Molecular Test Identifies Indolent Prostate Cancer

The three-gene biomarker, in conjunction with existing cancer-staging tests, could help physicians better determine which men with early prostate cancer can be safely followed with active surveillance and spared the risks of prostate removal or other invasive treatment.

Scientists at Columbia University Medical Center (New York, NY, USA) working with other intuitions, designed a bioinformatics approach to test the hypothesis that indolent and aggressive prostate tumors can be distinguished on the basis of expression of genes associated with cellular processes of aging and senescence.

In a blinded retrospective study, the team tested the prognostic accuracy of the three-gene panel on initial biopsy specimens from 43 patients who had been monitored with active surveillance for at least 10 years, from 1992 to 2012. All the patients had first been diagnosed with low-risk prostate cancer. Of the 43 patients, 14 ultimately developed advanced prostate cancer. All 14 were correctly identified by the test.

The scientists used a technique called gene set enrichment analysis to identify 19 genes, from which three genes, fibroblast growth factor receptor 1 (FGFR1), peripheral myelin protein-22 (PMP22), and cyclin-dependent kinase inhibitor 1 (CDKN1A), could together accurately predict the outcome of seemingly low-risk tumors Biopsy samples were obtained from patients and immunohistochemical analyses were performed with anti-FGFR1 (Abcam; Cambridge, MA, USA), anti-PMP22 (Sigma; St. Louis, MO, USA), and anti-CDKN1A (BD Pharmingen; St. Jose, CA, USA). The percentage of positive tumor cells and staining intensities were assessed for each core or biopsy, and composite scores were generated.

Mitchell C. Benson, MD, PhD, a professor of urology and a senior author of the study, said, “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.” The authors concluded that the three-gene signature may be incorporated into prognostic assays for monitoring patients on active surveillance to facilitate appropriate courses of treatment. The study was published on September 13, 2013, in the journal Science Translational Medicine.

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