scholarly journals Integrated bioinformatics analysis and screening hub genes in papillary thyroid cancer

2020 ◽  
Author(s):  
Rong Fan ◽  
Lijin Dong ◽  
Ping Li ◽  
Xiaoming Wang ◽  
Xuewei Chen
Keyword(s):  
Gene Ontology ◽  
Survival Analysis ◽  
Thyroid Cancer ◽  
Papillary Thyroid Cancer ◽  
Enrichment Analysis ◽  
Analysis Tool ◽  
Papillary Thyroid ◽  
Hub Genes ◽  
New Biomarkers ◽  
Online Software

Abstract Background With the increasing incidence, papillary thyroid cancer (PTC) is receiving more and more attention, but the pathogenesis of which is still not completely elucidated. The purpose of this study was to explore key biomarkers and new therapeutic targets in PTC. Methods GEO2R and Venn online software were used for differential gene screening analysis. Hub genes were screened via STRING and Cytoscape, following Gene Ontology and KEGG enrichment analysis. Finally, survival analysis and expression validation were performed via UALCAN online software and immunohistochemistry. Results We screened 334 consistently differentially expressed genes (DEGs), composed of 136 upregulated genes and 198 downregulated genes. Gene ontology enrichment analysis suggested that DEGs mainly enriched in the cancer-related pathways and functions. PPI network visualization was performed to select 17 upregulated and 13 downregulated DEGs. Finally, the expression verification and overall survival analysis conducted in the Gene Expression Profiling Interactive Analysis Tool (GEPIA) and UALCAN showed that LPAR5, TFPI and ENTPD1 were related to the development of PTC and the prognosis of PTC patients, and the expression of LPAR5 was verified by tissue chip. Conclusions In summary, the hub genes and pathways identified in the present study not only provided new biomarkers for PTC, but also will be useful for elucidating the pathogenesis of PTC.

scholarly journals Integrated bioinformatics analysis and screening of hub genes in papillary thyroid carcinoma

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0251962
Author(s):  
Rong Fan ◽  
Lijin Dong ◽  
Ping Li ◽  
Xiaoming Wang ◽  
Xuewei Chen
Keyword(s):  
Gene Ontology ◽  
Survival Analysis ◽  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Differentially Expressed Genes ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Papillary Thyroid ◽  
Hub Genes ◽  
Online Software

Background With the increasing incidence of papillary thyroid carcinoma (PTC), PTC continues to garner attention worldwide; however its pathogenesis remains to be elucidated. The purpose of this study was to explore key biomarkers and potential new therapeutic targets for, PTC. Methods GEO2R and Venn online software were used for screening of differentially expressed genes. Hub genes were screened via STRING and Cytoscape, followed by Gene Ontology and KEGG enrichment analysis. Finally, survival analysis and expression validation were performed using the UALCAN online software and immunohistochemistry. Results We identified 334 consistently differentially expressed genes (DEGs) comprising 136 upregulated and 198 downregulated genes. Gene Ontology enrichment analysis results suggested that the DEGs were mainly enriched in cancer-related pathways and functions. PPI network visualization was performed and 17 upregulated and 13 downregulated DEGs were selected. Finally, the expression verification and overall survival analysis conducted using the Gene Expression Profiling Interactive Analysis Tool (GEPIA) and UALCAN showed that LPAR5, TFPI, and ENTPD1 were associated with the development of PTC and the prognosis of PTC patients, and the expression of LPAR5, TFPI and ENTPD1 was verified using a tissue chip. Conclusions In summary, the hub genes and pathways identified in the present study not only provide information for the development of new biomarkers for PTC but will also be useful for elucidation of the pathogenesis of PTC.

scholarly journals Comprehensive Identification of Potential Crucial Genes and miRNA-mRNA Regulatory Networks in Papillary Thyroid Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-25
Author(s):  
Ben-yu Nan ◽  
Guo-Feng Xiong ◽  
Zi-Rui Zhao ◽  
Xi Gu ◽  
Xin-Sheng Huang
Keyword(s):  
Thyroid Cancer ◽  
Papillary Thyroid Cancer ◽  
Regulatory Networks ◽  
Thyroid Nodules ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Papillary Thyroid ◽  
Ppi Network ◽  
Hub Genes ◽  
Age Related

Background. Thyroid cancer is the most common endocrine malignancy, with a recent global increase of 20% in age-related incidence. Ultrasonography and ultrasonography-guided fine-needle aspiration biopsy (FNAB) are the most widely used diagnostic tests for thyroid nodules; however, it is estimated that up to 25% of thyroid biopsies are cytologically inconclusive. Molecular markers can help guide patient-oriented and targeted treatment of thyroid nodules and thyroid cancer. Methods. Datasets related to papillary thyroid cancer (PTC) or thyroid carcinoma (GSE129562, GSE3678, GSE54958, GSE138042, and GSE124653) were downloaded from the GEO database and analysed using the Limma package of R software. For functional enrichment analysis, the Kyoto Encyclopedia of Genes and Genomes pathway analysis and Gene Ontology were applied to differentially expressed genes (DEGs) using the Metascape website. A protein-protein interaction (PPI) network was built from the STRING database. Gene expression, protein expression, immunohistochemistry, and potential functional gene survival were analysed using the GEPIA website, the Human Protein Atlas website, and the UALCAN website. Potential target miRNAs were predicted using the miRDB and Starbase datasets. Results. We found 219 upregulated and 310 downregulated DEGs, with a cut-off of p < 0.01 and ∣ log   FC ∣ > 1.5 . The DEGs in papillary thyroid cancer were mainly enriched in extracellular structural organisation. At the intersection of the PPI network and Metascape MCODEs, the hub genes in common were identified as FN1, APOE, CLU, and SDC2. In the targeted regulation network of miRNA-mRNA, the hsa-miR-424-5p was found to synchronously modulate two hub genes. Survival analysis showed that patients with high expression of CLU and APOE had better prognosis. Conclusions. CLU and APOE are involved in the molecular mechanism of papillary thyroid cancer. The hsa-miR-424-5p might have the potential to reverse the processes of papillary thyroid cancer by modulating the hub genes. These are potential targets for the treatment of patients with papillary thyroid cancer.

Identification of gene co-expression modules and hub genes associated with lymph node metastasis of papillary thyroid cancer

Endocrine ◽  
2019 ◽  
Vol 66 (3) ◽  
pp. 573-584 ◽  
Author(s):  
Tianyu Zhai ◽  
Dilidaer Muhanhali ◽  
Xi Jia ◽  
Zhiyong Wu ◽  
Zhenqin Cai ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Papillary Thyroid Cancer ◽  
Papillary Thyroid ◽  
Hub Genes ◽  
Node Metastasis

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 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.

Four genes relevant to pathological grade and prognosis in ovarian cancer

2020 ◽  
Vol 29 (2) ◽  
pp. 169-178 ◽  
Author(s):  
Xue Pan ◽  
Ying Chen ◽  
Song Gao
Keyword(s):  
Ovarian Cancer ◽  
Gene Ontology ◽  
Survival Analysis ◽  
Network Analysis ◽  
Enrichment Analysis ◽  
Progression Free Survival ◽  
Receptor Interaction ◽  
Pathological Grade ◽  
Hub Genes ◽  
Tissue Samples

BACKGROUND: Ovarian cancer is the common tumor in female, the prognostic of which is influenced by a series of factors. In this study, 4 genes relevant to pathological grade in ovarian cancer were screened out by the construction of weighted gene co-expression network analysis. METHODS: GSE9891 with 298 ovarian cancer cases had been used to construct co-expression networks. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses was used to analyze the possible mechanism of genes involved in the malignant process of ovarian cancer. Hub genes were validated in other independent datasets, such as GSE63885, GSE26193 and GSE30161. Survival analysis based on the hub genes was performed by website of Kaplan Meier-plotter. RESULTS: The result based on weighted gene co-expression network analysis indicated that turquoise module has the highest association with pathological grade. Gene Ontology enrichment analysis revealed that the genes in turquoise module main enrichment in inflammatory response and immune response. Kyoto Encyclopedia of Genes and Genomes enrichment analysis revealed that the genes in turquoise module main enrichment in cytokine-cytokine receptor interaction and chemokine signaling pathway. In turquoise module, a total of 4 hub genes (MS4A4A, CD163, CPR65, MS4A6A) were identified. Then, 4 hub genes were effectively verified in the test datasets (GSE63885, GSE26193 and GSE30161) and tissue samples from Shengjing Hospital of China Medical University. Survival analysis indicated that the 4 hub genes were associated with poor progression-free survival of ovarian cancer. CONCLUSIONS: In conclusion, 4 hub genes (MS4A4A, CD163, CPR65, MS4A6A) were verified associated with pathological grade of ovarian cancer. Moreover, MS4A4A, CD163, MS4A6A may serve as a surface marker for M2 macrophages. Targeting the 4 hub genes may can improve the prognosis of ovarian cancer.

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 a Four-miRNA Signature Predicts Prognosis in Papillary Thyroid Cancer

2021 ◽  
Author(s):  
YANG FAN ◽  
Hongzhong zhou
Keyword(s):  
Thyroid Cancer ◽  
High Risk ◽  
Papillary Thyroid Cancer ◽  
Papillary Thyroid ◽  
Normal Tissues ◽  
Significant Difference ◽  
Differentially Expressed Mirnas ◽  
Score Model ◽  
New Biomarkers

Abstract Background: In newly diagnosed patients with thyroid cancer, papillary thyroid cancer (PTC), accounts for ninety percent of all cases. Although PTC is known as a relatively adolescent malignant disease, there still is a high possibility of recurrence in PTC patients, who suffered from poor prognosis. Therefore, new biomarkers are necessary to guide more effective stratification of PTC patients and personalization of therapy to avoid overtreatment or inadequate treatment. Accumulating evidence demonstrates that miRNAs have broad application prospects as diagnostic biomarkers in cancer. Methods: The present study aims to explore novel markers consists of miRNA-associated signature for PTC prognostication, utilizing data from the TCGA database. We obtained and analyzed data of 497 PTC patients from the TCGA. The patients were randomly assigned to a training cohort or testing cohort. Results: We discovered 237 differentially expressed miRNAs in tumorous thyroid tissues comparing to normal tissues The effect evaluation of excavated differently expressed miRNAs was conducted by our risk score model. We then successfully generated a four-miRNA potential prognostic signature, which reliably distinguishes patients from high risk and low risk with a significant difference in overall survival (P <0.01) and was effective in predicting five-year disease survival. Conclusions: Our results indicated a four miRNAs signature that has a robust predicting effect on the prognosis of PTC. Therefore, we would recommend more radical treatment and closer follow-up of high-risk individuals.

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