Examination of tumour tissues by direct MALDI-mass spectrometry imaging and profiling.

The purpose of the work described in this thesis was to develop and apply efficient methodologies based on MALDI-MSI for the direct analysis and targeting of protein tumour biomarkers within both frozen and formalin fixed paraffin embedded (FFPE) cancerous tissue sections.Method development for protein analysis directly in tumour tissue sections were performed using tumour xenograft models. This involved improvements in sample preparation, such as tissue washing protocols, and the development of data pre-processing methods prior to statistical analysis using a freely available software package, which referred to as Spec Align.The use of MALDI-MSI for studying proteome patterns directly from tumour tissue sections with no requirement for known targets is demonstrated. In addition, in situ identification of proteins within tumour tissue sections was achieved and correlated with their localisation. The method demonstrated here involved the use of octyl glucoside, a non-ionic detergent, which aims to improve the solubilisation and detection of low abundance and membrane-associated proteins within tumour tissue section after on-tissue digestion. The coupling of MALDI-MSI with ion mobility separation (IMS) has been found to improve the specificity and selectivity of the method.Combining these two methodological approaches allowed the targeting and identification of known tumour biomarkers and potential protein markers in various tumour tissue samples including frozen AQ4N dosed colon tumour xenografts and FFPE human adenocarcinoma tissue sections. The localisation and identification of proteins correlated to tumour growth and aggressiveness were studied using IMS-Tag MALDI-MSI, a novel concept developed in this work.In order to demonstrate its use as a potential biomarker discovery tool, MALDI-MSI was used for high throughput analysis of proteins within tissue micro arrays. Combining MALDI-MSI with statistical analysis allowed the design of a novel tumour classification model based on proteomic imaging information after on-tissue digestion.Another challenge for the MALDI-MSI technology is to achieve more targeted quantitative approaches for in situ analysis of proteins. A proof-of-concept based on multiple reaction monitoring (MRM) analysis with MALDI-MSI is described using a high repetition rate solid state laser. This aimed to improve the sensitivity and specificity of the methodology for the investigation of peptides/proteins directly within tumour tissue sections.