An Algorithm Combining Patient Performance Status, Second Hit Analysis, PROVEAN and Dann Prediction Tools Could Foretell Sensitization to PARP Inhibitors in Digestive, Skin, Ovarian and Breast Cancers

Area of Science:

• Oncology
• Genetics
• Pharmacology

Background:

• PARP inhibitors are effective for ovarian and other cancers with homologous repair (HR) deficiency.
• Variants of unknown significance (VUS) in HR genes hinder patient eligibility for PARP inhibitor therapy.
• Approximately 40% of genetic variants are classified as VUS.

Purpose of the Study:

• To develop a method for classifying VUS in HR genes.
• To predict patient response to PARP inhibitors based on VUS classification.
• To potentially increase the number of patients eligible for PARP inhibitor treatment.

Main Methods:

• Analysis of next-generation sequencing (NGS) data from 78 metastatic patients treated with PARP inhibitors.
• Utilized in silico predictions and variant allelic frequency to classify VUS.
• Developed a prediction algorithm for VUS sensitivity in patients with Performance Status below 3.

Main Results:

• Among 41 patients treated with olaparib, 3 had benign variants, 26 had pathogenic variants, and 12 had VUS.
• Benign variants showed no response to olaparib; pathogenic variants were associated with a median Progression-Free Survival (PFS) of 190 days.
• Patients with VUS-carrying tumors exhibited variable responses, suggesting potential sensitivity to PARP inhibitors.

Conclusions:

• VUS in HR genes can be computationally classified as benign or deleterious.
• The developed algorithm may identify patients with VUS who could benefit from PARP inhibitors.
• Further validation in larger cohorts is necessary to confirm the algorithm's efficacy.