14978 results for "cancer studies using rna-seq"

in 19.29 milliseconds.

• Elevated circulating tumor cells reflect high proliferation and genomic complexity in multiple myeloma - RNA validation cohort

  This reposiroty contains bulk RNA data generated by Blood Cancer Research Group (Ostrava, Czech Republic) as a part of publication named "Elevated circulating tumor cells reflect high proliferation and genomic complexity in multiple myeloma" published in Hemapshere.

  Study EGAS50000001212

• Single-cell proteogenomics of MDS upon AZA

  To study the evolution of the clonal molecular and cellular architecture of MDS upon the treatment with AZA, we performed scDNA-seq of an amplicon panel of 53 genes recurrently mutated in myeloid malignancies, as well as typically lost or gain DNA regions, and scProt-seq of 42 cell-surface proteins to provide a simultaneous landscape of the genetic setting and immunophenotype using the Tapestri platform (MissionBio). We sequenced thousands of cells from 14 MDS patients, where paired bone marrow samples were obtained at the timepoint of diagnosis and after AZA treatment.

  Study EGAS00001007427

• A Pilot Study Using Next Generation Sequencing in Advanced Cancers: Feasibility and Challenges

  In this study, we used NGS to identify somatic events in advanced stage cancer patients to demonstrate the feasibility for using this approach to improve patient treatment.

  Study phs000657

• Transcriptomic Analysis of HIV-Infected Cells

  Defining the attributes of rare CD4 T cells that harbor latent HIV under therapy with anti-retroviral agents has been challenging due to difficulties in identifying and isolating these cells. These cells represent an important barrier to cure, and characterizing them would aid the design and development of novel HIV cure strategies. In this study, we addressed this challenge using a custom microfluidic technology named Focused Interrogation of cells by Nucleic acid Detection and Sequencing (FIND-seq) that isolates HIV-infected cell transcriptomes, based on HIV DNA detection. We applied this method to HIV DNA+ memory CD4 T cells isolated from blood from five persons with HIV who were receiving anti-retroviral agents. After curating samples based on data quality, we proceeded with bioinformatics analysis from three persons. This analysis identified six transcriptomic pathways that were inhibited in HIV DNA+ cells compared to HIV DNA- cells. These included death receptor signaling, necroptosis signaling, and anti-proliferative G-alpha12/13 signaling. Furthermore, we identified two gene clusters, including 60 and 85 genes, that were significantly associated with HIV DNA+ cells identified by co-expression network analysis. These genes included negative regulators of HIV transcription that were higher in HIV DNA+ cells, positive regulators of HIV transcription that were lower in HIV DNA+ cells, and other genes involved in the negative regulation of mRNA translation, additional RNA processing functions, and the regulation of cellular state and fate. We further examined these signatures in transcriptomic data from CD4 T cell subsets sorted by flow cytometry from nine persons with HIV. We found a partial similarity between the smaller cluster of genes and the signature of CCR6- peripheral TFH cells. Raw sequencing data from all eleven human participant samples included in the study are available. These include samples from two participants who were studied only by FIND-seq, three participants who were studied by both FIND-seq and flow cytometry and six participants who were studied only by flow cytometry.

  Study phs003095

• Combination pembrolizumab and radiotherapy induces systemic anti-tumor immune responses in immunologically-cold non-small cell lung cancer

  This data set includes sequence files from whole exome sequencing and RNA sequencing from serial tissue and blood biospecimens from a phase 2 clinical trial of stereotactic body radiation therapy (SBRT) followed by pembrolizumab in metastatic non-small cell lung cancer (NSCLC; NCT02492568).

  Study EGAS50000000277

• National Heart, Lung, and Blood Institute (NHLBI) Heart Healthy Lenoir (HHL) Genomics Study

  The HHL genomics study uses a systems approach to develop models integrating clinical and genomic data. Previously we developed and tested an approach known as the SAMARA (Supporting A Multidisciplinary Approach to Research in Atherosclerosis) project that applied recent advances in biomedical and computational sciences at The University of North Carolina at Chapel Hill to develop a deeper understanding of human cardiovascular disease (CVD). The Heart-Healthy Lenoir Project expands these studies into the community, using this methodology to: 1) determine the prevalence of genomic risk signatures in high-risk community populations using genome-wide Single Nucleotide Polymorphism (SNP) analysis; 2) develop novel genomic models incorporating high-risk features in this population; and 3) determine whether genomic signatures can be used to predict responsiveness to interventions that underlie CVD disparities. DNA was obtained from participants enrolled in two of the HHL clinical trials, 1) Improving Care for Patients With High Blood Pressure (NCT01425515) or 2) Heart-Healthy Lenoir Lifestyle Study (NCT01433484). Participants could enroll in both trials concurrently.

  Study phs001471

• Genome-wide Association Study of Adiposity in Samoans

  The research goal of this study is to identify genetic variation that increases susceptibility to obesity and cardiometabolic phenotypes among adult Samoans using genome-wide association (GWAS) methods. DNA from peripheral blood and phenotypic information were collected from 3,119 adult Samoans, 23 to 70 years of age. The participants reside throughout the independent nation of Samoa, which is experiencing economic development and the nutrition transition. Genotyping was performed with the Affymetrix Genome-Wide Human SNP 6.0 Array using a panel of approximately 900,000 SNPs. Anthropometric, fasting blood biomarkers and detailed dietary, physical activity, health and socio-demographic variables were collected. We are replicating the GWAS findings in an independent sample of 2,500 Samoans from earlier studies. After replication of genomic regions and informative SNPs in those regions, we will determine sequences of the important genes, and determine the specific genetic variants in the sequenced genes that are associated with adiposity and related cardiometabolic conditions. We will also identify gene by environment interactions, focusing on dietary intake patterns and nutrients.

  Study phs000914

• Reference exome data for Australian Aboriginal populations to support health-based research

  Whole exome sequencing (WES) is a popular and successful technology which is widely used in both research and clinical settings. However, there is a paucity of reference data for Aboriginal Australians to underpin the translation of health-based genomic research. Here we provide a catalogue of variants called after sequencing the exomes of 50 Aboriginal individuals from the Northern Territory (NT) of Australia and compare these to 72 previously published exomes from a Western Australian (WA) population of Martu origin. Sequence data for both NT and WA samples were processed using an ‘intersect-then-combine’ (ITC) approach, using GATK and SAMtools to call variants. A total of 289,829 variants were identified in at least one individual in the NT cohort and 248,374 variants in at least one individual in the WA cohort. Of these, 166,719 variants were present in both cohorts, whilst 123,110 variants were private to the NT cohort and 81,655 were private to the WA cohort. Our data set provides a useful reference point for genomic studies on Aboriginal Australians.

  Study EGAS00001003745

• Whole exome sequencing (WES), shallow whole genome sequencing (sWGS), ultra-deep targeted sequencing (TS), RNA whole transcriptome sequencing (RNAseq), targeted TCR sequencing in RNA (RNA-TCRseq) from breast cancer samples.

  Whole exome sequencing (WES), shallow whole genome sequencing (sWGS), ultra-deep targeted sequencing (TS), RNA whole transcriptome sequencing (RNAseq) bam files. Targeted TCR sequencing in RNA (RNA-TCRseq) cram files.

  Dataset EGAD00001003933

• AML Proteogenomic Landscape Whole-transcriptome RNA-Sequencing

  Whole transcriptome RNA-sequencing of purified bone marrow blasts of 136 de novo, treatment naive AML patients. For further details, we refer to the manuscript "The Proteogenomic Landscape of AML" by Jayavelu, Wolf, Buettner et al. mRNA extraction and whole transcriptome sequencing For transcriptome analysis the TruSeq Total Stranded RNA kit was used, starting with 250ng of total RNA, to generate RNA libraries following the manufacturer’s recommendations (Illumina, San Diego, CA, USA). 100bp paired-end reads were sequenced on the NovaSeq 6000 (Illumina) with a median of 57 mio. reads per sample. RNA Data Analysis Data quality control was performed with FastQC v0.11.9. Reads were aligned to the human reference genome (Ensembl GRCh38 release 82) using STAR v2.6.1. Gene count tables were generated while mapping, using Gencode v31 annotations. All downstream analyses were carried out using R v4.0 and BioConductor v3.12 (Huber et al., 2015; R Core Team, 2020). Size-factor based normalization was performed using DESeq2 v1.28.1(Love et al., 2014).

  Dataset EGAD00001008484

• Single-cell RNA-seq of immune cells sorted from human melanoma tumors

  Tumor immune cell compositions play a major role in response to immunotherapy but the heterogeneity and dynamics of immune infiltrates in human cancer lesions remain poorly characterized. Here we identify conserved intratumoral CD4 and CD8 T cell behaviors in scRNA-seq data from 25 melanoma patients. We discover a large population of CD8 T cells showing continuous progression from an early effector "transitional" into a dysfunctional T cell state. CD8 T cells that express a complete cytotoxic gene set are rare, and TCR sharing data suggest their independence from the transitional and dysfunctional cell states. Notably, we demonstrate that dysfunctional T cells are the major intratumoral proliferating immune cell compartment and that the intensity of the dysfunctional signature is associated with tumor-reactivity. Our data demonstrate that CD8 T cells previously defined as exhausted, are in fact a highly proliferating, clonal and dynamically differentiating cell population within the human tumor microenvironment.

  Study EGAS00001003363

• Integrative genomic analysis reveals cancer-associated mutations at diagnosis of CML in patients with high risk disease

  Genomic events associated with poor outcome in chronic myeloid leukemia (CML) are poorly understood. We performed whole exome sequencing, copy number variation and/or RNA-Seq for 65 patients to discover mutations at diagnosis and blast crisis (BC). Forty-six chronic phase patients with the extremes of outcome were studied at diagnosis. Cancer gene variants were detected in 15/27 patients (56%) with subsequent BC or poor outcome and in 3/19 optimal responders (16%), P=.007. Frequently mutated genes at diagnosis were ASXL1, IKZF1 and RUNX1. The methyltransferase SETD1B was a novel recurrently mutated gene. A novel class of variant associated with the Philadelphia translocation was detected at diagnosis in 11/46 patients (24%) comprising fusions and/or rearrangement of genes on the translocated chromosomes, with evidence of fragmentation, inversion and imperfect sequence reassembly. These were more frequent at diagnosis in patients with poor outcome: 9/27 (33%) versus 2/19 optimal responders (11%), P=.07. Thirty-nine patients were tested at BC and all had cancer gene variants, including ABL1 kinase domain mutations in 58%. However, ABL1 mutations co-occurred with other mutated cancer genes in 89% of cases, and these predated ABL1 mutations in 62% of evaluable patients. Gene fusions not associated with the Philadelphia translocation occurred in 42% of patients at BC and commonly involved fusion partners that were known cancer genes (78%). Genomic analysis revealed numerous relevant variants at diagnosis in patients with poor outcome and all patients at BC. Future refined biomarker testing of specific variants will likely provide prognostic information to facilitate a risk-adapted therapeutic approach.

  Study EGAS00001003071

• Plasma mutation profile of precursor lesions and colorectal cancer using the Oncomine Colon cfDNA Assay

  Colorectal cancer (CRC) is the second leading cause of cancer death worldwide. Early detection of precursor lesions or early-stage cancer could hamper cancer development or improve survival rates. Liquid biopsy, which detects tumor biomarkers, such as mutations, in blood, is a promising avenue for cancer screening. To assess the presence of genetic variants in plasma cell-free tumor DNA from patients with precursor lesions and colorectal cancer using the commercial Oncomine Colon cfDNA Assay. Cell-free DNA (cfDNA) samples from the blood plasma of 52 Brazilian patients were analyzed. Eight patients did not have any significant lesions (five normal colonoscopies and three hyperplastic polyps), 24 exhibited precursor lesions (13 nonadvanced adenomas, ten advanced adenomas, and one sessile serrated lesion), and 20 patients with cancer (CRC). The mutation profile of 14 CRC-associated genes were determined by next-generation sequencing (NGS) using the Oncomine Colon cfDNA Assay in the Ion Torrent PGM/S5 sequencer.

  Dataset EGAD50000000679

• S_CORT_Stratification_in_COloRecTal_cancer_

  Colorectal cancer samples will be submitted for Illumina sequencing using a custom capture of 116 genes implicated in colorectal tumourigenesis. Driver mutations will be detected and ultimately correlated with phenotypic data.

  Study EGAS00001001521

• Deciphering RBP - alternative splicing networks in ALS iPSC-MN: TDP-43, NOVA1, NOVA2 and RBFOX2 eCLIP-seq

  We produced enhanced cross-linking immunoprecipitation (eCLIP) sequencing data of the RNA binding proteins (RBP) TDP-43, NOVA1, NOVA2 and RBFOX2 in iPSC motor neurons of two healthy control individuals, respectively.

  Study EGAS00001005880

• Single cell RNAseq of PBMC from bladder cancer patients

  This dataset contains single cell RNA sequencing data of PBMC samples from 20 bladder cancer patients. cDNAs and single cell RNA libraries were prepared following manufacturer’s user guide (10x Genomics). Each library was sequenced in HiSeq4000 (Illumina) to achieve ~300 million reads following manufacturer’s sequencing specification.

  Dataset EGAD00001006182

• small RNA next generation sequencing in head and neck cancer

  small RNA next generation sequencing in head and neck cancer

  Dataset EGAD00001008402

• Genetic Studies in the Hutterites

  We conducted genetic studies of disease-associated quantitative phenotypes, including microbiome and gene expression studies, and common diseases, such as asthma and Alzheimer's disease, by genotyping and/or sequencing in the Hutterites, a founder population of European descent. The Hutterites who have participated in our studies live on communal farms in South Dakota and are related to each other through multiple lines of descent in a 3,657-person, 13-generation pedigree with 64 founders. The small number of founding genomes reduces genetic heterogeneity whereas their communal lifestyle ensures that non-genetic factors are remarkably uniform between individuals. Our sample includes >1,600 subjects who have participated in our studies of fertility (since 1982), asthma, cardiovascular disease and other complex phenotypes (since 1993), microbiome studies (since 2011), and/or immune response (since 2012). The variable 'Total number of consented subjects' reflects the count of subjects with individual level phenotype and genotype data in dbGaP.

  Study phs000185

• cfDNA methylation dataset for colon cancer

  Enzymatic conversion-based methylation sequencing data (EM-seq) for colon cancer used in the MESA study

  Dataset EGAD50000000075

• Evaluation of novel therapies using primary cultured gynecological cancer cells and search for predictors of efficacy

  The objective of this study is to establish an optimal method to evaluate the anti-tumor efficacy and biological activity of the novel therapies under investigation in our department using cancer tissues and cells derived from patients with gynecological malignancies in vitro and to evaluate them in practice. This research will contribute to the development of new treatments for gynecological cancer.

  Study JGAS000809

• Human Blastocyst 10X Single Cell RNA Sequencing

  Recent advances in human blastoids have opened new avenues for modeling early human development and implantation. One limitation of our first protocol for human blastoid generation was relatively low efficiency. We now report an optimized protocol for the efficient generation of large quantities of high-fidelity human blastoids from naive pluripotent stem cells. This enabled proteomics analysis that identified phosphosite-specific signatures potentially involved in the derivation and/or maintenance of the signaling states in human blastoids. Additionally, we uncovered endometrial stromal effects in promoting trophoblast cell survival, proliferation, and syncytialization during co-culture with blastoids and blastocysts. Side-by-side single-cell RNA sequencing revealed similarities and differences in transcriptome profiles between pre-implantation blastoids and blastocysts, as well as post-implantation cultures, and uncovered a population resembling early migratory trophoblasts during co-culture with endometrial stromal cells. Our optimized protocol will facilitate broader use of human blastoids as an accessible, perturbable, scalable, and tractable model for human blastocysts. In addition, this study is the first to use the 10X Genomics platform for human blastocysts, and we anticipate this resource will be widely used by the community as a reference for future studies.

  Study phs003122

• Kidney_tumour_RNA

  This is a bulk DNA and RNA sequencing study of human renal tumours

  Study EGAS00001002487

• Aggregated panel-seq VCF for initial cohort screened for BoB

  Aggregated VCF file from cancer genes panel seq for the initial (n=500) cohort of solid tumors screened for the Basket of Baskets study

  Dataset EGAD00001008437

• Melanoma Genome Sequencing Project

  Melanoma is the most prevalent cause of skin cancer morbidity and mortality. In order to characterize the full range of somatic mutations that may drive the growth of melanoma, we are sequencing tumor and normal DNA from a set of roughly 150 melanomas. For the majority of samples (approximately 90% of the cases), mutations in protein coding genes will be assessed in the exonic DNA of tumor-normal pairs using hybrid capture and paired-end DNA sequencing. For a few of DNA samples (approximately 10% of the cases), the entire genomes will be analyzed to assess the possible contribution of complex structural rearrangements contributing to oncogenesis. The sequencing data are supplemented by copy number profiling on the same tumors using high-density SNP arrays. Integration of these approaches will enable the unbiased and comprehensive characterization of both known and novel recurrent DNA alterations that arise in melanoma.Versions 1-4 contain whole exome and bulk RNA sequencing data for patients with melanoma.Version 5 - We compared somatic genomic profiles from matched pre-treatment and post-resistance tumor biopsies in patients with metastatic melanoma who exhibited heterogeneous responses to immune checkpoint inhibitors (ICIs). This version includes whole exome sequencing (WES) data from 14 patients.

  Study phs000452

• smMIP-seq of 18 FFPE prostate samples (normal and tumour pairs) to identify mutations

  smMIP-Seq was performed on radical prostatectomy formalin-fixed paraffin-embedded sample pairs (n = 18). Library prep was done by capture of targeted sequences with single molecule (unique molecular index) tagged molecular inversion probes (MIP) and sequenced as 75bp paired end on Illumina NextSeq 500. Sequences were aligned to the human genome (hg38) using BWA.

  Dataset EGAD00001006109

• Genome-Wide Analysis for Addiction Susceptibility Genes

  Genome wide analysis for addiction susceptibility genes is an affected sibling pair linkage study using subjects who were patients in methadone replacement treatment programs (MMTP). Such patients are highly addicted to opioids and usually to other addicting substances as well. For entry into the programs, patients had to be at least 18 years of age and had to satisfy DSM-IV criteria for opioid dependence. Despite their common substance use disorder diagnosis, patients enrolled in MMTPs generally have a heterogeneous mix of co-morbid psychiatric disorders including anti-social personality disorder, major depression and anxiety disorders, and often satisfy DSM-IV criteria of substance use disorders other than opioid dependence. Genetic analysis was carried out using genotyping data obtained from a 10K SNP array, and non-parametric linkage was assessed using MERLIN. This resulted in the identification of a linkage peak on 14q that overlapped the NRXN3 gene (neurexin 3), which was previously identified as a potential candidate gene for addiction, and subsequently identified as a target gene in other addiction studies and autism. In version 2 of this study, a text file containing 7704 SNPs with large allele frequency discrepancy as compared to 1000 Genomes is included. Users have the option to exlude these 7704 SNPs.

  Study phs001266

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__Colorectal_LCM

  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 EGAS00001003455

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__Colorectal

  he 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 EGAS00001003774

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__clear_cell_renal_cell_carcinoma___2

  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 EGAS00001003542

• A Functional Network of Gastric-Cancer-Associated Splicing Events Controlled by Dysregulated Splicing Factors

  Except for a few genes known to have oncogenic spliceforms in gastric cancer, the full scope of aberrant splicing in gastric oncogenesis remains unclear. In this study, we elucidated the alternative splicing events associated with gastric carcinogenesis and identified upstream regulators governing these events. We performed RNA-seq on 19 matched tumor/normal pairs and a panel of gastric cancer cell lines, and identified 361 tumor associated (TA) alternative splicing events (ASEs), which included known oncogenic ASEs in genes such as INSR, FGFR2, CD44 and KRAS. We further identified 8 splicing factors dysregulated in gastric tumors, the expression of which are correlated to the splice ratio of the TA ASEs. We thereby constructed a dysregulated splicing network in gastric cancer, consisting of alternative splicing changes correlated to their potential regulators. This network featured three potential regulatory modules centered around the splicing factors ESRP2, MBNL1 and PTPB1. Knockdown of each splicing factor led to the expected changes in splicing of approximately half of the ASEs assayed. Thus, dysregulation of the splicing factors indeed was the cause of many of the TA ASEs. Pathway enrichment analysis showed that genes affected by tumor associated splicing were pre-dominantly involved in cytoskeletal organization. Concordant with this, knockdown of the splicing factors regulating the TA ASEs led to the expected changes in trans-well migration activity. Thus, we have established for the first time a comprehensive splicing network that likely drives gastric tumor progression, based on which novel therapeutic targets can be identified for further evaluation.

  Study EGAS00001002256