Whole-genome analysis informs breast cancer response to aromatase inhibition

Abstract

To correlate the variable clinical features of oestrogen-receptor-positive breast cancer with somatic alterations, we studied pretreatment tumour biopsies accrued from patients in two studies of neoadjuvant aromatase inhibitor therapy by massively parallel sequencing and analysis. Eighteen significantly mutated genes were identified, including five genes (RUNX1, CBFB, MYH9, MLL3 and SF3B1) previously linked to haematopoietic disorders. Mutant MAP3K1 was associated with luminal A status, low-grade histology and low proliferation rates, whereas mutant TP53 was associated with the opposite pattern. Moreover, mutant GATA3 correlated with suppression of proliferation upon aromatase inhibitor treatment. Pathway analysis demonstrated that mutations in MAP2K4, a MAP3K1 substrate, produced similar perturbations as MAP3K1 loss. Distinct phenotypes in oestrogen-receptor-positive breast cancer are associated with specific patterns of somatic mutations that map into cellular pathways linked to tumour biology, but most recurrent mutations are relatively infrequent. Prospective clinical trials based on these findings will require comprehensive genome sequencing.

Figure 1. Genome-wide somatic mutations

Circos plots indicate validated somatic mutations comprising tier 1 point mutations and indels, genome-wide copy number alterations, and structural rearrangements in six representative genomes. Three on-treatment Ki67 lesser than or at 10% (top panel: BRC15, BRC17, and BRC22) and three on-treatment Ki67 greater than 10% (bottom panel: BRC44, BRC47, and BRC50) cases are shown. Significantly mutated genes are highlighted in red. No purity-based copy number corrections were used for plotting copy number.

Figure 2. MAP3K1 and MAP2K4 mutations observed in 317 samples

Somatic status of all mutations was obtained by Sanger sequencing of PCR products or Illumina sequencing of targeted capture products. The locations of conserved protein domains are highlighted. Each nonsynonymous substitution, splice site mutation, or indel is designated with a circle at the representative protein position with color to indicate translation effects of the mutation.

Figure 3. Structural variants in significantly mutated or frequently deleted genes

One MAP3K1 deletion in BRC49 and one MAP2K4 deletion in BRC47, and one ELP3-NRG1 fusion in BRC49 identified using Illumina paired-end reads from whole genome sequence data. Arcs represent multiple breakpoint-spanning read pairs with sequence coverage depth plotted in black across the region.

Figure 4. Key cancer pathway components altered in luminal breast tumours

(a) Only genetic alterations identified in 46 WGS cases were shown. Alterations were discovered in key genes in the TP53/RB, MAPK, PI3K/AKT/mTOR pathways. Genes colored blue and red are predicted to be functionally inactivated and activated, respectively, through focused mutations including point mutations and small indels (M), copy number deletions (C), or other structural changes (S) that affect the gene. The inter-connectedness of this network (several pathways) shows that there are many different ways to perturb a pathway. (b) Eight interaction networks from canonical maps are significantly over-represented by mutations in 77 luminal breast tumours (46 WGS and 31 exome cases). In the concentric circle diagram, tumors are arranged as radial spokes and categorized by their mutation status in each network (concentric ring color) and SMG mutation status (black dots). Tumor classification by pathway analysis shows many tumors unaffected by a given SMG often harbor other mutations in the same network. For full annotation, see Supplementary Information and Supplementary Fig. 6.

Figure 5. Pathway signatures reveal connections between mutations and clinical outcomes

PARADIGM-based pathway signatures were derived for tumour feature dichotomies including mutation driven gene signatures (mutant vs. non-mutant), histopathology type (lobular vs. ductal), preoperative endocrine prognostic index (PEPI) score (PEPI=0 favorable vs. PEPI>0 unfavorable), PAM50 Luminal A subtype (LumA vs. LumB) and the reverse (LumB vs. LumA), histopathology grade (grades II&III vs. I), baseline Ki67 levels (>=14% vs. <14%), and end-of-treatment Ki67 levels (>=10% vs. <10%) and overall PEPI score (higher than mean unfavorable vs. lower than mean favorable). Pearson correlations were computed between all pair-wise signatures; positive correlations, red; negative correlations, blue; column features ordered identically as rows. Correlation analysis on the 77 samples in the discovery set is shown.