Development of an in vitro genotoxicity assay to detect retroviral vector-induced lymphoid insertional mutants.

Safety assessment in retroviral vector-mediated gene therapy remains challenging. In clinical trials for different blood and immune disorders, insertional mutagenesis led to myeloid and lymphoid leukemia. We previously developed the In Vitro Immortalization Assay (IVIM) and Surrogate Assay for Genotoxicity Assessment (SAGA) for pre-clinical genotoxicity prediction of integrating vectors. Murine hematopoietic stem and progenitor cells (mHSPCs) transduced with mutagenic vectors acquire a proliferation advantage under limiting dilution (IVIM) and activate stem cell- and cancer-related transcriptional programs (SAGA). However, both assays present an intrinsic myeloid bias due to culture conditions. To detect lymphoid mutants, we differentiated mHSPCs to mature T cells and analyzed their phenotype, insertion site pattern, and gene expression changes after transduction with retroviral vectors. Mutagenic vectors induced a block in differentiation at an early progenitor stage (double-negative 2) compared to fully differentiated untransduced mock cultures. Arrested samples harbored high-risk insertions close to Lmo2, frequently observed in clinical trials with severe adverse events. Lymphoid insertional mutants displayed a unique gene expression signature identified by SAGA. The gene expression-based highly sensitive molecular readout will broaden our understanding of vector-induced oncogenicity and help in pre-clinical prediction of retroviral genotoxicity.

Predicting genotoxicity of viral vectors for stem cell gene therapy using gene expression-based machine learning.

Hematopoietic stem cell gene therapy is emerging as a promising therapeutic strategy for many diseases of the blood and immune system. However, several individuals who underwent gene therapy in different trials developed hematological malignancies caused by insertional mutagenesis. Preclinical assessment of vector safety remains challenging because there are few reliable assays to screen for potential insertional mutagenesis effects in vitro. Here we demonstrate that genotoxic vectors induce a unique gene expression signature linked to stemness and oncogenesis in transduced murine hematopoietic stem and progenitor cells. Based on this finding, we developed the surrogate assay for genotoxicity assessment (SAGA). SAGA classifies integrating retroviral vectors using machine learning to detect this gene expression signature during the course of in vitro immortalization. On a set of benchmark vectors with known genotoxic potential, SAGA achieved an accuracy of 90.9%. SAGA is more robust and sensitive and faster than previous assays and reliably predicts a mutagenic risk for vectors that led to leukemic severe adverse events in clinical trials. Our work provides a fast and robust tool for preclinical risk assessment of gene therapy vectors, potentially paving the way for safer gene therapy trials.