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

## TL;DR

scDrugAtlas is a database of single-cell drug responses that helps study tumor heterogeneity and drug resistance in cancer.

## Contribution

The novelty is the compilation of over 100 single-cell drug response datasets into a unified database with confidence levels for responses.

## Key findings

- scDrugAtlas includes data from 1023 samples across 77 drugs and 31 cancer types.
- Each drug response is assigned a confidence level based on tissue source and drug exposure factors.
- The database aims to support precision medicine and computational drug resistance research.

## Abstract

Tumour heterogeneity often leads to substantial differences in responses to same drug treatment. The presence of pre-existing or acquired drug-resistant cell subpopulations within a tumour survive and proliferate, ultimately resulting in tumour relapse and metastasis. The drug resistance is the leading cause of failure in clinical tumour therapy. Therefore, accurate identification of drug-resistant tumour 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 tumour 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 1023 samples, across 77 unique drugs and 31 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 tumour cells and underlying molecular mechanism.

Database URL: http://drug.hliulab.tech/scDrugAtlas/.