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发现和验证癌症遗传相关性:方法与陷阱。

Discovering and validating cancer genetic dependencies: approaches and pitfalls.

机构信息

Stanford University, Palo Alto, CA, USA.

Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.

出版信息

Nat Rev Genet. 2020 Nov;21(11):671-682. doi: 10.1038/s41576-020-0247-7. Epub 2020 Jun 19.

Abstract

Cancer 'genetic dependencies' - genes whose products are essential for cancer cell fitness - are promising targets for therapeutic development. However, recent evidence has cast doubt on the validity of several putative dependencies that are currently being targeted in cancer clinical trials, underscoring the challenges inherent in correctly identifying cancer-essential genes. Here we review several common techniques and platforms for discovering and characterizing cancer dependencies. We discuss the strengths and drawbacks of different gene-perturbation approaches, and we highlight the use of poorly validated genetic and pharmacological agents as a common cause of target misidentification. A careful consideration of the limitations of current technologies and cancer models will improve our ability to correctly uncover cancer genetic dependencies and will facilitate the development of improved therapeutic agents.

摘要

癌症“遗传依赖性”——其产物对癌细胞适应性至关重要的基因——是治疗开发的有前途的靶点。然而,最近的证据对目前在癌症临床试验中针对的几个假定依赖性提出了质疑,凸显了正确识别癌症必需基因所固有的挑战。在这里,我们回顾了几种发现和表征癌症依赖性的常用技术和平台。我们讨论了不同基因干扰方法的优缺点,并强调了使用未经充分验证的遗传和药理学试剂作为目标错误识别的常见原因。仔细考虑当前技术和癌症模型的局限性将提高我们正确揭示癌症遗传依赖性的能力,并有助于开发更好的治疗药物。

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