Dataset Information

Identification of Biomarkers Based on Differentially Expressed Genes in Papillary Thyroid Carcinoma.

ABSTRACT: The incidence of papillary thyroid carcinoma (PTC) is increasing rapidly throughout the world. Hence, there is an urgent need for identifying more specific and sensitive biomarkers to explorate the pathogenesis of PTC. In this study, three pairs of stage I PTC tissues and matched normal adjacent tissues were sequenced by RNA-Seq, and 719 differentially expressed genes (DEGs) were screened. KEGG pathway enrichment analyses indicated that the DEGs were significantly enriched in 28 pathways. A total of 18 nodes consisting of 20 DEGs were identified in the top 10% of KEGG integrated networks. The functions of DEGs were further analysed by GO. The 13 selected genes were confirmed by qRT-PCR in 16 stage I PTC patients and by The Cancer Genome Atlas (TCGA) database. The relationship interactions between DEGs were analysed by protein-protein interaction networks and chromosome localizations. Finally, four newly discovered genes, COMP, COL3A1, ZAP70, and CD247, were found to be related with PTC clinical phenotypes, and were confirmed by Spearman's correlation analyses in TCGA database. These four DEGs might be promising biomarkers for early-stage PTC, and provide an experimental foundation for further exploration of the pathogenesis of early-stage PTC.

SUBMITTER: Han J

PROVIDER: S-EPMC6028435 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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Identification of Biomarkers Based on Differentially Expressed Genes in Papillary Thyroid Carcinoma.

Han Jun J Chen Meijun M Wang Yihan Y Gong Boxuan B Zhuang Tianwei T Liang Lingyu L Qiao Hong H

Scientific reports 20180702 1

The incidence of papillary thyroid carcinoma (PTC) is increasing rapidly throughout the world. Hence, there is an urgent need for identifying more specific and sensitive biomarkers to explorate the pathogenesis of PTC. In this study, three pairs of stage I PTC tissues and matched normal adjacent tissues were sequenced by RNA-Seq, and 719 differentially expressed genes (DEGs) were screened. KEGG pathway enrichment analyses indicated that the DEGs were significantly enriched in 28 pathways. A tota ...[more]

PMID: 29967488

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Project description:BackgroundThe techniques of DNA microarray and bioinformatic analysis have exhibited efficiency in identifying dysregulated gene expression in human cancers. In this study, we used integrated bioinformatics analysis to improve our understanding of the pathogenesis of papillary thyroid cancer (PTC).MethodsIn this study, we integrated four Gene Expression Omnibus (GEO) datasets, GSE33630, GSE35570, GSE60542 and GSE29265, including 136 normal samples and 157 PTC specimens. The contents of the four datasets are based on GPL570, an Affymetrix Human Genome U133 Plus 2.0 array. Gene ontology (GO) analysis was used to identify characteristic the biological attributes of differentially expressed genes (DEGs) between PTC and normal samples. GO annotation was performed on the DEGs obtained, and the process relied on the DAVID online tool. Kyoto Encyclopedia of Genes and Genomes (KEGG) approach enrichment analyses were adopted to obtain the basic functions of the DEGs. The KOBAS online analysis database was used to complete DEG KEGG pathway comparison and analysis. The search tool (STRING) database was mainly used to search for interacting genes and complete the construction of protein-protein interaction (PPI) networks.ResultsFive hundred-ninety DEGs were consistently expressed in the four datasets; 327 of them were upregulated, while 263 were downregulated. Ten DEGs, including five upregulated (ENTPD1, THRSP, KLK10, ADAMTS9, MIR31HG) and five downregulated (SCARA5, EPHB1, CHRDL1, LOC440934, FOXP2) genes, were randomly selected for q-PCR in our own tissue samples to validate the integrated data. The most highly enriched GO terms were extracellular exosome (GO:0070062), cell adhesion (GO:0070062), positive regulation of gene expression (GO:0010628), and extracellular matrix (ECM) organization (GO:0030198). KEGG pathway analysis was performed, and it was found that abnormally expressed genes effectively participated in pathways such as tyrosine metabolism, complement and coagulation cascades, cell adhesion molecules (CAMs), transcriptional misregulation and ECM-receptor interaction pathways.ConclusionsFive hundred-ninety DEGs were identified in PTC by integrated microarray analysis. The GO and KEGG analyses presented here suggest that the DEGs were enriched in extracellular exosome, tyrosine metabolism, CAMs, complement and coagulation cascades, transcriptional misregulation and ECM-receptor interaction pathways. Functional studies of PTC should focus on these pathways.

Project description:BackgroundPapillary thyroid carcinoma (PTC) accounts for most of the proportion of thyroid cancer (TC). The objective of this study was to identify diagnostic, differentially expressed long noncoding RNAs (lncRNAs) and microRNAs (miRNAs), contributing to understanding the epigenetics mechanism of PTC.MethodsThe data of lncRNA, miRNA, and mRNA were downloaded from the Cancer Genome Atlas (TCGA) dataset, followed by functional analysis of differentially expressed mRNAs. Optimal diagnostic lncRNA and miRNA biomarkers were identified via random forest. The regulatory network between optimal diagnostic lncRNA and mRNAs and optimal diagnostic miRNA and mRNAs was identified, followed by the construction of ceRNA network of lncRNA-mRNA-miRNA. Expression validation and diagnostic analysis of lncRNAs, miRNAs, and mRNAs were performed. Overexpression of ADD3-AS1 was performed in PTC-UC3 cell lines, and cell proliferation and invasion assay were used for investigating the role of ADD3-AS1 in PTC.ResultsA total of 107 differentially expressed lncRNAs, 81 differentially expressed miRNAs, and 515 differentially expressed mRNAs were identified. 11 lncRNAs and 6 miRNAs were regarded as the optimal diagnostic biomarkers for PTC. The epigenetic modifications via the above diagnostic lncRNAs and miRNAs were identified, including MIR181A2HG-FOXP2-hsa-miR-146b-3p, BLACAT1/ST7-AS1-RPS6KA5-hsa-miR-34a-5p, LBX2-AS1/MIR100HG-CDHR3-hsa-miR-34a-5p, ADD3-AS1-PTPRE-hsa-miR-9-5p, ADD3-AS1-TGFBR1-hsa-miR-214-3p, LINC00506-MMRN1-hsa-miR-4709-3p, and LOC339059-STK32A-hsa-miR-199b-5p. In the functional analysis, MMRN1 and TGFBR1 were involved in cell adhesion and endothelial cell migration, respectively. Overexpression of ADD3-AS1 inhibited cell growth and invasion in PTC cell lines.ConclusionThe identified lncRNAs/miRNAs/mRNA were differentially expressed between normal and cancerous tissues. In addition, identified altered lncRNAs and miRNAs may be potential diagnostic biomarkers for PTC. Additionally, epigenetic modifications via the above lncRNAs and miRNAs may be involved in tumorigenesis of PTC.

Project description:ContextThe BRAF V600E mutation (BRAF-MUT) confers an aggressive phenotype in papillary thyroid carcinoma, but unidentified additional genomic abnormalities may be required for full phenotypic expression.ObjectiveRNA sequencing (RNA-Seq) was performed to identify genes differentially expressed between BRAF-MUT and BRAF wild-type (BRAF-WT) tumors and to correlate changes to patient clinical status.DesignBRAF-MUT and BRAF-WT tumors were identified in patients with T1N0 and T2-3N1 tumors evaluated in a referral medical center. Gene expression levels were determined (RNA-Seq) and fusion transcripts were detected. Multiplexed capture/detection and digital counting of mRNA transcripts (nCounter, NanoString Technologies) validated RNA-Seq data for immune system-related genes.PatientsBRAF-MUT patients included nine women, three men; nine were TNM stage I and three were stage III. Three (25%) had tumor infiltrating lymphocytes. BRAF-WT included five women, three men; all were stage I, and five (62.5%) had tumor infiltrating lymphocytes.ResultsRNA-Seq identified 560 of 13 085 genes differentially expressed between BRAF-MUT and BRAF-WT tumors. Approximately 10% of these genes were related to MetaCore immune function pathways; 51 were underexpressed in BRAF-MUT tumors, whereas 4 (HLAG, CXCL14, TIMP1, IL1RAP) were overexpressed. The four most differentially overexpressed immune genes in BRAF-WT tumors (IL1B; CCL19; CCL21; CXCR4) correlated with lymphocyte infiltration. nCounter confirmed the RNA-Seq expression level data. Eleven different high-confidence fusion transcripts were detected (four interchromosomal; seven intrachromosomal) in 13 of 20 tumors. All in-frame fusions were validated by RT-PCR.ConclusionBRAF-MUT papillary thyroid cancers have reduced expression of immune/inflammatory response genes compared with BRAF-WT tumors and correlate with lymphocyte infiltration. In contrast, HLA-G and CXCL14 are overexpressed in BRAF-MUT tumors. Sixty-five percent of tumors had between one and three fusion transcripts. Functional studies will be required to determine the potential role of these newly identified genomic abnormalities in contributing to the aggressiveness of BRAF-MUT and BRAF-WT tumors.

Dataset Information

Identification of Biomarkers Based on Differentially Expressed Genes in Papillary Thyroid Carcinoma.

Publications

Identification of Biomarkers Based on Differentially Expressed Genes in Papillary Thyroid Carcinoma.

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