9338 results for "cancer rna-seq"

in 69.87 milliseconds.

• Dataset for leiomyosarcoma-RNA

  Rare cancer sequencing data of 87 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008849

• Dataset for colorectal_cancer-RNA

  Rare cancer sequencing data of 97 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008855

• Dataset for head_and_neck_cancer-RNA

  Rare cancer sequencing data of 92 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008861

• Single Cell Analysis Program - Transcriptome (SCAP-T)

  This initiative is part of the Single Cell Analysis Program (SCAP) and is funded through the NIH Common Fund (See http://nihroadmap.nih.gov/), which supports cross-cutting programs that are expected to have exceptionally high impact. Common Fund initiatives address key roadblocks in biomedical research that impede basic scientific discovery and its translation into improved human health. In addition, these programs capitalize on emerging opportunities to catalyze progress across multiple biomedical fields. Single cell analysis has recently emerged as an important field of research because technologies have improved in sensitivity and throughput sufficiently to begin measuring and understanding heterogeneity in complex biological systems and correlating it with changes in biological function and disease processes. By profiling individual cells it is possible to resolve rare cells, transient cell states, and the influence of organization and environment on such cells and states, which cannot be described by ensemble measurements. The long-term goal of the SCAP is to accelerate this move towards personalizing health to the cellular level by understanding the link between cell heterogeneity, tissue function and emergence of disease through the discovery, development and translation of innovative approaches which will dramatically change the way cells are characterized. The SCAP will focus on research, which will systematically measure, analyze and model cell-to-cell variation, and identify crucial differences and rare biological states, which may have important functional consequences. Under SCAP, there are three studies to evaluate the cellular heterogeneity using transcriptional profiling of single cells (U01): University of Pennsylvania: Role of single cell mRNA variation in systems associated electrically excitable cells University of Southern California: Evaluation of cellular heterogeneity using patchclamp and RNA-seq of single cells University of California at San Diego: Single cell sequencing and in situ mapping of RNA transcripts in human brains The SCAP has been designed as a five-year program with several components: (1) the collection, analysis and sharing of comprehensive expression datasets to understand the role of heterogeneity in tissues and systemically and identify critical parameters and states; (2) the discovery of new, innovative tools for spatiotemporal imaging, manipulation, analysis and modeling of a biologically relevant population of cells with minimal perturbation; (3) milestone-driven validation and translation of technologies for characterizing single cells in situ meeting the needs of end-users; and (4) development and coordination of a multidisciplinary research community through workshops and other collective endeavors. Further details about the NIH SCAP-T program can be found here http://commonfund.nih.gov/singlecell/. The SCAP-T data sets include the detailed phenotype information, experimental protocols, QC information, RNA-sequencing data and NGS results from human heart and human brain cells. The first data release includes 697 single cells from human brain and heart. The second data release includes an additional 978 single cells from human brain and heart. The third data release includes an additional 1631 single cells from human brain and heart. The fourth data release is a correction to this study, but adds no new cells. The fifth data release includes an additional 2984 single cells from human brain and heart. The sixth data release includes an additional 944 single cells from human brain and heart. The seventh data release includes an additional 1977 single cells from human brain and heart. The SCAP-T data portal provides a customized interface for users to quickly identify and retrieve files by phenotypes, and data properties such as sequencing facility or coverage for all of these 9231 single cells. For more information about the SCAP-T study and the data portal, please visit http://www.scap-t.org.

  Study phs000833

• Exceptional Responders Initiative

  The Exceptional Responders Initiative is a pilot study to investigate the underlying molecular factors driving exceptional treatment responses of cancer patients to drug therapies. Study researchers will examine molecular profiles of tumors from patients either enrolled in a clinical trial for an investigational drug(s) and who achieved an exceptional response relative to other trial participants, or who achieved an exceptional response to a non-investigational chemotherapy. An exceptional response is defined as achievement of either a complete response or a partial response for at least 6 months duration in a trial or treatment where the overall response rate is < 10%. The hope is to discover underlying molecular features that can be further investigated and may eventually predict benefit from a given drug or class of drugs for a particular patient. This pilot project will successfully characterize approximately 100 cases of tumor tissue and, when available, case-matched germline DNA. All samples will undergo whole exome sequencing, and cases with sufficient nucleic acids will undergo additional analyses (e.g. whole genome sequencing, mRNA-sequencing, mi RNA sequencing, promoter methylation analysis, SNP etc). Each case will be annotated with demographic and clinical information, along with follow-up information minimally sufficient to correlate molecular profiles with response. Both retrospective and prospective collections will be considered. The project will also accept sequencing data and clinical data from patients who have had sequencing performed outside of this project. All data will be de-identified and placed in a controlled access database so other investigators may use them for additional insights. Clinically annotated tissue specimens meeting the criteria will be provided by groups participating in the Exceptional Cases Initiative to a Biospecimen Core Resource (BCR), which will perform quality control on the tissues, and will use a standard operating procedure to isolate nucleic acids. The nucleic acids will be shipped to a sequencing center to perform whole exome sequencing and analysis. These findings will be made available to the broader cancer research community in a controlled access database.

  Study phs001145

• Identification of Somatic Changes in Tumors from Fanconi Anemia Patients

  This study focused on the identification of genomic signatures present in tumors from Fanconi anemia patients. Fanconi anemia is a rare hereditary disease caused by defects in DNA interstrand crosslink repair. The primary patient phenotypes are bone marrow failure and cancer predisposition. We concentrated on squamous cell carcinomas and used whole genome Illumina sequencing (22 tumor samples and 12 normal samples) , whole exome sequencing (37 tumor samples and 33 normal samples), PacBio long-read whole-genome (nine tumor and four normal samples),10X linked-read whole-genome sequencing, 10x single-cell/nuclei 3’ RNA sequencing (three tumor samples), 10x Visium spatial transcriptomics (one tumor sample), EPIC 850K methylation array (six samples), and bulk RNAseq (six tumor samples) to identify somatic changes present in tumors. The study aimed to identify changes that drive tumorigenesis in Fanconi anemia, give insight into the early development and aggressive nature of these tumors, and suggest therapeutic avenues for these patients. Another goal was to compare the genomic changes identified in tumors from Fanconi anemia patients with sporadic head and neck cancers. This study demonstrated that the tumors from Fanconi anemia individuals are generally not driven by HPV. Instead, they acquire mutations in the p53 tumor suppressor. The main characteristic of the tumors is the presence of a high number of structural variants in the form of small deletions, unbalanced translocations, and fold-back inversions, which often form complex rearrangements. These rearrangements result in amplifications and deletions of a multitude of oncogenes and tumor suppressors, respectively. The study also shows that lack of the Fanconi anemia DNA repair pathway leads to an epithelial-to-mesenchymal transition in a mouse model and in human samples that may influence the behavior of tumors in Fanconi anemia. Finally, comparing genomic changes in Fanconi anemia and sporadic tumors of the head and neck, we propose that the structural variants present in sporadic cancer result in a functional deficiency of the Fanconi anemia DNA repair pathway.

  Study phs002652

• Automated machine-learning approach for next generation profiling of sequence alterations, mutation burden, microsatellite instability, and structural variants in human cancers

  Sequence and structural alterations together with tumor mutation burden (TMB) and microsatellite instability (MSI) have been identified as biomarkers for the determination of response to targeted and immune checkpoint inhibitor therapies. However, widespread clinical adoption of these biomarkers has historically been limited due to barriers such as evidence of clinical utility and reimbursement. We have developed 2.2 Mb targeted NGS system and an automated machine-learning analysis approach (PGDx elio™ tissue complete, ETC) that has been FDA cleared for examination of 500+ cancer-related genes and 68 mononucleotide repeats for identification of sequence and structural alterations, TMB, and MSI in solid cancers in a clinical setting. We designed and trained this approach using sequence data from 4,174 cancers and >124,000 in silico alterations and evaluated the methodology in >2,550 tumor or non-cancerous normal samples. Independent analyses of ETC sequence changes in 440 formalin fixed paraffin embedded (FFPE) tumor or cell line samples using MSK-IMPACT™, FoundationOne®, and ddPCR revealed a positive percent agreement (PPA) >97% with high sensitivity as low as 3% mutant allele fraction. We observed high concordance between panel-wide and whole-exome TMB for 307 pan-cancer FFPE tumors (Pearson r=0.95, p < 0.0001) using samples with ≥20% tumor cellularity. Comparison of the mutation context and repeat-based MSI approach in ETC with a multiplex MSI PCR assay in 223 samples revealed a PPA of 99% and negative predictive agreement (NPA) >99%. We confirmed the accuracy and precision of TMB and MSI measurements across three independent laboratories (CV of <5% and average PPA >99%, respectively). Finally, evaluation of amplifications and translocations against DNA and RNA-based approaches exhibited >98% NPA and PPA of 86% and 82% respectively. These results demonstrate high analytical performance for determination of sequence and structural changes, TMB, and MSI using a targeted NGS panel and provide a scalable and facile approach for evaluating these biomarkers in a clinical laboratory.

  Study EGAS00001005556

• Human Liver Cohort (HLC)

  The Human Liver Cohort (HLC) study aimed to characterize the genetic architecture of gene expression in human liver using genotyping, gene expression profiling, and enzyme activity measurements of Cytochrom P450. The HLC was assembled from a total of 780 liver samples screened. DNA samples were genotyped on the Affymetrix 500K SNP and Illumina 650Y SNP genotyping arrays. Only data from those samples which were collected postmortem are accessible through this submission. These 228 samples represent a subset of the 427 samples included in the Human Liver Cohort Publication (Schadt, Molony et al. 2008, PMID: 18462017). RNA samples were profiled on a custom Agilent 44,000 feature microarray composed of 39,280 oligonucleotide probes targeting transcripts representing 34,266 known and predicted genes, including high-confidence, noncoding RNA sequences. Gene Expression data for the samples from which it could be obtained is available in GEO under accession number GSE9588. Results and networks will be made available for download from Sage Bionetworks.

  Study phs000253

• Functional Genomic Landscape of Acute Myeloid Leukemia

  The implementation of targeted therapies for acute myeloid leukemia has been challenged by complex mutational patterns within and across patients as well as a dearth of pharmacologic agents for most mutational events. Here, we report initial findings from the Beat AML program on a cohort of 672 tumor specimens collected from 562 patients. We assessed these specimens using whole exome sequencing, RNA-sequencing, and ex vivo drug sensitivity analyses. Our data reveal novel mutational events not previously detected in AML. We show association of drug response with mutational status, including instances of drug sensitivity that are specific to combinatorial mutational events. Integration with RNA-sequencing also revealed gene expression signatures, which predict a role of specific gene networks in drug response. Collectively, this report offers a dataset, accessible by the Beat AML data viewer (www.vizome.org), that can be leveraged to address clinical, genomic, transcriptomic, and functional inquiries into the biology of AML.

  Study phs001657

• Unraveling the heterogeneity of multiple myeloma identifies therapy resistant subpopulation with vulnerability to the splicing pathway intervention

  Intra-tumor heterogeneity underlies the therapy resistance of multiple myeloma (MM). However, its details remain unknown. Here, we performed single-cell RNA sequencing coupled with VDJ targeted sequencing on highly purified bone marrow lineage marker-negative CD38+ MM cells from patients at diagnosis and in remission. This approach successfully subdivided MM cells into distinct clusters, unraveling their heterogeneity and plasticity on the axis of cell surface CD138 expression. Notably, unique clusters were identified in the minor CD138-negative population that resisted therapies. CRISPR/Cas9 screening of upregulated genes in the resistant population identified their vulnerability to the splicing pathway inhibition, among which RNA-binding protein 39 (RBM39) appeared to be overexpressed in the resistant population and involved in aberrant splicing. Genetic and pharmacological inhibition of RBM39 exerted a profound synthetic lethal effect on them. Our results unveil an uncharacterized subpopulation associated with therapy resistance and provide a novel therapeutic strategy targeting the splicing pathway in MM.

  Study JGAS000723

• Recurrent somatic mutations in POLR2A define a distinct subset of meningiomas

  RNA polymerase II mediates the transcription of all protein-coding genes in eukaryotic cells, a process that is fundamental to life. Genomic mutations in this enzyme have not been previously linked to any pathology in humans, a testament to its indispensable role in cell biology. Based on a combination of next-generation genomic analyses of 775 meningiomas, we report that recurrent somatic p.Gln403Lys or p.Leu438_His439del mutations in POLR2A, which encodes the catalytic subunit of RNA polymerase II1, are sufficient to hijack this essential enzyme and drive neoplasia. POLR2A mutant tumors reveal dysregulation of key meningeal identity genes, including WNT6 and ZIC1/ZIC42,3. In addition to POLR2A, NF2, SMARCB1, TRAF7, KLF4, AKT1, PIK3CA and SMO4-8, we also report somatic mutations in AKT3, PIK3R1, PRKAR1A, and SUFU in meningiomas. Our results identify a role for essential transcriptional machinery in driving tumorigenesis and define mutually exclusive meningioma subgroups with distinct clinical and pathological features.

  Study EGAS00001001916

• Dataset of RNA-sequencing of childhood acute myeloid leukemia

  This dataset includes 139 bam files of mRNA sequencing. All subjects are tumor samples of pediatric acute myeloid leukemia.

  Dataset EGAD00001005078

• Single-cell Full Transcriptome RNA sequencing

  Single cell full transcriptome sequencing of CD19 CAR T-cell infusion products used for standard of care treatment for relapsed/refractory large B-cell lymphoma.

  Dataset EGAD00001006325

• Single cell targeted RNA sequencing

  Single cell hybrid-capture targeted sequencing of CD19 CAR T-cell infusion products used for standard of care treatment for relapsed/refractory large B-cell lymphoma.

  Dataset EGAD00001006327

• MYC and MINCR-regulated lncRNAs in hT-RPE-MycER cells

  RNA-sequencing data from teh hT-RPE-MycER cell line after MYC activation and after MINCR knock-down in conditions of MYC ON or OFF

  Dataset EGAD00001001598

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

  RNAseq data from the TRACERx 421 cohort

  Dataset EGAD00001009862

• Gene expression associated with Klinefelter syndrome

  RNA-sequencing profiling of leucocytes from peripheral blood samples from 9 KS patients, 9 control males and 13 female controls

  Dataset EGAD00001010078

• APCIM_Nanostring_HD

  Expression of immune related genes in 12 healthy donors. Expression assessed by analyzing whole blood-derived RNA samples using a Nanostring nCounter Immunology V2 panel (579 genes)

  Dataset EGAD00010002554

• Single-cell RNA-sequencing of H3-K27M diffuse midline glioma.

  Fastq files are deposited for single-cell transcriptomes of patient H3-K27M diffuse midline gliomas, generated using the SMART-seq2 method.

  Dataset EGAD00001011339

• Genome-Wide Association Study of Lung Cancer Susceptibility in Never-Smoking Women in Asia

  To learn about the etiology of lung cancer among never-smoking women in Asia, we formed the Female Lung Cancer Consortium in Asia (FLCCA), which includes studies of lung cancer in Eastern Asia and conducted a GWAS. We analyzed a total of 5510 lung cancer cases and 4544 controls and identified 3 novel loci (Lan et al., 2012). Of these study subjects, 4922 lung cancer cases and 3959 controls are available for posting. Lan et al.., Genome-wide association analysis identifies new lung cancer susceptibility loci in never-smoking women in Asia. Nat Genet. 2012 Dec;44(12):1330-5. doi: 10.1038/ng.2456. Epub 2012 Nov 11. PubMed PMID: 23143601.

  Study phs000716

• WGS-Lung Cancer sample 30 pair

  This study includes 30 paired samples of Korean Lung Cancer paitients. 30 Lung Cancer samples are paired with each normal(Saliva derived for control) sequencing data.The results of this WGS study were analyzed by Mutect and GATK for ranking germline variants and cancer variants to make mutational profile matrix.

  Study EGAS00001001474

• Genomic analysis of Japanese gastric cancer (345 gastric cancers of NCC)

  As a contribution to the International Cancer Genome Consortium, whole exome sequencing of 345 Japanese gastric cancer (345 gastric cancers of NCC) with various histological subtypes have been conducted. This study aims to identify unique and common driver genes and molecular subtypes in Japanese gastric cancer.

  Study EGAS00001002884

• MCO colorectal cancer genomics at UNSW

  This dataset contains DNA sequencing data from 95 colorectal cancer and matched-normal samples. The dataset contains targeted deep sequencing of selected regulatory elements in 95 cancer and matched-normal samples, and data for one sample that was additionally whole-genome sequenced (cancer and matched-normal).

  Study EGAS00001003450

• The landscape of cancer genes and mutational processes in breast cancer

  The landscape of cancer genes and mutational processes in breast cancer

  Dataset EGAD00001000133

• Mapping the Evolution of T Cell States During Response and Resistance to Adoptive Cellular Therapy

  We investigated single T cell transcriptional states that define donor lymphocyte infusion (DLI) response and resistance from cryopreserved bone marrow mononuclear cells from 15 patients with relapsed chronic myeloid leukemia (CML) after allogeneic hematopoietic stem cell transplant. By integrating bulk ATAC-seq data from sorted T cell populations from these bone marrow samples, we also defined gene regulatory networks that underlay these clusters.

  Study phs002877

• ATAC_SEQ_MAIN___PHASE_1

  This is a study to test ATAC-seq protocols. CD4+ and CD8+ cells have been obtained from three different anatomical compartments. We aim to assay open-chromatin regions across these cells and perform comparative analyses.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/

  Study EGAS00001000947

• Modeling glioblastoma invasion using human brain organoids and single-cell transcriptomics

  We performed scRNA-seq of patient-derived glioblastoma cells alone or after co-culture with human iPSC-derived cerebral organoid cells. Transcriptional changes implicated in the invasion process that are coherent across patient samples indicate that GBM cells reactively upregulate genes required for their dispersion. Potential interactions between GBM and organoid cells identified by an in silico receptor-ligand pairing screen suggest functional therapeutic targets.

  Study EGAS00001003852

• GEX CITE-Seq performance dataset

  To understand the impact of enzymatic treatments on gene expression and epitope preservation on major immune cell populations, skin dissociation (SkinD) and solid soft tumor dissociation (TumorD) were tested on three healthy PBMC samples in triplicate (D1, D2, D3), against an untreated control. CITE-seq performance was assessed on a solid biopsy cohort of 11 samples (5 healthy skin samples, 3 primary melanoma samples, 3 melanoma metastasis samples) as well as on a liquid biopsy PBMC cohort consisting of three healthy donors and three immunotherapy-treated melanoma patients. This dataset contains the GEX data for each sample. Data is provided in the form of pooled BAM files. Linkage between samples, BAM files and hashtags is provided in a separate linkage file.

  Dataset EGAD00001008418

• ADT/SPEX CITE-Seq performance dataset

  To understand the impact of enzymatic treatments on gene expression and epitope preservation on major immune cell populations, skin dissociation (SkinD) and solid soft tumor dissociation (TumorD) were tested on three healthy PBMC samples in triplicate (D1, D2, D3), against an untreated control. CITE-seq performance was assessed on a solid biopsy cohort of 11 samples (5 healthy skin samples, 3 primary melanoma samples, 3 melanoma metastasis samples) as well as on a liquid biopsy PBMC cohort consisting of three healthy donors and three immunotherapy-treated melanoma patients. This dataset contains the ADT/SPEX data for each sample. Data is provided in the form of pooled BAM files. Linkage between samples, BAM files and hashtags is provided in a separate linkage file.

  Dataset EGAD00001008419

• Targeted_analysis_of_chondrosarcoma_cancer_genes

  Targeted analysis of chondrosarcoma cancer genes

  Study EGAS00001001765

• Discover Cancer Image Europe, the first release of the EUCAIM platform to fuel cancer research and data sharing

  The EUCAIM consortium and the European Commission have announced the release of Cancer Image Europe, a platform to fuel collaborative innovation and data sharing across Europe. This constitutes a major milestone in EUCAIM's development and an exciting step towards achieving the project's vision and goals. The platform aims to accelerate the pace of AI development and other data-intensive cancer research activities, constituting the basis for a fully-fledged infrastructure for sharing, reusing, and exploiting cancer imaging data, especially using AI techniques. A platform paving the way for the future of cancer diagnosis and treatment Cancer Image Europe brings benefits to researchers, clinicians, and AI innovators across Europe as it addresses the fragmentation of existing cancer image repositories. The platform gathers a public catalogue of cancer imaging datasets from the repositories of the EU-funded AI for Health Imaging projects. A distributed Atlas of Cancer Imaging with over 60 million anonymised cancer image data from over 100,000 patients will be established as part of future updates. The first version of Cancer Image Europe also includes a public catalogue of cancer imaging datasets, a federated searching tool to understand the information available in the federated providers, and full integration with Life Science Login. Moreover, it reuses and adds value to key components of EU-funded research projects and infrastructure in the field of cancer. The Public Catalogue When we talk about data re-use, data discovery is key. The EUCAIM public catalogue is the result of a systematic and collaborative process to which the EGA-CRG has actively contributed. This browsing interface gathers the metadata of the available cancer imaging datasets. This descriptive information will help researchers in their data retrieval. Our contribution to the Public Catalogue comes from our experience gained in the deployment of our federated network, the Federated EGA (FEGA), and as partners in projects such as EuCanImage (AI4HI initiative), in which we worked on the definition of common data models, ontologies and data standards. The EUCAIM Project EUCAIM is a cornerstone of the European Commission-initiated European Cancer Imaging Initiative, a flagship of the Europe's Beating Cancer Plan, which aims to foster innovation and deployment of digital technologies in cancer treatment and care, to achieve more precise and faster clinical decision-making, diagnostics, treatments, and predictive medicine for cancer patients. For more information about the first release of the Cancer Image Europe platform and the EUCAIM project, please visit cancerimage.eu.

  Blog discover-cancer-image-europe

• Mutational anysis of breast cancer stem cells

  Exome sequences of breast cancer have been investigated for many patients. Recently it has been shown that there are intra-heterogeneity in tumor tissues. When the tumor cells were sequenced in bulk condition, only the major populations��� (clones���) mutations will be detected. Based on cancer stem theory, each populations��� cells are derived from each cancer stem cells, which their numbers are not so different among different clones. Here, we separated cancer cells into cancer stem cells and non-cancer stem cells exploiting cancer stem cell specific surface markers. By comping two groups��� mutation, we identified mutations, which were only detected in stem cell population. These mutations could be the mutations in cells of small size populations, and maybe the important mutations to understand the heterogeneity of tumor tissues, progression, and/or prediction for the outcome to therapies.

  Study JGAS000304

• Cancer Genetic Markers of Susceptibility (CGEMS) Breast Cancer Genome-wide Association Study (GWAS) - Primary Scan: Nurses' Health Study - Additional Cases: Nurses' Health Study 2

  The initial stage of the Cancer Genetic Markers of Susceptibility (CGEMS) breast cancer genome-wide association study (GWAS) included genotyping 528,173 SNPs (Illumina HumanHap550) in 1,145 postmenopausal women of European ancestry with invasive breast cancer and 1,142 controls from the Nurses' Health Study (NHS). Subsequently, incident invasive breast cancer cases from the Nurses' Health Study 2 (NHS2) cohort were genotyped using the Illumina HumanHap 610 quad. The NHS2 cases are younger than the cases in the first stage of the CGEMS breast cancer GWAS, which only included postmenopausal women. The NHS2 cases are a mix of pre- and postmenopausal women

  Study phs000147

• Epigenomic profile of diverse cancer

  Epigenomic profile of diverse cancer.

  Study EGAS00001004352

• Paired-end Whole Exome-seq analysis of TERT promoter duplication in GBM

  Dataset contains paired-end Whole Exome sequencing data from 5 tumor samples and 1 single normal blood sample from a single primary GBM patient.

  Dataset EGAD00001008768

• CIDR: Molecular Pathological Epidemiology of Colorectal Cancer

  Colorectal cancer, the second most commonly diagnosed cancer is a biologically heterogeneous disease. To characterize the molecular attributes of colorectal tumors, we conducted targeted sequencing at the Center for Inherited Disease Research (CIDR) on 4,518 tumor and matched normal DNA samples from the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) and the Colon Cancer Family Registry (CCFR). These consortia are based on cohort and population-based case-control studies.

  Study phs001905

• Exome and RNA sequencing data from 32 ocular and extraocular sebaceous carcinomas

  Sebaceous carcinomas (SeC) are cutaneous malignancies that, in rare cases, metastasize and prove fatal. Here we report whole exome sequencing on 32 SeC, revealing distinct mutational classes that explain both cancer ontogeny and clinical course. A UV-damage signature predominated 10/32 samples, while 9 were instead defined by microsatellite instability (MSI) mutations. UV-damage SeC exhibited poorly differentiated, infiltrative histopathologycompared to MSI signature SeC (p = 0.003), features previously associated with dissemination. Strikingly, UV-damage SeC transcriptomes and anatomic distributionclosely resembling those of cutaneous squamous cell carcinomas (SCC), implicating sun-exposed keratinocytes as a cell of origin. Like SCC, this UV-damage subclass harbors a high somatic mutation burden with >50 mutations/Mb, predicting immunotherapeutic response. In contrast, ocular SeC acquire far fewer mutations without a dominant signature, but show frequent truncating mutations in the ZNF750 epidermal differentiation regulator. Our data exemplify how different mutational processes convergently drive histopathologically related but clinically distinct cancers.

  Study EGAS00001002869

• Developmental Dynamics of Translation in the Human Brain

  We performed ribosome profiling and RNA sequencing from a total of 43 adult brain and 30 prenatal brain samples. The age of adult brain donors ranged from 18 to 82 years (average 39.5 years), with an average post-mortem interval of 9.9 hours. The gestational age of prenatal cortex samples ranged from 12 to 23 weeks, with a mean of 19.9 weeks. 

  Study phs002489

• Differentiation-associated ISG expression of NK cells in chronic viral hepatitis

  Little is known about the effects of ISGs on NK cell responses in chronic viral hepatitis. Here, we determined the expression, regulation and function of ISGs in NK cells with respect to phenotype and function, we performed high-throughput single cell RNA sequencing of circulating CD3-CD56+ NK cells from healthy donors (HD) and patients with chronic HBV or HCV infections.

  Study EGAS00001007771

• Mapping_genetic_variants_underlying_gene_regulation_in_healthy_intestinal_cell_types_to_identify_novel_IBD_drug_targets

  Biopsies from the terminal ileum and rectum of healthy individuals are digested on ice to single cells and processed for single-cell RNA-sequencing (10X Genomics and Illumina) 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/

  Study EGAS00001003647

• 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.

  Study EGAS00001000571

• Genomic and transcriptomic profiling of signalling networks in follicular lymphoma

  This dataset is composed of sequencing data from 16 patients diagnosed with follicular lymphoma, who developed transformed disease and for whom representative frozen tumor biopsy samples were available. For 14 patients there is paired material from both disease stages. DNA and RNA libraries were constructed and captured with a kinome bait library (Agilent Technologies), before sequencing on an Illumina platform.

  Study EGAS00001002175

• Whole-exome sequencing of PTC, benign nodule and normal tissues in 28 patients

  In order to comprehensively investigate the genetic relationship between PTC tumors and benign nodules, we totally collected 127 fresh-frozen biopsies samples from 28 patients with concurrent thyroid benign nodule and PTC (n=20) or simple benign nodule (n=8). We carried out whole-exome sequencing on all the 127 biopsies samples and RNA-sequencing in total of 40 samples.

  Study EGAS00001002312

• Capture Hi-C on Hodgkin lymphoma cell line L-428

  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.

  Study EGAS00001003032

• Transcriptional changes in GBM through therapy

  Primary glioblastoma (GBM) tumours recur following therapy, owing to treatment resistance mechanisms in unresectable cells. We have sequenced RNA from paired primary and locally recurrent GBM tumours to begin characterising therapy resistant cells and thereby infer the mechanisms by which they evaded treatment. Exome sequencing data from these samples were included in the first data release from the Glioma Longitudinal AnalySiS (GLASS) consortium

  Study EGAS00001003790

• Total RNAseq in the sporadic ALS and healthy control motor cortex

  Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by the degeneration of upper and lower motor neurons leading to progressive muscle weakness, wasting and paralysis that result in death within a few years from disease onset. In order to characterize RNA alterations in ALS, total RNAseq was performed in the ALS motor cortex, which is an early and vulnerable region in ALS.

  Study EGAS00001004286

• Microenvironment subtypes and association with tumor cell mutations and antigen expression in follicular lymphoma

  Follicular lymphoma (FL) is a B-cell lymphoma with a complex tumor microenvironment that is rich in non-malignant immune cells. We applied single-cell RNA-sequencing to characterize the immune microenvironment of FL. This provides a classification framework of the FL microenvironment, their association with FL genotypes and antigen presentation, and informs different potential immunotherapeutic strategies.

  Study EGAS00001006052

• Genome-Wide Discovery of Novel Breast Cancer Predisposing Mutations

  Cancer risk shows clear heritability, but the inherited genetic factors remain largely unknown. This project will seek to identify new genes in which mutations confer hereditary risk for early onset breast cancer, with important implications for both biological understanding and clinical prediction and prevention. Identifying cancer predisposing mutations can provide new biological insights and significantly impact important clinical decision making regarding treatment, surveillance and preventive approaches. Examples include the BRCA1 breast cancer susceptibility gene, which affects treatment decisions (surgical management), surveillance (frequent breast MRI) and prevention (oophorectory for prevention of ovarian cancer). Hereditary early onset breast cancer patients commonly present to Cancer Genetics clinics, but the majority of these patients do not have identifiable mutations in known candidate genes. Here, we will perform whole exome sequencing to discover novel cancer susceptibility genes. The patients have been recruited from Memorial Sloan Kettering Cancer Center (PIs Kenneth Offit and Zsofia Stadler) and Massachusetts General Hospital (PI Daniel Haber). All exome sequencing was performed at the Broad Institute of Harvard and MIT; samples sequence capture was performed using Agilent SureSelect Human All Exon Kit v2 and sequencing was performed on an Illumina HiSeq 2000 or 2500.

  Study phs000822

• Genome-Wide Scan for Genetic Variants Associated with Early-Onset Prostate Cancer

  This is a genome-wide association scan of 931 early-onset prostate cancer cases of European ancestry. The samples were selected from prostate cancer studies at the University of Michigan. Controls were previously genotyped individuals selected from the Cancer Genetics Markers of Susceptibility (CGEMS) and Illumina's iControlDB database.

  Study phs001185

• Genomic alterations in MM - CEL

  RNA from the same tumor sample (n=98) was also processed using the 3' IVT kit (Affymetrix) and hybridized to U133 Plus 2.0 arrays (Affymetrix).

  Dataset EGAD00010001577