Discovery and Validation of Novel Expression Signature for Postcystectomy Recurrence in High-Risk Bladder Cancer

• Published in: JNCI : Journal of the National Cancer Institute Vol. 106; no. 11; p. 1
• Main Authors: MITRA, Anirban P, LAM, Lucia L, SKINNER, Eila C, DAVICIONI, Elai, DANESHMAND, Siamak, BLACK, Peter C, GHADESSI, Mercedeh, ERHO, Nicholas, VERGARA, Ismael A, ALSHALALFA, Mohammed, BUERKI, Christine, HADDAD, Zaid, SIEROCINSKI, Thomas, TRICHE, Timothy J
• Format: Journal Article
• Language: English
• Published: Cary, NC Oxford University Press 01.11.2014; Oxford Publishing Limited (England)
• Subjects: Adult; Aged; Area Under Curve; Biological and medical sciences; Bladder cancer; Cystectomy; Female; Gene expression; Gene Expression Regulation, Neoplastic; Humans; Kaplan-Meier Estimate; Lymphatic Metastasis; Male; Medical sciences; Middle Aged; Multiple tumors. Solid tumors. Tumors in childhood (general aspects); Neoplasm Invasiveness; Neoplasm Recurrence, Local - epidemiology; Neoplasm Recurrence, Local - genetics; Nephrology. Urinary tract diseases; Nomograms; Predictive Value of Tests; Risk factors; RNA, Neoplasm - analysis; ROC Curve; Surgery; Transcriptome; Tumors; Tumors of the urinary system; Urinary Bladder Neoplasms - epidemiology; Urinary Bladder Neoplasms - genetics; Urinary Bladder Neoplasms - pathology; Urinary Bladder Neoplasms - surgery; Urinary system involvement in other diseases. Miscellaneous; Urinary tract. Prostate gland; Validation studies; Validation; High risk; Relapse; Urinary system disease; Cancerology; Bladder disease; Urinary tract disease; Malignant tumor; Bladder cancer; Cancer
• ISSN: 0027-8874; 1460-2105
• DOI: 10.1093/jnci/dju290

Nearly half of muscle-invasive bladder cancer patients succumb to their disease following cystectomy. Selecting candidates for adjuvant therapy is currently based on clinical parameters with limited predictive power. This study aimed to develop and validate genomic-based signatures that can better identify patients at risk for recurrence than clinical models alone. 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. Genomic (GC) and clinical (CC) classifiers for predicting recurrence were developed on a discovery set (n = 133). Performances of GC, CC, an independent clinical nomogram (IBCNC), and genomic-clinicopathologic classifiers (G-CC, G-IBCNC) were assessed in the discovery and independent validation (n = 66) sets. GC was further validated on four external datasets (n = 341). Discrimination and prognostic abilities of classifiers were compared using area under receiver-operating characteristic curves (AUCs). All statistical tests were two-sided. A 15-feature GC was developed on the discovery set with area under curve (AUC) of 0.77 in the validation set. This was higher than individual clinical variables, IBCNC (AUC = 0.73), and comparable to CC (AUC = 0.78). Performance was improved upon combining GC with clinical nomograms (G-IBCNC, AUC = 0.82; G-CC, AUC = 0.86). G-CC high-risk patients had elevated recurrence probabilities (P < .001), with GC being the best predictor by multivariable analysis (P = .005). Genomic-clinicopathologic classifiers outperformed clinical nomograms by decision curve and reclassification analyses. GC performed the best in validation compared with seven prior signatures. GC markers remained prognostic across four independent datasets. The validated genomic-based classifiers outperform clinical models for predicting postcystectomy bladder cancer recurrence. This may be used to better identify patients who need more aggressive management.