Identification of Cooperative Genetic Alterations in the Pathogenesis of Oral Cancer

口腔癌发病机制中协同遗传改变的鉴定

基本信息

批准号：
8916982
负责人：
Olivier Gevaert
金额：
$ 96.97万
依托单位：
STANFORD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-07-01 至 2019-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8916982
关键词：
Adenocarcinoma Advanced Development Air Algorithms Architecture Back Bioinformatics Biological Assay Biological Models Candidate Disease Gene Carcinoma Cell Survival Cells Chemosensitivity Assay Clustered Regularly Interspaced Short Palindromic Repeats Complementary DNA Complex Computer Analysis Critical Pathways DNA Methylation DNA Sequence Alteration Data Data Set Dependency Development Dysplasia Gene Expression Gene Mutation Genes Genetic Genomic Instability Genomics Goals Growth Head and neck structure Health Human Human Cell Line In Vitro Investigation Label Liquid substance Malignant Neoplasms Medicine Methods Methylation Modeling Molecular Mus Mutation Nature Neoplasm Metastasis Normal tissue morphology Oncogenes Oncogenic Operative Surgical Procedures Oral mucous membrane structure Organoids Output Pathogenesis Pathway interactions Patients Pharmaceutical Preparations Phenotype Primary Neoplasm Probability Process Protocols documentation Regulator Genes Sampling Specimen System Testing The Cancer Genome Atlas Tissues Transgenic Mice Update Validation Viral Xenograft Model Xenograft procedure base biobank combinatorial drug discovery epigenomics exome sequencing experience gastrointestinal gene interaction in vivo in vivo Model insight malignant breast neoplasm malignant mouth neoplasm malignant phenotype mouth squamous cell carcinoma neoplastic cell next generation novel novel strategies screening single cell sequencing small hairpin RNA tissue culture tumor tumor microenvironment

项目摘要

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.

描述（由适用提供）：通过癌症基因组地图集（TCGA）等项目，对人类恶性肿瘤的最新深度分子分析已显示出许多经常鉴定出的突变；但是，仅这些部分实际上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合成遗传相互作用的结果。因此，肿瘤的子集具有特定的共同发生的突变或基因组改变，以共依赖性方式进行合作。该应用的目的是确定与已知驱动器基因组改变口腔鳞状细胞癌（OSCC）合作的关键共依赖分子途径，这是头部和颈部最常见的恶性肿瘤之一。进而获得的洞察力将为新的药物发现和/或基本原理提供一个平台，以研究现有药物的新型组合。 AIM 1他们将使用Gevaert Lab开发的复杂的新生物信息学算法将突变和拷贝数变化数据与OSCC TCGA数据集中的DNA甲基化和基因表达数据集成在一起。这些算法将用于预测异质OSCC肿瘤之间的候选遗传相互作用，并鉴定与特定生物学过程（例如转移）相关的基因模块的主调节剂。在AIM 2中，使用患者衍生的异种移植物在体内合成致死性测定中使用“下一代”在体内合成致死性测定中，将通过Sunwoo Lab验证候选基因相互作用和主调节剂。候选转移的主要调节剂也将使用体内测定法进行评估。在AIM 3中，KUO实验室已经适应了他们在胃肠道3D空气界面初级器官培养物的培养和致癌转化方面的经验。在AIM 3中，3D器官培养方法还将直接从手术样品中直接从手术样品中生长原代OSCC肿瘤类器官，用于体外化学敏感性测试，与外外测序突变状态的相关性以及基于SHRNA/SGRNA的基因验证。（1）靶向患者衍生异种移植物和原发性肿瘤以及（2）将同时存在的突变引入正常口腔粘膜中的双向策略，将为我们对OSCC中合成遗传相互作用的理解提供重要的见解。此外，AIM 2和3的功能和遗传数据将被引导回目标1，以继续更新生物信息学模型。