Ultrasensitive detection of pancreatic cancer biomarkers by nanoscale engineered fluorescence enhancing materials
File(s)
Author(s)
Jawad, Zaynab Abdul Raheem
Type
Thesis
Abstract
Pancreatic cancer is one of the deadliest cancers in the world. The main reason is that patients do not show symptoms until the advanced stages of the disease, when it has spread to other organs. In the late stages, there is no cure for pancreatic cancer and the only feasible treatments are chemotherapy and radiotherapy, which only prolong survival by a few months. In fact, only 15% of patients present when the disease is still resectable with surgery, which is the only cure. The main reason for these poor outcomes is that there is no diagnostic test to detect the disease in the early asymptomatic stage. Nanotechnology is an emerging field that is providing solutions to some of the dilemmas in cancer. For diagnostics, nanoparticles are being used to increase the sensitivity of detecting circulating cancer biomarkers in blood using a phenomenon known as metal enhanced fluorescence. By increasing the sensitivity of detecting these biomarkers, it has been shown that lower tumour burden can be identified. Furthermore, novel biomarkers such as microRNAs are proving to be promising candidates as biomarkers for early pancreatic cancer. In this project, four different nanomaterials for metal enhanced fluorescence-based detection of biomarkers were developed and evaluated using pancreatic cancer biomarkers. The nanomaterials have been optimised for use in biosensing. The lowest limit of detection achieved using tunable gold nanotriangular arrays was 7.7 × 10−7 UmL−1 and 10-15 M for CA 19–9 and GPC-1 respectively. A concentration dependent metal enhanced fluorescent assay was achieved for microRNA-21, also for detecting pancreatic cancer. Both assays were highly specific for their respective analyte of interest. These nanomaterials show great potential as multiplexing platforms to simultaneously detect multiple biomarkers for pancreatic cancer. In future, this strategy may improve the detection of the disease in the early stages to improve patient outcomes.
Version
Open Access
Date Issued
2018-01
Date Awarded
2018-08
Copyright Statement
Attribution NoDerivatives 4.0 International Licence (CC BY-ND)
Advisor
Xie, Fang
Publisher Department
Materials
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)