1. Bimodal age distribution at diagnosis in breast cancer persists across molecular and genomic classifications
- Author
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Allott, Emma, Shan, Yue, Chen, Mengjie, Sun, Xuezheng, Garcia-Recio, Susana, Kirk, Erin L, Olshan, Andrew F, Geradts, Joseph, Earp, H Shelton, Carey, Lisa A, Perou, Charles M, Pfeiffer, Ruth M, Anderson, William F., and Troester, Melissa A.
- Subjects
Oncology ,Cancer Research ,medicine.medical_specialty ,Race ,Etiology ,Epidemiology ,Estrogen receptor ,Subtype ,Breast Neoplasms ,Biology ,Bimodality ,03 medical and health sciences ,0302 clinical medicine ,Breast cancer ,Age Distribution ,SDG 3 - Good Health and Well-being ,Internal medicine ,medicine ,Biomarkers, Tumor ,Humans ,PAM50 ,Age of Onset ,030304 developmental biology ,Aged ,Mixture model ,0303 health sciences ,Sequence Analysis, RNA ,Gene Expression Profiling ,Luminal a ,Genomics ,Middle Aged ,medicine.disease ,Immunohistochemistry ,3. Good health ,Cancer registry ,Gene Expression Regulation, Neoplastic ,030220 oncology & carcinogenesis ,Age distribution ,Female ,Akaike information criterion - Abstract
Purpose Female breast cancer demonstrates bimodal age frequency distribution patterns at diagnosis, interpretable as two main etiologic subtypes or groupings of tumors with shared risk factors. While RNA-based methods including PAM50 have identified well-established clinical subtypes, age distribution patterns at diagnosis as a proxy for etiologic subtype are not established for molecular and genomic tumor classifications. Methods We evaluated smoothed age frequency distributions at diagnosis for Carolina Breast Cancer Study cases within immunohistochemistry-based and RNA-based expression categories. Akaike information criterion (AIC) values compared the fit of single density versus two-component mixture models. Two-component mixture models estimated the proportion of early-onset and late-onset categories by immunohistochemistry-based ER (n = 2860), and by RNA-based ESR1 and PAM50 subtype (n = 1965). PAM50 findings were validated using pooled publicly available data (n = 8103). Results Breast cancers were best characterized by bimodal age distribution at diagnosis with incidence peaks near 45 and 65 years, regardless of molecular characteristics. However, proportional composition of early-onset and late-onset age distributions varied by molecular and genomic characteristics. Higher ER-protein and ESR1-RNA categories showed a greater proportion of late age-at-onset. Similarly, PAM50 subtypes showed a shifting age-at-onset distribution, with most pronounced early-onset and late-onset peaks found in Basal-like and Luminal A, respectively. Conclusions Bimodal age distribution at diagnosis was detected in the Carolina Breast Cancer Study, similar to national cancer registry data. Our data support two fundamental age-defined etiologic breast cancer subtypes that persist across molecular and genomic characteristics. Better criteria to distinguish etiologic subtypes could improve understanding of breast cancer etiology and contribute to prevention efforts.
- Published
- 2019