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Modeling Brain Tumors In Vivo Using Electroporation-Based Delivery of Plasmid DNA Representing Patient Mutation Signatures.

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https://doi.org/10.3791/65286Creative Commons 'BY' version 4.0 license
Abstract

Tumor models are critical for the preclinical testing of brain tumors in terms of exploring new, more efficacious treatments. With significant interest in immunotherapy, it is even more critical to have a consistent, clinically pertinent, immunocompetent mouse model to examine the tumor and immune cell populations in the brain and their response to treatment. While most preclinical models utilize orthotopic transplantation of established tumor cell lines, the modeling system presented here allows for a "personalized" representation of patient-specific tumor mutations in a gradual, yet effective development from DNA constructs inserted into dividing neural precursor cells (NPCs) in vivo. DNA constructs feature the mosaic analysis with the dual-recombinase-mediated cassette exchange (MADR) method, allowing for single-copy, somatic mutagenesis of driver mutations. Using newborn mouse pups between birth and 3 days old, NPCs are targeted by taking advantage of these dividing cells lining the lateral ventricles. Microinjection of DNA plasmids (e.g., MADR-derived, transposons, CRISPR-directed sgRNA) into the ventricles is followed by electroporation using paddles that surround the rostral region of the head. Upon electrical stimulation, the DNA is taken up into the dividing cells, with the potential of integrating into the genome. The use of this method has successfully been demonstrated in developing both pediatric and adult brain tumors, including the most common malignant brain tumor, glioblastoma. This article discusses and demonstrates the different steps of developing a brain tumor model using this technique, including the procedure of anesthetizing young mouse pups, to microinjection of the plasmid mix, followed by electroporation. With this autochthonous, immunocompetent mouse model, researchers will have the ability to expand preclinical modeling approaches, in efforts to improve and examine efficacious cancer treatment.

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