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Autophagy and Tumor Database: ATdb, a novel database connecting autophagy and tumor

Kelie Chen1, Dexin Yang1, Fan Zhao1

  • 1Department of Toxicology of School of Public Health, and Department of Gynecologic Oncology of Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China.

Database : the Journal of Biological Databases and Curation
|July 19, 2020
PubMed

Insights

Autophagy, a cellular process, plays a dual role in cancer, acting as both an anti-cancer and pro-tumor mechanism. The Autophagy and Tumor Database (ATdb) provides a comprehensive resource for exploring these complex autophagy-tumor interactions.

Area of Science:

  • Cell Biology
  • Oncology
  • Bioinformatics

Background:

  • Autophagy is a fundamental cellular process implicated in various diseases, particularly cancer.
  • The role of autophagy in tumorigenesis, progression, and metastasis is complex, context-dependent, and often contradictory.
  • A comprehensive resource is needed to understand the intricate relationship between autophagy and cancer.

Purpose of the Study:

  • To develop a centralized database, ATdb, for compiling and analyzing published information on autophagy and tumor research.
  • To facilitate in-depth understanding of the complex correlations between autophagy and tumor development.
  • To provide tools for context-dependent prediction and analysis of autophagy gene regulators in specific tumor subtypes and populations.

Main Methods:

  • Development of the Autophagy and Tumor Database (ATdb) at http://www.bigzju.com/ATdb/#/
  • Compilation of data including 25 tumor types, 137 autophagy-related genes, population filters, hazard ratio plots, interacting microRNAs and long non-coding RNAs, post-translational modifications, DNA methylation records, animal models, and clinical trials.
  • Implementation of search, browse, download, and online analysis functionalities, including predictive modeling and tumor clustering.

Main Results:

  • ATdb integrates extensive data on autophagy and tumor, encompassing genetic, epigenetic, and clinical information.
  • The database contains 219 population filters, 2650 hazard ratio trend plots, 658 interacting microRNAs, and 266 interacting long non-coding RNAs.
  • ATdb supports advanced analyses such as predicting autophagy gene regulators and clustering tumors based on long non-coding RNA interactions.

Conclusions:

  • ATdb serves as a powerful, user-friendly online platform for the research community.
  • It enables exploration of the multifaceted roles of autophagy in cancer.
  • The database offers novel insights into tumor biology and potential therapeutic strategies by analyzing complex autophagy-tumor interactions.

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