Abstract. Renal cell carcinomas (RCC) can be subclassified for general purposes into clear cell, papillary cell, chromophobe cell carcinomas and oncocytomas. Other tumours such as collecting duct, medullary, mucinous tubular and spindle cell and associated with Xp 11.2 translocations/TFE 3 gene fusion, are much less common. There is also a residual group of unclassified cases. Previous studies have shown that RCC has high glycolytic rates, and expresses GLUT transporters, but no distinction has been made among the different subtypes of renal cell tumours and their grades of malignancy. In clear renal cell carcinoma (cRCC) glycogen levels increase, glycolysis is activated and gluconeogenesis is reduced. The clear cell subtype of RCC is characterized histologically by a distinctive pale, glassy cytoplasm and this appearance of cRCC is due to abnormalities in carbohydrate and lipid metabolism, and this abnormality results in glycogen and sterol storage. Several isoforms of glucose carriers (GLUTs) have been identified. We show here in a panel of 80 cRCC samples a significant correlation between isoform 5 (GLUT5) and many pathological parameters such as grade of differentiation, pelvis invasion and breaking capsule. GLUT5 expression also appears to associate more strongly with the clear cell RCC subtype. These data suggest a role for the GLUT5 isoform in fructose uptake that takes place in cRCC cells and which subsequently leads to the malignant RCC progression.

Abstract. The aim of this study was to provide a methodology to make a clear distinction between malignant tumors and morphologically similar benign processes, by examining the expression of eGFr, VeGF, HiF1-α, survivin, Bcl-2 and p53 proteins. Four groups of patient samples were studied: group 1, low-grade astrocytomas (WHo grades i-ii) (n=6); group 2, peripheral area of high-grade astrocytomas (WHo grades iii-iV) (n=5); group 3, gliomatosis cerebri (n=11); and group 4, reactive gliosis (n=6). Tissue arrays (Tas) were designed to study apoptosis, angiogenesis and invasion-related proteins by immunohistochemistry (iHc). By means of nonparametric analysis (Mann-Whitney u test), eGFr staining was shown to be significantly lower in reactive gliosis than in the low-and high-grade astrocytomas (p=0.015 and p=0.030, respectively); Bcl-2 immunoreactivity was significantly higher in the gliomatosis cerebri samples than in the reactive processes (p=0.005); and finally, Bcl-2 presented significantly lower expression levels in reactive gliosis compared to the peripheral areas of high-grade astrocytomas (p=0.004). The results indicate that Bcl-2 and eGFr may be useful in conducting differential diagnosis between the above groups, while the expression of the remaining antibodies does not appear to aid in distinguishing between the samples analyzed.

Introduction. Kidney tumours are frequently characterised by hypoxic conditions due to a local imbalance between oxygen (O 2 ) supply and consumption. Hif1-α regulates angiogenesis, tumour growth, tumour progression, metastatic spread, and glucose metabolism by acting as a transcription factor for relevant genes. Here, we describe an immunohistochemical study of Hif1-α, a comprehensive computational study of Hif1-α interacting proteins (HIPs), an analysis correlating expression levels of Hif1-α with upstream and downstream proteins, and an analysis of the utility of Hif1-α for prognosis in a cohort of patients with renal cell carcinoma. Materials and methods. The patient cohort included 80 patients. For immunohistochemistry evaluation, tissue microarrays were constructed. The IntAct, MINT, and BOND databases were used for the HIP approach. The Kruskal-Wallis test was used for comparing protein expression with pathology measurements. Correlation was expressed as the Pearson coefficient. Results. Hif1-α expression correlates significantly with the "clear" histological subtype of renal cell carcinoma (p < 0.01). The samples with the worst prognoses related to the pathological variables analysed showed the highest levels of Hif1-α expression. Significant correlations were found with Bcl-2, CAIX, C-kit, EGFR, TGF-β, proteins of the VEGF family, proteins related to differentiation (such as Notch1 and Notch3) and certain metabolic enzymes. Bioinformatic analysis suggested 45 evidence-based HIPs and 4 complexes involving protein Hif1-α. Conclusions. This work summarises the multifaceted role of Hif1-α in the pathology of renal cell carcinomas, and it identifies HIPs that could help provide mechanistic explanations for the different behaviours seen in tumours.