Key modules and hub genes identified by coexpression network analysis for revealing novel biomarkers for larynx squamous cell carcinoma

2019 ◽  
Vol 120 (12) ◽  
pp. 19832-19840 ◽  
Author(s):  
Hang Zhang ◽  
Xudong Zhao ◽  
Mengmeng Wang ◽  
Wenyue Ji
Keyword(s):  
Squamous Cell Carcinoma ◽  
Network Analysis ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Coexpression Network ◽  
Hub Genes ◽  
Novel Biomarkers ◽  
Larynx Squamous Cell Carcinoma ◽  
Coexpression Network Analysis

scholarly journals Weighted Gene Co-Expression Network Analysis Identifies Hub Genes Associated with Occurrence and Prognosis of Oral Squamous Cell Carcinoma

2019 ◽  
Vol 25 ◽  
pp. 7272-7288 ◽  
Author(s):  
You Ge ◽  
Wei Li ◽  
Qian Ni ◽  
Yan He ◽  
Jinjin Chu ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Network Analysis ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Hub Genes

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 Three Survival-Related Genes of Esophageal Squamous Cell Carcinoma Identified by Weighted Gene Coexpression Network Analysis

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Di Lu ◽  
He Wang ◽  
Xuanzhen Wu ◽  
Jianxue Zhai ◽  
Xiguang Liu ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Network Analysis ◽  
Esophageal Squamous Cell Carcinoma ◽  
Coexpression Network ◽  
Gene Coexpression Network ◽  
Protein Coding ◽  
Protein Coding Genes ◽  
Gene Coexpression ◽  
Novel Biomarkers ◽  
Coexpression Network Analysis

Background. The aim of this study was to identify novel biomarkers associated with esophageal squamous cell carcinoma (ESCC) prognosis. Methods. 81 ESCC samples collected from The Cancer Genome Atlas (TCGA) were used as the training set, and 179 ESCC samples collected from the Gene Expression Omnibus database (GEO) were used as the validation set. The protein-coding genes of 25 samples from patients who completed the follow-up in TCGA were analyzed to construct a coexpression network by weighted gene coexpression network analysis (WGCNA). Gene ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analyses were performed for the selected genes. The least absolute shrinkage and selection operator (LASSO) Cox regression model was constructed to analyze survival-related genes, and an optimal prognostic model was developed as well as evaluated by Kaplan–Meier and ROC curves. Results. In this study, a module containing 43 protein-coding genes and strongly related to overall survival (OS) was identified through WGCNA. These genes were significantly enriched in retina homeostasis, antimicrobial humoral response, and epithelial cell differentiation. Besides, through the LASSO regression model, 3 genes (PDLIM2, DNASE1L3, and KRT81) significantly related to ESCC survival were screened and an optimal prognostic 3-gene risk prediction model was constructed. ESCC patients with low and high OS in both sets could be successfully discriminated by calculating a risk score with the linear combination of the expression level of each gene multiplied by the LASSO coefficient. Conclusions. Our study identified three novel biomarkers that have potential in the prognosis prediction of ESCC.

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 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 Correlation of alterations in the KEAP1 / CUL3 / NFE2L2 pathway with radiation failure in larynx squamous cell carcinoma

2021 ◽  
Author(s):  
Siddharth Sheth ◽  
Douglas R. Farquhar ◽  
Travis P. Schrank ◽  
Wesley Stepp ◽  
Angela Mazul ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Larynx Squamous Cell Carcinoma

scholarly journals Bioinformatics analysis of DNMT1 expression and its role in head and neck squamous cell carcinoma prognosis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jili Cui ◽  
Lian Zheng ◽  
Yuanyuan Zhang ◽  
Miaomiao Xue
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Immune Cell ◽  
Neck Squamous Cell Carcinoma ◽  
Hub Genes ◽  
Significant Difference ◽  
Dnmt1 Expression

AbstractHead and neck squamous cell carcinoma (HNSCC) is the sixth most common type of malignancy in the world. DNA cytosine-5-methyltransferase 1 (DNMT1) play key roles in carcinogenesis and regulation of the immune micro-environment, but the gene expression and the role of DNMT1 in HNSCC is unknown. In this study, we utilized online tools and databases for pan-cancer and HNSCC analysis of DNMT1 expression and its association with clinical cancer characteristics. We also identified genes that positively and negatively correlated with DNMT1 expression and identified eight hub genes based on protein–protein interaction (PPI) network analysis. Enrichment analyses were performed to explore the biological functions related with of DNMT1. The Tumor Immune Estimation Resource (TIMER) database was performed to explore the relationship between DNMT1 expression and immune-cell infiltration. We demonstrated that DNMT1 gene expression was upregulated in HNSCC and associated with poor prognosis. Based on analysis of the eight hub genes, we determined that DNMT1 may be involved in cell cycle, proliferation and metabolic related pathways. We also found that significant difference of B cells infiltration based on TP 53 mutation. These findings suggest that DNMT1 related epigenetic alterations have close relationship with HNSCC progression, and DNMT1 could be a novel diagnostic biomarker and a promising therapeutic target for HNSCC.

Identification of microRNAs as novel biomarkers for detecting esophageal squamous cell carcinoma in Asians: a meta-analysis

Tumor Biology ◽  
2014 ◽  
Vol 35 (11) ◽  
pp. 11595-11604 ◽  
Author(s):  
Yanying Wang ◽  
Qingxiu Wang ◽  
Na Zhang ◽  
Hong Ma ◽  
Yuchun Gu ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Meta Analysis ◽  
Novel Biomarkers
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