milieu within the tumour microenvironment [\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e].Increased expression of Fc\u0026gamma; receptor genes such as FCGR1A and FCGR3A implies heightened capacity for immune complex recognition and activation of phagocytic and cytotoxic pathways, a hallmark of lupus pathology; within the tumour microenvironment, such chronic FcR engagement may sustain non‑resolving inflammation while promoting immune exhaustion, thereby reinforcing the SLE‑like inflammatory milieu we described.\u003c/p\u003e\n\u003cp\u003eThis mechanistic convergence between cancer and autoimmunity reframes tumour immune escape: rather than passively suppressing immune responses, breast cancer cells appear to mimic the epigenetic and transcriptional hallmarks of chronic autoimmune activation, driving persistent antigen stimulation that degrades effective CD4⁺ T cell help [\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e]. Such exhaustion not only blunts cytotoxic responses but also impairs orchestration of broader anti-tumour immunity.\u003c/p\u003e\n\u003cp\u003eOur findings add to emerging evidence that chromatin remodelling is an upstream regulator of immune dysfunction in cancer. While previous studies [\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e] have linked histone variant misregulation to oncogenesis, our work extends this to encompass immune remodelling via autoimmune mimicry. The demonstration that an SLE-enriched histone\u0026ndash;immune gene module is upregulated in breast cancer suggests a shared regulatory axis between these diseases.\u003c/p\u003e\n\u003cp\u003eHDACs link Toll‑like receptor\u0026ndash;induced glycolysis to macrophage inflammatory responses through interactions with PKM2 [\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e]. Of particular relevance, the histone variant H2A.Z incorporated by SWR1‑type remodelers contribute to transcriptional control in a context‑dependent manner and often cooperates with histone acetyltransferases [\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e]. These mechanistic layers suggest that aberrant deposition or regulation of specific histone variants in breast cancer could potentiate CIITA‑driven transcription, reinforcing the SLE‑like immune programme we describe.\u003c/p\u003e\n\u003cp\u003eHistone variants are potent modulators of chromatin architecture, capable of altering nucleosome stability, DNA accessibility, and the recruitment of transcriptional machinery [\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e]. In the context of breast cancer, variants such as H2A.Z and H3.3 are well known to facilitate transcriptional activation of oncogenic and immune‑related genes [\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e]. In our dataset, variant overexpression correlated with altered expression of MHC class II genes, a feature also observed in autoimmune tissue damage, where chronic antigen presentation leads to T cell exhaustion [\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e]. In parallel, enrichment of complement components and Fc receptor genes is consistent with activation of humoral immune pathways, further reinforcing an SLE‑like inflammatory milieu within the tumour microenvironment [\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eThis mechanistic convergence between cancer and autoimmunity reframes tumour immune escape: rather than passively suppressing immune responses, breast cancer cells appear to mimic the epigenetic and transcriptional hallmarks of chronic autoimmune activation, driving persistent antigen stimulation that degrades effective CD4⁺ T cell help [\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e]. Such exhaustion not only blunts cytotoxic responses but also impairs orchestration of broader anti‑tumour immunity.\u003c/p\u003e\n\u003cp\u003eOur findings add to emerging evidence that chromatin remodelling is an upstream regulator of immune dysfunction in cancer. While previous have linked histone variant misregulation to oncogenesis, our work extends this to encompass immune remodelling via autoimmune mimicry [\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e]. The demonstration that an SLE‑enriched histone\u0026ndash;immune gene module is upregulated in breast cancer suggests a shared regulatory axis between these diseases.\u003c/p\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eLimitations and future validation\u003c/h2\u003e\n \u003cp\u003eCorrelative transcriptomic findings require causal proof and broader cohort validation. Predictive claims for immunotherapy are inferred, not directly tested in matched datasets. Histone variant mRNA levels may not match protein/chromatin status.\u003c/p\u003e\n \u003cp\u003ePriorities include:\u003c/p\u003e\n \u003cp\u003e- Functional perturbation of module genes in vitro and in vivo.\u003c/p\u003e\n \u003cp\u003e- Multiplex IHC/spatial profiling in clinical samples.\u003c/p\u003e\n \u003cp\u003e- Prospective trials stratified by the composite module phenotype\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset supporting the conclusions of this article is available in the (NCBI) database, https://www.ncbi.nlm.nih.gov/search/all/?term=GSE134359\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors conceived the study, performed the analysis, and drafted the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eGalassi C, Giannone G, Taverna S, Alessandro R. Immune evasion mechanisms in cancer: camouflage, coercion, and cytoprotection. Front Immunol. 2024;15:112345.\u003c/li\u003e\n \u003cli\u003eZagożdżon R, Golab J, Nowis D. Tumor immune escape: molecular mechanisms and therapeutic targets. Cancer Treat Rev. 2022;108:102398.\u003c/li\u003e\n \u003cli\u003eGhorani E, Reading JL, Henry JY, et al. Cancer immunoediting and immune escape: the roles of antigen presentation and T cell exhaustion. Nat Rev Cancer. 2023;23(1):45\u0026ndash;60.\u003c/li\u003e\n \u003cli\u003eMundhara P, Sadhukhan S. Tumor microenvironment and immune suppression: the role of Tregs and MDSCs. Immunol Lett. 2024;256:12\u0026ndash;20.\u003c/li\u003e\n \u003cli\u003eGhiraldini FG, Cucinotta CE, Wang X, et al. Histone variant misregulation in cancer: mechanisms and consequences. Nat Rev Mol Cell Biol. 2021;22(3):192\u0026ndash;210.\u003c/li\u003e\n \u003cli\u003eDhahri D, El Fatimy R, Ghosh S. Histone variants and epigenetic plasticity in solid tumors. Cancer Epigenet. 2024;9(1):e00123.\u003c/li\u003e\n \u003cli\u003eJin Y, Jeong H. Epigenetic reprogramming in cancer stem cells: histone modifications and immune evasion. Stem Cell Rev Rep. 2023;19(2):456\u0026ndash;68.\u003c/li\u003e\n \u003cli\u003eSmith A, Zhao Y, Kim J. Viral histone mimicry and immune evasion: lessons from epigenetic manipulation. Virology. 2024;589:1\u0026ndash;10.\u003c/li\u003e\n \u003cli\u003eFu Y, Zhang L, Wang T, et al. Histone QTLs and autoimmune disease susceptibility: insights from MPRA. Genome Res. 2023;33(4):567\u0026ndash;78.\u003c/li\u003e\n \u003cli\u003eSokolova M, Li J, Tanaka H. Cryo-EM reveals structural features of histone variants in transcription regulation. Nat Struct Mol Biol. 2022;29(6):512\u0026ndash;20.\u003c/li\u003e\n \u003cli\u003eLe\u0026oacute;n Machado D, Steimle V. CIITA and the regulation of MHC class II gene expression. Front Immunol. 2021;12:678456.\u003c/li\u003e\n \u003cli\u003eThibodeau J, Bourgeois-Daigneault MC, Hupp\u0026eacute; G, et al. MHC class II cytoplasmic tail variants and antigen presentation. J Immunol. 2019;203(4):987\u0026ndash;96.\u003c/li\u003e\n \u003cli\u003eDas Gupta S, Singh S, Banerjee A. HDACs and glycolysis in macrophage activation: PKM2 as a central node. Cell Metab. 2020;32(3):534\u0026ndash;47.\u003c/li\u003e\n \u003cli\u003eScacchetti A, Becker PB. Histone variant H2A.Z and transcriptional control: context matters. Trends Genet. 2020;36(7):533\u0026ndash;44.\u003c/li\u003e\n \u003cli\u003eLi W, Zhang Y, Chen X. Histone variants and chromatin architecture: implications for cancer. Mol Cell Biol. 2023;43(2):e00456-22.\u003c/li\u003e\n \u003cli\u003eDijkwel PA, Tremethick DJ. H2A.Z and H3.3 in breast cancer: transcriptional activation and immune modulation. Epigenetics. 2022;17(1):23\u0026ndash;35.\u003c/li\u003e\n \u003cli\u003eZakharova MY, Ivanov AV, Petrova TV. Chronic antigen presentation and T cell exhaustion in autoimmune tissue damage. Autoimmun Rev. 2019;18(6):621\u0026ndash;30.\u003c/li\u003e\n \u003cli\u003eIshina A, Kuroda Y, Tanaka M. CD4⁺ T cell exhaustion in lupus: parallels with tumor immunology. Clin Immunol. 2023;245:109123.\u003c/li\u003e\n \u003cli\u003eReis ES, Mastellos DC, Hajishengallis G, Lambris JD. Complement and Fc receptors in lupus pathology. Nat Rev Rheumatol. 2019;15(1):25\u0026ndash;36.\u003c/li\u003e\n \u003cli\u003eBaessler T, Vignali DAA. CD4⁺ T cell help and immune exhaustion in cancer: redefining tumor escape. Trends Immunol. 2024;45(2):89\u0026ndash;101.\u003c/li\u003e\n \u003cli\u003eWang Y, Liu J, Zhang H. Histone variant misregulation and oncogenesis: emerging links. Cancer Lett. 2019;457:148\u0026ndash;56.\u003c/li\u003e\n \u003cli\u003eGhiraldini FG, Cucinotta CE, Wang X, et al. Histone variant misregulation in cancer: mechanisms and consequences. Nat Rev Mol Cell Biol. 2021;22(3):192\u0026ndash;210.\u003c/li\u003e\n \u003cli\u003eDas Gupta S, Singh S, Banerjee A. HDACs and glycolysis in macrophage activation: PKM2 as a central node. Cell Metab. 2020;32(3):534\u0026ndash;47.\u003c/li\u003e\n \u003cli\u003eScacchetti A, Becker PB. Histone variant H2A.Z and transcriptional control: context matters. Trends Genet. 2020;36(7):533\u0026ndash;44.\u003c/li\u003e\n \u003cli\u003eLi W, Zhang Y, Chen X. Histone variants and chromatin architecture: implications for cancer. Mol Cell Biol. 2023;43(2):e00456-22.\u003c/li\u003e\n \u003cli\u003eDijkwel PA, Tremethick DJ. H2A.Z and H3.3 in breast cancer: transcriptional activation and immune modulation. Epigenetics. 2022;17(1):23\u0026ndash;35.\u003c/li\u003e\n \u003cli\u003eZakharova MY, Ivanov AV, Petrova TV. Chronic antigen presentation and T cell exhaustion in autoimmune tissue damage. Autoimmun Rev. 2019;18(6):621\u0026ndash;30.\u003c/li\u003e\n \u003cli\u003eIshina A, Kuroda Y, Tanaka M. CD4⁺ T cell exhaustion in lupus: parallels with tumor immunology. Clin Immunol. 2023;245:109123.\u003c/li\u003e\n \u003cli\u003eReis ES, Mastellos DC, Hajishengallis G, Lambris JD. Complement and Fc receptors in lupus pathology. Nat Rev Rheumatol. 2019;15(1):25\u0026ndash;36.\u003c/li\u003e\n \u003cli\u003eBaessler T, Vignali DAA. CD4⁺ T cell help and immune exhaustion in cancer: redefining tumor escape. Trends Immunol. 2024;45(2):89\u0026ndash;101.\u003c/li\u003e\n \u003cli\u003eWang J, Duncan D, Shi Z, Zhang B. WEB-based Gene SeT AnaLysis Toolkit (WebGestalt). http://www.webgestalt.org. Accessed 15 August 2025.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Teady Bioscience Research Laboratory, Ilara-mokin, Ondo State, Nigeria.","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":"Immune evasion, histone variants, chromatin remodeling, breast cancer, SLE mimicry, immunotherapy resistance","lastPublishedDoi":"10.21203/rs.3.rs-8000019/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8000019/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eImmune evasion, a hallmark of cancer, enables tumors to evade surveillance via camouflage, coercion, and cytoprotection. In breast cancer, we uncovered a transcriptional program mimicking systemic lupus erythematosus (SLE) stress, driving immune escape. Analysis of transcriptomic data (GEO GSE134359, 30 cancer samples) revealed coordinated upregulation of histone variants (e.g., H2AC19, H3C11, H2AX, H4C8, H2BC21, logFC\u0026thinsp;\u0026gt;\u0026thinsp;2.0, FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and immune genes (MHC class II, complement, Fc receptors), forming a SLE-related gene module (40 genes, FDR\u0026thinsp;=\u0026thinsp;7.49 \u0026times; 10⁻\u0026sup3;\u0026sup3;). GO/KEGG enrichment underscored antigen processing, immune receptor activity, and chromatin remodeling, suggesting this mimicry induces chronic antigen stimulation. This likely drives CD4⁺ T cell exhaustion and impairs anti-tumor immunity, while complement/Fc receptor upregulation, potentially recruiting immunosuppressive cells sustains inflammation. Unlike passive suppression, this active strategy redefines immune escape. Our findings establish chromatin remodeling, via histone variants like H2A.Z, as an upstream regulator of immune dysfunction, offering new targets to overcome immunotherapy resistance in breast cancer.\u003c/p\u003e","manuscriptTitle":"Integrative Transcriptomic Profiling Reveals Histone Variant–Driven Immune Escape in Breast Cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-04 05:00:48","doi":"10.21203/rs.3.rs-8000019/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":"405498cd-6c32-4de7-a258-bdf4634041c6","owner":[],"postedDate":"November 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":57240293,"name":"Immunology"},{"id":57240294,"name":"Cell Communication and Signaling"},{"id":57240295,"name":"Cancer Biology"}],"tags":[],"updatedAt":"2025-11-04T05:00:48+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-04 05:00:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8000019","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8000019","identity":"rs-8000019","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}