Zhao Xuyan, Cui Hanxiao, Zhou Mingjing, Ren Xueting, Li Zihao, Liu Peinan, Zhao Danni, Lin Shuai, Kang Huafeng
The Comprehensive Breast Care Center, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Department of Neurosurgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Ann Med. 2025 Dec;57(1):2495762. doi: 10.1080/07853890.2025.2495762. Epub 2025 May 7.
Kidney Renal Clear Cell Carcinoma (KIRC) is a prevalent urinary malignancies worldwide. Glycosylation is a key post-translational modification that is essential in cancer progression. However, its relationship with prognosis, tumour microenvironment (TME), and treatment response in KIRC remains unclear.
Expression profiles and clinical data were retrieved from The Cancer Genome Atlas and Gene Expression Omnibus databases. Consensus clustering, Cox regression, and LASSO regression analyses were conducted to develop an optimal glycogene-related signature. The prognostic relevance of this molecular signature was rigorously analyzed, along with its connections to tumour microenvironment (TME), tumour mutation burden, immune checkpoint activity, cancer-immunity cycle regulation, immunomodulatory gene expression patterns, and therapeutic response profiles. Validation was performed using real-world clinical specimens, quantitative PCR (qPCR), , supported by cohort analyses from the Human Protein Atlas (HPA) database.
A glycogene-associated prognostic scoring system was established to categorize patients into risk-stratified subgroups. Patients in the high-risk cohort exhibited significantly poorer survival outcomes ( < 0.001). By incorporating clinicopathological variables into this framework, we established a predictive nomogram demonstrating strong calibration and a concordance index (C-index) of 0.78. The high-risk subgroup displayed elevated immune infiltration scores ( < 0.001), upregulated expression of immune checkpoint-related genes ( < 0.05), and an increased frequency of somatic mutations ( = 0.043). The risk score positively correlated with cancer-immunity cycle activation and immunotherapy-related signals. The high-risk groups also showed associations with T cell exhaustion, immune-activating genes, chemokines, and receptors. Drug sensitivity analysis revealed that low-risk patients were more sensitive to sorafenib, pazopanib, and erlotinib, whereas high-risk individuals responded better to temsirolimus ( < 0.01). qPCR analyses consistently revealed distinct expression patterns of MX2 and other key genes across the risk groups, further corroborated by the HPA findings.
This glycogene-based signature provides a robust tool for predicting prognosis, TME characteristics, and therapeutic responses in KIRC, offering potential clinical utility in patient management.
肾透明细胞癌（KIRC）是全球范围内一种常见的泌尿系统恶性肿瘤。糖基化是一种关键的翻译后修饰，在癌症进展中至关重要。然而，其与KIRC预后、肿瘤微环境（TME）及治疗反应的关系仍不明确。
从癌症基因组图谱和基因表达综合数据库中检索表达谱和临床数据。进行共识聚类、Cox回归和LASSO回归分析，以建立最佳的糖基因相关特征。对该分子特征的预后相关性进行了严格分析，并分析了其与肿瘤微环境（TME）、肿瘤突变负荷、免疫检查点活性、癌症免疫循环调节、免疫调节基因表达模式及治疗反应谱的联系。使用真实世界临床标本、定量PCR（qPCR）进行验证，并得到人类蛋白质图谱（HPA）数据库队列分析的支持。
建立了一个糖基因相关的预后评分系统，将患者分为风险分层亚组。高风险队列中的患者生存结局明显较差（<0.001）。通过将临床病理变量纳入该框架，我们建立了一个预测列线图，显示出良好的校准性和0.78的一致性指数（C指数）。高风险亚组显示免疫浸润评分升高（<0.001）、免疫检查点相关基因表达上调（<0.05）和体细胞突变频率增加（=0.043）。风险评分与癌症免疫循环激活和免疫治疗相关信号呈正相关。高风险组还与T细胞耗竭、免疫激活基因、趋化因子和受体有关。药物敏感性分析显示，低风险患者对索拉非尼、帕唑帕尼和厄洛替尼更敏感，而高风险个体对替西罗莫司反应更好（<0.01）。qPCR分析一致显示MX2和其他关键基因在不同风险组中的表达模式不同，HPA的研究结果进一步证实了这一点。
这种基于糖基因的特征为预测KIRC的预后、TME特征和治疗反应提供了一个强大的工具，在患者管理中具有潜在的临床应用价值。
