The molecular basis of breast cancer pathological phenotypes

Abstract

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.

Keywords: PAM50; TCGA; bioinformatics; epithelial tubule formation; genomics; histological grade; mRNA.

Figure 1

Heatmap and unsupervised hierarchical clustering of the 38 significant genomic alterations and 11 morphological features based on the degree and direction of the associations. Inflammation and necrosis, marked nuclear pleomorphism and medium/high mitotic counts are clustered together, as they share many common genomic alterations.

Figure 2

Heatmap summarizing the FDRs of 485 significant pathways and unsupervised hierarchical clustering of morphological features. Features are clustered into two groups characterized mainly by proliferation and inflammation. Detailed pathways are presented in supplementary material, Figure S3. The proliferation cluster had increased cell proliferation and metabolism, and decreased inflammation and membrane receptor signalling. The inflammation cluster comprised largely immune-related signatures.

Figure 3

The prognostic significance of the transcriptomic signature for poorly differentiated epithelial tubules in ER-positive women was further validated in a meta-analysis across five cohorts. *The endpoint for GSE25066 is distant relapse-free survival; the endpoints for all other datasets are overall survival. The summary hazard ratio estimate is a weighted average. Weights are the reciprocal of the estimated variance (square of standard error for the analysis). CI, confidence interval.

Figure 4

(A) There were 17 overlapping genes between the transcriptomic signatures for medium/high mitotic count and marked nuclear pleomorphism, whereas genes predictive of poorly differentiated epithelial tubules were distinct. (B) Most of the genes in the transcriptomic signature for high histological grade were common to the signatures for medium/high mitotic count and marked nuclear pleomorphism, but were distinct from of poorly differentiated epithelial tubules.