10173 results for "cancer rna-seq"

in 29.54 milliseconds.

• Ovarian cancer sample size analysis

  The dataset contains exome sequencing fastq from 5 ovarian cancer patients, paired with tumor normal blood samples. Three tumor samples were sequenced from each patient: a biopsy sample ("-1" suffix in the file name), a local sample (multiple regions around the biopsy pooled together, with the "-2" suffix in the file name), and a global sample (multiple regions from the tumor pooled together, with a "-3" suffix in the file name).

  Dataset EGAD00001005947

• Whole Exome Sequencing of High grade T1 non-muscle invasive bladder cancer

  The dataset consists of a multisample VCF (version 4.1) and the corresponding annotated MAF file, containing the somatic point mutations found from exome sequencing across the high-grade T1 bladder cancer cohort (HGT1, n=61 samples). The VCF file is in accordance with the HTS format specifications (https://samtools.github.io/hts-specs/). The dataset comprises also a CSV file with clinical data.

  Dataset EGAD00001006346

• 47 urothelial cancer patients WES and 38 RNAseq

  We performed a global mutational landscape analysis using tumor samples from the 47 urothelial cancer patients included in MATCH-R or MOSCATO studies, with advanced metastatic disease and WES available (RNAseq is included for 38 patient samples).

  Dataset EGAD00001011063

• February 2021 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  February 2021 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001007919

• Comprehensive NGS Profiling to Enable Detection of ALK Gene Rearrangements and MET Amplifications in Non-Small Cell Lung Cancer

  We evaluate the analytical performance of the PGDx™ elio™ tissue complete assay, a 505 gene next-generation sequencing (NGS) tissue-based assay, that has now been FDA-cleared for use by physicians to help guide treatment decisions for cancer patients, using a NSCLC cohort of 38 patients.

  Dataset EGAD50000000016

• Genomic Profiling Reveals Heterogeneous Populations of Ductal Carcinoma In Situ

  Whole Exome Sequencing(WES) and copy number variation(CNV) analysis were performed using breast samples collected from non-invasive breast cancer patients in order to analysis of somatic mutations related to breast tumor phenotypes.

  Study JGAS000202

• Integrative Somatic and Germline Molecular Characterization of Genitourinary Cancers

  We have performed integrative bulk (whole exome sequencing of tumor and normal paired and whole transcriptome sequencing) and single cell analysis of primary and metastatic non-prostate genitourinary cancer specimens, such as renal and bladder tumors.

  Study phs002065

• Myelofibrosis Etiology and Transplant Outcomes

  The Myelofibrosis Etiology and Transplant Outcomes study is a collaboration between the National Cancer Institute and the Center for International Blood and Marrow Transplant Research (CIBMTR). The study aims to identify genomic factors affecting myelofibrosis pathogenesis and prognosis.

  Study phs002635

• WGS of single CTCs from 4 patients with metastatic cancer

  This dataset contains 352 paired fastq files sequenced by illumina Novoseq6000. Single-cell low-pass WGS analysis (illumina platform, PE150, 1-2x coverage) was performed on CTCs enriched using high-throughout microfluidic device from entire leukopak from patients with metastatic prostate cancer (GU-1 and GU-2) and metastatic hepatocellular carcinoma (HCC-1 and HCC-2). Patient matched white blood cells (WBC) served as internal controls.

  Dataset EGAD50000001006

• Germline and Somatic Genetic Landscape of Pediatric Rhabdomyosarcoma

  Dynamic approaches that integrate population-based research and molecular biology are needed to explain the mechanisms underlying pediatric rhabdomyosarcoma (RMS) and to determine novel prevention strategies. RMS, the most common soft-tissue sarcoma in children and adolescents, has one of the poorest 5-year survival rates among all pediatric cancers (less than 65%). One of the strongest risk factors for RMS is having a cancer predisposition syndrome. The syndromes that are most commonly seen among those with RMS are Li-Fraumeni, neurofibromatosis type 1, Costello, Noonan, and DICER1. Based on smaller clinic-based studies, only about 7% of RMS cases are thought to be associated with the genes responsible for these syndromes. However, there have been no population-based assessments to support this estimate. Even in the most recent large-scale evaluations of germline mutations in predisposition genes among children with cancer, very few RMS cases were included (43 cases). Furthermore, no distinctions were made between the major histologic subtypes of RMS: embryonal (eRMS) and alveolar (aRMS), which display differences in terms of age distribution, incidence, and cytogenetics. For instance, nearly 80% of alveolar cases are driven by a chromosomal translocation between either PAX3 or PAX7 and FOXO1, whereas these fusions are not seen in embryonal cases. In fact, RMS research is shifting from categorization based on histology to fusion status (eRMS is overwhelmingly fusion-negative). Another limitation in previous studies has been the inability to evaluate the frequency of de novo germline mutations (DNMs) in cancer predisposition genes due to the absence of any well-characterized cohorts of RMS case-parent trios. Therefore, a major gap in our understanding of the role of cancer predisposition in pediatric RMS that limit translational impact is there have been no population-based assessments to determine the true impact of these mutations on pediatric RMS, which limits clinical sequencing guidelines and surveillance protocols in these children.Overall Project Strategy: The objective of this project is to advance our understanding of the relationship between cancer predisposition genes and pediatric RMS. Our central hypotheses are: 1) mutations in cancer predisposition genes are more common than expected in children with RMS; and 2) children with fusion-negative tumors have a higher burden of germline mutations than those with fusion-positive tumors. The framework for this study relies on >600 well annotated samples collected from newly diagnosed RMS patients and stored in the Children’s Oncology Group (COG) Biopathology Center.

  Study phs002304

• DAC - The Netherlands Cancer Institute - Antoni van Leeuwenhoek

  Dac EGAC00001003316

• Enhanced detection of MRD with cfDNA Fragmentomics.

  Study EGAS00001007192

• Primary breast tumor heterogeneity through therapy

  Study EGAS00001003168

• THE NOWAC BLOOD-BREAST CANCER COMMITEE DATA ACCESS AGREEMENT

  Dac EGAC00001000743

• Genomic and transcriptome analysis for intrahepatic cholangiocarcinoma

  Study EGAS00001006007

• JAK and STAT alterations in CD30 positive LPD

  Study EGAS00001004181

• "Data Access Center Cancer Genomics Group"

  Dac EGAC00001000030

• Cancer Genome Database Data Access Committee (CGDB_DAC)

  Dac EGAC00001000033

• DAC for Single Cell Transcriptomics of Colorectal Cancer

  Dac EGAC00001000550

• Breast cancer multi-region sequencing from Sottoriva Lab

  Dac EGAC00001000890

• Harbin Medical University Cancer Hospital Data Access Commitee

  Dac EGAC00001000948

• DAC for study Non-coding RNAs in Breast Cancer

  Dac EGAC00001001090

• UT MD Anderson Cancer Center Genomic Medicine and Leukemia

  Dac EGAC00001001252

• ASAN Center for Cancer Genome Discovery Data Access Commitee

  Dac EGAC00001001285

• ASAN Center for Cancer Genome Discovery Data Access Commitee

  Dac EGAC00001001391