Urine and serum biomarkers for early diagnosis and risk assessment of pancreatic cancer

摘要 胰腺导管腺癌(PDAC)是最致命的癌症之一，主要原因是大多数病例 确诊为晚期，不治之症。虽然转移性PDAC的5年生存率为5%，但预后 显著改进了本地化PDAC。预后不良是由于缺乏诊断PDAC的生物标志物。 无症状的早期阶段，有可能治愈。早期PDAC的有效诊断有赖于 识别准确的非侵入性生物标记物，并结合筛查风险增加的策略 人口。我们的主要目标是识别血清、尿液和外切体中的非侵入性蛋白质生物标记物。 准确区分患有和不患有早期可切除PDAC的患者 治愈性手术。新的诊断方法也将改善对PDAC和良性胰腺疾病的区分 病理学。拟议研究的目标是开发临床可翻译的非侵入性生物标记物- 基于筛查(在高危人群中)和PDAC鉴别诊断的测试。我们的中心假设是 尿液、血清和外切体衍生的生物标志物的组合可能是协同作用的，提供了更好的 分类权。我们使用了回顾和前瞻性队列研究中的尿样和血清样本。 确定一系列用于早期检测和诊断的强候选组合多标记算法 PDAC。在目标1中，我们将优化PDAC差异诊断算法的性能，并将验证 胰腺癌基因临床诊断前采集样本的优化算法 环境风险(寻呼机)研究。在目标2中，我们将优化早期检测算法的性能 从三个前瞻性队列中收集的诊断前样本中可切除的PDAC，并验证优化的 来自南方社区队列研究(SCCS)的盲法平行血清/尿样中的EDA。如果成功， 我们的项目将产生新的、经过验证的风险评估和早期检测以及差异化算法 PDAC的诊断。这些算法结合在一起，将产生一种新的开创性的筛选范例 PDAC允许及时的救生干预。我们强大的前期数据，强大的协同性 调查小组，以及来自独特预期队列的平行尿样和血清样本的可用性 有助于成功完成拟议研究的可能性很高。

ABSTRACT Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers, primarily due to most cases being diagnosed at an advanced, incurable stage. While 5-year survival of metastatic PDAC is <5%, outcomes dramatically improve for localized PDAC. Poor prognosis is due to a lack of biomarkers for diagnosing PDAC at an early, asymptomatic stage when cure is possible. Effective diagnosis of early stage PDAC depends on identification of accurate, non-invasive biomarkers in combination with a strategy for screening increased risk populations. Our primary objective is to identify non-invasive protein biomarkers in serum, urine, and exosomes that accurately distinguish between patients with and without early stage resectable PDAC that is amenable to curative surgery. Novel diagnostics would also improve discrimination between PDAC and benign pancreatic pathologies. The goal of the proposed research is to develop clinically translatable noninvasive biomarkers- based tests for screening (in high risk groups) and differential diagnosis of PDAC. Our central hypothesis is that combinations of urinary, serum, and exosome derived biomarkers could be synergistic offering a superior classification power. We have used urine and serum samples from retrospective and prospective cohort studies to identify a range of strong candidate combinatorial multimarker algorithms for early detection and diagnosis of PDAC. In Aim 1, we will optimize the performance of a PDAC differential diagnosis algorithm and will validate the optimized algorithm in samples collected prior to clinical diagnosis in the Pancreatic Adenocarcinoma Gene Environment Risk (PAGER) study. In Aim 2, we will optimize the performance of an early detection algorithm for resectable PDAC in pre-diagnostic samples from three prospectively collected cohorts and validate the optimized EDA in blinded parallel serum/urine samples from the Southern Community Cohort Study (SCCS). If successful, our project will yield novel, validated algorithms for risk assessment and early detection and for differential diagnosis of PDAC. These algorithms when combined will result in a new pioneering screening paradigm for PDAC allowing for timely live-saving interventions. Our strong preliminary data, powerful and synergistic investigative team, and the availability of parallel urine and serum samples from unique prospective cohorts contribute to the high probability of successful accomplishing the proposed studies.