CPADS: a web tool for comprehensive pancancer analysis of drug sensitivity

Area of Science:

• Oncology
• Bioinformatics
• Computational Biology

Background:

• Drug therapy is crucial for cancer treatment, but personalized drug sensitivity analysis is limited.
• Existing tools lack comprehensive visualization and analysis of pancancer drug sensitivity.
• Accurate drug sensitivity data improves patient outcomes and quality of life.

Purpose of the Study:

• To develop a web-based tool for comprehensive pancancer drug sensitivity analysis and visualization.
• To integrate diverse datasets for a broad analysis of cancer drug response.
• To provide a platform for exploring drug resistance mechanisms at gene and pathway levels.

Main Methods:

• Collected pancancer drug sensitivity data from GEO, TCGA, and GDSC databases.
• Developed the Comprehensive Pancancer Analysis of Drug Sensitivity (CPADS) web tool using Shiny.
• Integrated transcriptomic data from over 29,000 samples, 44 cancer types, 288 drugs, and 9,000+ gene perturbations.

Main Results:

• CPADS enables various analyses including differential gene expression, gene correlation, pathway analysis, and gene perturbation analysis.
• The tool offers multiple visualization approaches for exploring drug sensitivity data.
• It facilitates the investigation of primary and secondary drug resistance at both gene and pathway levels.

Conclusions:

• CPADS provides a valuable resource for physicians and researchers studying cancer drug sensitivity.
• The tool aids in identifying pivotal genes and pathways involved in drug resistance.
• Integration of drug resistance and gene perturbation data offers novel insights for cancer therapy development.