The molecular basis of breast cancer pathological phenotypes.

Détails

ID Serval
serval:BIB_F7EC506788FE
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
The molecular basis of breast cancer pathological phenotypes.
Périodique
The Journal of pathology
Auteur(s)
Heng Y.J., Lester S.C., Tse G.M., Factor R.E., Allison K.H., Collins L.C., Chen Y.Y., Jensen K.C., Johnson N.B., Jeong J.C., Punjabi R., Shin S.J., Singh K., Krings G., Eberhard D.A., Tan P.H., Korski K., Waldman F.M., Gutman D.A., Sanders M., Reis-Filho J.S., Flanagan S.R., Gendoo D.M., Chen G.M., Haibe-Kains B., Ciriello G., Hoadley K.A., Perou C.M., Beck A.H.
ISSN
1096-9896 (Electronic)
ISSN-L
0022-3417
Statut éditorial
Publié
Date de publication
02/2017
Peer-reviewed
Oui
Volume
241
Numéro
3
Pages
375-391
Langue
anglais
Notes
Publication types: Journal Article
Publication Status: ppublish
Résumé
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 www.dx.ai/tcga_breast. Copyright © 2016 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Mots-clé
Biomarkers, Tumor/genetics, Breast Neoplasms/metabolism, Breast Neoplasms/pathology, Databases, Genetic, Female, Gene Expression Profiling, Genomics, Humans, Neoplasm Invasiveness, Phenotype, Receptors, Estrogen/metabolism
Pubmed
Création de la notice
01/12/2016 13:15
Dernière modification de la notice
20/08/2019 17:24
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