Novel approaches to improve prediction of cancer-associated thrombosis

项目摘要 静脉血栓栓塞（VTE）是癌症患者发病和死亡的重要原因。 大约20%的癌症患者发展为VTE，10%死于VTE。然而，癌症中VTE的风险 是高度可变的。识别高风险患者对于优化血栓预防的获益非常重要，但 单独的危险因素尚未被证明是有用的VTE预测因子。一个临床评分系统， 本申请的PI（“Khorana评分”）结合了五个临床变量以将患者分为高， 中等或低风险组，并且是用于预测癌症中VTE的最广泛使用的系统。的风险 低风险组中的VTE <1%，然而高风险组中只有18%的患者发生VTE;因此， 阳性预测值较低。此外，大多数患者属于中等风险组， 需要风险预测。几种止血生物标志物，包括循环组织因子（TF）、D-二聚体和 已经评估了P-选择素预测VTE的能力，但发现其效用有限。新的和创新 因此，迫切需要生物标志物。在本申请中，我们提出了一个两阶段的研究，以确定新的 癌症相关性VTE的生物标志物。我们首先提出了一个发现阶段，以确定新的候选人 生物标志物。这包括目标1，其检查接触和补体激活的生物标志物， 目的2，检查循环血浆/外泌体microRNA谱。新数据显示 激活系统（CAS），其由FXII、前激肽释放酶和激肽原组成，并导致FXI的激活， 内源性凝血途径，病理性血栓形成;然而，CAS在癌症相关性 血栓形成（CAT）尚未研究。我们令人信服的初步数据表明了这个系统的重要性， 我们开发了一系列新的CAS活性测定方法。在目标1中，我们将前瞻性评估 这些测定在患有胰腺癌、肺癌和结肠直肠癌的三个大的患者队列中的预测价值。 补体也被CAS激活，与血液系统疾病中的血栓形成有关，我们的初步研究表明， 研究表明，C3 a和C5 a与胰腺癌的预后相关;因此，我们将进一步研究C3 a和C5 a与胰腺癌的预后相关。 也要评估这些生物标志物。在目标2中，我们将探索生物标志物研究的另一个新兴领域- 循环microRNA（miRNA）。我们假设来自最高VTE风险的癌症患者的血浆含有 特定的miRNA水平增加，或独特的miRNA谱，我们的初步研究已经确定了六个 与癌症中VTE相关的血浆miRNA。在我们提案的第二个验证阶段，目标3将 使用来自独立的700份血浆样本验证目标1和2中发现的候选生物标志物 从3项大型跨国研究中获得的癌症患者队列。我们将把这些数据合并到一个 使用风险建模策略的新VTE预测模型。我们提出的研究对RFA反应很好 HL-18-021，并将导致新的生物标志物和改进的风险分层策略，以预测和预防 癌症中的VTE。

Project Summary Venous thromboembolism (VTE) is an important cause of morbidity and mortality in patients with cancer. Approximately 20% of patients with cancer develop, and 10% die, from VTE. However, the risk of VTE in cancer is highly variable. Identifying high-risk patients is important to optimize benefit from thromboprophylaxis, but solitary risk factors have not proven to be useful VTE predictors. A clinical scoring system developed by one of the PIs of this application (“Khorana score”) combines five clinical variables to segregate patients into high, intermediate, or low risk groups, and is the most widely used system for predicting VTE in cancer. The risk of VTE in the low-risk group is < 1%, however only 18% of patients in the high-risk group develop VTE; thus, the positive predictive value is low. Moreover, most patients fall into an intermediate-risk group for which improved risk prediction is needed. Several hemostatic biomarkers, including circulating tissue factor (TF), D-dimer, and P-selectin have been assessed for their ability to predict VTE, but found to have limited utility. New and innovative biomarkers are therefore urgently needed. In this application, we propose a two-phase study to define novel biomarkers of cancer-associated VTE. We first propose a discovery phase to identify novel candidate biomarkers. This encompasses Aim 1, which examines biomarkers of contact and complement activation, and Aim 2, which examines circulating plasma/exosome microRNA profiles. Emerging data has linked the contact activation system (CAS), which consists of FXII, prekallikrein and kininogen and leads to activation of FXI and the intrinsic coagulation pathway, to pathologic thrombosis; however, the role of the CAS in cancer-associated thrombosis (CAT) has not been studied. Our compelling preliminary data indicates the importance of this system, and we have developed an array of novel assays of CAS activity. In Aim 1, we will prospectively assess the predictive value of these assays in three large cohorts of patients with pancreas, lung, and colorectal cancers. Complement is also activated by the CAS, is linked to thrombosis in hematologic disorders, and our preliminary studies demonstrate that C3a and C5a are associated with outcomes in pancreatic cancer; thus, we will further evaluate these biomarkers as well. In Aim 2, we will explore another emerging area of biomarker research- circulating microRNA (miRNA). We hypothesize that plasma from cancer patients at greatest risk of VTE contains increased levels of specific miRNAs, or unique miRNA profiles, and our preliminary studies have identified six plasma miRNAs associated with VTE in cancer. In the second, validation phase of our proposal, Aim 3 will validate candidate biomarkers discovered in Aims 1 and 2 using plasma samples from an independent 700 patient cohort of cancer patients obtained from 3 large, multinational studies. We will incorporate this data into a new VTE prediction model using risk modeling strategies. Our proposed studies are highly responsive to RFA HL-18-021, and will lead to novel biomarkers and improved risk stratification strategies to predict and prevent VTE in cancer.