A four-gene signature predicts disease progression in muscle invasive bladder cancer

Wun Jae Kim, Seon Kyu Kim, Pildu Jeong, Seok Joong Yun, In Chang Cho, Isaac Yi Kim, Sung Kwon Moon, Hong Duck Um, Yung Hyun Choi

    Research output: Contribution to journalArticlepeer-review

    54 Scopus citations


    There are no reliable criteria to handle disease progression of muscle invasive bladder cancer (MIBC), which strongly influences patient survival. Therefore, an accurate predicting method to identify progressive MIBC patients is greatly needed. The aim of this study was to identify a genetic signature associated with disease progression in MIBC. To address this issue, we analyzed three independent cohorts (a training set, test set 1 and test set 2) comprising a total of 128 MIBC patients. Micro array gene expression profiling, including gene network analysis, was performed in the training set to identify a gene expression signature associated with disease progression. The prognostic value of the signature was validated in test set 1 and test set 2 by micro array and real-time reverse transcriptase polymerase chain reaction (RT-PCR), respectively. The determination of gene expression patterns by micro array data analysis identified 1,320 genes associated with disease progression. Gene network analysis of the 1,320 genes suggested that IL1B, S100A8, S100A9 and EGFR were important mediators of MIBC progression. We validated this putative four-gene signature in two independent cohorts (log-rank test, P< 0.05 each, respectively) and estimated the predictive value of the signature by multivariate Cox regression analysis (hazard ratio [HR], 6.24; 95% confidence interval [CI], 1.58-24.61; P= 0.009). Finally, signature-based stratification demonstrated that the four-gene signature was an independent predictor of MIBC progression. In conclusion, a molecular signature defined by four genes represents a promising diagnostic tool for the identification of MIBC patients at high risk of progression.

    Original languageEnglish (US)
    Pages (from-to)478-485
    Number of pages8
    JournalMolecular Medicine
    Issue number5-6
    StatePublished - May 2011

    All Science Journal Classification (ASJC) codes

    • Molecular Medicine
    • Molecular Biology
    • Genetics
    • Genetics(clinical)


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