Novel biomarkers of inflammation-associated immunity in cervical cancer

Front Oncol. 2024 Mar 12:14:1351736. doi: 10.3389/fonc.2024.1351736. eCollection 2024.

Abstract

Background: Cervical cancer (CC) is a highly malignant gynecological cancer with a direct causal link to inflammation, primarily resulting from persistent high-risk human papillomavirus (HPV) infection. Given the challenges in early detection and mid to late-stage treatment, our research aims to identify inflammation-associated immune biomarkers in CC.

Methods: Using a bioinformatics approach combined with experimental validation, we integrated two CC datasets (GSE39001 and GSE63514) in the Gene Expression Omnibus (GEO) to eliminate batch effects. Immune-related inflammation differentially expressed genes (DGEs) were obtained by R language identification.

Results: This analysis identified 37 inflammation-related DEGs. Subsequently, we discussed the different levels of immune infiltration between CC cases and controls. Weighted gene co-expression network analysis (WGCNA) identified seven immune infiltration-related modules in CC. We identified 15 immune DEGs associated with inflammation at the intersection of these findings. In addition, we constructed a protein interaction network using the String database and screened five hub genes using "CytoHubba": CXC chemokine ligand 8 (CXCL8), CXC chemokine ligand 10 (CXCL10), CX3C chemokine receptor 1 (CX3CR1), Fc gamma receptors 3B (FCGR3B), and SELL. The expression of these five genes in CC was determined by PCR experiments. In addition, we assessed their diagnostic value and further analyzed the association of immune cells with them.

Conclusions: Five inflammation- and immune-related genes were identified, aiming to provide new directions for early diagnosis and mid to late-stage treatment of CC from multiple perspectives.

Keywords: CIBERSORT; cervical cancer; differentially expressed inflammation-related genes; immune infiltration; inflammation-associated immune biomarkers.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This research was funded by the National Natural Science Foundation of China (Grant no.81702583), the Outstanding Youth Fund Project of Shanxi Province (Grant no.201901D211506), the China Postdoctoral Science Foundation (Grant no. 2019M651072)and the Research Project Supported by Shanxi Scholarship Council of China (Grant no. 2022-195). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.