Khelifa Leena, Hu Yubing, Tall Jennifer, Khelifa Rasha, Ali Amina, Poon Evon, Khelifa Mohamed Zaki, Yang Guowei, Jones Catarina, Moreddu Rosalia, Jiang Nan, Tasoglu Savas, Chesler Louis, Yetisen Ali K
Department of Chemical Engineering, Imperial College London, South Kensington, London, SW7 2BU, UK.
Division of Clinical Studies, The Institute of Cancer Research, London, SM2 5NG, UK.
Lab Chip. 2025 Jul 14. doi: 10.1039/d4lc00005f.
Neuroblastoma is an aggressive childhood cancer characterised by high relapse rates and heterogenicity. Current medical diagnostic methods involve an array of techniques, from blood tests to tumour biopsies. This process is associated with long-term physical and psychological trauma. Moreover, current technologies do not identify neuroblastoma at an early stage while tumours are easily resectable. In recent decades, many advancements have been made for neuroblastoma diagnosis, including liquid biopsy platforms, radiomics, artificial intelligence (AI) integration and biosensor technologies. These innovations support the trend towards rapid, non-invasive and cost-effective diagnostic methods which can be utilised for accurate risk stratification. Point-of-care (POC) diagnostic devices enable rapid and accurate detection of disease biomarkers and can be performed at the location of the patient. Whilst POC diagnostics has been well-researched within the oncological landscape, few devices have been reported for neuroblastoma, and these remain in the early research phase and as such are limited by lack of clinical validation. Recent research has revealed several potential biomarkers which have great translational potential for POC diagnosis, including proteomic, metabolic and epigenetic markers such as amplification and microRNAs (miRNAs). Using POC devices to detect high-risk biomarkers in biofluids such as blood and urine, offers a non-invasive approach to diagnosis of neuroblastoma, enabling early screening at a population level as well as real-time health monitoring at home. This is critical to mitigating long-term morbidity associated with late diagnosis and unnecessary treatment, in turn improving outcomes for neuroblastoma patients.
神经母细胞瘤是一种侵袭性儿童癌症，其特征为高复发率和异质性。当前的医学诊断方法涉及一系列技术，从血液检测到肿瘤活检。这个过程会带来长期的身体和心理创伤。此外，当前技术无法在肿瘤易于切除的早期阶段识别神经母细胞瘤。近几十年来，神经母细胞瘤诊断取得了许多进展，包括液体活检平台、放射组学、人工智能（AI）整合和生物传感器技术。这些创新支持了朝着快速、非侵入性和具有成本效益的诊断方法发展的趋势，这些方法可用于准确的风险分层。即时检测（POC）诊断设备能够快速准确地检测疾病生物标志物，并且可以在患者所在地进行检测。虽然POC诊断在肿瘤学领域已经得到了充分研究，但针对神经母细胞瘤的设备报道较少，并且这些设备仍处于早期研究阶段，因此受到缺乏临床验证的限制。最近的研究揭示了几种具有很大POC诊断转化潜力的潜在生物标志物，包括蛋白质组学、代谢和表观遗传标志物，如扩增和微小RNA（miRNA）。使用POC设备检测血液和尿液等生物流体中的高危生物标志物，为神经母细胞瘤的诊断提供了一种非侵入性方法，能够在人群水平上进行早期筛查，并在家中进行实时健康监测。这对于减轻与晚期诊断和不必要治疗相关的长期发病率至关重要，进而改善神经母细胞瘤患者的治疗效果。
