A Living Biobank of Breast Cancer Organoids Captures Disease Heterogeneity

Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10-8. The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores for individualized screening and prevention.

/pdf/association-analysis-identifies-65-new-breast-cancer-risk-24nfppemot.pdf

Association analysis identifies 65 new breast cancer risk loci

Chemoresistance Evolution in Triple-Negative Breast Cancer Delineated by Single-Cell Sequencing

Triple-negative breast cancer (TNBC) remains the most challenging breast cancer subtype to treat. To date, therapies directed to specific molecular targets have rarely achieved clinically meaningful improvements in outcomes of patients with TNBC, and chemotherapy remains the standard of care. Here, we seek to review the most recent efforts to classify TNBC based on the comprehensive profiling of tumors for cellular composition and molecular features. Technologic advances allow for tumor characterization at ever-increasing depth, generating data that, if integrated with clinical-pathologic features, may help improve risk stratification of patients, guide treatment decisions and surveillance, and help identify new targets for drug development. SIGNIFICANCE: TNBC is characterized by higher rates of relapse, greater metastatic potential, and shorter overall survival compared with other major breast cancer subtypes. The identification of biomarkers that can help guide treatment decisions in TNBC remains a clinically unmet need. Understanding the mechanisms that drive resistance is key to the design of novel therapeutic strategies to help prevent the development of metastatic disease and, ultimately, to improve survival in this patient population.

/pdf/insights-into-molecular-classifications-of-triple-negative-25t6fgeibb.pdf

Insights into Molecular Classifications of Triple-Negative Breast Cancer: Improving Patient Selection for Treatment.

The Genomic Landscape of Endocrine-Resistant Advanced Breast Cancers.

The genomic landscape of breast cancer is complex, and inter- and intra-tumour heterogeneity are important challenges in treating the disease. In this study, we sequence 173 genes in 2,433 primary breast tumours that have copy number aberration (CNA), gene expression and long-term clinical follow-up data. We identify 40 mutation-driver (Mut-driver) genes, and determine associations between mutations, driver CNA profiles, clinical-pathological parameters and survival. We assess the clonal states of Mut-driver mutations, and estimate levels of intra-tumour heterogeneity using mutant-allele fractions. Associations between PIK3CA mutations and reduced survival are identified in three subgroups of ER-positive cancer (defined by amplification of 17q23, 11q13–14 or 8q24). High levels of intra-tumour heterogeneity are in general associated with a worse outcome, but highly aggressive tumours with 11q13–14 amplification have low levels of intra-tumour heterogeneity. These results emphasize the importance of genome-based stratification of breast cancer, and have important implications for designing therapeutic strategies.

/pdf/the-somatic-mutation-profiles-of-2-433-breast-cancers-14mp3isbs5.pdf

The somatic mutation profiles of 2,433 breast cancers refines their genomic and transcriptomic landscapes

Bernard Pereira, Suet-Feung Chin, Oscar M. Rueda, Hans-Kristian Moen Vollan, Elena Provenzano, Helen A. Bardwell, Michelle Pugh, Linda Jones, Roslin Russell, Stephen-John Sammut, Dana W.Y. Tsui, Bin Liu, Sarah-Jane Dawson, Jean Abraham, Helen Northen, John F. Peden, Abhik Mukherjee, Gulisa Turashvili, Andrew R. Green, Steve McKinney, Arusha Oloumi, Sohrab Shah, Nitzan Rosenfeld, Leigh Murphy, David R. Bentley, Ian O. Ellis, Arnie Purushotham, Sarah E. Pinder, Anne-Lise Børresen-Dale, Helena M. Earl, Paul D. Pharoah, Mark T. Ross, Samuel Aparicio & Carlos Caldas

Erratum: The somatic mutation profiles of 2,433 breast cancers refine their genomic and transcriptomic landscapes (Nature Communications (2016) 7:11479 DOI: 10.1038/ncomms11479)

Steve McKinney

Papers

The somatic mutation profiles of 2,433 breast cancers refines their genomic and transcriptomic landscapes

Erratum: The somatic mutation profiles of 2,433 breast cancers refine their genomic and transcriptomic landscapes (Nature Communications (2016) 7:11479 DOI: 10.1038/ncomms11479)