Evidence map›Paper›PMID 40753287›Full record

ArticleDiscover oncology2025

Identification of hub genes for psoriasis and thyroid cancer using bioinformatics analysis.

HaiXia Shi, Yuan Guo, JuPing Chen, HaoChen Yuan, LiYa Wang, Yun Zhang, YanHua Li

Abstract read
In one paragraph

Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

HaiXia Shi *Department of Dermatology, The Affiliated Hospital of Yangzhou University, Yangzhou University, No. 368, Hanjiang Middle Road, Hanjiang District, Yangzhou, 225012, Jiangsu Province, China.
Yuan Guo *Department of Dermatology, The Affiliated Hospital of Yangzhou University, Yangzhou University, No. 368, Hanjiang Middle Road, Hanjiang District, Yangzhou, 225012, Jiangsu Province, China.
JuPing ChenDepartment of Dermatology, The Affiliated Hospital of Yangzhou University, Yangzhou University, No. 368, Hanjiang Middle Road, Hanjiang District, Yangzhou, 225012, Jiangsu Province, China.
HaoChen YuanDepartment of Dermatology, The Affiliated Hospital of Yangzhou University, Yangzhou University, No. 368, Hanjiang Middle Road, Hanjiang District, Yangzhou, 225012, Jiangsu Province, China.
LiYa WangDepartment of Dermatology, The Affiliated Hospital of Yangzhou University, Yangzhou University, No. 368, Hanjiang Middle Road, Hanjiang District, Yangzhou, 225012, Jiangsu Province, China.
Yun ZhangDepartment of Dermatology, The Affiliated Hospital of Yangzhou University, Yangzhou University, No. 368, Hanjiang Middle Road, Hanjiang District, Yangzhou, 225012, Jiangsu Province, China. zhangyun198809@126.com.
YanHua LiDepartment of Dermatology, The Affiliated Hospital of Yangzhou University, Yangzhou University, No. 368, Hanjiang Middle Road, Hanjiang District, Yangzhou, 225012, Jiangsu Province, China. swak_swa@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPsoriasis has been associated with an increased risk of various cancers, including thyroid cancer (TC), yet the molecular mechanisms linking these two diseases remain unclear.

objectiveThis study aimed to identify and analyze the differentially expressed genes (DEGs) between TC and psoriasis using bioinformatics approaches to explore potential molecular mechanisms and shared pathways. To the best of our knowledge, this is the first bioinformatics-based study to systematically identify and validate shared hub genes between thyroid cancer and psoriasis.

methodsA TC dataset from the TCGA database and five GEO datasets (GSE35570, GSE13355, GSE14905, GSE53431, and GSE29265) were analyzed, with GSE53431 and GSE29265 serving as validation sets. Differential expression was identified using Xiantao and GEO2R, followed by a series of bioinformatics analyses, including Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO) enrichment, protein-protein interaction (PPI) network construction, transcription factor (TF)-gene interaction, TF-miRNA coregulatory network analysis, and drug molecule prediction.

resultsA total of 79 DEGs associated with TC were identified. Key Enrichr KEGG pathways included a response to the bacterium, NABA MATRISOME ASSOCIATED, negative regulation of cell population proliferation, response to wounding, and HALLMARK KRAS SIGNALING UP. Six hub genes (SERPINA1, S100A9, CCL20, SLPI, LCN2, and CXCL8) were identified from the PPI network, with three genes (SERPINA1, CCL20, and LCN2) showing high diagnostic value for both TC and psoriasis. TF gene and miRNA interactions involving these hub genes and potential drug molecules were also identified.

conclusionThis study provides insight into potential biomarkers and therapeutic targets relevant to TC and psoriasis, identifying shared molecular pathways and hub genes that may guide future diagnostic and therapeutic approaches for these diseases.

Indexed as

BioinformaticsCCL20LCN2PsoriasisSERPINA1Thyroid cancer

Identifiers

PMID40753287
PMCPMC12317944

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