Modeling integration site data for safety assessment with MELISSA

Gene and cell therapies pose safety concerns due to potential insertional mutagenesis by viral vectors. We introduce MELISSA, a statistical framework for analyzing Integration Site (IS) data to assess insertional mutagenesis risk. MELISSA employs regression models to estimate and compare gene-specific integration rates and their impact on clone fitness. We tested MELISSA under three settings. First, we conducted simulation studies to verify its performance under controlled conditions. Second, we characterized the IS profile of a lentiviral vector on Mesenchymal Stem Cells (MSCs) and compared it with that of Hematopoietic Stem and Progenitor Cells (HSPCs), in addition to comparing the in vitro clonal dynamics of MSCs isolated from alternative tissues. Finally, we applied MELISSA to published IS data from patients enrolled in gene therapy clinical trials, successfully identifying both known and novel genes that drive changes in clone growth through vector integration. MELISSA identifies over– and under-targeted genes, estimates IS impact and explores biological relevance through pathway analysis. This offers a quantitative tool for researchers, clinicians, and regulators to bridge the gap between IS data and safety and efficacy evaluation, facilitating the generation of comprehensive data packages supporting Investigational New Drug (IND) and Biologics License (BLA) applications and the development of safe and effective gene and cell therapies.