Development and validation of a novel immune‒metabolic-Based classifier for hepatocellular carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39296052", "kind": "science-record", "revision": 3, "content_hash": "sha256:46dceb634389ce56e1de25221c1b75cb9c5de4bb8645d35f02132d84035c1af0", "created_at": "2026-11-01T20:29:28Z", "updated_at": "2026-11-01T22:12:43Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Development and validation of a novel immune‒metabolic-Based classifier for hepatocellular carcinoma.", "doi": "10.1016/j.heliyon.2024.e37327", "pmid": "39296052", "authors": ["Wenda Zhang", "Xinyi Zhou", "Lili Lin", "Anqi Lin", "Quan Cheng", "Zaoqu Liu", "Peng Luo", "Jian Zhang"], "journal": "Heliyon", "year": 2024, "abstract": "The heterogeneity of immune cells and metabolic pathways in hepatocellular carcinoma (HCC) patients has not been fully elucidated, leading to diverse clinical outcomes. Accurately distinguishing different HCC subtypes and recommending appropriate treatments is are highly important. In this study, we conducted a comprehensive analysis of 28 immune cells and 85 metabolic pathways in the TCGA-LIHC and GSE14520 datasets. Metabolism-related first principal component (MRPC1) and cytotoxic T lymphocyte (CTL) infiltration were used to assess the metabolic and immune infiltration levels of HCC patients, respectively. These two quantifiable indicators were then used to construct an immune‒metabolic classifier, which categorized HCC patients into three distinct groups. The potential biological mechanisms were explored through multiomics analysis, revealing that group S1 exhibited high metabolic activity and a high level of immune infiltration, that group S2 presented a low level of immune infiltration, and that group S3 presented low metabolic activity. This new immune‒metabolic classifier was well validated in a pancancer cohort of 9296 patients. The efficacy of multiple treatment approaches was assessed in relation to different immune‒metabolic groups, indicating that group S1 patients may benefit from immunotherapy, that group S2 patients are suitable for transcatheter arterial chemoembolization (TACE), and that group S3 patients are appropriate candidates for tyrosine kinase inhibitors. In conclusion, this immune‒metabolic classifier is anticipated to address the differences in treatment efficacy among HCC patients due to the heterogeneity of the tumor microenvironment, and to help refine the individualized treatment choices for clinical patients.", "claims": [{"id": "claim-method", "statement": "The ConsensusClusterPlus R package (v1.58.0) [33] was used to identify molecular subtypes of HCC on the basis of the activity of immune cells and metabolic pathways. At each iteration 80 % of the samples were divided into subsamples and each subsample was divided into up to k (maximum K = 6) groups basis of the on the Euclidean distance via the k-means algorithm.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39296052", "locator": "sections[5] \"Clustering for immune cells and metabolic pathways\" paragraph 2", "quote": "The ConsensusClusterPlus R package (v1.58.0) [33] was used to identify molecular subtypes of HCC on the basis of the activity of immune cells and metabolic pathways. At each iteration 80 % of the samples were divided into subsamples and each subsample was divided into up to k (maximum K = 6) groups basis of the on the Euclidean distance via the k-means algorithm."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Data to support the findings of this study is available on reasonable request from the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39296052", "locator": "sections[21] \"Data availability\" paragraph 2", "quote": "Data to support the findings of this study is available on reasonable request from the corresponding author."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A classifier was generated on the basis of the cutoff values for MRPC1 and CTL infiltration, and the classification efficacy of the classifier was evaluated (TCGA-LIHC: accuracy: 0.90, weighted F1: 0.90, weighted sensitivity: 0.93, weighted recall: 0.90; GSE14520: accuracy: 0.75, weighted F1: 0.75, weighted sensitivity: 0.83, weighted recall: 0.75) (Fig. 6B–E).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39296052", "locator": "sections[16] \"An immune‒metabolic-based classifier was established and validated in multiple cancer patients\" paragraph 2", "quote": "A classifier was generated on the basis of the cutoff values for MRPC1 and CTL infiltration, and the classification efficacy of the classifier was evaluated (TCGA-LIHC: accuracy: 0.90, weighted F1: 0.90, weighted sensitivity: 0.93, weighted recall: 0.90; GSE14520: accuracy: 0.75, weighted F1: 0.75, weighted sensitivity: 0.83, weighted recall: 0.75) (Fig. 6B–E)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A classifier was generated on the basis of the cutoff values for MRPC1 and CTL infiltration, and the classification efficacy of the classifier was evaluated (TCGA-LIHC: accuracy: 0.90, weighted F1: 0.90, weighted sensitivity: 0.93, weighted recall: 0.90; GSE14520: accuracy: 0.75, weighted F1: 0.75, weighted sensitivity: 0.83, weighted recall: 0.75) (Fig. 6B–E).", "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:39296052"], "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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