20_Matched_Pair_Breast_Cancer_Genomes - EGA European Genome-Phenome Archive

Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data

Dataset ID	Description	Technology	Samples
EGAD00001000082	20 Matched Pair Breast Cancer Genomes	Illumina Genome Analyzer II Illumina HiSeq 2000	42
EGAD00001000138	The expression data for this study can be found here: http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-1088/and its SNP6 data can be found here:http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-1087/	Illumina Genome Analyzer II Illumina HiSeq 2000	58
EGAD00001001335	We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.	Illumina Genome Analyzer II Illumina HiSeq 2000	28
EGAD00001001338	We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.	Illumina Genome Analyzer II Illumina HiSeq 2000	49
EGAD00001002237	The disordered transcriptomes of cancer encompass direct effects of somatic mutation on transcription; co-ordinated secondary alterations in transcriptional pathways; and increased transcriptional noise. To catalogue the rules governing how somatic mutation Overall, 59% of 6980 exonic substitutions were expressed. Compared to other classes, nonsense mutations showed lower expression levels than expected with patterns characteristic of nonsense-mediated decay. 14% of 4234 genomic rearrangements caused transcriptional abnormalities, including exon skips, exon reusage, fusion transcripts and premature poly-adenylation. We found productive, stable transcription from sense-to-antisense gene fusions and gene-to-intergenic rearrangements, suggesting that these mutation classes may drive more transcriptional disruption than previously suspected. Systematic integration of transcriptome with genome data therefore reveals the rules by which transcriptional machinery interprets somatic mutation.	Illumina Genome Analyzer II Illumina HiSeq 2000	59
EGAD00001002696	Recurrent breast cancer is almost universally fatal. We characterize 170 patients locally relapsed or distant metastatic cancers using massively parallel sequencing. We identify that the relapse-seeding clone disseminates late from the primary tumor. TP53 and AKT1 appear to be enriched in ER-positive cancers predisposed to relapse. Mutation acquisition continues at relapse as the same mutation signatures continue to operate and new signatures, such as that caused by radiotherapy appear de novo. In 49% of cases we identify drivers mutations private to the relapse and these are sampled from a wider range of cancer genes, including SWI-SNF complex and JAK-STAT signaling.	HiSeq X Ten Illumina HiSeq 2000	58

Publications	Citations
Genomic Evolution of Breast Cancer Metastasis and Relapse. Yates LR, Knappskog S, Wedge D, Farmery JHR, Gonzalez S, Martincorena I, Alexandrov LB, Van Loo P, Haugland HK, Lilleng PK, Gundem G, Gerstung M, Pappaemmanuil E, Gazinska P, Bhosle SG, Jones D, Raine K, Mudie L, Latimer C, Sawyer E, Desmedt C, Sotiriou C, Stratton MR, Sieuwerts AM, Lynch AG, Martens JW, Richardson AL, Tutt A, Lønning PE, Campbell PJ. Cancer Cell 32: 2017 169-184.e7	345
Integrative reconstruction of cancer genome karyotypes using InfoGenomeR. Lee Y, Lee H. Nat Commun 12: 2021 2467	2
A Cluster-Based Approach for the Discovery of Copy Number Variations From Next-Generation Sequencing Data. Liu G, Zhang J. Front Genet 12: 2021 699510	0
Spatial genomics maps the structure, nature and evolution of cancer clones. Lomakin A, Svedlund J, Strell C, Gataric M, Shmatko A, Rukhovich G, Park JS, Ju YS, Dentro S, Kleshchevnikov V, Vaskivskyi V, Li T, Bayraktar OA, Pinder S, Richardson AL, Santagata S, Campbell PJ, Russnes H, Gerstung M, Nilsson M, Yates LR. Nature 611: 2022 594-602	33
Evolving copy number gains promote tumor expansion and bolster mutational diversification. Wang Z, Xia Y, Mills L, Nikolakopoulos AN, Maeser N, Dehm SM, Sheltzer JM, Sun R. Nat Commun 15: 2024 2025	1