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，主要是由于大多数病例是在胰腺癌中发生的。 在晚期无法治愈的阶段被确诊虽然转移性PDAC的5年生存率<5%，但结局 显著改善局部PDAC。预后差是由于缺乏诊断PDAC的生物标志物， 可能治愈的早期无症状阶段。早期PDAC的有效诊断取决于 识别准确的非侵入性生物标志物，并结合筛查风险增加的策略 人口。我们的主要目标是确定血清、尿液和外泌体中的非侵入性蛋白质生物标志物 准确区分有和没有早期可切除PDAC的患者， 治疗性手术新的诊断方法也将提高PDAC和良性胰腺癌之间的区分 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志物- 用于筛查（高危人群）和PDAC鉴别诊断的基础测试。我们的核心假设是， 尿、血清和外来体来源的生物标志物的组合可以是协同的，提供上级生物标志物。 分类能力我们使用了来自回顾性和前瞻性队列研究的尿液和血清样本 鉴定一系列强候选组合多标记算法用于早期检测和诊断 PDAC。在目标1中，我们将优化PDAC鉴别诊断算法的性能，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（PAGER）研究。在目标2中，我们将优化早期检测算法的性能， 可切除的PDAC在三个前瞻性收集的队列的诊断前样本，并验证优化的 来自南方社区队列研究（SCCS）的设盲平行血清/尿液样本中的EDA。如果成功， 我们的项目将产生新的，有效的算法，用于风险评估和早期检测， PDAC的诊断这些算法结合在一起，将产生一个新的开拓性的筛选范式， PDAC允许及时采取挽救生命的干预措施。我们强大的初步数据，强大的协同作用 研究团队，以及来自独特前瞻性队列的平行尿液和血清样本的可用性 有助于成功完成拟议研究的高概率。

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.