Liu Hong, Mei Manxue, Zhong Hua, Lin Shuyin, Luo Jiahui, Huang Sirong, Zhou Jiuyao
Department of Pharmacology, School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, People's Republic of China.
Department of Gerontology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, People's Republic of China.
J Inflamm Res. 2025 Jan 21;18:973-994. doi: 10.2147/JIR.S498820. eCollection 2025.
Chronic kidney disease (CKD) is a progressive condition that arises from diverse etiological factors, resulting in structural alterations and functional impairment of the kidneys. We aimed to establish the Anoikis-related gene signature in CKD by bioinformatics analysis.
We retrieved 3 datasets from the Gene Expression Omnibus (GEO) database to obtain differentially expressed genes (DEGs), followed by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) of them, which were intersected with Anoikis-related genes (ARGs) to derive Anoikis-related differentially expressed genes (ARDEGs). Besides, we conducted weighted gene co-expression network analysis (WGCNA) to identify hub genes. And then, we adopted the quantitative real-time PCR (RT-qPCR) assay to validate the hub genes among several CKD animal models. Furthermore, we constructed a competitive endogenous RNA (ceRNA) network for the hub genes utilizing the ENCORI and miRDB databases, while also calculating Spearman correlation coefficients. Ultimately, we applied the CIBERSORTx algorithm to conduct immune infiltration analysis, classifying immune characteristics based on the abundance of 22 immune cell types.
To summarize, we identified 13 ARDEGs. WGCNA yielded 6 hub genes, all of which demonstrated significant diagnostic potential in univariate logistic regression analysis (<0.05). The principal pathways enriched were involved in cell cycle progression Toxoplasmosis, Cell adhesion molecules, Influenza A, Pathogenic Escherichia coli infection, Small cell lung cancer, Amoebiasis, TNF signaling pathway, and Leukocyte transendothelial migration. Notably, 6 immune cell types exhibited significant differences (<0.05) across subgroups with distinct immune characteristics. Moreover, 2 hub genes showed significant variations (<0.05) across these immune characteristic subtypes. Among the 4 types of CKD mouse models, the mRNA expression levels of LAMB3 and CDH3 were significantly (<0.05) up-regulated in the model group.
We identified 6 hub genes that may serve as potential key biomarkers of Anoikis-related progression in CKD.
慢性肾脏病（CKD）是一种由多种病因引起的进行性疾病，会导致肾脏结构改变和功能损害。我们旨在通过生物信息学分析建立CKD中失巢凋亡相关基因特征。
我们从基因表达综合数据库（GEO）中检索了3个数据集以获得差异表达基因（DEG），随后对其进行基因本体（GO）、京都基因与基因组百科全书（KEGG）分析、基因集富集分析（GSEA）和基因集变异分析（GSVA），并将这些分析结果与失巢凋亡相关基因（ARG）进行交叉分析以得出失巢凋亡相关差异表达基因（ARDEG）。此外，我们进行了加权基因共表达网络分析（WGCNA）以识别枢纽基因。然后，我们采用定量实时PCR（RT-qPCR）检测在几种CKD动物模型中验证枢纽基因。此外，我们利用ENCORI和miRDB数据库为枢纽基因构建了竞争性内源RNA（ceRNA）网络，同时还计算了斯皮尔曼相关系数。最后，我们应用CIBERSORTx算法进行免疫浸润分析，根据22种免疫细胞类型的丰度对免疫特征进行分类。
总之，我们鉴定出13个ARDEG。WGCNA产生了6个枢纽基因，在单因素逻辑回归分析中所有这些基因均显示出显著的诊断潜力（<0.05）。富集的主要通路涉及细胞周期进程、弓形虫病、细胞黏附分子、甲型流感、致病性大肠杆菌感染、小细胞肺癌、阿米巴病、肿瘤坏死因子信号通路和白细胞跨内皮迁移。值得注意的是，6种免疫细胞类型在具有不同免疫特征的亚组之间表现出显著差异（<0.05）。此外，2个枢纽基因在这些免疫特征亚型之间表现出显著差异（<0.05）。在4种CKD小鼠模型中，模型组中LAMB3和CDH3的mRNA表达水平显著上调（<0.05）。
我们鉴定出6个枢纽基因，它们可能是CKD中失巢凋亡相关进展的潜在关键生物标志物。
