MicroARN circulantes en sangre de pacientes con cáncer de próstata / Circulating MicroRNAs in Blood of Patients With Prostate Cancer

Introducción: Los microARN (miARN) son ARN reguladores de pequeño tamaño que no codifican para proteínas. La detección de células tumorales circulantes (CTC) proporcionaría información diagnóstica y pronóstica en los tumores de próstata (TP). En este sentido los miARN podrían constituir una nueva y prometedora clase de biomarcadores para la detección de CTC. Objetivos: Analizar miARN circulantes en sangre total como marcadores no invasivos en pacientes con cáncer de próstata localizado e individuos sanos. Material y métodos: Estudio preliminar con una N poblacional de 40 pacientes con una media de edad de 71 años y un PSA medio de 18, 9 ng/ml (rango). Respecto al grupo de riesgo (GR): un 33,3% bajo riesgo, un 30% riesgo intermedio y un 36,7% alto riesgo. Se realizó un estudio previo in silico que identificó 92 miARN candidatos seguido de otro in vivo para verificar los hallazgos del primero mediante tecnología de arrays de PCR a tiempo real. Resultados: El análisis estadístico de los resultados reveló 10 miARN candidatos con una expresión diferencial estadísticamente significativa entre los distintos grupos de riesgo y los controles sanos: hsa-miR-337-3p, hsa-miR-330-3p, hsa-miR-339-3p, hsa-miR-124, hsa-miR-218, hsa-miR-128, hsa-miR-10a, hsa-miR-199b-5p, hsa-miR-200b y hsa-miR-15b Conclusiones: Nuestros datos sugieren que los miARN circulantes pueden servir como biomarcadores para identificar grupos de riesgo en CaP

Introduction: MicroRNAs (miRNAs) are small regulatory RNAs that do not code for proteins. Detection of circulating tumor cells (CTC) would provide diagnostic and prognostic information in prostate tumors (PT). Thus, miRNAs could constitute a promising new class of biomarkers for CTC detection. Objectives: To analyze circulating microRNAs in whole blood as non-invasive markers in patients with localized prostate cancer and healthy individuals. Material and methods: A preliminary study including a population of 40 patients with mean age of 71 years and mean PSA of 18, 9ng/ml (range). Regarding the risk group (RG): 33.3% had low risk, 30% intermediate risk and 36.7% high risk. A previous in silico study identified 92 candidates and was followed by another in vivo to verify the findings of the former using array technology by real-time PCR. Results: Statistical analysis of the results revealed 10 microRNAs candidates with statistically significant differential expression between the different risk groups and healthy controls: hsa-miR-337-3p, hsa-miR-330-3p, hsa-miR-339-3p, hsa-miR-124, hsa-miR-218, hsa-miR-128, hsa-miR-10a, hsa-miR-199b-5p, hsa-miR-200b and hsa-miR-15b. Conclusions: Our data suggest that circulating microRNAs can act as biomarkers to identify risk groups in CaP

Circulating MicroRNAs in blood of patients with prostate cancer.

INTRODUCTION: MicroRNAs (miRNAs) are small regulatory RNAs that do not code for proteins. Detection of circulating tumor cells (CTC) would provide diagnostic and prognostic information in prostate tumors (PT). Thus, miRNAs could constitute a promising new class of biomarkers for CTC detection. OBJECTIVES: To analyze circulating microRNAs in whole blood as non-invasive markers in patients with localized prostate cancer and healthy individuals. MATERIAL AND METHODS: A preliminary study including a population of 40 patients with mean age of 71 years and mean PSA of 18, 9 ng/ml (range). Regarding the risk group (RG): 33.3% had low risk, 30% intermediate risk and 36.7% high risk. A previous in silico study identified 92 candidates and was followed by another in vivo to verify the findings of the former using array technology by real-time PCR. RESULTS: Statistical analysis of the results revealed 10 microRNAs candidates with statistically significant differential expression between the different risk groups and healthy controls: hsa-miR-337-3p, hsa-miR-330-3p, hsa-miR-339-3p, hsa-miR-124, hsa-miR-218, hsa-miR-128, hsa-miR-10a, hsa-miR-199b-5p, hsa-miR-200b and hsa-miR-15b. CONCLUSIONS: Our data suggest that circulating microRNAs can act as biomarkers to identify risk groups in CaP.

Searching for Hif1-alpha interacting proteins in renal cell carcinoma

INTRODUCTION: Kidney tumours are frequently characterised by hypoxic conditions due to a local imbalance between oxygen (O2) 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 (AU)

Searching for Hif1-α interacting proteins in renal cell carcinoma.

INTRODUCTION: Kidney tumours are frequently characterised by hypoxic conditions due to a local imbalance between oxygen (O2) 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-ß, 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.

Tissue array analysis for the differentiation of gliosis from gliomas.

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 non-parametric 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. The use of TAs to identify the protein expression profiles of biological markers related to different pathways was verified, and its potential as a discriminatory technique for everyday pathology procedures was demonstrated.

Fructose transporter GLUT5 expression in clear renal cell carcinoma.

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.