ArticleMolecular medicine reports2017
Investigating the mechanisms of papillary thyroid carcinoma using transcriptome analysis.
Article in Molecular medicine reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.
- The role of PI3K signaling pathway and its associated genes in papillary thyroid cancer.Journal of the Egyptian National Cancer Institute · 2021Pooled it
- Identification and validation of hub genes involved in papillary thyroid carcinoma progression.BMC cancer · 2026Article
- Tracing the molecular route to progression in miRNA-biogenesis-defective thyroid lesions.JCI insight · 2026Article
- Eva-1 homolog A promotes papillary thyroid cancer progression and epithelial-mesenchymal transition via the Hippo signalling pathway.Journal of cellular and molecular medicine · 2020Article
- High expression of NUCB2 promotes papillary thyroid cancer cells proliferation and invasion.OncoTargets and therapy · 2019Article
Corrections and comments
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Authors and funding
11 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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 β receptor 1 (TGFβR1; 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 TGFβR1 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.
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