TP53 mutations, expression and interaction networks in human cancers.

Xiaosheng Wang,Qingrong Sun

doi:10.18632/oncotarget.13483

Abstract

Although the associations of p53 dysfunction, p53 interaction networks and oncogenesis have been widely explored, a systematic analysis of TP53 mutations and its related interaction networks in various types of human cancers is lacking. Our study explored the associations of TP53 mutations, gene expression, clinical outcomes, and TP53 interaction networks across 33 cancer types using data from The Cancer Genome Atlas (TCGA). We show that TP53 is the most frequently mutated gene in a number of cancers, and its mutations appear to be early events in cancer initiation. We identified genes potentially repressed by p53, and genes whose expression correlates significantly with TP53 expression. These gene products may be especially important nodes in p53 interaction networks in human cancers. This study shows that while TP53-truncating mutations often result in decreased TP53 expression, other non-truncating TP53 mutations result in increased TP53 expression in some cancers. Survival analyses in a number of cancers show that patients with TP53 mutations are more likely to have worse prognoses than TP53-wildtype patients, and that elevated TP53 expression often leads to poor clinical outcomes. We identified a set of candidate synthetic lethal (SL) genes for TP53, and validated some of these SL interactions using data from the Cancer Cell Line Project. These predicted SL genes are promising candidates for experimental validation and the development of personalized therapeutics for patients with TP53-mutated cancers.

Highlights

TP53 mutations and dysfunction occur in more than half of all human cancer cases [1], and are independent markers of poor prognoses in some cancers [2]
Our study explored the associations of TP53 mutations, gene expression, clinical outcomes, and TP53 interaction networks across 33 cancer types using data from The Cancer Genome Atlas (TCGA)
This study shows that while TP53-truncating mutations often result in decreased TP53 expression, other non-truncating TP53 mutations result in increased TP53 expression in some cancers

Summary

INTRODUCTION

TP53 mutations and dysfunction occur in more than half of all human cancer cases [1], and are independent markers of poor prognoses in some cancers [2]. The study of the p53 pathway and its interaction networks is a promising source of insight for discovering therapeutic targets for TP53-mutated cancers [4]. There have been a number of studies of genomic alterations across cancer types based on TCGA data [6,7,8]. Few of them have focused on systematically exploring genomic alterations of TP53 and its related interaction networks across a number of different cancer types. In this study we explored genomic alterations of TP53 and its interaction networks by analyzing TCGA data across 33 human cancer types. We analyzed TP53 mutation and gene expression data to identify potential nodes in TP53 interaction networks, and performed survival analyses based on TP53 mutations and expression profiles across the 33 cancer types, respectively. We identified potential SL genes for TP53 to find molecular targets for personalized therapy of TP53-mutated cancer patients

RESULTS

DISCUSSION

MATERIALS AND METHODS

CONFLICTS OF INTEREST