ArticleCancer medicine2022
Multi-omics data identified TP53 and LRP1B as key regulatory gene related to immune phenotypes via EPCAM in HCC.
Article in Cancer medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 6 citations in OpenAlex.
- Functional Interpretation of Recurrent Genetic Variants in Hepatocellular Carcinoma: Molecular Consequences and Clinical Relevance.Human mutation · 2026Review
- Molecular regulation by ubiquitin-specific proteases (USPs) in HCC: cell cycle, oncogenic signaling, and beyond.Naunyn-Schmiedeberg's archives of pharmacology · 2025Review
- The Emerging Role of Ubiquitin-Specific Protease 36 (USP36) in Cancer and Beyond.Biomolecules · 2024Review
- Review
- Multi-omics data identified TP53 and LRP1B as key regulatory gene related to immune phenotypes via EPCAM in HCC.Cancer medicine · 2022Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMany studies showed that the prognosis of hepatocellular carcinoma (HCC) was significantly associated with the expressions of TP53 and LRP1B. However, the potential influence of the two genes on the malignant progression of HCC is still to be expounded.
methodsAccording to the correlation analysis between immune cells and expression levels of TP53 and LRP1B, we filtered the immune cells to perform unsupervised clustering analysis. Integration of multi-omic data analysis identified genetic alteration and epigenetic alteration. In addition, pathway analysis was used to explore the potential function of the differentially expressed mRNAs. According to the differentially expressed genes, we established an interaction network to seek the hub gene. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to build a prognosis model.
resultsThe unsupervised clustering analysis showed that the cluster A1 showed the highest immune cell levels and the cluster B2 showed the lowest immune cell levels. Multi-omics data analysis identified that somatic mutations, copy number variations, and DNA methylation levels had significant differences between cluster A1 and cluster B2. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis found that the upregulated mRNAs in the cluster A1 were mainly concentrated in T cell activation, external side of plasma membrane, receptor ligand activity, and cytokine-cytokine receptor interaction. Importantly, the EPCAM was identified as a critical node in the lncRNAs-miRNAs-mRNAs regulatory network correlated with the immune phenotypes. In addition, based on differentially expressed genes between cluster A1 and cluster B2, the prognostic model established by LASSO could predict the overall survival (OS) of HCC accurately.
conclusionsThe results indicated that the TP53 and LRP1B acted as the key genes in regulating the immune phenotypes of HCC via EPCAM.
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