Shao Jia, Zhang Can, Tang Yaonan, He Aiqin, Cheng Xiangyan
Department of Gynecology Oncology, Affiliated Tumor Hospital of Nantong University, Nantong, China.
Department of Obstetrics and Gynecology, Nantong Third People's Hospital, Affiliated Nantong Hospital 3 of Nantong University, Nantong, China.
PeerJ. 2025 May 22;13:e19422. doi: 10.7717/peerj.19422. eCollection 2025.
Cancer-associated hypersialylation is believed to be related to the metastatic cell phenotype and the suppression of sialyltransferases (SiaTs) has been suggested to be a potent preventive strategy against metastasis. The present research discovered SiaTs-related genes for cervical cancer (CC).
The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were applied to obtain the relevant samples. Mutation dataset were processed using mutect2 software. The gene modules were obtained weighted gene co-expression network analysis (WGCNA), and the enrichment analysis on the genes within the modules was implemented. Cox regression analysis and "glmnet" R package were applied to establish the relevant risk model. "MCPcounter" R package, ESTIMATE algorithm and TIMER online tools were used to depict the tumor immune microenvironment in CC. The mutation landscape was additionally plotted, and the response to immunotherapy in different cohorts were compared. Further reverse-transcription quantitative PCR and Transwell assays were performed to verify the expression and potential function of the screened key genes.
Mutation of 14 SiaTs was seen in CC. Subsequently, WGCNA-based identification of SiaTs-related gene modules was significantly enriched in metabolism-related pathways. The established RiskScore model manifested excellent prognostic classification efficiency. A poorer prognosis and occurrence of both immune evasion and reduced immunoreactivity may be seen in high-risk patients yet relatively higher immune cell scores were noticeable in low-risk patients. Angiogenesis and MYC target V2 may be the differentially activated pathways in high-risk patients, while those in low-risk patients were KRAS Signaling DN and Interferon alpha response. In addition, most immune checkpoint-correlated genes were identified to express higher in low-risk patients, while higher sensitivities to chemotherapy drugs was discovered in high-risk patients. Cellular assays have revealed that , , , , and were highly expressed yet , and were low-expressed in Hela cells and that silencing diminished the number of migrated and invaded Hela cells.
In this study, we systematically constructed and validated a risk scoring model based on SiaTs-related genes, which can effectively predict the prognosis and potential response to immunotherapy and chemotherapy in CC patients. This provides a new molecular basis and clinical reference for achieving individualized treatment.
癌症相关的高唾液酸化被认为与转移细胞表型有关，抑制唾液酸转移酶（SiaTs）被认为是一种有效的预防转移策略。本研究发现了宫颈癌（CC）中与SiaTs相关的基因。
应用癌症基因组图谱（TCGA）和基因表达综合数据库（GEO）获取相关样本。使用mutect2软件处理突变数据集。通过加权基因共表达网络分析（WGCNA）获得基因模块，并对模块内的基因进行富集分析。应用Cox回归分析和“glmnet”R包建立相关风险模型。使用“MCPcounter”R包、ESTIMATE算法和TIMER在线工具描绘CC中的肿瘤免疫微环境。此外，绘制了突变图谱，并比较了不同队列对免疫治疗的反应。进一步进行逆转录定量PCR和Transwell实验，以验证筛选出的关键基因的表达和潜在功能。
在CC中发现了14种SiaTs的突变。随后，基于WGCNA鉴定的与SiaTs相关的基因模块在代谢相关途径中显著富集。建立的风险评分模型显示出优异的预后分类效率。高风险患者可能预后较差，出现免疫逃逸和免疫反应降低的情况，而低风险患者的免疫细胞评分相对较高。血管生成和MYC靶标V2可能是高风险患者中差异激活的途径，而低风险患者中的途径是KRAS信号DN和干扰素α反应。此外，大多数免疫检查点相关基因在低风险患者中表达较高，而高风险患者对化疗药物的敏感性较高。细胞实验表明，在Hela细胞中， 、 、 、 、 高表达，而 、 、 低表达，沉默 减少了迁移和侵袭的Hela细胞数量。
在本研究中，我们系统地构建并验证了基于SiaTs相关基因的风险评分模型，该模型可以有效预测CC患者的预后以及对免疫治疗和化疗的潜在反应。这为实现个体化治疗提供了新的分子基础和临床参考。
