scDrugAtlas: an integrative single-cell drug response database for dissecting tumor heterogeneity in therapeutic efficacy

Abstract

Tumor heterogeneity often leads to substantial differences in responses to same drug treatment. The presence of pre-existing or acquired drug-resistant cell sub-populations within a tumor survive and proliferate, ultimately resulting in tumor relapse and metastasis. The drug resistance is the leading cause of failure in clinical tumor therapy. Therefore, accurate identification of drug-resistant tumor cell subpopulations could greatly facilitate the precision medicine and novel drug development. However, the scarcity of single-cell drug response data significantly hinders the exploration of tumor cell resistance mechanisms and the development of computational predictive methods. In this paper, we propose scDrugAtlas, a comprehensive database devoted to integrating the drug response data at single-cell level. We manually compiled more than 100 datasets containing single-cell drug responses from various public resources. The current version comprises large-scale single-cell transcriptional profiles and drug response labels from 1,023 samples (cell line, mouse, PDX models, patients and bacterium), across 78 unique drugs and 24 major cancer types. Particularly, we assigned a confidence level to each response label based on the tissue source (primary or relapse/metastasis), drug exposure time and drug-induced cell phenotype. We believe scDrugAtlas could greatly facilitate the Bioinformatics community for developing computational models and biologists for identifying drug-resistant tumor cells and underlying molecular mechanism. The scDrugAtlas database is available at: http://drug.hliulab.tech/scDrugAtlas/.