Identification of a 13‑mRNA signature for predicting disease progression and prognosis in patients with bladder cancer
- Hubin Yin
- Chen Zhang
- Xin Gou
- Weiyang He
- Daoju Gan
Affiliations: Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, P.R. China, Department of Obstetrics and 4The Central Laboratory, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, P.R. China
- Published online on: December 12, 2019 https://doi.org/10.3892/or.2019.7429
Copyright: © Yin
et al. This is an open access article distributed under the
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There are no reliable criteria to assess risk of progression of non‑muscle invasive bladder cancer to muscle invasive bladder cancer. The aim of the present study was to identify potential markers based on gene expression profiling to improve predictive power of disease progression and prognosis in patients with bladder cancer. In the present study, we screened seventy‑three differentially expressed genes by analyzing bladder cancer samples with or without progression. Forty‑seven prognosis‑related genes were screened, 13 of which were identified to build a progression‑associated gene signature using the LASSO regression method. Based on this 13‑mRNA signature, patients were divided into high‑ and low‑risk groups, with different prognostic outcomes. The gene signature was an independent prognostic factor for overall survival. Receiver operating characteristic analysis suggested that the signature performed well in the validation cohort and its predictive power outperformed other several published signatures. CTHRC1, MMP11, AEBP1, SNCAIP, COL1A1 and S100A8 were identified as hub genes and their expression levels were detected using reverse transcriptase‑quantitative polymerase chain reaction. The expression of CTHRC1 was elevated in aggressive bladder cancer compared with non‑invasive type, which suggests CTHRC1 may be a valuable biomarker for prediction of prognosis and progression of bladder cancer. Collectively, this 13‑mRNA signature may be useful in predicting disease progression and prognosis, thereby contributing to individualized management of patients with bladder cancer.