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Bimodal age distribution at diagnosis in breast cancer persists across molecular and genomic classifications.
Allott, Emma H; 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; Troester, Melissa A.
Afiliação
  • Allott EH; Centre for Cancer Research and Cell Biology, Queen's University Belfast, Belfast, UK. e.allott@qub.ac.uk.
  • Shan Y; Centre for Cancer Research and Cell Biology, Queen's University Belfast, Health Sciences Building, Room 2.12, 97 Lisburn Road, Belfast, BT9 7AE, Northern Ireland, UK. e.allott@qub.ac.uk.
  • Chen M; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Sun X; Departments of Medicine and Human Genetics, University of Chicago, Chicago, IL, USA.
  • Garcia-Recio S; Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Kirk EL; Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Olshan AF; Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Geradts J; Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Earp HS; Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Carey LA; Department of Population Sciences, City of Hope, Duarte, CA, USA.
  • Perou CM; Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Pfeiffer RM; Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Anderson WF; Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Troester MA; Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Biomarcadores Tumorais / Genômica Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Limite: Aged / Female / Humans / Middle aged Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Biomarcadores Tumorais / Genômica Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Limite: Aged / Female / Humans / Middle aged Idioma: En Ano de publicação: 2020 Tipo de documento: Article