Scientific Data (Jul 2023)

A global database for modeling tumor-immune cell communication

  • Yunjin Xie,
  • Weiwei Zhou,
  • Jingyi Shi,
  • Mengjia Xu,
  • Zijing Lin,
  • Donghao Li,
  • Jianing Li,
  • Shujun Cheng,
  • Tingting Shao,
  • Juan Xu

DOI
https://doi.org/10.1038/s41597-023-02342-5
Journal volume & issue
Vol. 10, no. 1
pp. 1 – 9

Abstract

Read online

Abstract Communications between tumor cells and surrounding immune cells help shape the tumor immunity continuum. Recent breakthroughs in high-throughput technologies as well as computational algorithms had reported many important tumor-immune cell (TIC) communications, which were scattered in thousands of published studies and impeded systematical characterization of the TIC communications across cancer. Here, a comprehensive database, TICCom, was developed to model TIC communications, containing 739 experimentally-validated or manually-curated interactions collected from more than 3,000 literatures as well as 4,537,709 predicted interactions inferred via six computational algorithms by reanalyzing 32 scRNA-seq datasets and bulk RNA-seq data across 25 cancer types. The communications between tumor cells and 14 types of immune cells were characterized, and the involved ligand-receptor interactions were further integrated. 14190 human and 3650 mouse integrated ligand-receptor interactions with supplemented corresponding function information were also stored in the TICCom database. Our database would serve as a valuable resource for investigating TIC communications.