Risk Stratification for and Early Detection of Liver Cancer

转化研究中心（TRC）包括一个多学科的临床和翻译团队， 研究人员，有一个强大的合作工作的跟踪记录，与集体使命，减少 HCC的负担在拟议的TRC的中心是两个独特的积极的前瞻性（在肝癌监测） 肝硬化患者的队列。其中一组来自癌症预防和研究所 （CPRIT）资助的正在进行的前瞻性多中心研究（Texas HCC Consortium）， 招募> 3000例肝硬化患者（> 12，000例监测事件和200例预期HCC病例）， 多种病因（包括治愈的HCV和非酒精性脂肪肝）。这些病人在常规治疗下 在德克萨斯州的5个医疗中心进行两年一次的监测。第二个是>700名患者的队列（> 1，300次就诊 截至2017年9月的监测事件和33例HCC事件病例）， 随后在休斯顿退伍军人管理局，大多数与治愈丙型肝炎病毒。真相与和解委员会将发挥杠杆作用，扩大后续行动， 来自两个队列的数据和样本，共同导致> 23，000次HCC监测（以及> 300例预期的HCC）与生物库标本，每次发作的临床和放射学数据，使其成为一个 为拟议的研究和其他跨财团项目提供宝贵的资源。使用这些数据 队列，我们将开发和测试新的个性化风险分层指数，以预测未来。 在不同病因的肝硬化患者中发展为HCC（目的1）。我们还将开发和 评估结合现有的基于HCC血液的生物标志物（例如，法新社，法新社L3， DCP）、它们随时间的纵向变化以及选择的宿主特征（年龄、病因学）。我们将 还检查了该算法在不同HCC风险分层患者中的性能（目标2）。我们的工作将 将其他患者和肝病相关因素纳入（新）生物标志物谱的框架， 无论生物标志物的类型如何，可能保持高度相关的区域。我们将高度评价 有希望的甲基化DNA标记物（MDM，液体活检）作为HCC风险预测的独立测试， 目标3。这些标志物已在组织病例对照1期研究中鉴定， 它们在2期研究中具有优异的HCC检测性能。我们将验证 研究队列中的个体标志物，并训练一种算法，该算法结合MDM以实现最大的 性能在3期生物标志物研究中，我们将在测试样本中整体验证算法，并在关键 基于HCC风险分层的亚组。我们的方法（优化可用标记，同时 保持强劲的前瞻性）将对HCC相关的直接和长期影响 发病率和死亡率。真相与和解委员会将利用现有的强有力的基础设施和关系， 完成拟议的研究。它也代表了一个新的和令人兴奋的途径与其他合作， U01财团的调查人员。

The Translational Research Center (TRC) includes a multidisciplinary team of clinical and translational researchers that has a strong track record of collaborative work, with the collective mission of reducing the burden of HCC. At the center of the proposed TRC lie two unique active prospective (in-HCC surveillance) cohorts of patients with cirrhosis. One of the cohorts comes from a Cancer Prevention and Research Institute of Texas (CPRIT) funded ongoing prospective multicenter study (Texas HCC Consortium) that is on target to recruit > 3000 patients with cirrhosis (>12,000 surveillance episodes and 200 expected HCC cases) from diverse etiologies (including cured HCV and non-alcoholic fatty liver disease). These patients are under routine bi-annual surveillance at 5 medical centers in Texas. The second is a cohort of >700 patients (>1,300 visits surveillance episodes and 33 incident HCC cases as of September 2017) recruited from and prospectively followed at the Houston VA, most with cured HCV. The TRC will leverage, extend follow up, and harmonize data and samples from both cohorts, collectively resulting in a > 23,000 episodes of HCC surveillance (and > 300 expected HCC) with bio-banked specimens, clinical and radiological data for each episode, rendering it an invaluable resource for the proposed research and other trans-consortium projects. Using data from these cohorts, we will develop and test novel personalized risk stratification indices for predicting the future ‐ development to HCC in patients with cirrhosis across diverse etiologies (Aim 1). We will also develop and evaluate an early detection algorithm that combines existing HCC blood based biomarkers (e.g., AFP, AFP L3, DCP), their longitudinal changes over time and select host features (age, etiology) in a phase 3 study. We will also examine the performance of this algorithm in patients at different HCC risk strata (Aim 2). Our work will set the framework for incorporating other patient and liver disease related factors into (new) biomarker profiles, an area that is likely to remain highly relevant irrespective of the type of biomarker. We will evaluate highly promising methylated DNA markers (MDMs, liquid biopsy) as an independent test for HCC risk prediction in Aim 3. These markers have been identified in tissue case control phase 1 studies, reliable assays have been developed and they have excellent performance for HCC detection in phase 2 studies. We will validate individual markers in the study cohort and train an algorithm that combines the MDM to achieve maximum performance. In a phase 3 biomarker study, we will validate the algorithm in the test sample overall and in key subgroups based on HCC risk strata. Our approach (optimizing available markers while simultaneously maintaining a strong forward outlook) will have both an immediate and long-lasting impact on HCC related morbidity and mortality. The TRC will build on established and strong infra-structure and relationships to complete the proposed research. It also represents a new and exciting avenue for collaboration with other investigators within the U01 consortium.