scholarly journals Application of weighted gene co-expression network analysis to identify key modules and hub genes in oral squamous cell carcinoma tumorigenesis

2018 ◽  
Vol Volume 11 ◽  
pp. 6001-6021 ◽  
Author(s):  
Xiaoqi Zhang ◽  
Hao Feng ◽  
Ziyu Li ◽  
Dongfang Li ◽  
Shanshan Liu ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Network Analysis ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Hub Genes

scholarly journals Identification and validation of key modules and hub genes associated with the pathological stage of oral squamous cell carcinoma by weighted gene co-expression network analysis

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8505 ◽  
Author(s):  
Xuegang Hu ◽  
Guanwen Sun ◽  
Zhiqiang Shi ◽  
Hui Ni ◽  
Shan Jiang
Keyword(s):  
Squamous Cell Carcinoma ◽  
Network Analysis ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Molecular Mechanisms ◽  
Pearson Correlation ◽  
Gene Set Enrichment Analysis ◽  
Hub Genes ◽  
T Stage

Background Oral squamous cell carcinoma (OSCC) is a major lethal malignant cancer of the head and neck region, yet its molecular mechanisms of tumourigenesis are still unclear. Patients and methods We performed weighted gene co-expression network analysis (WGCNA) on RNA-sequencing data with clinical information obtained from The Cancer Genome Atlas (TCGA) database. The relationship between co-expression modules and clinical traits was investigated by Pearson correlation analysis. Furthermore, the prognostic value and expression level of the hub genes of these modules were validated based on data from the TCGA database and other independent datasets from the Gene Expression Omnibus (GEO) database and the Human Protein Atlas database. The significant modules and hub genes were also assessed by functional analysis and gene set enrichment analysis (GSEA). Results We found that the turquoise module was strongly correlated with pathologic T stage and significantly enriched in critical functions and pathways related to tumourigenesis. PPP1R12B, CFD, CRYAB, FAM189A2 and ANGPTL1 were identified and statistically validated as hub genes in the turquoise module and were closely implicated in the prognosis of OSCC. GSEA indicated that five hub genes were significantly involved in many well-known cancer-related biological functions and signaling pathways. Conclusion In brief, we systematically discovered a co-expressed turquoise module and five hub genes associated with the pathologic T stage for the first time, which provided further insight that WGCNA may reveal the molecular regulatory mechanism involved in the carcinogenesis and progression of OSCC. In addition, the five hub genes may be considered candidate prognostic biomarkers and potential therapeutic targets for the precise early diagnosis, clinical treatment and prognosis of OSCC in the future.

scholarly journals Using weighted gene co-expression network analysis to identify key modules and hub genes in tongue squamous cell carcinoma

Medicine ◽  
2019 ◽  
Vol 98 (37) ◽  
pp. e17100 ◽  
Author(s):  
Ke Yin ◽  
Ying Zhang ◽  
Suxin Zhang ◽  
Yang Bao ◽  
Jie Guo ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Network Analysis ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Tongue Squamous Cell Carcinoma ◽  
Hub Genes

scholarly journals Integrative Multi−Omics Analysis Reveals Candidate Biomarkers for Oral Squamous Cell Carcinoma

2022 ◽  
Vol 11 ◽  
Author(s):  
Zhengqing Wan ◽  
Haofeng Xiong ◽  
Xian Tan ◽  
Tong Su ◽  
Kun Xia ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Differentially Expressed Genes ◽  
Squamous Cell ◽  
Therapeutic Targets ◽  
Differentially Expressed ◽  
Integrative Approach ◽  
Hub Genes ◽  
Ppi Networks

Oral squamous cell carcinoma (OSCC) is one of the most common types of cancer worldwide. Due to the lack of early detection and treatment, the survival rate of OSCC remains poor and the incidence of OSCC has not decreased during the past decades. To explore potential biomarkers and therapeutic targets for OSCC, we analyzed differentially expressed genes (DEGs) associated with OSCC using RNA sequencing technology. Methylation−regulated and differentially expressed genes (MeDEGs) of OSCC were further identified via an integrative approach by examining publicly available methylomic datasets together with our transcriptomic data. Protein−protein interaction (PPI) networks of MeDEGs were constructed and highly connected hub MeDEGs were identified from these PPI networks. Subsequently, expression and survival analyses of hub genes were performed using The Cancer Genome Atlas (TCGA) database and the Gene Expression Profiling Interactive Analysis (GEPIA) online tool. A total of 56 upregulated MeDEGs and 170 downregulated MeDEGs were identified in OSCC. Eleven hub genes with high degree of connectivity were picked out from the PPI networks constructed by those MeDEGs. Among them, the expression level of four hub genes (CTLA4, CDSN, ACTN2, and MYH11) were found to be significantly changed in the head and neck squamous carcinoma (HNSC) patients. Three hypomethylated hub genes (CTLA4, GPR29, and TNFSF11) and one hypermethylated hub gene (ISL1) were found to be significantly associated with overall survival (OS) of HNSC patients. Therefore, these hub genes may serve as potential DNA methylation biomarkers and therapeutic targets of OSCC.

scholarly journals Prognostic biomarkers and therapeutic targets in oral squamous cell carcinoma: a study based on cross-database analysis

Hereditas ◽  
2021 ◽  
Vol 158 (1) ◽  
Author(s):  
Wanli Yang ◽  
Wei Zhou ◽  
Xinhui Zhao ◽  
Xiaoqian Wang ◽  
Lili Duan ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Molecular Mechanisms ◽  
Cox Regression ◽  
Gene Signature ◽  
Genetic Alterations ◽  
Prognostic Biomarkers ◽  
Hub Genes

Abstract Background Oral squamous cell carcinoma (OSCC) is a malignant cancer, the survival rate of patients is disappointing. Therefore, it is necessary to identify the driven-genes and prognostic biomarkers in OSCC. Methods Four Gene Expression Omnibus (GEO) datasets were integratedly analyzed using bioinformatics approaches, including identification of differentially expressed genes (DEGs), GO and KEGG analysis, construction of protein-protein interaction (PPI) network, selection of hub genes, analysis of prognostic information and genetic alterations of hub genes. ONCOMINE, The Cancer Genome Atlas (TCGA) and Human Protein Atlas databases were used to evaluate the expression and prognostic value of hub genes. Tumor immunity was assessed to investigate the functions of hub genes. Finally, Cox regression model was performed to construct a multiple-gene prognostic signature. Results Totally 261 genes were found to be dysregulated. 10 genes were considered to be the hub genes. The Kaplan-Meier analysis showed that upregulated SPP1, FN1, CXCL8, BIRC5, PLAUR, and AURKA were related to poor outcomes in OSCC patients. FOXM1 and TPX2 were considered as the potential immunotherapeutic targets with future clinical significance. Moreover, we constructed a nine-gene signature (TEX101, DSG2, SCG5, ADA, BOC, SCARA5, FST, SOCS1, and STC2), which can be utilized to predict prognosis of OSCC patients effectively. Conclusion These findings may provide new clues for exploring the molecular mechanisms and targeted therapy in OSCC. The hub genes and risk gene signature are helpful to the personalized treatment and prognostic judgement.

scholarly journals Identification of Differential Methylation Regions and Correspondence Targeted Genes in Oral Squamous Cell Carcinoma

2020 ◽  
Author(s):  
Yan Niu ◽  
Qiusheng Shan ◽  
Yuanling Guo
Keyword(s):  
Squamous Cell Carcinoma ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Biological Process ◽  
Enrichment Analysis ◽  
Differential Methylation ◽  
Differentially Expressed ◽  
Hub Genes ◽  
R Software

Abstract Background The differential methylation included hypermethylation and hypomethylation plays significant role in the progression of many kind of cancers but study little in oral squamous cell carcinoma (OSCC). Methods GSE123781 and GSE87053 was used to analysis the differential methylation regions (DMRs) and predict the target genes in OSCC by R software and wANNOVAR respectively. the biological process and cell pathways of common targeted genes between GSE123781 and GSE87053 were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analysis. The hub genes (hub genes 1) in common targeted genes associated with cancer biological process was identified by protein to protein interaction network (PPI). In addition, GSE74530 and GSE30784 was used to identify common differentially expressed genes (DEGs) in OSCC by R software. The biological process and cell pathways of common DEGs was analyzed by GO and KEGG enrichment analysis. The hub genes (hub genes 2) in common DEGs associated with cancer biological process was identified by PPI network. The significant hub genes between hub genes 1 and hub genes 2 were identified by Venn picture. Finally, the expression level of significant hub genes and correspondence relationship with head and neck squamous cell carcinoma (HNSCC) patient survival were confirmed by The Cancer Genome Atlas (TCGA) dataset. Results There are 2146 common targeted genes regulated by DMRs between GSE123781 and GSE87053 and 278 hub genes in common targeted genes associated with cancer biological process. In addition, there are 895 common DEGs between GSE74530 and GSE30784 and 144 hub genes in common DEGs associated with cancer biological process. There are 9 significant hub genes between hub genes 1 and hub genes 2. Finally, these 9 significant hub genes differentially expressed in HNSCC tissues except CCR7 and quite associated with the survival of HNSCC patients. Conclusions CCR7, ETS1, RUNX3, CCR1, C3AR1, LAMB1, IRF7, LGALS3 and CDKN3 both are DEGs and regulated by DMRs in OSCC, which are quite associated with the progression of OSCC and the survival of HNSCC patients. All of these genes have much potential to be new biomarkers in targeted therapy of OSCC.

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