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. 2024 Dec 21:2024:baae124.
doi: 10.1093/database/baae124.

MiCK: a database of gut microbial genes linked with chemoresistance in cancer patients

Muhammad Shahzaib  1 , Muhammad Muaz  2 , Muhammad Hasnain Zubair  1 , Masood Ur Rehman Kayani  1
Affiliations

MiCK: a database of gut microbial genes linked with chemoresistance in cancer patients

Muhammad Shahzaib et al. Database (Oxford). .

Abstract

Cancer remains a global health challenge, with significant morbidity and mortality rates. In 2020, cancer caused nearly 10 million deaths, making it the second leading cause of death worldwide. The emergence of chemoresistance has become a major hurdle in successfully treating cancer patients. Recently, human gut microbes have been recognized for their role in modulating drug efficacy through their metabolites, ultimately leading to chemoresistance. The currently available databases are limited to knowledge regarding the interactions between gut microbiome and drugs. However, a database containing the human gut microbial gene sequences, and their effect on the efficacy of chemotherapy for cancer patients has not yet been developed. To address this challenge, we present the Microbial Chemoresistance Knowledgebase (MiCK), a comprehensive database that catalogs microbial gene sequences associated with chemoresistance. MiCK contains 1.6 million sequences of 29 gene types linked to chemoresistance and drug metabolism, curated manually from recent literature and sequence databases. The database can support downstream analysis as it provides a user-friendly web interface for sequence search and download functionalities. MiCK aims to facilitate the understanding and mitigation of chemoresistance in cancers by serving as a valuable resource for researchers. Database URL: https://microbialchemreskb.com/.

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Conflict of interest statement

None declared.

Figures

Figure 1.
Figure 1.
Framework of MiCK development, including (i) literature search for the identification of genes/enzymes linked to chemoresistance, (ii) retrieval of respective gene and enzyme sequences from NCBI Gene and UniProtKB databases, and (iii) sequence clustering for constructing MiCK using MySQL Workbench.
Figure 2.
Figure 2.
Statistics of distribution of chemoresistance genes (a) and their target drugs (b) included in MiCK.
Figure 3.
Figure 3.
Major components of the MiCK graphical user interface: (a) The Home page, (b) The Statistics page, (c) The Search page, and (d) The Downloads page.
See this image and copyright information in PMC

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