PURPOSE: Bladder cancer is a common malignancy characterized by a poor clinical outcome when tumors progress into invasive disease. We sought to define genetic signatures characteristic of aggressive clinical behavior in advanced bladder tumors. METHODS: Oligonucleotide arrays were utilized to analyze the transcript profiles of 105 bladder tumors: 33 superficial, 72 invasive lesions, and 52 normal urothelium. Hierarchical clustering and supervised algorithms were used to classify and stratify bladder tumors on the basis of stage, node metastases, and overall survival. Immunohistochemical analyses on bladder cancer tissue arrays (n = 294 cases) served to validate associations between marker expression, staging and outcome. RESULTS: Hierarchical clustering classified normal urothelium, superficial, and invasive tumors with 82.2% accuracy, and stratified bladder tumors on the basis of clinical outcome. Predictive algorithms rendered an 89%-correct rate for tumor staging using genes differentially expressed between superficial and invasive tumors. Accuracies of 82% and 90% were obtained for predicting overall survival when considering all patients with bladder cancer or only patients with invasive disease, respectively. A genetic profile consisting of 174 probes was identified in those patients with positive lymph nodes and poor survival. Two independent Global Test runs confirmed the robust association of this profile with lymph node metastases (P = 7.3(-13)) and overall survival (P = 1.9(-14)) simultaneously. Immunohistochemical analyses on tissue arrays sustained the significant association of synuclein with tumor staging and clinical outcome (P = .002). CONCLUSION: Gene profiling provides a genomic-based classification scheme of diagnostic and prognostic utility for stratifying advanced bladder cancer. Identification of this poor outcome profile could assist in selecting patients who may benefit from more aggressive therapeutic intervention.
PURPOSE:Bladder cancer is a common malignancy characterized by a poor clinical outcome when tumors progress into invasive disease. We sought to define genetic signatures characteristic of aggressive clinical behavior in advanced bladder tumors. METHODS:Oligonucleotide arrays were utilized to analyze the transcript profiles of 105 bladder tumors: 33 superficial, 72 invasive lesions, and 52 normal urothelium. Hierarchical clustering and supervised algorithms were used to classify and stratify bladder tumors on the basis of stage, node metastases, and overall survival. Immunohistochemical analyses on bladder cancer tissue arrays (n = 294 cases) served to validate associations between marker expression, staging and outcome. RESULTS: Hierarchical clustering classified normal urothelium, superficial, and invasive tumors with 82.2% accuracy, and stratified bladder tumors on the basis of clinical outcome. Predictive algorithms rendered an 89%-correct rate for tumor staging using genes differentially expressed between superficial and invasive tumors. Accuracies of 82% and 90% were obtained for predicting overall survival when considering all patients with bladder cancer or only patients with invasive disease, respectively. A genetic profile consisting of 174 probes was identified in those patients with positive lymph nodes and poor survival. Two independent Global Test runs confirmed the robust association of this profile with lymph node metastases (P = 7.3(-13)) and overall survival (P = 1.9(-14)) simultaneously. Immunohistochemical analyses on tissue arrays sustained the significant association of synuclein with tumor staging and clinical outcome (P = .002). CONCLUSION: Gene profiling provides a genomic-based classification scheme of diagnostic and prognostic utility for stratifying advanced bladder cancer. Identification of this poor outcome profile could assist in selecting patients who may benefit from more aggressive therapeutic intervention.
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Authors: Woonyoung Choi; Sima Porten; Seungchan Kim; Daniel Willis; Elizabeth R Plimack; Jean Hoffman-Censits; Beat Roth; Tiewei Cheng; Mai Tran; I-Ling Lee; Jonathan Melquist; Jolanta Bondaruk; Tadeusz Majewski; Shizhen Zhang; Shanna Pretzsch; Keith Baggerly; Arlene Siefker-Radtke; Bogdan Czerniak; Colin P N Dinney; David J McConkey Journal: Cancer Cell Date: 2014-02-10 Impact factor: 31.743
Authors: Jeffrey S Damrauer; Katherine A Hoadley; David D Chism; Cheng Fan; Christopher J Tiganelli; Sara E Wobker; Jen Jen Yeh; Matthew I Milowsky; Gopa Iyer; Joel S Parker; William Y Kim Journal: Proc Natl Acad Sci U S A Date: 2014-02-11 Impact factor: 11.205