Abstract 2443: Improved detection of low frequency mutations in ovarian and endometrial cancers by utilizing a highly accurate sequencing platform

Abstract

Abstract Ovarian and endometrial cancers come within the top-4 for incident cancers as well as deaths in North American women. Cure rates have not improved in 30 years as high-grade subtypes continue to be diagnosed in Stage III/IV. Attempts at early diagnosis have failed because high-grade cancer cells exfoliate and metastasize while the primary cancer is small and undetectable by existing tests based on imaging and blood-based tumor markers. DOvEEgene (Detecting Ovarian and Endometrial cancers Early using genomics) is a genomic uterine pap test developed by a McGill team to screen and detect these cancers while they are confined to the gynecologic organs and curable by surgery. The test identifies pathogenic somatic mutations in uterine brush samples. Here we tested the Onso system, a highly accurate sequencing technology from PacBio in order to potentially increase sensitivity while driving down sequencing costs by reducing required sequencing depth vs the current NGS standard. A highly sensitive, error-correcting capture technology (DOvEEgene-SureSelectHS) utilizing duplex error correction sequencing interrogated the exons of 23 genes involved in the development of sporadic and hereditary ovarian and endometrial cancers. We applied a combination of germline gene panel testing on saliva samples with deep duplex sequencing to detect somatic mutations at <0.1% VAF, interrogation of microsatellite loci for instability, and low coverage WGS for copy number analysis of uterine brush samples. We sequenced 20 duplex Illumina sequencing libraries produced using the DovEE assay at PE 100bp mode and compared Onso data in non- duplex sequencing mode as well as duplex sequencing mode to the original Illumina duplex sequencing method. Here, we present this comparison and highlight the benefits of high accuracy sequencing for the detection of very low frequency (<0.1%) somatic mutations. We observed improved mismatch rates for Onso data compared to Illumina, even after duplex error correction was applied. In addition, we found that more individuals are called as displaying microsatellite instablity from the Onso data, which may be due to improved sequencing performance in repetitive regions for Onso. Finally, we observed fewer potential false positive variant calls in the Onso data, highlighting the value of improved sequencing accuracy for rare variant detection. Citation Format: Timothée Revil, Nairi Pezeshkian, Lucy Gilbert, Alexandra Sockell, Jiannis Ragoussis. Improved detection of low frequency mutations in ovarian and endometrial cancers by utilizing a highly accurate sequencing platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2443.