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<p>Gene and cell therapies pose safety concerns due to potential insertional mutagenesis by viral vectors. We introduce MELISSA, a regression-based statistical framework for analyzing Integration Site (IS) data to assess insertional mutagenesis risk, by estimating and comparing gene-specific integration rates and their impact on clone fitness. 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). 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 offers a quantitative tool 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.</p>

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Modeling integration site data for safety assessment with MELISSA

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年8月23日

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  • Tsai-Yu Lin,
  • Giacomo Ceoldo,
  • Kimberley House,
  • Matthew Welty,
  • Thao Thi Dang,
  • Denise Klatt,
  • Christian Brendel,
  • Michael P. Murphy,
  • Kenneth Cornetta,
  • Danilo Pellin

摘要

Gene and cell therapies pose safety concerns due to potential insertional mutagenesis by viral vectors. We introduce MELISSA, a regression-based statistical framework for analyzing Integration Site (IS) data to assess insertional mutagenesis risk, by estimating and comparing gene-specific integration rates and their impact on clone fitness. 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). 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 offers a quantitative tool 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.