Transposon insertional mutagenesis in mice identifies human breast cancer susceptibility genes and signatures for stratification

Liming Chen, Piroon Jenjaroenpun, Andrea Mun Ching Pillai, Anna V. Ivshina, Zhim Siong Ow, Motakis Efthimios, Tang Zhiqun, Tuan Zea Tan, Song Choon Lee, Keith Rogers, Jerrold M. Ward, Seiichi Mori, David J. Adams, Nancy A. Jenkins, Neal G. Copeland, Kenneth Hon Kim Ban, Vladimir A. Kuznetsov, Jean Paul Thiery

Research output: Contribution to journalArticle

17 Scopus citations

Abstract

Robust prognostic gene signatures and therapeutic targets are difficult to derive from expression profiling because of the significant heterogeneity within breast cancer (BC) subtypes. Here, we performed forward genetic screening in mice using Sleeping Beauty transposon mutagenesis to identify candidate BC driver genes in an unbiased manner, using a stabilized N-Terminal truncated β-catenin gene as a sensitizer. We identified 134 mouse susceptibility genes from 129 common insertion sites within 34 mammary tumors. Of these, 126 genes were orthologous to protein-coding genes in the human genome (hereafter, human BC susceptibility genes, hBCSGs), 70% of which are previously reported cancer-Associated genes, and -16% are known BC suppressor genes. Network analysis revealed a gene hub consisting of E1A binding protein P300 (EP300), CD44 molecule (CD44), neurofibromin (NF1) and phosphatase and tensin homolog (PTEN), which are linked to a significant number of mutated hBCSGs. From our survival prediction analysis of the expression of human BC genes in 2,333 BC cases, we isolated a sixgene-pair classifier that stratifies BC patients with high confidence into prognostically distinct low-, moderate-, and high-risk subgroups. Furthermore, we proposed prognostic classifiers identifying three basal and three claudin-low tumor subgroups. Intriguingly, our hBCSGs are mostly unrelated to cell cycle/mitosis genes and are distinct from the prognostic signatures currently used for stratifying BC patients. Our findings illustrate the strength and validity of integrating functional mutagenesis screens in mice with human cancer transcriptomic data to identify highly prognostic BC subtyping biomarkers.

Original languageEnglish (US)
Pages (from-to)E2215-E2224
JournalProceedings of the National Academy of Sciences of the United States of America
Volume114
Issue number11
DOIs
StatePublished - Mar 14 2017

Keywords

  • Breast cancer
  • Cancer susceptibility
  • Prognostic gene signature
  • Sleeping Beauty
  • Survival prediction analysis

ASJC Scopus subject areas

  • General

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