A three-gene biomarker could be used as a predictor of prostate cancer growth to help doctors identify which patients need earlier treatment.
Using a technique called gene set enrichment analysis and a computer algorithm, researchers at the Herbert Irving Comprehensive Cancer Center at Columbia University Medical Center identified three genes that can be used to predict whether seemingly low-risk prostate cancer will remain slow-growing or will be aggressive.
"The problem with existing tests is that we cannot identify the small percentage of slow-growing tumors that will eventually become aggressive and spread beyond the prostate," said investigator Dr. Mitchell Benson, George F. Cahill Professor of Urology and chair of urology at CUMC.
With the use of existing cancer-staging tests plus the three-gene biomarker, which measures the level of expression of three genes associated with aging, researchers predict that physicians could better determine which men with early prostate cancer require regular testing and monitoring, known as "active surveillance." The three-gene biomarker test ideally would eliminate the need for unnecessary prostate removal or other invasive treatment.
To find the three-gene biomarker, researchers focused on genes related to aging, zeroing in on those affected by cellular senescence, a natural process that plays a role in tumor suppression and has been associated with benign prostate lesions in mouse models and in humans. Researchers identified 19 potential genes in a mouse model of slow-growing prostate cancer. Using a computer algorithm, they identified three genes--FGFR1, PMP22, and CDKN1A--that together can accurately predict the outcome of tumors that appear to be low-risk. Conversely, tumors that test negative for the biomarker are deemed aggressive.
Researchers tested their three-gene biomarker test using tissue samples of 43 patients who had been monitored at CUMC for at least 10 years. Out of those patients, 14 eventually developed advanced prostate cancer. The test was able to correctly identify all 14 patients. The findings are published online in the journal Science Translational Medicine.
A larger clinical trial is planned to further evaluate the test.
- read the press release