GENE-59. NOT ALL p53 MUTATIONS ARE CREATED EQUAL: A MURINE ASTROCYTE MODEL FOR HIGH-THROUGHPUT FUNCTIONAL ASSESSMENT OF p53 MISSENSE MUTATIONS

摘要

The tumor suppressor TP53 (p53) is the most commonly mutated gene in cancer and among the most frequently mutated genes in glioblastoma (GBM). The majority of p53 mutations in GBM are missense mutations in the DNA binding domain that lead to the production of full length mutant p53 protein. In addition to the complete loss of tumor suppressor function, these mutations have gain-of-function (GOF) properties either through attenuation of wild-type function or neomorphic functions. The variability in GOF mutations results in heterogeneity in cancer phenotypes between mutants that remain poorly understood. Here, we developed a murine astrocyte model to functionally assess a library of p53 mutants in parallel. Primary astrocytes were isolated from postnatal day one pups possessing a single copy of wild-type p53 flanked by loxP sites (TRP53f/-). We then built a library of 17 individual alleles of recurring mutations in GBM with flanking loxP sites. When co-transfected into the mouse astrocytes with a plasmid expressing Cre recombinase, the endogenous WT p53 was excised and replaced with a single copy of the mutant allele. In this way, all astrocytes expressed a single copy of mutant p53 from the endogenous p53 locus. As the mutant p53 cells expanded, aliquots of cells were extracted for targeted genomic sequencing of the p53 allele. Comparing the allelic frequencies of each mutant overtime revealed a wide distribution of growth rates between mutants. To validate the screen results, wildtype astrocytes were transduced with mutant p53-IRES-eGFP retrovirus to overexpress one of three mutations with divergent growth phenotypes. As observed in the initial screen, equivalent overexpression of the different p53 mutants was sufficient to induce significant differences in growth phenotype, with astrocytes expressing the Y217C growing the fastest, R172H second, and Y202C growing the slowest. Ongoing studies are evaluating mutation-specific p53 binding partners and transcriptional outputs.