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Many newly diagnosed prostate cancers present as low Gleason score tumors that require no treatment intervention. Distinguishing the many indolent tumors from the minority of lethal ones remains a major clinical challenge. We now show that low Gleason score prostate tumors can be distinguished as indolent and aggressive subgroups on the basis of their expression of genes associated with aging and senescence. Using gene set enrichment analysis, we identified a 19-gene signature enriched in indolent prostate tumors. We then further classified this signature with a decision tree learning model to identify three genes--FGFR1, PMP22, and CDKN1A--that together accurately predicted outcome of low Gleason score tumors. Validation of this three-gene panel on independent cohorts confirmed its independent prognostic value as well as its ability to improve prognosis with currently used clinical nomograms. Furthermore, protein expression of this three-gene panel in biopsy samples distinguished Gleason 6 patients who failed surveillance over a 10-year period. We propose that this signature may be incorporated into prognostic assays for monitoring patients on active surveillance to facilitate appropriate courses of treatment.

Original publication

DOI

10.1126/scitranslmed.3006408

Type

Journal article

Journal

Sci Transl Med

Publication Date

11/09/2013

Volume

5

Keywords

Aged, Aging, Animals, Biomarkers, Tumor, Decision Trees, Gene Expression Profiling, Gene Expression Regulation, Neoplastic, Genes, Neoplasm, Humans, Male, Mice, Middle Aged, Models, Biological, Prognosis, Prostatic Neoplasms, RNA, Messenger, Reproducibility of Results, Species Specificity