Ding Wenxiu, Liu Shu, Zhang Huiai, Ding Hongxia, Zhou Shaobing, Ye Hongxun
Department of Radiation Oncology, Taixing People's Hospital Affiliated to Yangzhou University, Taizhou, 225400, Jiangsu, China.
Department of Radiation Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
Discov Oncol. 2025 Jun 4;16(1):1000. doi: 10.1007/s12672-025-02459-6.
Ubiquitination, a pivotal posttranslational modification, plays a central role in regulating many biological processes. Nevertheless, its prognostic significance in cervical cancer remain largely unexplored.
Using unsupervised consensus cluster analysis, we identified molecular subtypes based on ubiquitin-associated genes. We also employed WGCNA to identify co-expressed genes and constructed a risk prognosis model using LASSO-penalized multivariate Cox analysis. We analyzed and illustrated the somatic mutational characteristics of patients according to their risk groups. To further our understanding, we assessed the correlation between the risk model and immune infiltration using the TIDE algorithm. Lastly, we investigated whether USP21 could influence the malignant behavior of cervical cancer cells.
TCGA-CESC samples were classified into three distinct subtypes based on ubiquitin-related genes. WGCNA analysis identified 1549 genes. We then developed a robust 13-gene signature (KLHL22, UBXN11, FBXO25, ANKRD13A, WSB1, WDTC1, ASB1, INPPL1, USP21, MIB2, USP30, TRIM32, SOCS1) that consistently performed well across various datasets. The risk classification significantly correlated with survival in both univariate and multivariate analyses. Additionally, mutation distribution in the CESC cohort varied among risk groups. Specifically, the high-risk group showed higher levels of TIDE scores, T-cell exclusion, CAF scores, and MDSC scores compared to the low-risk group. We also found that USP21 could promote the migration ability of cervical cells.
This study successfully established and validated a novel 13-gene signature, a valuable marker for predicting cervical cancer patient survival.
泛素化是一种关键的翻译后修饰，在调节许多生物学过程中发挥核心作用。然而，其在宫颈癌中的预后意义在很大程度上仍未得到探索。
我们使用无监督一致性聚类分析，基于泛素相关基因确定分子亚型。我们还采用加权基因共表达网络分析（WGCNA）来识别共表达基因，并使用套索惩罚多元Cox分析构建风险预后模型。我们根据患者的风险组分析并阐述了体细胞突变特征。为了进一步加深理解，我们使用TIDE算法评估了风险模型与免疫浸润之间的相关性。最后，我们研究了泛素特异性蛋白酶21（USP21）是否会影响宫颈癌细胞的恶性行为。
基于泛素相关基因，TCGA-CESC样本被分为三种不同的亚型。WGCNA分析确定了1549个基因。然后，我们开发了一个强大的由13个基因组成的特征标签（KLHL22、UBXN11、FBXO25、ANKRD13A、WSB1、WDTC1、ASB1、INPPL1、USP21、MIB2、USP30、TRIM32、SOCS1），该特征标签在各种数据集中均表现良好。风险分类在单变量和多变量分析中均与生存率显著相关。此外，CESC队列中的突变分布在不同风险组之间有所不同。具体而言，与低风险组相比，高风险组的TIDE评分、T细胞排除、癌症相关成纤维细胞（CAF）评分和骨髓来源的抑制细胞（MDSC）评分更高。我们还发现USP21可以促进宫颈细胞的迁移能力。
本研究成功建立并验证了一种新的由13个基因组成的特征标签，这是预测宫颈癌患者生存的有价值标志物。
