Prostate Field Cancerization: Deregulated Expression of Macrophage Inhibitory Cytokine 1 (MIC-1) and Platelet Derived Growth Factor A (PDGF-A) in Tumor Adjacent Tissue.
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Prostate field cancerization denotes molecular alterations in histologically normal tissues adjacent to tumors. Such alterations include deregulated protein expression, as we have previously shown for the key transcription factor early growth response 1 (EGR-1) and the lipogenic enzyme fatty acid synthase (FAS). Here we add the two secreted factors macrophage inhibitory cytokine 1 (MIC-1) and platelet derived growth factor A (PDGF-A) to the growing list of protein markers of prostate field cancerization. Expression of MIC-1 and PDGF-A was measured quantitatively by immunofluorescence and comprehensively analyzed using two methods of signal capture and several groupings of data generated in human cancerous (n = 25), histologically normal adjacent (n = 22), and disease-free (n = 6) prostate tissues. A total of 208 digitized images were analyzed. MIC-1 and PDGF-A expression in tumor tissues were elevated 7.1x to 23.4x and 1.7x to 3.7x compared to disease-free tissues, respectively (p<0.0001 to p = 0.08 and p<0.01 to p = 0.23, respectively). In support of field cancerization, MIC-1 and PDGF-A expression in adjacent tissues were elevated 7.4x to 38.4x and 1.4x to 2.7x, respectively (p<0.0001 to p<0.05 and p<0.05 to p = 0.51, respectively). Also, MIC-1 and PDGF-A expression were similar in tumor and adjacent tissues (0.3x to 1.0x; p<0.001 to p = 0.98 for MIC-1; 0.9x to 2.6x; p<0.01 to p = 1.00 for PDGF-A). All analyses indicated a high level of inter- and intra-tissue heterogeneity across all types of tissues (mean coefficient of variation of 86.0%). Our data shows that MIC-1 and PDGF-A expression is elevated in both prostate tumors and structurally intact adjacent tissues when compared to disease-free specimens, defining field cancerization. These secreted factors could promote tumorigenesis in histologically normal tissues and lead to tumor multifocality. Among several clinical applications, they could also be exploited as indicators of disease in false negative biopsies, identify areas of repeat biopsy, and add molecular information to surgical margins.
