Methylation signature genes identification of cancers occurrence and pattern recognition. (April 2020)

• Record Type: Journal Article
• Authors: Wang, Xuedong; Shang, Wenhui; Li, Xiaoqin; Chang, Yu
• Is Part Of: Computational biology and chemistry. Volume 85(2020)
• Publication Date: 2020-04
• Subjects: Cancer occurrence -- TCGA -- Cancer genomics -- Feature selection -- Bioinformatics; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2019.107198
• Languages: English
• ISSNs: 1476-9271

Abstract

Graphical abstract: Highlights: Focus on the early occurrence of cancer. The efficient and versatile method of gene screening for the occurrence of early cancer. The recognition accuracy and sensitivity greater than 97 % for all cancers. The occurrence of early cancer is closely related to immune and inflammatory responses. Abstract: In order to identify the signature genes of tumorigenesis, the pattern-recognition method was used to analyze the gene methylation (ME) data which included only normal and cancer samples and was collected from the TCGA (The Cancer Genome Atlas) database. Here, we analyzed the DNA methylation profiles of the six types of cancer and the ME signature genes for each cancer were selected by means of a combination of correlation, student's t -test and Elastic Net. Modeling by support vector machine, the accuracy of ME signature genes can be as high as 98 % for training set and as high as 97 % for the independent test set, the recognition accuracy of stage I is more than 97 % for training set and more than 98 % for test set. Then, the common signature genes and common pathways emerging in multiple cancers were obtained. A functional analysis of these signature genes indicates that the identified signatures have direct relationship with tumorigenesis and is very important for understanding the pathogenesis of cancer and the early therapy.