Fc receptor-like A promotes malignant behavior in renal cell carcinoma and correlates with tumor immune infiltration.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39108036", "kind": "science-record", "revision": 3, "content_hash": "sha256:5b1a7ad30dfbafd1a77c19072528bb21df54b57973b7d6f2710a6cd8f615157c", "created_at": "2026-11-01T20:29:11Z", "updated_at": "2026-11-01T22:12:23Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Fc receptor-like A promotes malignant behavior in renal cell carcinoma and correlates with tumor immune infiltration.", "doi": "10.1002/cam4.70072", "pmid": "39108036", "authors": ["Jun-Peng Liu", "Yi-Fan Jiang", "Jin-Wen Liu", "Chong-Jiang Tian", "Yu-Zhao Lin", "Yun-Zhi Yang", "Ze-Ke Zhang", "Yi-Liang Fang", "Bin Huang", "Hao Lin"], "journal": "Cancer medicine", "year": 2024, "abstract": "BACKGROUND: Our study aims to investigate the mechanisms through which Fc receptor-like A (FCRLA) promotes renal cell carcinoma (RCC) and to examine its significance in relation to tumor immune infiltration.\nMATERIALS AND METHODS: The correlation between FCRLA and data clinically related to RCC was explored using The Cancer Genome Atlas (TCGA), then validated using Gene Expression Omnibus (GEO) gene chip data. Enrichment and protein-protein interaction (PPI) network analyses were performed for FCRLA and its co-expressed genes. FCRLA was knocked down in RCC cell lines to evaluate its impact on biological behavior. Then the potential downstream regulators of FCRLA were determined by western blotting, and rescue experiments were performed for verification. The relevance between FCRLA and various immune cells was analyzed through GSEA, TIMER, and GEPIA tools. TIDE and ESTIMATE algorithms were used to predict the effect of FCRLA in immunotherapy.\nRESULTS: Fc receptor-like A was associated with clinical and T stages and could predict the M stage (AUC = 0.692) and 1-3- and 5-year survival rates (AUC = 0.823, 0.834, and 0.862) of RCC patients. Higher expression of FCLRA predicted an unfavorable overall survival (OS) in TCGA-RCC and GSE167573 datasets (p = 0.03, p = 0.04). FCRLA promoted the malignant biological behavior of RCC cells through the pERK1/2/-MMP2 pathway and was associated with tumor immune microenvironment in RCC.\nCONCLUSION: Fc receptor-like A is positively correlated with poor outcomes in RCC patients and plays an oncogenic role in RCC through the pERK1/2-MMP2 pathway. Patients with RCC might benefit from immunotherapy targeting FCRLA.", "claims": [{"id": "claim-method", "statement": "Kaplan–Meier analysis with the log‐rank test was performed to depict the OS curves.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39108036", "locator": "sections[4] \"Analysis of overall survival (OS) and clinicopathologic data, and construction of receiver operating characteristic (ROC) curves\" paragraph 2", "quote": "Kaplan–Meier analysis with the log‐rank test was performed to depict the OS curves."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The bioinformatics data used in this study are freely available from the TCGA database (https://portal.gdc.cancer.gov/projects/TCGA‐RCC) and the GEO database (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE167573). The authors did not have special access privileges.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39108036", "locator": "sections[31] \"DATA AVAILABILITY STATEMENT\" paragraph 2", "quote": "The bioinformatics data used in this study are freely available from the TCGA database (https://portal.gdc.cancer.gov/projects/TCGA‐RCC) and the GEO database (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE167573). 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This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE167573"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE167573"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39108036", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1002/cam4.70072", "sha256": "sha256:2de5a88016393043665e71cb10ccad0684b7ca939ed7b5d3d782b3dcbf968b7b", "bytes": 39995, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1002/cam4.70072", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11303447", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE167573", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE167573", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE167573", "version": null, "note": "The bioinformatics data used in this study are freely available from the TCGA database (https://portal.gdc.cancer.gov/projects/TCGA‐RCC) and the GEO database (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE167573). 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