American Association for Cancer Research, Cancer Epidemiology, Biomarkers & Prevention, 5(23), p. 714-724, 2014
DOI: 10.1158/1055-9965.epi-13-1023
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Abstract Background: Data are lacking to describe gene expression–based breast cancer intrinsic subtype patterns for population-based patient groups. Methods: We studied a diverse cohort of women with breast cancer from the Life After Cancer Epidemiology and Pathways studies. RNA was extracted from 1 mm punches from fixed tumor tissue. Quantitative reverse-transcriptase PCR was conducted for the 50 genes that comprise the PAM50 intrinsic subtype classifier. Results: In a subcohort of 1,319 women, the overall subtype distribution based on PAM50 was 53.1% luminal A, 20.5% luminal B, 13.0% HER2-enriched, 9.8% basal-like, and 3.6% normal-like. Among low-risk endocrine-positive tumors (i.e., estrogen and progesterone receptor positive by immunohistochemistry, HER2 negative, and low histologic grade), only 76.5% were categorized as luminal A by PAM50. Continuous-scale luminal A, luminal B, HER2-enriched, and normal-like scores from PAM50 were mutually positively correlated. Basal-like score was inversely correlated with other subtypes. The proportion with non-luminal A subtype decreased with older age at diagnosis, PTrend < 0.0001. Compared with non-Hispanic Whites, African American women were more likely to have basal-like tumors, age-adjusted OR = 4.4 [95% confidence intervals (CI), 2.3–8.4], whereas Asian and Pacific Islander women had reduced odds of basal-like subtype, OR = 0.5 (95% CI, 0.3–0.9). Conclusions: Our data indicate that over 50% of breast cancers treated in the community have luminal A subtype. Gene expression–based classification shifted some tumors categorized as low risk by surrogate clinicopathologic criteria to higher-risk subtypes. Impact: Subtyping in a population-based cohort revealed distinct profiles by age and race. Cancer Epidemiol Biomarkers Prev; 23(5); 714–24. ©2014 AACR.