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Resources for Interpreting Variants in Precision Genomic Oncology Applications.
Tsang, Hsinyi; Addepalli, KanakaDurga; Davis, Sean R.
Afiliação
  • Tsang H; Center for Biomedical Informatics and Information Technology, National Cancer Institute, National Institutes of Health, Gaithersburg, MD, United States.
  • Addepalli K; Attain, LLC, McLean, VA, United States.
  • Davis SR; Center for Biomedical Informatics and Information Technology, National Cancer Institute, National Institutes of Health, Gaithersburg, MD, United States.
Front Oncol ; 7: 214, 2017.
Article em En | MEDLINE | ID: mdl-28975082
Precision genomic oncology-applying high throughput sequencing (HTS) at the point-of-care to inform clinical decisions-is a developing precision medicine paradigm that is seeing increasing adoption. Simultaneously, new developments in targeted agents and immunotherapy, when informed by rich genomic characterization, offer potential benefit to a growing subset of patients. Multiple previous studies have commented on methods for identifying both germline and somatic variants. However, interpreting individual variants remains a significant challenge, relying in large part on the integration of observed variants with biological knowledge. A number of data and software resources have been developed to assist in interpreting observed variants, determining their potential clinical actionability, and augmenting them with ancillary information that can inform clinical decisions and even generate new hypotheses for exploration in the laboratory. Here, we review available variant catalogs, variant and functional annotation software and tools, and databases of clinically actionable variants that can be used in an ad hoc approach with research samples or incorporated into a data platform for interpreting and formally reporting clinical results.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Front Oncol Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Front Oncol Ano de publicação: 2017 Tipo de documento: Article