Overweight/obesity-related transcriptomic signature as a correlate of clinical outcome, immune microenvironment, and treatment response in hepatocellular carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36714595", "kind": "science-record", "revision": 3, "content_hash": "sha256:d8bbe63c3939a3e6a44da2eeacab88c9704564a7b4c1b778eb34b01bfcd776cf", "created_at": "2026-11-01T19:01:17Z", "updated_at": "2026-11-01T22:08:40Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Overweight/obesity-related transcriptomic signature as a correlate of clinical outcome, immune microenvironment, and treatment response in hepatocellular carcinoma.", "doi": "10.3389/fendo.2022.1061091", "pmid": "36714595", "authors": ["Ning-Ning Feng", "Xi-Yue Du", "Yue-Shan Zhang", "Zhi-Kai Jiao", "Xiao-Hui Wu", "Bao-Ming Yang"], "journal": "Frontiers in endocrinology", "year": 2022, "abstract": "Backgrounds: The pandemic of overweight and obesity (quantified by body mass index (BMI) ≥ 25) has rapidly raised the patient number of non-alcoholic fatty hepatocellular carcinoma (HCC), and several clinical trials have shown that BMI is associated with the prognosis of HCC. However, whether overweight/obesity is an independent prognostic factor is arguable, and the role of overweight/obesity-related metabolisms in the progression of HCC is scarcely known.\nMaterials and methods: In the present study, clinical information, mRNA expression profile, and genomic data were downloaded from The Cancer Genome Atlas (TCGA) as a training cohort (TCGA-HCC) for the identification of overweight/obesity-related transcriptome. Machine learning and the Cox regression analysis were conducted for the construction of the overweight/obesity-associated gene (OAG) signature. The Kaplan-Meier curve, receiver operating characteristic (ROC) curve, and the Cox regression analysis were performed to assess the prognostic value of the OAG signature, which was further validated in two independent retrospective cohorts from the International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO). Subsequently, functional enrichment, genomic profiling, and tumor microenvironment (TME) evaluation were utilized to characterize biological activities associated with the OAG signature. GSE109211 and GSE104580 were retrieved to evaluate the underlying response of sorafenib and transcatheter arterial chemoembolization (TACE) treatment, respectively. The Genomics of Drug Sensitivity in Cancer (GDSC) database was employed for the evaluation of chemotherapeutic response.\nResults: Overweight/obesity-associated transcriptome was mainly involved in metabolic processes and noticeably and markedly correlated with prognosis and TME of HCC. Afterward, a novel established OAG signature (including 17 genes, namely, GAGE2D, PDE6A, GABRR1, DCAF8L1, DPYSL4, SLC6A3, MMP3, RIBC2, KCNH2, HTRA3, PDX1, ATHL1, PRTG, SHC4, C21orf29, SMIM32, and C1orf133) divided patients into high and low OAG score groups with distinct prognosis (median overall survival (OS): 24.87 vs. 83.51 months, p < 0.0001), and the values of area under ROC curve (AUC) in predicting 1-, 2-, 3-, and 4-year OS were 0.81, 0.80, 0.83, and 0.85, respectively. Moreover, the OAG score was independent of clinical features and also exhibited a good ability for prognosis prediction in the ICGC-LIHC-JP cohort and GSE54236 dataset. Expectedly, the OAG score was also highly correlated with metabolic processes, especially oxidative-related signaling pathways. Furthermore, abundant enrichment of chemokines, receptors, MHC molecules, and other immunomodulators as well as PD-L1/PD-1 expression among patients with high OAG scores indicated that they might have better responses to immunotherapy. However, probably exclusion of T cells from infiltrating tumors resulting in lower infiltration of effective T cells would restrict immunotherapeutic effects. In addition, the OAG score was significantly associated with the response of sorafenib and TACE treatment.\nConclusions: Overall, this study comprehensively disclosed the relationship between BMI-guided transcriptome and HCC. Moreover, the OAG signature had the potential clinical applications in the future to promote clinical management and precision medicine of HCC.", "claims": [{"id": "claim-method", "statement": "The univariate and multivariate Cox regression analyses were used to disclose the factors associated with survival.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36714595", "locator": "sections[11] \"2.9 Statistical analysis\" paragraph 2", "quote": "The univariate and multivariate Cox regression analyses were used to disclose the factors associated with survival."}], "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 author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36714595", "locator": "sections[24] \"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 author."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A combination of univariate and multivariate Cox regression analyses revealed that the OAG score was a robust prognostic factor (HR = 5.20, 95% CI, 2.55–10.60, p < 0.0001), which was independent of clinical features in TCGA-HCC cohort ( Table 3 ).", "kind": "quantitative", "target": {"value": 95.0, "unit": "per cent", "tolerance": null, "source": "A combination of univariate and multivariate Cox regression analyses revealed that the OAG score was a robust prognostic factor (HR = 5.20, 95% CI, 2.55–10.60, p < 0.0001), which was independent of clinical features in TCGA-HCC cohort ( Table 3 )."}, "evidence": [{"asset": "source:pmid:36714595", "locator": "sections[17] \"3.5 Association between independent OAG score and clinical features\" paragraph 2", "quote": "A combination of univariate and multivariate Cox regression analyses revealed that the OAG score was a robust prognostic factor (HR = 5.20, 95% CI, 2.55–10.60, p < 0.0001), which was independent of clinical features in TCGA-HCC cohort ( Table 3 )."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A combination of univariate and multivariate Cox regression analyses revealed that the OAG score was a robust prognostic factor (HR = 5.20, 95% CI, 2.55–10.60, p < 0.0001), which was independent of clinical features in TCGA-HCC cohort ( Table 3 ).", "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:36714595"], "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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The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE54236", "GSE109211", "GSE104580"], "resolved_accessions": ["GSE54236", "GSE109211", "GSE104580"], "statements": ["The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding author."], "basis": "The paper names GSE54236, GSE109211, GSE104580 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["cox_ph"], "assets": ["source:pmid:36714595", "data:geo:GSE104580"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE104580"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T18:25:24Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 21099, "completion_tokens": 2887, "cached_tokens": 256}}, "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:36714595", "type": "paper", "label": "pmid:36714595"}, {"id": "source:pmid:36714595", "type": "manuscript", "label": "PMID 36714595 full text"}, {"id": "data:geo:GSE104580", "type": "dataset", "label": "GEO GSE104580"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:36714595", "type": "paper", "label": "pmid:36714595"}, {"id": "source:pmid:36714595", "type": "manuscript", "label": "PMID 36714595 full text"}, {"id": "data:geo:GSE104580", "type": "dataset", "label": "GEO GSE104580"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-36714595", "type": "extraction", "used": ["source:pmid:36714595"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE104580", "type": "accession_resolution", "used": ["data:geo:GSE104580"], "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:36714595", "parent_hash": "sha256:be8de47def53c09520c379466b9d470aaf4254f352273e767add9405d3d6c041", "fork_of": null, "generation": 2}, "gaps": ["asset:data:geo:GSE104580 licence not read", "asset:data:geo:GSE104580 not downloaded", "asset:data:geo:GSE109211 licence not read", "asset:data:geo:GSE109211 not downloaded", "asset:data:geo:GSE54236 licence not read", "asset:data:geo:GSE54236 not downloaded", "execution.not_run", "method.reader_differs_from_extractor", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"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": 1.0, "evidence": ["The univariate and multivariate Cox regression analyses were used to disclose the factors associated with survival."], "order_basis": "analysis_only", "id": "assay:1"}]}