15138 results for "cancer studies using rna-seq"

in 21.64 milliseconds.

• Study of Addiction: Genetics and Environment (SAGE)

  This study is part of the Gene Environment Association Studies initiative (GENEVA) funded by the National Human Genome Research Institute. The overarching goal is to identify novel genetic factors that contribute to addiction through a large-scale genome-wide association study of DSM-IV alcohol dependent (and frequently illicit drug dependent) cases and non-dependent, unrelated control subjects of European and African American descent. The focus of this proposal is a case-control design of unrelated individuals for a genetic association study of addiction. Cases are defined as individuals with DSM-IV alcohol dependence (lifetime) and potentially other illicit drug dependence. In addition to the categorical diagnosis, we have data on ordinal measurements of number of DSM-IV symptoms for alcohol, nicotine, marijuana, cocaine, opiates and other drugs so that we will able to construct quantitative measurements of addiction severity over a wide range of substances. Controls are defined as individuals who have been exposed to alcohol (and possibly to other drugs), but have never met lifetime diagnosis for alcohol dependence or dependence on other illicit substances. Analyses that include refinement of the phenotype and incorporation of important demographic and environmental factors into association studies will be pursued. Cases and controls were selected from three large, complementary datasets: the Collaborative Study on the Genetics of Alcoholism (COGA), the Family Study of Cocaine Dependence (FSCD), and the Collaborative Genetic Study of Nicotine Dependence (COGEND). COGA: COGA was initiated in 1989 and is a large-scale family study that has had as its primary aim the identification of genes that contribute to alcoholism susceptibility and related characteristics. COGA is funded through the National Institute on Alcohol Abuse and Alcoholism (NIAAA). Subjects were recruited from 7 sites across the U.S. Alcohol dependent probands were recruited from treatment facilities and assessed by personal interview. After securing permission, other family members were also assessed. A set of comparison families was drawn from the same communities as the families recruited through the alcohol dependent probands. Assessment involved a comprehensive personal interview developed for this project, the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA), which gathers detailed information on alcoholism related symptoms along with other drugs and psychiatric symptoms. Families with three or more first-degree relatives who were alcohol dependent were invited for more extensive testing, including neurophysiology evaluations (ERPs and EEGs) and a battery of neuropsychological assessments. Blood was obtained for genetic studies. Institutional Review Boards at all sites approved the protocols, including sharing in the NIAAA national repository. COGA has four Co-Principal Investigators Bernice Porjesz, Victor Hesselbrock, Howard Edenberg, and Laura Bierut. COGA includes nine different centers where data collection, analysis, and storage take place. The nine sites and Principal Investigators and Co-investigators are: University of Connecticut (Victor Hesselbrock); Indiana University (Howard Edenberg, John Nurnberger, Jr., Tatiana Foroud); University of Iowa (Samuel Kuperman); SUNY Downstate (Bernice Porjesz); Washington University in St. Louis (Laura Bierut, Alison Goate, John Rice); University of California at San Diego (Marc Schuckit); Howard University (Robert Taylor); Rutgers University (Jay Tischfield); Southwest Foundation (Laura Almasy). Q. Max Guo serves as the NIAAA Staff Collaborator. This national collaborative study is supported by the NIH Grant U10AA008401 from the National Institute on Alcohol Abuse and Alcoholism (NIAAA) and the National Institute on Drug Abuse (NIDA). Family Study of Cocaine Dependence (FSCD): This project was initiated in 2000 as a case-control family study of cocaine dependence funded through the National Institute on Drug Abuse (NIDA; PI: Laura Bierut). The primary goal was to increase the understanding of the familial and non-familial antecedents and consequences of cocaine dependence. Cocaine dependent individuals were systematically recruited from chemical dependency treatment units (both public and private; residential and outpatient) in the greater St. Louis metropolitan area. Community based control subjects were identified through a Missouri Driver's License Registry (maintained at Washington University for research purposes) and matched by age, race, gender, and residential zip code. As a supplement to this project, blood samples were collected for future genetic analysis and were included in the NIDA Genetics Consortium. Phenotypic data, DNA, and cell lines are in the NIDA Center for Genetics Studies. Collaborative Genetic Study of Nicotine Dependence (COGEND): COGEND was initiated in 2001 as a three-part program project grant funded through the National Cancer Institute (NCI; PI: Laura Bierut). The three projects included a study of the familial transmission of nicotine dependence, a genetic study of nicotine dependence, and a study of the relationship of nicotine dependence with nicotine metabolism. The primary goal is to detect, localize, and characterize genes that predispose or protect an individual with respect to heavy tobacco consumption, nicotine dependence, and related phenotypes and to integrate these findings with the family transmission and nicotine metabolism findings. The primary design is a community based case-control family study. All subjects were recruited from Detroit and St. Louis. Nicotine dependent cases and non-dependent smoking controls were identified and recruited. In addition, one sibling for each case and control subject was recruited in a subset of the sample. Over 56,000 subjects aged 25-44 years were screened by telephone, over 3,100 subjects were personally interviewed, and over 2,900 donated blood samples for genetic studies. All three studies (COGA, COGEND, FSCD) include measures of basic socio-demographic variables, including age, sex, race/ethnicity, family income, educational attainment, religious participation, and family structure. Other important covariates and/or potential moderators of genetic effects include comorbid addictions and age at initiation of use for cigarettes, alcohol and drugs. The assessments also include measures of various life stressors, such as physical and sexual abuse, which have been implicated in gene-environment interactions for several disorders. Coding for both individual variables and indices has been standardized across studies. All subjects were assessed in person by trained research assistants. Funding support for genotyping, which was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR), was provided by the NIH GEI (U01HG004438), the National Institute on Alcohol Abuse and Alcoholism, the National Institute on Drug Abuse, and the NIH contract "High throughput genotyping for studying the genetic contributions to human disease"(HHSN268200782096C). Note for Publications Related to Study: The Study of Addiction: Genetics and Environment (SAGE) has not yet generated publications. Below is a listing of publications related to the three studies from which the SAGE sample was selected. COGA has over 228 publications listed at www.niaaagenetics.org This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to addiction through a large-scale genome-wide association study of DSM-IV alcohol dependent (and frequently illicit drug dependent) cases and non-dependent, unrelated control subjects of European and African American descent. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000092

• Translating Gene-Calcium Interactions to Precision Medicine for Colorectal Cancer

  Identify functional and rare SNPs and their interactions with Ca intake levels in relation to risk of incident adenoma using whole-exome resequencing of 2468 colorectal adenoma cases and controls from PLCO. We will genotype promising rare and functional SNPs associated with incident adenoma in 570 incident cancer cases, 1,710 healthy controls, 710 adenoma recurrence cases and 966 recurrent adenoma controls from the intervention arm of PLCO to both confirm the associations with adenoma, and to identify when, in the natural history of CRC, chemoprevention by Ca-gene interactions occurs. We hypothesize that Ca-gene interactions prevent early-stage (incident adenoma) and mid-stage (adenoma recurrence) carcinogenesis as well as span the entire CRC carcinogenesis spectrum (i.e. incident CRC).

  Study phs002164

• TGS___Comprehensive_Molecular_Characterization_of_Colorectal_Cancer_Metastases__MOSAIC_

  Systematic next generation sequencing efforts are beginning to define the genomic landscape across a range of primary tumours, but we know very little of the mutational evolution that contributes to disease progression.We therefore propose to obtain a comprehensive description of genomic, transcriptomic and epigenomic changes in a cohort of matched primary and metastatic colorectal cancers, and additionally to explore the extent to which those mutations identified as recurrent in the metastatic setting are able to subvert normal biological processes using both genetically engineered mouse models and established cancer cell lines. This study will enable us to define to what extent primary tumour profiling can capture the biological processes operative in matched metastases as well as the significance of intratumoural heterogeneity.

  Study EGAS00001000958

• Clonal dominance defines metastatic dissemination in pancreatic cancer

  Using patient-derived cells from a pancreatic ductal adenocarcinoma, we created orthotopic clonal replica tumors to trace in an unbiased fashion clonal lineage dynamics of unperturbed tumor expansion and dissemination over time. The model revealed the complex multifaced nature of tumor clonal expansion and uncovered brisk changes in fitness that lead to a continuous reshuffling of tumor clonal architecture and alternating clonal dominance as a distinct feature of cancer growth. Paired analysis of clonal lineages in primary and secondary sites revealed fitness in the primary tumor as a major contributor to dissemination, although other clonal intrinsic and extrinsic factors may contribute to metastatic process. Molecular characterization of lineages with differential metastatic potential identified actionable strategy to suppress dissemination at the subclonal level.

  Study EGAS00001006358

• CRUK-ICGC Prostate DNA Methylation Sequencing Dataset (Prostatectomy Batches 1-6)

  This dataset includes Illumina EPIC Capture Sequencing Data of 376 samples from 188 men with prostate cancer. Samples were taken from primary tissue obtained at prostatectomy, with matched pathologically assessed non-cancer control material. This DNA methylation data includes donors and samples included in previously published WGS datasets (from CRUK-ICGC batches 1 to 3 [EGAD00001001116] and batches 4 to 6 [EGAD00001003225]; including the majority of donors used in Wedge et al, Nature Genetics 2018 [PMID: 29662167]). The targeted DNA methylation sequencing data in this EGA dataset were generated using the Illumina TruSeq methyl capture method (EPICseq), covering over 3.3 million CpGs in the human genome, representing a total targeted hybridisation capture panel of 107Mbp. According to the EPICseq protocol, DNA samples extracted from prostatectomy tissue samples were enriched for target regions using hybridisation capture, prior to bisulfite conversion, amplification and sequencing in pools of 12 samples (150 single end reads over two Illumina HiSeq4000 lanes). This approach generated DNA methylation profiles from prostate cancer and control samples at base-pair resolution across millions of CpGs in the human genome.

  Dataset EGAD00001010184

• Full genome sequencing of a monozygotic twin discordant for schizophrenia

  We sequenced the genomes from a monozygotic twin discordant for schizophrenia and a tumor-normal pair of an ovarian cancer patient. Using whole-genome twin data to discriminate between correctly identified single nucleotide variants (SNVs) and errors a strategy for the accurate detection of SNVs was developed. By applying stringent sequencing quality measures, excluding error-prone regions and selecting SNVs identified by different mapping and variation calling algorithms, error rates were ~37-fold reduced. This enabled us to identify the first discordant SNVs in monozygotic twins using whole-genome sequencing. In addition, by showing that novel SNVs are highly enriched in errors, accurate estimates of the number of novel and rare SNVs occurring in unrelated Caucasian individuals were obtained. Finally, somatic mutations in coding and regulatory sequences were reliably identified in the highly rearranged ovarian tumor. Overall, our data demonstrate that strategies to reduce error rates in whole-genomes are required for disease gene discovery.

  Study EGAS00001000152

• Neuroblastoma Smart-Seq2 Single Nuclei Sequencing Data

  Heterogeneity of tumors, including the presence of resistant clones, represents a great challenge for high-risk neuroblastoma (NB). Currently, there are no treatments that address cancer heterogeneity. Classification of bulk tumors and corresponding predictions are poor and too general. Understanding heterogeneity will provide critical insight for the development of targeted therapeutic strategies. In this study, we collected 10 human neuroblastoma tumor samples and performed whole-transcriptome profiling at single-nucleus resolution using SMART-Seq2 technology. This approach enables comprehensive characterization of transcriptional diversity within individual tumors, allowing us to identify distinct cellular subpopulations.

  Study EGAS50000001103

• Genetic landscape of pediatric Infant Acute Lymphoblastic leukemia

  We performed whole genome sequencing of tumor and normal DNA samples obtained from 22 infant ALL cases with MLL rearrangements. In addition, we sequenced 2 paired diagnostic-relapse samples. Using complementary pipelines, somatically acquired genetic changes were analyzed, including single nucleotide variations (SNVs), insertion/deletions, structural variations and copy number variations in the cancer genomes. In addition, exome sequencing was performed on paired diagnostic and normal DNA samples obtained from 20 cases of non-infant MLL rearranged leukemias and somatic mutations in the coding regions were identified.

  Study EGAS00001000246

• HCA_Female_Reproductive_Adult_WSSS_RNA

  HCA Endometrium_LM The endometrium regenerates monthly and its transformation is executed through dynamic changes in states and interactions of multiple cell types. Using transcriptomics methods we seek to profile changes of the endometrium across the menstrual cycle. Our map will have implications in women’s health and cancer, by enabling the interpretation of GWAS analyses or the studying functional consequences of somatic mutations. 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 EGAS00001004727

• Single cell exome sequencing of lung adenocarcinoma

  Single cell exome sequencing was performed on 200 single cells isolated from a lung adenocarcinoma, female, non-smoker patient. The cells were derived from two distant tumour sectors and a far normal sector. The single cells were amplified on the Fluidigm C1 machine using the GE Healthcare illustra GenomiPhi V2 DNA Amplification Kit prior to sequencing library preparation. In addition, bulk exome sequencing was also conducted for each tumour sectors. For this study, somatic variations were detected from the single cells and phylogenetic clustering was conducted to elucidate the evolutionary trajectory of lung cancer.

  Study EGAS00001002972

• Patterns of transcription factor programs and immune pathway activation define four major subtypes of SCLC with distinct therapeutic vulnerabilities

  Despite molecular and clinical heterogeneity, small cell lung cancer (SCLC) is treated as a single entity with predictably poor results. Using tumor expression data, we applied non-negative matrix factorization, which identified four SCLC subtypes defined largely by differential expression of transcription factors ASCL1, NEUROD1, and POU2F3 or low expression of all three transcription factor signatures accompanied by an Inflamed signature (SCLC-A, N, P and I, respectively). The presence of these subtypes were then validated in tumor gene expression data from the IMpower133 clinical trial.

  Study EGAS00001004888

• Systematic dissection of tumor-normal single-cell ecosystems across a thousand tumors of 30 cancer types

  The complexity of the tumor microenvironment poses significant challenges in cancer therapy. Here, to comprehensively investigate the tumor-normal ecosystems, we perform an integrative analysis of 4.9 million single-cell transcriptomes from 1,070 tumor and 493 normal samples in combination with pan-cancer 137 spatial transcriptomics, 8,887 TCGA, and 1,261 checkpoint inhibitor-treated bulk tumors. We define a myriad of cell states constituting the tumor-normal ecosystems and also identify hallmark gene signatures across different cell types and organs. Our atlas characterizes distinctions between inflammatory fibroblasts marked by AKR1C1 or WNT5A in terms of cellular interactions and spatial co-localization patterns. Co-occurrence analysis reveals interferon-enriched community states including tertiary lymphoid structure (TLS) components, which exhibit differential rewiring between tumor, adjacent normal, and healthy normal tissues. The favorable response of interferon-enriched community states to immunotherapy is validated using immunotherapy-treated cancers (n=1,261) including our lung cancer cohort (n=497). Deconvolution of spatial transcriptomes discriminates TLS-enriched from non-enriched cell types among immunotherapy-favorable components. Our systematic dissection of tumor-normal ecosystems provides a deeper understanding of inter- and intra-tumoral heterogeneity.

  Study EGAS50000000324

• Decoding Human Heart Morphogenesis through Single-cell Multi-modal Analyses

  The heart, which is the first organ to develop, is highly dependent on its form to function. However, how diverse cardiac cell types spatially coordinate to create complex morphological structures critical for heart function remains to be elucidated. Here, we show that integration of single cell RNA-sequencing with high-resolution multiplexed error-robust fluorescent in situ hybridization (MERFISH) not only resolves the identity of cardiac cell types developing the human heart but also provides a spatial mapping of individual cells that enables illumination of their organization into cellular communities forming distinct cardiac structures. We discovered that many of these cardiac cell types further specified into subpopulations exclusive to specific communities, supporting their specialization according to cellular ecosystem and anatomic region. In particular, ventricular cardiomyocyte subpopulations displayed an unexpected complex laminar organization across the ventricular wall and formed, with other cell subpopulations, several cellular communities. Interrogating cell-cell interactions within these communities revealed signaling pathways orchestrating the spatial organization of cardiac cell subpopulations during ventricular wall morphogenesis. In vivo conditional genetic mouse models and in vitro human pluripotent stem cell studies confirmed an intricate multicellular PLXN-SEMA crosstalk among specific ventricular cardiomyocyte, fibroblast and endothelial cell subpopulations that directs the compaction of the ventricular wall layers. Thus, these detailed findings into the cellular social interactions and specialization of cardiac cell types constructing and remodeling the human heart offer new insights into structural heart diseases as well as engineering complex multi-cellular tissues for human heart repair. Reprinted from Farah et al. (In press), with permission from Nature.

  Study phs002031

• Innate myeloid cell sbuset-specific gene expression patterns in the human colon are altered in Crohn's disease patients

  Background: There is a heterogeneous subset innate myeloid cells, such as macrophages and dendritic cells, in the human intestinal lamina propria. Several studies have demonstrated that these cells contribute to the maintenance of gut homeostasis through induction of inflammatory responses and tolerance via cell type-specific mechanisms; whereas, disrupted innate immune responses are implicated in the pathogenesis of Crohn?s disease. However, the detailed mechanisms by which each innate myeloid subset regulates gut homeostasis and inflammation largely remains unknown. Aim: We aimed to clarify the comprehensive gene expression profiles of innate myeloid cell subsets in the lamina propria from normal human colons (NC) and the inflamed colon sites from patients with Crohn?s disease (CDi). Methods: We performed RNA-sequencing analysis and precise bioinformatics analysis on three innate myeloid cell subsets, CD14-CD11c-, CD14-CD11c+, and CD14+CD11c+CD163low cells from NC and CDi. Results: Transcriptional analysis of the three subsets from the NC showed distinct gene expression patterns and gene ontology (GO) enrichment analysis revealed the associated innate myeloid subset-specific biological process (BP) terms. In addition, changes in gene expression patterns were observed in innate myeloid subsets from CDi. Furthermore, the core GO-BP terms for the genes upregulated in the innate myeloid cells from CDi were distinct from those found in NC. Conclusion: Our data identified the innate myeloid cell subset-specific transcriptomes and the associated enriched GO-BP terms in the NC and found these patterns were altered in CDi.

  Study JGAS000127

• Longitudinal_profiling_of_the_immune_response_to_Plasmodium_vivax_in_naive_hosts_by_RNA_sequencing

  Plasmodium vivax offers unique challenges for control and elimination, and may prove a tougher hurdle to overcome than Plasmodium falciparum. And yet compared to P. falciparum we know very little about the innate and adaptive immune responses that need to be harnessed to reduce disease and transmission. We recently generated a blood bank of a new clonal field isolate of P. vivax (PvW1) for human challenge studies and used systems immunology tools to track the host response throughout infection and convalescence. As part of this study, RNA-sequencing was used to resolve changes in whole blood gene expression through time in 6 volunteers (7-9 time-points per volunteer). In summary, these data show that P. vivax induces two distinct transcriptional programmes in whole blood during and after infection. During infection, transcriptional profiling reveals the rapid mobilisation of an emergency myeloid response, which leads to systemic inflammation and the recruitment of all major T cell subsets into lymphoid tissues. Six days after infection, this innate response subsides and a transcriptional signature of proliferation is revealed. This most likely represents widespread activation of lymphocytes, which return to the circulation after parasite clearance - transcriptional profiling of T cells at this time-point could therefore reveal the outcomes of critical cell-cell interactions that take place within the spleen during infection. 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 EGAS00001003847

• ecDNA copy number heterogeneity

  Neuroblastoma exhibits significant inter- and intra-tumour genetic heterogeneity and varying clinical outcomes. Here, we used DNA and RNA sequencing from the same single cells in cell lines and neuroblastoma patients to investigate these effects. We reveal extensive intercellular ecDNA copy number heterogeneity. We also provide direct evidence of how this heterogeneity influences the expression of cargo genes, including MYCN and its downstream targets, and the overall transcriptional state of neuroblastoma cells.

  Study EGAS50000000509

• RNA sequencing of untreated head and neck cancer patient-derived xenografts (PDXs) and matched patient tumor tissue.

  RNA sequencing was performed on untreated patient tumor tissue and matched patient-derived xenograft (PDX) models of primary head and neck squamous cell carcinoma (HNSCC). The aim of this analysis was to characterize the transcriptional landscape of the tumors in the in vivo setting. 117 total samples were sequenced with paired reads on 10 lanes from different flowcells. They were loaded as 2400 separate files to maintain the data as it was received from BGI - each sample is therefore composed of 5 separate EGAN with 4 files each, adding a 0.1 - .. - 0.5 to each BioSample ID to generate sample aliases. All R1 (and R2, separately) files referring to a BioSample ID should be concatenated to obtain fastq files corresponding to single patients or PDXs.

  Dataset EGAD50000002278

• Detection of brain cancer using genome-wide cell-free DNA fragmentomes

  Diagnostic delays in patients with brain cancer are common and can impact patient outcome. Development of a blood-based assay for detection of brain cancers could accelerate brain cancer detection. In this study, we analyzed genome-wide cell-free (cfDNA) fragmentomes, including fragmentation profiles and repeat landscapes, from the plasma of individuals with (n=148) and without (n=357) brain cancer. Machine learning analyses of cfDNA fragmentome features detected brain cancer across all grade gliomas (AUC=0.90, 95% CI: 0.87-0.93) and these results were validated in an independent prospectively collected cohort. cfDNA fragmentome changes in patients with gliomas represented a combination of fragmentation profiles from glioma cells and altered white blood cell populations in the circulation. These analyses reveal the properties of cfDNA in patients with brain cancer and open new avenues for noninvasive detection of these individuals.

  Study EGAS50000000986

• Targeted Illumina sequencing of 3399 plasma cfDNA samples and 1988 leukocyte DNA samples from 1995 metastatic prostate cancer patients

  Blood samples were collected from eight clinical trials and a British Columbia-based biobank. All plasma cfDNA and leukocyte DNA samples were processed with uniform methodology, and underwent targeted sequencing using a custom hybridization capture panel and Illumina instruments. Four different generations of custom hybridization capture panel were used, all providing coverage of the complete coding regions of 72 prostate cancer genes, and later panel generations also providing exhaustive coverage of the AR locus (including introns and flanking regulatory regions), as well as a genome-wide SNP grid for copy number analysis.

  Dataset EGAD50000001594

• CRISPR/Cas9-mediated genome editing of Schistosoma mansoni acetylcholinesterase

  Here we report successful gene knock-in (KI) in the eggs of Schistosoma mansoni by combining CRISPR/Cas9 with single-stranded oligodeoxynucleotides (ssODNs). We targeted the acetylcholinesterase (AChE) gene of S. mansoni using two synthetic guide RNAs (gRNAs), X5 and X7, respectively. Liver eggs of S. mansoni were exposed to CRISPR-vector containing X5 or X7 by electroporation. Simultaneously, eggs were transfected with a ssODN donor encoding a stop codon in all six frames. Next generation sequencing analysis revealed that CRISPR/Cas9-mediated editing in S. mansoni eggs resulted in Homology-Directed Repair (HDR) when template DNA ssODN provided. Furthermore, soluble egg antigen (SEA) from AChE-modified eggs exhibited markedly reduced AChE activity compared with controls, indicative that programmed Cas9 cleavage mutated the AChE gene. Following injection of modified schistosome eggs into the tail veins of mice, a significant decrease in granuloma size in the lungs of these animals. Notably, an enhanced Th2 response induced by eggs in lung, and splenocytes small intestine-draining mesenteric lymph node cells was also generated in mice injected with X5-KI eggs in different methods. These findings further demonstrate the power and utility of CRISPR/Cas9-based genome editing for undertaking functional genomics studies in schistosomes.

  Dataset EGAD00001006573