3291 results for "ovarian cancer"

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• Canadian prostate cancer samples (CPC-GENE) for PanProstate study

  CPC-GENE has sequenced the genomes of 350 intermediate risk prostate cancers to identify genetic signatures that differ in cancers that responded well to treatment compared with those that did not. CPC-GENE also has sequenced multiple regions of prostate cancer from the same gland to determine if and how the genetic make-up of prostate cancer varies within an individual man’s prostate

  Study EGAS00001003037

• B Cell Receptor Study From Metastatic Breast Cancer Tumour Samples

  B and T cells are key components of the adaptive immune system and play an important role in anti-cancer immunity. In this study, we performed an integrative analysis of the B cell and T cell repertoires across 27 metastatic breast tumours obtained from 8 donors with therapy-resistant lethal metastatic breast cancer at the time of a warm autopsy.

  Study EGAS00001006976

• Analysis of Loose Ends in Cancer Genome Structure

  Short-read sequencing (SRS) forms the basis of our understanding of cancer genome evolution, yet it is widely thought to be inadequate for detecting structural variants (SVs). To understand the nature of cancer SVs missed by SRS, we introduce the concept of "loose ends" - sites of missing rearrangements revealed by balancing copy number (CN) across the genomic intervals and adjacencies of a genome graph.

  Study EGAS00001007324

• Glioma_cell_lines_rearrangement_screen

  Genomic libraries (500 bps) will be generated from total genomic DNA derived from commomon epithelial cancer samples and subjected to total of eight lanes of 37 bp, paired end sequencing on the llumina GA. Paired reads will be mapped to build 37 of the human reference genome to facilitate the generation of genome wide copy number information, and the identification of novel rearranged cancer genes and gene fusions.

  Study EGAS00001000202

• Renal_Follow_Up_Series

  This study's purpose is to use data generated in Renal whole genome and exome Cancer sequencing to target specific areas in multiple other Renal Cancer samples. These areas will then be subjected to bespoke pull downs, tagged and then pool the resultant amplicons. These amplicons will then be sequenced. This is hoped to show the prevalence of previous findings in multiple individuals in a high throughput method.

  Study EGAS00001000095

• Non_Tumour_Renal_Cell_Line_Sequencing

  Genomic libraries (500 bps) will be generated from total genomic DNA derived from commomon epithelial cancer samples and subjected to total of eight lanes of 37 bp, paired end sequencing on the llumina GA. Paired reads will be mapped to build 37 of the human reference genome to facilitate the generation of genome wide copy number information, and the identification of novel rearranged cancer genes and gene fusions.

  Study EGAS00001000205

• ANGIOPREDICT - an FP7-funded project enabling personalised medicine for patients with metastatic colorectal cancer.

  In ANGIOPREDICT, academic cancer biologists and industry-based biotechnology researchers will work together with clinicians to identify biomarkers to predict whether individual metastatic colorectal cancer patients will respond positively to Avastin® combination therapy. Diagnostic tests using these biomarkers will also be developed to provide clinicians with the means to predict patient treatment responses in the future.

  Study EGAS00001005423

• Exome sequencing of paired primary tumor and metastatic breast cancer

  Prognosis evaluation of advanced breast cancer and therapeutic strategy are mostly based on clinical features of advanced disease and molecular profiling of the primary tumor. Very few studies have evaluated the impact of a prospective documentation of metastatic subtyping. The genomic landscape of metastatic breast cancer has mostly been described in very advanced, pretreated disease, limiting its transferability to clinical use.

  Study EGAS00001004578

• Foundation Medicine Adult Cancer Clinical Dataset (FM-AD)

  The Foundation Medicine adult cancer clinical dataset consists of 18,004 unique solid tumor samples that underwent genomic profiling on a single uniform platform as part of standard clinical care. The dataset is derived from the FoundationOne® genomic profiling assay version 2 that interrogates exonic regions of 287 cancer-related genes and selected introns from 19 genes known to undergo rearrangements in human cancer. Genomic DNA samples were sequenced to over 500x median coverage, and custom computational analyses identified all classes of genomic alterations (base substitutions, insertions and deletions, copy number alterations, and rearrangements). Since matched normal tissue was unavailable for analysis, these data underwent additional filtering to enrich for cancer-related events. The reported data includes genomic alterations that are known and suspected tumor drivers, as well as variants of unknown significance. To preserve patient anonymity, all known or suspected germline variants were removed from the data unless known to be associated with cancer development. The dataset contains genomic alteration profiles generated by FoundationOne version 2 testing for adult cancer patients (over 18 y.o.), and represents a vast diversity of tumor subtypes, including many rare diseases not profiled as part of large-scale profiling efforts. Cases are grouped into 16 broad disease categories containing tumors from 162 unique disease subtypes. Since specimens were profiled as part of clinical care, limited clinical parameters were available, including age, gender, tissue of origin, % of tumor nuclei, and diagnosis. Publication of this dataset is intended to allow the broad scientific community access to this unique cohort for use in scientific research projects of common and rare types of cancer, both for generating leads regarding causal mechanisms as well as cross-testing and confirming existing hypotheses. A pediatric cancer clinical dataset consisting of data from 1,215 patients under 18 y.o. is available separately at: FOUNDATION MEDICINE

  Study phs001179

• Childhood Cancer Data Initiative (CCDI): Enhancement of Data Sharing in Pediatric, Adolescent and Young Adult Cancers

  NCI's Childhood Cancer Data Initiative (CCDI) is building a community centered around childhood cancer care and research data. Through enhanced data sharing, we can improve our understanding of cancer biology to improve preventive measures, treatment, quality of life, and survivorship, as well as ensure that researchers learn from every child with cancer. While childhood cancers represent the leading cause of death in children over the age of 1, they are collectively rare, comprising approximately 1%‒3% of cancers diagnosed annually in the United States. Information on diagnosis, treatment, and outcomes is often stored at the hospital or institution where a child is treated, making it difficult to answer scientific questions about childhood cancer. Sharing clinical care and research data generated by children's hospitals, clinics, or networks broadly with the community can help us learn faster and, on a scale much larger than any single institution caring for children can learn on its own. To exploit the rapid advances in high-throughput DNA sequencing technologies and realize the goals of precision cancer medicine, the UMICH Cancer Center established the Michigan Oncology Sequencing Center (MI-ONCOSEQ). This UMICH Cancer Center provisions genomic data derived from the Michigan Oncology Sequencing Center (MI-ONCOSEQ) clinical sequencing assay for patients that fall within the inclusion criteria of the CCDI data sharing initiative. An "integrative sequencing approach" carried out in a CLIA-certified laboratory is utilized to provide a comprehensive landscape of the genetic alterations in individual tumor specimens for the purpose of identifying informative and/or actionable mutations. Using a number of computational pipelines that we have developed in-house or have adapted from the public domain, candidate molecular aberrations are nominated and then analyzed by scientists for clinical significance and/or relevance. This approach enables the detection of point mutations, insertions/deletions, gene fusions and rearrangements, amplifications/deletions, and outlier expressed genes. Furthermore, we can identify certain germline alterations that may also be relevant.

  Study phs002431