Age-specific changes in intrinsic breast cancer subtypes: a focus on older women

Oncologist. 2014 Oct;19(10):1076-83. doi: 10.1634/theoncologist.2014-0184. Epub 2014 Aug 20.

Abstract

Purpose: Breast cancer (BC) is a disease of aging and the number of older BC patients in the U.S. is rising. Immunohistochemical data show that with increasing age, the incidence of hormone receptor-positive tumors increases, whereas the incidence of triple-negative tumors decreases. Few data exist on the frequency of molecular subtypes in older women. Here, we characterize the incidence and outcomes of BC patients by molecular subtypes and age.

Patients and methods: Data from 3,947 patients were pooled from publicly available clinical and gene expression microarray data sets. The PAM50 algorithm was used to classify tumors into five BC intrinsic subtypes: luminal A, luminal B, HER2-enriched, basal-like, and normal-like. The association of age and subtype with recurrence-free survival (RFS), overall survival, and disease-specific survival (DSS) was assessed.

Results: The incidence of luminal (A, B, and A+B) tumors increased with age (p < .01, p < .0001, and p < .0001, respectively), whereas the percentage of basal-like tumors decreased (p < .0001). Among patients 70 years and older, luminal B, HER2-enriched, and basal-like tumors were found at a frequency of 32%, 11%, and 9%, respectively. In older women, luminal subtypes had better outcomes than basal-like and HER2-enriched subtypes. After controlling for subtype, treatment, tumor size, nodal status, and grade, increasing age had no impact on RFS or DSS.

Conclusion: More favorable BC subtypes increase with age, but older patients still have a substantial percentage of high-risk tumor subtypes. After accounting for tumor subtypes, age at diagnosis is not an independent prognostic factor for outcome.

Keywords: Age; Breast cancer; Elderly; Gene microarray.

Publication types

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

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Aged, 80 and over
  • Breast Neoplasms / classification*
  • Breast Neoplasms / diagnosis
  • Breast Neoplasms / therapy
  • Female
  • Gene Expression Profiling / methods
  • Humans
  • Middle Aged
  • Receptor, ErbB-2 / analysis
  • Receptors, Estrogen / analysis
  • Treatment Outcome
  • Triple Negative Breast Neoplasms / classification
  • Triple Negative Breast Neoplasms / diagnosis
  • Triple Negative Breast Neoplasms / therapy
  • Young Adult

Substances

  • Receptors, Estrogen
  • ERBB2 protein, human
  • Receptor, ErbB-2