Abstract
INTRODUCTION:
Spatial molecular analysis of tissues using MALDI MS is an emerging tool for pathology that enables discovery of diagnostically useful protein signatures that correlate with disease. An ongoing challenge is mapping disease-related proteomic changes in tissues with morphologically complex architecture where analysis at the single cell level is desired. Here we describe a novel highly sensitive workflow that allows the isolation and processing of selected cell subpopulations for MALDI MS analysis. Optimization of the method for fresh frozen and formalin fixed, paraffin embedded (FFPE) tissue is described, and the workflow is applied for the detection of differentially expressed proteins from cells related to perineural invasion (PNI) in human prostate cancer.
METHODS:
Tissue sections of 4–20 μm thickness were thaw-mounted onto Director slides for staining and dehydration. Laser capture microdissection (LCM) was carried out using a PALM microbeam instrument modified with a custom holder for mounting of capture chips consisting of Teflon printed slides. The sample was digested on-chip with trypsin in a humidity chamber to reduce evaporation of the digestion buffer. Differentially expressed peptides were detected directly from the chip using a 9.4 T Bruker Apex-Qe MALDI MS.
RESULTS:
An optimized workflow combining LCM, on-chip processing and analysis of fresh frozen and FFPE tissue allowed the detection of meaningful protein signatures from less than 50 dissected cells. Profiles from fresh frozen and FFPE mouse liver tissue from the same mouse showed similar peptide profiles, demonstrating successful on-chip antigen retrieval of FFPE tissue. We then applied this strategy for mapping of differentially expressed proteins in PNI. Molecular profiles from cells undergoing PNI and nerve distant bulk tumor cells showed many differentially expressed peptides, including peptides with m/z = 1356.624 and 1459.696. The rapid, high throughput analysis of cell type- and location-specific proteomes from pathologically important cells shows great potential for improving molecular diagnostics.