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 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 Long intergenic non-coding RNA 271 is predictive of a poorer prognosis of papillary thyroid cancer

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Ben Ma ◽  
Tian Liao ◽  
Duo Wen ◽  
Chuanpeng Dong ◽  
Li Zhou ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Signaling Pathway ◽  
Papillary Thyroid Cancer ◽  
Enrichment Analysis ◽  
Disease Status ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Advanced Tumor Stage ◽  
Papillary Thyroid ◽  
Advanced Tumor

Abstract A number of long non-coding RNAs (lncRNAs) have been found to play critical roles in oncogenesis and tumor progression. We aimed to investigate whether lncRNAs could act as prognostic biomarkers for papillary thyroid cancer (PTC) that may assist us in evaluating disease status and prognosis for patients. We found 220 lncRNAs with expression alteration from the annotated 2773 lncRNAs approved by the HUGO gene nomenclature committee in The Cancer Genome Atlas (TCGA) dataset, of which FAM41C, CTBP1-AS2, LINC00271, HAR1A, LINC00310 and HAS2-AS1 were associated with recurrence. After adjusting classical clinicopathogical factors and BRAF V600E mutation, LINC00271 was found to be an independent risk factor for extrathyroidal extension, lymph node metastasis, advanced tumor stage III/IV and recurrence in multivariate analyses. Additionally, LINC00271 expression was significantly downregulated in PTCs versus adjacent normal tissues (P < 0.001). The Gene Set Enrichment Analysis (GSEA) revealed that genes associated with cell adhesion molecules, cell cycle, P53 signaling pathway and JAK/STAT signaling pathway were remarkably enriched in lower-LINC00271 versus higher-LINC00271 tumors. In conclusion, LINC00271 was identified as a possible suppressor gene in PTC in our study, and it may serve as a potential predictor of poor prognoses in 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 In Silico Discovery of Candidate Drugs against Covid-19

Viruses ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 404 ◽  
Author(s):  
Claudia Cava ◽  
Gloria Bertoli ◽  
Isabella Castiglioni
Keyword(s):  
Gene Expression ◽  
In Silico ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Basic Mechanism ◽  
Cell Receptor ◽  
The Cancer Genome Atlas ◽  
Pathway Enrichment Analysis

Previous studies reported that Angiotensin converting enzyme 2 (ACE2) is the main cell receptor of SARS-CoV and SARS-CoV-2. It plays a key role in the access of the virus into the cell to produce the final infection. In the present study we investigated in silico the basic mechanism of ACE2 in the lung and provided evidences for new potentially effective drugs for Covid-19. Specifically, we used the gene expression profiles from public datasets including The Cancer Genome Atlas, Gene Expression Omnibus and Genotype-Tissue Expression, Gene Ontology and pathway enrichment analysis to investigate the main functions of ACE2-correlated genes. We constructed a protein-protein interaction network containing the genes co-expressed with ACE2. Finally, we focused on the genes in the network that are already associated with known drugs and evaluated their role for a potential treatment of Covid-19. Our results demonstrate that the genes correlated with ACE2 are mainly enriched in the sterol biosynthetic process, Aryldialkylphosphatase activity, adenosylhomocysteinase activity, trialkylsulfonium hydrolase activity, acetate-CoA and CoA ligase activity. We identified a network of 193 genes, 222 interactions and 36 potential drugs that could have a crucial role. Among possible interesting drugs for Covid-19 treatment, we found Nimesulide, Fluticasone Propionate, Thiabendazole, Photofrin, Didanosine and Flutamide.

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 Downregulation of TSPAN13 by miR-369-3p inhibits cell proliferation in papillary thyroid cancer (PTC)

2018 ◽  
Author(s):  
Peng Li ◽  
Mingqiang Dong ◽  
Zhigang Wang
Keyword(s):  
Cell Proliferation ◽  
Thyroid Cancer ◽  
Papillary Thyroid Cancer ◽  
Expression Profiles ◽  
Surface Proteins ◽  
The Cancer Genome Atlas ◽  
Luciferase Reporter ◽  
Papillary Thyroid ◽  
Small Interfering Rnas

Previous studies demonstrated dysregulation of different microRNAs in thyroid cancer. Tetraspanins (TSPANs) are cell surface proteins with critical roles in many cellular processes, and implications in tumor development. Here we investigated the role of miR-369-3p in papillary thyroid cancer (PTC) and its association with TSPAN13. miR-369-3p and the TSPAN13 gene expression profiles of 513 thyroid cancer and 59 normal thyroid tissues were downloaded from the Cancer Genome Atlas database. Thyroid cancer tissues were classified according to the histological type, grouped based on low and high median miR-369-3p and TSPAN13 expression, and analyzed in relation to overall survival (OS) of patients. Human PTC cell lines (TPC-1 and GLAG-66) and human embryonic kidney 293T (HEK293T) cells were used for in vitro analysis. Transfection experiments were performed with synthetic miRNA mimics for miR-369-3p and small interfering RNAs for TSPAN13. Relative expression of miR-369-3p and TSPAN13 mRNA was determined by RT-qPCR. Protein levels of TSPAN13 were determined by western blotting. Cell proliferation (CCK-8 assay), colony formation, and apoptosis (flow cytometry) were analyzed in transfected cells. Binding sites of miR-369-3p in TSPAN13 mRNA were determined by bioinformatics analysis and dual luciferase reporter assay. miR-369-3p was downregulated and TSPAN13 upregulated in PTC, follicular thyroid cancer, and tall cell variant tissues. Both low expression of miR-369-3p and high expression of TSPAN13 were associated with shorter OS in thyroid cancer patients. Overexpression of miR-369-3p significantly suppressed proliferation and promoted apoptosis in PTC cells. TSPAN13 was a direct target of miR-369-3p, and silencing of TSPAN13 phenocopied the effect of miR-369-3p mimics in PTC cells. Overall, the downregulation of miR-369-3p and consequent upregulation of its target TSPAN13 appear to be involved in pathophysiology of PTC.

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

scholarly journals A Five Autophagy-Related Long Non-Coding RNA Prognostic Model for Patients with Lung Adenocarcinoma

2021 ◽  
Author(s):  
Boxuan Liu ◽  
Yun Zhao ◽  
Shuanying Yang
Keyword(s):  
Lung Adenocarcinoma ◽  
Risk Score ◽  
Prognostic Model ◽  
Risk Model ◽  
Cox Regression ◽  
Predictive Ability ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Lasso Regression ◽  
Cox Regression Analysis

Abstract Background: Lung adenocarcinoma is the most occurred pathological type among non-small cell lung cancer. Although huge progress has been made in terms of early diagnosis, precision treatment in recent years, the overall 5-year survival rate of a patient remains low. In our study, we try to construct an autophagy-related lncRNA prognostic signature that may guide clinical practice.Methods: The mRNA and lncRNA expression matrix of lung adenocarcinoma patients were retrieved from TCGA database. Next, we constructed a co-expression network of lncRNAs and autophagy-related genes. Lasso regression and multivariate Cox regression were then applied to establish a prognostic risk model. Subsequently, a risk score was generated to differentiate high and low risk group and a ROC curve and Nomogram to visualize the predictive ability of current signature. Finally, gene ontology and pathway enrichment analysis were executed via GSEA.Results: A total of 1,703 autophagy-related lncRNAs were screened and five autophagy-related lncRNAs (LINC01137, AL691432.2, LINC01116, AL606489.1 and HLA-DQB1-AS1) were finally included in our signature. Judging from univariate(HR=1.075, 95% CI: 1.046–1.104) and multivariate(HR =1.088, 95%CI = 1.057 − 1.120) Cox regression analysis, the risk score is an independent factor for LUAD patients. Further, the AUC value based on the risk score for 1-year, 3-year, 5-year, was 0.735, 0.672 and 0.662 respectively. Finally, the lncRNAs included in our signature were primarily enriched in autophagy process, metabolism, p53 pathway and JAK/STAT pathway. Conclusions: Overall, our study indicated that the prognostic model we generated had certain predictability for LUAD patients’ prognosis.

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