Abstract
Purpose: We aimed to develop and validate a novel gene signature from published data and improve the prediction of survival in muscle-invasive bladder cancer (MIBC).Methods: We searched the published gene signatures associated with the overall survival (OS) of MIBC and compiled all 274 genes to develop a novel gene signature. RNAseq data of TCGA (the Cancer Genome Atlas) bladder cohort were downloaded. All genes were included in a univariate Cox hazard ratio model. We then used a reduced multivariate Cox regression model, which included only genes achieving P < 0.05 in the univariate model. A total of 172 patients at Fudan University Shanghai Cancer Center (FUSCC) and 61 patients from GEO datasets were used as an external validation set.Results: A total of 327 patients in the TCGA cohort were enrolled. We identified 274 genes from eight published papers on the OS of MIBC. Using the TCGA database, we identified 12 genes that correlated with OS (P < 0.05 in both univariate and multivariate analyses). By integrating these genes with the RT-qPCR data in our validation dataset and GEO datasets, we confirmed that the power for predicting OS of the 12-gene panel (AUC of 0.741 and 0.727, respectively) was higher than just clinical data (including gender, age, T stage, grade, and N stage) alone in the TCGA and FUSCC cohort (AUC of 0.667 and 0.631, respectively). Additionally, upon combining the clinical data and 12-gene panel together, the AUC increased to 0.768, 0.757, and 0.88 in the TCGA, FUSCC and GSE13507 cohorts, respectively.Conclusions: Applying published gene signatures and TCGA data, we successfully built and externally validated a novel 12-gene signature for the survival of MIBC.Brief ExplanationWe systemically reviewed all published prognostic gene signatures of muscle-invasive bladder cancer (MIBC) and integrated the genes in the TCGA MIBC cohort. This new gene panel was validated in a newly established MIBC cohort in GEO and FUSCC. This method can help update the previous established panels in a new way.
Highlights
Bladder cancer is the fourth most common cancer, with an incidence of ∼7% among all male malignancies, and the eighth most common cause of mortality in men [1]
(9, 13–19) that met our requirements; all genes included in these studies are featured in our candidate signature gene list after dereplication
Since the gene names in the gene models from the different reports were not consistent, we unified the IDs of all 274 genes into their official gene names to find the corresponding genes in the full the Cancer Genome Atlas (TCGA) gene list
Summary
Bladder cancer is the fourth most common cancer, with an incidence of ∼7% among all male malignancies, and the eighth most common cause of mortality in men [1]. Despite the considerable progress in the treatment of bladder cancer, the prognosis of patients with muscle-invasive bladder cancer (MIBC) remains poor, which is partly attributable to the heterogeneity of disease characteristics [4] This indicates the need for an accurate prognostic assessment after radical cystectomy that is essential for treatment decision-making, patient counseling, and most importantly for defining the indication of adjuvant chemotherapy [5]. The American Joint Committee on Cancer (AJCC) TNM staging system, which has been appropriately validated, is the most widely used prognostic model to predict outcome in patients treated with radical cystectomy [6] These staging systems provide useful estimates of clinical outcome, their major limitation is the difficulty of incorporating novel clinical information, such as molecular markers or more complex bioinformatics. We planned a study to integrate all of the published genes with TCGA RNAseq data to develop a novel gene panel and to validate the panel in our own cohort by qRT-PCR
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