Bimodal age distribution at diagnosis in breast cancer persists across molecular and genomic classifications

Epidemiology Sequence Analysis, RNA Gene Expression Profiling 610 Breast Neoplasms Genomics Middle Aged Immunohistochemistry name=SDG 3 - Good Health and Well-being 3. Good health Gene Expression Regulation, Neoplastic 03 medical and health sciences Age Distribution 0302 clinical medicine Biomarkers, Tumor /dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being Humans Female /dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being; name=SDG 3 - Good Health and Well-being Age of Onset Aged
DOI: 10.1007/s10549-019-05442-2 Publication Date: 2019-09-18T17:05:41Z
ABSTRACT
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, diagnosis a proxy for subtype are not established molecular and genomic tumor classifications.We evaluated smoothed distributions Carolina Breast Cancer Study cases within immunohistochemistry-based expression categories. Akaike information criterion (AIC) values compared the fit single density versus two-component mixture models. Two-component models estimated proportion early-onset late-onset categories by ER (n = 2860), ESR1 1965). findings were validated using pooled publicly available data 8103).Breast cancers best characterized incidence peaks near 45 65 years, regardless characteristics. However, proportional composition varied Higher ER-protein ESR1-RNA showed greater late age-at-onset. Similarly, shifting age-at-onset distribution, most pronounced found in Basal-like Luminal A, respectively.Bimodal was detected Study, similar to national registry data. Our support fundamental age-defined that persist across Better criteria distinguish could improve understanding etiology contribute prevention efforts.
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