iTReX: Interactive exploration of mono- and combination therapy dose response profiling data.

Area of Science:

• Computational Biology
• Pharmacology
• Bioinformatics

Background:

• High-throughput screening methods are crucial for assessing tumor cell drug sensitivity and resistance.
• These methods aid in developing predictive models for treatment response and inform precision oncology decisions.
• Existing analysis methods for drug efficacy often have limitations in curve fitting and combination therapy assessment.

Purpose of the Study:

• To introduce iTReX, a user-friendly Shiny/R application for analyzing mono- and combination drug therapy responses.
• To provide advanced dose-response curve modeling and differential drug sensitivity score (DSS) for combination profiling.
• To integrate modules for visualizing drug target interaction networks and matching omics data for biomarker discovery.

Main Methods:

• Development of an interactive Shiny/R application named iTReX.
• Implementation of an extended drug sensitivity score (DSS) using a five-parameter dose-response model.
• Inclusion of modules for drug target interaction network visualization and omics data integration.

Main Results:

• iTReX enables comprehensive analysis of various drug response readouts and treatment strategies.
• The application successfully validated a cost-effective drug combination screening approach.
• iTReX demonstrated its capability in identifying sample-specific biomarkers through drug target interaction networks.

Conclusions:

• iTReX offers a versatile platform for analyzing drug sensitivity and combination therapies in oncology.
• The application facilitates the identification of potential druggable targets and predictive biomarkers.
• iTReX supports precision oncology by integrating drug response data with omics features and network analysis.