Development of a lateral flow device for neuroblastoma diagnosis
File(s)
Author(s)
Khelifa, Leena
Type
Thesis
Abstract
Neuroblastoma is a rare, yet aggressive paediatric cancer characterised by heterogeneity resulting in diverse genetic profiles and clinical behaviours. Neuroblastoma-derived v-myc avian myelocytomatosis viral-related oncogene (MYCN) amplification is the most significant poor prognostic marker for the disease; however, its early detection remains a major clinical challenge. Current diagnostic approaches include imaging and tissue biopsies, which often induce long-term morbidity. In recent years, there has been growing interest in the development of minimally invasive diagnostic tools. This goal is underpinned by the discovery of circulating biomarkers, which have paved the way for the development of point-of-care (POC) technologies. This thesis focuses on the design and validation of novel immunoassay systems for neuroblastoma diagnosis. It begins with the first known attempt to detect MYCN protein in blood using enzyme-linked immunosorbent assay (ELISA), which showed potentially increased concentrations in sick patients compared to healthy controls. A proof-of-concept lateral flow assay (LFA) was developed for MYCN detection which involved the examination of several critical parameters such as pH dependency and matrix effects. Ultimately, challenges related to antibody stability and non-specific binding limited the device’s diagnostic utility. The development of a multiplexed LFA for other biomarkers linked to MYCN-amplification was explored, with ELISA validation undertaken for vanillylmandelic acid (VMA) and 3-methoxytyramine (3-MT). The shedding of cleaved anaplastic lymphoma kinase (ALK) in neuroblastoma cells was confirmed and antibody pair validation was undertaken which proved that ALK could be successfully sandwiched between two antibodies. These initial validation steps provided important groundwork for future assay development. To enhance the usability of the LFAs, a smartphone-based readout system was designed. The software utilised 3D printed hardware to accurately quantify analyte concentrations from test strip images. Together, this work is a foundational step towards tackling the existing hurdles in neuroblastoma diagnosis, offering successful integration of immunoassays into digitally enhanced platforms.
Version
Open Access
Date Issued
2025-07-02
Date Awarded
2026-03-01
Copyright Statement
Attribution-NonCommercial 4.0 International Licence (CC BY-NC)
License URL
Advisor
Yetisen, Ali
Publisher Department
Department of Chemical Engineering
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)