Lactate metabolism orchestrates immune dysregulation in renal cancer: A multi-omics and causal inference study.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:41406083", "kind": "science-record", "revision": 4, "content_hash": "sha256:c702d71ebc1ba8a8591d3ba1702ad33467c123fecb15ce3823b5c5aa6a658277", "created_at": "2026-11-01T20:31:24Z", "updated_at": "2026-11-01T22:57:37Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Lactate metabolism orchestrates immune dysregulation in renal cancer: A multi-omics and causal inference study.", "doi": "10.1177/00368504251408094", "pmid": "41406083", "authors": ["Jiangbo Li", "Chen Liu", "Zhiguang Fu", "Qi He", "Xu Liu", "Zhijia Sun"], "journal": "Science progress", "year": 2025, "abstract": "BackgroundLactate shapes the tumor microenvironment and modulates immunity. Investigating lactate metabolism genes in renal cell carcinoma (RCC) could elucidate therapeutic targets.MethodsSingle-cell RNA sequencing (GSE242299), bulk RNA sequencing (GSE102101), and spatial transcriptomics (GSE175540) data for RCC were retrieved from GEO. Data processing included quality control, normalization, and dimensionality reduction (R packages). RCTD and CellChat were used for spatial deconvolution and cell-cell communication analysis. CIBERSORT and GSEA evaluated immune infiltration and pathway enrichment. Lactylation scores were derived via single-sample gene set enrichment analysis (ssGSEA) of lactate metabolism genes. Mendelian randomization (MR) assessed gene-cancer risk associations.ResultsMacrophages demonstrated a higher potential for interactions with other cell types due to their extensive receptor-ligand relationships. Lactylation score and MR analysis identified six pivotal genes associated with renal cancer risk: C4A and SERPINA1 were correlated with an elevated disease risk, whereas CD70, FXYD2, SERPINE1, and TUBB6 were associated with a reduced risk. These genes are linked to the degree of immune cell infiltration and can influence the disease process through diverse mechanisms. We also explored the expression profiles of primary genes involved in lactate metabolism in RCC and compared the metabolic pathways between different groups. Notably, experimental validation via tissue microarray immunofluorescence confirmed that the risk-associated genes C4A and SERPINA1 were significantly overexpressed in RCC tumor tissues.ConclusionLactic acid metabolism regulates RCC progression by modulating metabolic activity and immune cell infiltration. Key lactate metabolism genes present novel targets for RCC treatment.", "claims": [{"id": "claim-method", "statement": "We employed a two-sample MR (TSMR) design to investigate the causal associations between lactate metabolism gene expression and RCC risk. For statistical analysis, the inverse-variance weighted (IVW) method under a random-effects model was designated as the primary analysis approach for estimating causal effects between lactate metabolism gene expression and RCC risk.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41406083", "locator": "sections[3] \"Retrieval of datasets\" paragraph 2", "quote": "We employed a two-sample MR (TSMR) design to investigate the causal associations between lactate metabolism gene expression and RCC risk."}, {"asset": "source:pmid:41406083", "locator": "sections[8] \"Statistical analysis\" paragraph 2", "quote": "For statistical analysis, the inverse-variance weighted (IVW) method under a random-effects model was designated as the primary analysis approach for estimating causal effects between lactate metabolism gene expression and RCC risk."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original data supporting the conclusions of this study will be provided by the authors without reservation. For further inquiries, please contact the corresponding author directly.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41406083", "locator": "sections[23] \"fn-group\" paragraph 1", "quote": "The original data supporting the conclusions of this study will be provided by the authors without reservation. For further inquiries, please contact the corresponding author directly."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study identified six lactate metabolism genes causally associated with RCC risk.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:41406083", "locator": "sections[20] \"Conclusion\" paragraph 2", "quote": "Through integration of single-cell sequencing, spatial transcriptomics, and MR, we identified six lactate metabolism genes (C4A, CD70, FXYD2, SERPINA1, SERPINE1, TUBB6) causally associated with RCC risk."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study identified six lactate metabolism genes causally associated with RCC risk.", "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:41406083"], "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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