Identification of Cooperative Genetic Alterations in the Pathogenesis of Oral Cancer

 描述（由申请人提供）：最近通过癌症基因组图谱（TCGA）等项目对人类恶性肿瘤进行的深入分子分析揭示了许多常见的突变;然而，实际上只有其中的一部分有助于特定癌症的发展。恶性表型通常是多种基因组和表观基因组畸变之间的合成遗传相互作用的结果。因此，肿瘤的子集具有以共依赖方式协作的特定共发生突变或基因组改变。本申请的目的是确定与口腔鳞状细胞癌（OSCC）（头颈部最常见的恶性肿瘤之一）中已知驱动基因组改变合作的关键共依赖分子途径。所获得的见解反过来将为新药发现提供平台和/或为现有药物的新型组合的研究提供理论依据。目标1将使用Gevaert实验室开发的复杂的新生物信息学算法，将突变和拷贝数改变数据与OSCC TCGA数据集中的DNA甲基化和基因表达数据整合在一起。这些算法将被用来预测，高概率，候选人之间的异质性口腔鳞癌肿瘤的遗传相互作用，并确定主调节基因模块相关的特定生物过程，如转移。在目标2中，候选基因相互作用和主调节因子将由Sunwoo实验室使用“下一代”体内合成致死性测定来验证，使用患者来源的异种移植物来更密切地反映原发性肿瘤。还将使用体内测定来评估转移的候选主调节因子。在目标3中，Kuo实验室将他们在胃肠道3D气液界面原代类器官培养物的培养和致癌转化方面的经验应用于OSCC。因此，我们验证的野生型口腔粘膜类器官方案将用于将共发生的突变和基因改变引入野生型人类和小鼠口腔粘膜组织中，以在功能上验证来自目标1和2的推定OSCC基因的致癌活性和多基因转化协同作用。在目标3中，3D类器官培养方法也将用于直接从手术样本中生长原发性人类OSCC肿瘤类器官，用于体外化学敏感性测试，与外显子组测序突变状态的相关性和基于shRNA/sgRNA的基因验证。这种双向策略（1）靶向患者来源的异种移植物和原发性肿瘤中的共发突变和（2）将共发突变引入正常口腔粘膜将为我们理解OSCC中的合成遗传相互作用提供重要见解。此外，目标2和3的功能和遗传数据将被送回目标1，以不断更新生物信息学模型。

 DESCRIPTION (provided by applicant): Recent in depth molecular analyses of human malignancies, through projects such as The Cancer Genome Atlas (TCGA), have revealed numerous frequently identified mutations; however, only a subset of these actually contribute to the development of particular cancers. The malignant phenotype is often the result of synthetic genetic interactions between multiple genomic and epigenomic aberrations. As such, subsets of tumors have specific co-occurring mutations or genomic alterations that cooperate in a co-dependent manner. The goal of this application is to identify the critical co-dependent molecular pathways that cooperate with known driver genomic alterations in oral squamous cell carcinoma (OSCC), one of the most frequent malignancies of the head and neck. The insight gained will, in turn, provide a platform for novel drug discovery and/or rationale for the investigation of novel combinations of existing drugs. Aim 1 will use sophisticated new bioinformatics algorithms developed by the Gevaert lab to integrate mutation and copy number alteration data with DNA methylation and gene expression data in OSCC TCGA data sets. These algorithms will be used to predict, with high probability, candidate genetic interactions among heterogeneous OSCC tumors and to identify master regulators of gene modules that are related to particular biologic processes, such as metastasis. In Aim 2, candidate gene interactions and master regulators will be validated by the Sunwoo lab using "next generation" in vivo synthetic lethality assays, using patient-derived xenografts to more closely reflect the primary tumor. Candidate master regulators of metastasis will also be evaluated using in vivo assays. In Aim 3, the Kuo lab has adapted their experience in culture and oncogenic transformation of gastrointestinal 3D air-liquid interface primary organoid cultures to OSCC. Accordingly, our validated wild-type oral mucosal organoid protocols will be used to introduce co-occurring mutations and gene alterations into wild-type human and mouse oral mucosa tissue to functionally validate the oncogenic activity and multigenic transforming synergy of putative OSCC genes from Aims 1 and 2. In Aim 3, the 3D organoid culture approach will also be used to grow primary human OSCC tumor organoids directly from surgical samples, for in vitro chemosensitivity testing, correlation against exome sequencing mutational status and shRNA/sgRNA-based gene validation. This bi-directional strategy of (1) targeting co-occurring mutations in patient-derived xenografts and primary tumors and (2) introducing co-occurring mutations into normal oral mucosa will provide important insight into our understanding of the synthetic genetic interactions in OSCC. Further, the functional and genetic data from Aims 2 and 3 will be channeled back to Aim 1 to continuously update the bioinformatics models.