生物
癌变
突变体
错义突变
基因
遗传学
突变
癌症研究
等位基因
损失函数
表型
作者
Nathan Rockwell,Nicole M. Warrington,Joshua B. Rubin
出处
期刊:Neuro-oncology
[Oxford University Press]
日期:2018-11-01
卷期号:20 (suppl_6): vi273-vi273
标识
DOI:10.1093/neuonc/noy148.1134
摘要
The tumor suppressor TP53 (p53) is the most commonly mutated gene in cancer and is one of the most frequently mutated genes in glioblastoma (GBM). The most common p53 mutations are missense mutations in the DNA binding domain that lead to the expression of full length mutant p53 protein. In addition to the loss of tumor suppressor function, these mutations can endow oncogenic gain-of-function abilities that allow mutant p53 to bind and regulate the promoters of aberrant target genes, driving tumorigenesis. However, the mechanisms that control mutant p53 target gene specificity and the subsequent malignant phenotypes are poorly understood. We combined and analyzed patient mutation data from the COSMIC, TCGA and IARC databases to determine the prevalence of individual p53 mutations in CNS tumors. This revealed a subset of six missense mutations that exhibit significant sex differences in their frequency, suggesting that these mutations may have a sex specific effect on cancer cell fitness. Four codons were mutated more frequently in females: Y205 (p=0.004), D184 (p=0.0172), V216 (p=0.0253), and V272 (p=0.0336), and two codons were mutated more frequently in males: Y220 (p=0.0104) and R282 (p=0.0496). We developed a murine astrocyte model that will allow us to investigate the sex specific effect of each gain-of-function mutation on transcription and tumorigenesis. Using CRISPR/Cas9, relevant point mutations were inserted into the p53 DNA-binding-domain of male and female p53 heterozygous primary mouse astrocytes. These astrocytes express a single mutant p53 allele, and reflect the silencing of the WT p53 allele common in GBM. Using this model, we can directly compare the transcriptional activity of each gain-of-function mutation using ChIP-sequencing and RNA-sequencing. These cells also provide a unique model for mechanistic studies to determine the tumorigenic effects of each gain-of-function mutation, including proliferation, invasion, clonogenicity and in vivo tumorigenesis.
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