Abstract
Single-cell RNA sequencing has revolutionized the high-resolution characterization of cellular heterogeneity within the tumor microenvironment. It is now widely recognized that cell heterogeneity plays a major role in determining variations in key clinical phenotypes, including patient survival, tumor size, lymph node involvement, metastasis, and responses to anticancer therapies. However, a critical gap remains in the lack of comprehensive databases that systematically link single-cell data to these clinically relevant phenotypes. To address this, we developed CPRCSdb (http://www.yzbio.top/CPRCSdb/), a comprehensive database that integrates clinical phenotypes with single-cell transcriptomic heterogeneity. CPRCSdb includes over 4.05 million cells from 1053 manually curated single-cell samples and 101 integrated datasets, along with 11,032 bulk RNA-seq samples, covering 29 cancer types. Our database spans 5 disease phenotype categories and the therapy response phenotypes of 30 different drugs. We analyzed 6197 associations between bulk-level phenotypes and single-cell heterogeneity, identifying over 1.13 million clinically relevant cells. Rigorous quality control measures were applied to ensure data accuracy. For each association, CPRCSdb supports downstream analyses, including differential expression, functional enrichment, and cell-cell communication inference. We anticipate that CPRCSdb will serve as a valuable and integrative resource for investigating the mechanisms underlying tumorigenesis and cancer progression.