ABSTRACT
The revolutionary CRISPR-Cas9 technology has revolutionized genetic engineering, and it holds immense potential for therapeutic interventions. However, the presence of off-target mutations and mismatch capacity poses significant challenges to its safe and precise implementation. In this study, we explore the implications of off-target effects on critical gene regions, including exons, introns, and intergenic regions. Leveraging a benchmark dataset and using innovative data preprocessing techniques, we have put forth the advantages of categorical encoding over one-hot encoding in training machine learning classifiers. Crucially, we use latent class analysis (LCA) to uncover subclasses within the off-target range, revealing distinct patterns of gene region disruption. Our comprehensive approach not only highlights the critical role of model complexity in CRISPR applications but also offers a transformative off-target scoring procedure based on ML classifiers and LCA. By bridging the gap between traditional target-off scoring and comprehensive model analysis, our study advances the understanding of off-target effects and opens new avenues for precision genome editing in diverse biological contexts. This work represents a crucial step toward ensuring the safety and efficacy of CRISPR-based therapies, underscoring the importance of responsible genetic manipulation for future therapeutic applications.
Subject(s)
CRISPR-Cas Systems , Clustered Regularly Interspaced Short Palindromic Repeats , Gene Editing , Mutation , RNA, Guide, CRISPR-Cas Systems , RNA, Guide, CRISPR-Cas Systems/genetics , Gene Editing/methods , Humans , Exons , Introns , Machine LearningABSTRACT
Chimeric antigen receptor T (CAR-T) cell therapy holds great promise as an innovative immunotherapeutic approach for cancer treatment. To optimize the production and application of CAR-T cells, we evaluated the in vivo stability and efficacy capacities of CAR-T cells developed under different conditions. In this study, CAR-T cells were activated using Phytohemagglutinin (PHA) or anti-CD3&anti-CD28 and were compared in an in vivo CD19+B-cell cancer model in mouse groups. Our results demonstrated that CAR-T cells activated with PHA exhibited higher stability and anti-cancer efficacy compared to those activated with anti-CD3&anti-CD28. Specifically, CAR19BB-T cells activated with PHA exhibited continuous proliferation and long-term persistence without compromising their anti-cancer efficacy. Kaplan-Meier survival analysis revealed prolonged overall survival in the CAR-T cell-treated groups compared to the only tumor group. Furthermore, specific LTR-targeted RT-PCR analysis confirmed the presence of CAR-T cells in the treated groups, with significantly higher levels observed in the CAR19BB-T (PHA) group compared to other groups. Histopathological analysis of spleen, kidney, and liver tissue sections indicated reduced inflammation and improved tissue integrity in the CAR-T cell-treated groups. Our findings highlight the potential benefits of using PHA as a co-stimulatory method for CAR-T cell production, offering a promising strategy to enhance their stability and persistence. These results provide valuable insights for the development of more effective and enduring immunotherapeutic approaches for cancer treatment. CAR-T cells activated with PHA may offer a compelling therapeutic option for advancing cancer immunotherapy in clinical applications.
