Zhao Weihong, Li Qi, Wen Songquan, Li Yaqin, Bai Ying, Tian Zhiyu
Department of Obstetrics and Gynecology, The Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, China.
The Second Clinical Medical College, Shanxi Medical University, Taiyuan, China.
Front Oncol. 2024 Mar 12;14:1351736. doi: 10.3389/fonc.2024.1351736. eCollection 2024.
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.
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.
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.
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.
宫颈癌（CC）是一种高度恶性的妇科癌症，与炎症有直接因果关系，主要由持续性高危型人乳头瘤病毒（HPV）感染引起。鉴于早期检测和中晚期治疗面临的挑战，我们的研究旨在识别宫颈癌中与炎症相关的免疫生物标志物。
我们采用生物信息学方法并结合实验验证，整合了基因表达综合数据库（GEO）中的两个宫颈癌数据集（GSE39001和GSE63514）以消除批次效应。通过R语言识别获得免疫相关炎症差异表达基因（DGEs）。
该分析确定了37个与炎症相关的差异表达基因。随后，我们讨论了宫颈癌病例与对照之间不同水平的免疫浸润情况。加权基因共表达网络分析（WGCNA）在宫颈癌中识别出七个与免疫浸润相关的模块。我们在这些结果的交叉点上确定了15个与炎症相关的免疫差异表达基因。此外，我们使用String数据库构建了蛋白质相互作用网络，并使用“CytoHubba”筛选出五个枢纽基因：CXC趋化因子配体8（CXCL8）、CXC趋化因子配体10（CXCL10）、CX3C趋化因子受体1（CX3CR1）、Fcγ受体3B（FCGR3B）和SEL。通过PCR实验确定了这五个基因在宫颈癌中的表达。此外，我们评估了它们的诊断价值，并进一步分析了免疫细胞与它们的关联。
确定了五个与炎症和免疫相关的基因，旨在从多个角度为宫颈癌的早期诊断和中晚期治疗提供新方向。
