Identification of latent biomarkers in connection with progression and prognosis in oral cancer by comprehensive bioinformatics analysis

Abstract

Background Oral cancer (OC) is a common and dangerous malignant tumor with a low survival rate. However, the micro level mechanism has not been explained in detail. Methods Gene and miRNA expression micro array data were extracted from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) and miRNAs (DE miRNAs) were identified by R software. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of genes and genomes (KEGG) pathway analysis were used to assess the potential molecular mechanisms of DEGs. Cytoscape software was utilized to construct protein–protein interaction (PPI) network and miRNA-gene network. Central genes were screened out with the participation of gene degree, molecular complex detection (MCODE) plugin, and miRNA-gene network. Then, the identified genes were checked by The Cancer Genome Atlas (TCGA) gene expression profile, Kaplan-Meier data, Oncomine, and the Human Protein Atlas database. Receiver operating characteristic (ROC) curve was drawn to predict the diagnostic efficiency of crucial gene level in normal and tumor tissues. Univariate and multivariate Cox regression were used to analyze the effect of dominant genes and clinical characteristics on the overall survival rate of OC patients. Results Gene expression data of gene expression profiling chip(GSE9844, GSE30784, and GSE74530) were obtained from GEO database, including 199 tumor and 63 non-tumor samples. We identified 298 gene mutations, including 200 upregulated and 98 downregulated genes. GO functional annotation analysis showed that DEGs were enriched in extracellular structure and extracellular matrix containing collagen. In addition, KEGG pathway enrichment analysis demonstrated that the DEGs were significantly enriched in IL-17 signaling pathway and PI3K-Akt signaling pathway. Then, we detected three most relevant modules in PPI network. Central genes (CXCL8, DDX60, EIF2AK2, GBP1, IFI44, IFI44L, IFIT1, IL6, MMP9,CXCL1, CCL20, RSAD2, and RTP4) were screened out with the participation of MCODE plugin, gene degree, and miRNA-gene network. TCGA gene expression profile and Kaplan-Meier analysis showed that high expression of CXCL8, DDX60, IL6, and RTP4 was associated with poor prognosis in OC patients, while patients with high expression of IFI44L and RSAD2 had a better prognosis. The elevated expression of CXCL8, DDX60, IFI44L, RSAD2, and RTP44 in OC was verified by using Oncomine database. ROC curve showed that the mRNA levels of these five genes had a helpful diagnostic effect on tumor tissue. The Human Protein Atlas database showed that the protein expressions of DDX60, IFI44L, RSAD2, and RTP44 in tumor tissues were higher than those in normal tissues. Finally, univariate and multivariate Cox regression showed that DDX60, IFI44L, RSAD2, and RTP44 were independent prognostic indicators of OC. Conclusion This study revealed the potential biomarkers and relevant pathways of OC from publicly available GEO database, and provided a theoretical basis for elucidating the diagnosis, treatment, and prognosis of OC.

Prognostic biomarker IL17A correlated with immune infiltrates in head and neck cancer

“…Recent studies suggested a pathogenic role of IL-17A in cancer. For example, the IL17 and PI3K-Akt signaling pathway are enriched in oral cancer [ 25 ]. The canonical IL-23/IL-17A pathway is activated in the tracheal mucosa of idiopathic subglottic stenosis patients [ 26 ].…”

MicroRNA-155 expression is associated with pulpitis progression by targeting SHIP1

“…Studies have stated that PI3K/AKT can be a pro-in ammation effector in oral diseases like periodontitis [44]. They can also affect the process of different kinds of oral squamous cancers [45]. However, in pulpitis and dental pulp speci c cells like the odontoblasts, their relationship still needs experimental evidence.…”

Antiviral DExD/H-box helicase 60 selectively inhibits translation from type II internal ribosome entry sites

“…Given their diverse cell biological roles, DExD/H box RNA helicases are associated with the development of many diseases such as cancer, aging, neurologic and immunologic disorders, and infectious disease (Steimer & Klostermeier, 2012). DDX60 expression has been shown to be dysregulated and associated with advanced disease and response to treatment of different cancers, such as oral cancers (Fu et al, 2016; Reyimu et al, 2021), gliomas (Zhang et al, 2021), and breast cancers (Ríos-Romero et al, 2020; Xin et al, 2020). Additionally, DNA methylation variability in DDX60 is associated with cases of mixed connective tissue disease (Carnero-Montoro et al, 2019).…”