Novel robust biomarkers for human bladder cancer based on activation of intracellular signaling pathways

Abstract

We recently proposed a new bioinformatic algorithm called OncoFinder for quantifying the activation of intracellular signaling pathways. It was proved advantageous for minimizing errors of high-throughput gene expression analyses and showed strong potential for identifying new biomarkers. Here, for the first time, we applied OncoFinder for normal and cancerous tissues of the human bladder to identify biomarkers of bladder cancer. Using Illumina HT12v4 microarrays, we profiled gene expression in 17 cancer and seven non-cancerous bladder tissue samples. These experiments were done in two independent laboratories located in Russia and Canada. We calculated pathway activation strength values for the investigated transcriptomes and identified signaling pathways that were regulated differently in bladder cancer (BC) tissues compared with normal controls. We found, for both experimental datasets, 44 signaling pathways that serve as excellent new biomarkers of BC, supported by high area under the curve (AUC) values. We conclude that the OncoFinder approach is highly efficient in finding new biomarkers for cancer. These markers are mathematical functions involving multiple gene products, which distinguishes them from "traditional" expression biomarkers that only assess concentrations of single genes.

Figure 1. Representation of the Correlation coefficients for pathway activation states depending on the normal/cancerous nature of BC tissue specimens, calculated for the PAS values of the different intracellular signaling pathways for the Comparisons (i) and (ii)

Negative correlation coefficients mean downregulation of a pathway in BC, positive – upregulation. Correlation Moscow/Moscow means correlation coefficients calculated for the Comparison (i); correlation Leth/Leth means correlation coefficients calculated for the Comparison (ii).