Dataset Information

ICGC breast cancer sequencing project SNP6 data

ABSTRACT: Affymetrix SNP6.0 breast cancer genome sequencing data

PROVIDER: EGAD00010000915 | EGA |

REPOSITORIES: EGA

ACCESS DATA

Publications

Landscape of somatic mutations in 560 breast cancer whole-genome sequences.

Nik-Zainal Serena S Davies Helen H Staaf Johan J Ramakrishna Manasa M Glodzik Dominik D Zou Xueqing X Martincorena Inigo I Alexandrov Ludmil B LB Martin Sancha S Wedge David C DC Van Loo Peter P Ju Young Seok YS Smid Marcel M Brinkman Arie B AB Morganella Sandro S Aure Miriam R MR Lingjærde Ole Christian OC Langerød Anita A Ringnér Markus M Ahn Sung-Min SM Boyault Sandrine S Brock Jane E JE Broeks Annegien A Butler Adam A Desmedt Christine C Dirix Luc L Dronov Serge S Fatima Aquila A Foekens John A JA Gerstung Moritz M Hooijer Gerrit K J GK Jang Se Jin SJ Jones David R DR Kim Hyung-Yong HY King Tari A TA Krishnamurthy Savitri S Lee Hee Jin HJ Lee Jeong-Yeon JY Li Yilong Y McLaren Stuart S Menzies Andrew A Mustonen Ville V O'Meara Sarah S Pauporté Iris I Pivot Xavier X Purdie Colin A CA Raine Keiran K Ramakrishnan Kamna K Rodríguez-González F Germán FG Romieu Gilles G Sieuwerts Anieta M AM Simpson Peter T PT Shepherd Rebecca R Stebbings Lucy L Stefansson Olafur A OA Teague Jon J Tommasi Stefania S Treilleux Isabelle I Van den Eynden Gert G GG Vermeulen Peter P Vincent-Salomon Anne A Yates Lucy L Caldas Carlos C van't Veer Laura L Tutt Andrew A Knappskog Stian S Tan Benita Kiat Tee BK Jonkers Jos J Borg Åke Å Ueno Naoto T NT Sotiriou Christos C Viari Alain A Futreal P Andrew PA Campbell Peter J PJ Span Paul N PN Van Laere Steven S Lakhani Sunil R SR Eyfjord Jorunn E JE Thompson Alastair M AM Birney Ewan E Stunnenberg Hendrik G HG van de Vijver Marc J MJ Martens John W M JW Børresen-Dale Anne-Lise AL Richardson Andrea L AL Kong Gu G Thomas Gilles G Stratton Michael R MR

Nature 20160502 7605

We analysed whole-genome sequences of 560 breast cancers to advance understanding of the driver mutations conferring clonal advantage and the mutational processes generating somatic mutations. We found that 93 protein-coding cancer genes carried probable driver mutations. Some non-coding regions exhibited high mutation frequencies, but most have distinctive structural features probably causing elevated mutation rates and do not contain driver mutations. Mutational signature analysis was extended ...[more]

PMID: 27135926

Similar Datasets

Project description:Breast cancer is a genetically and phenotypically complex disease. To understand the role of microRNAs in this molecular complexity, we performed miRNA expression analysis in a cohort of molecularly well-characterized human breast cancer (BC) cell lines to discover miRNAs associated with the most common molecular subtypes and the most frequent genetic aberrations.Using a microarray carrying LNA™ modified oligonucleotide capture probes (Exiqon), expression levels of 725 human miRNAs were measured in 51 BC cell lines. MiRNA expression was explored by unsupervised cluster analysis and then associated with the molecular subtypes and genetic aberrations commonly present in breast cancer. Unsupervised cluster analysis using the most variably expressed miRNAs divided the 51 BC cell lines into a major and a minor cluster predominantly mirroring the luminal and basal intrinsic subdivision of BC cell lines. One hundred and thirteen miRNAs were differentially expressed between these two main clusters of which half were related to the ER-status of the cell lines. Forty miRNAs were differentially expressed between basal-like and normal-like/claudin-low cell lines. Within the luminal-group of cell lines, 39 miRNAs were associated with ERBB2 overexpression and 24 miRNAs with E-cadherin gene mutations, which are frequent in this subtype of BC cell lines. In contrast, 31 different miRNAs were associated with E-cadherin promoter hypermethylation, which, contrary to E-cadherin mutation, is exclusively observed in BC cell lines that are not of luminal origin. The differential expression of 30 miRNAs were associated with p16INK4 status while only a few differentially expressed miRNAs were associated with BRCA1, or PIK3CA/PTEN, TP53 mutation status of the cell lines (P-value < 0.05). Twelve miRNAs were associated with DNA copy number variation of the respective locus. Luminal-basal and epithelial-mesenchymal associated miRNAs determine the overall subdivision of miRNA transcriptome of BC cell lines. Specific sets of miRNAs were associated with ERBB2 overexpression, p16INK4aor E-cadherin mutation or E-cadherin methylation status, which implies that these miRNAs may contribute to the driver role of the genetic aberrations. Additionally, miRNAs, which are located in a genomic region showing recurrent genetic aberrations, may themselves play a driver role in breast carcinogenesis or contribute to a driver gene in their vicinity. In short, our study provides detailed molecular miRNA portraits of BC cell lines, which can be exploited for functional studies of clinically important miRNAs.

Dataset Information

ICGC breast cancer sequencing project SNP6 data

Publications

Landscape of somatic mutations in 560 breast cancer whole-genome sequences.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure