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Deciphering dysregulation and CpG methylation in hepatocellular carcinoma using multi-omics and machine learning. | LitMetric

Deciphering dysregulation and CpG methylation in hepatocellular carcinoma using multi-omics and machine learning.

Epigenomics

Snyder Institute of Chronic Diseases, Health Research & Innovation Center, Cumming School of Medicine, University of Calgary, Alberta, Canada.

Published: September 2024

This study investigates the altered expression and CpG methylation patterns of histone demethylase in hepatocellular carcinoma (HCC), aiming to uncover insights and promising diagnostics biomarkers. Leveraging TCGA-LIHC multi-omics data, we employed R/Bioconductor libraries and Cytoscape to analyze and construct a gene correlation network, and LASSO regression to develop an HCC-predictive model. In HCC, downregulation is correlated with CpGs hypermethylation. Differential gene correlation analysis unveiled a liver carcinoma-associated network marked by increased cell division and compromised liver-specific functions. The LASSO regression identified a highly accurate HCC prediction signature, prominently featuring CpG methylation at cg02871891. Our study uncovers CpG hypermethylation at cg02871891, possibly influencing downregulation in HCC, suggesting these as promising biomarkers and targets.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11370911PMC
http://dx.doi.org/10.1080/17501911.2024.2374702DOI Listing

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