Bimodal age distribution at diagnosis in breast cancer persists across molecular and genomic classifications.
Breast Cancer Res Treat
; 179(1): 185-195, 2020 Jan.
Article
em En
| MEDLINE
| ID: mdl-31535320
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.Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Neoplasias da Mama
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Biomarcadores Tumorais
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Genômica
Tipo de estudo:
Diagnostic_studies
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Prognostic_studies
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Risk_factors_studies
Limite:
Aged
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Female
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Humans
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Middle aged
Idioma:
En
Ano de publicação:
2020
Tipo de documento:
Article