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Investigating the mechanisms of papillary thyroid carcinoma using transcriptome analysis.

ABSTRACT: As the predominant thyroid cancer, papillary thyroid cancer (PTC) accounts for 75?85% of thyroid cancer cases. This research aimed to investigate transcriptomic changes and key genes in PTC. Using RNA?sequencing technology, the transcriptional profiles of 5 thyroid tumor tissues and 5 adjacent normal tissues were obtained. The single nucleotide polymorphisms (SNPs) were identified by SAMtools software and then annotated by ANNOVAR software. After differentially expressed genes (DEGs) were selected by edgR software, they were further investigated by enrichment analysis, protein domain analysis, and protein?protein interaction (PPI) network analysis. Additionally, the potential gene fusion events were predicted using FusionMap software. A total of 70,172 SNPs and 2,686 DEGs in the tumor tissues, as well as 83,869 SNPs in the normal tissues were identified. In the PPI network, fibronectin 1 (FN1; degree=31) and transforming growth factor ? receptor 1 (TGF?R1; degree=22) had higher degrees. A total of 7 PPI pairs containing the non?synonymous risk SNP loci in the interaction domains were identified. Particularly, the interaction domains involved in the interactions of FN1 and 5 other proteins (such as FN1?tenascin C, TNC) had non?synonymous risk SNP loci. Furthermore, 11 and 4 gene fusion events were identified in all of the tumor tissues and normal tissues, respectively. Additionally, the NK2 homeobox 1?surfactant associated 3 (NKX2?1?SFTA3) gene fusion was identified in both tumor and normal tissues. These results indicated that TGF?R1 and the NKX2?1?SFTA3 gene fusion may be involved in PTC. Furthermore, FN1 and TNC containing the non?synonymous risk SNP loci might serve a role in PTC by interacting with each other.

SUBMITTER: Qiu J

PROVIDER: S-EPMC5865774 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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Investigating the mechanisms of papillary thyroid carcinoma using transcriptome analysis.

Qiu Jie J Zhang Wenwei W Xia Qingsheng Q Liu Fuxue F Zhao Shuwei S Zhang Kailing K Chen Min M Zang Chuanshan C Ge Ruifeng R Liang Dapeng D Sun Yan Y

Molecular medicine reports 20170824 5

As the predominant thyroid cancer, papillary thyroid cancer (PTC) accounts for 75‑85% of thyroid cancer cases. This research aimed to investigate transcriptomic changes and key genes in PTC. Using RNA‑sequencing technology, the transcriptional profiles of 5 thyroid tumor tissues and 5 adjacent normal tissues were obtained. The single nucleotide polymorphisms (SNPs) were identified by SAMtools software and then annotated by ANNOVAR software. After differentially expressed genes (DEGs) were select ...[more]

PMID: 28849102

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Project description:BackgroundThe tumor microenvironment (TME) plays a pivotal role in cancer progression in papillary thyroid carcinoma (PTC), yet the composition and the phenotype of cells within the TME in bilateral PTC are poorly understood.MethodsWe performed unbiased transcriptome-wide single-cell RNA sequencing (scRNA-seq) analysis on 29,561 cells from 3 pairs of bilateral PTC and 1 non-tumor thyroid sample. The results of the analysis were validated by a large-scale bulk transcriptomic dataset deposited in The Cancer Genome Atlas (TCGA) database.ResultsOur integrative analysis of thyroid follicular cells revealed 42 signaling pathways enriched in malignant follicular cells, including cytokine-cytokine receptor interaction, PI3K/Akt signaling pathway, mitogen-activated protein kinase (MAPK) signaling pathway, and tumor necrosis factor (TNF) signaling pathway. A 6-gene signature (CXCL3, CXCL1, IL1A, CCL5, TNFRSF12A, and IL18) in the cytokine-cytokine receptor interaction pathway was constructed to predict the prognosis of patients with PTC, with high risk scores being associated with decreased overall survival [hazard ratio (HR) = 3.863, 95% CI = 2.233-6.682, p < 0.001]. Gene set variation analysis (GSVA) indicated that the pathways enriched in bilateral PTC were significantly different, indicating great heterogeneity in bilateral PTC, even with the same BRAF V600E mutation. Comprehensive analysis of T cells revealed that the proportion of CD8+ tissue-resident memory T cells expressing IFNG decreased in tumor samples with advanced N stage. Within the myeloid compartment, the ratio of suppressive M2-like to pro-inflammatory M1-like macrophages increased with advanced disease stage, which was confirmed in the bulk dataset using transcriptomic profiles. In addition, we also identified numerous biologically critical interactions among myeloid cells, T cells, and follicular cells, which were related to T-cell recruitment, M2-like macrophage polarization, malignant follicular cell progression, and T-cell inhibitory signaling.ConclusionOur integrative analyses revealed great inter-tumor heterogeneity within the TME in bilateral PTC, which will offer assistance for precise diagnosis and treatment.

Project description:BACKGROUND:We present a functional gene association network of the CLIP2 gene, generated by de-novo reconstruction from transcriptomic microarray data. CLIP2 was previously identified as a potential marker for radiation induced papillary thyroid carcinoma (PTC) of young patients in the aftermath of the Chernobyl reactor accident. Considering the rising thyroid cancer incidence rates in western societies, potentially related to medical radiation exposure, the functional characterization of CLIP2 is of relevance and contributes to the knowledge about radiation-induced thyroid malignancies. METHODS:We generated a transcriptomic mRNA expression data set from a CLIP2-perturbed thyroid cancer cell line (TPC-1) with induced CLIP2 mRNA overexpression and siRNA knockdown, respectively, followed by gene-association network reconstruction using the partial correlation-based approach GeneNet. Furthermore, we investigated different approaches for prioritizing differentially expressed genes for network reconstruction and compared the resulting networks with existing functional interaction networks from the Reactome, Biogrid and STRING databases. The derived CLIP2 interaction partners were validated on transcript and protein level. RESULTS:The best reconstructed network with regard to selection parameters contained a set of 20 genes in the 1st neighborhood of CLIP2 and suggests involvement of CLIP2 in the biological processes DNA repair/maintenance, chromosomal instability, promotion of proliferation and metastasis. Peptidylprolyl Isomerase Like 3 (PPIL3), previously identified as a potential direct interaction partner of CLIP2, was confirmed in this study by co-expression at the transcript and protein level. CONCLUSION:In our study we present an optimized preselection approach for genes subjected to gene-association network reconstruction, which was applied to CLIP2 perturbation transcriptome data of a thyroid cancer cell culture model. Our data support the potential carcinogenic role of CLIP2 overexpression in radiation-induced PTC and further suggest potential interaction partners of the gene.

Project description:The incidence rate of papillary thyroid carcinoma (PTC) has rapidly increased in the recent decades, and the microRNA (miRNA) is one of the potential biomarkers in this cancer. Despite good prognosis, certain features such as lymph node metastasis (LNM) and BRAF V600E mutation are associated with a poor outcome. More than 50% of PTC patients present with LNM and BRAF V600E is the most common mutation identified in this cancer. The molecular mechanisms underlying these features are yet to be elucidated. This study aims to elucidate miRNA-genes interaction networks in PTC with or without LNM and to determine the association of BRAF V600E mutation with miRNAs and genes expression profiles. Next generation sequencing was performed to characterize miRNA and gene expression profiles in 20 fresh frozen tumor and the normal adjacent tissues of PTC with LNM positive (PTC LNM-P) and PTC without LNM (PTC LNN). BRAF V600E was genotyped using Sanger sequencing. Bioinformatics integration and pathway analysis were performed to determine the regulatory networks involved. Based on network analysis, we then investigated the association between miRNA and gene biomarkers, and pathway enrichment analysis was performed to study the role of candidate biomarkers. We identified 138 and 43 significantly deregulated miRNAs (adjusted p value?<?0.05; log2 fold change???-1.0 or ?1.0) in PTC LNM-P and PTC LNN compared to adjacent normal tissues, respectively. Ninety-six miRNAs had significant expression ratios of 3p-to-5p in PTC LNM-P as compared to PTC LNN. In addition, ribosomal RNA-reduced RNA sequencing analysis revealed 699 significantly deregulated genes in PTC LNM-P versus normal adjacent tissues, 1,362 genes in PTC LNN versus normal adjacent tissue, and 1,576 genes in PTC LNM-P versus PTC LNN. We provide the evidence of miRNA and gene interactions, which are involved in LNM of papillary thyroid cancer. These findings may lead to better understanding of carcinogenesis and metastasis processes. This study also complements the existing knowledge about deregulated miRNAs in papillary thyroid carcinoma development.

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Investigating the mechanisms of papillary thyroid carcinoma using transcriptome analysis.

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Investigating the mechanisms of papillary thyroid carcinoma using transcriptome analysis.

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