The Molecular Landscape of Premenopausal Breast Cancer

Breast Cancer Res. 2015 Aug 7;17:104. doi: 10.1186/s13058-015-0618-8.

Abstract

Introduction: Breast cancer in premenopausal women (preM) is frequently associated with worse prognosis compared to that in postmenopausal women (postM), and there is evidence that preM estrogen receptor-positive (ER+) tumors may respond poorly to endocrine therapy. There is, however, a paucity of studies characterizing molecular alterations in premenopausal tumors, a potential avenue for personalizing therapy for this group of women.

Methods: Using TCGA and METABRIC databases, we analyzed gene expression, copy number, methylation, somatic mutation, and reverse-phase protein array data in breast cancers from >2,500 preM and postM women.

Results: PreM tumors showed unique gene expression compared to postM tumors, however, this difference was limited to ER+ tumors. ER+ preM tumors showed unique DNA methylation, copy number and somatic mutations. Integrative pathway analysis revealed that preM tumors had elevated integrin/laminin and EGFR signaling, with enrichment for upstream TGFβ-regulation. Finally, preM tumors showed three different gene expression clusters with significantly different outcomes.

Conclusion: Together these data suggest that ER+ preM tumors have distinct molecular characteristics compared to ER+ postM tumors, particularly with respect to integrin/laminin and EGFR signaling, which may represent therapeutic targets in this subgroup of breast cancers.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomarkers, Tumor*
  • Breast Neoplasms / epidemiology
  • Breast Neoplasms / genetics*
  • Cluster Analysis
  • Computational Biology
  • DNA Copy Number Variations
  • DNA Methylation
  • Databases, Genetic
  • Female
  • Gene Expression Profiling*
  • Gene Expression Regulation
  • Humans
  • Mutation
  • Outcome Assessment, Health Care
  • Postmenopause
  • Premenopause*
  • Prognosis
  • Proteomics
  • Reproducibility of Results
  • Signal Transduction

Substances

  • Biomarkers, Tumor