Growing evidence supports the concept of breast cancer as a group of diseases with distinct etiologies. In a recent issue of Breast Cancer Research, Kwan and colleagues 1 report a pooled analysis of molecular subtypes in two prospective breast tumor datasets. Their analysis of 2,544 invasive breast cancers is a well-powered, case-only analysis of associations between established breast cancer risk factors and molecular subtypes of breast cancer 23. Together with similar findings from other studies, the results suggest racial disparities in the etiology of breast cancer subtypes and indicate that prevention strategies may be possible for aggressive breast cancers.

Evidence suggesting that distinct molecular subtypes of breast cancer have different etiologies has developed primarily from case-control studies. Case-control studies compare risk factor distributions among breast cancer cases to distributions among controls. In case-control analyses, breast cancer cases can be taken as a whole or can be stratified by molecular subtype 4567, but as the cases are divided into subgroups, the power to discover associations can be reduced. To address this challenge, a few studies have used an alternative study design, the case-only design, to study breast cancer subtypes 148910. Instead of defining controls as the referent group, case-only analyses compare risk factor distributions or pathology characteristics across subtypes (for example, comparing HER2-enriched, basal-like, or luminal B tumors to luminal A tumors). In case-only analyses, risk factor distributions that differ significantly across subgroups of cases are interpreted as etiologic heterogeneity. Case-only studies have a history of use for investigating gene-environment interactions and can be an efficient and powerful approach 1112. Thus, by pooled analysis of two studies and an efficient case-only design, Kwan and colleagues 1 have replicated previous significant findings and report novel interactions in the etiology of breast cancer subtypes.

Several previously reported interactions between risk factors and breast cancer subtypes are confirmed in the report by Kwan and colleagues 1. Their work supports interactions between parity and breastfeeding in triple negative breast cancer (TNBC) and/or basal-like breast cancer (BBC) 45. Collectively, the data suggest that breastfeeding may be particularly important for preventing aggressive subtypes of breast cancer. The analyses by Kwan and colleagues 1 also support previously reported links between TNBC/BBC and obesity 46. However, there have been divergent results for different obesity measures within and across studies and in interaction with other exposures 46910. While associations between obesity and molecular subtypes remain uncertain, there is agreement across several studies regarding patterns of breast cancer incidence by age and race.

Many of the studies linking race and aggressive breast cancer subtypes have included a substantial percentage of African Americans, allowing strong inference about subtype and racial disparities. The pooled analysis of the Life After Cancer Epidemiology (LACE) and Pathways studies included just 6% African-American cases 1, but a significant association was still observed between TNBC and race. In fact, the association between African American race and TNBC was among the strongest associations observed in their study. While evidence for a shift toward more aggressive subtypes in African-American women is consistent across several studies and has been observed in Surveillance, Epidemiology, and End Results (SEER) data 13, uncertainty remains about the genetic and environmental factors that contribute to the associations between race and breast cancer subtype. Complex relationships between biology, socioeconomics, and race exist, and future research in racially diverse populations will be needed to disentangle these factors and address disparities in breast cancer.

In integrating findings across studies, perhaps the greatest challenge is a lack of agreement about molecular definitions for subtypes. TNBCs include not only tumors that are truly BBCs, but also tumors for which there were false negatives for one or more of the three markers (estrogen receptor, progesterone receptor, or HER2). BBCs are measured with specificity by adding positive markers such as cytokeratin 5/6 or epidermal growth factor receptor 14 and future studies may take advantage of a 50-gene quantitative PCR assay for molecular subtypes 15. Nonetheless, specific markers for BBC are not presently available in most studies and the resulting misclassification can be substantial. In the Carolina Breast Cancer Study and the Polish Women's Health Study, only 60% and 66%, respectively, of TNBCs were BBCs when specific, positive markers were included in the definition of that subtype. Distinguishing true BBC from TNBC has had important implications for clinical prognosis 14, and while it has been argued that these distinctions may be more important in clinical than etiologic research 6, misclassification can be an important bias and deserves careful consideration. Kwan and colleagues 1 have emphasized the importance of these molecular definitions and propose future research on their dataset using specific BBC markers.

Research on the epidemiology of molecular subtypes is challenging. Ideal studies include biomarker data that allow classification of breast cancers into homogeneous subgroups, have large and racially diverse samples, and utilize efficient analytic strategies. This analysis by Kwan and colleagues 1 has contributed important data confirming that different breast cancer subtypes have unique profiles by reproductive factors, age, and race. This study and others like it hold the promise of defining novel prevention strategies for breast cancer subtypes that contribute to racial disparities.

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