Acosta Jonuelle, Johnson Grace A, Gould Samuel I, Dong Kexin, Lendner Yovel, Detrés Diego, Atwa Ondine, Bulkens Jari, Gruber Samuel, Contreras Manuel E, Wuest Alexandra N, Narendra Varun K, Hemann Michael T, Sánchez-Rivera Francisco J
Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA.
David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
bioRxiv. 2025 Feb 26:2025.02.23.639770. doi: 10.1101/2025.02.23.639770.
Human genome sequencing efforts in healthy and diseased individuals continue to identify a broad spectrum of genetic variants associated with predisposition, progression, and therapeutic outcomes for diseases like cancer. Insights derived from these studies have significant potential to guide clinical diagnoses and treatment decisions; however, the relative importance and functional impact of most genetic variants remain poorly understood. Precision genome editing technologies like base and prime editing can be used to systematically engineer and interrogate diverse types of endogenous genetic variants in their native context. We and others have recently developed and applied scalable sensor-based screening approaches to engineer and measure the phenotypes produced by thousands of endogenous mutations . However, the impact of most genetic variants in the physiological setting, including contextual differences depending on the tissue or microenvironment, remains unexplored. Here, we integrate new cross-species base editing sensor libraries with syngeneic cancer mouse models to develop a multiplexed platform for systematic functional analysis of endogenous genetic variants in primary and disseminated malignancies. We used this platform to screen 13,840 guide RNAs designed to engineer 7,783 human cancer-associated mutations mapping to 489 endogenous protein-coding genes, allowing us to construct a rich compendium of putative functional interactions between genes, mutations, and physiological contexts. Our findings suggest that the physiological environment and cellular organotropism are important contextual determinants of specific gene-variant phenotypes. We also show that many mutations and their effects fail to be detected with standard CRISPR-Cas9 nuclease approaches and often produce discordant phenotypes, potentially due to site-specific amino acid selection- or separation-of-function mechanisms. This versatile platform could be deployed to investigate how genetic variation impacts diverse phenotypes associated with cancer and other genetic diseases, as well as identify new potential therapeutic avenues to treat human disease.
对健康个体和患病个体的人类基因组测序工作不断发现与癌症等疾病的易感性、进展和治疗结果相关的广泛遗传变异。这些研究得出的见解具有指导临床诊断和治疗决策的巨大潜力；然而，大多数遗传变异的相对重要性和功能影响仍知之甚少。碱基编辑和引导编辑等精准基因组编辑技术可用于在其天然环境中系统地改造和研究各种类型的内源性遗传变异。我们和其他人最近开发并应用了基于传感器的可扩展筛选方法，以改造和测量数千种内源性突变产生的表型。然而，大多数遗传变异在生理环境中的影响，包括取决于组织或微环境的背景差异，仍未得到探索。在这里，我们将新的跨物种碱基编辑传感器文库与同基因癌症小鼠模型相结合，开发了一个用于对原发性和转移性恶性肿瘤中的内源性遗传变异进行系统功能分析的多重平台。我们使用这个平台筛选了13840个引导RNA，这些引导RNA旨在改造7783个人类癌症相关突变，这些突变映射到489个内源性蛋白质编码基因，使我们能够构建一个丰富的基因、突变和生理环境之间假定功能相互作用的汇编。我们的研究结果表明，生理环境和细胞器官嗜性是特定基因变异表型的重要背景决定因素。我们还表明，许多突变及其影响无法用标准的CRISPR-Cas9核酸酶方法检测到，并且通常会产生不一致的表型，这可能是由于位点特异性氨基酸选择或功能分离机制。这个多功能平台可用于研究遗传变异如何影响与癌症和其他遗传疾病相关的各种表型，以及确定治疗人类疾病的新潜在治疗途径。
