Identification and construction of a 13-gene risk model for prognosis prediction in hepatocellular carcinoma patients.

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Gene expression information of HCC was accessed from GEO database, and differentially expressed genes (DEGs) were obtained through the joint analysis of multi-chip. Functional and pathway enrichment analyses of DEGs indicated that the enrichment was mainly displayed in biological processes such as nuclear division. Based on TCGA-LIHC data set, univariate, LASSO, and multivariate Cox regression analyses were conducted on the DEGs. Then, 13 feature genes were screened for the risk model. Also, the hub genes were examined in our collected clinical samples and GEPIA database. The performance of the risk model was validated by Kaplan-Meier survival analysis and receiver operation characteristic (ROC) curves. While its universality was verified in GSE76427 and ICGC (LIRI-JP) validation cohorts. Besides, through combining patients' clinical features (age, gender, T staging, and stage) and risk scores, univariate and multivariate Cox regression analyses revealed that the risk score was an effective independent prognostic factor. Finally, a nomogram was implemented for 3-year and 5-year overall survival prediction of patients. Our findings aid precision prediction for prognosis of HCC patients.", "claims": [{"id": "claim-method", "statement": "Based on TCGA‐LIHC data set, univariate, LASSO, and multivariate Cox regression analyses were conducted on the DEGs.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35421268", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Based on TCGA‐LIHC data set, univariate, LASSO, and multivariate Cox regression analyses were conducted on the DEGs."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data that support the findings of this study are available on request from the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35421268", "locator": "sections[25] \"DATA AVAILABILITY STATEMENT\" paragraph 2", "quote": "The data that support the findings of this study are available on request from the corresponding author."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Then, 13 optimal feature genes were determined to establish a risk model (Figure 3C).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35421268", "locator": "sections[14] \"Generation and evaluation of the risk model\" paragraph 2", "quote": "Then, 13 optimal feature genes were determined to establish a risk model (Figure 3C)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Then, 13 optimal feature genes were determined to establish a risk model (Figure 3C).", "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:35421268"], "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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