Identification of key candidate genes and pathways in anaplastic thyroid cancer by bioinformatics analysis

Ding, Yonggang; Ren, Yulin; Xu, Yang-Shan; Wei, Chunhong; Zhang, Yongbin; Zhang, Shoukai; Guo, Changan

doi:10.1016/j.amjoto.2020.102434

Cited by 5 publications

(5 citation statements)

References 31 publications

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“…Additionally, CDK1 has also been found to be vital mediator in the progress of thyroid cancer. Wu et al suggested that CDK1 may serve as a novel diagnosis biomarker and potential therapeutic target for anaplastic thyroid cancer [42]. Several studies also determined CDK1 as a key gene in anaplastic thyroid cancer by bioinformatics analysis [43][44][45].…”

Section: Discussionmentioning

confidence: 99%

CDCA8 Contributes to the Development and Progression of Thyroid Cancer through Regulating CDK1

Xiang¹,

Sun²,

You³

et al. 2022

J. Cancer

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Background: This study aims to reveal regulatory role of cell division cycle associated 8 (CDCA8) in thyroid cancer progression and metastasis. Methods: A series of experiments in vivo and in vitro were performed to explore the function of CDCA8 in thyroid cancer. Results: Immunohistochemical analysis showed that CDCA8 expression levels were upregulated in thyroid cancer tissues compared with normal tissues, and were statistically correlated with tumor stage. Results of in vitro loss-of-function assay showed that downregulation of endogenous expression of CDCA8 could significantly inhibit cell proliferation, colony formation, cell migration, and promote apoptosis. Thyroid cancer cells lacking CDCA8 expression also had reduced tumorigenicity in vivo. Further, results of preliminary mechanistic exploration showed that CDK1 may be a potential downstream molecule of CDCA8 in regulating thyroid cancer progression. We subsequently confirmed that CDK1 itself exerted a significant regulatory function in thyroid cancer by loss-and gain-of-function experiments. Moreover, overexpression of CDK1 could weaken the tumor suppressive effect caused by CDCA8 knockdown. Conclusions: CDCA8 functions as an oncogene in thyroid cancer, and CDCA8 knockdown suppresses cancer development in vitro and in vivo. Additionally, CDK1 was further identified as a potential target of CDCA8 in thyroid cancer.

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Section: Discussionmentioning

confidence: 99%

CDCA8 Contributes to the Development and Progression of Thyroid Cancer through Regulating CDK1

Xiang¹,

Sun²,

You³

et al. 2022

J. Cancer

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“…Noticeably, in the intersection between the top 10 enriched pathways from both data sets UCEC and GSE63678, only BIP identified as novel candidate risk pathways Ubiquitin mediated proteolysis pathway ( p value = ) and Oxidative phosphorylation pathway ( p value = ) and reticulum pathway . [ 132 – 134 ] and [ 95 ] describe the involvement of those pathways in TC, which were ignored by the other tools.…”

Section: Discussionmentioning

confidence: 99%

Using BioPAX-Parser (BiP) to enrich lists of genes or proteins with pathway data

Agapito

Cannataro

2021

BMC Bioinformatics

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Background Pathway enrichment analysis (PEA) is a well-established methodology for interpreting a list of genes and proteins of interest related to a condition under investigation. This paper aims to extend our previous work in which we introduced a preliminary comparative analysis of pathway enrichment analysis tools. We extended the earlier work by providing more case studies, comparing BiP enrichment performance with other well-known PEA software tools. Methods PEA uses pathway information to discover connections between a list of genes and proteins as well as biological mechanisms, helping researchers to overcome the problem of explaining biological entity lists of interest disconnected from the biological context. Results We compared the results of BiP with some existing pathway enrichment analysis tools comprising Centrality-based Pathway Enrichment, pathDIP, and Signaling Pathway Impact Analysis, considering three cancer types (colorectal, endometrial, and thyroid), for a total of six datasets (that is, two datasets per cancer type) obtained from the The Cancer Genome Atlas and Gene Expression Omnibus databases. We measured the similarities between the overlap of the enrichment results obtained using each couple of cancer datasets related to the same cancer. Conclusion As a result, BiP identified some well-known pathways related to the investigated cancer type, validated by the available literature. We also used the Jaccard and meet-min indices to evaluate the stability and the similarity between the enrichment results obtained from each couple of cancer datasets. The obtained results show that BiP provides more stable enrichment results than other tools.

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“…23 Among those genes, CDK1 , TOP2A , CCNA2 , and CDC20 were also identified as hub genes in our study. Another bioinformatics analysis of the ATC transcriptome 24 involved 4 GEO datasets and identified 7 hub genes ( CDK1 , CCNB2 , BUB1B , CDC20 , RRM2 , CHEK1 , and CDC45 ). However, only CDK1 and CDC20 were present in our results.…”

Section: Discussionmentioning

confidence: 99%

Identification of Hub Genes in Anaplastic Thyroid Carcinoma: Evidence From Bioinformatics Analysis

Zhu

et al. 2020

Technol Cancer Res Treat

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Anaplastic thyroid carcinoma (ATC) is a rare type of thyroid cancer that results in fatal clinical outcomes; the pathogenesis of this life-threatening disease has yet to be fully elucidated. This study aims to identify the hub genes of ATC that may play key roles in ATC development and could serve as prognostic biomarkers or therapeutic targets. Two microarray datasets (GSE33630 and GSE53072) were obtained from the Gene Expression Omnibus database; these sets included 16 ATC and 49 normal thyroid samples. Differential expression analyses were performed for each dataset, and 420 genes were screened as common differentially expressed genes using the robust rank aggregation method. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were conducted to explore the potential bio-functions of these differentially expressed genes (DEGs). The terms and enriched pathways were primarily associated with cell cycle, cell adhesion, and cancer-related signaling pathways. Furthermore, a protein-protein interaction network of DEG expression products was constructed using Cytoscape. Based on the whole network, we identified 7 hub genes that included CDK1, TOP2A, CDC20, KIF11, CCNA2, NUSAP1, and KIF2C. The expression levels of these hub genes were validated using quantitative polymerase chain reaction analyses of clinical specimens. In conclusion, the present study identified several key genes that are involved in ATC development and provides novel insights into the understanding of the molecular mechanisms of ATC development.

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Identification of key candidate genes and pathways in anaplastic thyroid cancer by bioinformatics analysis

Cited by 5 publications

References 31 publications

CDCA8 Contributes to the Development and Progression of Thyroid Cancer through Regulating CDK1

CDCA8 Contributes to the Development and Progression of Thyroid Cancer through Regulating CDK1

Using BioPAX-Parser (BiP) to enrich lists of genes or proteins with pathway data

Identification of Hub Genes in Anaplastic Thyroid Carcinoma: Evidence From Bioinformatics Analysis

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