Most common breast cancer susceptibility variants have been identified through genome-wide association studies (GWAS) of predominantly estrogen receptor (ER)-positive disease1. We conducted a GWAS using 21,468 ER-negative cases and 100,594 controls combined with 18,908 BRCA1 mutation carriers (9,414 with breast cancer), all of European origin. We identified independent associations at P < 5 × 10−8 with ten variants at nine new loci. At P < 0.05, we replicated associations with 10 of 11 variants previously reported in ER-negative disease or BRCA1 mutation carrier GWAS and observed consistent associations with ER-negative disease for 105 susceptibility variants identified by other studies. These 125 variants explain approximately 14% of the familial risk of this breast cancer subtype. There was high genetic correlation (0.72) between risk of ER-negative breast cancer and breast cancer risk for BRCA1 mutation carriers. These findings may lead to improved risk prediction and inform further fine-mapping and functional work to better understand the biological basis of ER-negative breast cancer.

Significant endeavor has been applied to identify functional therapeutic targets in glioblastoma (GBM) to halt the growth of this aggressive cancer. We show that the receptor tyrosine kinase EphA3 is frequently overexpressed in GBM and, in particular, in the most aggressive mesenchymal subtype. Importantly, EphA3 is highly expressed on the tumor-initiating cell population in glioma and appears critically involved in maintaining tumor cells in a less differentiated state by modulating mitogen-activated protein kinase signaling. EphA3 knockdown or depletion of EphA3-positive tumor cells reduced tumorigenic potential to a degree comparable to treatment with a therapeutic radiolabelled EphA3-specific monoclonal antibody. These results identify EphA3 as a functional, targetable receptor in GBM.

The breast cancer risk variants identified in genome-wide association studies explain only a small fraction of the familial relative risk, and the genes responsible for these associations remain largely unknown. To identify novel risk loci and likely causal genes, we performed a transcriptome-wide association study evaluating associations of genetically predicted gene expression with breast cancer risk in 122,977 cases and 105,974 controls of European ancestry. We used data from the Genotype-Tissue Expression Project to establish genetic models to predict gene expression in breast tissue and evaluated model performance using data from The Cancer Genome Atlas. Of the 8,597 genes evaluated, significant associations were identified for 48 at a Bonferroni-corrected threshold of P < 5.82 × 10, including 14 genes at loci not yet reported for breast cancer. We silenced 13 genes and showed an effect for 11 on cell proliferation and/or colony-forming efficiency. Our study provides new insights into breast cancer genetics and biology.

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Treatment options for patients with brain metastases (BMs) have limited efficacy and the mortality rate is virtually 100%. Targeted therapy is critically under-utilized, and our understanding of mechanisms underpinning metastatic outgrowth in the brain is limited. To address these deficiencies, we investigated the genomic and transcriptomic landscapes of 36 BMs from breast, lung, melanoma and oesophageal cancers, using DNA copy-number analysis and exome-and RNA-sequencing. The key findings were as follows.

Mutations in the TP53 gene commonly result in the expression of a full-length protein that drives cancer cell invasion and metastasis. Herein, we have deciphered the global landscape of transcriptional regulation by mutant p53 through the application of a panel of isogenic H1299 derivatives with inducible expression of several common cancer-associated p53 mutants. We found that the ability of mutant p53 to alter the transcriptional profile of cancer cells is remarkably conserved across different p53 mutants. The mutant p53 transcriptional landscape was nested within a small subset of wild-type p53 responsive genes, suggesting that the oncogenic properties of mutant p53 are conferred by retaining its ability to regulate a defined set of p53 target genes. These mutant p53 target genes were shown to converge upon a p63 signalling axis. Both mutant p53 and wild-type p63 were co-recruited to the promoters of these target genes, thus providing a molecular basis for their selective regulation by mutant p53. We demonstrate that mutant p53 manipulates the gene expression pattern of cancer cells to facilitate invasion through the release of a pro-invasive secretome into the tumor microenvironment. Collectively, this study provides mechanistic insight into the complex nature of transcriptional regulation by mutant p53 and implicates a role for tumor-derived p53 mutations in the manipulation of the cancer cell secretome.

The clinical and pathologic heterogeneity of human breast cancer has long been recognized. Now, molecular profiling has enriched our understanding of breast cancer heterogeneity and yielded new prognostic and predictive information. Despite recent therapeutic advances, including the HER2-specific agent, trastuzumab, locoregional and systemic disease recurrence remain an ever-present threat to the health and well being of breast cancer survivors. By definition, disease recurrence originates from residual treatment-resistant cells, which regenerate at least the initial breast cancer phenotype. The discovery of the normal breast stem cell has re-ignited interest in the identity and properties of breast cancer stem-like cells and the relationship of these cells to the repopulating ability of treatment-resistant cells. The cancer stem cell model of breast cancer development contrasts with the clonal evolution model, whereas the mixed model draws on features of both. Although the origin and identity of breast cancer stem-like cells is contentious, treatment-resistant cells survive and propagate only because aberrant and potentially druggable signaling pathways are recruited. As a means to increase the rates of breast cancer cure, several approaches to specific targeting of the treatment-resistant cell population exist and include methods for addressing the problem of radioresistance in particular.

Genome-wide association studies (GWAS) have identified more than 170 breast cancer susceptibility loci. Here we hypothesize that some risk-associated variants might act in non-breast tissues, specifically adipose tissue and immune cells from blood and spleen. Using expression quantitative trait loci (eQTL) reported in these tissues, we identify 26 previously unreported, likely target genes of overall breast cancer risk variants, and 17 for estrogen receptor (ER)-negative breast cancer, several with a known immune function. We determine the directional effect of gene expression on disease risk measured based on single and multiple eQTL. In addition, using a gene-based test of association that considers eQTL from multiple tissues, we identify seven (and four) regions with variants associated with overall (and ER-negative) breast cancer risk, which were not reported in previous GWAS. Further investigation of the function of the implicated genes in breast and immune cells may provide insights into the etiology of breast cancer.