Personalized cancer models to discover and develop new therapeutic targets.

项目摘要/摘要 关于癌症基因组学的丰富数据为开发更有效的靶向提供了巨大的机会 治疗。然而，许多常见的突变癌症基因抵制药物靶向的努力，基因 肿瘤的异质性混淆了药物的选择或疗效，以及对常见药物的耐药性的产生。 使用的疗法很常见，几乎没有其他选择。需要新的方法来解决这些问题 挑战。利用由于常见突变基因突变而产生的细胞脆弱性， 例如合成致死性，是一种很有前途的方法，最近PARP抑制剂的批准证明了这一点 奥拉帕利治疗卵巢癌。我们已经开发和优化了一个合成致命发现平台，它需要 在患者来源的癌细胞培养和同基因细胞中进行高通量筛选以确定新靶点 系统。功能筛查结果与特定患者(N/1)和基于人群的结果相结合 基因组数据被用来确定对最大数量和最合适的患者有用的目标的优先顺序 基因组和分子背景。按优先顺序排列的目标要经过详尽的确认和正交 在生理相关环境中的验证，包括基因组特征的患者来源的细胞培养， 有机物和患者来源异种移植(PDX)模型。在我们的平台上确认的合成致死基因是 在物种间保守，已被确认为多种人类癌症的候选药物靶点 类型，并已导致研究人员启动的临床试验，说明了我们的平台的翻译效用。 这项提议的结果将是对几个人的新的有效靶点和治疗策略 癌症类型，包括对标准护理试剂耐药的癌症类型，以及对癌症生物学有更深入的了解 几个主要的癌症基因。

PROJECT SUMMARY/ABSTRACT The wealth of data on the genomics of cancer provides a great opportunity to develop more effective targeted therapies. However, many commonly mutated cancer genes resist efforts to target with drugs, genetic heterogeneity of tumors confounds choice or efficacy of drugs, and development of resistance to commonly used therapies is common, leaving few alternatives. New approaches are needed to address these challenges. Exploiting cellular vulnerabilities generated as a result of mutations in commonly mutated genes, e.g. synthetic lethality, is a promising approach, as illustrated by the recent approval of the PARP inhibitor olaparib in ovarian cancer. We have developed and optimized a synthetic lethal discovery platform that entails high throughput screening to identify novel targets in patient-derived cancer cell cultures and isogenic cell systems. Integration of functional screen results with both patient specific (N of 1) and population-based genomic data is used to prioritize targets useful to the greatest number of patients and in the most appropriate genomic and molecular contexts. Prioritized targets undergo exhaustive confirmation and orthogonal validation in physiologically-relevant settings including genomically characterized patient-derived cell cultures, organoids and patient derived xenograft (PDX) models. Synthetic lethal genes identified with our platform are conserved across species, have been confirmed as candidate drug targets across multiple human cancer types and have led to an investigator initiated clinical trial, illustrating the translational utility of our platform. The outcome of this proposal will be novel validated targets and therapeutic strategies to several human cancer types including those resistant to standard of care agents and a deeper understanding of the biology of several major cancer genes.