Identification of Novel Characteristics in TP53-Mutant Hepatocellular Carcinoma Using Bioinformatics

• Published in: Frontiers in genetics Vol. 13; p. 874805
• Main Authors: Yang, Yang, Qu, Yajuan, Li, Zhaopeng, Tan, Zhiyong, Lei, Youming, Bai, Song
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 16-05-2022
• Subjects: bioinformatics; Genetics; hepatocellular carcinoma; immune infiltration; prognostic model; TP53 mutation; immune infiltration; prognostic model; TP53 mutation; hepatocellular carcinoma; bioinformatics
• ISSN: 1664-8021; 1664-8021
• DOI: 10.3389/fgene.2022.874805

TP53 mutations are the most frequent mutations in hepatocellular carcinoma (HCC) and affect the occurrence and development of this cancer type. Therefore, it is essential to clarify the function and mechanism of TP53 mutations in HCC.
We performed a sequence of bioinformatic analyses to elucidate the characteristics of TP53 mutations in HCC. We downloaded the data of hepatocellular carcinoma from The Cancer Genome Atlas database and used different R packages for serial analyses, including gene mutation analysis, copy number variation analysis, analysis of the tumor mutational burden and microsatellite instability, differential gene expression analysis, and functional enrichment analysis of TP53 mutations, and performed gene set enrichment analysis. We established a protein-protein interaction network using the STRING online database and used the Cytoscape software for network visualization, and hub gene screening. In addition, we performed anticancer drug sensitivity analysis using data from the Genomics of Drug Sensitivity in Cancer. Immune infiltration and prognosis analyses were also performed.
Missense mutations accounted for a great proportion of HCC mutations, the frequency of single nucleotide polymorphisms was high, and C > T was the most common form of single nucleotide variations. TP53 had a mutation rate of 30% and was the most commonly mutated gene in HCC. In the TP53 mutant group, the tumor mutational burden (
< 0.001), drug sensitivity (
< 0.05), ESTIMATE score (
= 0.038), and stromal score (
< 0.001) dramatically decreased. The Cytoscape software screened ten hub genes, including CT45A1, XAGE1B, CT55, GAGE2A, PASD1, MAGEA4, CTAG2, MAGEA10, MAGEC1, and SAGE1. The prognostic model showed a poor prognosis in the TP53 mutation group compared with that in the wild-type group (overall survival,
= 0.023). Univariate and multivariate cox regression analyses revealed that TP53 mutation was an independent risk factor for the prognosis of HCC patients (
<0.05). The constructed prognostic model had a favorable forecast value for the prognosis of HCC patients at 1 and 3 years (1-year AUC = 0.752, 3-years AUC = 0.702).
This study further deepened our understanding of TP53-mutated HCC, provided new insights into a precise individualized therapy for HCC, and has particular significance for prognosis prediction.