Research Paper Volume 12, Issue 2 pp 1332—1365
Identification of key genes by integrating DNA methylation and next-generation transcriptome sequencing for esophageal squamous cell carcinoma
- 1 The Key Laboratory of Molecular Biology for High Cancer Incidence Coastal Chaoshan Area, Shantou University Medical College, Shantou 515041, Guangdong, P.R. China
- 2 Department of Biochemistry and Molecular Biology, Shantou University Medical College, Shantou 515041, Guangdong, P.R. China
- 3 Institute of Oncologic Pathology, Shantou University Medical College, Shantou 515041, Guangdong, P.R. China
- 4 Departments of Oncology Surgery, Shantou Central Hospital, Affiliated Shantou Hospital of Sun Yat-Sen University, Shantou 515041, Guangdong, P.R. China
- 5 Departments of Pathology, Shantou Central Hospital, Affiliated Shantou Hospital of Sun Yat-Sen University, Shantou 515041, Guangdong, P.R. China
- 6 Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
received: October 12, 2019 ; accepted: December 25, 2019 ; published: January 21, 2020 ;https://doi.org/10.18632/aging.102686
How to Cite
Copyright © 2020 Chen et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Aberrant DNA methylation leads to abnormal gene expression, making it a significant regulator in the progression of cancer and leading to the requirement for integration of gene expression with DNA methylation. Here, we identified 120 genes demonstrating an inverse correlation between DNA methylation and mRNA expression in esophageal squamous cell carcinoma (ESCC). Sixteen key genes, such as SIX4, CRABP2, and EHD3, were obtained by filtering 10 datasets and verified in paired ESCC samples by qRT-PCR. 5-Aza-dC as a DNA methyltransferase (DNMT) inhibitor could recover their expression and inhibit clonal growth of cancer cells in seven ESCC cell lines. Furthermore, 11 of the 16 genes were correlated with OS (overall survival) and DFS (disease-free survival) in 125 ESCC patients. ChIP-Seq data and WGBS data showed that DNA methylation and H3K27ac histone modification of these key genes displayed inverse trends, suggesting that there was collaboration between DNA methylation and histone modification in ESCC. Our findings illustrate that the integrated multi-omics data (transcriptome and epigenomics) can accurately obtain potential prognostic biomarkers, which may provide important insight for the effective treatment of cancers.