Identification of key pathways and genes in nasopharyngeal carcinoma based on WGCNA.

We aim to identify the potential genes and signaling pathways associated with the nasopharyngeal carcinoma (NPC) prognosis using Weighted Gene Co-Expression Network Analysis (WGCNA). Gene Expression Omnibus (GEO) query was utilized to download two NPC mRNA microarray data. WGCNA was conducted on differentially expressed genes (DEGs) to obtain tumor-associated gene modules. Genes in core modules were intersected with DEGs for gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis. GSE102349 dataset was devoted to identifying prognostic hub genes by survival analysis and the results were confirmed by quantitative polymerase chain reaction (qPCR). Co-expression networks were built, and we detected 12 gene modules. The Brown module and Magenta module were extremely associated with NPC samples. GO functional analysis and KEGG pathway analysis was carried out to the genes in the Brown and Magenta modules. Our data indicated that DEGs in Brown module and Magenta module were correlated with the biological regulation, metabolic process, reproduction, and cellular proliferation. Twenty-six hub genes were obtained and were considered to be closely related to NPC. GSE102349 dataset was devoted to identifying prognostic hub genes by survival analysis. The expression of IL33, MPP3 and SLC16A7 in GSE102349 dataset was significantly correlated with the progression-free survival (PFS). The results of qPCR indicated a strong correlation between SLC16A7 expression and the overall survival (OS). WGCNA contributed to the detection of gene modules and identification of hub genes and crucial genes. These crucial genes might be potential targets for pharmaceutic therapies with potential clinical significance.

Dai Y ，Chen W ，Huang J ，Xie L ，Lin J ，Chen Q ，Jiang G ，Huang C ... -  《-》

Identification of four key biomarkers and small molecule drugs in nasopharyngeal carcinoma by weighted gene co-expression network analysis.

Pan X ，Liu JH 《-》

Screening of core genes and prediction of ceRNA regulation mechanism of circRNAs in nasopharyngeal carcinoma by bioinformatics analysis.

Background: Nasopharyngeal carcinoma (NPC) represents a highly aggressive malignant tumor. Competing endogenous RNAs (ceRNA) regulation is a common regulatory mechanism in tumors. The ceRNA network links the functions between mRNAs and ncRNAs, thus playing an important regulatory role in diseases. This study screened the potential key genes in NPC and predicted regulatory mechanisms using bioinformatics analysis. Methods: The merged microarray data of three NPC-related mRNA expression microarrays from the Gene Expression Omnibus (GEO) database and the expression data of tumor samples or normal samples from the nasopharynx and tonsil in The Cancer Genome Atlas (TCGA) database were both subjected to differential analysis and Weighted Gene Co-expression Network Analysis (WGCNA). The results from two different databases were intersected with WGCNA results to obtain potential regulatory genes in NPC, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses. The hub-gene in candidate genes was discerned through Protein-Protein Interaction (PPI) analysis and its upstream regulatory mechanism was predicted by miRwalk and circbank databases. Results: Totally 68 upregulated genes and 96 downregulated genes in NPC were screened through GEO and TCGA. According to WGCNA, the NPC-related modules were screened from GEO and TCGA analysis results, and the genes in the modules were obtained. After the results of differential analysis and WGCNA were intersected, 74 differentially expressed candidate genes associated with NPC were discerned. Finally, fibronectin 1 (FN1) was identified as a hub-gene in NPC. Prediction of upstream regulatory mechanisms of FN1 suggested that FN1 may be regulated by ceRNA mechanisms involving multiple circRNAs, thereby influencing NPC progression through ceRNA regulation. Conclusion: FN1 is identified as a key regulator in NPC development and is likely to be regulated by numerous circRNA-mediated ceRNA mechanisms.

Chen H ，Shi X ，Ren L ，Wan Y ，Zhuo H ，Zeng L ，SangDan W ，Wang F ... -  《-》

Differentially Infiltrated Identification of Novel Diagnostic Biomarkers Associated with Immune Infiltration in Nasopharyngeal Carcinoma.

The prognostic value of tumor-infiltrating immune cells has been widely studied in nasopharyngeal carcinoma (NPC). However, the role of tumor-infiltrating immune cells in the diagnosis of NPC has not been fully elucidated. Thus, tumor-infiltrating immune cell-related biomarkers in the diagnosis of NPC patients were explored in the current study. Gene expression profiles of NPC patients were downloaded from the Gene Expression Omnibus (GEO) database. Differentially infiltrating immune cells (DDICs) between NPC and control samples were analyzed by the CIBERSORT algorithm. Weighted gene coexpression network analysis (WGCNA) was performed to screen hub genes significantly correlated with DDIC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of hub genes were performed with R package clusterProfiler. The diagnostic value of hub genes was evaluated by receiver operating characteristic (ROC) curves. RT-qPCR was conducted to validate the expression patterns of diagnostic markers in NPC and adjacent control tissues. The correlations between diagnostic markers and immunomodulators were analyzed using the TISIDB. The protein-protein interaction (PPI) network based on immunomodulators significantly associated with diagnostic biomarkers was constructed and visualized by STRING. The functional enrichment analysis of genes in the PPI network was analyzed by the WebGestalt online tool. The abundances of memory B cells, plasma cells, follicular helper T cells, activated NK cells, M0 macrophages, M1 macrophages, M2 macrophages, resting mast cells, and activated mast cells were significantly different between NPC and control samples. Dark orange was identified as the hub module, with a total of 371 genes associated with memory B cells, plasma cells, and M0 and M1 macrophages defined as hub genes, which were enriched into immune-related biological processes and pathways. FCER2, KHDRBS2, and IGSF9 were considered diagnostic biomarkers with areas under ROC curves as 0.985, 0.978, and 0.975, respectively. Moreover, real-time reverse transcriptase-polymerase chain reaction (RT-qPCR) suggested that the expression patterns of FCER2, KHDRBS2, and IGSF9 were consistent with the results in GEO datasets. TISIDB analysis revealed that FCER2, KHDRBS2, and IGSF9 had a strong association with 8 immunoinhibitors (BTLA, CD160, CD96, LAG3, PDCD1, TIGIT, CD244, and TGFB1) and 11 immunostimulators (CD27, CD28, CD40LG, CD48, ICOS, KLRC1, KLRK1, TMIGD2, TNFRSF13C, CXCR4, and C10 or f54). The PPI network implied that these 19 immunomodulators had interactions with other 50 genes. WebGestalt analysis demonstrated that 69 genes in the PPI network were enriched into cytokine-cytokine receptor interaction, NF-kappa B signaling pathway, and pathways in cancer. Our study identified novel diagnostic biomarkers and revealed potential immune-related mechanisms in NPC. These findings enlighten the investigation of the molecular mechanisms of tumor-infiltrating immune cells regulating NPC.

Gao P ，Lu W ，Hu S ，Zhao K ... -  《-》

Identification of Potential Therapeutic Gene Markers in Nasopharyngeal Carcinoma Based on Bioinformatics Analysis.

Nasopharyngeal carcinoma (NPC) is a common cancer found in the nasopharynx with high metastatic and invasive nature. Increasing evidences have identified the critical role of gene therapy in NPC treatment. Hence, this study was designed to identify specific gene markers that affected NPC progression through gene expression profile analysis. NPC-related gene expression data set gene set enrichment (GSE)53819 were retrieved and analyzed to screen out differentially expressed genes (DEGs), followed by determination of their expression in noncancerous tissues and NPC specimens. Next, weighted gene co-expression network analysis (WGCNA) was conducted on DEGs to obtain tumor-associated gene modules. Genes in those modules were intersected with DEGs for gene ontology and Kyoto Encyclopedia of Genes and Genomes functional enrichment analysis. Then protein-protein interaction network of tumor-associated genes was constructed to select genes most closely linked to NPC. Afterward, expression of chromosome 9 open reading frame 24 (c9orf24), primary ciliary dyskinesia protein 1 (PCDP1), and leucine-rich repeat-containing protein 46 (LRRC46) was detected in GSE53819 and further verified in GSE12452 and GSE64634. Differential analysis on GSE53819 found that 2,173 genes were aberrantly expressed in NPC, among which 917 genes are upregulated and 1,256 genes are downregulated. WGCNA showed that genes were enriched in 17 modules and 727 genes exhibited ectopic expression in NPC and enriched in cytokine-cytokine receptor interaction, cytochrome P450, and chemical carcinogenesis signaling pathways, among which c9orf24, PCDP1, and LRRC46 were poorly expressed in NPC. Therefore, c9orf24, PCDP1, and LRRC46 might serve as prominent diagnostic markers for NPC, which presents new insights for NPC therapy.

Xue K ，Cao J ，Wang Y ，Zhao X ，Yu D ，Jin C ，Xu C ... -  《-》