Characterizing Variants of Uncertain Drug Resistance (VUDRs) Using Quantitative Measurements at Clinical Exposures

Area of Science:

• Oncology
• Genetics
• Pharmacology

Background:

• Somatic mutations in oncogenes can cause anticancer drug resistance.
• Many such variants are clinically uncharacterized, termed Variants of Uncertain Drug Resistance (VUDRs).
• Lack of functional annotation for VUDRs hinders clinical management.

Purpose of the Study:

• To develop a high-throughput platform for classifying drug resistance variants.
• To assess the clinical implications of VUDRs for imatinib therapy.
• To establish a generalizable framework for resistance variant classification.

Main Methods:

• Deep mutational scanning was used to analyze 4922 imatinib resistance variants.
• Quantitative concentration-response measurements were linked to human pharmacokinetic data.
• 18 standards were used to validate performance across two orders of magnitude of drug sensitivity.

Main Results:

• The platform demonstrated strong quantitative performance and clinical concordance.
• Over 10% of analyzed clinical VUDRs conferred modest resistance, potentially manageable by dose escalation.
• Ancestry-specific variants were identified, suggesting the potential for private VUDRs.

Conclusions:

• A novel framework for high-throughput classification of drug resistance variants tied to human doses was established.
• Findings suggest dose escalation with generic imatinib may overcome modest resistance, potentially reducing financial toxicity.
• The study highlights the importance of characterizing VUDRs for personalized cancer therapy.