Ma Lan-Lan, Zhao Li-Juan, Zhang Ying, Ma Yan-Fen, Shang Qi, Liu Xiao-Li
Department of Obstetrics and gynecology, The Eighth Hospital of Wuhan, No.1288 of Jianshe Avenue, Wuhan, 430000, Hubei, China.
Discov Oncol. 2025 Jul 1;16(1):1224. doi: 10.1007/s12672-025-02901-9.
Genes associated efferocytosis play a critical role in tumor invasion, metastasis, and clinical outcomes in several malignancies. However, their prognostic relevance in cervical squamous carcinoma (CESC) is currently unclear.
Data from the Cancer Genome Atlas (TCGA) database were used to create the TCGA-CESC cohort. Additional CESC-related datasets (GSE44001 and GSE168652) were retrieved from the Gene Expression Omnibus database. Single-cell analysis of the GSE168652 dataset was conducted to identify differentially expressed genes (DEGs), associated with efferocytosis (ER-DEGs). CESC samples from the TCGA cohort were classified into clusters, and prognosis-related DEGs (PR-DEGs) were identified by comparing these clusters. The intersection of ER-DEGs and PR-DEGs generated a subset of prognosis-efferocytosis related DEGs (PER-DEGs). Subsequently, a risk model was developed using univariate Cox regression and least absolute shrinkage and selection operator analysis. Independent prognostic factors were further analyzed using Cox regression analysis. Functional pathways were examined through gene set enrichment analysis.
A total of 15 cell clusters were identified from the GSE168652 dataset and categorized into seven distinct cell types. Comparative analysis indicated 774 ER-DEGs between groups with high and low ERG expression levels. From these, 332 PER-DEGs were identified. A prognostic risk model was constructed based on seven characteristic genes: ITGA5, SNRPF, EGLN1, NDUFB7, NDUFA2, SRGAP3, and PCNA. Risk score and pathologic-N emerged as independent prognostic factors. These genes were found to be associated with multiple pathways implicated in the pathogenesis of CESC.
Seven efferocytosis-related prognostic genes were identified as prognostic markers for CESC, providing a scientific basis for further research on their role in disease progression.
与胞葬作用相关的基因在多种恶性肿瘤的肿瘤侵袭、转移及临床结局中起关键作用。然而，它们在宫颈鳞状细胞癌（CESC）中的预后相关性目前尚不清楚。
利用癌症基因组图谱（TCGA）数据库的数据创建了TCGA-CESC队列。从基因表达综合数据库中检索了其他CESC相关数据集（GSE44001和GSE168652）。对GSE168652数据集进行单细胞分析以鉴定与胞葬作用相关的差异表达基因（ER-DEGs）。将TCGA队列中的CESC样本分类为不同簇，并通过比较这些簇来鉴定与预后相关的差异表达基因（PR-DEGs）。ER-DEGs与PR-DEGs的交集产生了一组预后-胞葬作用相关差异表达基因（PER-DEGs）。随后，使用单变量Cox回归和最小绝对收缩和选择算子分析建立了风险模型。使用Cox回归分析进一步分析独立预后因素。通过基因集富集分析检查功能通路。
从GSE168652数据集中共鉴定出15个细胞簇，并分为7种不同的细胞类型。比较分析表明，ERG表达水平高和低的组之间有774个ER-DEGs。从中鉴定出332个PER-DEGs。基于7个特征基因构建了预后风险模型：整合素α5（ITGA5）、小核核糖核蛋白多肽F（SNRPF）、脯氨酰羟化酶1（EGLN1）、NADH脱氢酶（泛醌）Fe-S蛋白7（NDUFB7）、NADH脱氢酶（泛醌）α亚基2（NDUFA2）、突触后密度蛋白95、盘大蛋白和鸟苷酸激酶结构域蛋白3（SRGAP3）和增殖细胞核抗原（PCNA）。风险评分和病理分期N被确定为独立预后因素。发现这些基因与CESC发病机制中的多种通路相关。
鉴定出7个与胞葬作用相关的预后基因作为CESC的预后标志物，为进一步研究它们在疾病进展中的作用提供了科学依据。
