Mapping Gene Networks in Colon Cancer

绘制结肠癌基因网络图谱

• 批准号: 7211190
• 负责人: Norman H Lee
• 金额: $ 42.84万
• 依托单位: GEORGE WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-07-18 至 2011-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7211190
• 关键词: Adhesions; Adhesiveness; Binding; Biological; Biological Models; Cancer cell line; Cells; Chromosome Mapping; Colon Carcinoma; Colonic Adenoma; Computer Architectures; Computer Simulation; Data; Derivation procedure; Disease; Gene Expression; Gene Expression Profiling; Genes; Genome; Goals; Human; Invasive; Laboratories; Liver; Lung; Malignant Neoplasms; Maps; Metastatic Neoplasm to the Liver; Modeling; Molecular Probes; Molecular Profiling; Neoplasm Metastasis; Network-based; Numbers; Oncogenes; Phenotype; Play; Process; Property; RNA Interference; Research; Role; Sampling; Screening procedure; Series; Staging; Statistical Models; Testing; Therapeutic Intervention; Work; anticancer research; base; cancer cell; chromatin immunoprecipitation; colon cancer cell line; gene interaction; improved; loss of function; lymph nodes; network models; novel strategies; small hairpin RNA; transcription factor

DESCRIPTION (provided by applicant): Colon cancer, and cancer in general, is a disease of the genome which invariably is associated with aberrant expression of genes. What is not clearly understood is how these genes are interconnected in the context of an operational network that underlies the cancer phenotype. An understanding of the network connections of cancer-related genes offers the potential to identify critical branch points amendable to therapeutic intervention. The goal of this application is to map cancer gene networks in a well-defined series of colon cancer cell lines from the NCI-60 panel. This will be accomplished by implementing an iterative process involving phenotyping, gene expression profiling, transcription factor binding analysis, and computational modeling of gene interactions. The resulting network model will be tested by perturbing cancer cell lines with molecular probes called short hairpin RNAs (siRNAs) in a process known as RNA interference (RNAi). Genes within the network whose knockdown by RNAi leads to a loss-of-cancer phenotype are hypothesized to regulate the expression of downstream effector genes. This perturbation in cancer cell lines will be examined by a subsequent round of gene expression profiling, transcription factor binding analysis and computational modeling, thereby allowing us to progressively improve our cancer network model. The validity of the revised model will be scrutinized with an ensuing round of RNAi perturbation and loss-of- cancer phenotype screening, and the iterative process is repeated. Lastly, the biological significance of genes in our networks will be cross-validated with expression profiling data of staged human colon cancers (normal colon, adenomas, Dukes' B, C and D stage samples, and liver metastases). Our research objectives are summarized as follows: (1) Construct a map of the invasion gene network, (2) Construct a map of the (anti-)adhesion gene network, and (3) Build probabilistic models of the invasion and (anti-) adhesion gene networks.

描述（由申请人提供）：结肠癌以及一般的癌症是一种基因组疾病，其总是与基因的异常表达相关。目前尚不清楚的是这些基因如何在癌症表型背后的操作网络中相互关联。了解癌症相关基因的网络连接有可能确定适合治疗干预的关键分支点。此应用程序的目标是绘制 NCI-60 组中一系列明确定义的结肠癌细胞系中的癌症基因网络。这将通过实施涉及表型分析、基因表达谱、转录因子结合分析和基因相互作用的计算建模的迭代过程来实现。由此产生的网络模型将通过使用称为短发夹 RNA (siRNA) 的分子探针在称为 RNA 干扰 (RNAi) 的过程中干扰癌细胞系来进行测试。假设网络中的基因被 RNAi 敲低会导致癌症表型丧失，从而调节下游效应基因的表达。癌细胞系中的这种扰动将通过后续一轮的基因表达谱、转录因子结合分析和计算模型进行检查，从而使我们能够逐步改进我们的癌症网络模型。修订后的模型的有效性将通过随后一轮的 RNAi 扰动和癌症表型缺失筛选进行审查，并重复迭代过程。最后，我们网络中基因的生物学意义将与人类结肠癌分期（正常结肠癌、腺瘤、Dukes' B、C 和 D 期样本以及肝转移）的表达谱数据进行交叉验证。我们的研究目标概括如下：（1）构建入侵基因网络图谱，（2）构建（抗）粘附基因网络图谱，（3）构建入侵和（抗）粘附基因网络的概率模型。