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

Jones AC, Antillon KS, Jenkins SM, Janos SN, Overton HN, Shoshan DS, Fischer EG, Trujillo KA, Bisoffi M - PLoS ONE (2015)

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: University of New Mexico Health Sciences Center, Department of Biochemistry and Molecular Biology, Albuquerque, New Mexico, United States of America.

ABSTRACT
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.

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MIC-1 detection and quantitation in human prostate tissues (commercial tissue microarray).(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 Materials and Methods): (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)).
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pone.0119314.g003: MIC-1 detection and quantitation in human prostate tissues (commercial tissue microarray).(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 Materials and Methods): (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)).

Mentions: Expression levels for MIC-1 in tumor tissues were significantly elevated (10.2x to 23.4x by WSA and 7.1x to 9.4x by ROI) compared to disease-free tissues (p<0.05 to p<0.0001). In support of field cancerization, MIC-1 expression in tumor adjacent tissues was similarly and significantly elevated (19.2x to 38.4x by WSA and 7.4x to 20.5x by ROI) compared to disease-free tissues (p<0.05 to p<0.0001), and MIC-1 expression was similar (0.3x to 1.1x by WSA and 0.5x to 1.0x by ROI) in tumor and tumor adjacent tissues (p>0.05 for most of the analyses) (Table 2). Visual representation of data supporting prostate field cancerization for MIC-1 is given in Fig. 2. WSA analysis indicated that MIC-1 expression was significantly different between tumor and disease-free tissues (p(t)<0.01; p(WRS)<0.01) and between tumor adjacent and disease-free tissues (p(t)<0.001; p(WRS)<0.0001). In contrast, MIC-1 expression was highly similar (p(t) = 0.94; p(WRS) = 0.21) in tumor and tumor adjacent tissues (Fig. 2A). To address the possibility that matched status could influence the similarity of expression in tumor and their adjacent tissues, we determined the correlation coefficient for signal intensities derived from matched tissues, which indicated no match bias (r = 0.27). In addition, we also analyzed the difference in MIC-1 expression between images belonging to non-matched cases. Although this analysis comprised fewer data points, the difference between tumor and disease-free tissues (p(t)<0.01; p(WRS)<0.05), and between tumor adjacent and disease-free tissues (p(t)<0.05; p(WRS)<0.0001) remained significant, while MIC-1 expression in tumor and tumor-adjacent tissues (p(t) = 0.97; p(WRS) = 0.95) was similar (Fig. 2B). Figs. 2C and 2D depict similar findings for images analyzed by the ROI method. MIC-1 expression was significantly different between tumor and disease-free tissues (p(t)<0.001; p(WRS)<0.01) and between tumor adjacent and disease-free tissues (p(t)<0.001; p(WRS)<0.0001). In contrast, MIC-1 expression was similar (p(t) = 0.30; p(WRS) = 0.16) in tumor and tumor adjacent tissues (Fig. 2C). There was again no correlation in expression between matched tissues (r = 0.12) and in non-matched cases, the difference between tumor and disease-free tissues (p(t)<0.001; p(WRS)<0.05), and between tumor adjacent and disease-free tissues (p(t)<0.001; p(WRS)<0.001) remained significant, while MIC-1 expression in tumor and tumor-adjacent tissues (p(t) = 0.69; p(WRS) = 0.56) was similar (Fig. 2D). Of note, the level of inter- and intra-tissue heterogeneity for both types of measurements was high (coefficient of variation = 86.1%). Because MIC-1 expression seemed to clearly support the concept of field cancerization in prostate tissues, we determined its expression in an independent set of 9 matched tumor and adjacent tissues featured on commercially available tissue microarrays (Figs. 3A and 3B). Quantitation by both the WSA and ROI methods (Figs. 3C and 3D) revealed similar MIC-1 expression levels in tumor and tumor-adjacent tissues (0.9x by WSA [p(t) = 0.47; p(WRS) = 0.76] and 1.0x by ROI [p(t) = 0.59; p(WRS) = 0.82]) (Table 2). There was no correlation between the tumor and their adjacent tissues, indicating the absence of a match bias (r<0.1) and the inter- and intra-tissue heterogeneity was notably lower (16.9%), probably due to the conventional immunofluorescence method.


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

Jones AC, Antillon KS, Jenkins SM, Janos SN, Overton HN, Shoshan DS, Fischer EG, Trujillo KA, Bisoffi M - PLoS ONE (2015)

MIC-1 detection and quantitation in human prostate tissues (commercial tissue microarray).(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 Materials and Methods): (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)).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4358924&req=5

pone.0119314.g003: MIC-1 detection and quantitation in human prostate tissues (commercial tissue microarray).(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 Materials and Methods): (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)).
Mentions: Expression levels for MIC-1 in tumor tissues were significantly elevated (10.2x to 23.4x by WSA and 7.1x to 9.4x by ROI) compared to disease-free tissues (p<0.05 to p<0.0001). In support of field cancerization, MIC-1 expression in tumor adjacent tissues was similarly and significantly elevated (19.2x to 38.4x by WSA and 7.4x to 20.5x by ROI) compared to disease-free tissues (p<0.05 to p<0.0001), and MIC-1 expression was similar (0.3x to 1.1x by WSA and 0.5x to 1.0x by ROI) in tumor and tumor adjacent tissues (p>0.05 for most of the analyses) (Table 2). Visual representation of data supporting prostate field cancerization for MIC-1 is given in Fig. 2. WSA analysis indicated that MIC-1 expression was significantly different between tumor and disease-free tissues (p(t)<0.01; p(WRS)<0.01) and between tumor adjacent and disease-free tissues (p(t)<0.001; p(WRS)<0.0001). In contrast, MIC-1 expression was highly similar (p(t) = 0.94; p(WRS) = 0.21) in tumor and tumor adjacent tissues (Fig. 2A). To address the possibility that matched status could influence the similarity of expression in tumor and their adjacent tissues, we determined the correlation coefficient for signal intensities derived from matched tissues, which indicated no match bias (r = 0.27). In addition, we also analyzed the difference in MIC-1 expression between images belonging to non-matched cases. Although this analysis comprised fewer data points, the difference between tumor and disease-free tissues (p(t)<0.01; p(WRS)<0.05), and between tumor adjacent and disease-free tissues (p(t)<0.05; p(WRS)<0.0001) remained significant, while MIC-1 expression in tumor and tumor-adjacent tissues (p(t) = 0.97; p(WRS) = 0.95) was similar (Fig. 2B). Figs. 2C and 2D depict similar findings for images analyzed by the ROI method. MIC-1 expression was significantly different between tumor and disease-free tissues (p(t)<0.001; p(WRS)<0.01) and between tumor adjacent and disease-free tissues (p(t)<0.001; p(WRS)<0.0001). In contrast, MIC-1 expression was similar (p(t) = 0.30; p(WRS) = 0.16) in tumor and tumor adjacent tissues (Fig. 2C). There was again no correlation in expression between matched tissues (r = 0.12) and in non-matched cases, the difference between tumor and disease-free tissues (p(t)<0.001; p(WRS)<0.05), and between tumor adjacent and disease-free tissues (p(t)<0.001; p(WRS)<0.001) remained significant, while MIC-1 expression in tumor and tumor-adjacent tissues (p(t) = 0.69; p(WRS) = 0.56) was similar (Fig. 2D). Of note, the level of inter- and intra-tissue heterogeneity for both types of measurements was high (coefficient of variation = 86.1%). Because MIC-1 expression seemed to clearly support the concept of field cancerization in prostate tissues, we determined its expression in an independent set of 9 matched tumor and adjacent tissues featured on commercially available tissue microarrays (Figs. 3A and 3B). Quantitation by both the WSA and ROI methods (Figs. 3C and 3D) revealed similar MIC-1 expression levels in tumor and tumor-adjacent tissues (0.9x by WSA [p(t) = 0.47; p(WRS) = 0.76] and 1.0x by ROI [p(t) = 0.59; p(WRS) = 0.82]) (Table 2). There was no correlation between the tumor and their adjacent tissues, indicating the absence of a match bias (r<0.1) and the inter- and intra-tissue heterogeneity was notably lower (16.9%), probably due to the conventional immunofluorescence method.

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: University of New Mexico Health Sciences Center, Department of Biochemistry and Molecular Biology, Albuquerque, New Mexico, United States of America.

ABSTRACT
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.

Show MeSH
Related in: MedlinePlus