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Review [Abstract] In the last several years, researchers have exhibited an intense interest in the evolutionarily conserved signaling pathways that have crucial roles during embryonic development. Interestingly, the malfunctioning of these signaling pathways leads to several human diseases, including cancer. The chemical and biophysical events that occur during cellular signaling, as well as the number of interactions within a signaling pathway, make these systems complex to study. In silico resources are tools used to aid the understanding of cellular signaling pathways. Systems approaches have provided a deeper knowledge of diverse biochemical processes, including individual metabolic pathways, signaling networks and genome-scale metabolic networks. In the future, these tools will be enormously valuable, if they continue to be developed in parallel with growing biological knowledge. In this study, an overview of the bioinformatics resources that are currently available for the analysis of biological networks is provided.

In the last several years, researchers have exhibited an intense interest in the evolutionarily conserved signaling pathways that have crucial roles during embryonic development. Interestingly, the malfunctioning of these signaling pathways leads to several human diseases, including cancer. The chemical and biophysical events that occur during cellular signaling, as well as the number of interactions within a signaling pathway, make these systems complex to study. In silico resources are tools used to aid the understanding of cellular signaling pathways. Systems approaches have provided a deeper knowledge of diverse biochemical processes, including individual metabolic pathways, signaling networks and genome-scale metabolic networks. In the future, these tools will be enormously valuable, if they continue to be developed in parallel with growing biological knowledge. In this study, an overview of the bioinformatics resources that are currently available for the analysis of biological networks is provided.

468 Background: Detection of circulating tumor cells (CTC) may provide diagnostic and prognostic information in genitourinary tumors (GT). The aim of this work was identify aberrantly expressed miRNAs potentially useful for CTC detection in blood samples from patients with GT to assess their potential clinical significance, and to gain a greater understanding of the mechanisms driving tumor progression. Methods: We examined blood levels of 92 microRNAs in 113 metastatic patients: prostate (mP), renal cell carcinoma (mRCC), bladder tumors (mB) and healthy volunteers (HV) (N=18) using SYBR-green-based microRNA RT-qPCR arrays (Exiqon). Array design was made by literature review and bioinformatics approach using free databases. Relative Expression Software Tool (REST) and SPPS 21.0 were used to data processing and analysis. Results: microRNAs differential expressed between tumors and HV (only up-regulated miRNAs are shown in Table). Conclusions: microRNAs in the circulation are relatively stable, very accessible, low invasive and easily testable biomarkers. These results suggest that our bioinformatic approach is an useful high-throughput method to identified tumors-associated miRNAs. The selected miRNAs should be further evaluated for their potential as markers for CTC detection, prognosis and therapeutic outcome. Further studies of precision and sensitivity on these markers in this GT population will clarify its role as novel stable blood-based markers. [Table: see text]

451 Background: Renal cell carcinoma (RCC) is known to be resistant to chemotherapy. There is need for the identification of biomarkers capable to determine RCC prognosis factors and metastatic potential obtainable from non-invasive or minimally invasive techniques. Our aim was to derive predictive models which could predict more accurately than any one factor alone. Methods: To studythe cascade of events leading to the formation and progression of RCC, we assessed 29 markers by immunohistochemistry and qRT-PCR using tissue micro-array (TMA). Results: Multivariate logistic regression showed the best proteins combination for node status (NOTCH1 and GLUT5) and pelvis invasion (EGFR and DLL3). ROC curve analyses were made to analyse the accuracy of the best candidate proteins; it should be noted NOTCH1 and GLUT5 for node status prediction (AUC=0.833, 95% CI, 0.744-0.922; p

5087 Background: Recent studies have demonstrated that the aberrant expression of microRNAs (miRNAs)is related with the development of prostate cancer (PCa). Detection of circulating tumor cells (CTC) may provide diagnostic and prognostic information inPCa. The purpose is identifying circulating miRNAs potentially useful for CTC detection in patients with PCa. Methods: In the first study phase we examined blood levels of 92 miRNAs in 49 patients grouped in pools by risk classification: low-risk 42.8%, intermediate-risk 22.5% and high-risk 34.7% and healthy volunteers (N=10) using SYBR-green-based microARN RT-qPCR arrays (Exiqon). Prostate cancer diagnosis was obtained by transrectalultrasound guided biopsy of 10 cores, PSA and digital rectal examination was done previously. In the second study phase using quantitative real-time polymerase chain reaction (qPCR) by TaqMan Human MicroRNAAssays (Life Technologies), we compared the expression levels of miRNAs in blood samples from 34 patients of low-risk, 31 of intermediate-risk, 18 of high-risk localized disease and 22 healthy volunteers paired by age with cases. Receiver-operator characteristic (ROC) curve was used. Results: Blood samples from patients with low, intermediate, high-risk and healthy controls exhibit distinct circulating miRNA signatures. microRNAsdifferential expressed between risk groups (p

Historically, cell-signaling pathways have been studied as the compilation of isolated elements into a unique cascade that transmits extracellular stimuli to the tumor cell nucleus. Today, growing evidence supports the fact that intracellular drivers of tumor progression do not flow in a single linear pathway, but disseminate into multiple intracellular pathways. An improved understanding of the complexity of cancer depends on the elucidation of the underlying regulatory networks at the cellular and intercellular levels and in their temporal dimension. The high complexity of the intracellular cascades causes the complete inhibition of the growth of one tumor cell to be very unlikely, except in cases in which the so-called “oncogene addiction” is known to be a clear trigger for tumor catastrophe, such as in the case of gastrointestinal stromal tumors or chronic myeloid leukemia. In other words, the separation and isolation of the driver from the passengers is required to improve accuracy in cancer treatment. This review will summarize the signaling pathway crossroads that govern renal cell carcinoma proliferation and the emerging understanding of how these pathways facilitate tumor escape. We outline the available evidence supporting the putative links between different signaling pathways and how they may influence tumor proliferation, differentiation, apoptosis, angiogenesis, metabolism and invasiveness. The conclusion is that tumor cells may generate their own crossroads/crosstalk among signaling pathways, thereby reducing their dependence on stimulation of their physiologic pathways.

e15587 Background: Renal Cell Carcinoma (RCC) accounts for 2% of all adult malignancies, its remains a very aggressive and often fatal disease, and is increasingly being recognized as a metabolic d...

e22171 Background: We previously have studied differentially microRNA expression levels related to hormone refractory and sensitive prostate cancer cell lines (VCap and LNCap respectively). Now, we investigated circulating miRNAs differentially expressed between metastatic prostate adenocarcinomas (mPA) and healthy controls (HC) that may serve as novel diagnostic and/or prognosis markers. Methods: Using SYBR-green-based custom microRNA RT-qPCR arrays technology (Exiqon), we compared the expression levels of miRNAs in blood samples from 18 HC and 48 mPA. Results: Among a panel of 92 candidates we found 41 underexpressed (UE) and 8 overexpressed (OE) miRNAs. The level of significance was p

e15542 Background: Renal cell carcinoma (RCC) is known to be resistant to chemotherapy. The need for the identification of biomarkers capable of determining RCC prognosis factors and metastatic potential that are obtainable from non-invasive or minimally invasive techniques are desirable. The purpose from this analysis was to derive predictive models which could predict more accurately than any one factor alone. Methods: By tissue micro-array (TMA) technology we assessed 29 markers involved in the cascade of events leading to the formation and progression of this disease. The ability of multivariate logistic regression to improve the diagnostic accuracy for RCC by combining determinations of proteins markers and pathological variables was evaluated. Univariate analysis was used to select factors (p

448 Background: Many studies have demonstrated genetic and environmental factors lead to renal cell carcinoma (RCC) occurring during a protracted period of tumorigenesis. It seemed suitable identify and characterize potential molecular markers which might provide rapid and effective possibilities for early detection of RCC. The purpose from this analysis was to derive predictive models which could predict more accurately than any one factor alone. Methods: We assessed using quantitative real-time PCR (qPCR) with SYBR Green the profile of 32 predictive markers involved in the cascade of events leading to the formation and progression of this disease to evaluate their involvement in oncogenesis. RNA of quality was obtained in 90% of samples (N=80, 52/80 clear RCC, 6/80 papillary RCC and 14/80 chromophobe RCC) to carry out the study of gene expression. GenEx software was used for qPCR data processing and analysis. The potential correlation between mRNA expression and the pathological features of the study subjects was assessed by Pearson Chi-squared. Linear rather than logistic regression models were used (SPSS statistics 21.0 software). Additionally, a knowledgebases of biological pathways, Reactome and Snow (Babelomics), were used to superimpose our quantitative expression data. Results: The best gene predictors related to different pathological variables (histological type, tumor size, Fuhrman grade, number of involved nodes, renal pelvis invasion, lymphatic vessels invasion, and rupture of the renal capsule): Hif1-α (p < 0.001), Hif1-β (p = 0.035), DLL1 (p = 0 .012), DLL3 (p< 0.001), c-Kit (p = 0.002), PDGFR-β (p =0.002), PDGFR-α (p = 0.026), Bax-β (p = 0.005), Survivin (p = 0.028), Notch1 (p = 0.006), Notch2 (p = 0.007), Notch3 (p = 0.016), Notch4 (p = 0.005), EGFR (p = 0.029), Glut3 (p = 0.026), Glut5 (p = 0.036), FH (p = 0.018), CA9 (p = 0.030), and VHL-1(p = 0.015). Conclusions: Our data suggested that altered expression of certain members involved in the main pathways which feed RCC and their downstream targets analyzed together could improve the diagnostic accuracy for renal cancer by combining determinations of mRNA markers.

e15077 Background: Renal cell carcinomas (RCC) constitute a morphologically and genetically heterogeneous tumor.Wnt proteins are a large family of secreted glycoproteins that activate intracellular signal transduction pathways to control a wide variety of cellular processes such as determination of cell fate, proliferation, migration, and polarity.Wnt signalling may be playing a central role during RCC development. Methods: To characterize Wnt signalling activity in RCC, we gathered 48 tumor samples from patients diagnosed with metastatic RCC between years 2006 and 2011. Expression levels of Wnt family members (Wnt1, Wnt2, Wnt3a, Wnt4, Wnt5a, Wnt7a, and Wnt9a) were examined by real-time PCR and immunohistochemistry in tumor and normal tissue from removed kidneys. Results: Wnt1 and Wnt5a were up-regulated in clear cell RCC being their relative expression 2.4.103 (Wnt1) and 4.102 (Wnt5a) times higher in renal tumor tissue than in normal tissue. One-way ANOVA test showed Wnt3a and Wnt4 as the best protein markers to distinguish clear cell RCC (F=3.95, p=0.010 and F=3.05, p=0.029, respectively). Wnt1 and Wnt7a were over-expressed in those cases which had undergone nefrectomy (Mann-Whitney U test p=0.065 and p=0.056 respectively). Finally, Wnt2 protein level was associated with those patients with high risk prognosis (Kruskal-Wallis test p=0.001). Conclusions: Our results indicate that Wnt3a and Wnt4 are potentially useful immunohistochemical markers for the differential diagnosis between clear cell RCC and other subtypes of RCC and also suggest a role for Wnt2 as a high risk prognosis marker.

e15076 Background: The characterization of factors involved in the etiology of renal cell carcinoma (RCC) may lead to the identification of new targets for therapy and prognostic markers. Recent data indicate that Notch family members can be expressed by malignant RCC cells and this expression may have potential use as a strong prognostic factor. The aim of this study was to investigate the potential of Notch family members as prognostic markers for stage IV patients. Methods: We analyzed, by means of immunohistochemistry and quantitative polymerase chain reaction, protein and mRNA levels of 4 Notch family members in tumor specimens obtained from 48 patients with stage IV RCC. Clinicopathological data for these patients were evaluated. A 34% of the population had hypertension, 7.3% had hypothyroidism, 19.5% were diabetic, 7.7% prediabetic, and 22% showed hyperlipidemia. RCC specimens included clear cell RCC: 34; papillary: 3; mixed: 1; undifferentiated: 1; hypernephroma: 1.The association among biomarkers and clinicopathological factors were explored using One-Way ANOVA test and non-parametric statistics, Mann-Whitney U and Kruskal-Wallis tests. Results: Relative expression of Nocth3 and Notch4 transcript levels were elevated 25-fold in clear cell RCC tumors when compared with normal kidney tissues. Notch1 and Notch2 were overexpressed at protein level in clear cell RCC (p>0.05). Those renal tumors with right localization showed highest levels of Notch4 protein (p=0.096). Notch2 overexpression was associated with patients who had undergone nefrectomy (p=0.038). Finally, Bonferroni post-hoc statistic test showed us a statistically significant association (p = 0.020) between Nocth1 protein expression levels and patients with medium risk prognosis. Conclusions: These results show a deregulated expression of Notch receptors in RCC and suggest a role for this pathway in the progression of this tumoral pathology.

e15079 Background: Many studies have demonstrated genetic and environmental factors lead to renal cell carcinoma (RCC) occurring during a protracted period of tumorigenesis. It seemed suitable identify and characterize potential molecular markers appearing during of tumorigenesis which might provide rapid and effective possibilities for early detection of RCC. Methods: We assessed using quantitative real-time PCR (qPCR) the profile of 32 markers involved in the cascade of events leading to the formation and progression of RCC: invasiveness, angiogenesis and antiapoptotic mechanisms. RNA of quality was obtained in 90% of samples (N=80, 64/80 clear RCC, 8/80 papillary RCC and 8/80 chromophobe RCC) to carry out the study of gene expression. Nonparametric tests (Pearson's correlation coefficient test and Spearman's rho test, Kruskal — Wallis and Mann — Whitney) and Bonferroni post-hoc test were applied for statistical data analysis. Additionally, a knowledgebase of biological pathways, Reactome, was used to superimpose our quantitative expression data. Results: Statistical analysis comparing medians and means showed the following candidates as the best gene predictors related to different pathological variables (histological type, number of involved nodes, renal pelvis invasion, lymphatic vessels invasion and rupture of the renal capsule): Hif1-α (p