Detecting alterations at the molecular level linked to cancer is a key aspect in developing new strategies for treatment and for diagnosis.
For this purpose tissue biopsies are analyzed using various analytical techniques, such as mass spectrometry, and may result in the identification of novel biomarkers. Tissue microarrays TMAs contain a large number of biopsies prepared in an array format. The use of TMAs in biomedical workflows is significantly increasing in the past few years; the main challenge is the limited amount of sample available 1.
The aim of our work is to apply advanced nanoLC-MS MS techniques to reliably identify various glycans and proteins from histological tissue surfaces and to apply the workflow for the analysis of prostate cancer TMAs. Integrating proteomics data with glycan analysis has recently become widespread.
Glycosaminoglycans GAGs play crucial roles in cancer progression; however, their nanoscale analysis is still considered an analytical challenge compared to proteomics methods, prostate cancer histology are relatively straightforward. More than proteins were identified and quantified using label free quantitation from the 1.