Identification of S100A8-correlated genes for prediction of disease progression in non-muscle invasive bladder cancer

Abstract

Background: S100 calcium binding protein A8 (S100A8) has been implicated as a prognostic indicator in several types of cancer. However, previous studies are limited in their ability to predict the clinical behavior of the cancer. Here, we sought to identify a molecular signature based on S100A8 expression and to assess its usefulness as a prognostic indicator of disease progression in non-muscle invasive bladder cancer (NMIBC).

Methods: We used 103 primary NMIBC specimens for microarray gene expression profiling. The median follow-up period for all patients was 57.6 months (range: 3.2 to 137.0 months). Various statistical methods, including the leave-one-out cross validation method, were applied to identify a gene expression signature able to predict the likelihood of progression. The prognostic value of the gene expression signature was validated in an independent cohort (n = 302).

Results: Kaplan-Meier estimates revealed significant differences in disease progression associated with the expression signature of S100A8-correlated genes (log-rank test, P < 0.001). Multivariate Cox regression analysis revealed that the expression signature of S100A8-correlated genes was a strong predictor of disease progression (hazard ratio = 15.225, 95% confidence interval = 1.746 to 133.52, P = 0.014). We validated our results in an independent cohort and confirmed that this signature produced consistent prediction patterns. Finally, gene network analyses of the signature revealed that S100A8, IL1B, and S100A9 could be important mediators of the progression of NMIBC.

Conclusions: The prognostic molecular signature defined by S100A8-correlated genes represents a promising diagnostic tool for the identification of NMIBC patients that have a high risk of progression to muscle invasive bladder cancer.

Figure 1

Expression of S100A8 and progression of non-muscle invasive bladder cancer. A: Expression of S100A8 in 103 patients from the original cohort. B: Kaplan-Meier curves showing time to progression in the original cohort. C: Kaplan-Meier curves showing time to progression in the independent European cohort.

Figure 2

Gene expression pattern of S100A8-correlated genes and progression of two clusters. A: Gene expression patterns of S100A8 and its correlated genes. A total of 1,015 genes whose expression patterns are highly correlated with S100A8 were selected for cluster analysis (Pearson correlation test, P < 0.001, r < -0.3 or r > 0.3). Patients were divided into two groups: high S100A8 cluster (HSC) and low S100A8 cluster (LSC). B: Kaplan-Meier curves showing time to progression. The progression rate of HSC patients was significantly higher than that of LSC patients (log-rank test, P < 0.001).

Figure 3

Independent validation of the prognostic value of the signature. A: The validation strategy used for the construction of prediction models and the evaluation of predicted outcomes based on gene expression signature. B: Kaplan-Meier plots of progression of NMIBC patients from an independent European cohort predicted by compound covariate predictor (CCP), Bayesian compound covariate predictor (BCC), linear discriminator analysis (LDA), nearest centroid classification (NC), and support vector machines (SVM).

Figure 4

Functional classification of S100A8-correlated genes. Classification enrichment was determined using Ingenuity Pathway Analysis software. The threshold of significance was -log (P = 0.05).

Figure 5

Gene networks enriched with genes associated with S100A8. Gene networks of 1,015 genes that highly correlated with S100A8. Up- and down-regulated genes in the high S100A8 cluster (HSC) group are indicated in red and green, respectively. The intensity of color is indicative of the degree of over- or under-expression. Genes without highlighted color are not part of the progression signature but are associated with the regulated genes. Each line and arrow represents functional and physical interactions between the genes and the direction of regulation reported in the literature.

Figure 6

Comparison of expression levels between high S100A8 cluster (HSC) and low S100A8 cluster (LSC) patients. Two group box plot comparing expression levels of S100A8 (A), IL1B (B), and S100A9 (C) in HSC and LSC patients. P-value was obtained by two-sample t-test between HSC and LSC. The value of r indicates the correlation coefficient value of the gene compared with S100A8.