Four genes shared between rheumatoid arthritis and cervical cancer are associated with cervical cancer prognosis

Rheumatoid arthritis (RA) and cervical cancer (CC) are major global health challenges, yet the molecular connections between these two conditions remain poorly understood. To bridge this gap, our study employs bioinformatics approaches to explore shared genetic pathways and potential biomarkers. We started by identifying differentially expressed genes in RA and CC and then applied WGCNA to detect functionally related gene clusters using gene expression data from the GEO database. Additionally, we constructed protein-protein interaction (PPI) networks and examined the role of the immune microenvironment. To assess the prognostic relevance of key genes in CC, we leveraged survival data from TCGA. Our analysis identified 55 key genes common to RA and CC, with four-CXCL1, CXCL13, ZWINT, and PTTG1-emerging as significant. ROC curve validation confirmed their diagnostic potential, and a model incorporating these genes was associated with poorer prognosis in CC. Among them, CXCL1 stood out as especially crucial. Our findings suggest a potential link between chronic inflammation, immune dysregulation, and chemokine-related pathways in RA patients, which may contribute to an increased susceptibility to CC.

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Publication Details

Journal
Scientific Reports
Published
2025-05-07
DOI
https://doi.org/10.1038/s41598-025-01177-x
Primary Topic
Cytokine Signaling Pathways and Interactions
Type
article
Field-Weighted Citation Impact
0.00
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article

Four genes shared between rheumatoid arthritis and cervical cancer are associated with cervical cancer prognosis

S. Su, Weinan Yin, Ge Du, Shuo Chen et al.
Scientific Reports
Cytokine Signaling Pathways and Interactions
article

Four genes shared between rheumatoid arthritis and cervical cancer are associated with cervical cancer prognosis

S. Su, Weinan Yin, Ge Du, Shuo Chen, Huixia Liu, Bo Yang
article en

Abstract

Rheumatoid arthritis (RA) and cervical cancer (CC) are major global health challenges, yet the molecular connections between these two conditions remain poorly understood. To bridge this gap, our study employs bioinformatics approaches to explore shared genetic pathways and potential biomarkers. We started by identifying differentially expressed genes in RA and CC and then applied WGCNA to detect functionally related gene clusters using gene expression data from the GEO database. Additionally, we constructed protein-protein interaction (PPI) networks and examined the role of the immune microenvironment. To assess the prognostic relevance of key genes in CC, we leveraged survival data from TCGA. Our analysis identified 55 key genes common to RA and CC, with four-CXCL1, CXCL13, ZWINT, and PTTG1-emerging as significant. ROC curve validation confirmed their diagnostic potential, and a model incorporating these genes was associated with poorer prognosis in CC. Among them, CXCL1 stood out as especially crucial. Our findings suggest a potential link between chronic inflammation, immune dysregulation, and chemokine-related pathways in RA patients, which may contribute to an increased susceptibility to CC.

Scientific ReportsVol. 15(1)
Sun Yat-sen University (CN), General Hospital of Guangzhou Military Command (CN), The First Affiliated Hospital, Sun Yat-sen University (CN), Twelfth Guangzhou City People's Hospital (CN)
Good health and well-being
Openalex Percentile: Top 85%
Cytokine Signaling Pathways and Interactions
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