Deciphering KDM8 dysregulation and CpG methylation in hepatocellular carcinoma using multi-omics and machine learning.

ABSTRACT

Aim: This study investigates the altered expression and CpG methylation patterns of histone demethylase KDM8 in hepatocellular carcinoma (HCC), aiming to uncover insights and promising diagnostics biomarkers. Materials & methods: 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. Results: In HCC, KDM8 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. Conclusion: Our study uncovers CpG hypermethylation at cg02871891, possibly influencing KDM8 downregulation in HCC, suggesting these as promising biomarkers and targets.

Changes in gene function can play a role in causing cancer. In this study, we looked at how a specific gene called KDM8 behaves in liver cancer. By analyzing a large set of liver cancer samples, we investigated how gene interactions are different in this disease and if they can help predict liver cancer risk. Our results show that the KDM8 gene is less active, and its DNA gets chemically modified more often in liver cancer. We also found a group of genes and DNA changes, which are linked to the disease. Using this information, we identified 16 important markers and built a computer model that can accurately predict liver cancer. We found that DNA methylation at a specific spot called cg02871891 is especially important for predicting liver cancer. Overall, our study suggests that high levels of DNA methylation may lead to reduced KDM8 activity in liver cancer, which could be important for future research and better diagnostic tools.