9944 results for "cancer rna-seq"

in 58.64 milliseconds.

• Recalibrated alignment files of Saudi Thyroid Cancer

  The dataset consists of samples from papillary thyroid cancer patients. A total of 292 DNA samples from blood/normal and cancer tissue are subjected to whole exome sequencing using Illumina. The fastq files generated were aligned with reference genome ‘hg19’, duplicates were marked, realignment around indels and quality recalibration were performed to produce good quality variants. The recalibrated “.bam” files are included with this dataset.​

  Dataset EGAD00001003950

• The spatio-temporal evolution of lymph node spread in early breast cancer

  Set of multi-region sequenced breast cancer primary samples, lymph nodes and ctDNA. We collected samples from 11 breast cancer patients with lymph node involvement but no sign of distant metastasis. We performed a mix of whole-exome sequencing, targeted capture sequencing, and whole-genome sequencing of primary tumour samples and lymph nodes, as well as targeted capture sequencing of circulating tumour DNA.

  Dataset EGAD00001004122

• Multi-Region WES of Metastatic Colorectal Cancer

  In order to reconstruct the evolutionary history of metastatic colorectal cancer, we performed whole-exome sequencing of 12 metastatic colorectal cancer patients for whom the primary tumor and matched distant metastases to the brain (n=10) and liver (n=2). For 8 of the 12 patients, multiple regions (n=3-7) of the primary tumor and distant metastases were sequenced.

  Dataset EGAD00001004896

• Multimodal Genomic Features Predict Outcome of Immune Checkpoint Blockade in Non-small Cell Lung Cancer

  The dataset for Multimodal Genomic Features Predict Outcome of Immune Checkpoint Blockade in Non-small Cell Lung Cancer includes 106 bam files from whole exome next-generation sequencing on the Illumina HiSeq2500. The samples analyzed include matched tumor/normal samples from non-small cell lung cancer patients treated with immunotherapy.

  Dataset EGAD00001005796

• Breast Cancer Histology Images

  Fresh frozen breast cancer H&E tissue images collected and annotated by the International Cancer Genome Consortium (ICGC), that included the BASIS collaboration. Associated with whole genome sequence data as originally described by Nik-Zainal et al, Nature, 2016 (DOI: 10.1038/nature17676) and deposited with ID EGAS00001001178

  Dataset EGAD00010001911

• The dataset for Single molecule genome-wide mutation profiles of cell-free DNA for non-invasive detection of cancer

  The dataset for Single molecule genome-wide mutation profiles of cell-free DNA for non-invasive detection of cancer includes 57 BAM files from whole genome next-generation sequencing on the Illumina HiSeq2500. The samples analyzed include plasma samples from individuals with and without cancer.

  Dataset EGAD00001010891

• Quantitative analysis of a novel DNA hypermethylation panel using bronchial specimen for lung cancer diagnosis

  The dataset includes IDAT raw files for 10 samples and the analyzed DMP file which describes the differential methylation positions based on Illumina Infinium MethylationEPIC BeadChip. All samples (5 lung cancer cases vs. 5 benign lung disease controls) were obtained from bronchial washings at the site of the lesion under bronchoscopy manipulation. The histological type of the five lung cancer cases is adenocarcinoma and squamous cell carcinoma.

  Dataset EGAD00010002465

• Prediction of response to preoperative chemoradiotherapy in rectal cancer based on whole-exome sequencing and transcriptomic analysis

  Accumulating evidence suggests that radiotherapeutic success has an immune-associated component. We aimed to investigate the immunogenomic profiles associated with response to preoperative chemoradiotherapy (CRT) in patients with locally advanced rectal cancer.

  Study JGAS000158

• Whole Exome Sequencing of Parathyroid Cancer Identifies Candidate Driver Mutations and Core Pathways

  Here we performed genomic characterization of twenty-nine sporadic parathyroid cancers using next generation whole exome sequencing. Thirty-three novel candidate driver genes for sporadic parathyroid cancer were proposed, in addition to previously known driver genes CDC73 and MEN1.

  Study phs001765

• Germline Genetic Variants in Cancer-Susceptibility Genes in Patients with Osteosarcoma

  We conducted whole-exome sequencing of germline DNA from patients with osteosarcoma to estimate the frequency of pathogenic/likely pathogenic germline genetic variants in known cancer-susceptibility genes in a large population of osteosarcoma patients unselected for family history.

  Study phs002444

• EOSC4Cancer Synthetic Colorectal Cancer Genomic data

  In this study there are stored the synthetic datasets produced by partners involved in EOSC4Cancer. The study contains independent datasets available for the research community. The synthetic genomes have been created trying to mimic real cancer data.

  Study EGAS50000000190

• Clinical panel sequencing of cancer of unknown primary using TruSight Oncology 500 (TSO500)

  TruSight Oncology 500 (TSO500) cancer panel sequencing data on paired tumour and germline DNA from cancer of unknown primary samples. All of the samples in this dataset are matched to WGS data. This data was used to compare biomarker yield against what was achieved with WGS and contains n=51 tumour-only samples. All samples are in BAM format aligned with GRCh38 reference genome.

  Dataset EGAD50000000657

• Comprehensive genomic characterization of early stage bladder cancer - nanopore sequencing

  For this project about non-muscle invasive bladder cancer (NMIBC), we analysed long read sequencing data from 4 patients using the Nanopore platform. The dataset is composed of 8 BAM files: 4 tumor samples and 4 paired blood samples.

  Study EGAS50000000510

• Versatile workflow for cell-type resolved transcriptional and epigenetic profiles from cryopreserved human lung

  The complexity of the lung microenvironment and changes in cellular composition during disease progression make it exceptionally hard to understand molecular mechanisms leading to the development of chronic lung diseases. Although recent advances in cell-type resolved and single-cell sequencing approaches hold great promise for studying complex diseases, their implementation relies on local access to fresh tissue, as traditional tissue storage methods do not allow viable cell isolation. To overcome these hurdles, we developed a novel, versatile workflow that allows long-term storage of human lung tissue with high cell viability, permits thorough sample quality check before cell isolation, and is compatible with sequencing-based profiling, including single-cell approaches. We demonstrate that cryopreservation is suitable for the isolation of multiple cell types from human lung and is applicable to both healthy and diseased tissue, including COPD and tumour samples. Basal cells isolated from cryopreserved airways retain the ability to differentiate, indicating that cellular identity is not altered by cryopreservation. Importantly, using RNA sequencing and EPIC Array, we show that genome-wide gene expression and DNA methylation signatures are preserved upon cryopreservation, emphasizing the suitability of our workflow for -omics profiling of human lung cells. In addition, we obtained high-quality single-cell RNA sequencing data of cells isolated from the cryopreserved human lung, demonstrating that cryopreservation empowers single-cell approaches. Overall, thanks to its simplicity, our cryopreservation workflow is well-suited for prospective tissue collection by academic collaborators and biobanks, opening worldwide access to human tissue.

  Study EGAS00001004477

• Innate Immune Anti-Viral Deaminase Deregulation Fuels Pre-Leukemia Stem Cell Evolution

  This study evaluates the effect of Rebecsinib treatment on gene expression, isoform splicing, and ADAR1 mediated RNA editing in cells from an in vivo humanized mouse model which have been engrafted with human secondary AML cells. For analysis of cells from Rebesinib-treated animals, CD34+ cells were obtained from bone marrow and spleens of sAML-engrafted mice following once weekly treatment with 0 (Vehicle) or 5 or 10 mg/kg Rebecsinib. For analysis of cells from serial transplant recipients of cells harvested from Rebecsinib-treated mice, CD34+ cells were obtained from bone marrow and spleens of sAML-engrafted mice that were transplanted with cells from animals that received twice weekly treatment with 0 (Vehicle) or 10 mg/kg Rebecsinib. No further treatment was given to serial transplant recipients, thus allowing the analysis of molecular changes that are sustained following serial transplantation. Whole transcriptome sequencing was performed at The Scripps Research Institute Next Generation Sequencing Core on Illumina NextSeq 500 sequencers with 150bp paired-end reads.These data revealed a uniquely expressed ADAR1 splice isoform (with a retrained intronic region), global downregulation of normalized RNA editing events, and isoform switching from MCL1-L to MCL1-S in Rebecsinib-treated sAML-engrafted mice. These results demonstrate the anti-survival and anti-self-renewal effects of Rebecsinib treatment on the leukemia stem cell (LSC) population in sAML-engrafted mice as well as the reduction in the inflammation-induced, hyper-editing p150 isoform of ADAR1. Thus, Rebecsinib treatment has promise for reducing the LSC population in myeloproliferative disorders and associated cancers.

  Study phs002228

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: Oesophageal adenocarcinoma

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute (40X and 20X depth respectively). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development. This dataset contains all the data available for this study on 2021-09-27.

  Dataset EGAD00001006083

• MutWP1 CRUK Grand Challenge Mutographs of Cancer Colorectal

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Dataset EGAD00001007510

• The clinical utility of genomics in childhood cancer extends beyond targetable mutations - Cancer Panel data

  We deeply sequenced 864 cancer-associated genes and the complete genomes and transcriptomes for 300 pediatric and adolescent/young adult (AYA) patients with poor prognosis or rare tumors. Using integrative somatic-germline analyses, we assessed the clinical utility of cancer genomics in this population. Clinically actionable variants were identified in 56% of patients. Improved diagnostic accuracy led to modified management in a subset. Therapeutically targetable variants, found in 54% of patients, were of unanticipated timing and type, with over 20% of these derived from the germline. Enrichment in corroborating mutational signature 3 (‘BRCAness’) in patients with germline homologous recombination defects suggests they are drivers of pediatric cancers and potential targets for PARP inhibition. Comprehensive somatic-germline cancer genomic profiling is useful at multiple points in the care trajectory for pediatric/AYA patients, supporting its integration into early clinical management. Re-biopsy at the time of relapse should be considered, and specific attention to the mutational burden is indicated. Defective DNA repair genes in the germline may represent important targetable drivers.

  Study EGAS00001006642

• Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) - OncoArray Genotypes

  The data come from 40 studies participating in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). CIMBA recruits individuals with pathogenic mutations in BRCA1 or BRCA2. The majority of carriers were recruited through cancer genetics clinics offering genetic testing, and were enrolled into national or regional studies. The remainder were identified by population-based sampling of cases, or community recruitment. Eligibility to participate is restricted to carriers of pathogenic BRCA1/2 mutations who were 18 years or older at recruitment. Information collected included amongst other variables: age at recruitment; ages at breast and ovarian cancer diagnosis; and estrogen receptor (ER) status. Samples were genotyped using the Illumina OncoArray beadchip 500K SNP custom array. Details of the genotyping process and sample selection are included in Phelan et al, Identification of twelve new susceptibility loci for different histotypes of epithelial ovarian cancer, Nat Genet. 2017 May;49(5):680-691 (PMID:28346442), and Milne et al, Identification of ten variants associated with risk of estrogen receptor negative breast cancer, Nat Genet (in press).

  Study phs001321

• Kidney Two-Hit Mapping

  Germ-line genetic variants identified thus far generally account for only part of the genetic risk predicted for most cancers. A component of the remaining risk may be explained by functionally consequent genetic variants that are individually very rare (or private to that individual's family). While their identification may be highly informative for cancer etiology and biological knowledge, strategies that allow for agnostic (genome-wide) identification of such genes are not straight forward. This is particularly true for rare cancers where sufficient numbers of patients may simply not be available for appropriate statistically powered studies. In this project we have explored a study design based around the concept of "two-hit mapping" using the co-occurrence of germ-line and somatic mutations in the same gene to assist in the identification of susceptibility genes. The dataset includes 54 kidney cancer patients selected for enrichment of genetic disease, that is patients with: early age of onset and/or family history and/or bilateral disease. Germ-line and somatic (kidney cancer) tumor sequencing was carried out. These data may improve our understanding of kidney cancer.

  Study phs001971

• Single-Cell Analysis of Somatic Mutations in Human Bronchial Epithelial Cells in Relation to Aging and Smoking

  While lung cancer risk among smokers is dependent on smoking dose, it remains unknown if this increased risk reflects an increased rate of somatic mutation accumulation in normal lung cells. Here we applied single-cell whole genome sequencing of proximal bronchial basal cells from 33 subjects, aged between 11 and 86 years, with smoking histories varying from never smoking to 116 pack years. We found an increase in the frequency of single-nucleotide variants and small insertions and deletions with chronological age in never-smokers, with mutation frequencies significantly elevated among smokers. However, when plotted against smoking pack-years, mutations were found to follow the linear increase in cancer risk only until about 23 pack years, after which no further increase in mutation frequency was observed, pointing towards individual selection for mutation avoidance. Known lung cancer-defined global mutation signatures tracked with both age and smoking. Within study power limits, no significant enrichment for somatic mutations in lung cancer driver genes was observed.

  Study phs002758

• WGS of cell line MMML-seq / MALY-DE tumor_4167452

  This dataset contains the aligned whole genome sequencing data of cell line 380. This cell was established from the peripheral blood of a 15-year-old boy with acute lymphoblastic leukemia at relapse, showing an immature phenotype and carrying an IGH-MYC (t(8;14)) as well as an IGH-BCL2 (t(14;18)) chromosomal translocation. The sequencing was performed on an Illumina X-ten sequencer.

  Dataset EGAD00001004090

• FFPE

  The mutational status of 112 recurrently mutated genes in B-cell lymphoma was examined by targeted next-generation sequencing (NGS). Libraries were performed with 150 ng of genomic DNA (gDNA) obtained from formalin-fixed paraffin-embedded (FFPE) biopsy using molecular-barcoded library adapters (ThruPLEX Tag-seq kit; Takara) coupled with a custom hybridization capture based method (SureSelect XT Target Enrichment System Capture strategy, Agilent Technologies Inc.) and sequenced in a MiSeq instrument (Illumina, 2x150bp).

  Dataset EGAD00001006565

• cfDNA

  The mutational status of 112 recurrently mutated genes in B-cell lymphoma was examined by targeted next-generation sequencing (NGS). Libraries were performed with 15-30 ng of cfDNA obtained from plasma using molecular-barcoded library adapters (ThruPLEX Tag-seq kit; Takara) coupled with a custom hybridization capture based method (SureSelect XT Target Enrichment System Capture strategy, Agilent Technologies Inc.) and sequenced in a MiSeq instrument (Illumina, 2x150bp).

  Dataset EGAD00001006566

• Sensitive and reproducible cell-free methylome quantification with synthetic spike-in controls

  We created three technical replicates of cell-free DNA from AML patient plasma to assess batch effects and utility of spike-in controls for the cfMeDIP-seq method. Each set of samples were given to three different technicians with slightly different protocols. Details can be found in Wilson et al. "Sensitive and reproducible cell-free methylome quantification with synthetic spike-in controls".

  Dataset EGAD00001006986

• ATAC-Seq of GM adipose tissue samples

  This dataset contains 28 fastq files (11 files for subcutaneous tissue and 17 files for visceral tissue) from nine individuals. All samples were initially sequenced by SEx50 mode (16 files) and some of them were also sequenced by PEx100 mode (12 files). Sequencing was done on the Illumina HiSeq2000 platform.

  Dataset EGAD00001010254

• McGill EMC Community projects Release 7 for cell line "lung epithelial"

  Complete reference epigenome (as defined by IHEC) of a lung epithelial cell line with non-small Cell Lung Adenocarcinoma

  Dataset EGAD00001007679

• CITE-seq AdaptNK

  CITEseq was performed as outlined in Biolegend ‘TotalSeqTM-A Antibodies and Cell Hashing with 10x Single Cell 3' Reagent Kit v3 3.1 Protocol’ with minor modifications, using Biolegend oligo-conjugated antibodies and streptavidin TotalSeq reagents. Briefly, ADAPT-NK cells were stained with CD56-biotin mAb (Miltenyi, clone REA196), followed by TotalSeq antibodies and streptavidin-PE and Live/Dead Aqua (Invitrogen). Cells were subsequently sorted for viable CD56+ cells by flow cytometry.

  Dataset EGAD50000000329

• Profiling of gene expression and epigenomics in the fetal brain

  scRNA-seq and Cut&Tag from a sample of the human fetal brain. To compare neurogenesis in the primary human brain with that in organoids, we profiled transcriptome and chromatin accessibility (10X multiome) as well as bulk Cut&Tag of histone modifications H3K27me3, H3K27ac and H3K4me3. We used a human brain sample from GW 19 for all experiments.

  Dataset EGAD50000000225

• Strand-seq data of primary acute myeloid leukemia patient samples with complex karyotype

  In this study, we aimed to identify somatic structural variation of acute myeloid leukemia with complex karyotype (CK-AML) at the single-cell level and to investigate its direct consequence on the nucleosome occupancy using scNOVA approach. For this purpose, we performed strand-specific single-cell sequencing of primary leukemia samples from four CK-AML patients. We also performed strand-specific single-cell sequencing of two patient-derived xenografts (PDXs).

  Dataset EGAD00001011172

• Reduced Representation Bisulfite Sequencing (RRBS) in various tissues to discover DNA methylation markers for the diagnosis of breast and ovarian cancer.

  Despite a myriad of attempts in the last three decades to diagnose ovarian cancer (OC) earlier, this clinical aim still remains a significant challenge. In addition, monitoring treatment and early detection of fatal breast cancer (BC) remains a major unmet need. Aberrant methylation patterns of linked CpGs analyzed in DNA fragments shed by cancers into the bloodstream (i.e. cell-free DNA) can provide highly specific signals indicating cancer presence.In order to discover the most relevant CpG regions, we used RRBS and analysed several tissue samples: 11 prospectively collected invasive epithelial ovarian cancer samples (high grade serous n=8, low grade serous n=1, endometrioid n=1, mucinous n=1, mean age = 54.7 years), 8 prospectively collected invasive ductal breast cancer samples (2/8 triple negative; mean age = 56.6 years), one benign tumor (papillary serous cystadenoma, age = 86 years), 18 non-neoplastic tissue samples (breast n=7 and adnexal n=11, mean age = 60.2 years), two non-neoplastic endometrial tissues (mean age = 68 years) and twenty three white blood cell samples (mean age = 57.8 years) were assessed by RRBS. Genome wide methylation analysis was performed by Reduced Representation Bisulfite Sequencing (RRBS) at GATC Biotech. DNA was digested with MspI followed by size selection of the library, providing enhanced coverage for the CpG-rich regions. The digested DNA was adapter ligated, bisulfite modified and PCR amplified. The libraries were sequenced on Illumina’s HiSeq 2500. Analysis of the first samples sequenced with 100bp paired-end mode showed that the library insert size was small. Therefore, the remaining samples were sequenced with 50 bp paired-end mode. Using Genedata Expressionist® for Genomic Profiling v9.1, we established a bioinformatics pipeline for the detection of cancer specific differentially methylated regions (DMRs). The most promising DMRs were taken forward for the development and validation of serum based clinical assays.

  Study EGAS00001002609

• A Genome-Wide Association Study of Lung Cancer Risk

  Three genetic loci for lung cancer risk have been identified by genome-wide association studies (GWAS), but inherited susceptibility to specific histologic types of lung cancer is not well established. We conducted a GWAS of lung cancer and its major histologic types genotyping 515,922 single nucleotide polymorphisms (SNPs) in 5,739 incident lung cancer cases and 5,848 controls from one population-based case-control study and three cohort studies. Results were combined with summary data from 10 additional studies for a total of 13,300 cases and 19,666 controls of European descent. Four studies also provided histology data for replication resulting in 3,333 adenocarcinomas (AD), 2,589 squamous cell carcinomas (SQ), and 1,418 small cell carcinomas (SC). In analyses by histology, rs2736100 (TERT) on chromosome 5p15.33, was associated with risk of adenocarcinoma (OR=1.23, 95%CI=1.13-1.33, P=3.02x10-7), but not other histologic types (OR=1.01, P=0.84, and OR=1.00, P=0.93, for SQ and SC, respectively). This finding was confirmed in each replication study and overall meta-analysis (OR=1.24, 95%CI=1.17-1.31, P=3.74x10-14 for AD and OR=0.99, P=0.69 and OR=0.97, P=0.48, for SQ and SC, respectively). Other previously reported association signals on 15q25 and 6p21 were also refined, but no additional loci reached genome-wide significance. In conclusion, a lung cancer GWAS identified a distinct hereditary contribution to adenocarcinoma. Note: The lung study dataset to be released to dbGaP and caBIG excludes 47 individuals from the PLCO cohort who consented to participate only in cancer research projects and 22 individuals because of updated QC. Thus, the released dataset is derived from 11517 subjects, 5699 cases and 5818 controls. After the updated QC, the dataset to be released to dbGaP and caBIG includes 506062 SNPs.

  Study phs000336

• Ulcerative colitis study - WES data

  Whole Exome Sequencing data of Single crypts, bulk crypt samples, and colitis-associated cancer.

  Study EGAS00001003801

• ICGC prostate cancer whole genome mate-pair sequencing

  ICGC prostate cancer whole genome mate-pair sequencing

  Dataset EGAD00001000303

• SPECTA Lung cancer DNA FASTQ files

  SPECTA Lung cancer DNA FASTQ files (Illumina TST170 targeted analysis)

  Dataset EGAD00001006223

• panel data of ALK-positiv non-small cell lung cancer patients

  270 samples with ALK-positiv non-small cell lung cancer, targeted sequencing (198 kb panel size)

  Dataset EGAD00001006297

• SNParray copy number dataset

  4 oesophageal cancer derived organoid lines and 2 ovarian cancer derived organoid lines

  Dataset EGAD00010002002

• Geographic variation of mutagenic exposures in kidney cancer genomes – sequence data (Mutographs)

  Geographic variation of mutagenic exposures in kidney cancer genomes – sequence data (Mutographs)

  Dataset EGAD00001012102

• Amsterdam UMC Head and Neck Cancer Biology and Immunology

  This data access committee oversees data and assesses requests for the Head and Neck Cancer Biology and Immunology lab of Amsterdam UMC, location VUmc.

  Dac EGAC50000000350

• Target sequencing of 27 cancer-predisposing genes and 13 renal cell carcinoma-related genes in Japanese renal cell carcinoma patients

  Identifying causative genes via genetic testing is useful for the screening, prevention, and treatment of cancer. Several hereditary syndromes are known to occur in renal cell carcinoma (RCC). However, these evidences came from the European population; it remains unclear how the RCC-related genes and other cancer-predisposing genes contribute to the development RCC in the Japanese population. A case-control study of 14 RCC-related genes and 26 cancer-predisposing genes was performed using 1,563 Japanese patients with RCC and 6,016 controls. Patients were divided into two major histological subtypes of clear cell RCC (ccRCC) or non-clear cell RCC (nccRCC). Gene-based analysis of germline pathogenic variants in patients with each subtype and cancer-free subjects was performed. Following quality control, 1,532 patients with RCC and 5,996 controls were further analyzed. For ccRCC, 52 of 1,283 (4.05%) patients carried pathogenic variants mainly in the cancer-predisposing genes such as TP53 (P = 1.73 �� 10-4; OR, 5.8; 95% CI, 2.2���15.7). Approximately 80% of patients with pathogenic variants in TP53 had p.Ala189Val that was specific in East Asian population. For nccRCC, 14 of 249 (5.62%) patients carried pathogenic variants mainly in the RCC-related genes such as BAP1 (P = 6.27 �� 10-5; OR, Inf; 95% CI, 10.0���Inf), and FH (P = 6.27 �� 10-5; OR, Inf; 95% CI, 10.0���Inf). Our study showed different and population-specific contributions of risk genes between ccRCC and nccRCC in Japanese for better-personalized medicine.

  Study JGAS000414

• Lactate metabolism in cancer stem cell fate regulation

  Tumors arise as a result of uncontrolled cell proliferation driven by mutations in the signaling pathways that regulate the balance between cell division and differentiation. Despite of that, in the tumor, cancer stem cells seem to retain their capability to differentiate, which can lead to differential chemotherapy response. We previously showed that intestinal stem cells and differentiated cells display specific metabolic features and that they interact through metabolites. Moreover, we found that altering mitochondrial metabolism is sufficient to lead and define stem cell differentiation. In cancer, cellular metabolism is highly derailed. However, how metabolic changes in the cancer cell contribute to cell fate decisions remains unknown. Recently, the crosstalk between metabolism and epigenetics has emerged as one of the players in tumor development. Here we aim to address the impact of the altered metabolism of cancer cells on their epigenome as a regulatory axis of cell identity and fate. We use human-derived tumor organoids where we introduce genetic encoded fluorescent-based reporters to visualize cell identity and metabolism at single cell level. We combine 4D live imaging with a recently developed machine learning method to re-construct cell-lineages, trace stem cell state and metabolic changes during tumor organoid development. We find that, mimicking the tumor metabolic microenvironment (Warburg effect-driven low-glucose high-lactate) leads to changes cellular metabolism and histone acetylation. Strikingly, these alterations provoke profound changes in tumor development by increasing the population of cancer stem cells and their proliferation and differentiation dynamics.

  Study EGAS50000000063

• SCLC tumor sequencing

  In this study we have sequenced the tumor of 28 Small Cell Lung Cancer patients.

  Study EGAS00001003985

• A Comprehensive Catalogue of Somatic Mutations from a Human Cancer Genome

  A Comprehensive Catalogue of Somatic Mutations from a Human Cancer Genome

  Dataset EGAD00001000149

• Clinical Implications of Genomic Alterations in the Tumour and Circulation of Pancreatic Cancer Patients

  Clinical Implications of Genomic Alterations in the Tumour and Circulation of Pancreatic Cancer Patients

  Dataset EGAD00001001421

• The genetic evolution of precursor lesions in pancreatic cancer

  Mapping genetic evolution of pancreatic cancer precursor lesions such as IPMNs and PanINs.

  Dataset EGAD00001002232

• Single Cell RNAseq of blood and tumor from renal cancer patients

  Single Cell RNAseq of blood and tumor from renal cancer patients

  Dataset EGAD00001005977

• WGS data of ALK-positiv non-small cell lung cancer patients

  268 samples with ALK-positiv non-small cell lung cancer, ultra-low coverage whole genome sequencing

  Dataset EGAD00001006298

• WES data of serially passaged TIC-enriched spheres of colorectal cancer

  WES data of serially passaged TIC-enriched spheres of colorectal cancer (CRC)

  Dataset EGAD00001006266

• Whole genome bisulfite sequencing of prostate cancer samples upon oral pimonidazole administration

  Whole genome bisulfite sequencing of prostate cancer samples upon oral pimonidazole administration

  Dataset EGAD50000000099

• Genome-wide NanoRCS sequencing of cfDNA and ctDNA from liquid biopsies of healthy individuals and cancer patients

  Levels of circulating tumor DNA (ctDNA) in liquid biopsies may serve as a sensitive biomarker for real-time, minimally-invasive tumor diagnostics and monitoring. However, detecting ctDNA is challenging, as much fewer than 5% of the cell-free DNA in the blood typically originates from the tumor. To detect lowly abundant molecules, extremely sensitive sequencing methods are required. We developed a new technique, NanoRCS, which is based on Oxford Nanopore sequencing of concatenated copies of a single DNA molecule for genome-wide sequencing, and applied this to plasma of healthy individuals, Esophageal cancer patients and Granulosa cell tumor patients and ascites of Ovarian cancer patients. We also sequenced these samples on Illumina Novaseq, to compare the two techniques.

  Study EGAS50000000154

• Analysis of Recurrently Protected Genomic Regions in Urine Cell-Free DNA

  This study investigated fragmentation patterns in urine and plasma cell-free DNA and evaluated the relevance of such analysis for cancer diagnostics using urine samples. Specifically, we performed whole-genome sequencing at variable depths and evaluated genome-wide coverage in urine and plasma samples, relative to known genome annotation features. Tumor/germline exome sequencing data included was used to identify genome-wide copy number changes and their effect on cfDNA fragmentation in corresponding genomic regions in urine samples. Data included in this submission is whole-genome sequencing of urine and/or plasma cell-free DNA from healthy volunteers and/or cancer patients, and whole-exome sequencing of tumor DNA and germline DNA (peripheral blood cells) from cancer patients. 

  Study phs002273

• DAC for Early detection of ovarian cancer using cell-free DNA fragmentomes and protein biomarkers

  Ovarian cancer is a leading cause of death from gynecological malignancies worldwide. No effective screening methods exist resulting in tumor detection at advanced stages where treatment is less effective. In this study, we used whole-genome cell-free DNA (cfDNA) fragmentome and protein biomarker (CA-125 and HE4) analyses to evaluate 591 women, mostly post-menopausal, from the European Union or the United States with ovarian cancer, benign adnexal masses, or without ovarian lesions. Using a machine learning model that incorporated multi-analyte fragmentome data and protein measurements, we evaluated the detection of ovarian cancer in two clinical settings, detection of ovarian cancers among a healthy population, and classification of adnexal masses as benign or malignant. The combined approach detected ovarian cancer with specificity >99% and sensitivity of 72%, 69%, 87%, and 100% for stages I–IV, respectively (AUC=0.96, 95% CI: 0.94-0.99), including 90% of high grade serous ovarian cancers. At the same specificity, CA-125 alone detected 34%, 62%, 63%, and 100% of ovarian cancers for stages I–IV (p=0.001, two-sided test of equal proportions). Additionally, our approach differentiated benign masses from ovarian cancers with high accuracy (AUC of 0.88, 95% CI=0.83-0.92). These results were validated in an independent population. These findings show that integrated cfDNA fragmentome and protein analyses detect ovarian cancers with high performance, enabling a new accessible approach for noninvasive ovarian cancer screening and diagnostic evaluation.

  Dac EGAC50000000332

• Cancer_Genome_Project_Exome_Sequencing

  Agilent whole exome hybridisation capture was performed on genomic DNA derived from cancer and matched normal DNA from the same patients. Next Generation sequencing performed on the resulting exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes. Now we aim to re find and validate the findings of those exome libraries using bespoke pulldown methods and sequencing the products.

  Study EGAS00001000301

• Spontaneous mutations in the single TTN gene represent high tumor mutation burden

  Tumor mutation burden (TMB) is an emerging biomarker, whose calculation requires targeted sequencing of many genes. We investigated if the measurement of mutation counts within a single gene is representative of TMB. Whole exome sequencing (WES) data from the pan-cancer cohort (n=10,224) of TCGA, and targeted sequencing (tNGS) and TTN gene sequencing from 24 colorectal cancer samples (AMC cohort) were analyzed.

  Study EGAS00001004009

• Sequence data from stage I of the CCTG BR.36 ctDNA-directed, multi-center phase II study of molecular response adaptive immunotherapy in non-small cell lung cancer

  The dataset for the study "Early ctDNA molecular response captures therapeutic response in the first stage of CCTG BR.36 ctDNA-directed, multi-center phase II study of molecular response adaptive immunotherapy in non-small cell lung cancer", includes 134 bam files from hybrid capture targeted error-correction next-generation sequencing (PGDx Elio plasma resolve) from plasma cell-free DNA and matched white blood cell DNA from 35 individuals with non-small cell lung cancer on the BR.36 trial, alongside 11 bam files from targeted next generation sequencing (PGDx Elio tissue complete) of tumor DNA from 11 individuals with non-small cell lung cancer on the BR.36 trial.

  Dataset EGAD00001011359

• SDH_deficient_renal_tumours___RNA_

  Succinate dehydrogenase (SDH) deficient renal cancers are a rare and understudied subtype of renal cancer. As such they represent an unmet need in kidney cancer research. Here, we seek to describe the genomics and transcriptomics of SDH deficient renal cancers by sequencing five such tumours. We document their mutational burden, define driver mutations, demonstrate typical patterns of structural variants, and estimate the cell of origin and cellular composition.

  Study EGAS00001004103

• Sensitive circulating tumor DNA based residual disease detection in epithelial ovarian cancer

  In this study we implemented a circulating tumor DNA (ctDNA) based blood test for more accurate post-operative surveillance of this disease. We analyzed 264 plasma samples collected between June 2016 and September 2021 from 63 epithelial ovarian cancer patients using tumor-guided plasma cell-free DNA analysis to detect residual disease after treatment. Assay specificity was verified using cross-patient analysis of 1195 control samples.

  Study EGAS50000000245

• Large scale familial CRC exome sequencing study

  The burden of rare disruptive mutations to the heritable risk of colorectal cancer

  Study EGAS00001001666

• ALK inhibitors in the context of ALK-dependent cancer cell lines

  ALK inhibitors in the context of ALK-dependent cancer cell lines

  Dataset EGAD00001000078

• Matched breast cancer fusion gene study

  Matched breast cancer fusion gene study

  Dataset EGAD00001000097

• Genomic Alterations in Gingivo-buccal Cancer: ICGC-India Project_YR01

  Genomic Alterations in Gingivo-buccal Cancer: ICGC-India Project_YR01

  Dataset EGAD00001000272

• Sequencing data for Australian Ovarian Cancer study submitted 20121116

  Sequencing data for Australian Ovarian Cancer study submitted 20121116

  Dataset EGAD00001000293

• Sequencing data for Australian Pancreatic Cancer study submitted 20130102

  Sequencing data for Australian Pancreatic Cancer study submitted 20130102

  Dataset EGAD00001000323

• Whole exome sequence of biliary tract cancer

  Fastq files of 239 samples of biliary tract cancer

  Dataset EGAD00001001076

• TP53 in ovarian cancer panel aligned reads Data Access Committee

  TP53 targeted panel aligned reads consisting of BAM paired end reads from ovarian cancer tumor samples Data Access Committee

  Dataset EGAD00001003119

• Ovarian cancer organoid biobank - followup

  WGS of more samples in the ovarian cancer organoid biobank dataset.

  Dataset EGAD00001005707

• Sequence of breast cancer bone metastases PDX from 2 targeted panels

  Sequence of breast cancer bone metastases PDX obtained by 2 targeted panels

  Dataset EGAD00001010860

• Geographic variation of mutagenic exposures in kidney cancer genomes – filtered vcf files (Mutographs)

  Geographic variation of mutagenic exposures in kidney cancer genomes – filtered vcf files (Mutographs)

  Dataset EGAD00001012222

• Geographic variation of mutagenic exposures in kidney cancer genomes – patient metadata files (Mutographs)

  Geographic variation of mutagenic exposures in kidney cancer genomes – patient metadata files (Mutographs)

  Dataset EGAD00001012223

• Geographic variation of mutagenic exposures in kidney cancer genomes – copy number variants (Mutographs)

  Geographic variation of mutagenic exposures in kidney cancer genomes – copy number variants (Mutographs)

  Dataset EGAD00001013727

• Early ctDNA molecular response captures therapeutic response in the first stage of CCTG BR.36 ctDNA-directed, multi-center phase II study of molecular response adaptive immunotherapy in non-small cell lung cancer

  Study EGAS00001007298

• Characterising the evolutionary dynamics of cancer proliferation in single-cell clones with SPRINTER

  Characterising the evolutionary dynamics of cancer proliferation in single-cell clones with SPRINTER

  Dataset EGAD00001015411

• Genomic Alterations in Gingivo-buccal Cancer: ICGC-India Project_YR02

  As a part of the ICGC, India has undertaken genomic studies on gingivobuccal cancer of the oral cavity, which is the most prevalent form of cancer among men in India. There are various known environmental (life-style) correlates of this cancer, the most important of which are tobacco chewing and HPV infection. Paired DNA samples – isolated from the tumour tissue and from the blood of fifty six patients – have been analyzed to catalog germline and somatic mutations. Association between each observed genomic alteration and exposure to environmental risk factors is being explored.Detailed clinical characterization of the patients, collection of data on demographic and environmental exposures, and isolation of DNA samples from blood and tumour tissues collected from each patient are being done at the Advanced Centre for Research, Treatment and Education on Cancer, Mumbai. Exome capture and deep resequencing are being performed at the National Institute of Biomedical Genomics, Kalyani. We have analyzed the exomes of paired blood and tumour DNA samples using exome capture by Illumina TrueSeq Exome Enrichment kit followed by sequencing on Illumina HiSeq-2000. Each exome is being sequenced at a mean depth of 70x for Tumour and 40x for Blood. In addition, we have used Illumina Omni 2.5 SNP-chips to generate genotype data.

  Study EGAS00001001028

• Rapid identification of somatic genome rearrangements as personalized biomarkers for blood-based cancer monitoring

  Increasing evidence shows the value of circulating tumour DNA (ctDNA) to detect cancer and monitor its progression. Somatic genomic structural variations (SVs) are promising personalized biomarkers for sensitive and specific detection of ctDNA in liquid biopsies. However, accurate, affordable, and fast identification of such SV biomarkers is challenging, which hinders routine use in the clinic. Here, we demonstrate a novel approach - termed SHARC - for rapid discovery of somatic SV breakpoints as personalized tumour biomarkers. SHARC combines low-coverage cancer genome sketching by using Oxford Nanopore portable sequencing with a random forest classification and a dedicated filtering pipeline to enrich for somatic SVs. Our method leverages the real-time and long-read capabilities of Nanopore sequencing to identify somatic SV breakpoints at nucleotide resolution from a tumour biopsy within two days. We applied SHARC to tumour samples of high-grade ovarian and prostate cancer and validated on average 10 somatic SVs per sample with the use of PCR mini-amplicons. Finally, we demonstrate that these somatic SV biomarkers can be used to detect tumour presence from liquid biopsies in a quantitative manner and we retrospectively monitored treatment response in patients with prostate cancer, demonstrating its potential benefit for clinical practice.

  Study EGAS00001003963

• Quantitative analysis of a novel DNA hypermethylation panel for lung cancer diagnosis using bronchial specimens

  Non-diagnostic findings in Transbronchial Lung Biopsy (TBLB) and Endobronchial Ultrasound-guided Transbronchial Lung Biopsy (EBUS-TBLB) are not uncommon. A challenge is to improve lung cancer detection by TBLB/EBUS-TBLB. In order to improve the diagnostic yield of bronchoscopy, we used 850K methylation chip to identify methylation sites that distinguish malignant from benign lung nodules.We found that the combination of HOXA7, SHOX2,and SCT methylation analysis has the best diagnostic yield in 123 bronchial washing (sensitivity: 74·1%; AUC: 0·851) and 172 brushing samples (sensitivity: 86·1%; AUC: 0·915). We developed a kit comprising these three genes and validated the kit in 329 unique bronchial washing samples, 397 unique brushing samples, and 179 unique patients with both washing and brushing samples. The diagnostic accuracy of the panel alone in lung cancer diagnosis was 86·9%, 91·2% and 95% in bronchial washing, brushing, and washing+brushing samples, respectively. The panel's sensitivity in combination with cytology, rapid on-site evaluation (ROSE), and histology in lung cancer diagnosis was 90·8% and 95.8% in bronchial washing and brushing samples, respectively, and 100% in washing+brushing samples. Quantitative analysis of the three-gene panel improves lung cancer diagnosis by bronchoscopy.

  Study EGAS00001007089

• POT1 splice site mutant analysis

  We are interested in the contribution mutations in the Shelterin complex protein POT1 may have to the development of melanoma. We have identified a patient who carries a splice site mutation in POT1 and as part of our analysis of this gene we aim to sequence the transcriptome of this patient to see how this mutation influences splicing. RNA has been obtained from lymphocytes collected from the patient.

  Dataset EGAD00001000786

• Sequence Data for Paper: Epigenetic reprogramming during differentiation of human CD4+ T lymphocytes into memory stages

  Sequence Data of total RNA, miRNA, WGB, mRNA, NOMe, Chip (H3K27ac,H3K27me, H3K36me3, H3K4me1, H3K4me3, H3K9me3, Input)Short Desrciption: Epigenetic profiling of human CD4+ memory T cells reveals their proliferative history and argues in favor of a progressive differentiation model driven by epigenetically controlled master regulators.

  Dataset EGAD00001001865

• Glioblastoma CRISPR Screen (2017-04-27)

  This is an in vitro genome-wide CRISPR/cas9 screen in human glioblastoma stem cells, screening for genes essential for survival of these cells. These cells express cas9 and have been transfected with a guide RNA library causing gene knockouts. We will analyse the sequencing data for depletion of guide RNAs. This dataset contains all the data available for this study on 2017-04-27.

  Dataset EGAD00001003308

• Capture Hi-C on Hodgkin lymphoma

  In situ promoter capture Hi-C on Hodgkin lymphoma cell line L-428 in experimental triplicates. Hi-C libraries were prepared as previously described (Orlando et al., 2018, https://currentprotocols.onlinelibrary.wiley.com/doi/pdf/10.1002/cphg.63). Promoter capture was based on 32,313 biotinylated 120-mer RNA baits (Agilent). Hi-C libraries were sequenced using Illumina HiSeq 2000 technology. The files are in FASTQ format.

  Dataset EGAD00001004321

• BASIS miRNA data

  399 tumors profiled using Agilent miRNA microarrays (Product Number G4872A, design ID 046064). The arrays are based on miRBase release 19.0 and 2006 human miRNAs are represented. 150 ng total RNA was used as input.

  Dataset EGAD00010000917

• Glioblastoma CRISPR Screen (2016-06-02)

  This is an in vitro genome-wide CRISPR/cas9 screen in human glioblastoma stem cells, screening for genes essential for survival of these cells. These cells express cas9 and have been transfected with a guide RNA library causing gene knockouts. We will analyse the sequencing data for depletion of guide RNAs. This dataset contains all the data available for this study on 2016-06-02.

  Dataset EGAD00001002158

• TTV018 RORC IBD-associated genotype effects on RORgT expression and function in ex vivo T cells

  RNA sequencing of peripheral immune cells from patients +/- an IBD risk variant. Peripheral immune cells +/- in vitro test compound treatment. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001002233

• Next Generation Sequencing Characterization of Tregs in Human Peripheral Blood during Autoimmunity

  Tregs were sorted as CD4+CD25+CD127- cells from peripheral blood of 14 healthy individuals, 8 patients with systemic lupus erythematosus, 9 patients with rheumatoid arthritis, and 11 patients with multiple sclerosis. RNA was extracted and polyA libraries were prepared using the Illumina Truseq sample preparation kit v.2. Single-end sequencing was performed on NextSeq500.

  Dataset EGAD00001006193

• SARS-CoV2 nasal epithelium

  Single cell RNA sequence generated from human primary nasal epithelium differentiated at air-liquid interface. This dataset comprises tissue from two donors, with cultures either unexposed or exposed to SARS-CoV2. Libraries were prepared using the 10X Genomics pipeline as per manufacturer's instructions.

  Dataset EGAD00001008159

• WGS data for 67 patient cohort

  This dataset includes WGS data of samples from our paper titled "Dynamic phenotypic heterogeneity and the evolution of multiple RNA subtypes in Hepatocellular Carcinoma: The PLANET study." (National Science Review, nwab192. https://doi.org/10.1093/nsr/nwab192)

  Dataset EGAD00001008647

• MPM patients

  - RNA-sequencing data: 5 normal pleurae and 40 malignant pleural mesotheliomas - Targeted DNA-sequencing of the 165 genes included in the “Solid and Haematological tumors” panel (BRIGHTCore, Brussels, Belgium): 6 MPM samples. 2 FASTQ files for each sample (paired).

  Dataset EGAD00001008740

• RNAseq before and after cold pressor test

  The cold pressor test (CPT) is a widely used pain provocation test to investigate both pain tolerance and cardiovascular responses. Twenty-two females were phenotypically assessed before and after a CPT, and blood samples were taken for RNA-sequencing. Files were processed and quantified with kallisto v0.42.5 using the human reference transcriptome (Gencode Release 28). Countdata was rlog-transformed.

  Dataset EGAD00001009649

• TRACERx NSCLC - Multiregion RNA sequencing data from the 421 cohort

  RNAseq data from the TRACERx 421 cohort

  Dataset EGAD00001009862

• SMARTer bulk RNA sequencing for highly purified CD271+ BMSCs from NBM and AML

  bulk RNAseq was conducted on highly purified CD45 - CD71 - CD235a - CD31 - CD271 + BMSCs isolated from a cohort of newly diagnosed 62 AML patients, uniformly treated within an intensive chemotherapy clinical trial and selected to represent the mutational landscape of AML

  Dataset EGAD00001011056

• Sequencing data for oesophageal and related samples - Nowicki-Osuch, Zhuang et al (scRNA)

  Data supporting: “Single-cell RNA sequencing unifies developmental programs of Esophageal and Gastric Intestinal Metaplasia.” Nowicki-Osuch, Zhuang et al. scRNAseq (FASTQ files) 59 samples

  Dataset EGAD00001010074

• nanostring_gene_expression

  Two to four sections of 10 µm thickness each (depending on sample size) from the respective formalin-fixed paraffin-embedded (FFPE) tissue sample were used for RNA isolation on 46 resected tumors as well as 17 paired biopsies. Digital gene expression analysis was performed on the NanoString nCounter platform, utilizing the NanoString MAX/FLEX system, with the PanCancer Immune Profiling panel as well as the PanCancer Pathway panel provided by NanoString.

  Dataset EGAD00010002654

• Single-sell RNA sequencing counts from 7 acute myeloid leukemia patients and 3 healthy donors

  This dataset contains count data (from 10X CellRanger) and metadata from 7 acute myeloid leukemia subjects treated with chemotherapy, as well as data from 3 healthy donors. Additionally, the dataset includes VDJ data for all subjects except for 31_base and the 3 healthy donors (TCRseq not performed).

  Dataset EGAD50000000525

• Novel Epigenetic Markers for Toxicity after Intraoperative and Conventional Radiotherapy for Breast Cancer

  Ionizing radiation is a common treatment option for cancer but its use is limited by the unpredictable and highly heterogeneous onset of late side effects, especially radiation-induced fibrosis. Clinically applicable biomarkers and effective treatments for radiation fibrosis are currently unavailable. In order to identify novel markers we ran a genome-wide DNA methylation screen in primary dermal fibroblasts obtained from breast cancer patients before intraoperative radiotherapy. Cells from patients developing fibrosis within a three-year follow up were compared to those without fibrosis (12 individuals per group). Illumina Infinium HumanMethylation450 BeadChip Technology was used.

  Study EGAS00001001279

• molecular profiles of serum-derived extracellular vesicles in high-grade serous ovarian cancer

  Patients with high-grade serous ovarian cancer (HGSC) who have no visible residual disease (R0) after primary surgery have the best clinical outcomes, followed by patients who undergo neoadjuvant chemotherapy (NACT) and have response enabling interval cytoreductive surgery. Clinically useful predictive biomarkers for such distinctions are still lacking. Extracellular vesicles (EVs) have been recognized as liquid biopsy-based biomarkers for early cancer detection and disease surveillance in other disease settings. In this study, we performed extensive molecular characterization of serum-derived EVs and correlated them with therapeutic outcomes in patients with HGSC.

  Study EGAS00001006350

• Competitive selection of somatic mutant clones in normal human skin varies with body site

  The risk of getting non-melanoma skin cancer varies over 40-fold across the body. Here we map mutations in normal skin in high and low risk sites in normal donors and those with an increased risk of skin cancer. The density of mutations varied widely, with evidence of positive and negative genetic selection.  Regional differences in mutational signatures in high and low cancer risk sites and preferential selection of mutants of TP53 in high risk skin and FAT1 in lower risk skin were observed. 10% of clones had copy number changes in cancer associated genes and the largest had multiple driver mutations with loss of heterozygosity. In hair follicles, a proposed site of origin of skin cancers, mutations in the upper follicle resembled adjacent skin, but the lower follicle was sparsely mutated. We conclude cancer risk reflects the efficiency of transformation of oncogenic mutants rather than the density of mutant clones.

  Dataset EGAD00001006194

• Functional Analysis of Genetic Variants in African Americans with Breast Cancer

  The goal of this study is to identify and characterize novel genetic variants associated with a predisposition to breast cancer (BCa) in African Americans (AAs) using a family case-family control study design. Variants of unknown clinical significance (VUS) were characterized using bioinformatics tools. Future studies will further characterize select VUSs using in vitro genomic editing methods and functional assays to determine the functional consequences. The targeted sequencing data is made available for 85 actionable cancer genes. These genes have been previously classified with deleterious mutation(s) and whose phenotype results in a specific, defined medical recommendation(s).

  Study phs002977

• Germline sequencing

  Detection of SNVs/ indels in the germline of pediatric cancer patients with a focus on CHEK2 germline variants

  Study EGAS00001006705

• Germline sequencing

  Detection of SNVs/indels in the germline of pediatric cancer patients with a focus on CHEK2 germline variants.

  Study EGAS00001006254

• Identification of cis-regulatory mutations generating de novo edges in personalized cancer gene regulatory networks

  Whole genome sequencing data on 10 human cancer cell lines

  Dataset EGAD00001003824

• GENOMIC INSTABILITY IN MISMATCH REPAIR DEFICIENT COLORECTAL CANCER WES MSI Colorectal Cancer

  This dataset contains Whole Exome Sequencing of 47 MSI colorectal cancers (CRCs) and paired adjacent normal mucosa

  Dataset EGAD00001004550