12130 results for "cancer rna-seq"

in 13.57 milliseconds.

• Gene expression profile of mesothelial cells from peritoneal adhesion biopsies

  RNA-sequencing analysis was carried out on mesothelial cells isolated from peritoneal adhesion biopsies and compared to control human peritoneal mesothelial cells to identify a mesothelial-to-mesenchymal transition (MMT)-related gene signature in patients.

  Dataset EGAD00001008324

• Skin Fibroblast Transcriptome of Type 2 Diabetic Patients

  Comparative analysis of transcriptomes of skin fibroblasts in 17 Type 2 Diabetic individuals by RNA sequencing.

  Dataset EGAD00001004980

• Sequencing data for oesophageal / related samples - Kazachenka et al (RNA)

  Data supporting: "The transcriptional landscape of endogenous retroelements delineates esophageal adenocarcinoma subtypes" RNAseq for 279 samples

  Dataset EGAD00001011076

• Integrative Analysis of Lung Adenocarcinoma in Never Smokers

  We performed whole genome sequencing of lung cancers from never smoker subjects from Institut universitaire de cardiologie et de pneumologie de Québec - Université Laval (IUCPQ-UL) (N=125), Université Côte d'Azur (Nice) (N=47), the Environment And Genetics in Lung cancer Etiology (EAGLE) study (N=27), Yale University (N=22), and Moffitt Cancer Cente (N=11).

  Study phs001697

• Phylogenetic analysis of combined lobular and ductal carcinoma of the breast

  Breast cancer manifests in diverse forms, with particular reference to various cell types harboring different mutations and gene expression profiles. To elucidate the clonal relationship between cancer cells in tumors composed of both ductal and lobular phenotypes, we analyzed two combined lobular and ductal carcinoma (CLDC) cases, including one mixed ductal-lobular carcinoma (MDL) lesion, by next generation sequencing.

  Study JGAS000300

• Somatic_mutation_in_skin_epidermis__SMS_

  We aim to assess the range and depth of mutations in genes linked with cancer in skin epidermis surrounding lesions which are undergoing surgical removal. Patient history will be collected to provide a detailed outline of tumour type (including histology), skin type, and sunlight exposure. We will perform ultra-deep targeted sequencing using genes implicated in cancer to try and understand the background of mutations surrounding these lesions

  Study EGAS00001002165

• Somatic_mutation_and_clonal_evolution_in_the_human_bladder_Novaseq

  In this study, we aim to characterise the landscape of mutation and clonal selection in the human bladder. The data in this study will be generated by whole-genome sequencing of laser-dissected microbiopsies from the bladder. The samples utilised in this study will include urothelium from transplant donors with no history of bladder cancer and cystectomy specimens from patients with bladder cancer.

  Study EGAS00001003433

• SDH_deficient_renal_tumours___WGS_

  Succinate dehydrogenase (SDH) deficient renal cancers are a rare and understudied subtype of renal cancer. As such they represent an unmet need in kidney cancer research. Here, we seek to describe the genomics and transcriptomics of SDH deficient renal cancers by sequencing five such tumours. We document their mutational burden, define driver mutations, demonstrate typical patterns of structural variants, and estimate the cell of origin and cellular composition.

  Study EGAS00001004102

• MutWP5: CRUK Mutographs of Cancer: Breast: Cancer Mastectomy (WG) (2020-01-29)

  Sequencing of LCM-derived microbiopsies from 40 women who underwent mastectomies due to breast cancer. LCM and sequencing will be conducted on both normal, unaffected breast, and, where possible, tumour tissue. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue, and compare findings between the normal and associated cancer tissues. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this portion of the study will be compared to women who had cosmetic breast reduction surgeries and those who are BRCA carriers. . This dataset contains all the data available for this study on 2020-01-29.

  Dataset EGAD00001005922

• Ghana Breast Health Study

  The Ghana Breast Health Study (GBHS) was a multi-disciplinary, population-based case-control study conducted in Accra and Kumasi, Ghana that was designed to investigate breast cancer etiology in the West Africa region. The study enrolled 1,126 invasive breast cancer cases and 2,106 frequency matched population-based controls using census-based sampling. GHBS participants were between the ages of 18 to 74 years of age. Breast cancer cases were recruited at the time they presented with lesions suspicious of breast cancer at three hospitals: Korle Bu Teaching Hospital (Accra), Komfo Anoyke Teaching Hospital (Kumasi) and Peace and Love Hospital (Kumasi). These hospitals are the primary providers of treatment for breast cancer in Ghana, allowing for cases in our study to represent most breast cancers diagnosed in these areas during the study period. The following publications describe the GBHS in detail: 1) Brinton LA et al. Design considerations for identifying breast cancer risk factors in a population-based study in Africa. Int J Cancer 2017;140:2667-2677 (PMID:28295287). 2) Nyante SJ et al. Recruiting population controls for case-control studies in sub-Saharan Africa: The Ghana Breast Health Study. PloS one 2019;14:e0215347 (PMID:30990841)Among subjects with an available source of germline DNA genotyping was performed using the Infinium Global Screening Array-24 per the manufacturer’s guidelines using the Infinium automated protocol. We excluded probable duplicates and close relatives, and samples with a call rate < 95% or samples with extreme heterozygosity. Female sex was verified by Identifiler using X chromosome heterozygosity and the X chromosome inbreeding coefficient F statistics. The GLU genetics’ ld.tagzilla module was used to confirm African ancestry. To resolve more detailed population substructure, principal components analysis was conducted among all unrelated subjects using the EIGENSOFT v7.2.1. Imputation was performed using the Michigan imputation server Minimac3 with 1K genomes phase3 as reference panel.

  Study phs002387