Neoplasms study on dbGaP (611 participants)

phs002431 — Childhood Cancer Data Initiative (CCDI): Enhancement of Data Sharing in    Pediatric, Adolescent and Young Adult Cancers

<p>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. </p><p></p><div> </div><div>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. </div><br><div>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. </div><br><div> </div><div> </div><p></p>