An integrated clinical and genomic information system for cancer precision medicine
- 주제(키워드) Information system , Genomic medicine , Personalized medicine , Precision medicine , Targeted therapy , Oncology , Cancer
- 주제(기타) Genetics & Heredity
- 설명문(일반) [Jang, Yeongjun; Seo, Jihae; Kim, Sangok; Kwon, Yeajee; Lee, Sanghyuk] Ewha Womans Univ, ERCSB, Seoul, South Korea; [Jang, Yeongjun] Seoul Natl Univ, Coll Nat Sci, Interdisciplinary Program Bioinformat, Seoul, South Korea; [Choi, Taekjin; Kim, Jongho; Park, Jisub] Daumsoft Inc, Seoul, South Korea; [Lee, Seungjae] DNA Link Inc, Seoul, South Korea
- 등재 SCIE, SCOPUS
- 발행기관 BIOMED CENTRAL LTD
- 발행년도 2018
- 회의명 28th International Conference on Genome Informatics - Medical Genomics
- 개최지 Seoul, SOUTH KOREA
- 일자 OCT 31-NOV 03, 2017
- URI http://www.dcollection.net/handler/ewha/000000151396
- 본문언어 영어
- Published As http://dx.doi.org/10.1186/s12920-018-0347-9
초록/요약
Background: Increasing affordability of next-generation sequencing (NGS) has created an opportunity for realizing genomically-informed personalized cancer therapy as a path to precision oncology. However, the complex nature of genomic information presents a huge challenge for clinicians in interpreting the patient's genomic alterations and selecting the optimum approved or investigational therapy. An elaborate and practical information system is urgently needed to support clinical decision as well as to test clinical hypotheses quickly. Results: Here, we present an integrated clinical and genomic information system (CGIS) based on NGS data analyses. Major components include modules for handling clinical data, NGS data processing, variant annotation and prioritization, drug-target-pathway analysis, and population cohort explorer. We built a comprehensive knowledgebase of genes, variants, drugs by collecting annotated information from public and in-house resources. Structured reports for molecular pathology are generated using standardized terminology in order to help clinicians interpret genomic variants and utilize them for targeted cancer therapy. We also implemented many features useful for testing hypotheses to develop prognostic markers from mutation and gene expression data. Conclusions: Our CGIS software is an attempt to provide useful information for both clinicians and scientists who want to explore genomic information for precision oncology.
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