Abstract

Mutations in the TP53 gene are very common in human cancers, and are associated with poor clinical outcome. Transgenic mouse models lacking the Trp53 gene or that express mutant Trp53 transgenes produce tumours with malignant features in many organs. We previously showed the transcriptome of a p53-deficient mouse skin carcinoma model to be similar to those of human cancers with TP53 mutations and associated with poor clinical outcomes. This report shows that much of the 682-gene signature of this murine skin carcinoma transcriptome is also present in breast and lung cancer mouse models in which p53 is inhibited. Further, we report validated gene-expression-based tests for predicting the clinical outcome of human breast and lung adenocarcinoma. It was found that human patients with cancer could be stratified based on the similarity of their transcriptome with the mouse skin carcinoma 682-gene signature. The results also provide new targets for the treatment of p53-defective tumours.

Highlights

  • Mutations in the TP53 tumour suppressor gene are very common in human cancers, and in most cases are associated with a poor clinical outcome

  • Given the significant gene expression (GE) similarities between these mouse skin tumours and human breast carcinoma (BC) and lung adenocarcinoma (LAd) with a p53 mutation, in the present work the 682-gene signature was sought in genetically engineered mouse models (GEMMs) of BC and LAd showing p53 inhibition

  • Significant similarities were seen with the 682-gene signature for a LAd model in which p53 expression is repressed in the presence of an oncogenic KrasG12D allele (KrasLA2/+;Trp53LSL/LSL;Rosa26CreERT2 model) [18]

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Summary

Introduction

Mutations in the TP53 tumour suppressor gene are very common in human cancers, and in most cases are associated with a poor clinical outcome. Great efforts have been made to find specific therapies for TP53-mutant cancers [1], none are currently used in the clinical setting The lack of such therapies may be explained by the wide diversity of p53-related genomic alterations (point or truncating mutations, oncogenic or dominantnegative mutations, loss of heterozygosity, etc.) and by the presence of additional alterations in oncogenic signalling pathways [2]. Such mutations are predictors of resistance to Nutlin3a [3], an inhibitor of the MDM2 E3 ligase that negatively regulates p53 protein levels. An added value of p53-based biomarkers would be their potential use in predicting the response to cancer therapies, allowing for the personalised treatment of patients

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