Title |
Pathology-Driven Comprehensive Proteomic Profiling of the Prostate Cancer Tumor Microenvironment
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Published in |
Molecular Cancer Research, February 2017
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DOI | 10.1158/1541-7786.mcr-16-0358 |
Pubmed ID | |
Authors |
Lisa Staunton, Claire Tonry, Rosina Lis, Virginia Espina, Lance Liotta, Rosanna Inzitari, Michaela Bowden, Aurelie Fabre, John O'Leary, Stephen P Finn, Massimo Loda, Stephen R Pennington |
Abstract |
Prostate cancer (PCa) is the second most common cancer in men worldwide. Gleason grading is an important predictor of PCa outcomes and is influential in determining patient treatment options. Clinical decisions based on a Gleason score of 7 are difficult as the prognosis for individuals diagnosed with Gleason 4+3 cancer is much worse than for those diagnosed with Gleason 3+4 cancer. Laser capture microdissection (LCM) is a highly precise method to isolate specific cell populations or discrete microregions from tissues. This report undertook a detailed molecular characterization of the tumor microenvironment (TME) in PCa to define the proteome in the epithelial and stromal regions from tumor foci of Gleason grade 3 and 4. Tissue regions of interest were isolated from several Gleason 3+3 and Gleason 4+4 tumors using telepathology to leverage specialized pathology expertise to support LCM. Over 2,000 proteins were identified following liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis of all regions of interest. Statistical analysis revealed significant differences in protein expression (>100 proteins) between Gleason 3 and Gleason 4 regions - in both stromal and epithelial compartments. A subset of these proteins has had prior strong association with PCa, thereby providing evidence for the authenticity of the approach. Finally, validation of these proteins by immunohistochemistry (IHC) has been obtained using an independent cohort of PCa tumor specimens. This unbiased strategy provides a strong foundation for the development of biomarker protein panels with significant diagnostic and prognostic potential. |
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