Prostate Cancer Proteomics driven by Spatial Lipidomics Characterization

Alteration of cellular lipid metabolism is one of the hallmarks of prostate cancer (PCa). We have been using MALDI MS-Imaging to study these lipdomic changes in patient biopsies, with a novel workflow that then allows for additional proteomics information. The ability to spatially define sub-lipidomes is critical as the prostate tissue of PCa patients is highly heterogeneous. Consequently, the tissue-averaged lipidome observed using conventional bulk lipidomics can obscure details visible in spatial lipidomics.

Using spatial segmentation of the lipid MS-imaging data, we could classify tissues into stroma, healthy and cancerous epithelium (HE and CE). The region mapper tool in SCiLS Lab was used to create "cut lists" for a Laser Capture Microdissection system for each different tissue type. Excised tissues were digested using trypsin and analysed using a DIA PASEF LC-MS workflow. In this way over 5000 protein groups were identified, ~ 200 of which showed significant differences between HE and CE. Some of the differentially regulated proteins are involved in lipid metabolism and changes in the lipidome in the same tissues show good correlation with the changes at the protein level.

Key Learning Objectives:

• Classifying tissue subregions using MALDI Imaging
• Practical methods for a workflow that uses spatial and LC-MS analysis

Who should join:

• Scientists interested in combing traditional proteomics with spatial information
• Cancer researchers with an interest in adding spatial classification workflows
• Anyone wanting to expand knowledge on the breadth of utility from MALDI Imaging