scholarly journals Prediction of the mechanism of miRNAs in laryngeal squamous cell carcinoma based on the miRNA-mRNA regulatory network

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12075
Author(s):  
Jinhua Ma ◽  
Xiaodong Hu ◽  
Baoqiang Dai ◽  
Qiang Wang ◽  
Hongqin Wang
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Regulatory Network ◽  
Bioinformatics Analysis ◽  
Laryngeal Squamous Cell Carcinoma ◽  
Differentially Expressed ◽  
Cell Counting ◽  
Differentially Expressed Mirnas ◽  
Geo Database

In this study, a bioinformatics analysis is conducted to screen differentially expressed miRNAs and mRNAs in laryngeal squamous cell carcinoma (LSCC). Based on this information, we explored the possible roles of miRNAs in the pathogenesis of LSCC. The RNA-Seq data from 79 laryngeal cancer samples in the Gene Expression Omnibus (GEO) database were sorted. Differentially expressed miRNAs and mRNAs in LSCC are screened using the PERL programming language, and it was analysed by Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The miRNA-mRNA regulatory network of LSCC is constructed using Cytoscape software. Then, quantitative real-time PCR (QRT- PCR), Cell Counting Kit-8 (CCK8) and flow cytometry analysis we are used to further validate key miRNAs. We identified 99 differentially expressed miRNAs and 2,758 differentially expressed mRNAs in LSCC tissues from the GEO database. Four more important miRNAs displaying a high degree of connectivity are selected, these results suggest that they play an important role in the pathogenesis of LSCC. As shown in the present study, we identified specific miRNA-mRNA networks associated with the occurrence and development of LSCC through bioinformatics analysis. We found a miRNA molecule closely related to LSCC based on miRNA-mRNA network: miR-140-3p was down-regulated in LSCC. In addition, the potential antitumor effect of miR-140-3p in LSCC was verified in the experiment, and it was proved that overexpression of miR-140-3p could inhibit the proliferation of LSCC cells and promote cell apoptosis, suggesting that miR-140-3p may be a potential tumor marker in LSCC.

scholarly journals Whole-Transcriptome Analysis of CD133+CD144+ Cancer Stem Cells Derived from Human Laryngeal Squamous Cell Carcinoma Cells

2018 ◽  
Vol 47 (4) ◽  
pp. 1696-1710 ◽  
Author(s):  
Yongyan Wu ◽  
Yuliang Zhang ◽  
Min Niu ◽  
Yong Shi ◽  
Hongliang Liu ◽  
...  
Keyword(s):  
Stem Cells ◽  
Squamous Cell Carcinoma ◽  
Cancer Stem Cells ◽  
Cell Carcinoma ◽  
Laryngeal Cancer ◽  
Squamous Cell ◽  
Regulatory Network ◽  
Laryngeal Squamous Cell Carcinoma ◽  
Differentially Expressed ◽  
Luciferase Reporter

Background/Aims: CD133+CD44+ cancer stem cells previously isolated from laryngeal squamous cell carcinoma (LSCC) cell lines showed strong malignancy and tumorigenicity. However, the molecular mechanism underlying the enhanced malignancy remained unclear. Methods: Cell proliferation assay, spheroid-formation experiment, RNA sequencing (RNA-seq), miRNA-seq, bioinformatic analysis, quantitative real-time PCR, migration assay, invasion assay, and luciferase reporter assay were used to identify differentially expressed mRNAs, lncRNAs, circRNAs and miRNAs, construct transcription regulatory network, and investigate functional roles and mechanism of circRNA in CD133+CD44+ laryngeal cancer stem cells. Results: Differentially expressed genes in TDP cells were mainly enriched in the biological processes of cell differentiation, regulation of autophagy, negative regulation of cell death, regulation of cell growth, response to hypoxia, telomere maintenance, cellular response to gamma radiation, and regulation of apoptotic signaling, which are closely related to the malignant features of tumor cells. We constructed the regulatory network of differentially expressed circRNAs, miRNAs and mRNAs. qPCR findings for the expression of key genes in the network were consistent with the sequencing data. Moreover, our data revealed that circRNA hg19_circ_0005033 promotes proliferation, migration, invasion, and chemotherapy resistance of laryngeal cancer stem cells. Conclusions: This study provides potential biomarkers and targets for LSCC diagnosis and therapy, and provide important evidences for the heterogeneity of LSCC cells at the transcription level.

scholarly journals A Novel Signature Derived from Metabolism-Related Genes GPT and SMS to Predict Prognosis of Laryngeal Squamous Cell Carcinoma

2021 ◽  
Author(s):  
Yujie Shen ◽  
Qiang Huang ◽  
Yifan Zhang ◽  
Chi-Yao Hsueh ◽  
Liang Zhou
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Laryngeal Squamous Cell Carcinoma ◽  
Cox Regression ◽  
External Validation ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Clinical Samples ◽  
Prognostic Signature

Abstract Background A growing body of evidence has suggested the involvement of metabolism in the occurrence and development of tumors. But the link between metabolism and laryngeal squamous cell carcinoma (LSCC) has rarely been reported. This study seeks to understand and explain the role of metabolic biomarkers in predicting the prognosis of LSCC. Methods We identified the differentially expressed metabolism-related genes (MRGs) through RNA-seq data of TCGA (The Cancer Genome Atlas) and GSEA (Gene set enrichment analysis). After the screening of protein-protein interaction (PPI), hub MRGs were analyzed by least absolute shrinkage and selection operator (LASSO) and Cox regression analyses to construct a prognostic signature. Kaplan–Meier survival analysis and the receiver operating characteristic (ROC) was applied to verify the effectiveness of the prognostic signature in four cohorts (TCGA cohort, GSE27020 cohort, TCGA-sub1 cohort and TCGA-sub2 cohort). The expressions of the hub MRGs in cell lines and clinical samples were verified by quantitative reverse transcriptase PCR (qRT-PCR). The immunofluorescence staining of the tissue microarray (TMA) was carried out to further verify the reliability and validity of the prognostic signature. Cox regression analysis was then used to screen for independent prognostic factors of LSCC and a nomogram was constructed based on the results. Results Among the 180 differentially expressed MRGs, 14 prognostic MRGs were identified. A prognostic signature based on two MRGs (GPT and SMS) was then constructed and verified via internal and external validation cohorts. Compared to the adjacent normal tissues, SMS expression was higher while GPT expression was lower in LSCC tissues, indicating poorer outcomes. The risk score proved the prognostic signature as an independent risk factor for LSCC in both internal and external validation cohorts. A nomogram based on these results was developed for clinical application. Conclusions Differentially expressed MRGs were found and proven to be related to the prognosis of LSCC. We constructed a novel prognostic signature based on MRGs in LSCC for the first time and verified via different cohorts from both databases and clinical samples. A nomogram based on this prognostic signature was developed.

scholarly journals Functional analysis of lncRNAs based on competitive endogenous RNA in tongue squamous cell carcinoma

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6991 ◽  
Author(s):  
Yidan Song ◽  
Yihua Pan ◽  
Jun Liu
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Regulatory Network ◽  
Curve Analysis ◽  
Tongue Squamous Cell Carcinoma ◽  
Differentially Expressed ◽  
High Expression ◽  
Kaplan Meier ◽  
Competitive Endogenous Rna

BackroundTongue squamous cell carcinoma (TSCC) is the most common malignant tumor in the oral cavity. An increasing number of studies have suggested that long noncoding RNA (lncRNA) plays an important role in the biological process of disease and is closely related to the occurrence and development of disease, including TSCC. Although many lncRNAs have been discovered, there remains a lack of research on the function and mechanism of lncRNAs. To better understand the clinical role and biological function of lncRNAs in TSCC, we conducted this study.MethodsIn this study, 162 tongue samples, including 147 TSCC samples and 15 normal control samples, were investigated and downloaded from The Cancer Genome Atlas (TCGA). We constructed a competitive endogenous RNA (ceRNA) regulatory network. Then, we investigated two lncRNAs as key lncRNAs using Kaplan–Meier curve analysis and constructed a key lncRNA-miRNA-mRNA subnetwork. Furthermore, gene set enrichment analysis (GSEA) was carried out on mRNAs in the subnetwork after multivariate survival analysis of the Cox proportional hazards regression model.ResultsThe ceRNA regulatory network consists of six differentially expressed miRNAs (DEmiRNAs), 29 differentially expressed lncRNAs (DElncRNAs) and six differentially expressed mRNAs (DEmRNAs). Kaplan-Meier curve analysis of lncRNAs in the TSCC ceRNA regulatory network showed that only two lncRNAs, including LINC00261 and PART1, are correlated with the total survival time of TSCC patients. After we constructed the key lncRNA-miRNA -RNA sub network, the GSEA results showed that key lncRNA are mainly related to cytokines and the immune system. High expression levels of LINC00261 indicate a poor prognosis, while a high expression level of PART1 indicates a better prognosis.

Development of an immunogenomics-based prognostic index model of laryngeal squamous cell carcinoma

2020 ◽  
Author(s):  
Yujie Shen ◽  
Han Zhou ◽  
Shikun Dong ◽  
Meiping Lu ◽  
Weida Dong ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Laryngeal Squamous Cell Carcinoma ◽  
Cox Regression ◽  
Prognostic Index ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
Cox Regression Analysis

Abstract Background: The immune system greatly affects the prognosis of various malignancies. Studies on differentially expressed immune-related genes (IRGs) in the immune microenvironment of laryngeal squamous cell carcinoma (LSCC) have rarely been reported.Methods: In this paper, the prognostic potentials of IRGs in LSCC were explored. The RNAseq dataset containing differentially expressed IRGs and corresponding clinical information of LSCC patients was obtained from The Cancer Genome Atlas (TCGA). A total of 371 up-regulated and 61 down-regulated IRGs were identified. Subsequent functional enrichment analysis revealed that the pathway of IRGs was mainly enriched in the cytokine-cytokine receptor interaction. Then, 30 IRGs with prognostic potentials in LSCC were screened out, and the regulatory network induced by relevant transcription factors (TFs) were constructed.Results: Finally, multivariate Cox regression analysis was conducted to assess the prognostic potential of 15 IRGs after adjustment of clinical factors and LSCC patients were classified into 2 subgroups based on different outcomes. The gene expression of the model was verified by other independent databases. Nomogram including the 15 IRGs signature was established and shown some clinical net beneft. Intriguingly, B cells were significantly enriched in the low-risk group. Conclusion:These findings may contribute to the development of potential therapeutic targets and biomarkers for the new-immunotherapy of LSCC.

scholarly journals Identification of Potential Prognostic Biomarkers for Tongue Squamous Cell Carcinoma

2020 ◽  
Author(s):  
Mi Zhang ◽  
Sihui Zhang ◽  
Ling Wu ◽  
Dexiong Li ◽  
Jiang Chen
Keyword(s):  
Squamous Cell Carcinoma ◽  
Regression Analysis ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Bioinformatics Analysis ◽  
Cox Regression ◽  
Differentially Expressed ◽  
Coexpression Network ◽  
Ppi Network ◽  
Potential Biomarkers

Abstract Background: Tongue squamous cell carcinoma (TSCC) is one of the most common types of oral cancer and has a poor prognosis owing to a limited understanding of its pathogenetic mechanisms. The purpose of this study was to explore and identify potential biomarkers in TSCC by integrated bioinformatics analysis.Methods: The RNA sequencing data, methylation data, and clinical characteristics of TSCC patients were downloaded from The Cancer Genome Atlas (TCGA), and then differentially expressed RNAs (DERNAs), including differentially expressed long noncoding RNAs (DElncRNAs) and differentially expressed messenger RNAs (DEmRNAs), were identified in TSCC by bioinformatics analysis. Subsequently, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Hallmark pathway analyses were used to analyze the DERNAs. Univariate and multivariate Cox regression analyses were used to develop four-lncRNA and two-mRNA signatures and predict survival in TSCC patients. We established a risk model to predict the overall survival (OS) of TSCC patients based on the DERNAs with Kaplan–Meier analysis and the log-rank p test. Furthermore, weighted gene coexpression network analysis (WGCNA) was performed in Cytoscape, and a protein-protein interaction (PPI) network was established in the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database.Results: A total of 2,006 DEmRNAs and 1,001 DElncRNAs were found to be dysregulated in TSCC. A total of 417 DERNAs were used to construct the coexpression network, and the PPI network included 103 DEmRNAs. Univariate regression analysis of the DERNAs revealed 51 DElncRNAs and 90 DEmRNAs that were associated with OS in TSCC patients. Multivariate Cox regression analysis demonstrated that four of those lncRNAs (MGC32805, RP1-35C21.2, RP11-108K3.1, and RP11-109M17.2) and two mRNAs (CA9, GTSF1L) had significant prognostic value, and their cumulative risk score indicated that these four-lncRNA and two-mRNA signatures independently predicted OS in TSCC patients. Additionally, there was a positive correlation between the expression and methylation level of RP11-108K3.1, the OS significantly negatively correlated with hypermethylation and low expression of GTSF1L along with hypomethylation and high expression of CA9.Conclusions: The current findings provide novel insights into the molecular mechanisms of TSCC and identify four lncRNAs and two mRNAs that are potential biomarkers that may be independent prognostic signatures for TSCC diagnosis and treatment.

scholarly journals Prognostic Value of Immune Associated Long Non-Coding RNAs In Laryngeal Squamous Cell Carcinoma

2021 ◽  
Author(s):  
Weixing Liu ◽  
Pei Li ◽  
Yue Liu ◽  
Zhiyuan Wang ◽  
Jiamin Liu ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Molecular Mechanisms ◽  
Laryngeal Squamous Cell Carcinoma ◽  
Cox Regression ◽  
Critical Role ◽  
Differentially Expressed ◽  
Prognostic Signature ◽  
Sequencing Data

Abstract Background: Increasing studies have demonstrated that immune associated lncRNAs (IALs) take an important part in the occurrence and development of multiple cancers. However, the prognosis value of IALs in laryngeal squamous cell carcinoma (LSCC) remains unexplored. This study aimed to evaluate the importance of IALs in LSCC. Methods: RNA sequencing data profiles of LSCC and clinical information of patients were obtained from TCGA dataset. Correlation analysis was performed to screen IALs. Then, a IALs based prognostic signature was constructed through univariate and multivariate Cox regression. The uncover molecular mechanisms of these selected IALs were explored by the bioinformatics analyses.Results: a total of seven differentially expressed survival-associated IALs were found in LSCC patients. a six IALs (LINC02154, SNHG12, CHKB-DT, AL158166.1, AC027307.2 and AL121899.1) based prognostic signature was established, which was a reliable tool to predict the prognosis of LSCC. The area under the curve (AUC) were 0.817 (one-year), 0.847 (three-year) and 0.895 (five-year). Further analysis, there were different infiltration of immune cells between low-risk and high-risk group patients. Additionally, a lncRNA-miRNA-mRNA regulatory network basted on six IALs, 75 miRNAs, and 156 differentially expressed mRNAs was constructed.Conclusions: IALs may play critical role in the occurrence and progression of LSCC, and the IALs based prognostic signature can predict the overall survival rate of LSCC.

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