15028 results for "cancer studies using rna-seq"

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• MutWP1: CRUK Grand Challenge Mutographs of Cancer: Colorectal_LCM (2020-02-20)

  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. . This dataset contains all the data available for this study on 2020-02-20.

  Dataset EGAD00001005994

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: pancreas (2019-04-03)

  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 (Illumina HiSeqX, 40X and 20X depth respectively). 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. . This dataset contains all the data available for this study on 2019-04-03.

  Dataset EGAD00001004893

• Enhancing OSCC Prediction: The Prognostic Power of WPOI and Tumor Budding, and the Limited Impact of Molecular Resection Margins

  This dataset contains sequences with results of mutations observed in patients with oral squamous cell carcinoma. Mutations were detected by NGS in tumor tissue, tumor margins, and peripheral blood as a healthy control. Study was using a panel of 88 cancer-related genes, which were selected based on a literature search.

  Study EGAS50000000074

• Variant analysis on FFPE specimen from NSCLC patients (FoundationOne CDx)

  This study assessed the presence of somatic variants via the FoundationOne CDx panel of commonly mutated cancer genes and measure tumor mutational burden using next-generation sequencing panels. It was performed on genomic DNA from FFPE tissue of tumor resections. Mutations were used to draw OncoPrints and to assess TMB in relation with response metrics.

  Study EGAS50000001139

• Non-small cell lung cancer targeted sequencing

  Targeted sequencing of non-small cell lung cancer samples. BAM files of paired end reads aligned to hg19 using BWA MEM v0.7.1573. This targeted panel covers 370 genes of clinical relevance in non-small cell lung cancer.

  Dataset EGAD00001007918

• Transcriptomic intra-tumor heterogeneity of colorectal cancer varies depending on tumor location within the colorectum

  Background; Intra-tumor heterogeneity (ITH) of colorectal cancer (CRC) complicates molecular tumor classification, such as transcriptional subtyping. Differences in cellular states, biopsy cell composition, and tumor microenvironment may all lead to ITH. Here we analyze ITH at the transcriptomic and proteomic levels to ascertain whether subtype discordance between multiregional biopsies reflects relevant biological ITH or lack of classifier robustness. Further, we study the impact of tumor location on ITH.MethodsMultiregional biopsies from stage II and III CRC tumors were analyzed by RNA sequencing (41 biopsies, 14 tumors) and multiplex immune protein analysis (89 biopsies, 29 tumors). CRC subtyping were performed using consensus molecular subtypes (CMS), CRC intrinsic subtypes (CRIS), and TUMOR types. ITH-scores and network maps were defined to determine the origin of heterogeneity. A validation cohort was used with one biopsy per tumor (162 tumors).ResultsOverall, inter-tumor transcriptional variation exceeded ITH, and subtyping calls were frequently concordant between multiregional biopsies. Still, some tumors had high ITH and were classified discordantly. Proximal tumors showed ITH related to differences in the microenvironment, while ITH within distal tumors were cancer-cell related. This subtype discordancy reflected actual molecular ITH within the tumors. The relevance of the subtypes was reflected at protein level where several inflammation markers were significantly increased in immune related transcriptional subtypes, which was verified in an independent cohort (Wilcoxon rank sum test; p<0.05).ConclusionOur transcriptomic and proteomic analyses show that the tumor location along the colorectum influence the ITH of CRC, which again influence the concordance of subtyping.

  Study EGAS00001004668

• Bulk RNA-seq of monocytes and in vitro cultured monocyte-derived macrophages of ANCA-associated vasculitis patients with active and stable disease and healthy controls

  To study monocyte and macrophage activation in ANCA-associtated vasculitis (AAV), we performed bulk RNA sequencing of bead-selected monocytes and in vitro cultured monocyte-derived macrophages from AAV patients and healthy controls. Overview patients included for sequencing monocytes: - AAV active disease, n=4, MPO-AAV=4 - AAV remission, n=10, PR3-AAV=5, MPO-AAV=5 - Healthy controls, n=6 Overview patients included for sequencing monocyte-derived macrophages: - AAV active, n=1, PR3-AAV=1 - AAV remission, n=3, PR3-AAV=3 - Healthy controls, n=3

  Dataset EGAD50000000450

• Transcriptomics for IMMU-SCCHN1 cohort

  The goal of IMMUcan is to understand how the immune system interacts with tumors and how therapeutic interventions influence this interaction. This cohort includes patients with confirmed locally recurrent and/or metastatic squamous cell carcinoma of the head and neck (SCCHN) who receive first-line treatment with immune checkpoint inhibitors (ICI) or ICI combined with chemotherapy. This dataset contains transcriptomics data processed with the STAR pipeline. Two sequencing kits were employed: Roche KAPA for high-quality RNA samples and Takara SMART-Seq Stranded for samples with limited RNA quantities.

  Dataset EGAD50000002206

• Multi-region RNA-Seq data of 10 neuroblastoma cases

  To investigate intratumour heterogeneity and to better understand tumour evolution in neuroblastoma, we have performed a multi-region RNA sequencing on a total of 51 spatially separated tumor samples from 9 primary neuroblastomas (2 low-risk, 1 intermediate-risk and 6 high-risk) and 1 relapsed neuroblastoma. We also assessed the impact of chemotherapy on the clonal expansion by sequencing tumour regions from one medium risk and one high-risk tumour for which we had matched samples obtained at diagnosis and after chemotherapy.

  Dataset EGAD00001008133

• T2D-GENES Project 2: San Antonio Mexican American Family Studies

  The Type 2 Diabetes (T2D) Genetic Exploration by Next-generation sequencing in Ethnic Samples (T2D-GENES) Consortium is a collaborative international effort to identify genes influencing susceptibility to T2D in multiple ethnic groups using next generation sequencing. T2D-GENES Project 2 is a complex pedigree-based study designed to identify low frequency or rare variants influencing susceptibility to T2D, using whole genome sequence (WGS) information from 1,043 individuals in 20 Mexican American T2D-enriched pedigrees from San Antonio, Texas. The major objectives of this study are to identify low frequency or rare variants in and around known common variant signals for T2D, as well as to find novel low frequency or rare variants influencing susceptibility to T2D. The sampled individuals are obtained from two studies: the San Antonio Family Heart Study (SAFHS) and the San Antonio Family Diabetes/Gallbladder Study (SAFDGS), collectively referred to as the San Antonio Mexican American Family Studies (SAMAFS). The strategy is to sequence approximately 600 individuals at an average of 50x coverage across the entire genome, then impute genome wide genotypes for about 440 additional family members. The 600 sequenced individuals are specifically chosen for their value in imputing sequence information into other family members. By studying large pedigrees, we expect to find multiple individuals carrying each genetic variant, even if this variant is very rare in the population at large. Thus, a pedigree-based approach provides an excellent opportunity for identifying rare novel variants influencing risk of T2D and quantitative variation in T2D-related phenotypes. The whole genome sequencing has been done commercially by Complete Genomics, Inc. (CGI). The final data set includes whole genome sequence data for 607 individuals. After quality control, 585 sequenced individuals provide data for family based imputation, using Merlin linkage analysis software, into approximately 440 additional family members for whom chip based genotypes are available to indicate which parental haplotype is transmitted. Extensive phenotype data is provided for 1048 individuals. These include 5 sequenced individuals who do not belong to any of the 20 large pedigrees. Phenotype information was collected between 1991 and 2011 in the two contributing longitudinal studies. SAFHS participants may have information from up to 5 visits, and SAFDGS participants may have up to 4 visits. The clinical variables reported are coordinated with T2D-GENES Project 1 (multi-ethnic exome sequencing) and include T2D status and age at diagnosis, glycemic traits (fasting and 2 hour glucose and insulin), blood pressure, blood lipids (total cholesterol, HDL cholesterol, calculated LDL cholesterol and triglycerides), clinical chemistry (cystatin c, glutamic acid decarboxylase antibody titer (GadAb), creatinine, adiponectin and leptin). Glycated hemoglobin (HbA1c) was not measured for these individuals and insulin C-peptide is not included in this data set. Additional phenotype data include the medication status at each visit, classified in four categories as any current use of diabetes, hypertension or lipid-lowering medications, and, for females, current use of female hormones. Anthropometric measurements include age, sex, height, weight, hip circumference, waist circumference and derived ratios. Each phenotype variable has an initial summary column containing the most recent non-missing measurement for each individual, followed by the five potential time points for each individual, the number of non-missing measurements, and the age and year for the most recent non-missing measurement. For historical reasons, the order in which variables are presented on the dbGaP web site differs from their order in the data download file. When reading the comment fields for each variable, please note that commas are omitted to support data exchange in .csv format.

  Study phs000462

• Genomic Sequencing of Cervical Cancers

  Cervical cancer is responsible for 10-15% of cancer related deaths in women worldwide. The etiological role of infection with high-risk human papilloma viruses (HPV) in carcinomas of the cervix is well established. In general, the development of cervical carcinomas follows a progression from persistent HPV infection through precancerous lesions to invasive cancer. Previous studies have implicated somatic mutations in PIK3CA, PTEN, TP53, STK11 and KRAS as well as chromosome-arm level copy number alterations in the pathogenesis of cervical carcinomas. Here, we report whole exome sequencing analysis of 118 cervical carcinoma-normal paired samples from patients in Norway and Mexico, as well as transcriptome sequencing of 80 cases and whole genome sequencing of 13 tumor-normal pairs. Novel somatic mutations include recurrent E322K substitutions in the MAPK1 gene encoding the ERK2 kinase and inactivating mutations in the HLA-B gene. In addition, recurrent somatic mutations in FBXW7, EP300, and NFE2L2 are novel in the context of primary cervical carcinomas. Analysis of HPV integration sites revealed recurrent integration into the RAD51B locus as well as co-occurrence of HPV genome integration and copy number gains within several genomic loci. These findings shed new light on the pathogenesis of cervical carcinomas and suggest potential novel therapeutic targets.

  Study phs000600

• mRNA-seq data from ALL patients with NUP214::ABL1 disease

  Dataset contains mRNA-sequencing data (fastq files) from 2 patients with NUP214::ABL1 disease (one T-ALL and one B-ALL patient). Patient samples (peripheral blood or bone marrow) were taken at diagnosis (B-ALL) or relapse (T-ALL). mRNA was extracted from lymphoblasts and underwent paired-end sequencing (75bp) using the Illumina NextSeq platform. Transcriptomic data was used for identification of gene fusions, SNVs and InDels. mRNA-seq data for an additional B-ALL patient with NUP214::ABL1 disease utilised in this study has already been published (EGAS00001006460).

  Dataset EGAD50000001395

• Pseudogene RNAseq

  RNA sequencing to validate findings of somatic pseudogenes acquired during cancer development

  Dataset EGAD00001000732

• Inter and intra - tumor heterogeneity in Colorectal Cancer

  The dataset consists of two main sample groups. 1) The inter-tumour sample group contains a total of 97 samples from 27 patients. Each patient has a single normal and primary sample as well as one or more metastases. All samples were sequenced using IonTorrent PGM and a custom colorectal cancer (CRC) panel. 2) The intra-tumour sample group contains a total of 68 samples from a single tumour as well as a normal tissue sample. All 68 samples were sequenced using IonTorrent PGM and a custom CRC panel. Shallow whole genome sequencing was additionally applied to 10 of the samples using Illumina HiSeq 4000.

  Dataset EGAD00001003131