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A comparative study of curated contents by knowledge-based curation system in cancer clinical sequencing.

ABSTRACT: Medical oncologists are challenged to personalize medicine with scientific evidence, drug approvals, and treatment guidelines based on sequencing of clinical samples using next generation sequencer (NGS). Knowledge-based curation systems have the potential to help address this challenge. We report here the results of examining the level of evidence regarding treatment approval and clinical trials between recommendations made by Watson for Genomics (WfG), QIAGEN Clinical Insight Interpret (QCII), and Oncomine knowledge-based reporter (OKR). The tumor samples obtained from the solid cancer patients between May to June 2018 at Kindai University Hospital. The formalin-fixed paraffin-embedded tumor samples (n?=?31) were sequenced using Oncomine Comprehensive Assay v3. Variants including copy number alteration and gene fusions identified by the Ion reporter software were used commonly on three curation systems. Curation process of data were provided for 25 solid cancers using three curation systems independently. Concordance and distribution of curated evidence levels of variants were analyzed. As a result of sequencing analysis, nonsynonymous mutation (n?=?58), gene fusion (n?=?2) or copy number variants (n?=?12) were detected in 25 cases, and subsequently subjected to knowledge-based curation systems (WfG, OKR, and QCII). The number of curated information in any systems was 51/72 variants. Concordance of evidence levels was 65.3% between WfG and OKR, 56.9% between WfG and QCII, and 66.7% between OKR and QCII. WfG provided great number of clinical trials for the variants. The annotation of resistance information was also observed. Larger differences were observed in clinical trial matching which could be due to differences in the filtering process among three curation systems. This study demonstrates knowledge-based curation systems (WfG, OKR, and QCII) could be helpful tool for solid cancer treatment decision making. Difference in non-concordant evidence levels was observed between three curation systems, especially in the information of clinical trials. This point will be improved by standardized filtering procedure and enriched database of clinical trials in Japan.

SUBMITTER: Sakai K

PROVIDER: S-EPMC6683116 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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A comparative study of curated contents by knowledge-based curation system in cancer clinical sequencing.

Sakai Kazuko K Takeda Masayuki M Shimizu Shigeki S Takahama Takayuki T Yoshida Takeshi T Watanabe Satomi S Iwasa Tsutomu T Yonesaka Kimio K Suzuki Shinichiro S Hayashi Hidetoshi H Kawakami Hisato H Nonagase Yoshikane Y Tanaka Kaoru K Tsurutani Junji J Saigoh Kazumasa K Ito Akihiko A Mitsudomi Tetsuya T Nakagawa Kazuhiko K Nishio Kazuto K

Scientific reports 20190805 1

Medical oncologists are challenged to personalize medicine with scientific evidence, drug approvals, and treatment guidelines based on sequencing of clinical samples using next generation sequencer (NGS). Knowledge-based curation systems have the potential to help address this challenge. We report here the results of examining the level of evidence regarding treatment approval and clinical trials between recommendations made by Watson for Genomics (WfG), QIAGEN Clinical Insight Interpret (QCII), ...[more]

PMID: 31383922

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Project description:BackgroundMicrobes have been used as cell factories to synthesize various chemical compounds. Recent advances in synthetic biological technologies have accelerated the increase in the number and capacity of microbial cell factories; the variety and number of synthetic compounds produced via these cell factories have also grown substantially. However, no database is available that provides detailed information on the microbial cell factories and the synthesized compounds.ResultsIn this study, we established MCF2Chem, a manually curated knowledge base on the production of biosynthetic compounds using microbial cell factories. It contains 8888 items of production records related to 1231 compounds that were synthesizable by 590 microbial cell factories, including the production data of compounds (titer, yield, productivity, and content), strain culture information (culture medium, carbon source/precursor/substrate), fermentation information (mode, vessel, scale, and condition), and other information (e.g., strain modification method). The database contains statistical analyses data of compounds and microbial species. The data statistics of MCF2Chem showed that bacteria accounted for 60% of the species and that "fatty acids", "terpenoids", and "shikimates and phenylpropanoids" accounted for the top three chemical products. Escherichia coli, Saccharomyces cerevisiae, Yarrowia lipolytica, and Corynebacterium glutamicum synthesized 78% of these chemical compounds. Furthermore, we constructed a system to recommend microbial cell factories suitable for synthesizing target compounds and vice versa by combining MCF2Chem data, additional strain- and compound-related data, the phylogenetic relationships between strains, and compound similarities.ConclusionsMCF2Chem provides a user-friendly interface for querying, browsing, and visualizing detailed statistical information on microbial cell factories and their synthesizable compounds. It is publicly available at https://mcf.lifesynther.com . This database may serve as a useful resource for synthetic biologists.

Dataset Information

A comparative study of curated contents by knowledge-based curation system in cancer clinical sequencing.

Publications

A comparative study of curated contents by knowledge-based curation system in cancer clinical sequencing.

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