Improving prostate cancer screening by integration of SNPs with blood biomarkers

通过 SNP 与血液生物标志物的整合改善前列腺癌筛查

• 批准号: 8969796
• 负责人: ROBERT J. KLEIN
• 金额: $ 61.44万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-03-01 至 2018-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8969796
• 关键词: Accounting; Achievement; Biological Markers; Biopsy; Blood; Clinical; Clinical Research; Data; Development; Disease; Early Diagnosis; Environment; Ethnic Origin; Evaluation; Genetic; Genetic Variation; Genotype; Goals; Grant; Health; Human; Individual; Indolent; Knowledge; Light; Malignant Neoplasms; Malignant neoplasm of prostate; Measurement; Medical; Memorial Sloan-Kettering Cancer Center; Methods; Modeling; Mutation; Nested Case-Control Study; Outcomes Research; Performance; Phenotype; Population; Population Heterogeneity; Procedures; Production; Prostate; Prostate-Specific Antigen; Protein Isoforms; Proteins; Research Project Grants; Risk; Screening for Prostate Cancer; Seminal fluid; Sensitivity and Specificity; Single Nucleotide Polymorphism; Specificity; Statistical Models; Sweden; Testing; Twin Multiple Birth; Work; adverse outcome; anticancer research; base; cancer risk; case control; clinically significant; cohort; design; experience; genetic epidemiology; genetic information; genetic makeup; improved; innovation; men; mortality; older men; predictive modeling; prostate biopsy; screening; tool; young man

DESCRIPTION (provided by applicant): Each year, over 1,000,000 needless prostate biopsies are performed on men who present with elevated levels of prostate specific antigen (PSA) but show no evidence of cancer upon biopsy. Whether one believes that widespread PSA testing leads to overtreatment of indolent cancer or is an important tool to reduce prostate cancer mortality, screening for prostate cancer is unlikely to go away and it is clear that reducin these false positive findings will greatly reduce unnecessary medical procedures and their attendant adverse consequences. The long-term goal of this research project is to develop improved screening tests that will identify men at risk for prostate cancer, especially potentially lethal disease, with high sensitivity and specificity. The overall objective of this application isto determine if consideration of an individual's genetic makeup can improve the accuracy of screening tests based on PSA and other prostate-produced biomarkers. The central hypothesis underlying this application is that consideration of SNPs that are associated with levels of prostate cancer biomarkers and their interaction in predictive models will improve model performance. The rationale behind this project is that if SNPs do influence biomarker levels independent of disease status, then personalized biomarker evaluation that takes into account SNP genotype is necessary to maximize accuracy of the test. This approach to prostate cancer screening will be developed by: 1) Identifying SNPs associated with levels of PSA and other biomarkers in men without prostate cancer. A panel of SNPs previously associated with prostate cancer risk and/or levels of prostate secreted biomarkers will be tested for association with a panel of five isoforms of prostate secreted proteins in healthy young men and healthy older men. 2) Determining the ability of SNPs to improve accuracy of PSA-based predictive models. Using a nested case- control study, those SNPs associated with biomarker levels in aim 1 will be included, along with their interaction with biomarker levels, in a predictive model for prostate cancer. 3) Determining the generalizability of such models in diverse populations. The best model from aim 2 will be externally validated in three separate studies from the US and Sweden representing a variety of ethnicities and both nested case-control designs and a biopsy cohort. This proposal is innovative because it investigates the association of SNPs with levels of prostate biomarkers in healthy young men who can be presumed to be cancer-free; because it suggests interpretation of biomarkers in light of SNP genotype rather than simply combining biomarker and SNP information; and because it is not restricted to a population with a single ancestry. The expected outcome of this research is a predictive model for prostate cancer that integrates genetic variation with prostate secreted protein biomarkers. The positive impact of such a model will be the reduction of unnecessary biopsies while still facilitating the early detection of prostate cancer.

描述(申请人提供)：每年，超过1,000,000例不必要的前列腺活检被接受，这些患者的前列腺特异性抗原(PSA)水平升高，但活组织检查显示没有癌症的证据。无论人们认为广泛的PSA检测会导致惰性癌症的过度治疗，还是降低前列腺癌死亡率的重要工具，前列腺癌筛查都不太可能消失，显然，减少这些假阳性结果将大大减少不必要的医疗程序及其随之而来的不良后果。这项研究项目的长期目标是开发改进的筛查测试，以确定男性患前列腺癌的风险，特别是潜在的 致命性疾病，具有高度的敏感性和特异性。这项应用的总体目标是确定考虑个体的基因构成是否可以提高基于PSA和其他前列腺产生的生物标记物的筛查测试的准确性。支持这一应用的中心假设是，考虑与前列腺癌生物标记物水平相关的SNPs及其在预测模型中的相互作用将改善模型的性能。该项目背后的基本原理是，如果SNP确实影响独立于疾病状态的生物标记物水平，那么考虑SNP基因的个性化生物标记物评估对于最大限度地提高检测的准确性是必要的。这种前列腺癌筛查方法将通过：1)确定与非前列腺癌男性的PSA和其他生物标记物水平相关的SNPs。一组先前与前列腺癌风险和/或前列腺癌分泌生物标志物水平相关的SNPs将在健康年轻男性和健康老年男性中进行测试，以确定其与五种前列腺癌分泌蛋白亚型的相关性。2)确定SNPs对提高基于PSA的预测模型精度的能力。使用嵌套病例对照研究，那些与AIM 1中生物标记物水平相关的SNP及其与生物标记物水平的相互作用将被包括在前列腺癌的预测模型中 癌症。3)确定这些模型在不同群体中的泛化能力。来自AIM 2的最佳模型将在来自美国和瑞典的三项独立研究中进行外部验证，这三项研究分别代表了不同的种族，以及嵌套病例对照设计和活检队列。这一建议是创新的，因为它调查了SNPs与可以推定为无癌症的健康年轻男性前列腺生物标记物水平的关联；因为它建议根据SNP基因而不是简单地结合生物标记物和SNP信息来解释生物标记物；因为它并不局限于具有单一祖先的人群。这项研究的预期结果是一个前列腺癌的预测模型，它将遗传变异与前列腺分泌蛋白生物标记物结合在一起。这种模式的积极影响将是减少不必要的活检，同时仍有助于前列腺癌的早期发现。