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Determining the Influence Genomic Instability During Embryogenesis has on Tumor Penetrance

Determining the Influence Genomic Instability During Embryogenesis has on Tumor Penetrance
确定胚胎发生过程中基因组不稳定性对肿瘤外显率的影响
批准号:
9378133
负责人:
John M Parant
金额:
$19.38万
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-09-11 至 2019-08-31

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英文摘要
Abstract Li Fraumeni patients, which harbor heterozygous p53 germ line mutation, are highly predisposed to cancers. The penetrance of these individuals can vary greatly; some individuals have tumor onset prior to age 1, while some individual that do not present with cancer by age 74. P53 is the most widely mutated gene in sporadic cancers, therefore understanding the mechanisms that impact tumor penetrance will have great benefit to predicting individual cancer risk. It has been demonstrated that tumor that loss the wild-type p53 allele (loss of heterozygosity (LOH)) associate with earlier tumor onset. These LOH event are the result of genomic alterations associated with genomic instability. Therefore, an individual with frequent genomic instability events is more likely to have p53 LOH, and earlier tumor onset. We and others have shown that chromosome instability events have been documented in very early stage humans, mouse and zebrafish embryos. This has lead us to develop the hypothesize that differences in genomic instability during embryogenesis between individuals, which drive p53 LOH, determine the variability in tumor penetrance of LFS patients. While intuitive this hypothesis has not been formally tested. Within this proposal we will test this hypothesis by defining cohorts of animals with high genomic instability and low genomic instability during embryogenesis and determine if the amount of genomic instability determined the tumor penetrance in an animal model of LFS. The expected overall impact of the proposed work is that it will fundamentally advance our understanding of a how genomic instability during embryogenesis impacts tumorigenesis. This will serve as the foundation for future therapeutic intervention and predictive biomarkers of cancer risk.
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