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Title: Development of automated analysis and sorting of single cells using Laser Tweezers Raman Spectroscopy
Author: Casabella, Stephen
ISNI:       0000 0004 6495 1008
Awarding Body: University of Manchester
Current Institution: University of Manchester
Date of Award: 2015
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One in two people born after 1960 in the United Kingdom will be diagnosed with some form of cancer during their lifetime. Analysis of cancer at the bulk level means that individual attributes may be averaged, and single cell detection and interrogation techniques are therefore of particular interest. In recent years, significant progress has been made into the label-free detection and discrimination of individual cancer cells using Laser Tweezers Raman Spectroscopy (LTRS). However, methods have invariably involved a high degree of manual intervention, and before this technique can be translated into a clinical setting a greater degree of automation is required.\\Initial work has centred on the construction of a LTRS system for the analysis of individual prostate cancer cells and lymphocytes. A novel method of acquiring cell spectra using a microfluidic flow cell has been developed, and the optimum operating conditions for such a system are elucidated in this thesis. Using the system developed, the discrimination of epithelial prostate cells and lymphocytes has been achieved with a high degree of accuracy while requiring a significant reduction in operator input. Further developments to the system have made it possible to obtain Raman spectra for multiple cell lines in a completely automated manner, with no input required during the acquisition of spectra. \\A motivating factor behind the integration of LTRS with microfluidics is the possibility of a label-free equivalent of the Fluorescent Activated Cell Sorter (FACS), which remains the gold standard for single cell analysis. A number of significant steps toward the development of the Raman equivalent (RACS) are presented in this thesis, including the demonstration of an automated system which is capable of multivariate classification and cell translation in real time. Due to limitations relating to the microfluidic flow cells, it has not been possible to actively sort one cell line from a mixed population. However, the system presented in this thesis represents a considerable level of progress towards this objective.\\In addition to the construction of a LTRS arrangement, a 2D Raman mapping system has been developed for the analysis of adherent prostate cell line. This has allowed a direct comparison between the more common technique of Raman mapping and LTRS, and provides new insights into the level of information which can be obtained using LTRS. This thesis presents results obtained with both systems which enable malignant and normal prostate cell lines to be distinguished based on cytochrome-c levels. While cytochrome-c content has been linked with malignancy previously, this is the first demonstration of this relationship using a LTRS system which could be applied in a high throughput setting.
Supervisor: Scully, Patricia Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Raman spectroscopy ; Prostate Cancer