Spatial MS multiomics on clinical prostate cancer tissues.

Area of Science:

• Biochemistry
• Molecular Biology
• Oncology

Background:

• Mass spectrometry (MS) and MS imaging (MSI) are crucial for lipidomics and proteomics but typically require separate sample preparation.
• Advancements in omics technologies and bioinformatics enable multiomics analysis from a single sample.

Purpose of the Study:

• To develop and validate a workflow integrating spatial lipidomics and proteomics on the same prostate cancer tissue sample.
• To identify molecular markers differentiating cancerous from benign prostate tissues using a multiomics approach.

Main Methods:

• Matrix-assisted laser desorption/ionization MS imaging (MALDI-MSI) for spatial lipidomics on prostatectomy cores.
• Laser capture microdissection (LCM) guided by MSI data for region-specific proteomics.
• Data acquisition using a dia-PASEF workflow and analysis with SCiLS region mapper software.

Main Results:

• Identification of 5525 unique protein groups across dissected tissue regions.
• Significant enrichment of Lysophosphatidylcholine acyltransferase 1 (LPCAT1) in cancerous epithelium (CE) compared to benign epithelium (BE).
• Correlation of increased LPCAT1 protein abundance with altered phosphatidylcholine (PC) and lysophosphatidylcholine (LPC) ion intensity ratios in CE.

Conclusions:

• The integrated MSI-proteomics workflow successfully characterizes molecular differences between cancerous and benign prostate tissues.
• LPCAT1 is a potential biomarker for prostate cancer, with its abundance reflected in both proteomic and lipidomic profiles.