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Comprehensive DNA Methylation Analysis Using a Methyl-CpG-binding Domain Capture-based Method in Chronic Lymphocytic Leukemia Patients
Published on: June 16, 2017
DNA methylation-driven gene-based drug response prediction model for liver cancer: The critical role of GLS
Shuang Zheng1, Xi Yu1, Xiaozhou Wang1
1Department of Oncology, The People's Hospital of Liaoning Province, People's Hospital of China Medical University, Shenyang, Liaoning, China.
Background:
Aberrant DNA methylation plays a pivotal role in cancer progression by enhancing oncogene activation or silencing tumor suppressor genes, contributing to malignant phenotypes. Methylation driver genes (MDGs) are characterized by an inverse correlation between DNA methylation levels and mRNA expression, making them critical targets for cancer research.
Methods:
We analyzed the liver hepatocellular carcinoma (LIHC) dataset from The Cancer Genome Atlas (TCGA) using the R package MethylMix to identify MDGs. Prognostic models were developed through univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression, and multivariate Cox regression to identify core genes. We further evaluated the associations of these genes with the tumor immune microenvironment, immune checkpoint inhibitors (ICIs), and chemotherapeutic sensitivity. Finally, liver cancer tissue organoid culture experiments combined with DNA methylation sequencing were conducted to validate predictions of drug sensitivity.
Results:
A total of 21 MDGs were identified, among which GNA14, glutaminase (GLS), and GNG4 were selected to construct a prognostic risk score model. The model demonstrated robust predictive performance, with Receiver Operating Characteristic (ROC) values of 0.723, 0.764, and 0.716 for 1-, 3-, and 5-year survival, respectively. Among these, GLS emerged as a key gene, showing low methylation levels and high mRNA expression, which were associated with poor prognosis, significant alterations in the tumor immune microenvironment, and differential sensitivity to ICIs and chemotherapeutic agents.
Conclusion:
The three-gene MDG-based prognostic model effectively predicts survival outcomes in LIHC patients. Moreover, the methylation status of GLS serves as a biomarker for assessing immune microenvironment characteristics, responsiveness to immunotherapy, and chemotherapy sensitivity, highlighting its potential as a therapeutic target in liver cancer.
Insights
A three-gene methylation driver gene model predicts liver cancer survival. Glutaminase (GLS) methylation status indicates prognosis, immune microenvironment, and treatment response, offering a potential therapeutic target.
Area of Science:
- Oncology
- Epigenetics
- Genomics
Background:
- Aberrant DNA methylation drives cancer by altering oncogene and tumor suppressor gene expression.
- Methylation driver genes (MDGs) show an inverse correlation between DNA methylation and mRNA expression, crucial for cancer research.
Purpose of the Study:
- To identify methylation driver genes (MDGs) in liver hepatocellular carcinoma (LIHC).
- To develop a prognostic model for LIHC using MDGs.
- To investigate the association of MDGs with the tumor immune microenvironment and treatment sensitivity.
Main Methods:
- Analysis of TCGA LIHC dataset using MethylMix R package.
- Prognostic model development via univariate, LASSO, and multivariate Cox regression.
- Validation of drug sensitivity predictions using organoid culture and DNA methylation sequencing.
Main Results:
- Identified 21 MDGs, with GNA14, glutaminase (GLS), and GNG4 selected for a prognostic model.
- The three-gene model showed strong predictive performance for 1-, 3-, and 5-year survival (ROC values 0.723, 0.764, 0.716).
- GLS exhibited low methylation and high mRNA expression, correlating with poor prognosis, altered immune microenvironment, and differential treatment sensitivity.
Conclusions:
- A three-gene MDG model accurately predicts LIHC patient survival.
- GLS methylation status is a biomarker for immune microenvironment, immunotherapy response, and chemotherapy sensitivity.
- GLS presents a potential therapeutic target for liver cancer treatment.
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