Deciphering cancer therapy resistance via patient-level single-cell transcriptomics with CellResDB

Abstract

Cancer therapy resistance remains a major challenge, with limited resources available for systematically studying its underlying mechanisms at the patient level. The existing databases are either restricted to bulk RNA-seq data, lack single-cell resolution, or provide limited clinical annotations, making them insufficient for in-depth exploration of the tumor microenvironment (TME) dynamics in therapy resistance. To bridge this gap, we present CellResDB, a patient-derived platform comprising nearly 4.7 million cells from 1391 patient samples across 24 cancer types. CellResDB provides comprehensive annotations of TME features linked to therapy resistance. To enhance accessibility, we include an intelligent robot, CellResDB-Robot, which facilitates intuitive data retrieval and analysis. In summary, CellResDB represents a valuable resource for cancer therapy and provides an experimental protocol for applying large language models (LLMs) within the biomedical database. CellResDB is freely available at https://cellknowledge.com.cn/cellresponse. (Figure presented.)