Analisi comparativa dei metaboliti presenti nelle urine di soggetti sani ed affetti da carcinoma alla vescica

For several years proteomics research has been expected to lead to the finding of new markers that will translate into clinical tests applicable to samples such as serum, plasma and urine: so-called in vitro diagnostics (IVDs). Attempts to implement technologies applied in proteomics as 2DE, Immuno Blotting, Mass Spectrometry have initiated constructive discussions on opportunities and challenges inherent in such a translation process also with respect to the use of multi-marker profiling approaches and pattern signatures in IVD. It is mandatory to fulfil requirements in routine IVD, including disease prevention, diagnosis, prognosis, and treatment monitoring or follow up among others. To fulfill IVD requirements, it is essential to provide diagnostic tests that allow for definite and reliable diagnosis tied to a decision on interventions (prevention, treatment, or non treatment), meet stringent performance characteristics for each analyte (in particular test accuracy, including both precision of the measurement and trueness of the measurement), and provide adequate diagnostic accuracy, i.e., diagnostic sensitivity and diagnostic specificity, determined by the desired positive and negative predictive values which depend on disease frequency. The fulfilment of essential IVD requirements is mandatory in the regulated environment of modern diagnostics. Addressing IVD needs at an early stage can support a timely and effective transition of findings and developments into routine diagnosis. IVD needs reflect features that are useful in clinical practice. This helps to generate acceptance and assists the implementation process. The medical need for relevant biomarkers is enormous. This is particularly true for the many types of cancer, but other diseases such as Type 1 diabetes (DMT1) also lack useful and adequate diagnostic markers with high specificity and sensitivity. Despite advances in imaging technologies for early detection of diseases, proteomic and peptidomic multiplex techniques and metabolomics statistical analysis have evolved in recent years.