Background/aim: The proinflammatory protein S100A8, which is expressed in myeloid cells under physiological conditions, is strongly expressed in human cancer tissues. Its role in tumor cell differentiation and tumor progression is largely unclear and virtually unstudied in kidney cancer. In the present study, we investigated whether S100A8 could be a potential anticancer drug target and therapeutic biomarker for kidney cancer, and the underlying molecular mechanisms by exploiting its interaction profile with drugs.
Materials and methods: Microarray-based transcriptomics experiments using Affymetrix HuGene 1.0 ST arrays were applied to renal cell carcinoma specimens from Saudi patients for identification of significant genes associated with kidney cancer. In addition, we retrieved selected expression data from the National Center for Biotechnology Information Gene Expression Omnibus database for comparative analysis and confirmation of S100A8 expression. Ingenuity Pathway Analysis (IPA) was used to elucidate significant molecular networks and pathways associated with kidney cancer. The probable polar and non-polar interactions of possible S100A8 inhibitors (aspirin, celecoxib, dexamethasone and diclofenac) were examined by performing molecular docking and binding free energy calculations. Detailed analysis of bound structures and their binding free energies was carried out for S100A8, its known partner (S100A9), and S100A8-S100A9 complex (calprotectin).
Results: In our microarray experiments, we identified 1,335 significantly differentially expressed genes, including S100A8, in kidney cancer using a cut-off of p<0.05 and fold-change of 2. Functional analysis of kidney cancer-associated genes showed overexpression of genes involved in cell-cycle progression, DNA repair, cell death, tumor morphology and tissue development. Pathway analysis showed significant disruption of pathways of atherosclerosis signaling, liver X receptor/retinoid X receptor (LXR/RXR) activation, notch signaling, and interleukin-12 (IL-12) signaling. We identified S100A8 as a prospective biomarker for kidney cancer and in silico analysis showed that aspirin, celecoxib, dexamethasone and diclofenac binds to S100A8 and may inhibit downstream signaling in kidney cancer.
Conclusion: The present study provides an initial overview of differentially expressed genes in kidney cancer of Saudi Arabian patients using whole-transcript, high-density expression arrays. Our analysis suggests distinct transcriptomic signatures, with significantly high levels of S100A8, and underlying molecular mechanisms contributing to kidney cancer progression. Our docking-based findings shed insight into S100A8 protein as an attractive anticancer target for therapeutic intervention in kidney cancer. To our knowledge, this is the first structure-based docking study for the selected protein targets using the chosen ligands.
Keywords: Kidney cancer; S100A8; Saudi Arabia; anticancer target; docking; gene expression profiling.