National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China.
CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China.
Mol Cancer Res. 2023 Jul 5;21(7):691-697. doi: 10.1158/1541-7786.MCR-22-0909.
Cancer is one of the leading causes of human death. As metabolomics techniques become more and more widely used in cancer research, metabolites are increasingly recognized as crucial factors in both cancer diagnosis and treatment. In this study, we developed MACdb (https://ngdc.cncb.ac.cn/macdb), a curated knowledgebase to recruit the metabolic associations between metabolites and cancers. Unlike conventional data-driven resources, MACdb integrates cancer-metabolic knowledge from extensive publications, providing high quality metabolite associations and tools to support multiple research purposes. In the current implementation, MACdb has integrated 40,710 cancer-metabolite associations, covering 267 traits from 17 categories of cancers with high incidence or mortality, based entirely on manual curation from 1,127 studies reported in 462 publications (screened from 5,153 research papers). MACdb offers intuitive browsing functions to explore associations at multi-dimensions (metabolite, trait, study, and publication), and constructs knowledge graph to provide overall landscape among cancer, trait, and metabolite. Furthermore, NameToCid (map metabolite name to PubChem Cid) and Enrichment tools are developed to help users enrich the association of metabolites with various cancer types and traits.
MACdb paves an informative and practical way to evaluate cancer-metabolite associations and has a great potential to help researchers identify key predictive metabolic markers in cancers.
癌症是人类死亡的主要原因之一。随着代谢组学技术在癌症研究中的应用越来越广泛，代谢物被越来越多地认为是癌症诊断和治疗的关键因素。在这项研究中，我们开发了 MACdb（https://ngdc.cncb.ac.cn/macdb），这是一个经过精心整理的知识库，用于招募代谢物与癌症之间的代谢关联。与传统的数据驱动资源不同，MACdb 整合了来自广泛出版物的癌症代谢知识，提供高质量的代谢物关联和支持多种研究目的的工具。在当前的实现中，MACdb 已经整合了 40,710 个癌症-代谢物关联，涵盖了 17 种高发病率或高死亡率癌症类型的 267 种特征，这些关联完全是基于对 462 篇出版物中的 1127 项研究（从 5153 篇研究论文中筛选）中的手动整理。MACdb 提供直观的浏览功能，可在多维度（代谢物、特征、研究和出版物）上探索关联，并构建知识图谱，提供癌症、特征和代谢物之间的整体概况。此外，NameToCid（将代谢物名称映射到 PubChem Cid）和富集工具也得到了开发，以帮助用户丰富代谢物与各种癌症类型和特征的关联。
MACdb 为评估癌症-代谢物关联提供了一种信息丰富且实用的方法，并且有很大的潜力帮助研究人员识别癌症中的关键预测代谢标志物。
