Systematic Characterization and Targeting of Neomorphic Drivers in Cancer

项目概要/摘要 在癌症中已经发现了超过300万个体细胞突变和融合基因。然而，我们的能力， 预测功能后果和这些躯体畸变的治疗相关性仍然是一个主要的 挑战.更关键的是，我们还没有解决如何有效靶向新生像差的挑战 其中对肿瘤细胞内在或肿瘤微环境过程的功能后果是 通过调节过程、结合伴侣或细胞位置的关键变化而改变， 新的和不可预测的功能。为了应对这一挑战，针对PAR-21-274， CTD 2中心将采用 标识符， 生物标志物。 最先进的高通量计算和实验方法， 描述、验证和瞄准新的新形态驱动因素，并提名相关的预测因素 我们选择了神经胶质瘤、肉瘤和子宫内膜癌作为概念验证，因为它们代表 高度未满足的需要由点突变和融合基因驱动的癌症类型， 起源组织。在我们鉴定的驱动基因中，约15%的点突变和约30%的融合基因是 估计有新形态的影响。 理解 转移 可能 确定 战略 我们的应用程序将解决PAR中列出的三个关键领域：（i）改善 基因功能的途径和细胞布线在癌症的发生，发展， （ii）鉴定和确认候选生物靶标，以及 相关的预测标志物，其涉及癌症病因学，其易于调节;和（iii） 如何利用这些特定环境的新形态途径， 以免疫系统为目标，并确定耐药机制。基于我们的成功 L 在当前的CTD 2项目中，我们组建了一个协作、高效、跨学科的团队，包括米尔斯博士 （肿瘤生物学/临床试验），Deneen（分子遗传学/电穿孔肿瘤模型），Liang（计算 生物学）和陈（创新算法），并将追求三个具体目标;目标1：开发 用于预测新形态驾驶员像差的计算算法。目标2：确定和阐明 潜在的新形态驱动程序畸变的机制。目的3：阐明治疗 由新形态驾驶员畸变产生的责任。我们选择评估新形态驱动程序 因为它们作为一个类别，具有新的和不可预测的功能，这些功能会混淆分子信息决定， 这可能导致许多患者的靶向治疗失败。通过了解新形态 畸变影响肿瘤细胞中蛋白质和细胞途径内的下游功能 微环境，我们将确定可以在人体临床试验中直接测试的治疗机会， 在当前的CTD 2项目中得到证实（启动了>10项试验）。重要的是，我们对建模的关注是众所周知的， 预测的新形态突变和融合基因在本地模型将补充其他CTD 2 中心使用RNAi和CRISPR/Cas9策略对功能丧失（LOF）事件进行建模。

PROJECT SUMMARY/ABSTRACT More than 3 million somatic mutations and fusion genes have been identified in cancer. However, our ability to predict functional consequences and the therapeutic relevance of these somatic aberrations remains a major challenge. More critically, we have not solved the challenge of how to effectively target neomorphic aberrations where functional consequences on tumor cell-intrinsic or tumor microenvironment processes are altered through critical changes in regulatory processes, binding partners, or cellular locations, leading to novel and unpredictable functions. To address this challenge, in response to PAR-21-274, we propose a CTD2 Center that will employ identify, biomarkers. state-of-the-art, high-throughput computational and experimental approaches to characterize, validate, and target novel neomorphic drivers as well as nominate related predictive We have selected glioma, sarcoma, and endometrial cancers for proof of concept as they represent high unmet need cancer types that are driven by point mutations and fusion genes and encompass divergent tissues of origin. Of the driver genes we identified, ~15% of the point mutations and ~30% of the fusions are estimated to have neomorphic effects. understanding metastasis possibly determine strategies Our application wil address three key areas listed in the PAR: (i) improve of gene functions in pathways and cellular wiring important in cancer initiation, progression, and within the context of a few human tumors; (ii) identify and confirm candidate biological targets, and associated predictive markers, involved in cancer etiology which are amenable to modulation; and (iii) how these context-specific neomorphic pathways can be harnessed in combination with established that target the immune system, and identify mechanisms of resistance. Based on the success of our l current CTD2 project, we have assembled a collaborative, productive, interdisciplinary team comprising Drs. Mills (tumor biology/clinical trials), Deneen (molecular genetics/electroporation tumor models), Liang (computational biology), and Chen (innovative algorithms) and will pursue three Specific Aims; Aim 1: To develop computational algorithms for predicting neomorphic driver aberrations. Aim 2: To identify and elucidate mechanisms underlying potential neomorphic driver aberrations. Aim 3: To elucidate therapeutic liabilities engendered by neomorphic driver aberrations. We have chosen to evaluate neomorphic drivers because they, as a class, have new and unpredictable functions that confound molecularly informed decisions, potentially contributing to the failure of targeted therapy in many patients. By understanding how neomorphic aberrations affect downstream function within the protein and cellular pathways in tumor cells and the tumor microenvironment, we will identify therapeutic opportunities that can be directly tested in human clinical trials, as demonstrated in the current CTD2 project (>10 trials launched). Importantly, our focus on modeling known and predicted neomorphic mutations and fusion genes in autochthonous models will complement other CTD2 Centers' modeling of loss-of-function (LOF) events using RNAi and CRISPR/Cas9 strategies.