Dataset Information

Characterization of long non-coding RNA and messenger RNA profiles in laryngeal cancer by weighted gene co-expression network analysis.

ABSTRACT: Laryngeal cancer (LC) is a malignant tumor in the head and neck region. It was recently elucidated that long non-coding RNAs (lncRNAs) participate in the pathogenesis of LC. However, the detailed mechanism of lncRNA in LC and whether long non-coding RNAs serve as effective biomarkers remains unclear. Ribonucleic acid (RNA) sequence data of LC and 11 patient clinical traits were extracted from The Cancer Genome Atlas (TCGA) database and analyzed by weighted gene co-expression network analysis (WGCNA). A total of 9 co-expression modules were identified. The co-expression Pink module significantly correlated with four clinical traits, including history of smoking, lymph node count, tumor status, and the success of follow-up treatment. Based on the co-expression Pink module, lncRNA-microRNA (miRNA)-messenger RNA (mRNA) and lncRNA-RNA binding protein-mRNA networks were constructed. We found that 8 lncRNAs significantly impacted overall survival (OS) in LC patients. These identified lncRNA and hub gene biomarkers were also validated in multiple LC cells in vitro via qPCR. Taken together, this study provided the framework of co-expression gene modules of LC and identified some important biomarkers in LC development and disease progression.

SUBMITTER: Liu H

PROVIDER: S-EPMC6914418 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Characterization of long non-coding RNA and messenger RNA profiles in laryngeal cancer by weighted gene co-expression network analysis.

Liu Huanhuan H Sun Yi Y Tian Huan H Xiao Xiaolian X Zhang Jiaqi J Wang Yongzhen Y Yu Fengyan F

Aging 20191118 22

Laryngeal cancer (LC) is a malignant tumor in the head and neck region. It was recently elucidated that long non-coding RNAs (lncRNAs) participate in the pathogenesis of LC. However, the detailed mechanism of lncRNA in LC and whether long non-coding RNAs serve as effective biomarkers remains unclear. Ribonucleic acid (RNA) sequence data of LC and 11 patient clinical traits were extracted from The Cancer Genome Atlas (TCGA) database and analyzed by weighted gene co-expression network analysis (WG ...[more]

PMID: 31739287

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Project description:BackgroundCircular RNAs (circRNAs) and long non-coding RNAs (lncRNAs) have been recently identified as new classes of non-coding RNAs which participate in carcinogenesis and tumor progression. However, the functions of these non-coding RNAs and gene expression patterns are largely unknown.MethodsWe carried out high-throughput sequencing to analyze the differential expression of RNAs in 5 coupled laryngeal cancer (LC) and corresponding adjacent noncancerous tissues. Bioinformatics analyses were performed to predict the functions of these non-coding RNAs via co-expression, competing endogenous RNA networks and pathway enrichment analysis. The differential expression of the selected RNAs were confirmed using RT-qPCR. The CCK8, EDU, Transwell, and wound healing assays were conducted to validate the biological functions of SNHG29 in LC. Western blot assay was performed to identify the effects of SNHG29 having on the epithelial to mesenchymal transition process. Kaplan-Meier analysis was used to investigate whether the expression level of SNHG29 correlated with survival in LC patients. One-way ANOVA was used to analyze the correlation between the expression of SNHG29 and clinicopathological parameters of the included patients.ResultsCompared to normal laryngeal tissues, 31,763 non-coding RNAs were upregulated and 11,557 non-coding RNAs were downregulated in cancer tissues. SNHG29 expression was low in the LC cell lines and tissues predicting a better clinical prognosis. SNHG29 was also found to inhibit the proliferation, migration, and invasion ability of LC, exerting a suppressive role in the epithelial to mesenchymal transition process as well. SNHG29 downregulation was significantly correlated with differentiation (P=0.026), T-stage (P=0.041), lymphatic metastasis (P=0.044), and clinical stage (P=0.037). We found that the biological functions of differentially expressed transcripts included cell adhesion, biological adhesion, and migration and invasion related to adherens junction pathways.ConclusionsOur study was the first to describe the non-coding RNA profile of LC, and suggested that dysregulated non-coding RNAs could be involved in LC tumorigenesis. SNHG29 was demonstrated to play crucial roles in inhibiting the pathogenesis and progression of LC. Our findings provide a new approach for further analyses of pathogenetic mechanisms, the detection of novel transcripts, and the identification of valuable biomarkers for this tumor.

Project description:Laryngeal squamous cell carcinoma (LSCC) is the most common malignant tumor in the head and neck, and can seriously affect the daily life of patients. To study the mechanisms of LSCC, the microarray of GSE51958 was analyzed in the present study. GSE51958 was downloaded from Gene Expression Omnibus, and included a collection of LSCC tissue samples and matched adjacent non-cancerous tissue samples from 10 patients. Differentially-expressed genes (DEGs) were identified using limma package. Next, a weighted co-expression network was constructed for the DEGs by WGCNA package in R. Modules of the weighted co-expression network were obtained through constructing a hierarchical clustering tree using the hybrid dynamic shear tree method. Using the clusterProfiler package, the potential functions of DEGs in the modules correlated with LSCC were predicted by pathway enrichment analysis. In total, 959 DEGs were screened from the LSCC samples compared with the adjacent non-cancerous samples, including 553 upregulated and 406 downregulated genes. The appointed black, brown, gray, pink and yellow modules were screened for the DEGs in the weighted co-expression network. For the DEGs in the brown and yellow modules, the enriched pathways were cytokine-cytokine receptor interaction and metabolic pathways, respectively. The DEGs in the pink module were involved in the majority of pathways. With high connectivity degrees in the pink module, TPX2, microtubule-associated (TPX2; degree, 25), minichromosome maintenance complex component 2 (MCM2; degree, 25), ubiquitin-like with PHD and ring finger domains 1 (UHRF1; degree, 22), cyclin-dependent kinase 2 (CDK2; degree, 20) and protein regulator of cytokinesis 1 (PRC1; degree, 20) may be involved in LSCC. Overall, In conclusion, from the integrated bioinformatics analysis of genes that may be associated with LSCC, 959 DEGs were obtained from LSCC samples compared with adjacent non-cancerous samples, and TPX2, MCM2, UHRF1, CDK2 and PRC1 were found to hold a possible association with the disease.

Dataset Information

Characterization of long non-coding RNA and messenger RNA profiles in laryngeal cancer by weighted gene co-expression network analysis.

Publications

Characterization of long non-coding RNA and messenger RNA profiles in laryngeal cancer by weighted gene co-expression network analysis.

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