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Analysis of prostate cancer by proteomics using tissue specimens
Alvin Y Liu1, Hui Zhang, Carrie M Sorensen
1Department of Urology, University of Washington, Seattle, Washington 98195, USA. aliu@u.washington.edu
The Journal of Urology
|December 14, 2004
Summary
Prostate cancer diagnosis shows promise using surface-enhanced laser desorption/ionization (SELDI) protein profiling for pattern recognition. Quantitative proteomics identified tissue metalloproteinase inhibitor-1 as a potential biomarker down-regulated in cancer.
Area of Science:
- Proteomics
- Biomarker Discovery
- Cancer Diagnostics
Background:
- Prostate cancer cells exhibit altered gene expression compared to normal cells.
- Differences in proteomes between cancerous and normal prostate tissues are expected.
- Secreted protein species composition is particularly relevant for diagnostics.
Purpose of the Study:
- To profile prostate tissue samples using SELDI time-of-flight mass spectrometry to generate phenomic fingerprints.
- To identify differentially expressed proteins using quantitative proteomics based on glycopeptide capture and tandem mass spectrometry.
Main Methods:
- Patient-matched cancer and noncancer prostate specimens were processed into single cells.
- Supernatants were analyzed using reversed-phase hydrophobic ProteinChip Arrays for SELDI profiling (43 primary tumors, 26 matched).
- Quantitative proteomics was performed on one specimen, with results verified by Western blotting and immunohistochemistry.
Main Results:
- SELDI profiles indicated similarity among prostate cancers of comparable TNM stages.
- Quantitative proteomics identified tissue metalloproteinase inhibitor-1 as downregulated in cancerous tissue.
- Tissue metalloproteinase inhibitor-1 expression was localized to secretory cells.
Conclusions:
- SELDI protein profiling is feasible and holds potential for prostate cancer diagnosis via pattern recognition.
- Quantitative proteomics can identify numerous prostate cancer-specific biomarkers.