Abstract
Accurately identifying different types of cancer cells and subtypes is of paramount importance for improving the survival rates of patients. The conventional approaches for identifying cell types rely on expensive and time-consuming methods, include Polymerase Chain Reaction (PCR), Quantitative Polymerase Chain Reaction (qPCR), enzyme-linked immunosorbent assay (ELISA), and next-generation sequencing (NGS) technologies. Hence, there is an urgent requirement for a novel diagnostic approach that offers precise identification and high detection efficiency of different subtypes of breast cancer. The non-invasive and sensitive surface-enhanced Raman scattering (SERS) holds great promise as a technique for analyzing both chemical compounds and biomolecules. The label-free SERS detection has the potential to unravel intrinsic fingerprint information of biomarkers at a single cell and molecule level, thus enabling excellent scalability for this approach with simplified detection process and reduced costs. Therefore, through the development of highly sensitive and accurate SERS substrates with excellent signal stability, reliable label-free SERS bioprobes can serve as a crucial reference for cancer diagnosis. Noble metal nanomaterials, such as gold and silver nanoparticles, are extensively utilized as SERS substrates because of their ability to produce a significant electromagnetic enhancement. However, the efficacy of these substrates is impeded by the uneven distribution of "hot spots," leading to unpredictable variations in spectral stability and reproducibility. Consequently, this hinders their practical usability, making them less reliable for consistent results. Semiconductor-based SERS substrates have gained attention as promising alternatives due to their exceptional spectral stability, strong resistance to interference, and outstanding selectivity. However, they have presented a limited enhancement factor. Therefore, it is an urgent need to explore reliable SERS substrates combined with high sensitivity, and stability by the combined utilization of noble metals and semiconductor materials, leading to a mutually beneficial outcome. As cuprous oxide (Cu2O) has been well received and employed as good semiconductor materials due to the advantages of ease synthesis and environmental friendliness, we tried and prepared three types of Cu2O template as semiconductor substrate. After that, Ag nanoparticles were introduced to build core-shell structured Cu2O@ Ag composite. By using these bioprobes, we employed label-free SERS detection and machine learning assisted linear discriminant analysis to classify and identify different sources of cancer cells, hepatic cells, and subtypes of breast cancer cells.First, a flower-like Cu2O@Ag composite SERS substrate and machine learning assisted LDA model were established. The results of SERS detection demonstrated a good SER activity, as it can detect alizarin red (AR) molecules at a minimum concentration of 10-9 mol/L. Besides, the flower-like Cu2O@Ag showed potential in detecting several signaling molecules, like methylene blue (MB) and crystal violet (CV) molecules. In particular, the best spectral stability of detection was achieved for the Cu2O@Ag-AR with RSD values of 6.13% and 5.81% at Raman shift of 1256 cm-1 and 1440 cm-1. According to this, three different sources of cancer cells of pancreatic cancer, liver cancer and glioma were tested using the constructed SERS substrates as probes for label-free detection. An accuracy of 95.34% was obtained for classification of three cell lines according to the established LDA model.
Second, a hexahedral Cu2O@Ag SERS substrate was prepared. The XRD spectra and element scanning map of hexahedral Cu2O@Ag demonstrated the successful preparation of composite Cu2O@Ag. The spectral data demonstrated a better SERS activity compared to flower-like Cu2O@Ag. It is able to detect AR molecules at a minimum concentration of 10-10 mol/L and 4NTP molecules at a minimum concentration of 10-15 mol/L. In addition to this, the SERS activity has exhibited to detect several signaling molecules, including MB and 4NTP (4 Nitrophenthiol) molecules. In particular, the best stability of detection was achieved for the MB molecule with RSD value of 8.80% a at Raman shift of 1443 cm-1. The Cu2O@Ag-4NTP spectra also showed good stability, as the peaks at 1080 cm-1 and 11.34 cm-1 were 10.13% and 11.34%, respectively. To explore the potential in assisting in vitro modeling of fibrosis in hepatocytes, four different hepatic cells were tested using the constructed SERS substrates as probes for label-free detection. An accuracy of 93.297% was obtained for classification of four cell lines according to the established LDA model. AUC values for all four cells were greater than 95%, indicating that the method has a good ability to differentiate four kinds of hepatic cells.
Third, an octahedral Cu2O@Ag SERS substrate was constructed. The UV-vis spectra and element scanning map demonstrated the successful formation of composite octahedral Cu2O@Ag. It showed good SERS performance for its ability to detect 4NTP molecules at a minimum concentration of 10-15 mol/L with an EF up to 109. The Cu2O@Ag-4NTP spectra also showed good stability with RSD values less than 10%. The enhancement mechanism was subsequently investigated. The chemical enhancement is demonstrated by the attenuation of fluorescence lifetime of MB after being absorbed onto Cu2O@Ag and the CT contribution was calculated of 21.31%. FDTD (finite-difference time-domain) models explained the critical role of electromagnetic mechanism in SERS. Overall, the constructed metal-semiconductor composite material could give a synergistic effort for high sensitivity SERS detection. Finally, four subtypes of breast cancer were differentiated using this high-performance probe, obtaining an accuracy of 93.3%, which has shown great potential in cancer precision diagnosis.
Based on the above results and applications, we have gradually developed substrates with good SERS performance of Cu2O@Ag and investigated the synergistic mechanism of Raman enhancement by semiconductor and noble metal materials. The successful application of these probes for solving biological problems has developed a valuable path for the diagnosis of diseases.
| Date of Award | Jul 2024 |
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| Original language | English |
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| Supervisor | Yong Ren (Supervisor) |