Dataset Information

Construction and integrated analysis of crosstalking ceRNAs networks in laryngeal squamous cell carcinoma.

ABSTRACT:

Background

Laryngeal squamous cell carcinoma (LSCC) is one of the most common malignant tumours of the head and neck. Recent evidence has demonstrated that lncRNAs play important roles in tumour progression and could be used as biomarkers for early diagnosis, prognosis, and potential therapeutic targets. The "competitive endogenous RNA (ceRNA)" hypothesis states that lncRNAs competitively bind to miRNAs through their intramolecular miRNA reaction elements (MREs) to construct a wide range of ceRNA regulatory networks. This study aims to predict the role of ceRNA network in LSCC, for advancing the understanding of underlying mechanisms of tumorigenesis.

Material and methods

In this study, the functions of lncRNAs as ceRNAs in LSCC and their prognostic significance were investigated via comprehensive integrated expression profiles data of lncRNAs, mRNAs, and miRNAs obtained from The Cancer Genome Atlas (TCGA). Protein-protein interaction, gene ontology, pathway, and Kaplan-Meier curves analysis were used to profile the expression and function of altered RNAs in LSCC.

Results

As a result, 889 lncRNAs, 55 miRNAs and 1946 mRNAs were found to be differentially expressed in LSCC. These altered mRNAs were mainly involved in extracellular matrix organization, calcium signaling, and metabolic pathways. To study the regulatory function of lncRNAs, an lncRNA-mediated ceRNA network was constructed. This ceRNA network included 61 lncRNAs, seven miRNAs and seven target mRNAs. Of these RNAs, lncRNAs (TSPEAR-AS, CASK-AS1, MIR137HG, PART1, LSAMP-AS1), miRNA (has-mir-210) and mRNAs (HOXC13, STC2, DIO1, FOXD4L1) had a significant effect on the prognosis of LSCC.

Conclusion

The results of this study broaden the understanding of the mechanisms by which lncRNAs are involved in tumorigenesis. Furthermore, five lncRNAs (TSPEAR-AS, CASK-AS1, MIR137HG, PART1, LSAMP-AS1) were identified as potential prognostic biomarkers and therapeutic targets for LSCC. These results provide a basis for further experimental and clinical research.

SUBMITTER: Liu Y

PROVIDER: S-EPMC6657684 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Publications

Construction and integrated analysis of crosstalking ceRNAs networks in laryngeal squamous cell carcinoma.

Liu Yuehui Y Ye Fan F

PeerJ 20190722

<h4>Background</h4>Laryngeal squamous cell carcinoma (LSCC) is one of the most common malignant tumours of the head and neck. Recent evidence has demonstrated that lncRNAs play important roles in tumour progression and could be used as biomarkers for early diagnosis, prognosis, and potential therapeutic targets. The "competitive endogenous RNA (ceRNA)" hypothesis states that lncRNAs competitively bind to miRNAs through their intramolecular miRNA reaction elements (MREs) to construct a wide range ...[more]

PMID: 31367490

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Project description:Laryngeal squamous cell carcinoma (LSCC) is a genetically complex tumor type and one of the leading causes of cancer-associated disability and mortality. Genetic instability, such as chromosomal instability, is associated with the tumorigenesis of LSCC. Copy number variations (CNVs) have been demonstrated to contribute to the genetic diversity of tumor pathogenesis. Comparative genomic hybridization (CGH) has emerged as a high-throughput genomic technology that facilitates the aggregation of high-resolution data of cancer-associated genomic imbalances. In the present study, a total of 38 primary supraglottic LSCC cases were analyzed by high-resolution array-based CGH (aCGH) to improve the understanding of the genetic alterations in LSCC. Additionally, integration with bioinformatic analysis of microarray expression profiling data from the Gene Expression Omnibus (GEO) database provided a fundamental method for the identification of putative target genes. Genomic CNVs were detected in all cases. The size of net genomic imbalances per case ranged between a loss of 682.3 Mb (~24% of the genome) and a gain of 1,958.6 Mb (~69% of the genome). Recurrent gains included 2pter-q22.1, 3q26.1-qter, 5pter-p12, 7p22.3p14.1, 8p12p11.22, 8q24.13q24.3, 11q13.2q13.4, 12pter-p12.2, 18pter-p11.31 and 20p13p12.1, whereas recurrent losses included 3pter-p21.32, 4q28.1-q35.2, 5q13.2-qter, 9pter-p21.3 and monosomy 13. Gains of 3q26.1-qter were associated with tumor stage, poor differentiation and smoking history. Additionally, through integration with bioinformatic analysis of data from the GEO database, putative target oncogenes, including sex-determining region Y-box 2, eukaryotic translation initiation factor 4 gamma 1, fragile X-related gene 1, disheveled segment polarity protein 3, defective n cullin neddylation 1 domain containing 1, insulin like growth factor 2 mRNA binding protein 2 and CCDC26 long non-coding RNA, and tumor suppressor genes, such as CUB and sushi multiple domains 1, cyclin dependent kinase inhibitor 2A, protocadherin 20, serine peptidase inhibitor Kazal type 5 and Nei like DNA glycosylase 3, were identified in supraglottic LSCC. Supraglottic LSCC is a genetically complex tumor type and aCGH was demonstrated to be effective in the determination of molecular profiles with higher resolution. The present results enable the identification of putative target oncogenes and tumor suppressor gene mapping in supraglottic LSCC.

Project description:BackgroundLong non-coding RNAs (lncRNAs) can function as competing endogenous RNAs (ceRNAs) to interact with miRNAs to regulate target genes and promote cancer initiation and progression. The expression of lncRNAs and miRNAs can be epigenetically regulated. The goal of this study was to construct an lncRNA-miRNA-mRNA ceRNA network in laryngeal squamous cell carcinoma (LSCC) and reveal their methylation patterns, which was not investigated previously.MethodsMicroarray datasets available from the Gene Expression Omnibus database were used to identify differentially expressed lncRNAs (DELs), miRNAs (DEMs), and genes (DEGs) between LSCC and controls, which were then overlapped with differentially methylated regions (DMRs). The ceRNA network was established by screening the interaction relationships between miRNAs and lncRNAs/mRNAs by corresponding databases. TCGA database was used to identify prognostic biomarkers.ResultsFive DELs (downregulated: TMEM51-AS1, SND1-IT1; upregulated: HCP5, RUSC1-AS1, LINC00324) and no DEMs were overlapped with the DMRs, but only a negative relationship occurred in the expression and methylation level of TMEM51-AS1. Five DELs could interact with 11 DEMs to regulate 242 DEGs, which was used to construct the ceRNA network, including TMEM51-AS1-miR-106b-SNX21/ TRAPPC10, LINC00324/RUSC1-AS1-miR-16-SPRY4/MICAL2/ SLC39A14, RUSC1-AS1-miR-10-SCG5 and RUSC1-AS1-miR-7-ZFP1 ceRNAs axes. Univariate Cox regression analysis showed RUSC1-AS1 and SNX21 were associated with overall survival (OS); LINC00324, miR-7 and ZFP1 correlated with recurrence-free survival (RFS); miR-16, miR-10, SCG5, SPRY4, MICAL2 and SLC39A14 were both OS and RFS-related. Furthermore, TRAPPC10 and SLC39A14 were identified as independent OS prognostic factors by multivariate Cox regression analysis.ConclusionDNA methylation-mediated TMEM51-AS1 and non-methylation-mediated RUSC1-AS1 may function as ceRNAs for induction of LSCC. They and their ceRNA axis genes (particularly TMEM51-AS1-miR-106b-TRAPPC10; RUSC1-AS1-miR-16-SLC39A14) may be potentially important prognostic biomarkers for LSCC.

Project description:BackgroundLaryngeal squamous cell carcinoma (LSCC) is a kind of common and aggressive tumor with high mortality. The application of molecular biomarkers is useful for the early diagnosis and treatment of LSCC.MethodsThe expression and clinical information were obtained from The Cancer Genome Atlas (TCGA) database. Principal components analysis (PCA) was used to discriminate between LSCC and normal samples. The hub genes were screened out through univariate and multivariate cox analyses. The Kaplan-Meier (K-M) and receiver operating characteristic (ROC) curve was used to validate the predictive performance. The single sample gene set enrichment analysis (ssGSEA), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used to determine the enrichment function. Protein-Protein Interaction (PPI) network was constructed in STRING. The immune analysis was performed by ESTIMATE, IPS and xCELL. The drug sensitivity was identified with GSCA database.ResultsWe identified that 47 extracellular matrix (ECM) genes were differentially expressed in LSCC compared with normal group. Univariate and multivariate cox analysis determined that leucine-rich glioma-inactivated 4 (LGI4), matrilin 4 (MATN4), microfibrillar-associated protein 2 (MFAP2) and fibrinogen like 2 (FGL2) were closely related to the disease free survival (DSS) of LSCC. ROC curve determined that the risk model has a good predictive performance. PPI network showed the top 100 genes with high correlation of hub genes. The ssGSEA, GO and KEGG enrichment analyses determined that immune response was significantly involved in the development of LSCC. Immune infiltration analysis showed that most immune cells and immune checkpoints were inhibited in high risk score group. Drug sensitivity analysis showed that MATN4, FGL2 and LGI4 were negatively related to various drugs, while MFAP2 was positively related to many drugs.ConclusionWe established a risk model constructed with four ECM-related genes, which could effectively predict the prognosis of LSCC.

Project description:OBJECTIVE: To investigate the differentially expressed genes related to the chemosensitivity of laryngeal squamous cell carcinoma ï¼LSCCï¼by microarrays arrays. METHODS: 1. A total number of 11 patients who underwent induction chemotherapy for primary hypopharyngeal squamous cell carcinoma (7 patients are sensitive to chemotherapy ,and others are not) were recruited for microarray and miRNA array gene expression analysis 2. Bioinformatics analysis of differentially expressed genes screened by microarrays : The differential gene cluster analysis was applied in biological processes, cellular components and molecular functions by GO database; The differential gene enrichment analysis was applied in signaling pathways by KEGG database, and the differentially expressed and biologically meaningful core genes would be screened. RESULTS: 1. Analyzed by microarrays, there were 1554 genes significantly related to the sensitivity to chemotherapy; Among these 1554genes, 777 showed a higher expression in the tissue from patients who are sensitive to chemotherapy , while 785 presented the contrasting pattern. CONCLUSIONS: The research revealed a gene expression signature of chemosensitivity in laryngeal squamous cell carcinoma by microarrays arrays. The result will contribute to the understanding of the molecular basis of laryngeal squamous cell carcinoma and help to improve diagnosis and treatment. 1. A total number of 11 patients who underwent induction chemotherapy for primary hypopharyngeal squamous cell carcinoma (7 patients are sensitive to chemotherapy ,and others are not) were recruited for microarray and miRNA array gene expression analysis 2. Bioinformatics analysis of differentially expressed genes screened by microarrays : The differential gene cluster analysis was applied in biological processes, cellular components and molecular functions by GO database; The differential gene enrichment analysis was applied in signaling pathways by KEGG database, and the differentially expressed and biologically meaningful core genes would be screened.

Project description:Background:Recurrence remains a major obstacle to long-term survival of laryngeal squamous cell carcinoma (LSCC). We conducted a genome-wide integrated analysis of methylation and the transcriptome to establish methylation-driven genes prognostic signature (MDGPS) to precisely predict recurrence probability and optimize therapeutic strategies for LSCC. Methods:LSCC DNA methylation datasets and RNA sequencing (RNA-seq) dataset were acquired from the Cancer Genome Atlas (TCGA). MethylMix was applied to detect DNA methylation-driven genes (MDGs). By univariate and multivariate Cox regression analyses, five genes of DNA MDGs was developed a recurrence-free survival (RFS)-related MDGPS. The predictive accuracy and clinical value of the MDGPS were evaluated by receiver operating characteristic (ROC) and decision curve analysis (DCA), and compared with TNM stage system. Additionally, prognostic value of MDGPS was validated by external Gene Expression Omnibus (GEO) database. According to 5 MDGs, the candidate small molecules for LSCC were screen out by the CMap database. To strengthen the bioinformatics analysis results, 30 pairs of clinical samples were evaluated by digoxigenin-labeled chromogenic in situ hybridization (CISH). Results:A total of 88 DNA MDGs were identified, and five RFS-related MDGs (LINC01354, CCDC8, PHYHD1, MAGEB2 and ZNF732) were chosen to construct a MDGPS. The MDGPS can effectively divide patients into high-risk and low-risk group, with the area under curve (AUC) of 0.738 (5-year RFS) and AUC of 0.74 (3-year RFS). Stratification analysis affirmed that the MDGPS was still a significant statistical prognostic model in subsets of patients with different clinical variables. Multivariate Cox regression analysis indicated the efficacy of MDGPS appears independent of other clinicopathological characteristics. In terms of predictive capacity and clinical usefulness, the MDGPS was superior to traditional TNM stage. Additionally, the MDGPS was confirmed in external LSCC cohorts from GEO. CMap matched the 9 most significant small molecules as promising therapeutic drugs to reverse the LSCC gene expression. Finally, CISH analysis in 30 LSCC tissues and paired adjacent normal tissues revealed that MAGEB2 has significantly higher expression of LSCC compared to adjacent non-neoplastic tissues; LINC01354, CCDC8, PHYHD1, and ZNF732 have significantly lower expression of LSCC compared to adjacent non-neoplastic tissues, which were in line with bioinformatics analysis results. Conclusion:A MDGPS, with five DNA MDGs, was identified and validated in LSCC patients by combining transcriptome and methylation datasets analysis. Compared TNM stage alone, it generates more accurate estimations of the recurrence prediction and maybe offer novel research directions and prospects for individualized treatment of patients with LSCC.

Dataset Information

Construction and integrated analysis of crosstalking ceRNAs networks in laryngeal squamous cell carcinoma.

Background

Material and methods

Results

Conclusion

Publications

Construction and integrated analysis of crosstalking ceRNAs networks in laryngeal squamous cell carcinoma.

Similar Datasets

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