Prostate field cancerization: deregulated expression of macrophage inhibitory cytokine 1 (MIC-1) and platelet derived growth factor A (PDGF-A) in tumor adjacent tissue.

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

Association and Regulation of Protein Factors of Field Effect in Prostate Tissues

Field effect or field cancerization denotes the presence of molecular aberrations in structurally intact cells residing in histologically normal tissues adjacent to solid tumors. Currently, the etiology of prostate field‑effect formation is unknown and there is a prominent lack of knowledge of the underlying cellular and molecular pathways. We have previously identified an upregulated expression of several protein factors representative of prostate field effect, i.e., early growth response‑1 (EGR‑1), platelet‑derived growth factor‑A (PDGF‑A), macrophage inhibitory cytokine‑1 (MIC‑1), and fatty acid synthase (FASN) in tissues at a distance of 1 cm from the visible margin of intracapsule prostate adenocarcinomas. We have hypothesized that the transcription factor EGR‑1 could be a key regulator of prostate field‑effect formation by controlling the expression of PDGF‑A, MIC‑1, and FASN. Taking advantage of our extensive quantitative immunofluorescence data specific for EGR‑1, PDGF‑A, MIC‑1, and FASN generated in disease‑free, tumor‑adjacent, and cancerous human prostate tissues, we chose comprehensive correlation as our major approach to test this hypothesis. Despite the static nature and sample heterogeneity of association studies, we show here that sophisticated data generation, such as by spectral image acquisition, linear unmixing, and digital quantitative imaging, can provide meaningful indications of molecular regulations in a physiologically relevant in situ environment. Our data suggest that EGR‑1 acts as a key regulator of prostate field effect through induction of pro‑proliferative (PDGF‑A and FASN), and suppression of pro‑apoptotic (MIC‑1) factors. These findings were corroborated by computational promoter analyses and cell transfection experiments in non‑cancerous prostate epithelial cells with ectopically induced and suppressed EGR‑1 expression. Among several clinical applications, a detailed knowledge of pathways of field effect may lead to the development of targeted intervention strategies preventing progression from pre‑malignancy to cancer

Quantitative immunofluorescence of MIC-1 in human prostate tissues.

<p>(A-D) MIC-1 expression levels (indicated as signal intensities [pixel count]) in disease-free, tumor adjacent, and tumor tissues; the types of analysis were the following (as per <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0119314#sec002" target="_blank">Materials and Methods</a>): (A and B) Whole slide analysis (WSA) for all (A) and non-matched (B) cases in the UNMH/CHTN cohort; (C and D) region of interest (ROI) analysis for all (C) and non-matched (D) cases in the UNMH/CHTN cohort. Individual data points are shown as small black squares (partially overlapping); the boxes represent group medians (line across middle) and quartiles (25th and 75th percentiles) at its ends; lines above and below boxes indicate 10th and 90th percentiles, respectively. For each analysis, the number of images and cases is indicated; p values above the panels denote the level of statistical significance for the differences between groups, as calculated by the student’s t-test (p(t)) and by the Wilcoxon rank sums test (p(WRS)).</p

MIC-1 detection and quantitation in human prostate tissues (commercial tissue microarray).

<p>(A-B) Immunofluorescence with anti-MIC-1 antibody in a representative prostate tumor (A) and tumor adjacent tissue (B); pictures represent overlays of nuclear staining by DAPI (blue) and Alexa Fluor 488 immunostaining (yellow/white); the insets are Alexa Fluor 488 immunostaining only; white bars represent 10 micrometers. The diamond, closed arrow, and open arrow in B denote a typical lumen, epithelial cell compartment, and stromal cell compartment, respectively. (C-D) MIC-1 expression levels (indicated as signal intensities [pixel count]) in matched tumor adjacent and tumor tissues; the types of analysis were the following (as per <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0119314#sec002" target="_blank">Materials and Methods</a>): (C) Whole slide analysis (WSA), (D) region of interest (ROI) analysis. Individual data points are shown as small black squares (partially overlapping); the boxes represent group medians (line across middle) and quartiles (25th and 75th percentiles) at its ends; lines above and below boxes indicate 10th and 90th percentiles, respectively. For each analysis, the number of images and cases is indicated; p values above the panels denote the level of statistical significance for the differences between groups, as calculated by the student’s t-test (p(t)) and by the Wilcoxon rank sums test (p(WRS)).</p

Differences in expression of MIC-1 and PDGF-A in tumor, tumor adjacent, and disease-free prostate tissues obtained from UNMH/CHTN and on tissue microarrays (TMA).

<p>Tissues of a kind were grouped into four different categories, i.e. (i) all combined, (ii) above and below the median to counteract the effect of heterogeneity, and (iii) non-matched to counteract the possibility of a match effect bias.</p><p>¹ Ratio is based on the mean of all pixel intensities (expression) in the indicated group. The number of images utilized to calculate the ratio and the difference in expression are partially indicated in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0119314#pone.0119314.t001" target="_blank">Table 1</a> and Figs. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0119314#pone.0119314.g002" target="_blank">2</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0119314#pone.0119314.g004" target="_blank">4</a>.</p><p>² First significance measure p for the difference in expression is from the student’s t-test; the second significance measure p is from the Wilcoxon rank sums test.</p><p>³ WSA, analysis by whole slide.</p><p>⁴ ROI, analysis by region of interest.</p><p>⁵ n/a, not applicable.</p><p>Differences in expression of MIC-1 and PDGF-A in tumor, tumor adjacent, and disease-free prostate tissues obtained from UNMH/CHTN and on tissue microarrays (TMA).</p

MIC-1 (A-C) and PDGF-A (D-F) detection in human prostate tissues (UNMH/CHTN cohort).

<p>Representative cases of prostate tumors (A and D) and adjacent tissues (B and E), as well as cases of disease-free control tissues unrelated to cancer (C and F) are shown; pictures represent overlays of nuclear staining by DAPI (blue) and Alexa Fluor 633 immunostaining (yellow/white); the insets are Alexa Fluor 633 immunostaining only; white bars represent 10 micrometers. The diamonds, closed arrows, and open arrows in B and E denote a typical lumen, epithelial cell compartment, and stromal cell compartment, respectively.</p

Quantitative immunofluorescence of PDGF-A in human prostate tissues.

<p>(A-D) PDGF-A expression levels (indicated as signal intensities [pixel count]) in disease-free, tumor adjacent, and tumor tissues; the types of analysis were the following (as per <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0119314#sec002" target="_blank">Materials and Methods</a>): (A and B) Whole slide analysis (WSA) for values above (A) and below (B) the median of the values of all cases in the UNMH/CHTN cohort; (C and D) region of interest (ROI) analysis for values above (A) and below (B) the median of the values of all cases in the UNMH/CHTN cohort. Individual data points are shown as small black squares (partially overlapping); the boxes represent group medians (line across middle) and quartiles (25th and 75th percentiles) at its ends; lines above and below boxes indicate 10th and 90th percentiles, respectively. For each analysis, the number of images and cases is indicated; p values above the panels denote the level of statistical significance for the differences between groups, as calculated by the student’s t-test (p(t)) and by the Wilcoxon rank sums test (p(WRS)).</p

Association and regulation of protein factors of field effect in prostate tissues

Field effect or field cancerization denotes the presence of molecular aberrations in structurally intact cells residing in histologically normal tissues adjacent to solid tumors. Currently, the etiology of prostate field‑effect formation is unknown and there is a prominent lack of knowledge of the underlying cellular and molecular pathways. We have previously identified an upregulated expression of several protein factors representative of prostate field effect, i.e., early growth response‑1 (EGR‑1), platelet‑derived growth factor‑A (PDGF‑A), macrophage inhibitory cytokine‑1 (MIC‑1), and fatty acid synthase (FASN) in tissues at a distance of 1 cm from the visible margin of intracapsule prostate adenocarcinomas. We have hypothesized that the transcription factor EGR‑1 could be a key regulator of prostate field‑effect formation by controlling the expression of PDGF‑A, MIC‑1, and FASN. Taking advantage of our extensive quantitative immunofluorescence data specific for EGR‑1, PDGF‑A, MIC‑1, and FASN generated in disease‑free, tumor‑adjacent, and cancerous human prostate tissues, we chose comprehensive correlation as our major approach to test this hypothesis. Despite the static nature and sample heterogeneity of association studies, we show here that sophisticated data generation, such as by spectral image acquisition, linear unmixing, and digital quantitative imaging, can provide meaningful indications of molecular regulations in a physiologically relevant in situ environment. Our data suggest that EGR‑1 acts as a key regulator of prostate field effect through induction of pro‑proliferative (PDGF‑A and FASN), and suppression of pro‑apoptotic (MIC‑1) factors. These findings were corroborated by computational promoter analyses and cell transfection experiments in non‑cancerous prostate epithelial cells with ectopically induced and suppressed EGR‑1 expression. Among several clinical applications, a detailed knowledge of pathways of field effect may lead to the development of targeted intervention strategies preventing progression from pre‑malignancy to cancer