Dataset Information

TCGA based integrated genomic analyses of ceRNA network and novel subtypes revealing potential biomarkers for the prognosis and target therapy of tongue squamous cell carcinoma.

ABSTRACT:

Objectives

The study aimed to investigate the ceRNA network in biological development of Tongue Squamous Cell Carcinoma (TSCC) and to identify novel molecular subtypes of TSCC to screen potential biomarkers for target therapy and prognosis by using integrated genomic analysis based on The Cancer Genome Atlas (TCGA) database.

Material and methods

Data on gene expressions were downloaded from TCGA and GEO database. Differentially expressed RNAs(DERNAs) were shown by DESeq2 package in R. Functional enrichment analysis of DEmRNAs was performed using clusterprofilers in R. PPI network was established by referring to String website. Survival analysis of DERNAs was carried out by survival package in R. Interactions among mRNAs, miRNAs and lncRNAs were obtained from Starbase v3.0 and used to construct ceRNA network. Consensus Cluster Plus package was applied to identify molecular subtypes. All key genes were validated by comparing them with GEO microarray data. Statistical analyses of clinical features among different subtypes were performed using SPSS 22.0.

Results

A total of 2907 mRNAs (1366 up-regulated and 1541 down-regulated), 191miRNAs (98 up-regulated and 93 down-regulated) and 1831 lncRNAs (1151 up-regulated and 680 down-regulated) were identified from tumor and normal tissues. A ceRNA network was successfully constructed and 15 DEmRNAs, 1 DEmiRNA, 2 DElncRNAs associated with prognosis were employed. Furthermore, we firstly identified 2 molecular subtypes, basal and differentiated, and found that differentiated subtype consumed less alcohol and was related to a better overall survival.

Conclusion

The study constructed a ceRNA network and identified molecular subtypes of TSCC, and our findings provided a novel insight into this intractable cancer and potential therapeutic targets and prognostic indicators.

SUBMITTER: Li Z

PROVIDER: S-EPMC6541473 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

TCGA based integrated genomic analyses of ceRNA network and novel subtypes revealing potential biomarkers for the prognosis and target therapy of tongue squamous cell carcinoma.

Li Zaiye Z Jiang Canhua C Yuan Yongxiang Y

PloS one 20190529 5

<h4>Objectives</h4>The study aimed to investigate the ceRNA network in biological development of Tongue Squamous Cell Carcinoma (TSCC) and to identify novel molecular subtypes of TSCC to screen potential biomarkers for target therapy and prognosis by using integrated genomic analysis based on The Cancer Genome Atlas (TCGA) database.<h4>Material and methods</h4>Data on gene expressions were downloaded from TCGA and GEO database. Differentially expressed RNAs(DERNAs) were shown by DESeq2 package i ...[more]

PMID: 31141819

Similar Datasets

Project description:BackgroundHead and neck squamous cell carcinoma (HNSCC) is a frequently lethal malignancy, and the mortality is considerably high. The tumor microenvironment (TME) has been identified as a critical participation in cancer development, treatment, and prognosis. However, competing endogenous RNA (ceRNA) networks grouping with immune/stromal scores of HNSCC patients need to be further illustrated. Therefore, our study aimed to provide clues for searching promising prognostic markers of TME in HNSCC.Materials and methodsESTIMATE algorithm was used to calculate immune scores and stromal scores of the enrolled HNSCC patients. Differentially expressed genes (DEGs), lncRNAs (DELs), and miRNAs (DEMs) were identified by comparing the expression difference between high and low immune/stromal scores. Then, a ceRNA network and protein-protein interaction (PPI) network were constructed for selecting hub regulators. In addition, survival analysis was performed to access the association between immune scores, stromal scores, and differentially expressed RNAs in the ceRNA network and the overall survival (OS) of HNSCC patients. Then, the GSE65858 datasets from Gene Expression Omnibus (GEO) database was used for verification. At last, the difference between the clinical characteristics and immune cell infiltration in different expression groups of IL10RA, PRF1, and IL2RA was analyzed.ResultsSurvival analysis showed a better OS in the high immune score group, and then we constructed a ceRNA network composed of 97 DEGs, 79 DELs and 22 DEMs. Within the ceRNA network, FOXP3, IL10RA, STAT5A, PRF1, IL2RA, miR-148a-3p, miR-3065-3p, and lncRNAs, including CXCR2P1, HNRNPA1P21, CTA-384D8.36, and IGHV1OR15-2, were closely correlated with the OS of HNSCC patients. Especially, using the data from GSE65858, we successfully verified that IL10RA, PRF1, and IL2RA were not only significantly upregulated in patients high immune scores, but also their high expressions were associated with longer survival time. In addition, stratified analysis showed that PRF1 and IL2RA might be involved in the mechanism of tumor progress.ConclusionIn conclusion, we constructed a ceRNA network related to the TME of HNSCC, which provides candidates for therapeutic intervention and prognosis evaluation.

Project description:BackgroundThere is evidence that abnormal expression of lncRNAs is associated with hepatitis B virus (HBV) infection-induced hepatocellular carcinoma (HCC). However, the mechanisms remain not fully elucidated. The study aimed to identify novel lncRNAs and explore their underlying mechanisms based on the ceRNA hypothesis.MethodsThe RNA and miRNA expression profiling in 20 tumor and matched adjacent tissues from HBV-HCC patients were retrieved from the Gene Expression Omnibus database under accession numbers GSE77509 and GSE76903, respectively. Differentially expressed lncRNAs (DELs), miRNAs (DEMs), and genes (DEGs) were identified using the EdgeR package. Protein-protein interaction (PPI) network was constructed for DEGs followed by module analysis. The ceRNA network was constructed based on interaction relationships between miRNAs and mRNAs/lncRNAs. The functions of DEGs were predicted using DAVID and BinGO databases. The prognosis values (overall survival [OS] and recurrence-free survival [RFS]) of ceRNA network genes were determined using The Cancer Genome Atlas (TCGA) data with Cox regression analysis and Kaplan-Meier method.ResultsThe present study screened 643 DELs, 83 DEMs, and 1,187 DEGs. PPI network analysis demonstrated that CDK1 and CCNE1 were hub genes and extracted in functionally related modules. E2F2, CDK1, and CCNE1 were significantly enriched into cell cycle pathway. FAM182B-miR-125b-5p-E2F2 and LINC00346-miR-10a-5p-CDK1/CCNE1 ceRNA axes were obtained by constructing the ceRNA network. Patients with high expressions of DELs and DEGs in the above ceRNA axes had poor OS, while patients with the high expression of DEMs possessed excellent OS. CDK1 was also an RFS-related biomarker, with its high expression predicting poor RFS. The upregulation of LINC00346 and CDK1 but the downregulation of miR-10a-5p in HCC was validated in other microarray datasets and TCGA database.ConclusionThe LINC00346-miR-10a-5p-CDK1 axis may be an important mechanism for HBV-related HCC, and genes in this ceRNA axis may be potential prognostic biomarkers and therapeutic targets.

Dataset Information

TCGA based integrated genomic analyses of ceRNA network and novel subtypes revealing potential biomarkers for the prognosis and target therapy of tongue squamous cell carcinoma.

Objectives

Material and methods

Results

Conclusion

Publications

TCGA based integrated genomic analyses of ceRNA network and novel subtypes revealing potential biomarkers for the prognosis and target therapy of tongue squamous cell carcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets