Predictive Value of Progression-related Gene Classifier in Primary Non-muscle Invasive Bladder Cancer

Overview

Journal Mol Cancer

Publisher Biomed Central

Specialties Molecular Biology
Oncology

Date 2010 Jan 12

PMID 20059769

Citations 229

Authors

Wun-Jae Kim

Eun-Jung Kim

Seon-Kyu Kim

Yong-June Kim

Yun-Sok Ha

Pildu Jeong

Min-Ju Kim

Seok-Joong Yun

Keon Myung Lee

Sung-Kwon Moon

Sang-Cheol Lee

Eun-Jong Cha

Suk-Chul Bae

Affiliations

Soon will be listed here.

Abstract

Background: While several molecular markers of bladder cancer prognosis have been identified, the limited value of current prognostic markers has created the need for new molecular indicators of bladder cancer outcomes. The aim of this study was to identify genetic signatures associated with disease prognosis in bladder cancer.

Results: We used 272 primary bladder cancer specimens for microarray analysis and real-time reverse transcriptase polymerase chain reaction (RT-PCR) analysis. Microarray gene expression analysis of randomly selected 165 primary bladder cancer specimens as an original cohort was carried out. Risk scores were applied to stratify prognosis-related gene classifiers. Prognosis-related gene classifiers were individually analyzed with tumor invasiveness (non-muscle invasive bladder cancer [NMIBC] and muscle invasive bladder cancer [MIBC]) and prognosis. We validated selected gene classifiers using RT-PCR in the original (165) and independent (107) cohorts. Ninety-seven genes related to disease progression among NMIBC patients were identified by microarray data analysis. Eight genes, a progression-related gene classifier in NMIBC, were selected for RT-PCR. The progression-related gene classifier in patients with NMIBC was closely correlated with progression in both original and independent cohorts. Furthermore, no patient with NMIBC in the good-prognosis signature group experienced cancer progression.

Conclusions: We identified progression-related gene classifier that has strong predictive value for determining disease outcome in NMIBC. This gene classifier could assist in selecting NMIBC patients who might benefit from more aggressive therapeutic intervention or surveillance.

Citing Articles

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