Developing and Automating an Extracellular Vesicle-Based Test for Early Detection of Hepatocellular Carcinoma

开发和自动化基于细胞外囊泡的测试以早期检测肝细胞癌

基本信息

批准号：
10823687
负责人：
Sean Xiao Liu
金额：
$ 66.16万
依托单位：
EXIMIUS DIAGNOSTICS CORP
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-09-14 至 2026-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10823687
关键词：
ANXA5 gene Ablation Adopted Advanced Development Affect Alcoholic Liver Diseases Algorithms Antibodies Automation Bar Codes Bioinformatics Biological Markers Biometry Blood Circulation CD81 gene Cancer Etiology Case/Control Studies Cells Cessation of life Chemistry Chronic Hepatitis B Circulation Cirrhosis Clinical Clinical Practice Guideline DNA Detection Development Diagnosis Diagnostic Diagnostic tests Disease Early Diagnosis Etiology Excision Exhibits GPC3 gene Goals Guidelines Hepatitis B Hepatitis C Hepatology Hour Individual Joints Liver Liver Cirrhosis Liver diseases Mediating Medical center Membrane Proteins Methods Modality Motivation Oncology Operative Surgical Procedures Paper Pathology Patients Performance Phase Phospholipids Plasma Primary Malignant Neoplasm of Liver Primary carcinoma of the liver cells Process Prognosis Protein Analysis Quantitative Evaluations Recommendation Research Risk Robotics Sampling Serum Site Small Business Innovation Research Grant Specificity Specimen Surface System Systems Development TACSTD1 gene Testing Time Training Tumor-Derived Ultrasonography Validation Viral hepatitis alpha-Fetoproteins arm assay development biomarker development cell type circulating biomarkers cohort detection sensitivity diagnostic value early detection biomarkers extracellular vesicles hepatocellular carcinoma cell line in-vitro diagnostics innovation lipid nanoparticle liquid biopsy liver transplantation molecular pathology nanoparticle neoplastic cell non-alcoholic fatty liver disease novel marker predictive modeling product development robotic system technology platform tumor tumor microenvironment ultrasound

项目摘要

PROJECT SUMMARY Hepatocellular carcinoma (HCC) comprises 80-85% of primary liver cancers and frequently develops in patients with liver cirrhosis or chronic hepatitis B virus infection. HCC's poor prognosis is primarily due to advanced-stage diagnosis. Current clinical practice guidelines recommend biannual liver ultrasounds, with or without serum alpha-fetoprotein (AFP) testing, for at-risk patients to detect HCC at a curable stage. However, their accuracy is limited, with sensitivity between 60-70% and specificity of 90%. Consequently, novel biomarkers for early detection of HCC are urgently needed. Extracellular vesicles (EVs) are a heterogeneous group of lipid nanoparticles that are released by all types of cells, and even more so by tumor cells. Tumor-derived EVs are present in circulation at relatively early stages of disease and are readily accessible across all disease stages. Since the surface proteins of tumor EVs mirror those of the parental tumor cells and those cells within tumor microenvironment, exploiting the diagnostic potential of HCC EVs’ surface protein signatures as a novel biomarker for early detection of HCC holds great promise to significantly augment the ability of current diagnostic modalities. Over the last five years, our joint team comprised of Eximius Dx, UCLA, and Cedars Sinai Medical Center (CSMC) has demonstrated of HCC EV Surface Protein (SP) Test, capable of dissecting and quantifying subpopulations of HCC EVs in plasma samples. In our 2022 Hepatology paper, we summarized a phase-2 biomarker study which successfully validated the feasibility of HCC EV SP Test for early HCC detection. The long-term goal of this Direct-to-Phase-II proposal is to advance the development, optimization, and automation of the HCC EV SP Test, with the ultimate goal of establishing a more sensitive in vitro diagnostic (IVD) test based on HCC EVs. The innovation of the proposed HCC EV SP Test lies in the integration of two platform technologies: (i) EV Click MagBeads for click chemistry-mediated capture of subpopulations of HCC EVs, and (ii) real-time immuno-PCR for quantifying the captured HCC EVs. In parallel, an algorithm will be established to process the resulting HCC EV signatures into HCC EV SP score for distinguishing early-stage HCC from at-risk cirrhosis. This new IVD test will use less then 1-mL plasma and have a sample-to-answer workflow of no more than 3 hours. By adopting an in-house developed robotic system, the automated workflow allows for a throughput > 480 samples per round. Once optimized and automated the HCC EV SP Test will be validated by clinically annotated plasma samples to assess its diagnostic performance for distinguishing early-stage HCC from at-risk liver cirrhotic patients, covering etiologies including alcohol-associated liver disease (ALD), non-alcoholic fatty liver disease (NAFLD), and viral hepatitis (B/C). The successful development of the proposed HCC EV SP Test is rapidly translatable, enabling a sensitive HCC EV-based IVD test for detecting early-stage HCC.

项目概要肝细胞癌 (HCC) 占原发性肝癌的 80-85%，并且经常发生在患者中患有肝硬化或慢性乙型肝炎病毒感染的HCC预后不良主要是由于晚期。目前的临床实践指南建议每年两次进行肝脏超声检查，有或没有血清。甲胎蛋白 (AFP) 检测，用于高危患者检测可治愈阶段的 HCC。有限，经测试，早期新型生物标志物的敏感性为 60-70%，特异性为 90%。迫切需要检测 HCC 细胞外囊泡 (EV) 是一组异质脂质。所有类型的细胞，尤其是肿瘤细胞释放的纳米颗粒。存在于疾病相对早期阶段的循环中，并且在所有疾病阶段都很容易获得。由于肿瘤 EV 的表面蛋白反映了亲本肿瘤细胞和肿瘤内细胞的表面蛋白微环境，利用 HCC EV 表面蛋白特征的诊断潜力作为一种新型方法用于早期检测 HCC 的生物标志物有望显着增强当前诊断的能力方式。在过去的五年里，我们的联合团队由 Eximius Dx、加州大学洛杉矶分校和 Cedars Sinai 医疗中心组成华润上华 (CSMC) 展示 HCC EV 表面蛋白 (SP) 检测，能够解剖和定量在我们的 2022 年肝病学论文中，我们总结了血浆样本中的 HCC EV 亚群。生物标志物研究成功验证了 HCC EV SP 测试用于早期 HCC 检测的可行性。该直接进入第二阶段提案的长期目标是推进开发、优化和自动化 HCC EV SP 测试的最终目标是建立一种更灵敏的体外诊断 (IVD) 测试拟议的 HCC EV SP 测试的创新在于两种平台技术的集成： (i) EV Click MagBeads 用于点击化学介导的 HCC EV 亚群捕获，以及 (ii) 实时捕获同时，将建立一种算法来处理捕获的 HCC EV。由此产生的 HCC EV 特征转化为 HCC EV SP 评分，以区分早期 HCC 和高危肝硬化。这项新的 IVD 测试将使用少于 1 mL 的血浆，并且样本到答案的工作流程不超过 3 通过采用内部开发的机器人系统，自动化工作流程可实现 > 小时的吞吐量。每轮 480 个样本一旦优化并自动化，HCC EV SP 测试将得到临床验证。带注释的血浆样本，以评估其区分早期 HCC 和高危 HCC 的诊断性能肝硬化患者，涵盖病因包括酒精相关性肝病 (ALD)、非酒精性脂肪肝肝病（NAFLD）和病毒性肝炎（B/C）拟议的 HCC EV SP 测试的成功开发。可快速翻译，从而能够进行基于 HCC EV 的灵敏 IVD 测试来检测早期 HCC。