S100A6 has been implicated in a variety of biological functions as well as tumorigenesis. In this study, we investigated the expression status of S100A6 in relation to the clinicopathological features and prognosis of patients with gastric cancer and further explored a possible association of its expression with epigenetic regulation. S100A6 expression was remarkably increased in 67.5% of gastric cancer tissues as compared with matched noncancerous tissues. Statistical analysis demonstrated a clear correlation between high S100A6 expression and various clinicopathological features, such as depth of wall invasion, positive lymph node involvement, liver metastasis, vascular invasion, and tumor-node metastasis stage (P < 0.05 in all cases), as well as revealed that S100A6 is an independent prognostic predictor (P ؍ 0.026) significantly related to poor prognosis (P ؍ 0.0004). Further exploration found an inverse relationship between S100A6 expression and the methylation status of the seventh and eighth CpG sites in the promoter/first exon and the second to fifth sites in the second exon/second intron. In addition, the level of histone H3 acetylation was found to be significantly higher in S100A6-expressing cancer cells. After 5-azacytidine or trichostatin A treatment, S100A6 expression was clearly increased in S100A6 low-expressing cells. In conclusion, our results suggested that S100A6 plays an important role in the progression of gastric cancer, affecting patient prognosis, and is up-regulated by epigenetic regulation. (Am J
Diabetic nephropathy (DN) is a primary cause of renal failure. However, studies providing renal gene expression profiles of diabetic tubulointerstitial injury are scarce and its molecular mechanisms still await clarification. To identify vital genes involved in the diabetic tubulointerstitial injury, three microarray data sets from gene expression omnibus (GEO) were downloaded. A total of 127 differentially expressed genes (DEGs) were identified by limma package. Gene set enrichment analysis (GSEA) plots showed that sister chromatid cohesion was the most significant enriched gene set positively correlated with the DN group while retinoid X receptor binding was the most significant enriched gene set positively correlated with the control group. Enriched Gene Ontology (GO) annotations and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of DEGs mostly included extracellular matrix organization, extracellular space, extracellular matrix structural constituent, and Staphylococcus aureus infection. Twenty hub genes from three significant modules were ascertained by Cytoscape. Correlation analysis and subgroup analysis between hub genes and clinical features of DN showed that ALB, ANXA1, APOH, C3, CCL19, COL1A2, COL3A1, COL4A1, COL6A3, CXCL6, DCN, EGF, HRG, KNG1, LUM, SERPINA3, SPARC, SRGN, and TIMP1 may involve in diabetic tubulointerstitial injury. ConnectivityMap analysis indicated the most significant three compounds are 5182598, thapsigargin and 5224221. In conclusion, this study may provide new insights into the molecular mechanisms underlying diabetic tubulointerstitial injury as well as potential targets for diagnosis and therapeutics of DN.
PLA2G2A may predict survival and might be a potential biomarker for early detection and individualized therapy.
Diabetic nephropathy (DN) is a major cause of end‐stage renal disease. Although intense efforts have been made to elucidate the pathogenesis, the molecular mechanisms of DN remain to be clarified. To identify the candidate genes in the progression of DN, microarray datasets GSE30122, GSE30528, and GSE47183 were downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) were identified, and function enrichment analyses were performed. The protein‐protein interaction network was constructed and the module analysis was performed using the Search Tool for the Retrieval of Interacting Genes and Cytoscape. A total of 61 DEGs were identified. The enriched functions and pathways of the DEGs included glomerulus development, extracellular exosome, collagen binding, and the PI3K‐Akt signaling pathway. Fifteen hub genes were identified and biological process analysis revealed that these genes were mainly enriched in acute inflammatory response, inflammatory response, and blood vessel development. Correlation analysis between unexplored hub genes and clinical features of DN suggested that COL6A3, MS4A6A,PLCE1, TNNC1, TNNI1, TNN2, and VSIG4 may involve in the progression of DN. In conclusion, DEGs and hub genes identified in this study may deepen our understanding of molecular mechanisms underlying the progression of DN, and provide candidate targets for diagnosis and treatment of DN.
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