TITLE:
Identification of Driver Genes in Primary Liver Cancer by Integrating NGS and TCGA Mutation Data
AUTHORS:
Lin Li, Lin Niu, Na Guo, Luyang Cheng, Tengfei Hao, Ying Xu, Xiangling Li, Qian Xu, Lei Liu, Songhe Yang
KEYWORDS:
Primary Liver Cancer, Mutation, Next-Generation Sequencing, TCGA, Driver Genes
JOURNAL NAME:
Open Journal of Gastroenterology,
Vol.12 No.1,
January
14,
2022
ABSTRACT: Background: This study is aimed towards an exploration of
mutant genes in primary liver cancer (PLC) patients by using bioinformatics
and data mining techniques. Methods: Peripheral blood or
paraffin-embedded tissues from 8 patients with PLC were analyzed using a 551
cancer-related gene panel on an Illumina NextSeq500 Sequencer (Illumina). Meanwhile,
the data of 396 PLC cases were downloaded from The Cancer Genome Atlas (TCGA)
database. The common mutated genes were obtained after integrating the mutation
information of the above two cohorts, followed by functional enrichment and
protein-protein interaction (PPI) analyses. Three well-known databases,
including Vogelstein’s list, the Network of Cancer Gene (NCG), and the Catalog
of Somatic Mutations in Cancer (COSMIC) database were used to screen driver
genes. Furthermore, the Chi-square and logistic analysis were performed to
analyze the correlation between the driver genes and clinicopathological
characteristics, and Kaplan-Meier (KM) method and multivariate Cox analysis were conducted to
evaluate the overall survival outcome. Results: In total, 84 mutation
genes were obtained after 8 PLC patients undergoing gene mutation detection
with next-generation sequencing (NGS). The top 100 most mutate gene data from
PLC patients in TCGA database were downloaded. After integrating the above two
cohorts, 17 common mutated genes were identified. Next, 11 driver genes were
screened out by analyzing the intersection of the 17 mutation genes and the
genes in the three well-known databases.Among them, RB1,
TP53, and KRAS gene mutations were connected with clinicopathological
characteristics, while all the 11 gene mutations had no relationship with
overall survival. Conclusion: This study investigated the mutant genes
with significant clinical implications in PLC patients, which may improve the
knowledge of gene mutations in PLC molecular pathogenesis.