ArticleJournal of gastrointestinal oncology2025
Multi-omics analyses develop and validate the optimal prognostic model on overall survival prediction for resectable hepatocellular carcinoma.
Article in Journal of gastrointestinal oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- EBF1 regulates sensory establishment in the cochlea by positioning the medial boundary of the prosensory domain and restricting proliferation of the sensory progenitor population.Development (Cambridge, England) · 2026Article
- Navigating the Labyrinth of Hepatocellular Carcinoma: Leveraging AI/ML for Precision Oncology.Oncology research · 2026Review
- Liver biopsy in the modern era: from traditional techniques to artificial intelligence and multi-omics integration.Frontiers in medicine · 2025Review
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Authors and funding
6 authors.
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Abstract
Background: Prediction of prognosis in patients with hepatocellular carcinoma (HCC) by single-omics profiling has been widely studied. However, the prognosis related to biomarkers of multiple omics has not been investigated. We aimed to establish and validate a prediction model for prognosis prediction of resectable HCC combining multi-omics and clinicopathological factors. Methods: The training cohort involved multi-omics data of 330 patients with resectable HCC (stage I-IIIA) at mutational, copy number variation (CNV), transcriptional, and methylation levels from The Cancer Genome Atlas (TCGA) database, along with clinicopathological information. The validation cohort involved samples from 40 HCC patients of Beijing Youan Hospital. Univariate and multivariate analyses were performed in single-omics with clinicopathological variables regarding patient prognosis, and independent risk factors were combined to establish the multi-omics model. The predictive accuracy was assessed by the receiver operating characteristic (ROC) method. Results: The mutational, copy number, transcriptional, and methylation alterations in HCC were characterized. Conclusions: A multi-omics model combining molecular aberrancies and clinicopathological information was established and proved to be optimal for prognosis prediction of resectable HCC. This model may be helpful for therapeutic strategy selection and survival assessment.
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