Multiomics combined with single-cell analysis shows that mitophagy-related genes could accurately predict the prognosis of patients with clear cell renal cell carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38482447", "kind": "science-record", "revision": 3, "content_hash": "sha256:affcc667acc84af190dd6de42f0ea7021efe2df257f3d96e9b10cb222b906387", "created_at": "2026-11-01T19:20:25Z", "updated_at": "2026-11-01T22:11:27Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Multiomics combined with single-cell analysis shows that mitophagy-related genes could accurately predict the prognosis of patients with clear cell renal cell carcinoma.", "doi": "10.21037/tcr-23-1765", "pmid": "38482447", "authors": ["Hang Yin", "Yonggui Xiao", "Hubo Li", "Yong Wang", "Liguo Zhang", "Anliang Yao", "Shaosan Kang", "Fenghong Cao"], "journal": "Translational cancer research", "year": 2024, "abstract": "Background: Clear cell renal cell carcinoma (ccRCC) is a heterogeneous tumor that accounts for a large proportion of kidney cancer, It is prone to recurrence and metastasis, and has a high mortality rate. Although mitophagy is important for metastasis and the recurrence of various tumors, its effect on renal clear cell carcinoma is poorly understood.\nMethods: Mitophagy-related genes were obtained through the GeneCards database. We normalised the data from different sources by removing the batch effect. Next, we conducted a preliminary screening of mitophagy-related genes and obtained prognosis-related genes from differentially expressed genes. We constructed a prognostic model using least absolute shrinkage and selection operator (LASSO) regression with data from The Cancer Genome Atlas (TCGA) and GSE29609 datasets and validated it internally. International Cancer Genome Consortium (ICGC) and E-MTAB-1980 cohorts also provided double external validation. In addition, we combined multi-omics and single-cell data to comprehensively analyse mitophagy-related gene model signature (MRGMS). Combined with the mitophagy-related gene model (MRGM) score, we constructed a nomogram. Finally, we performed pathway enrichment analysis using a variety of methods.\nResults: Multiomics and single-cell data analysis showed that the MRGMS is important for patients with ccRCC and is expected to become a new biomarker. The construction of a nomogram was conducive to accurately predicting patient survival.\nConclusions: Mitophagy-related genes are important for predicting the prognosis of ccRCC and are conducive to the development of more personalised treatment plans for patients.", "claims": [{"id": "claim-method", "statement": "We applied least absolute shrinkage and selection operator (LASSO) regression and cross-validation to obtain the best MRGMS for building the model.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38482447", "locator": "sections[6] \"MRGM construction with prognostically associated differential mitophagy-related genes\" paragraph 2", "quote": "We applied least absolute shrinkage and selection operator (LASSO) regression and cross-validation to obtain the best MRGMS for building the model."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Using “mitophagy” as the keyword, we retrieved 5,655 mitophagy-related genes (https://www.genecards.org/) from the searchable GeneCards database.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38482447", "locator": "sections[4] \"Access to research data using public databases\" paragraph 2", "quote": "Using “mitophagy” as the keyword, we retrieved 5,655 mitophagy-related genes (https://www.genecards.org/) from the searchable GeneCards database."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A prognostic model was constructed using LASSO regression with TCGA and GSE29609 data and was internally validated.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38482447", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "We constructed a prognostic model using least absolute shrinkage and selection operator (LASSO) regression with data from The Cancer Genome Atlas (TCGA) and GSE29609 datasets and validated it internally."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A prognostic model was constructed using LASSO regression with TCGA and GSE29609 data and was internally validated.", "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:38482447"], "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. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:E-MTAB-1980"], "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:E-MTAB-1980"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38482447", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.21037/tcr-23-1765", "sha256": 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"version": null, "note": "Using “mitophagy” as the keyword, we retrieved 5,655 mitophagy-related genes (https://www.genecards.org/) from the searchable GeneCards database.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Using “mitophagy” as the keyword, we retrieved 5,655 mitophagy-related genes (https://www.genecards.org/) from the searchable GeneCards database.", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM4819725", "GSM4819726", "GSM4819727", "GSM4819728", "GSM4819729", "GSM4819730", "GSM4819731", "GSM4819732", "GSM4819733", "GSM4819734", "GSM4819735", "GSM4819736", "GSM4819737", "GSM4819738"], "sample_count": 14, "group_sizes": null, "group_sizes_basis": null, "platform": "16791", "taxon": "Homo sapiens", "title": "Single Cell Analyses of Renal Cell Cancers Reveal Insights into Tumor Microenvironment, Cell of Origin, and Therapy Response", "resolution_checked_at": "2026-11-01T18:46:34Z", 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No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["cox_ph"], "assets": ["source:pmid:38482447", "data:geo:E-MTAB-1980"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:E-MTAB-1980"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T19:12:04Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": null}, "calls": 5, "usage": {"prompt_tokens": 9356, "completion_tokens": 2627, "cached_tokens": 264}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:38482447", "type": "paper", "label": "pmid:38482447"}, {"id": "source:pmid:38482447", "type": "manuscript", "label": "PMID 38482447 full text"}, {"id": "data:geo:E-MTAB-1980", "type": "dataset", "label": "GEO E-MTAB-1980"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:38482447", "type": "paper", "label": "pmid:38482447"}, {"id": "source:pmid:38482447", "type": "manuscript", "label": "PMID 38482447 full text"}, {"id": "data:geo:E-MTAB-1980", "type": "dataset", "label": "GEO E-MTAB-1980"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-38482447", "type": "extraction", "used": ["source:pmid:38482447"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-E-MTAB-1980", "type": "accession_resolution", "used": ["data:geo:E-MTAB-1980"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:38482447", "parent_hash": "sha256:497410e041f7a1e1dd643155170790e2884d238ea1402e0c4013ece81979cbe3", "fork_of": null, "generation": 2}, "gaps": ["asset:data:geo:E-MTAB-1980 licence not read", "asset:data:geo:E-MTAB-1980 not downloaded", "asset:data:geo:GSE159115 licence not read", "asset:data:geo:GSE159115 not downloaded", "asset:data:geo:GSE29609 licence not read", "asset:data:geo:GSE29609 not downloaded", "asset:data:geo:GSE40435 licence not read", "asset:data:geo:GSE40435 not downloaded", "asset:data:geo:GSE53757 licence not read", "asset:data:geo:GSE53757 not downloaded", "execution.not_run", "method.reader_named_unmapped", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "ihc", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["in expression level. Finally, we queried the immunohistochemistry of MRGMS in the HPA database. Channel enrich", "s; TISCH, Tumor Immune Single-cell Hub; IHC, Immunohistochemistry; M, model; T, test; LASSO, least absolute sh", "mnibus; TISCH, Tumor Immune Single-cell Hub; IHC, Immunohistochemistry; M, model; T, test; LA"], "order_basis": "paper_text_order:2491", "id": "assay:1"}, {"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["cox_ph"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 0.8, "evidence": ["Cox regression"], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}