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Hormone therapy is a standard treatment for metastatic prostate cancer patients but may also benefit a subset of localized prostate cancer patients who underwent surgery but have particularly aggressive disease. However, it is not clear how to identify which localized disease patients should receive hormone therapy, and the historical protocol of trial-and-error brings with it significant and unnecessary side effects for those patients who end up not responding to the treatment — hence it is not commonly used in this setting. What if a doctor could know in advance whether a patient would benefit from hormone therapy? Thanks to a new PCF-funded study lead by Dr. Felix Feng at University of California San Francisco, that may be what’s coming.

So how did they do it? Researchers repurposed a biomarker test, called PAM50, that has been used for over a decade to identify which breast cancer patients are the best candidates for hormone treatment. They used the PAM50 test to divide prostate tumors into three subtypes based on gene expression. Their results revealed that starting hormone treatment after surgery reduced the spread of the tumor in one of the three types, known as luminal B, found to be a particularly aggressive, hormone-dependent form affecting about 1/3 of men with the disease.

For patients with luminal B tumors, this research may lead to new treatment protocols, such as the earlier use of hormone therapy. However, for men with one of the other two subtypes, this test can avoid hormone therapy and it’s frustrating side effects, such as fatigue, sexual dysfunction, and other conditions.

Should you ask your doctor for this test? Actually, because PAM50 is available clinically, some doctors (particularly those in academic centers) may now begin using it to select patients to receive hormone therapy post-surgery. Additionally, Dr. Feng and his co-author Dr. Daniel Spratt of the University of Michigan will validate their results in a large prospective clinical trial that is anticipated to start later this year.