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Development of synthetic lethality in cancer: molecular and cellular classification.

Shijie LiWin TopatanaSarun JuengpanichJiasheng CaoJiahao HuBin ZhangDiana MaXiujun CaiMing-Yu Chen
Published in: Signal transduction and targeted therapy (2020)
Recently, genetically targeted cancer therapies have been a topic of great interest. Synthetic lethality provides a new approach for the treatment of mutated genes that were previously considered unable to be targeted in traditional genotype-targeted treatments. The increasing researches and applications in the clinical setting made synthetic lethality a promising anticancer treatment option. However, the current understandings on different conditions of synthetic lethality have not been systematically assessed and the application of synthetic lethality in clinical practice still faces many challenges. Here, we propose a novel and systematic classification of synthetic lethality divided into gene level, pathway level, organelle level, and conditional synthetic lethality, according to the degree of specificity into its biological mechanism. Multiple preclinical findings of synthetic lethality in recent years will be reviewed and classified under these different categories. Moreover, synthetic lethality targeted drugs in clinical practice will be briefly discussed. Finally, we will explore the essential implications of this classification as well as its prospects in eliminating existing challenges and the future directions of synthetic lethality.
Keyphrases
  • clinical practice
  • machine learning
  • deep learning
  • cancer therapy
  • squamous cell carcinoma
  • stem cells
  • mesenchymal stem cells
  • young adults
  • copy number
  • drug induced
  • lymph node metastasis
  • replacement therapy