One of the most fundamental questions in biology is: which cells communicate with each other
during organismal growth, development, immune responses, and the pathogenesis of complex
diseases. There is an urgent need for an expert-curated reference database comprising
experimentally validated, gold-standard CCCs support the development of computational inference
tools.
Here, we present CCCdb (http://www.licpathway.net/cccdb/index.php), a comprehensive, manually
curated database of experimentally validated cell–cell communications for human and mouse. A
total of 8,353 entries were extracted from thousands of publications, each annotated with
standardized information on cell types, tissues, and phenotypes. These entries cover 98 tissues,
1,145 cell types, and 577 phenotypes, encompassing communication via direct contact, autocrine,
paracrine, and endocrine signaling. CCCdb compiles experiment-supported CCCs across cellular
subtypes, tissue interfaces, and physiological or pathological states. To enhance accessibility
and biological interpretability, CCCdb integrates a ReAct-based AI assistant that enables
intelligent natural-language queries and intuitive navigation through biological information.
Understanding how cells communicate to maintain tissue homeostasis and drive disease progression
is essential for decoding complex biological systems.
Mingcong Xu, Guorui Zhang, Xuan Wang, Yiqing Chen, Chenchen Feng, Jincheng Guo, Xuan Fan, Liyuan Liu, Yuezhu Wang, Ting Cui, Jiaqi Liu, Libo Luo, Qing Xun, Yiguang Fan, Xiaoyu Ma, Huifang Tang, Chunquan Li, Desi Shang, CCCdb: a comprehensive manually curated database for cell–cell communication in human and mouse, Nucleic Acids Research, 2025;, gkaf1105, https://doi.org/10.1093/nar/gkaf1105