Gene-Gene Interactions and Their Functional Roles in Prostate Cancer Aggressiveness

基因间相互作用及其在前列腺癌侵袭性中的功能作用

• 批准号: 9177847
• 负责人: Hui-Yi Lin
• 金额: $ 14.78万
• 依托单位: LSU HEALTH SCIENCES CENTER
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-07 至 2018-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9177847
• 关键词: Affect; Alleles; American; Androgen Metabolism; Androgen Receptor; Angiogenesis Pathway; Apoptosis; Biological; Biological Markers; CSF1 gene; Cancer Etiology; Cancer Patient; Cessation of life; Clinical; Collection; Complex; Data; Data Set; Disease; EGF gene; Epidermal Growth Factor Receptor; Etiology; Fibroblast Growth Factor; Galectin 3; Gene Expression; Genes; Genetic; Genetic Markers; Genotype; Gleason Grade for Prostate Cancer; Goals; Heterogeneity; Individual; Indolent; Lead; Machine Learning; Malignant neoplasm of prostate; MicroRNAs; Mitochondria; Odds Ratio; Oncogenic; Pathogenesis; Pathway interactions; Patients; Phenotype; Physicians; Play; Prostate-Specific Antigen; Prostatic Neoplasms; Proteins; Public Domains; Quantitative Trait Loci; Regulation; Reporting; Research; Research Design; Risk; Role; Second Primary Cancers; Single Nucleotide Polymorphism; Solid; Staging; The Cancer Genome Atlas; Time; Tissues; Validation; Vascular Endothelial Growth Factors; abstracting; angiogenesis; base; cancer diagnosis; cancer risk; cohort; evidence base; gene interaction; genetic variant; genome wide association study; high risk; improved; innovation; men; new therapeutic target; precision medicine; receptor; research study; screening; tool; tumor

Project Summary/Abstract Prostate cancer with substantial clinical heterogeneity is the most common cancer and the second leading cause of cancer-related death in American men. It remains unclear why some prostate tumors are more aggressive than others. Existing clinical features (such as prostate specific antigen (PSA), clinical stage and Gleason score) are not sufficient for classifying high- and low-risk prostate cancer patients. It has been shown that approximately 20% of low-risk prostate cancer patients died due to conservative treatment. Thus, there is an urgent need for identifying additional biomarkers in order to improve prediction accuracy of prostate cancer aggressiveness. The majority of current studies focus on evaluating individual genetic variants, which may not be sufficient to explain the complexity of disease causality. The objective of this study is to identify gene-gene interactions within the four candidate pathways (angiogenesis, mitochondria, miRNA, and androgen metabolism) associated with prostate cancer aggressiveness and their impact on gene expression. The genetic variants (both individual effects and interactions) associated with prostate cancer aggressiveness will be performed using the existing genetic data from the large scale prostate cancer consortium, a collection of approximately 22,000 prostate cancer patients. The associations between genetic variants and gene expressions will be identified using public domain genetic data and will be validated using a cohort data set with 1065 prostate cancer patients. Evaluating genetic variants with gene expression levels helps to identify downstream genes which can guide further study and may lead to discovery of novel therapeutic targets. Our study findings can provide valuable information toward understanding pathogenesis of prostate cancer and identifying genotype combinations for predicting prostate cancer aggressiveness. As for the long-term impact, the study results may be applied in developing effective screening tools to predict prostate cancer aggressiveness.

项目总结/摘要 具有显著临床异质性的前列腺癌是最常见的癌症， 美国男性癌症相关死亡的第二大原因。目前尚不清楚为什么有些人 前列腺肿瘤比其他肿瘤更具侵袭性。现有临床特征（如前列腺 特异性抗原（PSA）、临床分期和Gleason评分）不足以将高- 和低风险前列腺癌患者。据统计，约20%的低风险 前列腺癌患者因保守治疗而死亡。因此，迫切需要 鉴定另外的生物标志物以提高前列腺癌的预测准确性 侵略性目前的大多数研究集中在评估个体遗传变异， 这可能不足以解释疾病因果关系的复杂性。的目的 研究是鉴定四种候选途径（血管生成， 线粒体、miRNA和雄激素代谢）与前列腺癌相关 攻击性及其对基因表达的影响。基因变异（两个个体 影响和相互作用）与前列腺癌的侵袭性将进行 使用来自大规模前列腺癌联盟的现有遗传数据， 大约22，000名前列腺癌患者。遗传变异与 基因表达将使用公共领域的遗传数据进行鉴定，并将使用 1065例前列腺癌患者的队列数据集。用基因评估遗传变异 表达水平有助于识别下游基因，这可以指导进一步的研究， 从而发现新治疗靶点。我们的研究结果可以提供有价值的 了解前列腺癌发病机制和识别基因型的信息 用于预测前列腺癌侵袭性的组合。至于长期影响， 研究结果可用于开发有效的筛查工具，以预测前列腺癌 侵略性