Literature DB >> 32887540

The differences of regulatory networks between papillary and anaplastic thyroid carcinoma: an integrative transcriptomics study.

Zongfu Pan1, Lu Li2, Yangyang Qian3,4, Xinyang Ge5, Xiaoping Hu1, Yiwen Zhang1, Minghua Ge3,4, Ping Huang1.   

Abstract

BACKGROUND: Unlike papillary thyroid cancer (PTC), anaplastic thyroid carcinoma (ATC) is extremely aggressive and rapidly lethal without effective therapies. However, the differences of master regulators and regulatory networks between PTC and ATC remain unclear.
Methods: Three representative datasets comprising 32 ATC, 69 PTC, and 78 normal thyroid tissue samples were combined to form a large dataset. Differentially expressed genes (DEGs) were identified and enriched by limma package and gene set enrichment analysis, respectively. Subsequently, protein-protein interaction network and transcription factors (TFs) regulatory network were constructed to identify gene modules and master regulators. Further, master regulators were validated by RT-PCR and western blot. Finally, Kaplan-Meier plotter was applied to evaluate their prognostic values.
Results: A total of 560 DEGs were identified as ATC-specific malignant signature. The regulatory network analysis showed that nine master regulators were significantly correlated with three gene modules and potentially regulated the expression of DEGs in three gene modules, respectively. Furthermore, CREB3L1, FOSL2, E2F1 and CAT were significantly associated with overall survival of thyroid cancer patients. FOXM1, FOSL2, MYBL2, AVEN and E2F1 were unfavorable factors of recurrence-free survival (RFS), while CAT was a favorable factor of RFS. RT-PCR and western blot confirmed that six TFs were obviously up-regulated in ATC tissues/cell line as compared with PTC and normal thyroid tissues/cell lines, respectively. In addition, 19 ATC-specific kinases were identified to illustrate the potential post-translational modification. Conclusions: Our findings provide a comprehensive insight into malignant mechanism of ATC, which may indicate their value in the future investigation of ATC.

Entities:  

Keywords:  Anaplastic thyroid carcinoma; bioinformatics; malignancy; regulatory network; transcription factor

Year:  2020        PMID: 32887540      PMCID: PMC7537793          DOI: 10.1080/15384047.2020.1803009

Source DB:  PubMed          Journal:  Cancer Biol Ther        ISSN: 1538-4047            Impact factor:   4.742


  36 in total

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10.  mRNA expression in papillary and anaplastic thyroid carcinoma: molecular anatomy of a killing switch.

Authors:  Aline Hébrant; Geneviève Dom; Michael Dewaele; Guy Andry; Christophe Trésallet; Emmanuelle Leteurtre; Jacques E Dumont; Carine Maenhaut
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  2 in total

1.  Transcription Factor E2F1 Exacerbates Papillary Thyroid Carcinoma Cell Growth and Invasion via Upregulation of LINC00152.

Authors:  Junjie Yang; Yong Ying; Xiangtai Zeng; Jiafeng Liu; Yang Xie; Zefu Deng; Zhiqiang Hu; Zanbin Li
Journal:  Anal Cell Pathol (Amst)       Date:  2022-05-10       Impact factor: 4.133

2.  CREB3L1 promotes tumor growth and metastasis of anaplastic thyroid carcinoma by remodeling the tumor microenvironment.

Authors:  Zongfu Pan; Tong Xu; Lisha Bao; Xiaoping Hu; Tiefeng Jin; Jinming Chen; Jianqiang Chen; Yangyang Qian; Xixuan Lu; Lu Li; Guowan Zheng; Yiwen Zhang; Xiaozhou Zou; Feifeng Song; Chuanming Zheng; Liehao Jiang; Jiafeng Wang; Zhuo Tan; Ping Huang; Minghua Ge
Journal:  Mol Cancer       Date:  2022-10-03       Impact factor: 41.444

  2 in total

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