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.