New testing approach to predict outcome in patients with bladder cancer

Jan 29 2007

A new testing approach has been shown to be effective in identifying patients at the highest risk of cancer relapse after surgery for bladder cancer, say researchers in the February issue of The Lancet Oncology.

"Bladder cancer recurs in many patients after radical cystectomy [removal of the bladder and surrounding tissues]. Conventional prognostic features such as tumour grade, stage, and lymph-node status are not accurate enough to predict outcomes in patients with bladder cancer", says one of the study's researcher Dr Yair Lotan, from the Texas Southwestern Medical Center, Dallas, TX, USA.

The researchers analysed bladder samples from 226 patients that were removed during surgery for bladder cancer. Using a tissue profiling technique, the authors tested for four different proteins (known as P53, Bcl-2, caspase-3, and survivin) that have been implicated in causing cancer. The researchers found that when expression of all four proteins was altered, patients had a greater risk of developing a recurrence of their bladder cancer, and eventual death from the disease, compared with patients who had no change of expression of these proteins.

"We found that evaluation of combined apoptosis biomarkers [markers of cell death] status can help identify patients at high risk of recurrence and death from bladder cancer after radical cystectomy, independent of conventional prognostic features", says member of the research team, Dr Jose Karam. Lead researcher Professor Shahrokh Shariat continues, "clinical trials are needed to target bladder cancer in patients with a high number of [alterations], as these patients have poor survival rates with current treatments and might benefit the most from experimental therapy".

In a linked Reflection and Reaction commentary, Dr Francisco Real and Dr Nuria Malats state that, "this is the first study in which multiple apoptosis markers have been used together to asess the value in improving accuracy of predicting outcome for patients with bladder cancer".