{"title":"氧化石墨烯夹心结构铬粒蛋白A的电化学信号关闭竞争免疫分析用于神经内分泌肿瘤检测","authors":"Supakeit Chanarsa, Patrawadee Yaiwong, Siriporn Anuthum, Kullapa Chanawanno, Jaroon Jakmunee and Kontad Ounnunkad*, ","doi":"10.1021/acsmeasuresciau.5c0004810.1021/acsmeasuresciau.5c00048","DOIUrl":null,"url":null,"abstract":"<p >Neuroendocrine tumors (NETs), often misdiagnosed and mistreated, require early detection for precise therapeutic interventions. This study presents a newly developed competitive electrochemical immunosensor for sensitive and selective detection of chromogranin A (CgA), a key biomarker for diagnosing and monitoring NETs. The sensor, featuring a sandwiched structure with versatile and multifunctional graphene oxide (GO), utilizes polyethylenimine-capped gold nanoparticles (PEI-AuNPs) to enhance the electroreactivity and biocompatibility of a screen-printed electrode (SPE). The immunosensor operates by immobilizing standard CgA antigens on the PEI-AuNPs/GO-modified SPE surface and employing GO nanotags loaded with anti-CgA antibodies (Ab) and ferrocene monocarboxylic acid (Fc) redox probes to capture target CgA. As the CgA concentration increases, the current response of the immunosensor decreases due to a reduction in the amount of Fc/Ab/GO tags on the electrode surface. This reduction occurs because the nanotags bind to the free CgA in the sample rather than the CgA immobilized on the electrode. The immunosensor demonstrates a good linearity (0.10–50 ng mL<sup>–1</sup>), a low detection limit of 90 pg mL<sup>–1</sup>, and high accuracy in detecting CgA levels in human serum samples. With its high specificity, long-term stability, and excellent reproducibility, our cost-effective and user-friendly platform holds promise for clinical screening and point-of-care diagnosis of NETs. Further optimization of the immunosensor’s design and exploration of its use for additional biomarkers could enhance NETs’ diagnosis and provide advancements in managing other related health conditions.</p>","PeriodicalId":29800,"journal":{"name":"ACS Measurement Science Au","volume":"5 3","pages":"388–396 388–396"},"PeriodicalIF":4.6000,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsmeasuresciau.5c00048","citationCount":"0","resultStr":"{\"title\":\"Electrochemical Signal-Off Competitive Immunoassay of Chromogranin A toward a Sandwiched Graphene Oxide Structure for Neuroendocrine Tumor Detection\",\"authors\":\"Supakeit Chanarsa, Patrawadee Yaiwong, Siriporn Anuthum, Kullapa Chanawanno, Jaroon Jakmunee and Kontad Ounnunkad*, \",\"doi\":\"10.1021/acsmeasuresciau.5c0004810.1021/acsmeasuresciau.5c00048\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >Neuroendocrine tumors (NETs), often misdiagnosed and mistreated, require early detection for precise therapeutic interventions. 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引用次数: 0
摘要
神经内分泌肿瘤(NETs)经常被误诊和误治,需要早期发现以进行精确的治疗干预。本研究提出了一种新开发的竞争性电化学免疫传感器,用于敏感和选择性检测嗜铬粒蛋白a (CgA),这是诊断和监测NETs的关键生物标志物。该传感器采用多功能氧化石墨烯(GO)夹层结构,利用聚乙烯亚胺包覆的金纳米颗粒(PEI-AuNPs)来增强丝网印刷电极(SPE)的电反应性和生物相容性。该免疫传感器的工作原理是将标准CgA抗原固定在PEI-AuNPs/GO修饰的SPE表面,并使用负载抗CgA抗体(Ab)和二茂铁单羧酸(Fc)氧化还原探针的GO纳米标签来捕获目标CgA。随着CgA浓度的增加,由于电极表面Fc/Ab/GO标签数量的减少,免疫传感器的电流响应降低。这种还原发生是因为纳米标签结合到样品中的游离CgA而不是固定在电极上的CgA。该免疫传感器具有良好的线性关系(0.10 ~ 50 ng mL-1),低检出限(90 pg mL-1),检测人血清样品中CgA水平的准确性高。该平台具有高特异性、长期稳定性和良好的可重复性,具有成本效益和用户友好性,有望用于NETs的临床筛查和即时诊断。进一步优化免疫传感器的设计并探索其用于其他生物标志物的用途,可以增强NETs的诊断,并在管理其他相关健康状况方面取得进展。
Electrochemical Signal-Off Competitive Immunoassay of Chromogranin A toward a Sandwiched Graphene Oxide Structure for Neuroendocrine Tumor Detection
Neuroendocrine tumors (NETs), often misdiagnosed and mistreated, require early detection for precise therapeutic interventions. This study presents a newly developed competitive electrochemical immunosensor for sensitive and selective detection of chromogranin A (CgA), a key biomarker for diagnosing and monitoring NETs. The sensor, featuring a sandwiched structure with versatile and multifunctional graphene oxide (GO), utilizes polyethylenimine-capped gold nanoparticles (PEI-AuNPs) to enhance the electroreactivity and biocompatibility of a screen-printed electrode (SPE). The immunosensor operates by immobilizing standard CgA antigens on the PEI-AuNPs/GO-modified SPE surface and employing GO nanotags loaded with anti-CgA antibodies (Ab) and ferrocene monocarboxylic acid (Fc) redox probes to capture target CgA. As the CgA concentration increases, the current response of the immunosensor decreases due to a reduction in the amount of Fc/Ab/GO tags on the electrode surface. This reduction occurs because the nanotags bind to the free CgA in the sample rather than the CgA immobilized on the electrode. The immunosensor demonstrates a good linearity (0.10–50 ng mL–1), a low detection limit of 90 pg mL–1, and high accuracy in detecting CgA levels in human serum samples. With its high specificity, long-term stability, and excellent reproducibility, our cost-effective and user-friendly platform holds promise for clinical screening and point-of-care diagnosis of NETs. Further optimization of the immunosensor’s design and exploration of its use for additional biomarkers could enhance NETs’ diagnosis and provide advancements in managing other related health conditions.
期刊介绍:
ACS Measurement Science Au is an open access journal that publishes experimental computational or theoretical research in all areas of chemical measurement science. Short letters comprehensive articles reviews and perspectives are welcome on topics that report on any phase of analytical operations including sampling measurement and data analysis. This includes:Chemical Reactions and SelectivityChemometrics and Data ProcessingElectrochemistryElemental and Molecular CharacterizationImagingInstrumentationMass SpectrometryMicroscale and Nanoscale systemsOmics (Genomics Proteomics Metabonomics Metabolomics and Bioinformatics)Sensors and Sensing (Biosensors Chemical Sensors Gas Sensors Intracellular Sensors Single-Molecule Sensors Cell Chips Arrays Microfluidic Devices)SeparationsSpectroscopySurface analysisPapers dealing with established methods need to offer a significantly improved original application of the method.