Abstract
Proteomics assays hold great promise for unraveling molecular events that underlie human diseases. Effective analysis of clinical samples is essential, but this task is considerably complicated by tissue heterogeneity. Laser capture microdissection (LCM) can be used to selectively isolate target cells from their native tissue environment. However, the small number of cells that is typically procured by LCM severely limits proteome coverage and biomarker discovery potential achievable by conventional proteomics platforms. Herein, we describe the use of nanoLC-FT-ICR MS for analyzing protein digests of 3000 LCM-derived tumor cells from breast carcinoma tissue, corresponding to 300 ng of total protein. A total of 2282 peptides were identified by matching LC-MS data to accurate mass and time (AMT) tag databases that were previously established for human breast (cancer) cell lines. One thousand and three unique proteins were confidently identified with two or more peptides. Based on gene ontology categorization, identified proteins appear to cover a wide variety of biological functions and cellular compartments. This work demonstrates that a substantial number of proteins can be detected and identified from limited number of cells using the AMT tag approach, and opens doors for high-throughput in-depth proteomics analysis of clinical samples.
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