Longitudinal Proteomic and Metabolomic Predictors of Pancreatic Cyst Malignant Progression and Early Stage Pancreatic Cancer

项目摘要/摘要 胰腺导管腺癌(PDAC)的预后很差，主要是由于其诊断较晚。这是至关重要的 识别早期的PDAC及其前体。其中一个先兆是导管内乳头状黏液性肿瘤。 (IPMN)，胰腺囊肿的一种。国际共识指南建议高位IPMN切除 无手术指征的IPMN的恶性风险和监测。根据放射学/临床表现， 指南在区分良性和恶性IPMN方面有令人沮丧的特异性，而且准确性很差 预测IPMN恶性进展。迫切需要寻找预测肿瘤恶性进展的生物标志物。 推定为“低风险”的IPMN。拟议研究的主要目标是识别和验证蛋白质和 代谢物特征及其纵向变化可区分IPMN恶性进展和 检测早期PDAC。在初步数据的支持下，我们的中心假设是， 这些信号在血浆和/或胰腺囊液中的轨迹预示着IPMN的恶性 进展期和早期PDAC。具体目标：1.调查血浆和囊液的水平和轨迹 蛋白质组生物标志物和代谢组学标志在预测IPMN恶性进展中的作用 未来的监控队列。胰腺囊液的蛋白质组学和代谢组学研究 将对160名IPMN手术患者进行检查，以确定与高级别 和侵袭性IPMN。1B：从1A和6个蛋白(THBS2、PGE2、LRG1、TIMP1、C1RL、& 在我们的初步研究中发现的PTPRJ)将在连续血浆(n=3)和囊液(n=~2.5)中测量。 监测的500例IPMN患者的样本。1C：从1A和4血浆中鉴定出的顶级代谢物 在我们的R21研究中，与IPMN不典型增生级别相关的代谢物将在1B人群中进行量化。这个 将根据IPMN评估在1B和1C中测量的蛋白质和代谢物的水平和轨迹 恶性进展。1D：将从蛋白质中构建IPMN恶性进展的风险预测模型 以及在1B和1C、CA19-9和临床/影像特征中鉴定和验证的代谢物。2.评估 血浆蛋白质组生物标记物和代谢组学标志物的水平和轨迹用于检测早期... 在PLCO队列中嵌套的符合探针的病例对照研究中分期PDAC。2A：在1A中确定的蛋白质 1B中列出的6个生物标记物将在242个连续的诊断前血浆样本(n=3)中进行测量 PDAC案例(包括早期病例80例)和对照242例。2B：在2A人群中，顶级代谢物 在我们的飞行员中，从1A、1C中描述的4种代谢物和预测早期PDAC的5种代谢物中鉴定出 研究将会确定。2C：将从蛋白质开发早期PDAC风险预测模型 以及在2A和2B中鉴定的代谢物，CA19-9，以及临床/影像特征。我们的预期结果将允许 临床医生在进展为浸润性癌症之前及时切除具有高恶性潜力的IPMN，同时 避免不必要的手术。早期发现PDAC将大大提高患者的存活率。

Project Summary/Abstract Pancreatic ductal adenocarcinoma (PDAC) has a dire prognosis mainly due to its late diagnosis. It is vital to identify early-stage PDAC and its precursors. One such precursor is intraductal papillary mucinous neoplasm (IPMN), a type of pancreatic cyst. International consensus guidelines recommend resection of IPMN with high malignancy risk and surveillance of IPMN without surgical indications. Based on radiologic/clinical findings, the guidelines have a dismal specificity for discerning benign from malignant IPMN and a poor accuracy of predicting IPMN malignant progression. It is urgent to identify biomarkers that predict malignant progression of presumed “low-risk” IPMN. The primary objective of the proposed study is to identify and validate protein and metabolite signatures and their longitudinal changes which can discriminate IPMN malignant progression and detect early-stage PDAC. Supported by preliminary data, our central hypothesis is that the levels and trajectories of such signatures in plasma and/or pancreatic cyst fluid are predictive of IPMN malignant progression and early-stage PDAC. Specific Aims: 1. Investigate plasma and cyst fluid levels and trajectories of proteomic biomarkers and metabolomics signatures for prediction of IPMN malignant progression in a prospective surveillance cohort. 1A: A global proteomics and metabolomics study of pancreatic cyst fluid in 160 IPMN surgical patients will be conducted to identify proteins and metabolites associated with high-grade and invasive IPMN. 1B: Top proteins identified from 1A and 6 proteins (THBS2, PGE2, LRG1, TIMP1, C1RL, & PTPRJ) discovered in our preliminary studies will be measured in serial plasma (n=3) and cyst fluid (n=~2.5) samples from 500 IPMN patients under surveillance. 1C: Top metabolites identified from 1A and 4 plasma metabolites correlated with IPMN dysplasia grade in our R21 study will be quantified in the 1B population. The levels and trajectories of proteins and metabolites measured in 1B and 1C will be evaluated in relation to IPMN malignant progression. 1D: A risk prediction model for IPMN malignant progression will be built from proteins and metabolites identified and validated in 1B and 1C, CA 19-9, and clinical/imaging features. 2. Evaluate levels and trajectories of plasma proteomic biomarkers and metabolomics signatures for detection of early- stage PDAC in a PRoBE-compliant case-control study nested in the PLCO cohort. 2A: proteins identified in 1A and 6 biomarkers listed in 1B will be measured in serial prediagnostic plasma samples (n=up to 3) from 242 PDAC cases (incl. 80 early-stage cases) and 242 matched controls. 2B: In the 2A population, top metabolites identified from 1A, 4 metabolites described in 1C, and 5 metabolites predicting early-stage PDAC in our pilot studies will be determined. 2C: A risk prediction model for early-stage PDAC will be developed from proteins and metabolites identified in 2A and 2B, CA 19-9, and clinical/imaging features. Our expected results will allow clinicians to timely resect IPMNs with high malignant potential before progression to invasive cancer, while avoiding unnecessary surgeries. Detecting early-stage PDAC will substantially increase patient survival.