The molecular basis of breast cancer pathological phenotypes

Yujing J. Heng, Susan C. Lester, Gary M.K. Tse, Rachel E. Factor, Kimberly H. Allison, Laura C. Collins, Yunn Yi Chen, Kristin C. Jensen, Nicole B. Johnson, Jong Cheol Jeong, Rahi Punjabi, Sandra J. Shin, Kamaljeet Singh, Gregor Krings, David A. Eberhard, Puay Hoon Tan, Konstanty Korski, Frederic M. Waldman, David A. Gutman, Melinda SandersJorge S. Reis-Filho, Sydney R. Flanagan, Deena M.A. Gendoo, Gregory M. Chen, Benjamin Haibe-Kains, Giovanni Ciriello, Katherine A. Hoadley, Charles M. Perou, Andrew H. Beck

Research output: Contribution to journalArticlepeer-review

86 Scopus citations


The histopathological evaluation of morphological features in breast tumours provides prognostic information to guide therapy. Adjunct molecular analyses provide further diagnostic, prognostic and predictive information. However, there is limited knowledge of the molecular basis of morphological phenotypes in invasive breast cancer. This study integrated genomic, transcriptomic and protein data to provide a comprehensive molecular profiling of morphological features in breast cancer. Fifteen pathologists assessed 850 invasive breast cancer cases from The Cancer Genome Atlas (TCGA). Morphological features were significantly associated with genomic alteration, DNA methylation subtype, PAM50 and microRNA subtypes, proliferation scores, gene expression and/or reverse-phase protein assay subtype. Marked nuclear pleomorphism, necrosis, inflammation and a high mitotic count were associated with the basal-like subtype, and had a similar molecular basis. Omics-based signatures were constructed to predict morphological features. The association of morphology transcriptome signatures with overall survival in oestrogen receptor (ER)-positive and ER-negative breast cancer was first assessed by use of the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset; signatures that remained prognostic in the METABRIC multivariate analysis were further evaluated in five additional datasets. The transcriptomic signature of poorly differentiated epithelial tubules was prognostic in ER-positive breast cancer. No signature was prognostic in ER-negative breast cancer. This study provided new insights into the molecular basis of breast cancer morphological phenotypes. The integration of morphological with molecular data has the potential to refine breast cancer classification, predict response to therapy, enhance our understanding of breast cancer biology, and improve clinical management. This work is publicly accessible at

Original languageEnglish
Pages (from-to)375-391
Number of pages17
JournalJournal of Pathology
Issue number3
StatePublished - Feb 1 2017

Bibliographical note

Funding Information:
The data used in this study were in whole or in part based on the data generated by the TCGA Research Network: Funding for this project was provided by the Klarman Family Foundation (AHB), the National Cancer Institute of the National Institutes of Health (SPORE grant P50CA168504; AHB), and the National Library of Medicine of the National Institutes of Health Career Development Award (Number K22LM011931; AHB).

Publisher Copyright:
Copyright © 2016 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.


  • PAM50
  • TCGA
  • bioinformatics
  • epithelial tubule formation
  • genomics
  • histological grade
  • mRNA

ASJC Scopus subject areas

  • Pathology and Forensic Medicine


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