15077 results for "cancer studies using rna-seq"

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• 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

• “Castration-persistence” is a distinct state of tolerance to androgen receptor targeting therapies in prostate cancer

  Androgen receptor (AR) signalling is important in prostate cancer progression, and therapies that specifically target this pathway are the mainstay of treatment for advanced disease. Treatment however is non-curative, and resistance develops inevitably with time. Although the mechanisms that drive progressive ‘castration resistant’ disease are reasonably well characterized, how tumours survive acute pathway inhibition is unclear. We performed a neo-adjuvant study of a novel combination of AR targeting therapies, and noted that the objective response to treatment was highly variable. To determine what was driving tumour persistence in poorly responding patients, we comprehensively characterised pre- and post-treatment samples were using both whole genome and RNA-sequencing. We find that ‘castration-persistence’ is a distinct state from ‘castration-resistance’, and is mediated by global transcriptional reprogramming leading to transitional EMT state, which is shared with benign luminal epithelial cells. This appears to be AP-1 and KLF driven, and represents and integration of multiple signalling pathways, particularly IGF2, offering a number of tractable strategies to improve clinical response to AR targeting therapies.

  Study EGAS00001003172

• clonealign: 10X genomics chromium single-cell RNA-sequencing

  10X genomics chromium single-cell RNA-sequencing of (i) patient derived triple negative breast cancer xenograft (ii) primary tumour and ascites ovarian cancer cell lines at tumour recurrence.

  Dataset EGAD00001004552

• TPM for IMpower133 (GO30081)

  This dataset contains log2(TPM + 1) for 271 tumor samples profiled by RNA-seq for the entire transcriptome for samples originating from IMpower133 (GO30081).

  Dataset EGAD50000000196

• RNA-seq data of CRC-PDX tumors after drug treatment

  We obtained bulk RNAseq data of CRC-PDX tumors after administration of drug or vehicle to clarify the mechanisms of action.

  Dataset EGAD50000000849

• Convergent genetic adaptation in human tumors developed under systemic hypoxia and in populations living at high altitudes

  Genomic files, including whole-exome and RNA-seq data from tumors and cell lines, were generated and analyzed in this study.

  Dac EGAC50000000484

• RNA-seq of murine osteosarcoma cell line genetically modified for CYR61

  Transcriptomic analysis of K7M2 murine osteosarcoma cells stably modified to overexpress or repress CYR61

  Study EGAS50000000526

• Melanoma transcriptome profiling

  This dataset includes transcriptome profiling of 68 early-passage metastatic melanoma cell lines. The data are provided as paired-end RNA seq fastq files.

  Dataset EGAD00001006270

• Melanoma microRNA profiling

  This dataset includes microRNA profiling of 61 early-passage metastatic melanoma cell lines. The data are provided as single-end small RNA seq fastq files.

  Dataset EGAD00001006269

• HDAC inhibitor quisinostat in synovial sarcoma cell lines

  An RNA Seq study of the effects of HDAC inhibitor Quisinostat on six different synovial sarcoma cell lines

  Dataset EGAD00001003810

• 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

• Characterization of Immune-Related Gene Expression in Lung Cancer

  We performed a comprehensive analysis of inter- and intratumor heterogeneity of immune gene expression in 160 lung cancer patients from the Environment And Genetics in Lung cancer Etiology (EAGLE) study. The transcriptome was profiled with RNA sequencing in 269 tumor samples and 110 normal tissue samples from 160 subjects.

  Study phs002346

• Studying the single cell characteristics of pancreatic cancer

  Pancreatic cancer is a dangerous malignancy in the pancreas. In this study we use single-cell RNA sequencing technique to help understand the transcriptome characteristics of pancreatic tumor cells. This study help understands the complex microenvironment of pancreatic tumors and will likely to benefit clinical research of pancreatic cancer treatments.

  Study EGAS00001003889

• Single-cell/single-nucleus RNA-seq of Embryonal Tumor with Multilayered Rosettes (ETMR)

  Embryonal tumor with multilayered rosettes (ETMR) is a pediatric brain tumor with dismal prognosis. We analyzed eleven ETMR patient samples using single-cell transcriptomics. We reveal a spatially distinct cellular hierarchy that spans highly proliferative neural stem-like cells and more differentiated neuron-like cells. C19MC is predominantly expressed in stem-like cells and controls a transcriptional network governing stemness and lineage commitment. Systematic analysis of receptor-ligand interactions between malignant cell types reveals FGFR and NOTCH signaling as oncogenic pathways. Our study provides fundamental insights into ETMR pathobiology and a powerful rationale for more effective targeted therapies.

  Study EGAS50000000937

• Risk and modifying factors in Frontotemporal Dementia

  Understanding the molecular mechanisms underlying frontotemporal dementia (FTD) is essential for the development of successful therapies. Here, we present Phase 1 of a multi-omics, multi-model data resource for FTD research which will allows in-depth molecular research into these mechanisms. We have integrated and analysed data from the frontal lobe of FTD patients with mutations in MAPT, GRN and C9orf72 and detected common and distinct dysregulated cellular pathways. Our results highlight that excitatory neurons are the most vulnerable neuronal cell type and that vascular aberrations are a common hallmark in FTD. Via integration of multi-omics data, we detected several transcription factors and pathways which regulate the strong neuroinflammation observed in FTD-GRN. Finally, using small RNA-seq data and verification experiments in cellular models, we identified several up-regulated miRNAs that inhibit cellular trafficking pathways in FTD and lead to microglial activation. In this work we shed light on novel mechanistic and pathophysiological hallmarks of FTD. In addition, we believe that this comprehensive, multi-omics data resource will further mechanistic FTD research by the community.

  Study EGAS00001004895

• DNA methylation database for gynecological cancer detection, classification and assay development

  MeD-seq data (fastq files) from gynecological cancers and associated healthy tissues. In total 292 fastq files generated by MeD-seq are deposited consisting of: healthy tissues (vulva n=11, cervix n=15, endometrium n=13, fallopian tube n=18 and ovary n=13), precursor lesions of cancer (vulva n=23 and cervix n=46) and cancer (vulva n=21, cervix n=45, endometrium n=26, fallopian tube n=8 and ovary n=33)

  Dataset EGAD50000000611

• 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__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__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

• Integrated RNA-seq analysis of tumor thrombus

  We prospectively enrolled 83 patients with a renal mass and TT scheduled to undergo surgical resection. To accurately integrate genomic and transcriptomic findings and enable histological co-registration, simultaneous isolation of DNA and RNA was performed from individual samples characterized histologically through immediately flanking sections

  Study EGAS00001005512

• Whole Exome and RNA-Sequencing of Germline, Small Bowel Carcinoid Primary Tumor, and Liver Metastasis Trios

  This dataset includes trios of germline/constitutional, primary tumor (small bowel carcinoid), and metastatic tumor (liver) trios for 5 patients (i.e. 15 samples total). Constitutional, primary tumor, and metastatic tumor samples all underwent whole exome sequencing (WES or WXS). Primary and metastatic tumor samples underwent RNA sequencing (RNA-seq).

  Dataset EGAD00001010036

• Transcriptome of CD4+ T cells and CD8+ T cells in glioblastoma multiforme

  Patients included in this study were over 18 years of age and had a histology-confirmed diagnosis of glioblastoma multiforme (GBM). Exclusion criteria were the previous administration of any anti-tumor therapy including radiation therapy. All patients gave written informed consent. The study was approved by the local ethics committee (TUM Medical school) and conducted following the Declaration of Helsinki. During resection of the tumors, tumor tissue and tissue from normal appearing brain within the operative channel was collected. Blood was drawn during the surgical procedure. Single cell suspensions were prepared from the tumor tissue, the normal appearing brain, and the blood. CD4+ T cells and CD8+ T cells were sorted by flow cytometry. Only patients with a complete set of specimens (CD4+ tumor infiltrating lymphocytes (TIL), CD8+ TIL, CD4+ T cells from normal appearing brain, CD8+ T cells from normal appearing brain, blood-derived CD4+ and CD8+ T cells) containing a minimum of 1000 cells in each sorted sample were further analyzed (n=9). Total RNA was isolated from sorted cell populations using the RNAeasy Plus micro kit (Qiagen, 74034). Quality and integrity of total RNA was controlled on a Bioanalyzer 2100 (Agilent Technologies). Library preparation for bulk-sequencing of poly(A)-RNA was done as described previously (Parekh et al., 2016). Briefly, barcoded cDNA of each sample was generated with a Maxima RT polymerase (ThermoFisher Scientific, EP0742) using oligo-dT primer containing barcodes, unique molecular identifiers (UMIs) and an adaptor. Ends of the cDNAs were extended by a template switch oligo (TSO) and full-length cDNA was amplified with primers binding to the TSO-site and the adaptor. NEB UltraII FS kit was used to fragment cDNA. After end repair and A-tailing, a TruSeq adapter was ligated and 3'-end-fragments were finally amplified using primers with Illumina P5 and P7 overhangs. In comparison to previous descriptions (Parekh et al., 2016), the P5 and P7 sites were exchanged to allow sequencing of the cDNA in read 1 and barcodes and UMIs in read 2 to achieve a better cluster recognition. The library was sequenced on a NextSeq 500 (Illumina) with 59 cycles for the cDNA in read 1 and 16 cycles for the barcodes and UMIs in read 2. Data were processed using the published Drop-seq pipeline (v1.0) to generate sample- and gene-wise UMI tables (Macosko et al., 2015). Reference genome (GRCh38) was used for alignment. Transcript and gene definitions were used according to the Genecode Annotation Version 35.

  Dataset EGAD50000000226

• Single-cell RNA-seq of cervical smears and early placental material

  Fastq files of single-cell RNA-sequencing data generated with 10X Genomics of twelve non-invasive cervical samples from pregnant women (7-12 weeks gestational age) and six placental biopsies from patients who had a recurrent miscarriage early during gestation (<12 weeks gestational age).

  Dataset EGAD00001010094

• Integrated analysis of whole genome and RNA sequencing in 22 HBV-associated HCCs

  RIKEN collection WGS and RNA-seq reads for 66 HBV-associated HCC and matched blood or liver samples from 22 donors.

  Dataset EGAD00001001035

• Using_genetics_to_identify_cell_types_and_mechanisms_underlying_susceptibility_to_primary_sclerosing_cholangitis

  Primary sclerosing cholangitis (PSC) is a T-cell mediated, chronic inflammatory condition of the biliary tree that is strongly associated with inflammatory bowel disease. Genome-wide association studies have identified 22 non-HLA genetic risk variants associated PSC. Identifying the genes impacted by these variants has proven difficult as the majority lie in non-coding regions of the genome. Knowledge of the genes and biological pathways these non-coding variants are perturbing is vital to understanding the disease biology. One means of assessing the impact of non-coding variants within disease associated loci upon genes is via colocalisation with eQTL. Many eQTL are cell-type specific, requiring the analysis of disease relevant cell types to detect colocalisation. We have collected PSC-relevant T-cell-subtypes from the peripheral blood of PSC patients via fluorescence activated cell sorting in preparation for RNA sequencing and mapping of eQTL. Samples were collected at the Norfolk and Norwich University Hopital, for which local ethical approval has been granted. Lysed cell samples will be transferred to WTSI and DNA/RNA will be extracted from lysed cell samples by T143 before genotyping (DNA) and custom library preparation and sequencing (RNA). 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 EGAS00001002643