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Five subtypes of prostate cancer identified, paving way for more personalized treatments

MRI provides the best picture of primary prostate cancer, but ordinary MRI (left) must be enhanced with diffusion weighted (center) or dynamic contrast enhanced (right) technologies to give the optimum view of the tumor. (Courtesy of Dr. Oguz Akin, Memorial Sloan Kettering Cancer Center)
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Through genomic profiling of 259 men with prostate cancer, scientists have identified five groups of prostate cancer with distinct DNA signatures.

The discovery represents a major advance as researchers can now begin trying to tailor therapies to those subtypes. The approach has worked well in breast cancer and helped millions avoid the unnecessary cost, pain and time spent on treatments that are destined to fail.

[Obama touts ‘lifesaving’ potential of personalized medicine]

Such work is the backbone of President Obama's $215 million precision medicine initiative announced in January, which aims to pioneer a new approach to how we treat disease by moving away from a "one-size-fits-all" approach to medicine to one that takes into account things like a person’s genetic makeup, or the genetic profile of a tumor.

[A new way to study cancer and its treatments]

The prostate cancer study, reported in EBioMedicine, used samples from 482 tumors from those men, who were part of studies in Cambridge, Britain, and Stockholm. The scientists identified 100 genes associated with prostate cancer, including 94 that had not been previously associated with the disease.

Most importantly, they found that a small subset of the 100 genes predicted poor prognosis better than any other method that had been used in a clinic setting.

[He had a 3.5-pound tumor and months to live. Here’s how he survived.]

"For the first time in prostate cancer this study demonstrates the importance of integrated genomic analyses incorporating both benign and tumour tissue data in identifying molecular alterations leading to the generation of robust gene sets that are predictive of clinical outcome in independent patient cohorts," the researchers wrote. They said this information could be "used for early detection of aggressive cases in a clinical setting, and inform treatment decisions."

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