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

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.

Conflict of interest statement

Disclosures of potential conflicts of interest may be found at the end of this article.

©AlphaMed Press.

Figures

Figure 1.

CONSORT diagram of publicly available gene array data sets used to define breast cancer subtypes using the PAM50 model [6]. Abbreviations: BCSS, breast cancer-specific survival; OS, overall survival; RFS, recurrence-free survival.

Figure 2.

PAM50 intrinsic subtypes by age. The sum of the first column is 101% because of rounding.

Figure 3.

PAM50 intrinsic subtypes by immunohistochemical molecular subtypes for all patients. The sums of the third and fourth columns are 101% because of rounding.

Figure 4.

PAM 50 subtypes by age according to HR and HER2 phenotype. (A): HR+/HER2−. (B): HR−/HER2− (“triple-negative”). (C): HR+/HER2+. (D): HR−/HER2+.

Figure 5.

Outcomes according to subtype and age. Recurrence-free survival (RFS) was used as a surrogate for outcome in the non-Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) data sets. Overall survival (OS) and disease-specific survival (DSS) were used as surrogates for outcome in the METABRIC data set (see Fig. 1). Normal-like samples were excluded. (A): RFS by PAM50 for all age cohorts. (B): RFS by PAM50 for 70–93-year age cohort. (C): OS by PAM50 for all age cohorts. (D): OS by PAM50 for 70–93-year age cohort. (E): DSS by PAM50 for all age cohorts. (F): DSS by PAM50 for 70–93-year age cohort.