Functional assessment of genes and common genetic risk variants in ovarian cancer

卵巢癌基因和常见遗传风险变异的功能评估

• 批准号: 7933448
• 负责人: THOMAS A SELLERS
• 金额: $ 58.33万
• 依托单位: H. LEE MOFFITT CANCER CTR & RES INST
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-04-01 至 2014-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7933448
• 关键词: Alleles; Biochemical; Bioinformatics; Biological; Biological Assay; Biological Process; Biology; Cancer cell line; Candidate Disease Gene; Cell Line; Clinical Research; Colorectal; Communities; Complementary DNA; DNA; DNA Binding; DNA Microarray Chip; Data; Decision Trees; Deoxyribonuclease I; Development; Diagnosis; Disease; Distant; Elements; Environment; Epithelial Cells; Epithelial ovarian cancer; Epithelium; Etiology; FGFR2 gene; Gene Expression; Gene Expression Regulation; Genes; Genetic Predisposition to Disease; Genetic Risk; Genotype; Goals; Growth; Gynecologic; Hypersensitivity; Instruction; Junk DNA; Knowledge; Lead; Location; Malignant Neoplasms; Malignant neoplasm of ovary; Mediating; Methodology; Methods; Methylation; MicroRNAs; Microarray Analysis; Modeling; Mutation; Nature; Normal tissue morphology; Nucleic Acid Regulatory Sequences; Open Reading Frames; Ovarian; Ovary; Penetrance; Peripheral Blood Lymphocyte; Physiological; Predisposition; Primary Neoplasm; Prostate; Proteins; RNA Splicing; Regulatory Element; Reporter; Research; Risk; Role; Sequence Analysis; Single Nucleotide Polymorphism; Testing; Tissue Microarray; Transcript; Variant; Woman; base; cancer risk; chromatin immunoprecipitation; data mining; falls; genetic variant; genome wide association study; genome-wide; improved; lentiviral-mediated; lung melanoma; malignant breast neoplasm; migration; protein expression; protein function; small hairpin RNA; tool

PROJECT SUMMARY (See instructions): N.2: Project 2 Ovarian cancer is a lethal gynecologic malignancy and its development is poorly understood. We have performed four independent genome wide association studies (GWAS) in ovarian cancer and have identified highly significant, replicated single nucleotide polymorphisms (SNPs) associated with ovarian cancer risk. In Project 1, these GWAS will be combined to identify additional susceptibility loci and genetic variants associated with risk. Here we will evaluate the functional significance of candidate genes and SNPs at these loci. The specific aims are as follows: 1. To evaluate the role of candidate genes at susceptibility loci in ovarian cancer. We will use bioinformatics tools to extract publicly available data describing a role for candidate genes in cancer. Next, we will assess differences in transcript/protein expression between ovarian cancer cell lines and primary tumours, and normal ovarian epithelia. Then we will determine whether candidate genes have acquired somatic genetic changes in primary ovarian cancers. 2. To determine the functional significance of candidate SNPs in the susceptibility regions. Bioinformatics tools will be employed to determine whether a SNP's DNA location can predict functional impact. We will also correlate SNP genotype and copy number variants (CNVs) with differential germline expression and methylation status. 3. To evaluate the role of candidate SNPs located distant from known Open Reading Frames. We expect several SNP associations to fall in "gene deserts". Bioinformatics tools will be used to predict microRNAs or distant regulatory regions, and to identify conserved elements. We will look for functional evidence of regulatory elements correlated with SNP location using chromatin immunoprecipitation and sequencing analysis (ChlP-Seq). 4. To perform detailed functional characterization of candidate genes and SNPs. We will evaluate the biological significance of candidate genes using three-dimensional culture models of ovarian cancers and normal ovaries. We will modulate their expression using cDNA or shRNA expression mediated by lentlviral transduction. Bioinformatics predictions of SNP function will be tested using specific functional assays that will depend on the nature of the candidate gene and SNP. This will include mobility shift DNA binding, reporter and DNAse I hypersensitivity assays. The knowledge gained from this large collaborative study will significantly contribute to our understanding of the functional rationale underlying genetic susceptibility and survival in women diagnosed with ovarian cancer.

项目总结(见说明)：编号2：项目2 卵巢癌是一种致命的妇科恶性肿瘤，对其发展情况知之甚少。我们已经在卵巢癌中进行了四项独立的全基因组关联研究，并发现了与卵巢癌风险相关的高度显著的、复制的单核苷酸多态(SNPs)。在项目1中，将结合这些GWAS来确定与风险相关的其他易感基因座和遗传变异。在这里，我们将评估候选基因和SNPs在这些基因座上的功能意义。具体研究目的如下：1.探讨卵巢癌易感基因候选基因在卵巢癌发病中的作用。我们将使用生物信息学工具提取公开可用的数据，描述候选基因在癌症中的作用。接下来，我们将评估卵巢组织中转录/蛋白表达的差异 癌细胞系和原发肿瘤，以及正常卵巢上皮。然后我们将确定是否 在原发性卵巢癌中，候选基因已获得体细胞遗传学改变。2.确定候选SNPs在易感区域的功能意义。生物信息学工具将被用来确定SNP的DNA位置是否可以预测功能影响。我们还将把SNP基因型和拷贝数变异(CNV)与不同的种系表达和甲基化状态联系起来。3.评估远离已知开放阅读框架的候选SNPs的作用。我们预计，有几个SNP关联将陷入“基因沙漠”。生物信息学工具将被用来预测微小RNA或遥远的调控区域，并识别保守的元件。我们将使用染色质免疫沉淀和测序分析(ChlP-Seq)来寻找与SNP定位相关的调控元件的功能证据。4.对候选基因和SNPs进行详细的功能鉴定。我们将使用卵巢癌和正常卵巢的三维培养模型来评估候选基因的生物学意义。我们将通过慢病毒转导介导的cDNA或shRNA表达来调节它们的表达。对SNP功能的生物信息学预测将使用特定的功能分析进行测试，这将取决于候选基因和SNP的性质。这将包括迁移率改变DNA结合，报告和DNase I超敏分析。从这项大型合作研究中获得的知识将大大有助于我们理解卵巢癌患者遗传易感性和存活率背后的功能基础。