Diagnostic technologies for neuroblastoma

Abstract

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 MYCN 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.

Fig. 1. Overview of the current clinical pathway for neuroblastoma diagnosis. Patients often present with non-specific symptoms such as abdominal pain, hypertension, weight loss, or Hutchinson syndrome. Initial diagnostic steps include blood and urine tests (e.g., VMA/HVA levels), followed by imaging techniques such as ultrasound, CT, MRI, 18F-FDG PET, and MIBG scintigraphy. Confirmation requires invasive tissue or bone marrow biopsy and immunohistochemical analysis. The diagnostic timeline spans from hours to several days, with increasing costs, invasiveness, and patient anxiety along the pathway.

Fig. 2. Recent advances in neuroblastoma diagnostics. (a) Nuclear imaging using radiolabelled MIBG enables targeted visualization of neuroblastoma via the norepinephrine transporter. (b) AI-assisted radiomics applied to MRI/CT allows risk stratification of patients based on extracted imaging features. (c) Flow cytometry identifies and quantifies cancerous cells within heterogeneous populations to detect early biomarkers. (d) Liquid biopsy captures circulating biomarkers (EVs, cfDNA, miRNAs, CTCs) for non-invasive risk and stage assessment. (e) POCUS offers real-time, bedside imaging to support rapid clinical decision-making. (f) Immunosensors and electrochemical biosensors detect analytes through colorimetric or electrical signals, enabling sensitive multiplexed diagnostics.

Fig. 3. Schematic of a general LFA device and examples of application. (a) Schematic of a colorimetric LFA enhanced by platinum-group metal (PGM) nanoparticles with peroxidase-like activity. The PGM NPs are functionalised with antibodies to form detection probes that bind target analytes, enabling sensitive signal amplification at the test line via catalytic colour development after a post-treatment step. Reproduced from ref. with permission from Demetrios A. Spandidos Ed. & Pub., copyright 2017. (b) MARQ-LFIA platform for SARS-CoV-2 detection. Nasal swab samples are applied to a lateral flow strip functionalised with a multiple aptamer recognition-based quantum dot fluorescent probe (ApMQS). Multiple aptamers target distinct epitopes on the viral N protein, enhancing sensitivity. A portable fluorescence reader captures test and control line intensities within 30 seconds, enabling rapid and highly sensitive point-of-care diagnosis. Reproduced from ref. with permission from Royal Society of Chemistry, copyright 2025. (c) Coloured dCNPs@P-Ab used in competitive and sandwich-format multiplex lateral flow assays (mLFAs). In the competitive format (left), increasing analyte concentration reduces the test line signal, while in the sandwich format (right), signal intensity correlates with target concentration. Distinct colors enable visual differentiation of multiple targets at separate test lines. Reproduced from ref. with permission from ACS Publications, copyright 2025.

Fig. 4. Point-of-care diagnostic devices. (a) Schematic of a lab-on-a-chip (LoC) device utilizing capillary-driven flow through microfluidic channels. Detection zones support both optical and electrochemical readouts for versatile biomarker quantification. (b) Graphene-based lab-on-a-chip (G-LOC) platform for multiplexed, non-invasive detection of kidney function biomarkers (e.g., Na⁺, K⁺, urea) in saliva. Graphene sensors are functionalised with ionophores and enzymatic interfaces, enabling real-time monitoring via a mobile electrochemical station. Reproduced from ref. with permission from ACS Publications, copyright 2024. (c) Electrochemical biosensors use enzymatic reactions to induce redox or impedance changes upon target binding. These electrical changes are quantified via portable potentiostats or impedance analyzers, offering rapid and sensitive detection at the point of care. (d) Electrochemical immunosensor for the detection of α-synuclein in Parkinson's disease. The platform integrates a laser-induced graphene electrode modified with gold nanoparticles and antibodies, enabling label-free impedance-based detection with high sensitivity. Reproduced from ref. with permission from Elsevier, copyright 2025.

Fig. 5. Point-of-care diagnostic devices. (a) General schematic of an optical biosensor: a light source excites the sample at a functionalised sensing surface, where the interaction with specific analytes induces measurable changes in optical properties (e.g., absorbance, fluorescence, or refractive index). These changes are then detected by a photodetector for signal quantification. (b) Paper-based biosensor for blood urea nitrogen (BUN) detection using an integrated optical film and photodiode-based detection unit. Color intensity from enzymatic reactions is quantified digitally, enabling rapid and low-cost clinical assessment. Reproduced from ref. with permission from Elsevier, copyright 2023. (c) Plasmonic glucose biosensor featuring self-assembled anisotropic gold nanoparticles on a paper substrate. Glucose-induced etching alters nanoparticle shape and color, enabling semi-quantitative visual analysis with high stability in biological fluids. Reproduced from ref. with permission from Elsevier, copyright 2021. (d) Smartphone-based POC diagnostic platform using a 3D-printed chamber with integrated RGB LEDs and a smartphone camera. Fluorescent lateral flow strips can be inserted for real-time image-based quantification of nucleic acid amplification signals. Reproduced from ref. with permission from Elsevier, copyright 2019. (e) Electrochemical glucose biosensor with a smartphone-connected interface. A screen-printed carbon electrode is modified with Fe₃O₄–poly(thiophene) nanocomposites to enable sensitive and stable glucose detection in saliva, urine, and blood. Reproduced from ref. with permission from Elsevier, copyright 2022.

Fig. 6. Schematic representation of how point-of-care (POC) devices can enhance cancer management across the care continuum. POC technologies support early screening through accessible, non-invasive tests; enable faster, real-time diagnosis; facilitate treatment monitoring via at-home biomarker tracking; and contribute to research by generating high-frequency, real-world clinical data. Together, these applications promote timely interventions, personalised care, and improved outcomes in oncology.

Leena Khelifa

Yubing Hu

Amina Ali

Catarina Jones

Nan Jiang

Ali K. Yetisen