Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1065
Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1069
Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1074
Cancer RNA-seq consisting of FASTQ single-end reads from 1 colon-cancer individual RNA-seq was performed on illumina This dataset contains reads from a single region.
10x Single Cell Gene Expression library TENX068 for Triple negative breast cancer patient-derived xenograft SA609X4XB03080
10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0146_002 for Triple negative breast cancer patient-derived xenograft SA609X5XB03223
10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0152_001 for Triple negative breast cancer patient-derived xenograft SA609X6XB03401
Cancer and germline exomes consisting of FASTQ reads from 6 individuals (4 melanoma, 1 lung and 1 colon cancer). Exome sequencing was performed on illumina with a depth of 100x to 200x. 2 Melanoma datasets contain reads from 2 different tumor regions 2 Melanoma datasets contain reads from 1 tumor region and from a tumor derived cell line 1 Melanoma dataset contains reads from 2 healthy tissues Colon and lung datasets contain both 1 matched germline-tumor pair
RNA-seq dataset of Oncogenic and immunological targets for matched therapy of pediatric blood cancer patients: Dutch iTHER study experience
Development of a targeted methylation assay to determine the cell-type composition of a sample. As we age, many tissues become colonised by microscopic clones carrying somatic driver mutations. Some of these clones represent a first step towards cancer whereas others may contribute to ageing and other diseases. However, our understanding of the clonal landscapes of human tissues, and their impact on cancer risk, ageing and disease, remains limited due to the challenge of detecting somatic mutations present in small numbers of cells. Here, we introduce a new version of nanorate sequencing (NanoSeq), a duplex sequencing method with error rates of less than 5 per billion base pairs, which is compatible with whole-exome and targeted gene sequencing. Deep sequencing of polyclonal samples with single-molecule sensitivity enables the simultaneous detection of mutations in large numbers of clones, yielding accurate somatic mutation rates, mutational signatures and driver mutation frequencies in any tissue. Applying targeted NanoSeq to 1,042 non-invasive samples of oral epithelium and 371 samples of blood from a twin cohort, we found an unprecedentedly rich landscape of selection, with 46 genes under positive selection driving clonal expansions in the oral epithelium, over 62,000 driver mutations, and evidence of negative selection in some genes. The high number of positively selected mutations in multiple genes provides high-resolution maps of selection across coding and non-coding sites, a form of in vivo saturation mutagenesis. Multivariate regression models enable mutational epidemiology studies on how carcinogenic exposures and cancer risk factors, such as age, tobacco or alcohol, alter the acquisition and selection of somatic mutations. Accurate single-molecule sequencing has the potential to unveil the polyclonal landscape of any tissue, providing a powerful tool to study early carcinogenesis, cancer prevention and the role of somatic mutations in ageing and disease.
