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

Publication ,  Journal Article
Allott, EH; Shan, Y; Chen, M; Sun, X; Garcia-Recio, S; Kirk, EL; Olshan, AF; Geradts, J; Earp, HS; Carey, LA; Perou, CM; Pfeiffer, RM ...
Published in: Breast Cancer Res Treat
January 2020

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.

Duke Scholars

Published In

Breast Cancer Res Treat

DOI

EISSN

1573-7217

Publication Date

January 2020

Volume

179

Issue

1

Start / End Page

185 / 195

Location

Netherlands

Related Subject Headings

  • Sequence Analysis, RNA
  • Oncology & Carcinogenesis
  • Middle Aged
  • Immunohistochemistry
  • Humans
  • Genomics
  • Gene Expression Regulation, Neoplastic
  • Gene Expression Profiling
  • Female
  • Breast Neoplasms
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Allott, E. H., Shan, Y., Chen, M., Sun, X., Garcia-Recio, S., Kirk, E. L., … Troester, M. A. (2020). Bimodal age distribution at diagnosis in breast cancer persists across molecular and genomic classifications. Breast Cancer Res Treat, 179(1), 185–195. https://doi.org/10.1007/s10549-019-05442-2
Allott, Emma H., Yue Shan, Mengjie Chen, Xuezheng Sun, Susana Garcia-Recio, Erin L. Kirk, Andrew F. Olshan, et al. “Bimodal age distribution at diagnosis in breast cancer persists across molecular and genomic classifications.Breast Cancer Res Treat 179, no. 1 (January 2020): 185–95. https://doi.org/10.1007/s10549-019-05442-2.
Allott EH, Shan Y, Chen M, Sun X, Garcia-Recio S, Kirk EL, et al. Bimodal age distribution at diagnosis in breast cancer persists across molecular and genomic classifications. Breast Cancer Res Treat. 2020 Jan;179(1):185–95.
Allott, Emma H., et al. “Bimodal age distribution at diagnosis in breast cancer persists across molecular and genomic classifications.Breast Cancer Res Treat, vol. 179, no. 1, Jan. 2020, pp. 185–95. Pubmed, doi:10.1007/s10549-019-05442-2.
Allott EH, Shan Y, Chen M, Sun X, Garcia-Recio S, Kirk EL, Olshan AF, Geradts J, Earp HS, Carey LA, Perou CM, Pfeiffer RM, Anderson WF, Troester MA. Bimodal age distribution at diagnosis in breast cancer persists across molecular and genomic classifications. Breast Cancer Res Treat. 2020 Jan;179(1):185–195.
Journal cover image

Published In

Breast Cancer Res Treat

DOI

EISSN

1573-7217

Publication Date

January 2020

Volume

179

Issue

1

Start / End Page

185 / 195

Location

Netherlands

Related Subject Headings

  • Sequence Analysis, RNA
  • Oncology & Carcinogenesis
  • Middle Aged
  • Immunohistochemistry
  • Humans
  • Genomics
  • Gene Expression Regulation, Neoplastic
  • Gene Expression Profiling
  • Female
  • Breast Neoplasms