Prediction of dynamical drug sensitivity and resistance by module network rewiring-analysis based on transcriptional...

Area of Science:

• Systems biology
• Pharmacogenomics
• Computational biology

Background:

• Understanding functional reorganization at the network level is crucial for deciphering drug responses and therapeutic mechanisms.
• Existing methods often focus on molecular networks or individual genes, potentially missing higher-level functional changes.

Purpose of the Study:

• To introduce a novel model and framework, module network rewiring-analysis (MNR), for characterizing functional reorganization in complex biological systems.
• To systematically study dynamic drug sensitivity and resistance during therapeutic interventions.

Main Methods:

• Developed and applied the module network rewiring-analysis (MNR) framework to analyze functional reorganization at the module network level.
• Investigated gene expression data from Hepatitis C virus patients undergoing Interferon therapy.
• Focused on module network rewiring rather than individual molecular analysis.

Main Results:

• MNR identified consistent module genes that revealed novel genotypes associated with drug sensitivity, outperforming traditional differential gene expression analyses.
• Functional connections and reconnections among modules, bridged by biological pathways, were found essential for effective drug response.
• Hierarchical structures of the temporal module network served as spatio-temporal biomarkers for monitoring therapy efficacy, toxicity, and resistance.

Conclusions:

• MNR is an effective tool for identifying module biomarkers and predicting dynamic drug sensitivity and resistance.
• The framework aids in characterizing complex dynamic processes underlying therapy response.
• Provides systematic biological insights for pharmacogenomic applications.