A novel m6A‐related prognostic signature for predicting the overall survival of hepatocellular carcinoma patients. Issue 1 (14th October 2021)

• Record Type: Journal Article
• Authors: Xie, Shiyang; Wang, Yaxuan; Huang, Jin; Li, Guang
• Is Part Of: IET systems biology. Volume 16:Issue 1(2022)
• Page Start: 1
• Page End: 17
• Publication Date: 2021-10-14
• Subjects: gene signature -- hepatocellular carcinoma -- m6A -- prognosis -- TCGA; Systems biology -- Periodicals; Cell physiology -- Periodicals; Biological systems -- Mathematical models -- Periodicals; Genetics -- Mathematical models -- Periodicals; Computational biology -- Periodicals; 573
• DOI: 10.1049/syb2.12036
• Languages: English
• ISSNs: 1751-8849

Abstract

Abstract: Liver hepatocellular carcinoma (LIHC) comprises most cases of liver cancer with a poor prognosis. N 6 ‐methyladenosine (m6A) plays important biological functions in cancers. Thus, the present research was aimed to determine biomarkers of m6A regulators that could effectively predict the prognosis of LIHC patients. Based on the data collected from the Cancer Genome Atlas (TCGA) database, the correlation between the mRNA expression levels and copy number variation (CNV) patterns were determined. Higher mRNA expression resulted from the increasing number of 9 genes. Using the univariate Cox regression analysis, 11 m6A regulators that had close correlations with the LIHC prognosis were identified. In addition, under the support of the multivariate Cox regression models and the least absolute shrinkage and selection operator, a 4‐gene (YTHDF2, IGF2BP3, KIAA1429, and ALKBH5) signature of m6A regulators was constructed. This signature was expected to present a prognostic value in LIHC (log‐rank test p value < 0.0001). The GSE76427 ( n = 94) and ICGC‐LIRI‐JP ( n = 212) datasets were used to validate the prognostic signature, suggesting strong power to predict patients' prognosis for LIHC. To sum up, genetic alterations in m6A regulatory genes were identified as reliable and effective biomarkers for predicting the prognosis of LIHC patients.