Nanoparticle-Powered Chemiluminescent Lateral Flow Biosensor Array for Early Diagnosis of Pancreatic Cancer

_______________________________________________________________________________________ 项目-1。纳米粒子驱动的化学发光侧向流生物传感器阵列用于早期 胰腺癌的诊断（主要研究者：刘国栋医生） 项目摘要 胰腺癌（Pancreatic cancer，PC）是一种预后最差的恶性肿瘤。由于缺乏 早期症状和适当的方法来检测胰腺癌的早期阶段，以及其 由于疾病进展迅速，当确诊时，这种疾病往往已经相当晚期了。的 5-所有阶段的年相对存活率约为6%。因此，早期发现PC， 分期切除是降低死亡率、提高生存率的关键。这个研究项目的目标是 探索一种快速、简便、敏感的早期诊断前列腺癌的方法。我们的初步结果， 侧向流核酸生物传感器、定量免疫层析条生物传感器以及集成的 核酸和蛋白质生物传感器为所考虑的方法提供了概念验证。我们 假设用纳米颗粒动力 荧光侧向流生物传感器阵列将为前列腺癌的早期诊断提供一种简单、快速的工具 具有改进的特异性。miR-196 a（据报道是PC诊断的潜在miRNA生物标志物）和CA 19-9（一种获批的预后和PC病程后的生物标志物）将用作模型靶点， 优化实验条件。该方法最初将开发一种超灵敏的NCLFB， 碱性磷酸酶（ALP）/DNA（或ALP/抗体）功能化的二氧化硅纳米颗粒（Si-NP）探针， 检测血浆中的miR-196 a（不进行聚合酶链反应（PCR）扩增）和CA 19-9， 随后开发一种集成的荧光生物传感器，用于同时检测 miR-196 a和CA 19-9在单个平台中。最后，将制作NCLFB阵列并用于检测 miRNA组（miR-16、miR-196 a和miR-210）和蛋白质生物标志物组（CA 19-9、ICAM-1和 生物传感器阵列将用来自PC患者和对照组（健康人）的血浆样品进行测试。 供者、肝病患者以及胰腺炎、胰腺囊肿和其他癌症[乳腺癌、结肠癌和肺癌] 患者），并将采用qRT-PCR和酶联免疫吸附试验验证结果。 该项目的长期目标是开发一种简单快速的PC早期诊断工具。该项目提供 北达科他州州立大学的COBRE中心的一个翻译组件。这个平台有潜力 扩展到检测其他生物标志物，监测对治疗的反应，并提供实时 PC患者的预后信息。 _______________________________________________________________________________________

_______________________________________________________________________________________ Project-1. Nanoparticle-Powered Chemiluminescent Lateral-Flow Biosensor Array for the Early Diagnosis of Pancreatic Cancer (PI: Dr. Guodong Liu) Project Summary Pancreatic Cancer (PC) is a lethal disease with the worst prognosis of all the major malignancies. Due to the lack of early symptoms and appropriate methods to detect pancreatic carcinoma at an early stage as well as its aggressive progression, the disease is often quite advanced by the time a definite diagnosis is established. The 5-year relative survival rate for all stages is approximately 6%. Therefore, detection of PC at an early, surgically resectable stage is the key to decrease mortality and to improve survival. The goal of this research project is to explore a fast, simple and sensitive approach for the early diagnosis of PC. Our preliminary results for the lateral-flow nucleic acid biosensors, quantitative immunochromatographic strip biosensors, and the integrated nucleic-acid and protein biosensors provide the proof-of-concept for the contemplated methodology. We hypothesize that simultaneous detection of miRNAs and protein biomarkers with a nanoparticle-powered chemiluminescent lateral-flow biosensor (NCLFB) array will offer a simple and fast tool for early PC diagnosis with improved specificity. The miR-196a (reported to be a potential miRNA biomarker for a PC diagnosis) and CA 19-9 (an approved biomarker for prognosis and following the course of PC) will be used as model targets to optimize the experimental conditions. The approach will initially develop an ultrasensitive NCLFB based on alkaline phosphatase (ALP)/DNA (or ALP/antibody)-functionalized silica nanoparticle (Si-NP) probes for detecting miR-196a (without polymerase chain reaction (PCR) amplification) and CA 19-9 in plasma, respectively; and subsequently develop an integrated chemiluminescent biosensor for simultaneous detection of miR-196a and CA 19-9 in a single platform. Finally, the NCLFB array will be fabricated and used for the detection of a miRNA panel (miR-16, miR-196a, and miR-210) and protein biomarker panel (CA 19-9, ICAM-1, and OPG).The biosensor array will be tested with plasma samples from PC patients and control groups (healthy donors, liver-disease patients, as well as pancreatitis, pancreatic-cyst, and other cancer [breast, colon, and lung] patients), and the results will be validated with qRT-PCR and enzyme-linked immunosorbent assay. The long-term goal of this project is to develop a simple and fast tool for PC early diagnosis. The project provides a translational component to the COBRE center at North Dakota State University. This platform has the potential to be extended for detecting other biomarkers, monitoring the response to therapy, and providing real-time prognostic information for PC patients. _______________________________________________________________________________________