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Computational tool uses patient's genomic data to find best treatment for bladder cancer

 9 months ago       121 Views

When it comes to cancer, one-size-does-not-fit-all.

"One of the challenges that we have when taking care of patients with bladder cancer is that from one patient to the next, the prognosis, the stage and the response to different kinds of treatment differ," said Dr. Seth Paul Lerner, who is the director of urologic oncology and of the Multidisciplinary Bladder Cancer Program as well as professor of urology and Beth and Dave Swalm Chair in Urologic Oncology at Baylor College of Medicine. "The diverse cancer characteristics pose a challenge when selecting the best treatment for each patient."

At Baylor, Lerner and his colleagues have been studying the genomic underpinnings of these differences among patients with muscle invasive bladder cancer. As part of the Cancer Genome Atlas Research Network group, they reported in 2017 a comprehensive molecular characterization of 412 muscle-invasive bladder cancers that resulted in the identification of five expression-based cancer subtypes. The researchers also reported the different survival outcomes of each subtype. For instance, one of the subtypes named 'neuronal' has a very distinct expression profile and is associated with poor survival and less favorable outcomes.


Author: @DailyCupofYoga

Source: news-medical.net

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