Comparative analysis of biological profiles of benign prostate hyperplasia and prostate cancer as potential diagnostic, prognostic and predictive indicators

The prognosis in prostate cancer depends on several clinical-morphological factors, such as Gleason score, pTNM and preoperative PSA level. Reliable biological markers are being sought to supplement clinicalmorphological data in order to better predict prognosis and to select an individualized therapeutic option. The aim of this study was a comparative analysis of the expression of biological markers, such as Hif-1&#945;, bcl-2, p53, Ki-67, cyclin D1 and CD44 in BPH and prostate cancer, as well as examining their association with standard prognostic factors in prostate cancer. The immunohistochemical analysis was made on 82 formalin-fixed, paraffin- embedded tissue blocks: 43 prostate cancer specimens derived from patients who had undergone radical resection, and 39 prostate bioptates derived from patients with BPH. A positive correlation was demonstrated between Gleason score and the expression of both Hif-1&#945; (R = 0.32, p < 0.05) and Ki-67 (R = 0.30, p < 0.05). Additionally, a negative correlation was demonstrated between tumor stage (pTNM) and bcl-2 expression (R = &#8211;0.35, p < 0.05). Hif-1&#945; as a hypoxia marker and Ki-67 as a proliferation marker, both correlated with Gleason score, may constitute important additional prognostic indicators in prostate cancer patients. (Folia Histochemica et Cytobiologica 2011; Vol. 49, No. 3, pp. 452&#8211;457

The Sum of Tumour-to-Brain Ratios Improves the Accuracy of Diagnosing Gliomas Using 18F-FET PET.

Gliomas are common brain tumours, but obtaining tissue for definitive diagnosis can be difficult. There is, therefore, interest in the use of non-invasive methods to diagnose and grade the disease. Although positron emission tomography (PET) with 18F-fluorethyltyrosine (18F-FET) can be used to differentiate between low-grade (LGG) and high-grade (HGG) gliomas, the optimal parameters to measure and their cut-points have yet to be established. We therefore assessed the value of single and dual time-point acquisition of 18F-FET PET parameters to differentiate between primary LGGs (n = 22) and HGGs (n = 24). PET examination was considered positive for glioma if the metabolic activity was 1.6-times higher than that of background (contralateral) brain, and maximum tissue-brain ratios (TBRmax) were calculated 10 and 60 min after isotope administration with their sums and differences calculated from individual time-point values. Using a threshold-based method, the overall sensitivity of PET was 97%. Several analysed parameters were significantly different between LGGs and HGGs. However, in a receiver operating characteristics analysis, TBR sum had the best diagnostic accuracy of 87% and sensitivity, specificity, and positive and negative predictive values of 100%, 72.7%, 80%, and 100%, respectively. 18F-FET PET is valuable for the non-invasive determination of glioma grade, especially when dual time-point metrics are used. TBR sum shows the greatest accuracy, sensitivity, and negative predictive value for tumour grade differentiation and is a simple method to implement. However, the cut-off may differ between institutions and calibration strategies would be useful

Parameter values as predictive factors for high-grade glioma.

<p>Parameter values as predictive factors for high-grade glioma.</p

Values of single and dual time-point PET parameters for high-grade and low-grade gliomas.

<p>Values of single and dual time-point PET parameters for high-grade and low-grade gliomas.</p

ROC curve for the combined parameter TBR10 + TBR difference; Threshold = 1.602.

<p>ROC curve for the combined parameter TBR10 + TBR difference; Threshold = 1.602.</p

Studies estimating TBR_max values in gliomas.

<p>Studies estimating TBR_max values in gliomas.</p

SUV kinetics for high (left graph) and low (right graph) grade gliomas.

<p>SUV kinetics for high (left graph) and low (right graph) grade gliomas.</p