Decoding tumor heterogeneity in uveal melanoma: basement membrane genes as novel biomarkers and therapeutic targets revealed by multi-omics approaches for cancer immunotherapy.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37822877", "kind": "science-record", "revision": 4, "content_hash": "sha256:f1b284091bdd17c047ef95b1951b963bc1c5260a5a7f9f3b960edec4f93ab4d7", "created_at": "2026-11-01T19:02:41Z", "updated_at": "2026-11-01T22:52:53Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Decoding tumor heterogeneity in uveal melanoma: basement membrane genes as novel biomarkers and therapeutic targets revealed by multi-omics approaches for cancer immunotherapy.", "doi": "10.3389/fphar.2023.1264345", "pmid": "37822877", "authors": ["Yunyue Li", "Huabao Cai", "Jinyan Yang", "Xixi Xie", "Shengbin Pei", "Yifan Wu", "Jinhao Zhang", "Guobin Song", "Jieying Zhang", "Qinhong Zhang", "Hao Chi", "Guanhu Yang"], "journal": "Frontiers in pharmacology", "year": 2023, "abstract": "Background: Uveal melanoma (UVM) is a primary intraocular malignancy that poses a significant threat to patients' visual function and life. The basement membrane (BM) is critical for establishing and maintaining cell polarity, adult function, embryonic and organ morphogenesis, and many other biological processes. Some basement membrane protein genes have been proven to be prognostic biomarkers for various cancers. This research aimed to develop a novel risk assessment system based on BMRGs that would serve as a theoretical foundation for tailored and accurate treatment. Methods: We used gene expression profiles and clinical data from the TCGA-UVM cohort of 80 UVM patients as a training set. 56 UVM patients from the combined cohort of GSE84976 and GSE22138 were employed as an external validation dataset. Prognostic characteristics of basement membrane protein-related genes (BMRGs) were characterized by Lasso, stepwise multifactorial Cox. Multivariate analysis revealed BMRGs to be independent predictors of UVM. The TISCH database probes the crosstalk of BMEGs in the tumor microenvironment at the single-cell level. Finally, we investigated the function of ITGA5 in UVM using multiple experimental techniques, including CCK8, transwell, wound healing assay, and colony formation assay. Results: There are three genes in the prognostic risk model (ADAMTS10, ADAMTS14, and ITGA5). After validation, we determined that the model is quite reliable and accurately forecasts the prognosis of UVM patients. Immunotherapy is more likely to be beneficial for UVM patients in the high-risk group, whereas the survival advantage may be greater for UVM patients in the low-risk group. Knockdown of ITGA5 expression was shown to inhibit the proliferation, migration, and invasive ability of UVM cells in vitro experiments. Conclusion: The 3-BMRGs feature model we constructed has excellent predictive performance which plays a key role in the prognosis, informing the individualized treatment of UVM patients. It also provides a new perspective for assessing pre-immune efficacy.", "claims": [{"id": "claim-method", "statement": "To compare the overall survival (OS) between the high-risk and low-risk groups, Kaplan-Meier (KM) survival curves and log-rank tests were employed. In addition, Lasso regression analyses were performed to assess the potential relevance of BMRGs. A stepwise multivariate Cox regression analysis was then employed to construct a BMRG signature. The predictive performance of the model was evaluated using a time-dependent ROC curve.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37822877", "locator": "sections[16] \"2.14 Statistical analysis\" paragraph 2", "quote": "To compare the overall survival (OS) between the high-risk and low-risk groups, Kaplan-Meier (KM) survival curves and log-rank tests were employed. In addition, Lasso regression analyses were performed to assess the potential relevance of BMRGs. A stepwise multivariate Cox regression analysis was then employed to construct a BMRG signature. The predictive performance of the model was evaluated using a time-dependent ROC curve."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37822877", "locator": "sections[31] \"Data availability statement\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The constructed BMRGs signature possesses excellent predictive ability in prognosticating UVM patients.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37822877", "locator": "sections[22] \"3.5 3-BMRGs signatures exhibit superior performance compared to others in prognostic prediction\" paragraph 2", "quote": "Overall, our study indicates that our constructed BMRGs signature possesses excellent predictive ability in prognosticating UVM patients."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The constructed BMRGs signature possesses excellent predictive ability in prognosticating UVM patients.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:37822877"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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