Purpose: Selecting muscle-invasive bladder cancer patients for adjuvant therapy is currently based on clinical variables with limited power. We hypothesized that genomic-based signatures can outperform clinical models to identify patients at higher risk. Method:Transcriptome-wide expression profiles were generated using 1.4 million feature-arrays on archival tumors from 225 patients who underwent radical cystectomy and had muscle-invasive and/or node-positive bladder cancer. A 15-feature GC was developed on the discovery set with area under curve (AUC) of 0.77 in the validation set. A cohort comprised of 225 patients with organ-confined, muscle-invasive (pT2N0M0),extravesical (pT3-4aN0M0), and node-positive (pTanyN1-3M0) UCB who underwent radicalcystectomy at the University of Southern California between 1998 and 2004 was used. Each patient had aminimum two-year follow-up post-cystectomy unless they recurred prior to that date. Patients receiving neoadjuvant chemotherapy, and those with clinical evidence of lymphadenopathy or distant metastasis at diagnosis were excluded.
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