Identification of Cooperative Genetic Alterations in the Pathogenesis of Oral Cancer

 描述(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了深入的分子分析，发现了许多经常被发现的突变；然而，这些突变中只有一小部分实际上有助于特定癌症的发展。恶性表型通常是多个基因组和表观基因组异常之间综合遗传相互作用的结果。因此，肿瘤的亚群具有特定的共生突变或基因组改变，它们以相互依赖的方式协同工作。这项应用的目标是确定与口腔鳞状细胞癌(OSCC)的已知驱动因素基因组改变相配合的关键相互依赖的分子通路，OSCC是头颈部最常见的恶性肿瘤之一。所获得的洞察力反过来将为新药发现和/或现有药物的新组合的研究提供一个平台。Aim 1将使用Gevert实验室开发的复杂的新生物信息学算法，将突变和拷贝数量变化数据与OSCC TCGA数据集中的DNA甲基化和基因表达数据整合在一起。这些算法将被用来高概率地预测异质性口腔鳞癌肿瘤之间的候选遗传相互作用，并识别与特定生物过程相关的基因模块的主要调节因子，如转移。在目标2中，Sunwoo实验室将使用“下一代”体内合成致死性分析来验证候选基因相互作用和主要调节因子，使用患者来源的异种移植物来更接近地反映原发肿瘤。转移的候选主控调节器也将使用体内试验进行评估。在目标3中，Kuo实验室将他们在胃肠道3D气液界面原代有机物培养和致癌转化方面的经验应用于口腔鳞癌。因此，我们验证的野生型口腔黏膜类器官方案将被用于将共生突变和基因改变引入野生型人和小鼠口腔黏膜组织，以从功能上验证来自AIMS 1和2的假定的OSCC基因的致癌活性和多基因转化协同作用。在AIMS 3中，3D有机类化合物培养方法也将被用于直接从手术样本中培养原代人OSCC肿瘤有机物，用于体外化疗敏感性测试、与外显子组序列突变状态的相关性以及基于shRNA/sgRNA的基因验证。这种双向策略(1)针对患者来源的异种移植和原发肿瘤中的共生突变，以及(2)将共生突变引入正常口腔粘膜，将为我们理解口腔鳞癌中的合成遗传相互作用提供重要的见解。此外，AIMS 2和AIMS 3的功能和遗传数据将传回AIMS 1，以持续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.