7825 results for "canc*"

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• T-WGBS for Naive B Cell

  Tagged-WGBS for 3 Naive B Cell samples of the CancerEpiSys-PRECiSe project.

  Dataset EGAD00001005966

• WGBS for T-Cell and B-Cell, control and tumor

  WGBS data for 75 paired fastq, spread over 31 samples (4 healthy T-cell, 7 healthy B-cell, 20 B-cell CLL tumors) of the CancerEpiSys-PRECiSe project.

  Dataset EGAD00001005970

• Single MII oocyte mRNA expression from women

  This dataset contains 14 paired-end FASTQ sequences from mRNA-Seq on single human M-II stage oocytes that were collected from ovarian tissue from unstimulated patients undergoing fertility preservation treatments due to cancer diagnoses, which did not influence ovarian function. Cumulus-oocyte-complexes were matured in vitro according Gruhn et al (Science 365: 1466-1469) and short term flash frozen prior to lysis, RNA extraction, full length cDNA preparation and amplification using the Ultra-low-input SMART-Seq2 v4 kit from Takara Clonetech. Further, these cDNA were used to prepare libraries for sequencing according the Nextera XT DNA library preparation kit from Illumina

  Dataset EGAD00001005971

• CYPTAM - PacBio SMRT sequencing

  Dataset contains CYP2D6 sequencing data of 566 individuals who used tamoxifen as adjuvant breast cancer therapy. Phenotype data consists of the ratio between the metabolites endoxifen and desmethyltamoxifen (Metabolic ratio (MR)) as a proxy for CYP2D6 enzyme activity. Each sample is linked to one bam-file containing the CYP2D6 sequence.

  Dataset EGAD00001005972

• Long-read sequencing of prostate adenocarcinoma metastatic to left axillary lymph node. Data used to support Figure 6 in Pubmed ID 32025007 "Pan-Cancer Analysis of Whole Genomes Consortium." Nature 2020 578:8293.

  Oxford Nanopore long-read sequencing of A17-LAxillaryLN2Met-23312 PELICAN sample, identified as D051965 un Pan-Cancer Analysis of Whole Genomes study, and identified as PD13412a by prior Gundem et al whole genome sequencing study (PMID 25830880). Data used to support Figure 6 in Pubmed ID 32025007 "Pan-Cancer Analysis of Whole Genomes Consortium." Nature 2020 578:8293.

  Dataset EGAD00001005974

• NanoString gene expression of PBMC from bladder cancer and RCC patients

  This dataset contains NanoString gene expression of PBMC from patients from IMvigor210, IMvigor211 and IMmotion150 cohorts

  Dataset EGAD00001005976

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

  Single Cell RNAseq of blood and tumor from renal cancer patients

  Dataset EGAD00001005977

• Omics data of advanced bladder cancer

  To identify the therapeutic targets in a treatment-refractory cancer patient, we performed single-cell RNA sequencing for 3,115 cells from primary bladder cancer (BC159-T#3) and patient-derived xenografts (BC159-T#3-PDX-vehicle and BC159-T#3-PDX-tipifarnib). Matched time-series bulk tumor tissues were also sequenced using whole exome target probe (WES) and whole transcriptome target probe (WTS).

  Dataset EGAD00001005978

• MutWP5: CRUK Mutographs of Cancer: Lung: PD37920 (WG) (2020-02-20)

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2020-02-20.

  Dataset EGAD00001005990

• MutWP5: CRUK Mutographs of Cancer: Lung: PD38234 (WG) (2020-02-20)

  Sequencing of LCM-derived microbiopsies from explanted lung from pulmonary fibrosis patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2020-02-20.

  Dataset EGAD00001005991

• Whole-exome sequences of ovarian clear cell carcinomas and paired normal DNA

  Whole-exome sequencing dataset for the Australian Ovarian Cancer Study (AOCS) and The Jikei University School of Medicine (JIKEI) ovarian clear cell carcinoma (OCCC) clinical outliers project, representing 10 donors. Consists of 20 fastq files: one normal and one tumour from each patient.

  Dataset EGAD00001006004

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: Colorectal_LCM (2020-02-20)

  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. . This dataset contains all the data available for this study on 2020-02-20.

  Dataset EGAD00001005994

• 108 samples liver cancer and normal controls (54 pairs), whole exome sequencing

  liver cancer paired with normal controls, viral and non-viral origin

  Dataset EGAD00001006005

• WES

  WES was performed on 2 TURP, 6 biopsies, 1 CDX, 1 cell line, 6 CTCs, 1 DNA germline and 1WBC from prostate cancer

  Dataset EGAD00001006009

• Neoantigen study samples for prostate cancer

  Whole exome sequencing and RNA sequencing data from 30 patients with prostate cancer.

  Dataset EGAD00001005713

• UCSF Pediatric Bithalamic Glioma Genome Project

  Targeted next-generation sequencing of 13 pediatric bithalamic diffuse gliomas. BAM files of targeted next-generation DNA sequencing data of 13 pediatric gliomas, with multi-region sequencing data from 2 of these cases (17 total tumor samples). Genomic DNA was extracted from formalin-fixed, paraffin-embedded blocks of tumor tissue from using the QIAamp DNA FFPE Tissue Kit (Qiagen). Capture-based next-generation DNA sequencing was performed at the University of California, San Francisco Clinical Cancer Genomics Laboratory, using an assay that targets all coding exons of 480 cancer-related genes, select introns of 47 genes, and TERT promoter with a total sequencing footprint of 2.8 Mb (UCSF500 Cancer Panel). Sequencing libraries were prepared from genomic DNA, and target enrichment was performed by hybrid capture using a custom oligonucleotide library (Nimblegen SeqCap EZ Choice). Captured libraries were sequenced as paired-end 100 bp reads on an Illumina HiSeq 2500 instrument. Duplicate sequencing reads were removed computationally to allow for accurate allele frequency determination and copy number calling.

  Dataset EGAD00001005499

• Sequencing files for "A Unifying Paradigm for Transcriptional Heterogeneity and Squamous Features in Pancreatic Ductal Adenocarcinoma."

  Files from DNA and RNA sequencing from primary tumors and metastases from pancreatic cancer patients along with matched normal tissues.

  Dataset EGAD00001005519

• Bam files for a metastatic bladder cancer patient with BAP1 variants

  This dataset consists of three bam files (two cell-free DNA and one germline DNA) from a metastatic bladder cancer patient with BAP1 variants. Bam files were generated from targeted Illumina sequencing data.

  Dataset EGAD00001005520

• Heterogeneous metabolic signatures are linked to cancer cell differentiation in colorectal cancer

  Colorectal cancer (CRC) is characterized by functional intratumor heterogeneity that shares many similarites with the hierarchical organization of the normal intestinal epithelium. In order to relate transcriptional subtypes to functional tumor cell heterogeneity we applied scRNA-seq to 12 patient-derived CRC spheroid cultures. We identified shared expression programs that relate to intestinal lineages and revealed metabolic signatures that are linked to cancer cell differentiation. In addition, we validated and complemented sequencing results by quantitative microscopy using live-dyes and multiplexed RNA fluorescence in situ hybridization, thereby revealing metabolic compartmentalization and potential cell-cell interactions. Finally, we demonstrate functional differences between metabolically distinct lineage subtypes that might have strong implications for future treatment strategies of CRC.

  Dataset EGAD00001005524

• Ovarian cancer organoid biobank - followup

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

  Dataset EGAD00001005707

• MDA whole exome sequencing data for bladder cancer

  46 BAM files from 23 urothelial bladder cancer patients on an immunotherapy clinical trial. PBMC normal samples and solid tumor samples are paired. Alignment was done by BWA with reference genome hg19.

  Dataset EGAD00001005712

• DESIGN-NKI RNA-seq

  RNA-Seq data of 36 HPV-negative HNSCC specimens from patients treated at The Netherlands Cancer Institute, Amsterdam. HNSCC biopsy samples obtained prior to treatment (chemo-radiotherapy) were used for polyA mRNA sequencing.

  Dataset EGAD00001005715

• DESIGN-NKI low coverage WGS

  Low-coverage whole genome sequencing data of 37 HPV-negative HNSCC specimens from patients treated at The Netherlands Cancer Institute. HNSCC biopsy samples obtained prior to treatment (chemo-radiotherapy) were used for WGS to a depth of approx. 0.5X.

  Dataset EGAD00001005718

• NKI-MET HNSCC RNA-Seq

  RNA-Seq data of 8 HNSCC specimens from patients diagnosed with metastatic disease at The Netherlands Cancer Institute, Amsterdam. Primary HNSCC biopsy samples obtained prior to treatment were used for polyA mRNA sequencing.

  Dataset EGAD00001005720

• ART-NKI II HNSCC RNA-Seq

  RNA-Seq data of 25 HNSCC specimens from patients treated at The Netherlands Cancer Institute, Amsterdam and enrolled in the ARTFORCE trial. HNSCC biopsy samples obtained prior to treatment (chemo-radiotherapy) were used for polyA mRNA sequencing.

  Dataset EGAD00001005721

• DESIGN II HNSCC RNA-Seq

  RNA-Seq data of 28 HPV-negative HNSCC specimens from patients treated at the Netherlands Cancer Institute (Amsterdam), VU Medical Centre (Amsterdam) or MAASTRO Clinic (Maastricht) in The Netherlands. HNSCC biopsy samples were obtained prior to treatment (chemo-radiotherapy) for the prospective study within the DESIGN project and used for polyA mRNA sequencing.

  Dataset EGAD00001005722

• Illumina short-reads and 10X Genomics linked-reads sequencing data for MCF7 and a primary breast tumor sample

  This dataset contains whole genome sequencing data from Illumina short-reads sequencing (2X150bp) and 10X Genomics linked-reads sequencing. Both the sequencing technologies were used to sequence MCF7 cell line and a primary breast triple-negative cancer sample. The fastq of paired-end reads for both the samples sequenced with both the technologies is available.

  Dataset EGAD00001005724

• WES of blood and patient-matched cecum tumor tissue samples, Panel NGS of patient-matched cfDNA

  WES using IDT xGen Research Exome on Illumina NovaSeq 2x150bp: Normal sample (buffy coat), cecum tumor biopsy at diagnosis, ileocecal valve region tumor sample at week 19, pericolonic metastasis at week 19, lymph node metastasis at week 19, peritoneal metastasis at week 19. Week 19 samples from hemicolectomy. Deep coverage cfDNA NGS using PanCeq pan-cancer panel on NextSeq 2x150bp: week 2 and week 10.

  Dataset EGAD00001005737

• Whole exome sequencing of advanced gastric cancer

  To define the cellular characteristics of malignant ascites of advanced gastric cancer patients and search for therapeutic strategies, we obtained 5 malignant ascites and 1 cerebrospinal fluid from five patients with gastric cancer. We analyzed single-cell RNA-seq data of 180 cells from 4 malignant ascites and 1 cerebrospinal fluid metastasis using Fluidigm® C1™ System. Whole exome sequencing data was also generated from blood or tumor tissue.

  Dataset EGAD00001005740

• Substantial somatic genomic variation and selection for BCOR mutations in human induced pluripotent stem cells

  Human Induced Pluripotent Stem Cells (hiPSC) are an established patient-specific model system where opportunities are emerging for cell-based therapies. We compared and contrasted hiPSCs derived from different tissues, skin and blood, in the same individual. We show extensive single-nucleotide mutagenesis in all hiPSC lines, although fibroblast-derived hiPSCs (F-hiPSCs) are particularly heavily mutagenized by ultraviolet (UV)-related damage. We utilized genome sequencing data on 454 F-hiPSCs and 44 blood-derived hiPSCs (B-hiPSCs) to gain further insights. Across 324 whole genome sequenced (WGS) F-hiPSCs derived by the Human Induced Pluripotent Stem Cell Initiative (HipSci), UV-related damage is present in ~72% of cell lines, sometimes causing substantial mutagenesis (range 0.25-15 per Mb). Furthermore, we find remarkable genomic heterogeneity between independent F-hiPSC clones derived from the same reprogramming process in the same donor, due to oligoclonal populations within fibroblasts. Combining WGS and exome-sequencing data of 452 HipSci F-hiPSCs, we identify 272 predicted pathogenic mutations in cancer-related genes, of which 21 genes were hit recurrently three or more times, involving 77 (17%) lines. Notably, 151 of 272 mutations were present in starting fibroblast populations suggesting that more than half of putative driver events in F-hiPSCs were acquired in vivo. In contrast, B-hiPSCs reprogrammed from erythroblasts show lower levels of genome-wide mutations (range 0.28-1.4 per Mb), no UV damage, but a strikingly high prevalence of acquired BCOR mutations in ~57% of lines, indicative of strong selection pressure. All hiPSCs had otherwise stable, diploid genomes on karyotypic pre-screening, highlighting how copy-number-based approaches do not have the required resolution to detect widespread nucleotide mutagenesis. This work strongly suggests that models for cell-based therapies require detailed nucleotide-resolution characterization prior to clinical application.

  Dataset EGAD00001007029

• Cryopreservation of human cancers conserves tumour heterogeneity for single-cell multi-omics analysis

  Single-cell RNA-Sequencing of three primary breast cancers, two primary prostate cancers, and a metastatic melanoma sample from Wu et al. (2021) Genome Medicine study. Each tumour was sequenced across different cryopreservation conditions including Fresh Tissue (FT), cryopreserved single-cell suspensions (CCS), cryopreserved solid tissue fragments (CT) and a cryopreserved after overnight cold storage (CO). Data was generated using the Chromium controller (10X Genomics) and sequenced on the NextSeq platform.

  Dataset EGAD00001007030

• Molecular profiling of tissue autopsies and ctDNA

  The dataset contains high-throughput sequencing data derived from a cancer autopsy series of 10 patients. As part of this study, whole-exome sequencing and RNA-seq were performed for spatially distinct tissue biopsies from the patients. In addition, plasma samples from the patients were sequenced using a custom panelt to profile ctDNA. There are 106 files containing whole-exome sequencing data, 107 files containing RNA-seq data, and 9 files containing plasma sequencing data.

  Dataset EGAD00001007040

• bladder cancer patient data

  This contains H3K27ac ChIP-seq, RNA-seq and HiC fastq files.

  Dataset EGAD00001007052

• Early breast cancer (WGS)

  Low-coverage whole genome sequencing of 29 early breast cancer samples.

  Dataset EGAD00001007056

• Early breast cancer (WES)

  Whole-exome sequencing of 30 early breast cancer samples.

  Dataset EGAD00001007057

• CITE-seq of early breast cancer

  CITE-seq of early breast cancer samples.

  Dataset EGAD00001007058

• Circulating cell-free DNA analyses for Patient Monitoring in Small Cell Lung Cancer

  This study consists of over 200 data files from cfDNA and germline DNA from 69 patients and 32 healthy normal volunteers discussed in this publication.

  Dataset EGAD00001007070

• Whole Exome Sequencing of Mixed Histology Lung Cancer

  We conducted whole-exome sequencing (WES) and microarray profiling on 19 micro-dissected tumor regions of different histologic subtypes from 9 patients with lung cancers of mixed histologic patterns including 6 LUAD, 6 LCNEC, 3 SCLC, 3 LUSC, and one poorly differentiated NSCLC-NOS.

  Dataset EGAD00001007076

• WGS of HSPC clones of healthy individual sequenced with Illumina NovaSeq 6000

  Dataset contains WGS sequecing data from clonally expanded hematopoietic stem cells from 7 individual pediatric cancer patients. Samples were taken before (DX - diagnosis) or Follow-up (DX2/REM/FU - Diagnosis 2, remission or follow-up, respectively). In addtion, cord blood clones (Designated CB) treated with X-ray radiation, Cisplatin, Maphosphamide, Vincristine and Doxorubicin and untreated cord blood hematopoietic stem/progenitor cells were have been whole-genome sequenced. (Abbreviations RAD, CISPL, MAPH, VINC, DOX and CTRL, respectively)

  Dataset EGAD00001007078

• Exome sequencing of replication repair deficient brain cancers

  This dataset contains exome sequencing from replication repair deficient brain tumor samples.

  Dataset EGAD00001006920

• Transcriptome sequencing of replication repair deficient brain cancers

  Hypermutant tumors which harbor many somatic mutations may obscure the interpretation of targetable genomic events. This dataset contains transcriptome sequencing from 21 replication repair deficient brain tumor samples as well as healthy controls.

  Dataset EGAD00001006921

• Longitudinal single-cell RNA-seq data from metastatic ovarian cancer

  Longitudinal single-cell RNA-seq data of prospectively collected tumor tissue samples before and after chemotherapy from 11 HGSOC patients.

  Dataset EGAD00001006922

• Assessment of cannabidiol and Δ9-tetrahydrocannabiol in mouse models of medulloblastoma

  These data were used in the following publication: Andradas, C.; Byrne, J.; Kuchibhotla, M.; Ancliffe, M.; Jones, A.C.; Carline, B.; Hii, H.; Truong, A.; Storer, L.C.D.; Ritzmann, T.A.; et al. Assessment of Cannabidiol and delta9-Tetrahydrocannabiol in Mouse Models of Medulloblastoma and Ependymoma. Cancers 2021, 13, 330. https://doi.org/10.3390/cancers13020330 There are 4 paired-end RNA-seq samples from paediatric brain cancer cell lines.

  Dataset EGAD00001006923

• MutWP5: CRUK Mutographs of Cancer: Lung: PD37920 (Targeted) (2021-02-02)

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Targeted sequencing will be conducted on samples to identify drivers of interest and clonality of the samples, well-performing samples will be sent for subsequent whole-genome sequencing. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006929

• MutWP5: CRUK Mutographs of Cancer: Lung: PD38233 (WG) (2021-02-02)

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006930

• MutWP5: CRUK Mutographs of Cancer: Lung: PD43291_Novaseq (Exome) (2021-02-02)

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutaiton burden in different portions of the lung. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this poriton of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006932

• MutWP4: CRUK Grand Challenge Mutographs of Cancer: Pancreatic Organoids (2021-02-02)

  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, Kings College London will characterise the mutational signatures induced by putative human carcinogens in order to identify the origins of mutational signatures found in human cancers. To achieve this human organoid cell cultures will be exposed to a representative catalogue of known or suspected human carcinogens and mutagens and, using whole genome sequencing, the patterns of mutations induced by them will be determined. Somatic mutational signatures will be subsequently extracted by non-negative matrix factorisation methods and correlated with exposure 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 2021-02-02.

  Dataset EGAD00001006933

• Exome Sequencing of Gastric Cancer Samples

  We perform whole exome sequencing on 50 pairs of gastric cancer and matched normal samples.

  Dataset EGAD00001006957

• Bulk tumor RNAseq of bladder cancer patients

  RNAseq fastq files from 611 bulk pre-treatment tumors from two indications: metastatic urothelial bladder cancer patients (IMvigor210) and metastatic renal cell carcinoma (IMmotion150)

  Dataset EGAD00001006960

• Whole-genome sequencing of gastric cancer with peritoneal metastasis

  Whole-genome sequencing of 135 tumor samples and 98 normal samples of gastric cancer with peritoneal metastasis

  Dataset EGAD00001006963

• MicroRNA profiling by next-generation sequencing for colorectal cancer screening

  The dataset contains raw miRNA sequencing data of plasma samples from 20 newly diagnosed colorectal cancer cases and 20 controls free of colorectal neoplasms matched by age and sex. It includes files in the FASTQ compressed (.gz) format.

  Dataset EGAD00001006966

• UROMOL 2020 - RNA-seq data validation

  For this project about non-muscle invasive bladder cancer (NMIBC), we analysed total RNA-seq data from 47 patients used for validation. Sequencing of total RNA was performed using KAPA RNA HyperPrep Kit with RiboErase HMR (Roche). RNA input was 100 to 500 ng. The dataset is composed of 94 fastq files.

  Dataset EGAD00001006967

• Targeted sequencing of Human esophageal epithelium microbiopsies

  NOTCH1 mutant clones occupy the majority of normal human esophagus by middle age, but are comparatively rare in esophageal cancers, suggesting NOTCH1 mutations may promote clonal expansion but impede carcinogenesis. Here we test this hypothesis. Visualizing and sequencing NOTCH1 mutant clones in aging normal human esophagus, reveals frequent biallelic mutations that block NOTCH1 signaling.  In mouse esophagus, heterozygous Notch1 mutation confers a competitive advantage over wild type cells, an effect enhanced by loss of the second allele.  Notch1 loss alters transcription but has minimal effects on epithelial structure and cell dynamics. In a carcinogenesis model, Notch1 mutations were less prevalent in tumors than normal epithelium. Deletion of Notch1 reduced tumor growth, an effect recapitulated by anti-NOTCH1 antibody treatment.  We conclude that Notch1 mutations in normal epithelium are beneficial as wild type Notch1 promotes tumor expansion. NOTCH1 blockade has therapeutic potential in esophageal squamous tumors.

  Dataset EGAD00001006969

• Clinical phenotype data

  Clinical data corresponding to the patients with ovarian cancer studied using scRNA-seq and bulk RNA-seq. Variables include molecular subtype, predicted immune phenotype, reviewing pathologist comment, final immune phenotype, histology characterization, and tumor stage.

  Dataset EGAD00001006973

• scRNA-seq using 10X Genomics platform

  Matrices of counts from single-cell RNA-seq data for 15 samples from patients with ovarian cancer, 5 samples for each of the 3 tumor immune phenotypes (Infiltrated, Excluded and Desert). Dissociated cells from each tumor sample have been sorted to isolate live cells from the 3 compartments: tumor, immune and stromal. Each of the compartments has been analyzed separately by scRNAseq, excluding some desert tumors for which cells from the stromal and immune compartments have been pooled. Sequencing was performed using 10X Genomics Chromium Single Cell platform (v2 Chemistry).

  Dataset EGAD00001006974

• Bulk RNAseq fastq files

  RNAseq FASTq files from 15 samples from patients with ovarian cancer, 5 samples for each of the 3 tumor immune phenotypes (Infiltrated, Excluded and Desert).

  Dataset EGAD00001006975

• HER2-negative primary breast cancers WES

  Temporal HER2-negative breast cancers WES

  Dataset EGAD00001006980

• Breast Cancer TNBC Single-Cell RNA-Seq Dataset

  Single-cell RNA-Sequencing of five TNBC primary breast cancers from Wu et al. (2020) EMBO J study. Data was generated using the Chromium controller (10X Genomics) and sequenced on the NextSeq 500 platform.

  Dataset EGAD00001006981

• Single-cell RNA-seq data from metastatic ovarian cancer for quality control study

  This study includes treatment-naïve fresh tissue sample from 4 HGSOC patients.

  Dataset EGAD00001006984

• Single-cell gene expression data from CD8+ T cells from two Austrian COVID19 patients stimulated with wildtype and mutant SARS-Cov-2 peptides

  The data contains single-cell gene sequencing data (10x Genomics) from FACS-purified CD8 T lymphocytes from two Austrian patients. The cells were stimulated with one MHC class I peptides obtained from a common (wild type) variant and an emerging mutant variant of the SARS-Cov-2 virus. Then the samples were multiplexed using hashtag oligos. We provide the raw and aligned sequence data for: i. The single-cell experiments ii. The PCR-amplified samples for enrichment of the hashtag oligo multiplexing barcodes iii. The PCR-amplified samples for enrichment of the T Cell Receptor (TCR) VDJ region for immuno-profiling. The samples and libraries were processed and obtained in collaboration between St. Anna Children's Cancer Research Institute (CCRI), CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, and the Medical University of Vienna. The cell barcodes and processed data has been submitted to the GEO database with GEO accession GSE166651.

  Dataset EGAD00001006995

• WES_SCLC_MDACC

  To identify genomic drivers present in limited-stage small cell lung cancer (LS-SCLC); To determine the overall tumor mutational burden in LS-SCLC; To determine genomic intratumor heterogeneity (ITH) in LS-SCLC.

  Dataset EGAD00001007004

• RNA-sequencing of primary urothelial bladder cancer samples

  Paired-end RNA-sequencing of tumour tissue samples (n=85) from primary urothelial bladder cancer patients. Sequencing was performed using either HiSeq (n=27) or NextSeq (n=58) Illumina platforms. Of the 85 samples, 78 are Non-muscle invasive (NMIBC) and 7 are Muscle invasive (MIBC).

  Dataset EGAD00001007005

• hereditary BrEAst Case CONtrol study (BEACCON)

  The BEACCON study aimed to address the lack of power of previous studies to identify novel BC predisposition genes by performing extensive sequencing in 12,000 women (11,511 analysed following exclusions) and further enhancing power by using an ‘extreme phenotype’ design with enrichment of familial non-BRCA1 and BRCA2 cases, compared with a control population of older women with ongoing confirmation of cancer-free status at June 2019. Three-quarters of the 1303 candidate genes screened were selected based on empiric evidence from local (69 multi-case BC families) or international whole exome sequencing studies, and the remainder were included to provide detailed coverage of functional pathways with established associations with BC.

  Dataset EGAD00001007025

• Sequencing of Plasma DNA from breast cancer patients

  Dataset contains plasma DNA whole genome sequencing on 4 breast cancer patients. It also includes matched germline and tumour whole genome sequencing data. Two benign cancer patients were also sequenced and their plasma DNA and matched germline whole genome sequencing data are included in the dataset. Samples were sequenced on Illumina HiSeqX Ten.

  Dataset EGAD00001006869

• Cell-free DNA TAPS provides multimodal information for early cancer detection

  TAPS data from 21 patients with HCC, 23 patients with PDAC, 30 non-cancer controls, 4 patients with cirrhosis, and 7 patients with pancreatitis.

  Dataset EGAD00001006871

• Targeted amplicon sequencing on 218 samples from Stage 1 epithelial ovarian cancer biopises

  BAM files (aligned against the hg38 genome) from a targeted amplicon sequencing (139 genes) experiment (median depth 1000X) on 218 samples from Stage 1 epithelial ovarian cancer biopises. Samples labeled "bis" or "tris" with the same ID are relapses; "left" or "right" samples indicate, in the case of bilateral tumor, from which ovary the sample was taken.

  Dataset EGAD00001006873

• Multi-region WGS of a RET fusion positive cancer

  high depth WGS sequencing of 8 sites of a RET fusion tumour

  Dataset EGAD00001006878

• Evaluation of capture and amplicon-based targeted sequencing methods on formalin-fixed tumours

  Three capture (Agilent’s SureSelectXT HS, Illumina’s Nextera Rapid Capture Custom, and New England Biolabs’ Next Direct Custom) and one amplicon-based (Qiagen’s Human Breast Cancer Panel) targeted sequencing methods on 6-8 paired blood and FFPE from the Malaysian Breast Cancer Cohort.

  Dataset EGAD00001006879

• Shallow whole genome sequencing on stage 1 epithelial ovarian cancer

  BAM files (aligned against the hg38 genome) from a shallow whole-genome sequencing experiment (median depth 0.5X) on 218 samples from Stage 1 epithelial ovarian cancer biopises. Samples labeled "bis" or "tris" with the same ID are relapses; "left" or "right" samples indicate, in the case of bilateral tumor, from which ovary the sample was taken.

  Dataset EGAD00001006881

• Panel sequencing data of IMPACT2 patients

  Patient samples were sequenced by Foundation Medicine, Inc. (Cambridge, MA), using FoundationOne CDx, a comprehensive NGS-based in vitro diagnostic device designed to capture cancer genes.

  Dataset EGAD00001006887

• Nanopore sequencing from liquid biopsy: analysis of copy number variations from cell-free DNA of lung cancer patients

  Molecular cancer paper (https://doi.org/10.1186/s12943-021-01327-5): This dataset contain shallow whole-genome sequencing (sWGS) of plasma cell-free DNA from cancer patients and healthy subjects, obtained with both Nanopore and Illumina technology. A total of 6 cancer patients and 5 healthy subjects have been sequenced with Nanopore; 4 of the cancer patients have been also sequenced with Illumina. In addition, genomic DNA from white blood cells of one healthy subjects, genomic and 160bp DNA from HEK cells have been sequenced with Nanopore. Genome Biology paper: 3 additional healthy samples have been sequenced (HU), two different bioinformatic pipeline were applied. 2019: Fastqs from the molecular cancer paper were re-demultiplexed and adapter-trimmed (using guppy for multiplex samples, and porechop for singleplex) preserving 5' ends to allow fragmentomics analysis. HAC: All the samples were basecalled with the same updated High Accuracy model (the latest at the time of the analysis) and post-processed as the 2019 dataset. Raw FAST5 are currently available upon request, but will be uploaded soon.

  Dataset EGAD00001006888

• PIK3CA SiMSen-Seq

  Simple, Multiplexed, PCR-based barcoding of DNA for Sensitive mutation detection using Sequencing (SiMSen-Seq) of 11 PIK3CA hotspot mutations in plasma DNA of breast cancer patients.ng

  Dataset EGAD00001006897

• Single cell sequencing of ovarian cancer

  Single cell sequencing of 12 ovarian cancer biopsies from 7 patients.

  Dataset EGAD00001006898

• RNA of peripheral blood for pancreatic cancer and chronic pancreatitis

  Samples of nucleated cells found in peripheral blood from over 300 patients suffering from resectable pancreatic ductal adenocarcinoma, non-resectable pancreatic cancer, chronic pancreatitis, or none of these. Please cite this article when using data: Al-Fatlawi, A.; Malekian, N.; García, S.; Henschel, A.; Kim, I.; Dahl, A.; Jahnke, B.; Bailey, P.; Bolz, S.N.; Poetsch, A.R.; Mahler, S.; Grützmann, R.; Pilarsky, C.; Schroeder, M. Deep Learning Improves Pancreatic Cancer Diagnosis Using RNA-Based Variants. Cancers 2021, 13, 2654. https://doi.org/10.3390/cancers13112654

  Dataset EGAD00001006915

• Single cells of colorectal cancer organoids

  458 single cell samples of multiple colorectal cancer organoids

  Dataset EGAD00001007305

• SPECTA Lung cancer VCF files

  SPECTA Lung cancer VCF files

  Dataset EGAD00001006260

• RNA-Seq of serially passaged TIC-enriched spheres of colorectal cancer

  18 samples of RNA-Seq of serially passaged TIC-enriched spheres of colorectal cancer (CRC), sequenced on HiSeq2000 and HiSeq2500

  Dataset EGAD00001006264

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

  WGS data of serially passaged TIC-enriched spheres of colorectal cancer

  Dataset EGAD00001006265

• 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

• Single cell transcriptomes of of primary tumors and normal endometrial derived organoids treated with DBZ

  Endometrial carcinoma, the most common gynecologic cancer, develops from endometrial epithelium which is composed of secretory and ciliated cells. Pathologic classification is unreliable and there is a need for prognostic tools. We used single cell sequencing to study organoid model systems derived from normal endometrial endometrium to discover novel markers specific for endometrial ciliated or secretory cells. We performed single cell sequencing on endometrial and ovarian tumours, and on organoids both treated with DBZ and normal and found both secretory-like and ciliated-like tumour cells.

  Dataset EGAD00001006280

• Shallow whole genome sequencing from plasma DNA of BC, CRC and NSCLC patients

  This is the raw data obtained from shallow whole-genome sequencing of plasma DNA (plasma-Seq) for calling of somatic copy number alterations as well as focal amplifications and deletions from patients with breast, colorectal and non-small cell lung cancer.

  Dataset EGAD00001006288

• Raw sequencing data of PERMED-01 trial

  Targeted sequencing (t-NGS) of frozen advanced cancers tissue was established with three panels covering 395 to 560 candidate cancer genes. Sequencing was done using the 2x150-bp paired-end technology on the Illumina MiSeq and NextSeq500 platforms. The DNA libraries of all coding exons were done with the HaloPlex Target Enrichment System (Agilent, Santa Clara, CA, USA).

  Dataset EGAD00001006289

• Characterization of four subtypes in morphologically normal tissue excised proximal and distal to breast cancer

  RNA sequencing data from breast cancers (n=18) and their matched HN tissues (n=36), healthy breast from cosmetic reduction mammoplasty (RM; n=5), and risk reducing mastectomies (RR, n=5), with peritumoral samples excised proximal to (TP, less than 2 cm) and distal from (TD, 5-10 cm) the primary tumor.

  Dataset EGAD00001006291

• ctDNA monitoring using patient-specific sequencing and integration of variant reads - Breast cohort

  Circulating tumor-derived DNA (ctDNA) can be used to monitor cancer dynamics noninvasively. Detection of ctDNA can be challenging in patients with low-volume or residual disease, where plasma contains very few tumor-derived DNA fragments. We show that sensitivity for ctDNA detection in plasma can be improved by analyzing hundreds to thousands of mutations that are first identified by tumor genotyping. We describe the INtegration of VAriant Reads (INVAR) pipeline, which combines custom error-suppression methods and signal-enrichment approaches based on biological features of ctDNA. With this approach, the detection limit in each sample can be estimated independently based on the number of informative reads sequenced across multiple patient-specific loci. We applied INVAR to custom hybrid-capture sequencing data from 176 plasma samples from 105 patients with melanoma, lung, renal, glioma, and breast cancer across both early and advanced disease. By integrating signal across a median of >105 informative reads, ctDNA was routinely quantified to 1 mutant molecule per 100,000, and in some cases with high tumor mutation burden and/or plasma input material, to individual parts per million. This resulted in median Area Under the Curve (AUC) values of 0.98 in advanced cancers, and 0.80 in early stage and challenging settings for ctDNA detection. We generalized this method to whole-exome and whole-genome sequencing, showing that the INVAR may be applied without requiring personalized sequencing panels, so long as a tumor mutation list is available. As tumor sequencing becomes increasingly performed, such methods for personalized cancer monitoring may enhance the sensitivity of cancer liquid biopsies.

  Dataset EGAD00001006293

• Somatic mutations and single cell transcriptomes reveal the root of malignant rhabdoid tumours

  Like many childhood cancers, malignant rhabdoid tumours (MRT) are thought to arise from aberrant foetal development. Although MRT predominantly exhibit a mesenchymal phenotype, it has been suggested that the foetal root of MRT lies in neural crest development. Here, we combine phylogenetic analyses of MRT, single cell mRNA assays, and functional experiments in patient-derived MRT organoids, to define the embryological origin of MRT and explore therapeutic avenues that may drive MRT differentiation. Phylogenetic analyses from the distribution of somatic mutations revealed that MRT were related to neural crest-derived, but not to mesodermal tissues, providing direct evidence of the neural crest origin of MRT in humans. In MRT organoids, reversal of the principal driver event underpinning MRT, SMARCB1 loss, induced differentiation along mesenchymal pathways. Together, these findings placed MRT cells on a developmental trajectory of neural crest to mesenchyme conversion, and defined the transcriptional changes underpinning MRT differentiation. Searching perturbation databases for agents that mimic these mRNA changes, we identified HDAC and mTOR inhibition as potential differentiation agents. Treatment of MRT organoids with this drug combination induced proliferation arrest with transcriptional changes akin to SMARCB1 re-expression. Our study defines the embryological root of MRT and proposes a differentiation treatment for this often fatal childhood cancer.

  Dataset EGAD00001006296

• 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

• 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

• Genomic and transcriptomic data of glioma specimens

  Dataset consists of 207 glioma samples of WHO grades II, III and IV. Dataset consists 182 tumor derived genomic data of ~700 cancer-related and epigenetic-related genes with matched blood samples for 48 specimens. Dataset also consists transcriptomic data for 105 specimens. In total 335 bam files were deposited.

  Dataset EGAD00001006299

• AVENIO Expanded ctDNA panel sequence alignments (BAMs) from plasma DNA of BC, CRC and NSCLC patients

  The AVENIO ctDNA Expanded Kit is a next-generation sequencing (NGS) liquid biopsy assay with a 77 gene panel (192 kb) containing genes in U.S. National Comprehensive Cancer Network (NCCN) Guidelines and emerging cancer biomarkers. This pan-cancer assay was applied to 48 plasma samples from patients with breast, colorectal and non-small cell lung cancer. After sequencing 150bp paired-end, reads were aligned to the hg38 genome with the AVENIO Oncology Analysis Software (version 2.0). These files are the deduplicated alignments generated by the analysis software used for subsequent variant, indel and CNV calling.

  Dataset EGAD00001006301

• RNA-SEQ for the Caldas Lab breast cancer PDTX collection

  RNA-SEQ for the Caldas Lab breast cancer PDTX collection. This includes both single and paired end runs

  Dataset EGAD00001006307

• WGS and WES of Advance Prostate Cancer

  The dataset consists of BAM files of 2 pairs of matched tumor/normal samples of a men with advanced prostate cancer. One pair is whole genome sequencing: WGS_T/WGS_N for tumor and normal samples, respectively; and the other pair is whole exome sequencing: WES_T/WES_N for tumor and normal specimens, respectively. Details can be found at the publication titled: "Molecular Medicine Tumor Board: Whole Genome Sequencing to Inform on Personalized Medicine for a Man with Advanced Prostate Cancer"

  Dataset EGAD00001006487

• Transcriptomic profiling of prostate cancer metastasis xenograft models

  RNA-seq profiling of 2 prostate cancer xenograft mouse models, each at the intact state (n=3), castrated state (n=4) and castrated + AR replacement (n=3).

  Dataset EGAD00001006551

• Lung cancers from admixed Latin American populations (1)

  Raw data from cancer panel sequencing of lung adenocarcinomas from admixed Latin American populations. Predominantly samples carrying known oncogene mutations (n=581).

  Dataset EGAD00001006552

• The Precision Medicine in Liver Cancer across an Asia-pacific NETwork (PLANET) - Intratumoural immune heterogeneity

  The clinical relevance of immune landscape intratumoural heterogeneity (immune-ITH) and its role in tumour evolution remain largely unexplored. Here, we uncover significant spatial and phenotypic immune–ITH from multiple tumour sectors and decipher its relationship with tumour evolution and disease progression in hepatocellular carcinomas (HCC). Immune–ITH is associated with tumour transcriptomic-ITH, mutational burden, and distinct immune microenvironments. Tumours with low immune–ITH experience higher immunoselective pressure and escape via loss of heterozygosity in human leukocyte antigens and immunoediting. Instead, the tumours with high immune-ITH evolve to a more immunosuppressive/exhausted microenvironment. This gradient of immune pressure along with immune-ITH represents a hallmark of tumour evolution, which is closely linked to the transcriptome-immune networks that contributes to disease progression and immune inactivation. Remarkably, high immune-ITH and its transcriptomic signature are predictive for worse clinical outcome in HCC patients. This in-depth investigation of ITH provides evidence on tumour-immune co-evolution along HCC progression.

  Dataset EGAD00001006570

• Lung cancers from admixed Latin American populations (2)

  Raw data from cancer panel sequencing of lung adenocarcinomas from admixed Latin American populations, predominantly samples without known oncogene mutations (n=532).

  Dataset EGAD00001006571

• Somatic variants in 344 colorectal cancer samples

  The dataset contains somatic variants in 344 colorectal cancer samples. Variants are called with Mutect2 (GRCh38). Important: VCF-files include also variants, which have been annotated as "str_contraction" and "panel_of_normals". Please, use only "PASS" variants in studies, which are not microsatellite repeat related. Samples are sequenced with Novaseq 6000, HiSeq 2000, and HiSeq X Ten instruments (average coverage depth ~30+). The dataset consists of 257 MSS, 58 MSI, 25 MSS IBD, and 4 POLE mutant CRCs.

  Dataset EGAD00001006572

• RNA-seq study of a Princess Margaret Cancer Centre human acute myeloid leukemia patient cohort

  The PMCC AML RNAseq dataset consists of 81 AML patient samples (clinical data in Supplemental Table 11 of manuscript), processed in two batches. These patient samples are able to engraft in the NSG (NOD.Cg PrkdcscidIl2rgtm1Wjl /SzJ) mouse model. Five patients (90543, 598, 90240, 110484, 100500) were included in both batches. Viaably frozen material from the Leukemia Tissue Bank at Princess Margaret Cancer Centre/ University Health Network were thawed by dropwise addition of X-VIVO + 50% fetal calf serum supplemented with DNase (100μg/mL final concentration, Roche). RNA was extracted from bulk peripheral blood mononuclear cells (PBMC) using the RNeasy Micro Kit (Qiagen Inc.). A paired-end 76 base-pair flow-cell lane Illumina High seq 2000 yielded an average of 240 million sequence reads aligning to genome per sample at the Genome Sciences Centre, BC Cancer Agency for cohort 1. Cohort 2 was subjected to 125 bp, paired-end RNA-sequencing on the Illumina HiSeq 2500 with an average of 50 million reads/sample at the Centre for Applied Genomics, Sick Kids Hospital.

  Dataset EGAD00001006576

• Prognostic and immunomodulatory consequences of ERV expression in ovarian cancer

  The dataset contains transcriptional data obtained using total RNA sequencing on a Illumina machin. 59 samples are from the Hammersmith Hospital (HH) cohort of human primary ovarian tumours and 20 samples are from ovarian cancer cell lines Kuramochi (3 replicates) and Ovsaho (2 replicates) treated with 1 uM DNMTi guadecitabine or vehicle, at an early (day 5) or late (day 8) timepoint.

  Dataset EGAD00001006589

• Combinatorial CRISPR screen identifies fitness effects of paralogues FAM50A and FAM50B

  Genetic redundancy has evolved as a way for human cells to survive the loss of genes that are single copy and essential in other organisms, but also allows tumours to survive despite having highly rearranged genomes. In this study we CRISPR screen 1,191 gene pairs, including paralogues and known and predicted synthetic lethal interactions to identify 105 gene combinations whose co-disruption results in a loss of cellular fitness. 27 pairs influence fitness across multiple cell lines including the paralogues FAM50A/FAM50B, two genes of unknown function. Silencing of FAM50B occurs across a range of tumour types and in this context disruption of FAM50A reduces cellular fitness whilst promoting micronucleus formation and extensive perturbation of transcriptional programmes. This dataset includes CRISPR screening of cancer cell lines, RNA sequencing studies of cancer cell lines and also data from the sequencing of tumour xenografts collected from mice.

  Dataset EGAD00001006649

• RRBS analysis to characterize the epigenomic conservation between species in the context of Aging and Cancer.

  This dataset contains Raw Reduced Representation DNA bisulfite-sequencing data obtained from human brain samples corresponding to 3 Young and 3 Old individuals (aging context), and 3 normal and 3 Glioblastoma samples (tumor context). RRBS libraries were prepared at Diagenode SA and samples were sequenced using the Illumina Novaseq6000 sequencing platform.The accompanying samples from this study (mouse tissues) are located at the ENA database under the accession number PRJEB41460.

  Dataset EGAD00001006650