The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups.

The elucidation of breast cancer subgroups and their molecular drivers requires integrated views of the genome and transcriptome from representative numbers of patients. We present an integrated analysis of copy number and gene expression in a discovery and validation set of 997 and 995 primary breast tumours, respectively, with long-term clinical follow-up. Inherited variants (copy number variants and single nucleotide polymorphisms) and acquired somatic copy number aberrations (CNAs) were associated with expression in ~40% of genes, with the landscape dominated by cis- and trans-acting CNAs. By delineating expression outlier genes driven in cis by CNAs, we identified putative cancer genes, including deletions in PPP2R2A, MTAP and MAP2K4. Unsupervised analysis of paired DNA–RNA profiles revealed novel subgroups with distinct clinical outcomes, which reproduced in the validation cohort. These include a high-risk, oestrogen-receptor-positive 11q13/14 cis-acting subgroup and a favourable prognosis subgroup devoid of CNAs. Trans-acting aberration hotspots were found to modulate subgroup-specific gene networks, including a TCR deletion-mediated adaptive immune response in the ‘CNA-devoid’ subgroup and a basal-specific chromosome 5 deletion-associated mitotic network. Our results provide a novel molecular stratification of the breast cancer population, derived from the impact of somatic CNAs on the transcriptome

A clinically applicable molecular-based classification for endometrial cancers

BackgroundClassification of endometrial carcinomas (ECs) by morphologic features is inconsistent, and yields limited prognostic and predictive information. A new system for classification based on the molecular categories identified in The Cancer Genome Atlas is proposed.MethodsGenomic data from the Cancer Genome Atlas (TCGA) support classification of endometrial carcinomas into four prognostically significant subgroups; we used the TCGA data set to develop surrogate assays that could replicate the TCGA classification, but without the need for the labor-intensive and cost-prohibitive genomic methodology. Combinations of the most relevant assays were carried forward and tested on a new independent cohort of 152 endometrial carcinoma cases, and molecular vs clinical risk group stratification was compared.ResultsReplication of TCGA survival curves was achieved with statistical significance using multiple different molecular classification models (16 total tested). Internal validation supported carrying forward a classifier based on the following components: mismatch repair protein immunohistochemistry, POLE mutational analysis and p53 immunohistochemistry as a surrogate for 'copy-number' status. The proposed molecular classifier was associated with clinical outcomes, as was stage, grade, lymph-vascular space invasion, nodal involvement and adjuvant treatment. In multivariable analysis both molecular classification and clinical risk groups were associated with outcomes, but differed greatly in composition of cases within each category, with half of POLE and mismatch repair loss subgroups residing within the clinically defined 'high-risk' group. Combining the molecular classifier with clinicopathologic features or risk groups provided the highest C-index for discrimination of outcome survival curves.ConclusionsMolecular classification of ECs can be achieved using clinically applicable methods on formalin-fixed paraffin-embedded samples, and provides independent prognostic information beyond established risk factors. This pragmatic molecular classification tool has potential to be used routinely in guiding treatment for individuals with endometrial carcinoma and in stratifying cases in future clinical trials

Interpretation of somatic POLE mutations in endometrial carcinoma

Pathogenic somatic missense mutations within the DNA polymerase epsilon (POLE) exonuclease domain define the important subtype of ultramutated tumours (‘POLE‐ultramutated’) within the novel molecular classification of endometrial carcinoma (EC). However, clinical implementation of this classifier requires systematic evaluation of the pathogenicity of POLE mutations. To address this, we examined base changes, tumour mutational burden (TMB), DNA microsatellite instability (MSI) status, POLE variant frequency, and the results from six in silico tools on 82 ECs with whole‐exome sequencing from The Cancer Genome Atlas (TCGA). Of these, 41 had one of five known pathogenic POLE exonuclease domain mutations (EDM) and showed characteristic genomic alterations: C>A substitution > 20%, T>G substitutions > 4%, C>G substitutions  100 mut/Mb. A scoring system to assess these alterations (POLE‐score) was developed; based on their scores, 7/18 (39%) additional tumours with EDM were classified as POLE‐ultramutated ECs, and the six POLE mutations present in these tumours were considered pathogenic. Only 1/23 (4%) tumours with non‐EDM showed these genomic alterations, indicating that a large majority of mutations outside the exonuclease domain are not pathogenic. The infrequent combination of MSI‐H with POLE EDM led us to investigate the clinical significance of this association. Tumours with pathogenic POLE EDM co‐existent with MSI‐H showed genomic alterations characteristic of POLE‐ultramutated ECs. In a pooled analysis of 3361 ECs, 13 ECs with DNA mismatch repair deficiency (MMRd)/MSI‐H and a pathogenic POLE EDM had a 5‐year recurrence‐free survival (RFS) of 92.3%, comparable to previously reported POLE‐ultramutated ECs. Additionally, 14 cases with non‐pathogenic POLE EDM and MMRd/MSI‐H had a 5‐year RFS of 76.2%, similar to MMRd/MSI‐H, POLE wild‐type ECs, suggesting that these should be categorised as MMRd, rather than POLE‐ultramutated ECs for prognostication. This work provides guidance on classification of ECs with POLE mutations, facilitating implementation of POLE testing in routine clinical care

A clinically applicable molecular-based classification for endometrial cancers

BACKGROUND: Classification of endometrial carcinomas (ECs) by morphologic features is inconsistent, and yields limited prognostic and predictive information. A new system for classification based on the molecular categories identified in The Cancer Genome Atlas is proposed. METHODS: Genomic data from the Cancer Genome Atlas (TCGA) support classification of endometrial carcinomas into four prognostically significant subgroups; we used the TCGA data set to develop surrogate assays that could replicate the TCGA classification, but without the need for the labor-intensive and cost-prohibitive genomic methodology. Combinations of the most relevant assays were carried forward and tested on a new independent cohort of 152 endometrial carcinoma cases, and molecular vs clinical risk group stratification was compared. RESULTS: Replication of TCGA survival curves was achieved with statistical significance using multiple different molecular classification models (16 total tested). Internal validation supported carrying forward a classifier based on the following components: mismatch repair protein immunohistochemistry, POLE mutational analysis and p53 immunohistochemistry as a surrogate for ‘copy-number' status. The proposed molecular classifier was associated with clinical outcomes, as was stage, grade, lymph-vascular space invasion, nodal involvement and adjuvant treatment. In multivariable analysis both molecular classification and clinical risk groups were associated with outcomes, but differed greatly in composition of cases within each category, with half of POLE and mismatch repair loss subgroups residing within the clinically defined ‘high-risk' group. Combining the molecular classifier with clinicopathologic features or risk groups provided the highest C-index for discrimination of outcome survival curves. CONCLUSIONS: Molecular classification of ECs can be achieved using clinically applicable methods on formalin-fixed paraffin-embedded samples, and provides independent prognostic information beyond established risk factors. This pragmatic molecular classification tool has potential to be used routinely in guiding treatment for individuals with endometrial carcinoma and in stratifying cases in future clinical trials