Mitochondrial metabolic reprogramming-mediated immunogenic cell death reveals immune and prognostic features of clear cell renal cell carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37213288", "kind": "science-record", "revision": 3, "content_hash": "sha256:cad9f4632778da138a162135629a8f7186d623796bd8133748e11e0f1d3eaac2", "created_at": "2026-11-01T19:01:54Z", "updated_at": "2026-11-01T22:09:31Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Mitochondrial metabolic reprogramming-mediated immunogenic cell death reveals immune and prognostic features of clear cell renal cell carcinoma.", "doi": "10.3389/fonc.2023.1146657", "pmid": "37213288", "authors": ["Lin Yang", "Jing Xiong", "Sheng Li", "Xiaoqiang Liu", "Wen Deng", "Weipeng Liu", "Bin Fu"], "journal": "Frontiers in oncology", "year": 2023, "abstract": "Background: Mitochondrial metabolic reprogramming (MMR)-mediated immunogenic cell death (ICD) is closely related to the tumor microenvironment (TME). Our purpose was to reveal the TME characteristics of clear cell renal cell carcinoma (ccRCC) by using them.\nMethods: Target genes were obtained by intersecting ccRCC differentially expressed genes (DEGs, tumor VS normal) with MMR and ICD-related genes. For the risk model, univariate COX regression and K-M survival analysis were used to identify genes most associated with overall survival (OS). Differences in the TME, function, tumor mutational load (TMB), and microsatellite instability (MSI) between high and low-risk groups were subsequently compared. Using risk scores and clinical variables, a nomogram was constructed. Predictive performance was evaluated by calibration plots and receiver operating characteristics (ROC).\nResults: We screened 140 DEGs, including 12 prognostic genes for the construction of risk models. We found that the immune score, immune cell infiltration abundance, and TMB and MSI scores were higher in the high-risk group. Thus, high-risk populations would benefit more from immunotherapy. We also identified the three genes (CENPA, TIMP1, and MYCN) as potential therapeutic targets, of which MYCN is a novel biomarker. Additionally, the nomogram performed well in both TCGA (1-year AUC=0.862) and E-MTAB-1980 cohorts (1-year AUC=0.909).\nConclusions: Our model and nomogram allow accurate prediction of patients' prognoses and immunotherapy responses.", "claims": [{"id": "claim-method", "statement": "Univariate COX regression and K-M survival analysis (screening criteria: p<0.01; GEPIA database, http://gepia.cancer-pku.cn/index.html) were performed using TCGA-KIRC expression and survival data to identify TGs most associated with overall survival (OS), which was then used to perform a least absolute shrinkage and selector operation analysis (LASSO) with the “glmnet” package.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37213288", "locator": "sections[6] \"Developing a risk model based on prognosis-related genes\" paragraph 2", "quote": "Univariate COX regression and K-M survival analysis (screening criteria: p<0.01; GEPIA database, http://gepia.cancer-pku.cn/index.html) were performed using TCGA-KIRC expression and survival data to identify TGs most associated with overall survival (OS), which was then used to perform a least absolute shrinkage and selector operation analysis (LASSO) with the “glmnet” package."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/ Supplementary Material , further inquiries can be directed to the corresponding authors.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37213288", "locator": "sections[26] \"Data availability statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/ Supplementary Material , further inquiries can be directed to the corresponding authors."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study screened 140 differentially expressed target genes, including 12 prognostic genes, and found higher immune score, immune-cell infiltration, TMB, and MSI scores in the high-risk group.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37213288", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "We screened 140 DEGs, including 12 prognostic genes for the construction of risk models. We found that the immune score, immune cell infiltration abundance, and TMB and MSI scores were higher in the high-risk group. Thus, high-risk populations would benefit more from immunotherapy."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study screened 140 differentially expressed target genes, including 12 prognostic genes, and found higher immune score, immune-cell infiltration, TMB, and MSI scores in the high-risk group.", "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:37213288"], "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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