Associations between genomic stratification of breast cancer and centrally reviewed tumour pathology in the METABRIC cohort.

The integration of genomic and transcriptomic profiles of 2000 breast tumours from the METABRIC [Molecular Taxonomy of Breast Cancer International Consortium] cohort revealed ten subtypes, termed integrative clusters (IntClust/s), characterised by distinct genomic drivers. Central histopathology (N = 1643) review was undertaken to explore the relationship between these ten molecular subtypes and traditional clinicopathological features. IntClust subtypes were significantly associated with histological type, tumour grade, receptor status, and lymphocytic infiltration (p < 0.0001). Lymph node status and Nottingham Prognostic Index [NPI] categories were also significantly associated with IntClust subtype. IntClust 3 was enriched for tubular and lobular carcinomas, the latter largely accounting for the association with CDH1 mutations in this cluster. Mucinous carcinomas were not present in IntClusts 5 or 10, but did not show an association with any of the remaining IntClusts. In contrast, medullary-like cancers were associated with IntClust 10 (15/26). Hormone receptor-positive tumours were scattered across all IntClusts. IntClust 5 was dominated by HER2 positivity (127/151), including both hormone receptor-positive (60/72) and hormone receptor-negative tumours (67/77). Triple-negative tumours comprised the majority of IntClust 10 (132/159) and around a quarter of IntClust 4 (52/217). Whilst the ten IntClust subtypes of breast cancer show characteristic patterns of association with traditional clinicopathological variables, no IntClust can be adequately identified by these variables alone. Hence, the addition of genomic stratification has the potential to enhance the biological relevance of the current clinical evaluation and facilitate genome-guided therapeutic strategies

Small molecule inhibition of group I p21-activated kinases in breast cancer induces apoptosis and potentiates the activity of microtubule stabilizing agents

IntroductionBreast cancer, the most common cause of cancer-related deaths worldwide among women, is a molecularly and clinically heterogeneous disease. Extensive genetic and epigenetic profiling of breast tumors has recently revealed novel putative driver genes, including p21-activated kinase (PAK)1. PAK1 is a serine/threonine kinase downstream of small GTP-binding proteins, Rac1 and Cdc42, and is an integral component of growth factor signaling networks and cellular functions fundamental to tumorigenesis.MethodsPAK1 dysregulation (copy number gain, mRNA and protein expression) was evaluated in two cohorts of breast cancer tissues (n = 980 and 1,108). A novel small molecule inhibitor, FRAX1036, and RNA interference were used to examine PAK1 loss of function and combination with docetaxel in vitro. Mechanism of action for the therapeutic combination, both cellular and molecular, was assessed via time-lapse microscopy and immunoblotting.ResultsWe demonstrate that focal genomic amplification and overexpression of PAK1 are associated with poor clinical outcome in the luminal subtype of breast cancer (P = 1.29 × 10−4 and P = 0.015, respectively). Given the role for PAK1 in regulating cytoskeletal organization, we hypothesized that combination of PAK1 inhibition with taxane treatment could be combined to further interfere with microtubule dynamics and cell survival. Consistent with this, administration of docetaxel with either a novel small molecule inhibitor of group I PAKs, FRAX1036, or PAK1 small interfering RNA oligonucleotides dramatically altered signaling to cytoskeletal-associated proteins, such as stathmin, and induced microtubule disorganization and cellular apoptosis. Live-cell imaging revealed that the duration of mitotic arrest mediated by docetaxel was significantly reduced in the presence of FRAX1036, and this was associated with increased kinetics of apoptosis.ConclusionsTaken together, these findings further support PAK1 as a potential target in breast cancer and suggest combination with taxanes as a viable strategy to increase anti-tumor efficacy

Landscapes of cellular phenotypic diversity in breast cancer xenografts and their impact on drug response

Funder: Cancer Research UK (CRUK); doi: https://doi.org/10.13039/501100000289Funder: AstraZeneca; doi: https://doi.org/10.13039/100004325Abstract: The heterogeneity of breast cancer plays a major role in drug response and resistance and has been extensively characterized at the genomic level. Here, a single-cell breast cancer mass cytometry (BCMC) panel is optimized to identify cell phenotypes and their oncogenic signalling states in a biobank of patient-derived tumour xenograft (PDTX) models representing the diversity of human breast cancer. The BCMC panel identifies 13 cellular phenotypes (11 human and 2 murine), associated with both breast cancer subtypes and specific genomic features. Pre-treatment cellular phenotypic composition is a determinant of response to anticancer therapies. Single-cell profiling also reveals drug-induced cellular phenotypic dynamics, unravelling previously unnoticed intra-tumour response diversity. The comprehensive view of the landscapes of cellular phenotypic heterogeneity in PDTXs uncovered by the BCMC panel, which is mirrored in primary human tumours, has profound implications for understanding and predicting therapy response and resistance

Differential oestrogen receptor binding is associated with clinical outcome in breast cancer.

Oestrogen receptor-α (ER) is the defining and driving transcription factor in the majority of breast cancers and its target genes dictate cell growth and endocrine response, yet genomic understanding of ER function has been restricted to model systems. Here we map genome-wide ER-binding events, by chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq), in primary breast cancers from patients with different clinical outcomes and in distant ER-positive metastases. We find that drug-resistant cancers still recruit ER to the chromatin, but that ER binding is a dynamic process, with the acquisition of unique ER-binding regions in tumours from patients that are likely to relapse. The acquired ER regulatory regions associated with poor clinical outcome observed in primary tumours reveal gene signatures that predict clinical outcome in ER-positive disease exclusively. We find that the differential ER-binding programme observed in tumours from patients with poor outcome is not due to the selection of a rare subpopulation of cells, but is due to the FOXA1-mediated reprogramming of ER binding on a rapid timescale. The parallel redistribution of ER and FOXA1 binding events in drug-resistant cellular contexts is supported by histological co-expression of ER and FOXA1 in metastatic samples. By establishing transcription-factor mapping in primary tumour material, we show that there is plasticity in ER-binding capacity, with distinct combinations of cis-regulatory elements linked with the different clinical outcomes

A network analysis to identify mediators of germline-driven differences in breast cancer prognosis

cited By 0Identifying the underlying genetic drivers of the heritability of breast cancer prognosis remains elusive. We adapt a network-based approach to handle underpowered complex datasets to provide new insights into the potential function of germline variants in breast cancer prognosis. This network-based analysis studies similar to 7.3 million variants in 84,457 breast cancer patients in relation to breast cancer survival and confirms the results on 12,381 independent patients. Aggregating the prognostic effects of genetic variants across multiple genes, we identify four gene modules associated with survival in estrogen receptor (ER)-negative and one in ER-positive disease. The modules show biological enrichment for cancer-related processes such as G-alpha signaling, circadian clock, angiogenesis, and Rho-GTPases in apoptosis.Peer reviewe

Common germline polymorphisms associated with breast cancer-specific survival

Abstract Introduction Previous studies have identified common germline variants nominally associated with breast cancer survival. These associations have not been widely replicated in further studies. The purpose of this study was to evaluate the association of previously reported SNPs with breast cancer-specific survival using data from a pooled analysis of eight breast cancer survival genome-wide association studies (GWAS) from the Breast Cancer Association Consortium. Methods A literature review was conducted of all previously published associations between common germline variants and three survival outcomes: breast cancer-specific survival, overall survival and disease-free survival. All associations that reached the nominal significance level of P value <0.05 were included. Single nucleotide polymorphisms that had been previously reported as nominally associated with at least one survival outcome were evaluated in the pooled analysis of over 37,000 breast cancer cases for association with breast cancer-specific survival. Previous associations were evaluated using a one-sided test based on the reported direction of effect. Results Fifty-six variants from 45 previous publications were evaluated in the meta-analysis. Fifty-four of these were evaluated in the full set of 37,954 breast cancer cases with 2,900 events and the two additional variants were evaluated in a reduced sample size of 30,000 samples in order to ensure independence from the previously published studies. Five variants reached nominal significance (P <0.05) in the pooled GWAS data compared to 2.8 expected under the null hypothesis. Seven additional variants were associated (P <0.05) with ER-positive disease. Conclusions Although no variants reached genome-wide significance (P <5 x 10−8), these results suggest that there is some evidence of association between candidate common germline variants and breast cancer prognosis. Larger studies from multinational collaborations are necessary to increase the power to detect associations, between common variants and prognosis, at more stringent significance levels

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Genome-wide association study of germline variants and breast cancer-specific mortality

BACKGROUND: We examined the associations between germline variants and breast cancer mortality using a large meta-analysis of women of European ancestry. METHODS: Meta-analyses included summary estimates based on Cox models of twelve datasets using ~10

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