DRMref

DRMref characterizes drug resistance mechanisms at single-cell resolution across human cancers by integrating single-cell datasets to catalogue resistant cellular states, associated molecular features, and treatment contexts.

Key Features:

• Comprehensive Data Coverage: Includes 42 single-cell datasets from 30 studies comprising 382 samples across 13 major cancer types and 26 subtypes, covering 35 treatment regimens and 42 drugs.
• Cellular and Molecular Annotations: Provides annotations of cellular composition, intratumoral heterogeneity, epithelial–mesenchymal transition (EMT), cell–cell interactions, and differentially expressed genes in resistant cells.
• Mechanism Analysis: Catalogues drug resistance mechanisms including aberrations of therapeutic targets and drug inactivation via structural modification.
• Pathway Enrichment and Network Analyses: Performs enrichment analyses for hallmark pathways, KEGG pathways, and GO terms and conducts network analyses to characterize regulatory relationships.
• Regulatory Element Identification: Identifies microRNAs, sequence motifs, and transcription factors associated with resistant cell populations.

Scientific Applications:

• Study of drug resistance mechanisms: Enables investigation of cellular and molecular bases of resistance at single-cell resolution across diverse cancers and treatments.
• Evaluation of combination therapies: Supports analysis of treatment contexts and molecular interactions relevant to assessing drug combination strategies.
• Discovery of therapeutic targets: Facilitates identification of candidate targets and regulatory elements within resistant cell populations for potential intervention.
• Personalized oncology research: Provides single-cell–level evidence to inform hypotheses about tailored treatment strategies and vulnerabilities in resistant cells.

Methodology:

Computational methods explicitly include differential expression analysis, pathway enrichment of hallmark/KEGG/GO terms, network analyses, identification of microRNAs, motifs, and transcription factors, and annotation of cellular composition, intratumoral heterogeneity, EMT, and cell–cell interactions.