Abstract LB255: Benchmarking NGS integration site analysis methods in support of long-term safety monitoring of gene therapy products

Abstract

Abstract The FDA Guidance to Industry on Long Term Follow-Up (LTFU) After Administration of Human Gene Therapy Products states the importance of longitudinal testing of gene products introduced into human subjects. Depending on the delivery mechanism, the therapeutic gene product may or may not integrate into the genome. Of particular interest are gene-product integrations near proto-oncogenes which might lead to malignancies. The FDA LTFU guidance states that recipients of an integrating gene therapy modality should be tracked for 15 years, while those receiving a non-integrating therapy modality should be tracked for 5 years. Therefore, advanced analytical methods are needed to identify, quantify, and track integration events across the genome. Here, we provide a comprehensive evaluation of methods leveraging next-generation sequencing approaches for genome-wide analysis of lentiviral integration events. Our analysis employed well-characterized standards consisting of varying copy number and known integration sites. ​ The approaches we characterized can be bucketed into two major groups: PCR amplification approaches and target capture-based approaches. All methods detected true positives with strong correlation to theoretical integration site dosage levels down to 1% allele frequency. Comparatively, PCR amplification-based approaches have lower data requirement per sample suggesting higher sensitivity, greater molecular capture, and lower limit of detection compared with target enrichment-based approaches. Target enrichment-based approaches can afford the flexibility to capture the integrated vector, which is of interest for characterizing partial integration events. While all methodologies performed well in our study, the choice of assay (or assays) for testing will depend on numerous factors including but not limited to the viral vector system and construct and starting material availability. Citation Format: Jeffrey M. Otto, Yongjun Fan, Guanhui Bao, David Corney, Ben Niu, Qiu Yu, Baursha Khan, Laure Turner, Chris Mozdzierz, Haythem Latif, Ginger Zhou. Benchmarking NGS integration site analysis methods in support of long-term safety monitoring of gene therapy products [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr LB255.