Brain Tumor Modelling Using the CRISPR-Cas9 Base Editing Technology

Abstract

Introduction: In common solid tumors, a plethora of genetic alterations can act as disease-driver mutation. Approximately, 95% of these variants are single-base substitutions, being cytidine-to-thymidine (C-to-T) conversion the most common among them. Cytosine base editors (CBEs) enable efficient C-to-T substitutions at targeted loci without double-stranded breaks, overcoming one of the main limitations in classical CRISPR-Cas9 technology. A major application of base editing technology is the study or treatment of disease-associated point mutations. In this project, we will focus on the most common point mutations in different genes across paediatric and adult brain tumors: e.g. CTNNB1 and TP53, frequently altered in the medulloblastoma, and PIK3CA and TP53, commonly associated with adult gliomas. Material and methods: To properly recapitulate some of the genetic alterations identified in brain tumors, we have combined the RCAS-TVA model and the CBE system for somatic genome editing. We have generated an animal model expressing TVA receptor under the control of specific promoters (GFAP or Nestin) together with an inducible CBE in order to exploit the base editing technology in the neural stem cells compartment in vivo. By intracranial injection of these mice with sgRNAs for specific genetic alterations, we will be able to recapitulate these point mutations in vivo. Results: We have successfully generated a novel mouse model for generation of brain tumors driven by point mutations in several genes that are known to drive tumorigenesis in humans. Characterization of these tumors allowed the detection by Sanger sequencing of C-to-T conversion in all samples, as well as the activation of downstream signaling derived from each mutations. We observed a complete loss of TP53 expression upon Tp53Q97*, which translates into an early stop codon in Tp53 sequence. On the other hand, we also validated the overexpression of TP53 as a consequence of Tp53R270C mutations with no major changes in downstream effectors, as it has been previously described in the literature. Conclusion: By integrating the RCAS-TVA system together with BE we have developed a more precise and flexible tool to better recapitulate in a more efficient way many point mutations identified in different brain tumor types. Using the RCAS-TVA-BE model we were able to model common point mutations in brain cancer and confirm their contribution in tumor formation.