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INTERNATIONAL CONGRESS OF

CancerGenetics

• Multiscale Bioinformatic Modeling for CRISPR-Based Immune Cell Engineering: A Framework for Targeted Cancer Immunotherapy

• Javad Sarvmeili,¹ Effat Alizadeh,^2,*
  1. Department of Medical Biotechnology, Faculty of Advanced Medical Sciences, Tabriz University of Medical Sciences
  2. Department of Medical Biotechnology, Faculty of Advanced Medical Sciences, Tabriz University of Medical Sciences
  
  
  
• Introduction: Cancer remains a major public health challenge, largely due to tumor cells’ ability to evade immune surveillance, which significantly limits the efficacy of existing therapies. Immunotherapy, particularly using T and NK cells, represents a promising approach; however, inhibitory pathways such as PD-1/PD-L1 and LAG3 continue to suppress their function. In recent years, CRISPR/Cas9 gene-editing technology has emerged as a powerful tool for reprogramming immune cells, enabling precise genetic modifications to enhance their proliferation, survival, and antitumor activity. Despite reported experimental successes, critical questions remain regarding optimal target design, minimization of off-target effects, and assessment of sustained immune responses. In this study, we developed a comprehensive bioinformatic framework that simultaneously focuses on three aspects: identifying optimal gene-editing targets, designing tumor-specific receptors and promoters, and simulating immune responses within the tumor microenvironment.
• Methods: Key genes involved in immune suppression, including PDCD1, LAG3, and TGFBRII, were retrieved from reputable genomic databases (NCBI, Ensembl). CRISPR strategies were designed using CRISPOR and Cas-OFFinder to predict sgRNA sequences with high efficiency and minimal off-target potential. To reprogram immune cell function, antigen-specific receptor sequences (CAR and TCR) and cytokine-stimulatory genes (IL-2 and IL-12) were placed under tumor-specific promoters and optimized using VectorBuilder and in silico promoter design tools. Next, a multilayer simulation pipeline was developed. At the first layer, molecular modeling (PyMOL and SwissSidechain) assessed the stability of CRISPR-induced edits and the likelihood of unintended mutations. The second layer employed network-based immune simulations (CellDesigner and COPASI) to analyze T/NK-tumor interactions in the presence or absence of inhibitory genes. The third layer used multiscale agent-based modeling to simulate engineered cell infiltration into the tumor microenvironment. Additionally, gene delivery systems, including lipid nanoparticles (LNPs) and viral vectors, were designed in silico, with their stability modeled using CHARMM-GUI and NanoModeler.
• Results: CRISPR design analysis indicated that the selected sgRNAs targeting PDCD1 and LAG3 exhibited optimal cutting efficiency and low off-target risk (CFD scores and ≤3 potential mismatches). Immune network modeling predicted that simultaneous knockout of these genes could synergistically reduce inhibitory signaling while enhancing T/NK cell activation and survival. At the expression level, HIF-1α-responsive promoters driving IL-2 and IL-12 secretion under hypoxic conditions demonstrated controlled expression patterns, potentially minimizing systemic toxicity. Agent-based and multiscale simulations showed that edited cells achieved improved penetration into central tumor regions and greater tumor burden reduction over time compared to baseline lines, although absolute efficacy depended on model parameters and requires experimental validation. Modeling of delivery systems suggested that LNPs offer predicted advantages in stability and customizability over viral vectors. Collectively, these findings provide a computational framework for the design and optimization of CRISPR-based immune cell engineering, guiding future experimental studies.
• Conclusion: The primary innovation of this study is an integrated bioinformatic pipeline encompassing sgRNA design, tumor-specific promoter engineering, and simulation of immune cell infiltration in the tumor microenvironment. Unlike previous studies that focused solely on sgRNA design or gene target identification, this approach provides a comprehensive view of the multilayer consequences of immune cell engineering. Integration of tumor-specific promoter design with network and multiscale simulations enables more accurate prediction of efficacy and safety prior to laboratory experimentation. This framework demonstrates that CRISPR-based engineering, combining inhibitory gene knockout, incorporation of enhancing receptors, and tumor-specific promoters, offers a novel strategy for targeted cancer immunotherapy. While simulation-based, these results lay a robust foundation for future experimental studies and can facilitate the development of allogeneic, off-the-shelf therapies, supporting safer, cost-effective, and scalable protocols for cancer patients.
• Keywords: Cancer immunotherapy, Bioinformatics, Immune cell engineering, CRISPR/Cas9, Multiscale simulation