Abstract 2191: Detection of actionable lung cancer fusion genes with known and novel partners from highly degraded FFPE material

Abstract

Abstract Chromosomal rearrangements resulting in expression of oncogenic chimeric proteins drive tumor progression. Gene fusions are promising targets for cancer therapy in various types of cancers. Therefore, faithful detection of gene fusions is essential in precision medicine. Previously, fusions have been detected using FISH, RT-PCR and RNA-seq. Targeted sequencing provides better sensitivity as only the regions associated with the driver genes are sequenced, increasing possible coverage depth, and reducing cost. We developed a targeted RNA-based lung cancer fusion panel utilizing 5’ RACE technology to construct a NGS library for detection of fusion transcripts present in total RNA from highly degraded samples, such as blood or FFPE samples. The panel is deliberately designed to cover 64 known actionable fusion genes as well as novel gene fusions. Using an in-house fusion RNA mix comprising of 52 fusion transcripts, the panel was optimized and balanced. A total of 40 lung cancer patient FFPE samples, one 6-fusion FFPE reference sample and three fusion positive cell line samples were used for validating the panel. Limit of detection (LoD) was determined using the in-house RNA mix and normal lung tissue RNA. The minimum RNA input to detect all 52 fusion transcripts was 10-4 ng (0.1 pg) of mixture of RNAs in background of 10 ng of normal lung tissue RNA. The panel successfully detected all six fusion transcripts with 10 ng of RNA from a 6-fusion reference FFPE sample. With this confirmation, we tested clinically relevant sample types which are damaged RNAs from FFPE material. This study demonstrates the performance of our newly developed NGS fusion gene panel with clinical samples. It accommodates highly degraded RNA samples with low amounts of input. The next step would be to expand the testing to include more samples and cell-free RNAs. Citation Format: Bongyong Lee, Alisha Babu, Aiguo Zhang, Michael Y. Sha. Detection of actionable lung cancer fusion genes with known and novel partners from highly degraded FFPE material [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2191.