Protein patterns can be used to identify bladder cancer

A pattern of 22 polypeptides (proteins) could help distinguish patients with bladder cancer from individuals with other malignant and non-malignant genitourinary diseases, according to researchers reporting in the March issue of The Lancet Oncology. "From signatures of polypeptide mass, we established a model for predicting the presence of cancer", says lead author Prof Dan Theodorescu (University of Virginia Health Sciences Center, Charlottesville, VA, USA).

Although cancer of the urinary bladder is a common disease with an estimated 63 210 new cases in the USA in 2005, the current diagnostic tests are not very specific or sensitive. Previous studies have identified biomarker (protein) patterns that would distinguish patients with urothelial carcinoma--the most common malignant disease of the urinary bladder--from healthy controls. However, Theodorescu and colleagues wanted to identify a specific protein pattern that would, in addition, distinguish patients with urothelial carcinoma from those with other urinary diseases that can present with similar clinical signs and symptoms as those associated with bladder cancer.

They used urine samples from 46 patients with urothelial carcinoma and 33 healthy volunteers to establish a protein model. This model was then refined further using 366 urine samples from individuals with malignant and non-malignant genitourinary diseases. Using one of these refined models, the researchers correctly identified between 86% and 100% of 31 patients with urothelial carcinoma, 138 people who had other genitourinary diseases, and 11 healthy individuals.

Prof Theodorescu states: "At present, we are applying these methods to the discovery of biomarkers that can predict tumour stage, recurrence, progression and treatment response in patients with bladder cancer".

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Contact: Prof Dan Theodorescu, Dept of Molecular Physiology and Biological Physics, Box 422, University of Virginia Health Sciences Center, Charlottesville, VA 22908, USA. T) + 1 434 924 0042 dt9d@virginia.edu


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