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

Yanfei Wu1, Wei Huang1, Xinda Ren1

  • 1College of Computer and Information Engineering, Nanjing Tech University, Nanjing 211816, Jiangsu, China.

Insights

scDrugAtlas is a new database integrating single-cell drug response data to combat tumor drug resistance. This resource aids researchers in developing predictive models and identifying resistant cancer cells.

Area of Science:

  • Bioinformatics
  • Cancer Research
  • Computational Biology

Background:

  • Tumor heterogeneity causes varied drug responses, with resistant cells leading to relapse and metastasis.
  • Drug resistance is a major obstacle in cancer therapy, hindering treatment efficacy.
  • Limited single-cell drug response data impedes understanding resistance mechanisms and developing predictive computational methods.

Purpose of the Study:

  • To introduce scDrugAtlas, a comprehensive database for single-cell level drug response data.
  • To provide a valuable resource for researchers studying tumor cell drug resistance.
  • To facilitate the development of computational models and identify drug-resistant cancer cells.

Main Methods:

  • Manually compiled over 100 datasets of single-cell drug responses from public resources.
  • Integrated large-scale single-cell transcriptional profiles and drug response labels.
  • Assigned confidence levels to response labels based on tissue source, drug exposure, and cell phenotype.

Main Results:

  • The database contains data from 1023 samples, 77 drugs, and 31 cancer types.
  • Includes single-cell transcriptional profiles and associated drug response labels.
  • Provides confidence scores for drug response labels to enhance data reliability.

Conclusions:

  • scDrugAtlas serves as a crucial resource for the bioinformatics and cancer research communities.
  • Enables the development of advanced computational models for predicting drug response.
  • Supports biologists in identifying drug-resistant tumor cells and their underlying molecular mechanisms.

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