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An integrated clinical and genomic information system for cancer precision medicine

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 interpret...

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Autores principales: Jang, Yeongjun, Choi, Taekjin, Kim, Jongho, Park, Jisub, Seo, Jihae, Kim, Sangok, Kwon, Yeajee, Lee, Seungjae, Lee, Sanghyuk
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5918454/
https://www.ncbi.nlm.nih.gov/pubmed/29697362
http://dx.doi.org/10.1186/s12920-018-0347-9
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author Jang, Yeongjun
Choi, Taekjin
Kim, Jongho
Park, Jisub
Seo, Jihae
Kim, Sangok
Kwon, Yeajee
Lee, Seungjae
Lee, Sanghyuk
author_facet Jang, Yeongjun
Choi, Taekjin
Kim, Jongho
Park, Jisub
Seo, Jihae
Kim, Sangok
Kwon, Yeajee
Lee, Seungjae
Lee, Sanghyuk
author_sort Jang, Yeongjun
collection PubMed
description 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12920-018-0347-9) contains supplementary material, which is available to authorized users.
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spelling pubmed-59184542018-04-30 An integrated clinical and genomic information system for cancer precision medicine Jang, Yeongjun Choi, Taekjin Kim, Jongho Park, Jisub Seo, Jihae Kim, Sangok Kwon, Yeajee Lee, Seungjae Lee, Sanghyuk BMC Med Genomics Software 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12920-018-0347-9) contains supplementary material, which is available to authorized users. BioMed Central 2018-04-20 /pmc/articles/PMC5918454/ /pubmed/29697362 http://dx.doi.org/10.1186/s12920-018-0347-9 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Software
Jang, Yeongjun
Choi, Taekjin
Kim, Jongho
Park, Jisub
Seo, Jihae
Kim, Sangok
Kwon, Yeajee
Lee, Seungjae
Lee, Sanghyuk
An integrated clinical and genomic information system for cancer precision medicine
title An integrated clinical and genomic information system for cancer precision medicine
title_full An integrated clinical and genomic information system for cancer precision medicine
title_fullStr An integrated clinical and genomic information system for cancer precision medicine
title_full_unstemmed An integrated clinical and genomic information system for cancer precision medicine
title_short An integrated clinical and genomic information system for cancer precision medicine
title_sort integrated clinical and genomic information system for cancer precision medicine
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5918454/
https://www.ncbi.nlm.nih.gov/pubmed/29697362
http://dx.doi.org/10.1186/s12920-018-0347-9
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