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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.