Genetic signature, identified in mouse model, can predict whether prostate cancer is likely to spread, and whether it responds to anti-androgen therapy. It is also useful in evaluating responses to treatment, according to a study in Nature Cancer. "If we could know in advance which patients will develop metastases, we could start treatments earlier and treat the cancer more aggressively," says the study's senior author, Cory Abate-Shen, PhD, chair of the Department of Molecular Pharmacology and Therapeutics, the Michael and Stella Chernow Professor of Urologic Sciences (in Urology), and professor of pathology & cell biology (in the Herbert Irving Comprehensive Cancer Center) at Columbia University Vagelos College of Physicians and Surgeons.
‘META-16 was found to be highly effective at predicting time to metastasis and response to anti-androgen therapy. It could also be used to develop therapies against metastatic prostate cancer.’"Conversely, patients whose disease is likely to remain confined to the prostate could be spared from getting unnecessary therapy."
Tweet it Now
Majority of the prostate cancers are localized and can be successfully managed by active surveillance or local therapy. But once prostate cancer spreads, it is considered incurable, and five-year survival rates drop to approximately 30%.
"The problem is that with existing tests, it's hard to know which cancers are which," says the study's lead author, Juan M. Arriaga, PhD, associate research scientist in molecular pharmacology and therapeutics at Columbia University Vagelos College of Physicians and Surgeons.
"We miss a lot of aggressive cancers that should have been treated earlier, and we overtreat some slow-growing cancers that probably would not have spread."
Using the mouse model, the researchers discovered that bone metastases have a different molecular profile than that of primary tumors. "By focusing on those differences, we were able to identify 16 genes that drive localized prostate cancer to metastasize," Abate-Shen says.
META-16 was found to be highly effective at predicting time to metastasis and response to anti-androgen therapy (which is used to suppress androgen, the male hormone, which promotes tumor progression). It could also be used to develop therapies against metastatic prostate cancer.