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MADET:一个手动策展的微生物组对癌症治疗疗效和毒性影响的知识库。

MADET: a Manually Curated Knowledge Base for Microbiomic Effects on Efficacy and Toxicity of Anticancer Treatments.

机构信息

Center for Infection and Immunity Studies, School of Medicine, Shenzhen Campus of Sun Yat-Sen University, Shenzhen, Guangdong, China.

Independent Researcher, Beijing, China.

出版信息

Microbiol Spectr. 2022 Dec 21;10(6):e0211622. doi: 10.1128/spectrum.02116-22. Epub 2022 Oct 18.

Abstract

A plethora of studies have reported the associations between microbiota and multiple diseases, leading to the development of at least four databases to demonstrate microbiota-disease associations, i.e., gutMDisorder, mBodyMap, Gmrepo, and Amadis. Moreover, gut microbiota mediates drug efficacy and toxicity, whereas a comprehensive database to elucidate the microbiota-drug associations is lacking. Here, we report an open-access knowledge base, MADET (Microbiomics of Anticancer Drug Efficacy and Toxicity), which harbors 483 manually annotated microbiota-drug associations from 26 studies. MADET provides user-friendly functions allowing users to freely browse, search, and download data conveniently from the database. Users can customize their search filters in MADET using different types of keywords, including bacterial name (e.g., Akkermansia muciniphila), anticancer treatment (e.g., anti-PD-1 therapy), and cancer type (e.g., lung cancer) with different types of experimental evidence of microbiota-drug association and causation. We have also enabled user submission to further enrich the data documented in MADET. The MADET database is freely available at https://www.madet.info. We anticipate that MADET will serve as a useful resource for a better understanding of microbiota-drug associations and facilitate the future development of novel biomarkers and live biotherapeutic products for anticancer therapies. Human microbiota plays an important role in mediating drug efficacy and toxicity in anticancer treatment. In this work, we developed a comprehensive online database, which documents over 480 microbiota-drug associations manually curated from 26 research articles. Users can conveniently browse, search, and download the data from the database. Search filters can be customized using different types of keywords, including bacterial name (e.g., Akkermansia muciniphila), anticancer treatment (e.g., anti-PD-1 therapy), and cancer type (e.g., lung cancer), with different types of experimental evidence of microbiota-drug association. We anticipate that this database will serve as a convenient platform for facilitating research on microbiota-drug associations, including the development of novel biomarkers for predicting drug outcomes as well as novel live biotherapeutic products for improving the outcomes of anticancer drugs.

摘要

大量研究报告了微生物组与多种疾病之间的关联,这促使至少开发了四个数据库来展示微生物组-疾病关联,即 gutMDisorder、mBodyMap、Gmrepo 和 Amadis。此外,肠道微生物组介导药物疗效和毒性,而缺乏全面的数据库来阐明微生物组-药物关联。在这里,我们报告了一个开放获取的知识库,MADET(抗癌药物疗效和毒性的微生物组学),其中包含 26 项研究中手动注释的 483 种微生物组-药物关联。MADET 提供了用户友好的功能,允许用户方便地从数据库中自由浏览、搜索和下载数据。用户可以使用不同类型的关键字(例如,阿克曼氏菌属 muciniphila)、抗癌治疗(例如,抗 PD-1 治疗)和癌症类型(例如,肺癌),以及不同类型的微生物组-药物关联和因果关系的实验证据,在 MADET 中自定义搜索过滤器。我们还启用了用户提交功能,以进一步丰富 MADET 中记录的数据。MADET 数据库可在 https://www.madet.info 上免费获取。我们预计 MADET 将成为更好地理解微生物组-药物关联的有用资源,并为未来开发用于抗癌治疗的新型生物标志物和活体生物治疗产品提供便利。

人类微生物组在介导抗癌治疗中的药物疗效和毒性方面发挥着重要作用。在这项工作中,我们开发了一个全面的在线数据库,其中记录了超过 480 种从 26 篇研究文章中手动整理的微生物组-药物关联。用户可以方便地从数据库中浏览、搜索和下载数据。搜索过滤器可以使用不同类型的关键字(例如,阿克曼氏菌属 muciniphila)、抗癌治疗(例如,抗 PD-1 治疗)和癌症类型(例如,肺癌),以及不同类型的微生物组-药物关联的实验证据进行自定义。我们预计该数据库将成为促进微生物组-药物关联研究的便捷平台,包括开发用于预测药物结果的新型生物标志物以及用于改善抗癌药物效果的新型活体生物治疗产品。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/484e/9769678/e6bc4c7e5fb1/spectrum.02116-22-f001.jpg

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