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pmid:33300278
Development and validation of a CTNNB1-associated metabolic prognostic model for hepatocellular carcinoma.
Junyu Huo · Liqun Wu · Yunjin Zang
Journal of cellular and molecular medicine · 2021 doi:10.1111/jcmm.16181
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Experiment
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Complete file
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We obtained the mRNA expression profiles and clinicopathological data from The Cancer Genome Atlas (TCGA), the International Cancer Genomics Consortium (ICGC) and the Gene Expression Omnibus database (GSE14520 and GSE116174). We conducted gene set enrichment analysis on HCC patients with and without mutant CTNNB1 through TCGA dataset. The Kaplan-Meier analysis and univariate Cox regression analysis assisted in screening metabolic genes related to prognosis, and the prognosis model was constructed using the Lasso and multivariate Cox regression analysis. The prognostic model showed good prediction performance in both the training cohort (TCGA) and the validation cohorts (ICGC, GSE14520, GSE116174), and the high-risk group presented obviously poorer overall survival compared with low-risk group. Cox regression analysis indicated that the risk score can be used as an independent predictor for the overall survival of HCC. 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"17 (48.57%)"]], "row_count": 23, "column_count": 5, "numeric_cells": 45, "header_rows": 2, "locator": "section[16]/table-wrap[4]#jcmm16181-tbl-0006"}}], "gaps": ["asset:data:geo:GSE116174 not downloaded", "asset:data:geo:GSE116174 licence not read", "asset:data:geo:GSE14520 not downloaded", "asset:data:geo:GSE14520 licence not read"]}, "analysis": {"state": "complete", "methods": [{"id": "method-1", "family": "survival_analysis", "specific": "kaplan_meier", "label": "Survival analysis", "dsl_operations": ["survival_km"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.7, "band": "medium", "quote": "Kaplan-Meier"}}, {"id": "method-2", "family": "survival_analysis", "specific": "cox_proportional_hazards", "label": "Survival analysis", "dsl_operations": ["cox_ph"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.7, "band": "medium", "quote": "Cox regression"}}], "targets": [], "gaps": []}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["survival_km"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: kaplan_meier."}, "capability": {"tier": "R1", "capability_id": 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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": ["GSE14520", "GSE116174"], "resolved_accessions": ["GSE14520", "GSE116174"], "statements": ["The data sets analysed for this study were obtained from The Cancer Genome Atlas (TCGA) (https://portal.gdc.cancer.gov/), the International Cancer Genome Consortium (ICGC) (https://icgc.org/), the Gene Expression Omnibus (GEO) (https://www.ncbi.nlm.nih.gov/geo/) and UCSC Xena website (https://xenabrowser.net/)."], "basis": "The paper names GSE14520, GSE116174 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. 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