Identification of Differentially Expressed Genes Associated with Papillary Thyroid Carcinoma

2020 ◽  
Vol 23 (6) ◽  
pp. 546-553
Author(s):  
Hongyuan Cui ◽  
Mingwei Zhu ◽  
Junhua Zhang ◽  
Wenqin Li ◽  
Lihui Zou ◽  
...  
Keyword(s):  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Cellular Proliferation ◽  
Mrna Level ◽  
Thyroid Tissue ◽  
Differentially Expressed ◽  
Thyroid Tumors ◽  
Papillary Thyroid

Objective: Next-generation sequencing (NGS) was performed to identify genes that were differentially expressed between normal thyroid tissue and papillary thyroid carcinoma (PTC). Materials & Methods: Six candidate genes were selected and further confirmed with quantitative real-time polymerase chain reaction (qRT-PCR), and immunohistochemistry in samples from 24 fresh thyroid tumors and adjacent normal tissues. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was used to investigate signal transduction pathways of the differentially expressed genes. Results: In total, 1690 genes were differentially expressed between samples from patients with PTC and the adjacent normal tissue. Among these, SFRP4, ZNF90, and DCN were the top three upregulated genes, whereas KIRREL3, TRIM36, and GABBR2 were downregulated with the smallest p values. Several pathways were associated with the differentially expressed genes and involved in cellular proliferation, cell migration, and endocrine system tumor progression, which may contribute to the pathogenesis of PTC. Upregulation of SFRP4, ZNF90, and DCN at the mRNA level was further validated with RT-PCR, and DCN expression was further confirmed with immunostaining of PTC samples. Conclusion: These results provide new insights into the molecular mechanisms of PTC. Identification of differentially expressed genes should not only improve the tumor signature for thyroid tumors as a diagnostic biomarker but also reveal potential targets for thyroid tumor treatment.

scholarly journals Identification of Differentially Expressed Kinase and Screening Potential Anticancer Drugs in Papillary Thyroid Carcinoma

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Huairong Zhang ◽  
Bo Gao ◽  
Bingyin Shi
Keyword(s):  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Signaling Pathway ◽  
Protein Kinases ◽  
Molecular Mechanisms ◽  
Kinase Inhibitors ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Papillary Thyroid

Aim. We aim to identify protein kinases involved in the pathophysiology of papillary thyroid carcinoma (PTC) in order to provide potential therapeutic targets for kinase inhibitors and unfold possible molecular mechanisms.Materials and Methods. The gene expression profile of GSE27155 was analyzed to identify differentially expressed genes and mapped onto human protein kinases database. Correlation of kinases with PTC was addressed by systematic literature search, GO and KEGG pathway analysis.Results. The functional enrichment analysis indicated that “mitogen-activated protein kinases pathway” expression was extremely enriched, followed by “neurotrophin signaling pathway,” “focal adhesion,” and “GnRH signaling pathway.” MAPK, SRC, PDGFRa, ErbB, and EGFR were significantly regulated to correct these pathways. Kinases investigated by the literature on carcinoma were considered to be potential novel molecular therapeutic target in PTC and application of corresponding kinase inhibitors could be possible therapeutic tool.Conclusion. SRC, MAPK, and EGFR were the most important differentially expressed kinases in PTC. Combined inhibitors may have high efficacy in PTC treatment by targeting these kinases.

scholarly journals Network Analyses of Integrated Differentially Expressed Genes in Papillary Thyroid Carcinoma to Identify Characteristic Genes

Genes ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 45 ◽  
Author(s):  
Junliang Shang ◽  
Qian Ding ◽  
Shasha Yuan ◽  
Jin-Xing Liu ◽  
Feng Li ◽  
...  
Keyword(s):  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Differentially Expressed Genes ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Papillary Thyroid ◽  
Topological Properties ◽  
Network Analyses ◽  
Genetic Mechanisms

Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer. Identifying characteristic genes of PTC are of great importance to reveal its potential genetic mechanisms. In this paper, we proposed a framework, as well as a measure named Normalized Centrality Measure (NCM), to identify characteristic genes of PTC. The framework consisted of four steps. First, both up-regulated genes and down-regulated genes, collectively called differentially expressed genes (DEGs), were screened and integrated together from four datasets, that is, GSE3467, GSE3678, GSE33630, and GSE58545; second, an interaction network of DEGs was constructed, where each node represented a gene and each edge represented an interaction between linking nodes; third, both traditional measures and the NCM measure were used to analyze the topological properties of each node in the network. Compared with traditional measures, more genes related to PTC were identified by the NCM measure; fourth, by mining the high-density subgraphs of this network and performing Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, several meaningful results were captured, most of which were demonstrated to be associated with PTC. The experimental results proved that this network framework and the NCM measure are useful for identifying more characteristic genes of PTC.

Identification of biomarkers associated with cervical lymph node metastasis in papillary thyroid carcinoma: Evidence from an integrated bioinformatic analysis

2021 ◽  
pp. 1-10
Author(s):  
Zheng Zhang ◽  
Shuangshuang Zhao ◽  
Keke Wang ◽  
Mengyuan Shang ◽  
Zheming Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lymph Node ◽  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Differentially Expressed Genes ◽  
Cervical Lymph Node ◽  
Receptor Activity ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Papillary Thyroid

Integrated analysis of accumulated data is an effective way to obtain reliable potential diagnostic molecular of cervical lymph node metastases (LNM) in papillary thyroid carcinoma (PTC). The benefits of prophylactic lymph node dissection (PLND) for these clinically node-negative (cN0) patients remained considerable controversies. Hence, elucidation of the mechanisms of LNM and exploration of potential biomarkers and prognostic indicators are essential for accurate diagnosis of LNM in PTC patients. Up to date, advanced microarray and bioinformatics analysis have advanced an understanding of the molecular mechanisms of disease occurrence and development, which are necessary to explore genetic changes and identify potential diagnostic biomarkers. In present study, we performed a comprehensive analysis of the differential expression, biological functions, and interactions of LNM-related genes. Two publicly available microarray datasets GSE60542 and GSE129562 were available from Gene Expression Omnibus (GEO) database. Differentially expressed genes between clinically node-positive (cN1) and cN0 PTC samples were screened by an integrated analysis of multiple gene expression profile after gene reannotation and batch normalization. Our results identified 48 differentially expressed genes (DEGs) genetically associated with LNM in PTC patients. Gene ontology (GO) analyses revealed the changes in the modules were mostly enriched in the regulation of MHC class II receptor activity, the immune receptor activity, and the peptide antigen binding. Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis of DEGs displayed that the intestinal immune network for IgA production, staphylococcus aureus infection, and cell adhesion molecules (CAMs). To screen core genes related to LNM of PTC from the protein-protein interaction network, top 10 hub genes were identified with highest scores. Our results help us understand the exact mechanisms underlying the metastasis of cervical LNM in PTC tissues and pave an avenue for the progress of precise medicine for individual patients.

scholarly journals Validation of Reference Genes for Normalization of Relative qRT-PCR Studies in Papillary Thyroid Carcinoma

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
S. Adeleh Razavi ◽  
Mandana Afsharpad ◽  
Mohammad Hossein Modarressi ◽  
Maryam Zarkesh ◽  
Parichehreh Yaghmaei ◽  
...  
Keyword(s):  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Internal Control ◽  
Reference Genes ◽  
Thyroid Tissue ◽  
Optimal Number ◽  
Thyroid Tumors ◽  
Papillary Thyroid ◽  
Tissue Samples ◽  
Qrt Pcr

Abstract Quantitative reverse transcription polymerase chain reaction (qRT-PCR) in thyroid tumors require accurate data normalization, however, there are no sufficient studies addressing the suitable reference genes for gene expression analysis in malignant and normal thyroid tissue specimens. The purpose of this study was to identify valid internal control genes for normalization of relative qRT-PCR studies in human papillary thyroid carcinoma tissue samples. The expression characteristics of 12 candidate reference genes (GAPDH, ACTB, HPRT1, TBP, B2M, PPIA, 18SrRNA, HMBS, GUSB, PGK1, RPLP0, and PGM1) were assessed by qRT-PCR in 45 thyroid tissue samples (15 papillary thyroid carcinoma, 15 paired normal tissues and 15 multinodular goiters). These twelve candidate reference genes were selected by a systematic literature search. GeNorm, NormFinder, and BestKeeper statistical algorithms were applied to determine the most stable reference genes. The three algorithms were in agreement in identifying GUSB and HPRT1 as the most stably expressed genes in all thyroid tumors investigated. According to the NormFinder software, the pair of genes including ‘GUSB and HPRT1’ or ‘GUSB and HMBS’ or ‘GUSB and PGM1’ were the best combinations for selection of pair reference genes. The optimal number of genes required for reliable normalization of qPCR data in thyroid tissues would be three according to calculations made by GeNorm algorithm. These results suggest that GUSB and HPRT1 are promising reference genes for normalization of relative qRT-PCR studies in papillary thyroid carcinoma.

scholarly journals Identification of key genes of papillary thyroid carcinoma by integrated bioinformatics analysis

2020 ◽  
Vol 40 (8) ◽  
Author(s):  
Gang Xue ◽  
Xu Lin ◽  
Jing-Fang Wu ◽  
Da Pei ◽  
Dong-Mei Wang ◽  
...  
Keyword(s):  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Differentially Expressed Genes ◽  
Disease Free Survival ◽  
Differentially Expressed ◽  
Mrna Levels ◽  
Papillary Thyroid ◽  
Positive Role ◽  
Immune Infiltration ◽  
Key Genes

Abstract Background: Papillary thyroid carcinoma (PTC) is one of the fastest-growing malignant tumor types of thyroid cancer. Therefore, identifying the interaction of genes in PTC is crucial for elucidating its pathogenesis and finding more specific molecular biomarkers. Methods: Four pairs of PTC tissues and adjacent tissues were sequenced using RNA-Seq, and 3745 differentially expressed genes were screened (P<0.05, |logFC|>1). The enrichment analysis indicated that the vast majority of differentially expressed genes (DEGs) may play a positive role in the development of cancer. Then, the significant modules were analyzed using Cytoscape software in the protein–protein interaction network. Survival analysis, TNM analysis, and immune infiltration analysis of key genes were analyzed. And the expression of ADORA1, APOE, and LPAR5 genes were verified by qPCR in PTC compared with matching adjacent tissues. Results: Twenty-five genes were identified as hub genes with nodes greater than 10. The expression of 25 genes were verified by the GEPIA database, and the overall survival and disease-free survival analyses were conducted with Kaplan–Meier plotter. We found only three genes were confirmed with our validation and were statistically significant in PTC, namely ADORA1, APOE, and LPAR5. Further analysis found that the mRNA levels and methylation degree of these three genes were significantly correlated with the TNM staging of PTC. And these three genes were related to PTC immune infiltration. Verification of the expression of these three genes by RT-qPCR and Western blot further confirmed the reliability of our results. Conclusion: Our study identified three genes that may play key regulatory roles in the development, metastasis, and immune infiltration of papillary thyroid carcinoma.

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 lncRNA-miRNA-mRNA ceRNA Network in Thyroid Carcinoma from The Cancer Genome Atlas

2020 ◽  
Author(s):  
Guoheng Mo ◽  
Qunguang Jiang ◽  
Zixuan Wang ◽  
Zhaoting Zheng ◽  
XiaoSi Chen
Keyword(s):  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Molecular Mechanisms ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Papillary Thyroid ◽  
Cerna Network ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Abstract Increasing evidence indicates that the competitive endogenous RNA (ceRNA) hypothesis, that is, long non-coding RNA (LncRNA) can competitively bind microRNA (miRNA) through miRNA response elements to affect the expression of target RNA, and dysregulation of LncRNA expression plays a key role in tumor progression. The papillary thyroid carcinoma that we studied is the most significant pathological type of thyroid cancer, but its ceRNA network has not been extensively evaluated. We analyzed level-3 data from RNA-Seq of 58 para-carcinoma tissues and 501 patients with primary papillary thyroid carcinoma (PTC) using the DEseq software package and downloaded clinical information from The Cancer Genome Atlas (TCGA) to find potential biomarkers or therapeutic targets. As a result, 149 differential miRNAs were selected, including 117 up -regulated, 32 down-regulated, and 3099 differential mRNAs, including 1976 up-regulated, 1123 down-regulated, and 434 differential lncRNAs, including 331 up-regulated and 103 down-regulated (Fold Change > 2, P < 0.05). The interactions between these differentially expressed RNA groups constitute the ceRNA network of PTC. Moreover, we used the microde database to predict the miRNAs that may be acted by the above screened differential lncRNAs and intersected with the selected miRNAs, and further predicted the target genes of the intersecting miRNAs by TargetScan, miRTarBase and miRDB, and intersected with the selected mRNAs. From the constructed ceRNA network we can see that Linc00460 may cause the invasion and metastasis of PTC by competitively inhibiting hsa-mir-150 and upregulating the expression of its downstream target gene EREG. Our study identified a series of lncRNAs associated with PTC progression and prognosis, and this complex ceRNA interaction network provides guidance for better understanding of the molecular mechanisms of PTC and can be used as an effective diagnostic tool for PTC invasion, metastasis and prognosis. Kaplan-Meier analysis of the differentially expressed RNAs associated with PTC pathogenesis confirmed that the lncRNAs AC097717.1, C20orf203, EMX2OS were potentially associated with the prognosis of PTC (P<0.05).

scholarly journals Validation of MicroRNA-188-5p Inhibition Power on Tumor Cell Proliferation in Papillary Thyroid Carcinoma

2020 ◽  
Vol 29 ◽  
pp. 096368972091830 ◽  
Author(s):  
Ping Zhou ◽  
Andrew Irving ◽  
Huifang Wu ◽  
Juan Luo ◽  
Johana Aguirre ◽  
...  
Keyword(s):  
Cell Proliferation ◽  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Tumor Cell ◽  
Cellular Proliferation ◽  
Tumor Cell Proliferation ◽  
Papillary Thyroid ◽  
Tumor Tissues ◽  
Potential Biomarker ◽  
And Function

Given the crucial role of microRNAs in the cellular proliferation of various types of cancers, we aimed to analyze the expression and function of a cellular proliferation-associated miR-188-5p in papillary thyroid carcinoma (PTC). Here we demonstrate that miR-188-5p is downregulated in PTC tumor tissues compared with the associated noncancerous tissues. We also validate that the miR-188-5p overexpression suppressed the PTC cancer cell proliferation. In addition, fibroblast growth factor 5 (FGF5) is observed to be downregulated in the PTC tumor tissues compared with the associated noncancerous tissues. Subsequently, FGF5 is identified as the direct functional target of miR-188-5p. Moreover, the silencing of FGF5 was found to inhibit PTC cell proliferation, which is the same pattern as miR-188-5p overexpression. These results suggest that miR-188-5p-associated silencing of FGF5 inhibits tumor cell proliferation in PTC. It also highlights the importance of further evaluating miR-188-5p as a potential biomarker and therapy target in PTC.

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