11769 results for "cancer rna-seq"

in 20.23 milliseconds.

• Chromosomal copy number heterogeneity predicts survival rates across cancers

  Survival rates of cancer patients vary widely within and between malignancies. While genetic aberrations are at the root of all cancers, individual genomic features cannot explain these distinct disease outcomes. In contrast, intra-tumour heterogeneity (ITH) has the potential to elucidate pan-cancer survival rates and the biology that drives cancer prognosis1,2. Unfortunately, a comprehensive and effective framework to measure ITH across cancers is missing3. Here, we introduce a scalable measure of chromosomal copy number heterogeneity that predicts patient survival across cancers. We show that the level of ITH can be derived from a single-sample copy number profile. Using gene-expression data we demonstrate that ongoing chromosomal instability underlies the observed heterogeneity. Analysing 11,534 primary cancer samples from 35 different malignancies, we find that copy number heterogeneity can be accurately deduced and predicts cancer survival across tissues of origin and stages of disease. Our results provide a unifying molecular explanation for the different survival rates observed between cancer types.

  Study EGAS00001004702

• Whole genome sequencing of patients with or at risk for HCC

  Liver cancer is a major cause of cancer mortality worldwide. Screening individuals at high risk, including those with cirrhosis and viral hepatitis, provides an avenue for improved survival, but current screening methods are inadequate. In this study, we used whole-genome cell-free DNA (cfDNA) fragmentome analyses to evaluate 724 individuals from the United States, the European Union, or Hong Kong with hepatocellular carcinoma (HCC) or who were at average or high-risk for HCC. Using a machine learning model that incorporated multifeature fragmentome data, the sensitivity for detecting cancer was 88% in an average-risk population at 98% specificity and 85% among high-risk individuals at 80% specificity. We validated these results in an independent population. cfDNA fragmentation changes reflected genomic and chromatin changes in liver cancer, including from transcription factor binding sites. These findings provide a biological basis for changes in cfDNA fragmentation in patients with liver cancer and provide an accessible approach for noninvasive cancer detection.

  Study EGAS00001007249

• Functionally Active Copy Number Variants Associated with Prostate Cancer Risk

  Prostate cancer is a leading cause of cancer death in males throughout the world and has the largest estimated effect of heritability among the most common tumor types. Copy Number Variants (CNVs) are a recently recognized class of human germline polymorphisms (Iafrate AJ, et al. (2004) Nat Genet 36, 949-951; Sebat J, et al. (2004) Science 305, 525-528.) and are associated with a variety of human diseases, including cancer. This study characterized 1,903 individuals from the Tyrol Early Prostate Cancer Detection Program (Bartsch G, et al. (2008) BJU Int 101, 809-816) using a computational framework (Banerjee S, et al. (2011) PLoS One 29;6(3)). The study results establish non-coding and coding germline CNVs as significant risk factors for prostate cancer susceptibility and implicate their role in disease development and progression. The study "Identification of functionally active, low frequency copy number variants at 15q21.3 and 12q21.31 associated with prostate cancer risk," Demichelis F, Setlur SR, Proc Natl Acad Sci U S A. 2012 Apr 24;109(17):6686-91.

  Study phs000487

• Comprehensive Genomic Data Deposition for Pancreatic Cancer Precision Medicine Studies: Clinical Trials NCT02451982 and NCT02648282

  This submission includes specimens from 89 pancreatic cancer patients at Johns Hopkins Hospital, comprising 41 surgically resectable and 48 locally advanced pancreatic cancer (LAPC) cases. These samples originate from two clinical studies, NCT02451982 and NCT02648282, following the Johns Hopkins Medical Institution Institutional Review Board-approved registry protocol at the Pancreatic Cancer Precision Medicine Center of Excellence Program. Written consent for specimen use, obtained from participants in the original studies, covers additional research, including this one. Biopsy specimens collected through endoscopic ultrasound-guided fine needle core biopsies or surgically resected tumors are included. NCT02451982 is a platform trial evaluating immunotherapy combinations for surgically resectable pancreatic ductal adenocarcinoma in the neo-adjuvant and adjuvant settings. It investigates the GVAX pancreatic cancer vaccine with immune-boosting cyclophosphamide, exploring immune cell trafficking and the impact of PD-1 blocking. NCT02648282 focuses on the efficacy and safety of combining cyclophosphamide, pembrolizumab, GVAX, and stereotactic body radiotherapy (SBRT) in locally advanced pancreatic cancer, with an emphasis on anti-tumor activity. Both studies provide valuable insights into innovative pancreatic cancer treatment approaches.

  Study phs003600

• Cancer immune control needs senescence induction by Stat1 dependent cell cycle regulator pathways in tumours

  Immune checkpoint bloackade (ICB)-based or natural cancer immune responses largely eliminate tumours. Yet, they require additional mechanisms to arrest those cancer cells that are not rejected. Cytokine-induced senescence (CIS) can stably arrest cancer cells, suggesting that interferon-dependent induction of senescence-inducing cell cycle regulators is needed to control those cancer cells that escape from killing. Here we report in two different cancers sensitive to T cell-mediated rejection, we show that deletion of the senescence-inducing cell cycle regulators p16Ink4a/p19Arf (Cdkn2a) or p21Cip1 (Cdkn1a) in the tumour cells abrogated both, the natural and the ICB-induced cancer immune control. Also in humans, melanoma metastases that progressed rapidly during ICB have losses of senescence-inducing genes and amplifications of senescence inhibitors. Metastatic cells also resist CIS. Such genetic and functional alterations are infrequent in metastatic melanomas regressing during ICB. Thus, activation of tumour-intrinsic, senescence-inducing cell cycle regulators is required to stably arrest those cancer cells that escape from eradication.

  Study EGAS00001004151

• Accurate detection of tumor-specific fusion genes reveals strongly immunogenic personal neo-antigens

  Fusion genes arising from cancer-associated somatic mutations are a potential rich source for highly immunogenic neo-antigens. However, their exploitation as targets for personalized cancer immunotherapy is currently limited by the lack of computational tools allowing transcriptome-wide identification of unique fusion genes in an accurate and sensitive manner. Here, we present EasyFuse, a computational pipeline, to detect individual and cancer-specific fusion genes in next-generation-sequencing transcriptome data obtained from human cancer samples. Using machine learning, EasyFuse predicts personal fusion genes with high precision and sensitivity and outperforms previously described approaches as qualified by an unprecedented ground-truth dataset of >1500 verification experiments in relevant patient samples. By testing immunogenicity with autologous blood lymphocytes from cancer patients we detected pre-established CD4+ and CD8+ T cell responses for 10 of 21 (48%), and for 1 of 30 (3%) of identified fusion genes, respectively. In conclusion, we demonstrate accurate detection of cancer-specific fusion genes. The high frequency of T cell responses detected in cancer patients support the relevance of private fusion genes as neo-antigens for personalized immunotherapies, especially for tumors with low point mutation burdens.

  Study EGAS00001004877

• National Cancer Institute (NCI) Early Onset Malignancies Initiative (EOMI): Molecular profiling of Breast, Colon, Kidney, Liver, Multiple Myeloma, and Prostate among Racially and Ethnically Diverse Populations

  The Early Onset Malignancies Initiative (EOMI) is focused on collecting specimens from racially and ethnically diverse population groups with six different types of cancer (breast, prostate, colon, liver, kidney, and multiple myeloma). This initiative is a partnership between the Center for Research Strategy, the Center for Cancer Genomics and the Division of Cancer (DCP). DCP's NCI Community Oncology Research Program (NCORP) is a critical partner. The acquisition of the cancer and matching normal biospecimens in this initiative are from newly diagnosed early onset cancer patients who identify as Non-Hispanic Black, Hispanic, American Indian or Alaska Native, or Non-Hispanic White. The Minority/Underserved NCORPs sites will collect the samples for this project. By carrying out this initiative in the NCORP's national network of investigators, cancer care providers, and research institutions, the EOMI will harness the community-based partnerships to improve participation among these racial/ethnic groups. The NCORP investigators, as participants in NCI's clinical trials network, will annotate the biologic samples with clinical information that will enhance the ability to answer questions about molecular determinants of early disease, treatment response, and/or prognosis. The EOMI will be a step forward in addressing racial/ethnic disparities and in understanding cancer in underserved populations.

  Study phs001952

• CRUK-ICGC Prostate Cancer Group Study

  Prostate cancer somatic genomic sequencing data generated from 2011 onwards under auspices of the International Cancer Genome Consortium Prostate Cancer UK consortium (CRUK-ICGC Prostate Group), co-led by Colin Cooper and Ros Eeles, with other Principal Investigators (Brewer, Neal, Bova, McDermott, Wedge, Lynch, Massie, and Foster) and others as listed in study publications. Funded by Cancer Research UK and other funders as listed in study publications. Contents and publications related to each dataset are described with each dataset (EGAD) entry. Our study was funded with the ambition of collecting Whole Genome DNA sequence data from 250 prostate cancers, with matching transcriptome and methylome data. The original aims of the project were: 1.To understand the significance of multifocal prostate cancer. 2.To understand the clinical heterogeneity of prostate cancer to devise markers for predicting outcome and for drug targeting. 3.To understand the molecular basis of development and spread of castration-resistant and metastatic disease 4.To understand the aetiology of prostate cancer particularly the large variation in incidences that occur in different populations and ethnic groups. Please see https://doi.org/10.5281/zenodo.4022439 for links between sample IDs reported in literature and EGA IDs.

  Study EGAS00001000262

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__clear_cell_renal_cell_carcinoma

  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.

  Study EGAS00001002608

• TRACERx 100: metastatic samples

  Whole exome sequencing of 10 metastatic biopsies from four TRACERx100 patients (see EGA dataset EGAS00001002247), collected either after relapse or death. The data from these samples are initially published with Abbosh, C. et al. Phylogenetic ctDNA analysis depicts early stage lung cancer evolution. Nature http://dx.doi.org/10.1038/nature22364 (2017). Abstract: Earlier detection of relapse following primary surgery for non-small cell lung cancer and the characterization of emerging subclones seeding metastatic sites might offer new therapeutic approaches to limit tumor recurrence. The potential to non-invasively track tumor evolutionary dynamics in ctDNA of early-stage lung cancer is not established. Here we conduct a patient-specific approach to ctDNA profiling in the first 100 lung TRACERx (TRAcking Cancer Evolution through therapy (Rx)) study participants, including one patient co-recruited to the PEACE (Posthumous Evaluation of Advanced Cancer Environment) post-mortem study. We identify independent predictors of ctDNA release in early-stage non-small cell lung cancer and perform tumor volume limit of detection analyses. Through blinded profiling of post-operative plasma, we observe evidence of adjuvant chemotherapy resistance and identify patients destined to experience recurrence of their lung cancer. Finally, we show that phylogenetic ctDNA profiling tracks the subclonal nature of lung cancer relapse and metastases, providing a new approach for ctDNA driven therapeutic studies.

  Study EGAS00001002415

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__head___neck

  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. Non-tumour DNA is also studied for some cancer types. 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.

  Study EGAS00001005450

• Whole genome and transcriptome sequencing of lung cancer patients and cell lines at Genentech

  Version 1 Whole genome sequencing was applied to tumor and adjacent normal lung tissue in an individual non-small-cell lung cancer patient. We present an analysis of somatic changes identified throughout the tumor genome, including single-nucleotide variants, copy number variants, and large-scale chromosomal rearrangements. Over 50,000 high-confidence single-nucleotide variants were identified, revealing evidence of substantial smoking-related DNA damage as well as distinct mutational pressures within the tumor resulting in uneven distribution of somatic mutations across the genome. Version 2 Lung cancer is a highly heterogeneous disease in terms of both underlying genetic lesions and response to therapeutic treatments. We performed deep whole genome sequencing and transcriptome sequencing on 19 lung cancer cell lines and 3 lung tumor/normal pairs. Overall, our data show that cell line models exhibit similar mutation spectra to human tumor samples. Smoker and never-smoker cancer samples exhibit distinguishable patterns of mutations. A number of epigenetic regulators are frequently altered by mutations or copy number changes. A systematic survey of splice-site mutations identified over 100 splice site mutations associated with cancer specific aberrant splicing, including mutations in several known cancer-related genes. Differential usages of splice isoforms were also studied. Taken together, these data present a comprehensive genomic landscape of a large number of lung cancer samples and further demonstrate that cancer specific alternative splicing is a widespread phenomenon that has potential utility as therapeutic biomarkers.

  Study phs000299

• NCI Cancer Model Development for the Human Cancer Model Initiative (HCMI)

  The Cancer Model Development Center (CMDC) project is part of the Human Cancer Model Initiative (HCMI) and is managed by the Office of Cancer Genomics within the Center for Cancer Genomics at the National Cancer Institute (NCI). The goal of the HCMI is to generate approximately 1000 novel human "next generation" tumor-derived models as a community resource. The models aim to faithfully recapitulate the cellular complexity and heterogeneity of human tumors. The CMDCs are tasked by the NCI with producing a proportion of the cancer models. Wellcome Sanger Institute (WSI) is a contributing member of the HCMI. Models developed by HCMI are being derived from a number of tumor types and subtypes (see below), including rare adult, pediatric and understudied cancers. The number of models and the clinical sites from which patient samples are acquired is increasing. Normal tissue, originating tumor, and tumor-derived models are sequenced. The next generation cancer models are associated with rich clinical and genomic data through the NCI Genomic Data Commons for all researchers to advance cancer research. The CMDC and HCMI models will serve as excellent tools in research to provide insight into the pathways that influence tumor growth and progression, how tumors respond to therapy, etc. Ultimately, the data generated using these models will support the development of personalized oncology. There is a delay between registered IDs and model availability. The current model count is found in The HCMI Searchable Catalog which is updated when new models are available for distribution to the research community.

  Study phs001486

• Ontario Institute for Cancer Research; Biliary Tract Cancer

  Next Generation Sequencing data from Biliary Tract cancers

  Study EGAS50000000972

• SNP array datas of 'Matched' cancer/PNE

  SNP array data of 31 Matched cancer/PNE samples

  Study EGAS00001003331

• A Sequential Window of Opportunity Trial of Anti-PD-L1/TGF-β trap (M7824) Alone and in Combination with TriAd Vaccine and N-803 for Resectable Head and Neck Squamous Cell Carcinoma not Associated with Human Papillomavirus Infection

  This submission includes the whole exome and bulk RNA sequencing associated with the correlative study of clinical specimens from a prospective clinical study of neoadjuvant bintrafusp alfa in patients with newly diagnosed, surgically resectable oral cavity or laryngeal squamous cell carcinoma. 

  Study phs002849

• Spatiotemporal Analysis of the Human Cerebellum

  We sought to characterize neural progenitors within spatially demarcated regions of the human cerebellum at a molecular level during neurogenesis. We used laser-capture microdissection to enrich for cells within the ventricular zone and subventricular zone regions of the rhombic lip, external granule cell layer and Purkinje cell layer, then performed RNA-sequencing on the enriched samples.

  Study phs001908

• Vulnerabilities of Midbrain Dopaminergic Neurons to Parkinson's Disease Revealed by Single-Cell Genomics

  We developed a novel protocol for the enrichment of midbrain DA neurons from frozen tissue. We subsequently performed single-nuclei RNA-sequencing on enriched samples from postmortem midbrain tissue from human, macaque, tree shrew, rat, and mouse. We identified vulnerable and resistant populations from these data and associated genetic enrichments and differential expression changes.

  Study phs002879

• Personalized Treatment of Sezary Syndrome through a CTLA4:CD28 Fusion

  We sequenced two tumor and one normal whole genome libraries for a Sezary syndrome patient and also sequenced RNA libraries for each tumor. We identified a novel, highly expressed CTLA4:CD28 gene fusion that is predicted to results in a leading to stimulatory T-cell signaling in the presence of an inhibitory signal.

  Study phs000773

• 10X single cell RNA- and feature barcode sequencing of 38 AML samples

  This dataset contains fastq-files from single cell 3' RNA- and feature barcode sequencing of AML samples using 10X technology (Chromium Single Cell 3ʹ Reagent Kit v3). In total, the dataset contains data from 38 AML samples from either bone marrow or peripheral blood, representing the following genetic subtypes: NPM1-mutated, myelodysplasia related, TP53-mutated, CBFB::MYH11, RUNX1::RUNX1T1, AML without class-defining mutations, and AML meeting criteria of two subtypes. The data consists of sequenced gene expression libraries from 38 samples and feature barcoding libraries covering a panel of 10-14 surface proteins for 34 samples.

  Dataset EGAD50000001577

• Paraganglioma Smart-Seq2 Single Nuclei Sequencing Data

  Paraganglioma is a rare neuroendocrine tumor that originates from chromaffin cells of the adrenal medulla or extra-adrenal paraganglia. This study aims to investigate the heterogeneity of this tumor and to identify potential biomarkers associated with its malignancy. To achieve this, we performed single-nucleus RNA sequencing of human paraganglioma samples using the SMART-Seq2 protocol.

  Study EGAS50000001184

• Comprehensive genomic analysis of patient derived orthotopic xenograft model in primary central nervous system lymphoma

  The purpose of this study is to investigate genetic background of orthotopic xenograft cells and aseess consistency with parent tumor cells. For exome sequencing, we used two distinct PCNSL cells (YML9 and YML11). We also performed RNA sequencing for 7 PCNSL patient tumor cells to compare NF-kB pathway activation.

  Study JGAS000178

• Integrative understanding of human immune system by functional genomics and development of intervention strategies for the prevention of autoimmune diseases

  To elucidate the feature of age-associated helper T (ThA) cells and its contribution to autoimmune diseases, single-cell RNA-sequencing analysis of peripheral blood CD4+ T cells from healthy control, CD4+ T cells in muscles and bronchoalveolar lavage fluid (BALF) from patients with idiopathic inflammatory myopathy were conducted.

  Study JGAS000648

• 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/

  Study EGAS00001001590

• Investigation of relapse prediction in infants with MLL-rearranged Acute Lymphoblastic Leukemia

  In infants with ALL, accurate relapse prediction would enable treatment strategies that take relapse risk into account, with potential benefits for both low- and high-risk patients. Through analysis of bone marrow biopsies taken at initial diagnosis, we show that single-cell RNA sequencing can predict future relapse occurrence.

  Study EGAS00001003986