TRIM37 expression is associated with prognosis and immune-related features in luminal A breast cancer and hepatocellular carcinoma

TRIM37 expression is associated with prognosis and immune-related features in luminal A breast cancer and hepatocellular carcinoma | 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 TRIM37 expression is associated with prognosis and immune-related features in luminal A breast cancer and hepatocellular carcinoma Xiaozhong Teng, Pengyu Li, Zhicheng Zheng, Kai Li, Feng Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9298547/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Tripartite motif-containing protein 37 (TRIM37), an innate immunity–related E3 ubiquitin ligase, is increasingly implicated in tumor biology; however, its prognostic relevance and relationship to the tumor immune microenvironment across human cancers remain poorly defined. In the present study, we examined TRIM37 expression, clinical outcomes, prognostic importance, and immune associations of TRIM37 across multiple human cancers using publicly available cancer genomics and immunology databases. Analyses incorporated data from Oncomine, TIMER2.0, GEPIA2, TISIDB, CVCDAP, Kaplan–Meier plotter, and bc-GenExMiner to assess expression patterns, survival outcomes, and immune correlations. TRIM37 overexpression was observed in several malignancies, including breast, esophageal, head and neck, liver hepatocellular, lung adenocarcinoma, lung squamous cell carcinoma, and gastric cancers, collectively termed TRIM37-overexpressing cancers. Higher TRIM37 expression was associated with adverse prognosis, particularly in luminal A breast cancer and liver hepatocellular carcinoma. In breast cancer, TRIM37 expression was associated with multiple immunomodulators and immune cell infiltration. Notably, in luminal A tumors, high TRIM37 expression coincided with increased Th2-related immune populations, regulatory T cells, and M2 macrophages, alongside reduced Th1-associated CD8 + T cells and natural killer cells, consistent with an immunosuppressive tumor microenvironment. These findings identify TRIM37 as a candidate prognostic biomarker and link its expression to immune regulation of the tumor microenvironment, providing a clear rationale for experimental and clinical validation. TRIM37 luminal A breast cancer hepatocellular carcinoma tumor immune microenvironment immune infiltration bioinformatic analysis prognostic biomarker Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1 Introduction Breast cancer remains the most frequently diagnosed malignancy and a leading cause of cancer-related morbidity and mortality among women worldwide. According to contemporary estimates, breast cancer accounts for 12% of all newly diagnosed cancers and 7% of cancer-related deaths, with incidence continuing to rise in many regions [ 1 ]. Although advancements in early detection and systemic therapy have substantially reduced breast cancer mortality, metastatic disease remains largely incurable, with a median overall survival of approximately 3 years [ 2 ]. These data highlight the ongoing need to identify molecular features that contribute to disease progression and adverse clinical outcomes. Increasing attention has focused on the tumor microenvironment as a determinant of prognosis and therapeutic response in breast cancer. Tumor-infiltrating lymphocytes and specific immune cell subsets have been associated with clinical outcomes across breast cancer subtypes, and immune contexture is increasingly recognized as a determinant of response to systemic therapies [ 3 , 4 ]. In parallel, the clinical success of immune checkpoint inhibitors in several solid tumors has intensified interest in immune-related biomarkers that may refine risk stratification and inform therapeutic decision making [ 5 , 6 ]. Despite these advances, the tumor-intrinsic molecular factors that associate with variation in immune-related features across breast cancer subtypes remain incompletely defined. Tripartite motif (TRIM) family proteins are E3 ubiquitin ligases that regulate diverse cellular processes relevant to tumor biology, including chromatin organization, centrosome homeostasis, and protein stability. Several TRIM family members have been implicated in immune-related signaling pathways, including antigen processing, and regulation of inflammatory responses [ 7 – 9 ]. TRIM37, also known as MUL, is located within the 17q23 chromosomal region, which is amplified in a substantial proportion of breast cancers [ 10 , 11 ]. TRIM37 encodes a RING–B-box–coiled-coil protein expressed across multiple tissues and has been implicated in chromatin regulation, centrosome function, and genomic stability [ 12 – 14 ]. TRIM37 is a histone H2A ubiquitin ligase and an oncogenic driver in breast cancer, where it promotes transcriptional repression of tumor suppressor genes and centrosome dysfunction [ 15 , 16 ]. Elevated TRIM37 expression has been associated with therapeutic resistance in breast cancer and hepatocellular carcinoma [ 17 – 19 ]. Although TRIM family proteins are recognized contributors to both tumor biology and immune-related pathways, the clinical importance of TRIM37 expression in relation to immune-associated features has not been systematically examined. Prior studies of TRIM37 have primarily focused on tumor cell–intrinsic mechanisms in selected cancer types [ 7 – 9 , 20 ], and it remains unclear whether TRIM37 expression correlates with immune infiltration patterns, immunomodulatory gene expression, or clinically relevant immune-associated phenotypes in human tumors. Moreover, although TRIM37 has been linked to adverse outcomes in breast cancer and hepatocellular carcinoma, it is uncertain whether these associations reflect broader patterns across cancers or are restricted to specific molecular and clinical contexts. To address these gaps, we conducted a systematic integrative analysis of TRIM37 expression across multiple human cancers using publicly available transcriptomic datasets. We examined the association between TRIM37 expression and clinical outcomes, with particular attention to breast cancer subtypes and hepatocellular carcinoma, where prior evidence suggests potential relevance. In parallel, we evaluated correlations between TRIM37 expression, immunomodulatory molecules, and estimated immune cell infiltration patterns. By integrating expression, survival, and immune-related analyses across independent datasets, we sought to clarify the clinical contexts in which TRIM37 expression is associated with prognosis and immune-related transcriptomic features, and to identify tumor types and subgroups for which TRIM37 warrants further mechanistic and translational investigation. 2 Materials and methods 2.1 Data sources and TRIM37 expression analysis TRIM37 gene expression across multiple human cancer types was analyzed using publicly available (online) transcriptomic databases. Differential expression of TRIM37 between tumor and non-tumor tissues was first assessed using the Oncomine database [ 21 ], with significance thresholds set at P = 0.001, a fold-change of 1.5, and gene ranking criteria as defined by the platform. TRIM37 expression patterns across various cancer types were further examined using TIMER2.0 [ 22 ], which integrates RNA sequencing data from The Cancer Genome Atlas (TCGA). In addition, GEPIA2 [ 23 ] was used to compare the expression of TRIM37 between TCGA tumor samples and non-tumor tissues derived from TCGA adjacent tissues, and non-diseased tissues from the Genotype-Tissue Expression (GTEx) project. Differential expression analyses in GEPIA2 were performed using one-way analysis of variance (ANOVA) with default parameters. Because non-tumor tissue data originated from different sources, comparisons relied on the standardized normalization procedures implemented within the platforms. 2.2 Survival and clinical outcome analysis The association between TRIM37 expression and clinical outcomes across various cancer types was evaluated using several independent platforms, including TISIDB [ 24 ], CVCDAP [ 25 ], Kaplan–Meier Plotter [ 26 ], and bc-GenExMiner version 4.6 [ 27 ]. Patients were stratified into high- and low-expression groups based on the median TRIM37 expression value in each dataset, according to the standard procedures implemented by the respective platforms. Survival outcomes, including overall survival and relapse-related endpoints where available, were assessed using log-rank tests as implemented within each database. No multivariable survival models were applied. 2.3 Analysis of immunomodulators Associations between TRIM37 expression and immunomodulatory molecules, including immunostimulators, immunoinhibitors, and major histocompatibility complex (MHC) molecules, were retrieved from TISIDB. To examine these associations further in breast cancer, correlations between TRIM37 expression and immunomodulator gene expression were assessed using tumor and non-tumor tissue datasets in GEPIA2. 2.4 Tumor immune cell infiltration analysis The relationship between TRIM37 expression and immune cell infiltration was evaluated using TIMER2.0 [ 14 ], which integrates TIMER, CIBERSORT, CIBERSORT-ABS, XCELL, QUANTISEQ, MCPcounter, and EPIC. These approaches estimate the relative abundance of immune cell populations in TCGA samples based on bulk RNA sequencing data. Spearman correlation analysis adjusted for tumor purity was used to assess associations between TRIM37 expression and levels of immune cell infiltration. Significance was defined as a two-sided p < 0.05. In addition, correlations between TRIM37 expression and tumor-infiltrating lymphocyte signatures were explored using TISIDB, in which immune cell abundance was inferred by gene set variation analysis based on gene expression profiles. 2.5 Functional annotation of TRIM37 Functional annotation of TRIM37 was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway, Gene Ontology, and Reactome databases with the KOBAS online analysis tool [ 28 ]. 2.6 Statistical analysis Gene expression analyses were conducted using Oncomine, TIMER2.0, and GEPIA2. Correlations between TRIM37 expression and immunomodulators, immune cell signatures, and tumor immune cell infiltration were assessed using Spearman rank correlation tests. Comparisons between immune subtypes were determined using Kruskal–Wallis tests. Survival analyses were evaluated using log-rank tests as implemented by the respective platforms. All additional analyses and data visualization were performed using Python (Python Software Foundation). The strength of Spearman correlation coefficients (ρ) was interpreted as follows: 0.00–0.19, very weak; 0.20–0.39, weak; 0.40–0.59, moderate; 0.60–0.79, strong; or 0.80–1.0, very strong [ 29 ]. A two-sided p < 0.05 was considered significant. 3 Results 3.1 TRIM37 mRNA expression across human cancers TRIM37 mRNA expression levels differed between tumor and non-tumor tissues across multiple cancer types. Increased TRIM37 expression was found in breast cancer, esophageal cancer, head and neck cancer, liver hepatocellular cancer, lung adenocarcinoma, lung squamous cell carcinoma, and gastric cancer (stomach adenocarcinoma) compared with non-tumor tissues (Fig. 1 a and 1 b). These cancer types were collectively designated as TRIM37-overexpressing cancers (TRIM37-OECs). Subtype-level analysis found that TRIM37 expression was significantly higher in luminal A breast cancer, luminal B breast cancer, and iCluster3 liver hepatocellular, compared with corresponding matched non-tumor tissues (Fig. 1 c). (a) Differential TRIM37 expression across multiple tumor types relative to non-tumor tissues. (b) TRIM37 expression in cancers from TCGA cohorts. * p < 0.05, ** p < 0.01, *** p < 0.001. (c) TRIM37 expression in breast cancer and liver hepatocellular subtypes. T, tumor; N, non-tumor, * p < 0.05. Cancer Genome Atlas nomenclature abbreviations: BRCA, breast cancer; ESCA, esophageal cancer; HNSC, head and neck cancer; LIHC, liver hepatocellular cancer; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; STAD, gastric cancer (stomach adenocarcinoma). 3.2 Prognostic associations of TRIM37 across cancers Across 30 cancer types, TRIM37 expression showed heterogeneous associations with overall survival. Higher TRIM37 expression was associated with shorter overall survival in adrenocortical cancer, kidney chromophobe carcinoma, kidney renal papillary cell carcinoma, liver hepatocellular carcinoma, and mesothelioma, whereas longer overall survival was found for colon adenocarcinoma, lower-grade glioma, and rectal adenocarcinoma (Fig. 2 a). (a) Pan-cancer associations between TRIM37 expression and overall survival. Longer, positive correlation; Shorter, negative correlation; NS, not significant. (b) Kaplan–Meier survival analysis for liver hepatocellular carcinoma. (c) Independent validation using the PanCancer Database. OS, overall survival; RFS, relapse-free survival; PFS, progression-free survival; DSS, disease-specific survival. Among TRIM37-OECs, a significant association between TRIM37 expression and overall survival was only found in liver hepatocellular cancer. For liver hepatocellular cancer, Kaplan–Meier Plotter analysis showed that higher TRIM37 expression was associated with shorter overall survival (HR 1.51, 95% CI 1.05–2.17, p = 0.023), relapse-free survival (RFS; HR 1.47, 95% CI 1.05–2.04, p = 0.023), progression-free survival (PFS; HR 1.40, 95% CI 1.04–1.88, p = 0.024), and disease-specific survival (DSS; HR 1.64, 95% CI 1.03–2.6, p = 0.036) (Fig. 2 b). Independent analysis using PanCancer Atlas data showed consistent associations between higher TRIM37 expression and shorter overall survival ( p < 0.001), progression-free interval (PFI; p < 0.001), DSS ( p < 0.001), and disease-free interval (DFI; p = 0.0093) in liver hepatocellular cancer (Fig. 2 c). Stratified analysis showed that higher TRIM37 expression was associated with shorter overall survival in stage 2 and AJCC-T2 liver hepatocellular cancer. Shorter RFS was found for grades 2 and 3 disease. Associations were also found for male patients, Asian patients, and patients who consumed alcohol (Supplementary Fig. 1). 3.3 TRIM37 expression and prognosis in luminal A breast cancer The prognostic relevance of TRIM37 expression varied across breast cancer subtypes. In luminal A breast cancer (ER + /HER2 − and low proliferation), higher TRIM37 expression was associated with shorter disease-free survival (DFS) in analyses based in TCGA RNA sequencing data (HR 2.65, 95% CI 1.09–6.43, p = 0.031; Fig. 3 a) and Affymetrix microarray datasets (HR 1.41, 95% CI 1.10–1.81, p = 0.008, Fig. 3 b). Consistent results were found when luminal A tumors were classified using Hu’s single-sample predictor (TCGA: HR 1.95, 95% CI 1.07–3.57, p = 0.030; Affymetrix: HR 1.41, 95% CI 1.05–1.91, p = 0.024; Fig. 3 c and 3 d). Associations between TRIM37 expression and survival outcomes in other breast cancer subtypes were not found consistently across datasets (Supplementary Fig. 2). In Kaplan–Meier Plotter analyses, higher TRIM37 expression was significantly associated with poorer overall survival (HR 1.53, 95% CI 1.07–2.19, p = 0.018; Fig. 3 e) and RFS (HR 1.36, 95% CI 1.14–1.63, p < 0.001; Fig. 3 f) in luminal A breast cancer only (Supplementary Fig. 3). 3.4 Functional annotation of TRIM37 Functional enrichment analysis identified several biological processes associated with TRIM37. The most enriched terms included aggresome assembly, negative regulation of centriole replication, histone H2A-K119 monoubiquitination, histone H2A monoubiquitination, and the ESC/E(Z) complex (Supplementary Fig. 4). Reactome pathway analysis further identified associations with antigen processing (ID: R-HAS-983168), class I MHC-mediated antigen processing and presentation (ID: R-HSA-983169), and pathways related to the adaptive immune system (ID: R-HSA-1280218). 3.5 Associations between TRIM37 and immune-related molecules In breast cancer, TRIM37 expression showed significant correlations with multiple immune-related molecules, including immunostimulators, immunoinhibitors, and MHC molecules (Fig. 4 a–c). Similar correlation patterns were found when these associations were evaluated in independent datasets (Fig. 4 d–f). Comparison between tumor and non-tumor tissues showed that a subset of immune-related molecules exhibited opposite correlation patterns with TRIM37 expression in breast cancer relative to non-tumor tissues. These included nine immunostimulators, seven immunoinhibitors, and two MHC molecules (Fig. 4 d–f). 3.6 TRIM37 expression and immune cell infiltration TRIM37 expression was associated with multiple immune cell populations in breast cancer. Positive correlations were found for several lymphoid and myeloid populations, whereas negative correlations were observed for selected T-cell subsets, natural killer cells, and endothelial cells (Fig. 5 a). Similar associations were found for other TRIM37-OECs (Supplementary Fig. 5). Analysis of immune-related gene signatures found concordant associations between TRIM37 expression and signatures of T-cell follicular helper cells, natural killer cells, Th1 cells, and natural killer T cells in breast cancer (Fig. 5 b; Supplementary Fig. 6). 3.7 TRIM37 expression and immune infiltration across breast cancer subtypes Subtype-specific analyses found associations between TRIM37 expression and immune cell infiltration across breast cancer subtypes (Supplementary Fig. 7). In luminal A breast cancer, TRIM37 expression showed positive correlations with Th2-associated immune populations, regulatory T cells, and M2 macrophages, and negative correlations with Th1-associated immune populations, including CD8 + T cells and natural killer cells (Fig. 6 ). In luminal A, HER2 + , and basal breast cancer subtypes, the correlation patterns between TRIM37 expression and Th1- or Th2-associated immune populations were more heterogeneous, with no consistent pattern found. 4 Discussion Here, we systematically analyzed TRIM37 expression, clinical associations, and immune-related correlations across multiple cancer types using publicly available transcriptomic datasets. TRIM37 was consistently overexpressed in several malignancies, including breast cancer, esophageal cancer, head and neck squamous cell carcinoma, liver hepatocellular carcinoma, lung adenocarcinoma, lung squamous cell carcinoma, and gastric cancer. These designations reflect higher cohort-level mRNA expression relative to non-tumor tissues and do not capture intratumoral or cell-type–specific heterogeneity. Among these TRIM37-overexpressing cancers, higher TRIM37 expression showed robust and reproducible associations with adverse clinical outcomes in liver hepatocellular carcinoma and in luminal A breast cancer. In parallel, TRIM37 expression correlated with multiple immune-related molecules and estimated immune cell populations, with subtype-specific immune association patterns most evident in luminal A breast cancer. TRIM37 is a tripartite motif family E3 ubiquitin ligase with established roles in chromatin regulation and centrosome biology that are relevant to tumorigenesis. TRIM37 has been identified as a histone H2A ubiquitin ligase and breast cancer oncoprotein [ 15 ]. Independent work has linked TRIM37 to centrosome dysfunction and mitotic errors, suggesting that its overexpression is associated with genomic instability [ 16 ]. The overexpression patterns observed in breast cancer are consistent with prior evidence implicating amplification of the 17q23 region and inclusion of TRIM37 within this locus [ 10 , 11 ]. However, the biological consequences of TRIM37 overexpression appear to be context-dependent, as TRIM37 expression is associated with divergent survival outcomes across different cancer types. Within TRIM37-overexpressing cancers, liver hepatocellular carcinoma showed the most reproducible adverse survival associations across independent datasets and endpoints. These associations align with broader evidence linking TRIM family members to immune infiltration patterns and checkpoint-related features in hepatocellular carcinoma cohorts [ 30 ]. TRIM37 overexpression promotes chemoresistance in hepatocellular carcinoma models, supporting the clinical relevance of elevated TRIM37 expression in this tumor type [ 19 ]. Nevertheless, observed hazard ratios varied across datasets, likely reflecting differences in cohort composition, expression measurement platforms, and clinical endpoint definitions. Breast cancer displayed subtype-specific patterns, with consistent adverse associations for TRIM37 expression in luminal A disease but not across other intrinsic subtypes. TRIM37-mediated oncogenic transcriptional repression and chromosomal instability have been demonstrated in models of breast cancer [ 15 , 16 ]. TRIM37 has also been implicated in therapeutic resistance in breast cancer [ 17 ], and in chemoresistance and metastatic behavior in triple-negative breast cancer [ 18 ]. More recently, germline and regulatory variation affecting TRIM37 expression has been associated with triple-negative breast cancer outcomes in Black women, reinforcing the clinical relevance of TRIM37-regulated pathways in at least a subset of breast cancers [ 31 ]. Consistent with the present findings, recent clinical evidence indicates that TRIM37 expression is prognostic in ER-positive/HER2-negative breast cancer but not in triple-negative disease, further supporting subtype-specific relevance [ 32 ]. A central contribution of the present study is the characterization of immune-related correlations associated with TRIM37 expression. TRIM proteins are recognized regulators of innate immune sensing and downstream signaling, and ubiquitin-mediated pathways play critical roles in immune activation thresholds, antigen processing, and cytokine signaling [ 7 , 20 – 22 ]. Consistent with this biology, TRIM37 expression correlated with multiple immunomodulators, including immunostimulators, immunoinhibitors, and MHC molecules, as well as with estimated immune cell populations. These associations reflect transcriptomic correlations and do not establish whether TRIM37 directly regulates immune recruitment, cytokine signaling, or antigen presentation. These associations should be interpreted cautiously, because they are derived from bulk tumor transcriptomes and computational deconvolution approaches [ 22 , 24 ]. The subtype-specific immune association patterns in luminal A breast cancer are of particular interest. Higher TRIM37 expression correlated with immune profiles consistent with increased Th2-associated CD4 + T cells, regulatory T cells, and M2 macrophages, while reduced associations were found with CD8 + T cells and natural killer cells. These patterns are consistent with established patterns of tumor immunoediting and immune polarization, in which chronic tumor-associated infiltration can be accompanied by immunosuppressive cellular programs [ 33 , 34 ]. Importantly, these immune correlations were not consistently observed across other breast cancer subtypes, underscoring the context-dependent nature of TRIM37-associated immune features. Clinically, tumor-infiltrating lymphocytes and specific lymphocyte subsets have been recognized as prognostic and predictive biomarkers in breast cancer [ 3 , 4 , 35 ]. From a translational viewpoint, the present findings support further evaluation of TRIM37 expression as a prognostic biomarker in luminal A breast cancer and liver hepatocellular carcinoma using clinically annotated cohorts with standardized endpoints and multivariable adjustment. Given the reliance on univariable survival analyses and computational immune inference, clinical utility cannot be inferred from the present data alone. Moreover, TRIM37 expression may serve as a stratification feature in studies of tumor–immune interactions; any implications for responsiveness to immune checkpoint blockade remain speculative and require direct clinical validation [ 5 , 6 ]. The evolving expectation that computational biomarker signals are strengthened by tissue-based validation and clinically meaningful subgroup analyses is supported by contemporary studies integrating bioinformatic discovery with experimental validation [ 36 , 37 ]. We acknowledge several limitations highlighted here. The analyses were based entirely on public datasets and cross-platform resources, including Oncomine, TCGA, and GTEx, introducing heterogeneity related to sequencing platforms, normalization pipelines, patient populations, cohort composition, sample processing, and batch effects that may persist despite platform-level correction. Survival analyses did not incorporate multivariable models adjusting for key clinical confounders, such as age, subtype, or treatment. Immune correlations were inferred using bulk transcriptome deconvolution methods and cannot substitute for direct quantification of immune cell localization, spatial distribution, or functional state within tumor tissue. Accordingly, it is not possible to determine whether TRIM37 actively drives immune remodeling, is regulated by the immune microenvironment, or reflects broader tumor progression. Therefore, the present results do not establish causality but identify consistent associations that warrant further investigation. Because TRIM37 immunoreactivity can be assessed in formalin-fixed, paraffin-embedded tissue, evaluation in institutional cohorts or tissue microarrays is a logical next step. Finally, mechanistic studies that perturb TRIM37 expression in subtype-specific models are required to determine whether TRIM37 contributes directly to tumor-intrinsic programs that influence antigen presentation, cytokine signaling, or immune evasion [ 5 , 7 , 20 ]. Declarations Author contributions All authors contributed to the conception and design of the study. Xiaozhong Teng and Pengyu Li performed data collection and analysis. Xiaozhong Teng wrote the first draft of the manuscript, and all the authors read and commented on earlier versions. Feng Wang , Kai Li and Zhicheng Zheng participated in the discussions, language editing, and manuscript review. All the authors have read and approved the final manuscript. Acknowledgements We thank Robin James Storer, PhD, from Liwen Bianji (Edanz) (www.liwenbianji.cn) for editing the English text of a draft of this manuscript. Funding This work was not funded by any funding. Data availability The datasets generated and analyzed for this study can be found in the Oncomine database (https://www. oncomine.org/resource/login.html), TIMER2.0 database (http://timer.cistrome.org/), GEPIA2 database (http://gepia2.cancer-pku.cn/), TISIDB database (http://cis.hku. hk/TISIDB/), CVCDAP database (https://omics.bjcancer.org/cvcdap/home.do), Kaplan-Meier Plotter Database (https://kmplot.com/analysis/), TIMER2.0 database (http://timer.cistrome.org/), Reactome databases(available online: http://kobas.cbi.pku.edu.cn/). Ethics approval and consent to participate Not applicable. Clinical trial number Not applicable. Competing interests The authors declare that this research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest. References Bray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, Jemal A. 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Breast Cancer Res Treat. 2012;131:765–75. https://doi.org/10.1007/s10549-011-1457-7 . Xie C, Mao X, Huang J, Ding Y, Wu J, Dong S, et al. KOBAS 2.0: a web server for annotation and identification of enriched pathways and diseases. Nucleic Acids Res. 2011;39:W316–22. https://doi.org/10.1093/nar/gkr483 . Web Server issue. Schober P, Boer C, Schwarte LA. Correlation coefficients: appropriate use and interpretation. Anesth Analg. 2018;126:1763–8. https://doi.org/10.1213/ANE.0000000000002864 . Cao J, Su B, Peng R, Tang H, Tu D, Tang Y, et al. Bioinformatics analysis of immune infiltrates and tripartite motif ( TRIM ) family genes in hepatocellular carcinoma. J Gastrointest Oncol. 2022;13:1942–58. https://doi.org/10.21037/jgo-22-619 . Tihagam RD, Lou S, Zhao Y, Liu KS-Y, Singh AT, Koo BI, et al. The TRIM37 variant rs57141087 contributes to triple-negative breast cancer outcomes in Black women. EMBO Rep. 2025;26:245–72. https://doi.org/10.1038/s44319-024-00331-2 . Tsuchida J, Wu R, Nagahashi M, Ebos JML, Ishikawa T, Shimoda M, et al. TRIM37 expression is associated with immune suppression poor response to neoadjuvant chemotherapy and worse survival in ER-positive/HER2-negative breast cancer. Ann Surg Oncol. 2025 Nov;21. https://doi.org/10.1245/s10434-025-18764-x . Smyth MJ, Dunn GP, Schreiber RD. Cancer immunosurveillance and immunoediting: the roles of immunity in suppressing tumor development and shaping tumor immunogenicity. Adv Immunol. 2006;90:1–50. https://doi.org/10.1016/S0065-2776(06)90001-7 . Emens LA. Breast cancer immunotherapy: facts and hopes. Clin Cancer Res. 2018;24:511–20. https://doi.org/10.1158/1078-0432.CCR-16-3001 . Nelson MA, Ngamcherdtrakul W, Luoh S-W, Yantasee W. Prognostic and therapeutic role of tumor-infiltrating lymphocyte subtypes in breast cancer. Cancer Metastasis Rev. 2021;40:519–36. https://doi.org/10.1007/s10555-021-09968-0 . Xing W, Deng M, Wang W, Liu Y, Mi X, Li H, Ge X. Bioinformatics analysis and experimental validation of ASF1B in breast tumors. Cancer Med. 2025;14:e71073. https://doi.org/10.1002/cam4.71073 . Hasannejad F, Darzi M, Yasaei M, Unveiling. GBE1 as a hypoxia-related prognostic gene with significant impact on immune cell infiltration in HER2-enriched breast cancer. Discov Oncol. 2025;16:975. https://doi.org/10.1007/s12672-025-02826-3 Additional Declarations No competing interests reported. Supplementary Files SupplementaryFigure1.jpg SupplementaryFigure4.jpg SupplementaryFigure3.jpg SupplementaryFigure6.jpg SupplementaryFigure2.jpg SupplementaryFigure7.jpg SupplementaryFigure5.jpg Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 11 May, 2026 Reviewers agreed at journal 28 Apr, 2026 Reviewers agreed at journal 28 Apr, 2026 Reviewers invited by journal 21 Apr, 2026 Editor assigned by journal 03 Apr, 2026 Submission checks completed at journal 03 Apr, 2026 First submitted to journal 02 Apr, 2026 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9298547","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":631189599,"identity":"d9589b33-c02b-4198-9543-3353fa82370d","order_by":0,"name":"Xiaozhong Teng","email":"","orcid":"","institution":"Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xiaozhong","middleName":"","lastName":"Teng","suffix":""},{"id":631189600,"identity":"615610f0-63b2-4d55-8c55-5917687c23b6","order_by":1,"name":"Pengyu Li","email":"","orcid":"","institution":"Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Pengyu","middleName":"","lastName":"Li","suffix":""},{"id":631189601,"identity":"f505bfdb-de38-4332-8408-d16bd144c85d","order_by":2,"name":"Zhicheng Zheng","email":"","orcid":"","institution":"Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zhicheng","middleName":"","lastName":"Zheng","suffix":""},{"id":631189605,"identity":"ad32f2a4-1caf-4148-ad47-54987f5ac626","order_by":3,"name":"Kai Li","email":"","orcid":"","institution":"Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Kai","middleName":"","lastName":"Li","suffix":""},{"id":631189613,"identity":"fb227b55-1e5f-4676-80d0-024c3da2eb39","order_by":4,"name":"Feng Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA10lEQVRIie3QPQ6CMBTA8UeaPJdG1poQvEINCecpCxMmjh1IlGBg8OsGegVHRwxJp7o7liO4OYqzBnBz6H96Q3/pawFstj8M3byqBE+XxSjLjJBpPxkzFRkjlbOndc2NVv3EhySYGU2cI4vjSbMmAxYDFbOoQIKQhDJaIbjlRnQTkquWeIigw3t08YDp23nQLRSdbUs0AmfzPpKELSEMCQ0X7TCIBFxowhExhmHk/clCKoGU1ExoRXvfMj3k1fXJUzE9NdnjKVPfLXfd5CP623GbzWazfe0Fv5tJJuGpv1kAAAAASUVORK5CYII=","orcid":"","institution":"Capital Medical University","correspondingAuthor":true,"prefix":"","firstName":"Feng","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2026-04-02 05:53:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9298547/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9298547/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108183335,"identity":"d148b65d-3ca5-46a9-a73a-9ccf2c63e2e8","added_by":"auto","created_at":"2026-04-30 09:00:48","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":6928229,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTRIM37 expression levels across human cancers and tumor subtypes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(a) Differential TRIM37 expression across multiple tumor types relative to non-tumor tissues. (b) TRIM37 expression in cancers from TCGA cohorts. *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001. (c) TRIM37 expression in breast cancer and liver hepatocellular subtypes. T, tumor; N, non-tumor, *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05. Cancer Genome Atlas nomenclature abbreviations: BRCA, breast cancer; ESCA, esophageal cancer; HNSC, head and neck cancer; LIHC, liver hepatocellular cancer; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; STAD, gastric cancer (stomach adenocarcinoma).\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9298547/v1/e47c9a178a492535b6c6a721.jpg"},{"id":108183315,"identity":"5d17437f-074a-4433-8ca7-4bc2fced9ccc","added_by":"auto","created_at":"2026-04-30 09:00:40","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":5056278,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAssociation between TRIM37 expression and overall survival across human cancers\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(a) Pan-cancer associations between TRIM37 expression and overall survival. Longer, positive correlation; Shorter, negative correlation; NS, not significant. (b) Kaplan–Meier survival analysis for liver hepatocellular carcinoma. (c) Independent validation using the PanCancer Database. OS, overall survival; RFS, relapse-free survival; PFS, progression-free survival; DSS, disease-specific survival.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9298547/v1/0772371a53ddca303779a906.jpg"},{"id":108491389,"identity":"e24b615c-1539-4302-8caf-be7247d81d9e","added_by":"auto","created_at":"2026-05-05 09:53:41","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":4766158,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePrognostic value of TRIM37 expression in luminal A breast cancer\u003c/strong\u003e (a–d) Kaplan–Meier survival analyses comparing high and low TRIM37 expression groups. DFS was analyzed using the bc-GenExMiner database with TCGA data and Affymetrix JetSet probe data. (e) OS and (f) RFS were examined using the Kaplan–Meier Plotter database. OS, overall survival; RFS, relapse-free survival; PFS, progression-free survival; DSS, disease-specific survival.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9298547/v1/c0754e639496bf96515c99d0.jpg"},{"id":108491041,"identity":"a97962b1-de5e-452a-9796-a09b878d9825","added_by":"auto","created_at":"2026-05-05 09:51:30","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":4957161,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAssociations between TRIM37 expression and immuno-related molecules\u003c/strong\u003e Spearman correlations of TRIM37 expression with (a) immunostimulators, (b) immunoinhibitors, and (c) MHC molecules. Spearman correlations of TRIM37 expression with (d) immunostimulators, (e) immunoinhibitors, and (f) MHC molecules in breast cancer, tumor, TCGA tumor data; normal, TCGA normal data and GTEx data. Positive correlation: ρ \u0026gt; 0, negative correlation: ρ \u0026lt; 0.\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9298547/v1/7e8b071d65710a072ae8bf00.jpg"},{"id":108183332,"identity":"76b7c391-c77e-44ef-8296-69cb858e24d9","added_by":"auto","created_at":"2026-04-30 09:00:44","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":5518878,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAssociations between TRIM37 expression and immune cell infiltration in breast cancer\u003c/strong\u003e (a)Spearman correlations between TRIM37 expression and estimated immune cell populations using multiple deconvolution approaches. Only significant correlations (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05) are shown. Threshold: absolute ρ \u0026gt; 0.19. (b) Spearman correlations between TRIM37 expression and immune-cell gene signatures.\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9298547/v1/d0222e1d04096b72aa5ee92f.jpg"},{"id":108183763,"identity":"a78cf852-4938-4a67-8f89-e4a97243f1a2","added_by":"auto","created_at":"2026-04-30 09:02:42","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":3173323,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSubtype-specific association between TRIM37 expression and Th1/Th2-related immune populations in breast cancer\u003c/strong\u003e Correlations between TRIM37 expression and Th1- and Th2-associated immune cell populations across intrinsic breast cancer subtypes. Only significant (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05) correlations confirmed by at least two methods are shown. Threshold: absolute ρ \u0026gt; 0.19.\u003c/p\u003e","description":"","filename":"Figure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9298547/v1/e64e52e91e59b958876722b9.jpg"},{"id":108979089,"identity":"18fd7f63-7afb-4596-b2ee-14964a8a906c","added_by":"auto","created_at":"2026-05-11 11:55:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":30667161,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9298547/v1/a46bd3e2-e777-4188-b8bb-23582ba1ccb7.pdf"},{"id":108183491,"identity":"808b2285-c6ec-43d0-adb1-a32dae2f1b6b","added_by":"auto","created_at":"2026-04-30 09:01:40","extension":"jpg","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":3971824,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9298547/v1/d4358f48a2288075a0c50240.jpg"},{"id":108183806,"identity":"340ee26f-4012-4546-b0dc-f4b09643a327","added_by":"auto","created_at":"2026-04-30 09:02:51","extension":"jpg","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2321013,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9298547/v1/f8e4351840acda189aff4df9.jpg"},{"id":108183329,"identity":"8f5472fb-4280-4b43-96f6-91c14c599b53","added_by":"auto","created_at":"2026-04-30 09:00:43","extension":"jpg","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":3858215,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9298547/v1/98029c608e8ba3f6e4df7425.jpg"},{"id":108183342,"identity":"ab3a57a6-bd33-43ee-bb5e-9f015cc8ecac","added_by":"auto","created_at":"2026-04-30 09:00:49","extension":"jpg","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":3297523,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9298547/v1/c5bac0f4e6bcf96baf222a61.jpg"},{"id":108183505,"identity":"27c5451a-4680-46ff-ba48-2df5b6bd064d","added_by":"auto","created_at":"2026-04-30 09:01:50","extension":"jpg","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":5266234,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9298547/v1/0a9b4917ede3b98b617148ee.jpg"},{"id":108976465,"identity":"063733b4-07c0-4b3c-8cc7-70d12707f4b6","added_by":"auto","created_at":"2026-05-11 11:22:53","extension":"jpg","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":5410316,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9298547/v1/2051d8126066071aaa00f47c.jpg"},{"id":108183339,"identity":"df04a8d1-e0f9-46e5-9496-1f0c15293e62","added_by":"auto","created_at":"2026-04-30 09:00:48","extension":"jpg","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":7798999,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9298547/v1/13c66e6e9595911709b3a34d.jpg"}],"financialInterests":"No competing interests reported.","formattedTitle":"TRIM37 expression is associated with prognosis and immune-related features in luminal A breast cancer and hepatocellular carcinoma","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eBreast cancer remains the most frequently diagnosed malignancy and a leading cause of cancer-related morbidity and mortality among women worldwide. According to contemporary estimates, breast cancer accounts for 12% of all newly diagnosed cancers and 7% of cancer-related deaths, with incidence continuing to rise in many regions [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Although advancements in early detection and systemic therapy have substantially reduced breast cancer mortality, metastatic disease remains largely incurable, with a median overall survival of approximately 3 years [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. These data highlight the ongoing need to identify molecular features that contribute to disease progression and adverse clinical outcomes.\u003c/p\u003e \u003cp\u003eIncreasing attention has focused on the tumor microenvironment as a determinant of prognosis and therapeutic response in breast cancer. Tumor-infiltrating lymphocytes and specific immune cell subsets have been associated with clinical outcomes across breast cancer subtypes, and immune contexture is increasingly recognized as a determinant of response to systemic therapies [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In parallel, the clinical success of immune checkpoint inhibitors in several solid tumors has intensified interest in immune-related biomarkers that may refine risk stratification and inform therapeutic decision making [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Despite these advances, the tumor-intrinsic molecular factors that associate with variation in immune-related features across breast cancer subtypes remain incompletely defined.\u003c/p\u003e \u003cp\u003eTripartite motif (TRIM) family proteins are E3 ubiquitin ligases that regulate diverse cellular processes relevant to tumor biology, including chromatin organization, centrosome homeostasis, and protein stability. Several TRIM family members have been implicated in immune-related signaling pathways, including antigen processing, and regulation of inflammatory responses [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. TRIM37, also known as MUL, is located within the 17q23 chromosomal region, which is amplified in a substantial proportion of breast cancers [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. TRIM37 encodes a RING\u0026ndash;B-box\u0026ndash;coiled-coil protein expressed across multiple tissues and has been implicated in chromatin regulation, centrosome function, and genomic stability [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. TRIM37 is a histone H2A ubiquitin ligase and an oncogenic driver in breast cancer, where it promotes transcriptional repression of tumor suppressor genes and centrosome dysfunction [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Elevated TRIM37 expression has been associated with therapeutic resistance in breast cancer and hepatocellular carcinoma [\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough TRIM family proteins are recognized contributors to both tumor biology and immune-related pathways, the clinical importance of TRIM37 expression in relation to immune-associated features has not been systematically examined. Prior studies of TRIM37 have primarily focused on tumor cell\u0026ndash;intrinsic mechanisms in selected cancer types [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], and it remains unclear whether TRIM37 expression correlates with immune infiltration patterns, immunomodulatory gene expression, or clinically relevant immune-associated phenotypes in human tumors. Moreover, although TRIM37 has been linked to adverse outcomes in breast cancer and hepatocellular carcinoma, it is uncertain whether these associations reflect broader patterns across cancers or are restricted to specific molecular and clinical contexts.\u003c/p\u003e \u003cp\u003eTo address these gaps, we conducted a systematic integrative analysis of TRIM37 expression across multiple human cancers using publicly available transcriptomic datasets. We examined the association between TRIM37 expression and clinical outcomes, with particular attention to breast cancer subtypes and hepatocellular carcinoma, where prior evidence suggests potential relevance. In parallel, we evaluated correlations between TRIM37 expression, immunomodulatory molecules, and estimated immune cell infiltration patterns. By integrating expression, survival, and immune-related analyses across independent datasets, we sought to clarify the clinical contexts in which TRIM37 expression is associated with prognosis and immune-related transcriptomic features, and to identify tumor types and subgroups for which TRIM37 warrants further mechanistic and translational investigation.\u003c/p\u003e"},{"header":"2 Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Data sources and TRIM37 expression analysis\u003c/h2\u003e \u003cp\u003eTRIM37 gene expression across multiple human cancer types was analyzed using publicly available (online) transcriptomic databases. Differential expression of TRIM37 between tumor and non-tumor tissues was first assessed using the Oncomine database [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], with significance thresholds set at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001, a fold-change of 1.5, and gene ranking criteria as defined by the platform. TRIM37 expression patterns across various cancer types were further examined using TIMER2.0 [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], which integrates RNA sequencing data from The Cancer Genome Atlas (TCGA). In addition, GEPIA2 [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] was used to compare the expression of TRIM37 between TCGA tumor samples and non-tumor tissues derived from TCGA adjacent tissues, and non-diseased tissues from the Genotype-Tissue Expression (GTEx) project. Differential expression analyses in GEPIA2 were performed using one-way analysis of variance (ANOVA) with default parameters. Because non-tumor tissue data originated from different sources, comparisons relied on the standardized normalization procedures implemented within the platforms.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Survival and clinical outcome analysis\u003c/h2\u003e \u003cp\u003eThe association between TRIM37 expression and clinical outcomes across various cancer types was evaluated using several independent platforms, including TISIDB [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], CVCDAP [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], Kaplan\u0026ndash;Meier Plotter [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], and bc-GenExMiner version 4.6 [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Patients were stratified into high- and low-expression groups based on the median TRIM37 expression value in each dataset, according to the standard procedures implemented by the respective platforms. Survival outcomes, including overall survival and relapse-related endpoints where available, were assessed using log-rank tests as implemented within each database. No multivariable survival models were applied.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Analysis of immunomodulators\u003c/h2\u003e \u003cp\u003eAssociations between TRIM37 expression and immunomodulatory molecules, including immunostimulators, immunoinhibitors, and major histocompatibility complex (MHC) molecules, were retrieved from TISIDB. To examine these associations further in breast cancer, correlations between TRIM37 expression and immunomodulator gene expression were assessed using tumor and non-tumor tissue datasets in GEPIA2.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Tumor immune cell infiltration analysis\u003c/h2\u003e \u003cp\u003eThe relationship between TRIM37 expression and immune cell infiltration was evaluated using TIMER2.0 [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], which integrates TIMER, CIBERSORT, CIBERSORT-ABS, XCELL, QUANTISEQ, MCPcounter, and EPIC. These approaches estimate the relative abundance of immune cell populations in TCGA samples based on bulk RNA sequencing data. Spearman correlation analysis adjusted for tumor purity was used to assess associations between TRIM37 expression and levels of immune cell infiltration. Significance was defined as a two-sided \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. In addition, correlations between TRIM37 expression and tumor-infiltrating lymphocyte signatures were explored using TISIDB, in which immune cell abundance was inferred by gene set variation analysis based on gene expression profiles.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Functional annotation of TRIM37\u003c/h2\u003e \u003cp\u003eFunctional annotation of TRIM37 was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway, Gene Ontology, and Reactome databases with the KOBAS online analysis tool [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Statistical analysis\u003c/h2\u003e \u003cp\u003eGene expression analyses were conducted using Oncomine, TIMER2.0, and GEPIA2. Correlations between TRIM37 expression and immunomodulators, immune cell signatures, and tumor immune cell infiltration were assessed using Spearman rank correlation tests. Comparisons between immune subtypes were determined using Kruskal\u0026ndash;Wallis tests. Survival analyses were evaluated using log-rank tests as implemented by the respective platforms. All additional analyses and data visualization were performed using Python (Python Software Foundation). The strength of Spearman correlation coefficients (ρ) was interpreted as follows: 0.00\u0026ndash;0.19, very weak; 0.20\u0026ndash;0.39, weak; 0.40\u0026ndash;0.59, moderate; 0.60\u0026ndash;0.79, strong; or 0.80\u0026ndash;1.0, very strong [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. A two-sided \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1 TRIM37 mRNA expression across human cancers\u003c/h2\u003e \u003cp\u003eTRIM37 mRNA expression levels differed between tumor and non-tumor tissues across multiple cancer types. Increased TRIM37 expression was found in breast cancer, esophageal cancer, head and neck cancer, liver hepatocellular cancer, lung adenocarcinoma, lung squamous cell carcinoma, and gastric cancer (stomach adenocarcinoma) compared with non-tumor tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). These cancer types were collectively designated as TRIM37-overexpressing cancers (TRIM37-OECs).\u003c/p\u003e \u003cp\u003eSubtype-level analysis found that TRIM37 expression was significantly higher in luminal A breast cancer, luminal B breast cancer, and iCluster3 liver hepatocellular, compared with corresponding matched non-tumor tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e(a) Differential TRIM37 expression across multiple tumor types relative to non-tumor tissues. (b) TRIM37 expression in cancers from TCGA cohorts. *\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, **\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ***\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001. (c) TRIM37 expression in breast cancer and liver hepatocellular subtypes. T, tumor; N, non-tumor, *\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Cancer Genome Atlas nomenclature abbreviations: BRCA, breast cancer; ESCA, esophageal cancer; HNSC, head and neck cancer; LIHC, liver hepatocellular cancer; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; STAD, gastric cancer (stomach adenocarcinoma).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Prognostic associations of TRIM37 across cancers\u003c/h2\u003e \u003cp\u003eAcross 30 cancer types, TRIM37 expression showed heterogeneous associations with overall survival. Higher TRIM37 expression was associated with shorter overall survival in adrenocortical cancer, kidney chromophobe carcinoma, kidney renal papillary cell carcinoma, liver hepatocellular carcinoma, and mesothelioma, whereas longer overall survival was found for colon adenocarcinoma, lower-grade glioma, and rectal adenocarcinoma (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e(a) Pan-cancer associations between TRIM37 expression and overall survival. Longer, positive correlation; Shorter, negative correlation; NS, not significant. (b) Kaplan\u0026ndash;Meier survival analysis for liver hepatocellular carcinoma. (c) Independent validation using the PanCancer Database. OS, overall survival; RFS, relapse-free survival; PFS, progression-free survival; DSS, disease-specific survival.\u003c/p\u003e \u003cp\u003eAmong TRIM37-OECs, a significant association between TRIM37 expression and overall survival was only found in liver hepatocellular cancer. For liver hepatocellular cancer, Kaplan\u0026ndash;Meier Plotter analysis showed that higher TRIM37 expression was associated with shorter overall survival (HR 1.51, 95% CI 1.05\u0026ndash;2.17, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.023), relapse-free survival (RFS; HR 1.47, 95% CI 1.05\u0026ndash;2.04, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.023), progression-free survival (PFS; HR 1.40, 95% CI 1.04\u0026ndash;1.88, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.024), and disease-specific survival (DSS; HR 1.64, 95% CI 1.03\u0026ndash;2.6, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.036) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003eIndependent analysis using PanCancer Atlas data showed consistent associations between higher TRIM37 expression and shorter overall survival (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), progression-free interval (PFI; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), DSS (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and disease-free interval (DFI; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0093) in liver hepatocellular cancer (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec).\u003c/p\u003e \u003cp\u003eStratified analysis showed that higher TRIM37 expression was associated with shorter overall survival in stage 2 and AJCC-T2 liver hepatocellular cancer. Shorter RFS was found for grades 2 and 3 disease. Associations were also found for male patients, Asian patients, and patients who consumed alcohol (Supplementary Fig.\u0026nbsp;1).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3 TRIM37 expression and prognosis in luminal A breast cancer\u003c/h2\u003e \u003cp\u003eThe prognostic relevance of TRIM37 expression varied across breast cancer subtypes. In luminal A breast cancer (ER\u003csup\u003e+\u003c/sup\u003e/HER2\u003csup\u003e\u0026minus;\u003c/sup\u003e and low proliferation), higher TRIM37 expression was associated with shorter disease-free survival (DFS) in analyses based in TCGA RNA sequencing data (HR 2.65, 95% CI 1.09\u0026ndash;6.43, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.031; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea) and Affymetrix microarray datasets (HR 1.41, 95% CI 1.10\u0026ndash;1.81, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). Consistent results were found when luminal A tumors were classified using Hu\u0026rsquo;s single-sample predictor (TCGA: HR 1.95, 95% CI 1.07\u0026ndash;3.57, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.030; Affymetrix: HR 1.41, 95% CI 1.05\u0026ndash;1.91, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.024; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed).\u003c/p\u003e \u003cp\u003eAssociations between TRIM37 expression and survival outcomes in other breast cancer subtypes were not found consistently across datasets (Supplementary Fig.\u0026nbsp;2). In Kaplan\u0026ndash;Meier Plotter analyses, higher TRIM37 expression was significantly associated with poorer overall survival (HR 1.53, 95% CI 1.07\u0026ndash;2.19, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.018; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee) and RFS (HR 1.36, 95% CI 1.14\u0026ndash;1.63, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ef) in luminal A breast cancer only (Supplementary Fig.\u0026nbsp;3).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Functional annotation of TRIM37\u003c/h2\u003e \u003cp\u003eFunctional enrichment analysis identified several biological processes associated with TRIM37. The most enriched terms included aggresome assembly, negative regulation of centriole replication, histone H2A-K119 monoubiquitination, histone H2A monoubiquitination, and the ESC/E(Z) complex (Supplementary Fig.\u0026nbsp;4). Reactome pathway analysis further identified associations with antigen processing (ID: R-HAS-983168), class I MHC-mediated antigen processing and presentation (ID: R-HSA-983169), and pathways related to the adaptive immune system (ID: R-HSA-1280218).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Associations between TRIM37 and immune-related molecules\u003c/h2\u003e \u003cp\u003eIn breast cancer, TRIM37 expression showed significant correlations with multiple immune-related molecules, including immunostimulators, immunoinhibitors, and MHC molecules (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea\u0026ndash;c). Similar correlation patterns were found when these associations were evaluated in independent datasets (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed\u0026ndash;f).\u003c/p\u003e \u003cp\u003eComparison between tumor and non-tumor tissues showed that a subset of immune-related molecules exhibited opposite correlation patterns with TRIM37 expression in breast cancer relative to non-tumor tissues. These included nine immunostimulators, seven immunoinhibitors, and two MHC molecules (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed\u0026ndash;f).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.6 TRIM37 expression and immune cell infiltration\u003c/h2\u003e \u003cp\u003eTRIM37 expression was associated with multiple immune cell populations in breast cancer. Positive correlations were found for several lymphoid and myeloid populations, whereas negative correlations were observed for selected T-cell subsets, natural killer cells, and endothelial cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). Similar associations were found for other TRIM37-OECs (Supplementary Fig.\u0026nbsp;5).\u003c/p\u003e \u003cp\u003eAnalysis of immune-related gene signatures found concordant associations between TRIM37 expression and signatures of T-cell follicular helper cells, natural killer cells, Th1 cells, and natural killer T cells in breast cancer (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb; Supplementary Fig.\u0026nbsp;6).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.7 TRIM37 expression and immune infiltration across breast cancer subtypes\u003c/h2\u003e \u003cp\u003eSubtype-specific analyses found associations between TRIM37 expression and immune cell infiltration across breast cancer subtypes (Supplementary Fig.\u0026nbsp;7). In luminal A breast cancer, TRIM37 expression showed positive correlations with Th2-associated immune populations, regulatory T cells, and M2 macrophages, and negative correlations with Th1-associated immune populations, including CD8\u003csup\u003e+\u003c/sup\u003e T cells and natural killer cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn luminal A, HER2\u003csup\u003e+\u003c/sup\u003e, and basal breast cancer subtypes, the correlation patterns between TRIM37 expression and Th1- or Th2-associated immune populations were more heterogeneous, with no consistent pattern found.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eHere, we systematically analyzed TRIM37 expression, clinical associations, and immune-related correlations across multiple cancer types using publicly available transcriptomic datasets. TRIM37 was consistently overexpressed in several malignancies, including breast cancer, esophageal cancer, head and neck squamous cell carcinoma, liver hepatocellular carcinoma, lung adenocarcinoma, lung squamous cell carcinoma, and gastric cancer. These designations reflect higher cohort-level mRNA expression relative to non-tumor tissues and do not capture intratumoral or cell-type\u0026ndash;specific heterogeneity. Among these TRIM37-overexpressing cancers, higher TRIM37 expression showed robust and reproducible associations with adverse clinical outcomes in liver hepatocellular carcinoma and in luminal A breast cancer. In parallel, TRIM37 expression correlated with multiple immune-related molecules and estimated immune cell populations, with subtype-specific immune association patterns most evident in luminal A breast cancer.\u003c/p\u003e \u003cp\u003eTRIM37 is a tripartite motif family E3 ubiquitin ligase with established roles in chromatin regulation and centrosome biology that are relevant to tumorigenesis. TRIM37 has been identified as a histone H2A ubiquitin ligase and breast cancer oncoprotein [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Independent work has linked TRIM37 to centrosome dysfunction and mitotic errors, suggesting that its overexpression is associated with genomic instability [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The overexpression patterns observed in breast cancer are consistent with prior evidence implicating amplification of the 17q23 region and inclusion of TRIM37 within this locus [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. However, the biological consequences of TRIM37 overexpression appear to be context-dependent, as TRIM37 expression is associated with divergent survival outcomes across different cancer types.\u003c/p\u003e \u003cp\u003eWithin TRIM37-overexpressing cancers, liver hepatocellular carcinoma showed the most reproducible adverse survival associations across independent datasets and endpoints. These associations align with broader evidence linking TRIM family members to immune infiltration patterns and checkpoint-related features in hepatocellular carcinoma cohorts [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. TRIM37 overexpression promotes chemoresistance in hepatocellular carcinoma models, supporting the clinical relevance of elevated TRIM37 expression in this tumor type [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Nevertheless, observed hazard ratios varied across datasets, likely reflecting differences in cohort composition, expression measurement platforms, and clinical endpoint definitions.\u003c/p\u003e \u003cp\u003eBreast cancer displayed subtype-specific patterns, with consistent adverse associations for TRIM37 expression in luminal A disease but not across other intrinsic subtypes. TRIM37-mediated oncogenic transcriptional repression and chromosomal instability have been demonstrated in models of breast cancer [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. TRIM37 has also been implicated in therapeutic resistance in breast cancer [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], and in chemoresistance and metastatic behavior in triple-negative breast cancer [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. More recently, germline and regulatory variation affecting TRIM37 expression has been associated with triple-negative breast cancer outcomes in Black women, reinforcing the clinical relevance of TRIM37-regulated pathways in at least a subset of breast cancers [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Consistent with the present findings, recent clinical evidence indicates that TRIM37 expression is prognostic in ER-positive/HER2-negative breast cancer but not in triple-negative disease, further supporting subtype-specific relevance [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA central contribution of the present study is the characterization of immune-related correlations associated with TRIM37 expression. TRIM proteins are recognized regulators of innate immune sensing and downstream signaling, and ubiquitin-mediated pathways play critical roles in immune activation thresholds, antigen processing, and cytokine signaling [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Consistent with this biology, TRIM37 expression correlated with multiple immunomodulators, including immunostimulators, immunoinhibitors, and MHC molecules, as well as with estimated immune cell populations. These associations reflect transcriptomic correlations and do not establish whether TRIM37 directly regulates immune recruitment, cytokine signaling, or antigen presentation. These associations should be interpreted cautiously, because they are derived from bulk tumor transcriptomes and computational deconvolution approaches [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe subtype-specific immune association patterns in luminal A breast cancer are of particular interest. Higher TRIM37 expression correlated with immune profiles consistent with increased Th2-associated CD4\u003csup\u003e+\u003c/sup\u003e T cells, regulatory T cells, and M2 macrophages, while reduced associations were found with CD8\u003csup\u003e+\u003c/sup\u003e T cells and natural killer cells. These patterns are consistent with established patterns of tumor immunoediting and immune polarization, in which chronic tumor-associated infiltration can be accompanied by immunosuppressive cellular programs [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Importantly, these immune correlations were not consistently observed across other breast cancer subtypes, underscoring the context-dependent nature of TRIM37-associated immune features. Clinically, tumor-infiltrating lymphocytes and specific lymphocyte subsets have been recognized as prognostic and predictive biomarkers in breast cancer [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFrom a translational viewpoint, the present findings support further evaluation of TRIM37 expression as a prognostic biomarker in luminal A breast cancer and liver hepatocellular carcinoma using clinically annotated cohorts with standardized endpoints and multivariable adjustment. Given the reliance on univariable survival analyses and computational immune inference, clinical utility cannot be inferred from the present data alone. Moreover, TRIM37 expression may serve as a stratification feature in studies of tumor\u0026ndash;immune interactions; any implications for responsiveness to immune checkpoint blockade remain speculative and require direct clinical validation [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The evolving expectation that computational biomarker signals are strengthened by tissue-based validation and clinically meaningful subgroup analyses is supported by contemporary studies integrating bioinformatic discovery with experimental validation [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe acknowledge several limitations highlighted here. The analyses were based entirely on public datasets and cross-platform resources, including Oncomine, TCGA, and GTEx, introducing heterogeneity related to sequencing platforms, normalization pipelines, patient populations, cohort composition, sample processing, and batch effects that may persist despite platform-level correction. Survival analyses did not incorporate multivariable models adjusting for key clinical confounders, such as age, subtype, or treatment. Immune correlations were inferred using bulk transcriptome deconvolution methods and cannot substitute for direct quantification of immune cell localization, spatial distribution, or functional state within tumor tissue. Accordingly, it is not possible to determine whether TRIM37 actively drives immune remodeling, is regulated by the immune microenvironment, or reflects broader tumor progression. Therefore, the present results do not establish causality but identify consistent associations that warrant further investigation. Because TRIM37 immunoreactivity can be assessed in formalin-fixed, paraffin-embedded tissue, evaluation in institutional cohorts or tissue microarrays is a logical next step. Finally, mechanistic studies that perturb TRIM37 expression in subtype-specific models are required to determine whether TRIM37 contributes directly to tumor-intrinsic programs that influence antigen presentation, cytokine signaling, or immune evasion [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the conception and design of the study. Xiaozhong Teng and Pengyu Li performed data collection and analysis. Xiaozhong Teng wrote the first draft of the manuscript, and all the authors read and commented on earlier versions. Feng Wang , Kai Li and Zhicheng Zheng participated in the discussions, language editing, and manuscript review. All the authors have read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Robin James Storer, PhD, from Liwen Bianji (Edanz) (www.liwenbianji.cn) for editing the English text of a draft of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was not funded by any funding. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed for this study can be found in the Oncomine database (https://www. oncomine.org/resource/login.html), TIMER2.0 database (http://timer.cistrome.org/), GEPIA2 database (http://gepia2.cancer-pku.cn/), TISIDB database (http://cis.hku. hk/TISIDB/), CVCDAP database (https://omics.bjcancer.org/cvcdap/home.do), Kaplan-Meier Plotter Database (https://kmplot.com/analysis/), TIMER2.0 database (http://timer.cistrome.org/), Reactome databases(available online: http://kobas.cbi.pku.edu.cn/).\u003c/p\u003e\n\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\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that this research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, Jemal A. 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Discov Oncol. 2025;16:975. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s12672-025-02826-3\u003c/span\u003e\u003cspan address=\"10.1007/s12672-025-02826-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dion","sideBox":"Learn more about [Discover Oncology](https://www.springer.com/12672)","snPcode":"","submissionUrl":"","title":"Discover Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"TRIM37, luminal A breast cancer, hepatocellular carcinoma, tumor immune microenvironment, immune infiltration, bioinformatic analysis, prognostic biomarker","lastPublishedDoi":"10.21203/rs.3.rs-9298547/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9298547/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTripartite motif-containing protein 37 (TRIM37), an innate immunity\u0026ndash;related E3 ubiquitin ligase, is increasingly implicated in tumor biology; however, its prognostic relevance and relationship to the tumor immune microenvironment across human cancers remain poorly defined. In the present study, we examined TRIM37 expression, clinical outcomes, prognostic importance, and immune associations of TRIM37 across multiple human cancers using publicly available cancer genomics and immunology databases. Analyses incorporated data from Oncomine, TIMER2.0, GEPIA2, TISIDB, CVCDAP, Kaplan\u0026ndash;Meier plotter, and bc-GenExMiner to assess expression patterns, survival outcomes, and immune correlations. TRIM37 overexpression was observed in several malignancies, including breast, esophageal, head and neck, liver hepatocellular, lung adenocarcinoma, lung squamous cell carcinoma, and gastric cancers, collectively termed TRIM37-overexpressing cancers. Higher TRIM37 expression was associated with adverse prognosis, particularly in luminal A breast cancer and liver hepatocellular carcinoma. In breast cancer, TRIM37 expression was associated with multiple immunomodulators and immune cell infiltration. Notably, in luminal A tumors, high TRIM37 expression coincided with increased Th2-related immune populations, regulatory T cells, and M2 macrophages, alongside reduced Th1-associated CD8\u0026thinsp;+\u0026thinsp;T cells and natural killer cells, consistent with an immunosuppressive tumor microenvironment. These findings identify TRIM37 as a candidate prognostic biomarker and link its expression to immune regulation of the tumor microenvironment, providing a clear rationale for experimental and clinical validation.\u003c/p\u003e","manuscriptTitle":"TRIM37 expression is associated with prognosis and immune-related features in luminal A breast cancer and hepatocellular carcinoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-29 13:07:04","doi":"10.21203/rs.3.rs-9298547/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"262656547652463310311017280579084830771","date":"2026-05-12T03:07:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"121429167184471593525823486791158987517","date":"2026-04-29T02:13:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"41643469056876124111725047294400359290","date":"2026-04-28T15:16:53+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-21T10:43:59+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-04T01:55:30+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-04T01:54:43+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Oncology","date":"2026-04-02T05:44:11+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dion","sideBox":"Learn more about [Discover Oncology](https://www.springer.com/12672)","snPcode":"","submissionUrl":"","title":"Discover Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"823566ef-195e-4b47-ab63-03f27b792862","owner":[],"postedDate":"April 29th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"262656547652463310311017280579084830771","date":"2026-05-12T03:07:19+00:00","index":76,"fulltext":""},{"type":"reviewerAgreed","content":"121429167184471593525823486791158987517","date":"2026-04-29T02:13:13+00:00","index":58,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-29T13:07:04+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-29 13:07:04","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9298547","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9298547","identity":"rs-9298547","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}