Combining mechanistic quantitative systems pharmacology modeling and patient-derived organoid testing in MET-aberrant...

Area of Science:

• Oncology
• Pharmacology
• Systems Biology

Background:

• Non-small cell lung cancer (NSCLC) with MET exon 14 skipping mutations or MET amplification presents aggressive phenotypes and significant therapeutic challenges.
• Current MET-targeted therapies face limitations including resistance, short response duration, and suboptimal response rates, highlighting the need for novel treatment strategies.
• Addressing unmet needs in MET-aberrant NSCLC requires effective combination therapies, dose optimization, and personalized medicine approaches.

Purpose of the Study:

• To develop a quantitative systems pharmacology (QSP) model to mechanistically simulate the MET signaling network in NSCLC.
• To integrate preclinical and clinical data for 16 candidate drugs to advance translational drug research.
• To explore a hybrid QSP and patient-derived organoid (PDO) data approach for personalized treatment regimen design in MET-amplified NSCLC.

Main Methods:

• Development of a multiscale QSP model capturing MET signaling network complexity.
• Integration of multiscale preclinical-clinical datasets for 16 candidate drugs.
• Calibration, validation, and application of the QSP model for high-throughput efficacy analysis of combination therapies and dose ranges.
• Integration of patient-derived organoid (PDO) drug sensitivity data into the QSP framework.

Main Results:

• The validated QSP model enabled high-throughput analysis of emerging combination therapies across various dose ranges for MET-aberrant NSCLC.
• The QSP framework provided crucial insights for drug development and dose optimization.
• Integration with PDO data demonstrated translational utility for designing personalized treatment regimens in MET-amplified NSCLC patients.

Conclusions:

• This study presents the first multiscale QSP investigation of MET dysregulation for translational cancer drug research.
• The hybrid QSP-PDO data analysis paradigm offers a novel route to facilitate personalized medicine in NSCLC.
• The developed QSP model serves as a valuable tool for optimizing combination therapies and advancing personalized treatment strategies for MET-aberrant NSCLC.