scholarly journals Identification of pivotal lncRNAs in papillary thyroid cancer using lncRNA–mRNA–miRNA ceRNA network analysis

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7441 ◽  
Author(s):  
Weiwei Liang ◽  
Fangfang Sun
Keyword(s):  
Gene Expression ◽  
Thyroid Cancer ◽  
Network Analysis ◽  
Papillary Thyroid Cancer ◽  
Enrichment Analysis ◽  
Integrated Analysis ◽  
Pathway Enrichment Analysis ◽  
Papillary Thyroid ◽  
Cerna Network ◽  
Go Terms

Background To identify pivotal lncRNAs in papillary thyroid cancer (PTC) using lncRNA–mRNA–miRNA ceRNA network analysis. Methods We obtained gene expression profiles from the gene expression omnibus database. Cancer specific lncRNA, cancer specific miRNA and cancer specific mRNA were identified. An integrated analysis was conducted to detect potential lncRNA–miRNA–mRNA ceRNA in regulating disease transformation. The lncRNA regulated gene ontology (GO) terms and regulated pathways were performed by function analysis. Survival analysis was performed for the pivotal lncRNAs. Results A total of four lncRNAs, 15 miRNAs and 375 mRNAs are identified as the key mediators in the pathophysiological processes of PTC. GO annotation enrichment analysis showed the most relevant GO terms are signal transduction, integral component of membrane and calcium ion binding. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis showed different changed genes mainly enriched in pathways in cancer, PI3K-Akt signaling pathway and focal adhesion. Among four lncRNAs, only SLC26A4-AS1 was significantly associated with PTC patient disease free survival. Conclusion This study has constructed lncRNA–mRNA–miRNA ceRNA networks in PTC. The study provides a set of pivotal lncRNAs for future investigation into the molecular mechanisms.

scholarly journals Identification of immune-related lncRNAs to improve the prognosis prediction for patients with papillary thyroid cancer

2021 ◽  
Vol 41 (2) ◽  
Author(s):  
Zhiyang Li ◽  
Weixun Lin ◽  
Jiehua Zheng ◽  
Weida Hong ◽  
Juan Zou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Thyroid Cancer ◽  
Papillary Thyroid Cancer ◽  
Predictive Ability ◽  
Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Clinical Samples ◽  
Pathway Enrichment Analysis ◽  
Lasso Regression ◽  
Papillary Thyroid

Abstract Objective: To identify immune-related long non-coding RNAs (lncRNAs) in papillary thyroid cancer (PTC). Methods: The Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases were used to obtain the gene expression profile. Immune-related lncRNAs were screened from the Molecular Signatures Database v4.0 (MsigDB). We performed a survival analysis of critical lncRNAs. Further, the function of prognostic lncRNAs was inferred using the Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) to clarify the possible mechanisms underlying their predictive ability. The assessment was performed in clinical samples and PTC cells. Results: We obtained 4 immune-related lncRNAs, 15 microRNAs (miRNAs), and 375 mRNAs as the key mediators in the pathophysiological processes of PTC from the GEO database. Further, Lasso regression analysis identified seven prognostic markers (LINC02550, SLC26A4-AS1, ACVR2B-AS1, AC005479.2, LINC02454, and AL136366.1), most of which were related to tumor development. The KEGG pathway enrichment analysis showed different, changed genes mainly enriched in the cancer-related pathways, PI3K-Akt signaling pathway, and focal adhesion. Only SLC26A4-AS1 had an intersection in the results of the two databases. Conclusion: LncRNA SLC26A4-AS1, which is the most associated with prognosis, may play an oncogenic role in the development of PTC.

scholarly journals BCL2 and hsa-miR-181a-5p are potential biomarkers associated with papillary thyroid cancer based on bioinformatics analysis

2019 ◽  
Vol 17 (1) ◽  
Author(s):  
Cong Zhang ◽  
Chunrui Bo ◽  
Lunhua Guo ◽  
Pingyang Yu ◽  
Susheng Miao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Thyroid Cancer ◽  
Gene Regulatory Network ◽  
Papillary Thyroid Cancer ◽  
Regulatory Network ◽  
Mirna Gene ◽  
Cancer Type ◽  
Papillary Thyroid ◽  
Ppi Network ◽  
Gene Regulatory

Abstract Background The morbidity of thyroid carcinoma has been rising worldwide and increasing faster than any other cancer type. The most common subtype with the best prognosis is papillary thyroid cancer (PTC); however, the exact molecular pathogenesis of PTC is still not completely understood. Methods In the current study, 3 gene expression datasets (GSE3678, GSE3467, and GSE33630) and 2 miRNA expression datasets (GSE113629 and GSE73182) of PTC were selected from the Gene Expression Omnibus (GEO) database and were further used to identify differentially expressed genes (DEGs) and deregulated miRNAs between normal thyroid tissue samples and PTC samples. Then, Gene Ontology (GO) and pathway enrichment analyses were conducted, and a protein-protein interaction (PPI) network was constructed to explore the potential mechanism of PTC carcinogenesis. The hub gene detection was performed using the CentiScaPe v2.0 plugin, and significant modules were discovered using the MCODE plugin for Cytoscape. In addition, a miRNA-gene regulatory network in PTC was constructed using common deregulated miRNAs and DEGs. Results A total of 263 common DEGs and 12 common deregulated miRNAs were identified. Then, 6 significant KEGG pathways (P < 0.05) and 82 significant GO terms were found to be enriched, indicating that PTC was closely related to amino acid metabolism, development, immune system, and endocrine system. In addition, by constructing a PPI network and miRNA-gene regulatory network, we found that hsa-miR-181a-5p regulated the most DEGs, while BCL2 was targeted by the most miRNAs. Conclusions The results of this study suggested that hsa-miR-181a-5p and BCL2 and their regulatory networks may play important roles in the pathogenesis of PTC.

Characteristics of lipid metabolism-related gene expression-based molecular subtype in papillary thyroid cancer

2020 ◽  
Vol 52 (10) ◽  
pp. 1166-1170
Author(s):  
Midie Xu ◽  
Tuanqi Sun ◽  
Shishuai Wen ◽  
Tingting Zhang ◽  
Xin Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Thyroid Cancer ◽  
Lipid Metabolism ◽  
Papillary Thyroid Cancer ◽  
Molecular Subtype ◽  
Papillary Thyroid ◽  
Related Gene

scholarly journals Alternative mutations of BRAF, RET and NTRK1 are associated with similar but distinct gene expression patterns in papillary thyroid cancer

Oncogene ◽  
2004 ◽  
Vol 23 (44) ◽  
pp. 7436-7440 ◽  
Author(s):  
Milo Frattini ◽  
Cristina Ferrario ◽  
Paola Bressan ◽  
Debora Balestra ◽  
Loris De Cecco ◽  
...  
Keyword(s):  
Gene Expression ◽  
Thyroid Cancer ◽  
Papillary Thyroid Cancer ◽  
Expression Patterns ◽  
Gene Expression Patterns ◽  
Papillary Thyroid ◽  
Distinct Gene

scholarly journals Liver X Receptor β Related to Tumor Progression and Ribosome Gene Expression in Papillary Thyroid Cancer

2020 ◽  
Vol 35 (3) ◽  
pp. 656-668
Author(s):  
Seonhyang Jeong ◽  
In-Kyu Kim ◽  
Hyunji Kim ◽  
Moon Jung Choi ◽  
Jandee Lee ◽  
...  
Keyword(s):  
Gene Expression ◽  
Thyroid Cancer ◽  
Tumor Progression ◽  
Papillary Thyroid Cancer ◽  
Liver X Receptor ◽  
Papillary Thyroid
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