SETD8C302R Mutation Revealed from Myofibroblastoma-Discordant Monozygotic Twins Leads to p53/p21 Deficit and WEE1 Inhibitor Sensitivity.
Miao LiHongwu WangHongwei LiaoJiaxin ShenYinfang WuYanping WuQingyu WengChen ZhuXinwei GengFen LanYang XiaBin ZhangHang ZouNan ZhangYunzhi ZhouZhihua ChenHuahao ShenSongmin YingWen LiPublished in: Advanced science (Weinheim, Baden-Wurttemberg, Germany) (2020)
High-throughput gene sequencing has identified various genetic variants as the culprits for some common hereditary cancers. However, the heritability of a substantial proportion of cancers remains unexplained, which may result from rare deleterious mutations hidden in a myriad of nonsense genetic variations. This poses a great challenge to the understanding of the pathology and thus the rational design of effective treatments for affected patients. Here, whole genome sequencing is employed in a representative case in which one monozygotic twin is discordant for lung inflammatory myofibroblastoma to disclose rare tumor-related mutations. A missense single nucleotide variation rs61955126 T>C in the lysine methyltransferase SETD8 (accession: NM_020382, SETD8C302R ) is exposed. It is shown that SETD8 is vital for genomic integrity by promoting faithful DNA replication, and its C302R mutation downregulates the p53/p21 pathway. Importantly, the SETD8C302R mutation significantly increases the sensitivity of cancer cells to WEE1 inhibition. Given that WEE1 inhibitors have shown great promise for clinical approval, these results impart a potential therapeutic approach using WEE1 inhibitor for cancer patients carrying the same mutation, and indicate that genome sequencing and genetic functional studies can be integrated into individualized therapies.
Keyphrases
- single cell
- genome wide
- copy number
- high throughput
- end stage renal disease
- ejection fraction
- newly diagnosed
- prognostic factors
- dna methylation
- chronic kidney disease
- intellectual disability
- photodynamic therapy
- machine learning
- big data
- peritoneal dialysis
- transcription factor
- autism spectrum disorder
- young adults
- artificial intelligence
- genome wide identification
- preterm birth
- deep learning
- childhood cancer