Posters

Nodal involvement in bladder cancer is an independent indicator of prognosis. This study employed an iterative machine learning process called genetic programming on quantitative expression values of 70 genes to classify primary urothelial carcinoma samples into those associated with or without nodal metastasis. The generated rules showed a strong predilection for ICAM1, MAP2K6 and KDR resulting in gene expression motifs that cumulatively suggested a pattern ICAM1>MAP2K6>KDR for node positive ca

Increased nitric oxide (NO) production has been implicated in the pathogenesis of the hyperdynamic circulation found in patients with advanced liver disease. There were no differences between patients with liver disease and controls with regard whole body NO production. Our results, in a well characterised set of patients, argue against greater basal NOS-dependent whole body NO production in patients with decompensated liver disease.

LC-MS based proteomic experiments are used to compare complex biological samples across multiple conditions. Fast, powerful computational tools are needed to explore and detect differences in the areas of Expression Proteomics and Biomarker Discovery. In general, specialized steps are necessary to solve these difficult problems (binning, alignment & normalization, peak picking, relative quantitation, etc.). MS-Xelerator is a collection of software tools dedicated to all of the above tasks.

Caveolin1 (Cav-1) function either as a tumor supressor or as a promoter of metastasis. Overexpresion of cav-1 was correlated with: tumoral grading, proliferration markers (Ki67, p53), serum tumor markers (CEA, CA19.9) and angiogenic markers (VEGF, bFGF).

Recently, TaqMan® assays have been developed for detection of genetic variation at gene level using primers and probes designed for genomic DNA sequences. The R package TaqGCN contains classes and methods that can be used for data reading and plotting, and for predicting gene copy number.