A novel glycogene-related signature for prognostic prediction and immune microenvironment assessment in kidney renal clear cell carcinoma
Background 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 r...
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| Language: | English |
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Taylor & Francis Group
2025-12-01
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| Series: | Annals of Medicine |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/07853890.2025.2495762 |
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| author | Xuyan Zhao Hanxiao Cui Mingjing Zhou Xueting Ren Zihao Li Peinan Liu Danni Zhao Shuai Lin Huafeng Kang |
| author_facet | Xuyan Zhao Hanxiao Cui Mingjing Zhou Xueting Ren Zihao Li Peinan Liu Danni Zhao Shuai Lin Huafeng Kang |
| author_sort | Xuyan Zhao |
| collection | DOAJ |
| description | Background 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.Method 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), and immunohistochemistry (IHC), supported by cohort analyses from the Human Protein Atlas (HPA) database.Results 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 (p < 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 (p < 0.001), upregulated expression of immune checkpoint-related genes (p < 0.05), and an increased frequency of somatic mutations (p = 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 (p < 0.01). qPCR and IHC analyses consistently revealed distinct expression patterns of MX2 and other key genes across the risk groups, further corroborated by the HPA findings.Conclusion 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. |
| format | Article |
| id | doaj-art-19026f00a0974590a623b34c35c819e9 |
| institution | Kabale University |
| issn | 0785-3890 1365-2060 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Annals of Medicine |
| spelling | doaj-art-19026f00a0974590a623b34c35c819e92025-08-20T03:48:46ZengTaylor & Francis GroupAnnals of Medicine0785-38901365-20602025-12-0157110.1080/07853890.2025.2495762A novel glycogene-related signature for prognostic prediction and immune microenvironment assessment in kidney renal clear cell carcinomaXuyan Zhao0Hanxiao Cui1Mingjing Zhou2Xueting Ren3Zihao Li4Peinan Liu5Danni Zhao6Shuai Lin7Huafeng Kang8The Comprehensive Breast Care Center, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, ChinaThe Comprehensive Breast Care Center, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, ChinaThe Comprehensive Breast Care Center, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, ChinaDepartment of Urology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, ChinaThe Comprehensive Breast Care Center, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, ChinaThe Comprehensive Breast Care Center, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, ChinaThe Comprehensive Breast Care Center, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, ChinaThe Comprehensive Breast Care Center, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, ChinaBackground 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.Method 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), and immunohistochemistry (IHC), supported by cohort analyses from the Human Protein Atlas (HPA) database.Results 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 (p < 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 (p < 0.001), upregulated expression of immune checkpoint-related genes (p < 0.05), and an increased frequency of somatic mutations (p = 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 (p < 0.01). qPCR and IHC analyses consistently revealed distinct expression patterns of MX2 and other key genes across the risk groups, further corroborated by the HPA findings.Conclusion 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.https://www.tandfonline.com/doi/10.1080/07853890.2025.2495762GlycogenesignatureKIRCimmune microenvironmentprognosis |
| spellingShingle | Xuyan Zhao Hanxiao Cui Mingjing Zhou Xueting Ren Zihao Li Peinan Liu Danni Zhao Shuai Lin Huafeng Kang A novel glycogene-related signature for prognostic prediction and immune microenvironment assessment in kidney renal clear cell carcinoma Annals of Medicine Glycogene signature KIRC immune microenvironment prognosis |
| title | A novel glycogene-related signature for prognostic prediction and immune microenvironment assessment in kidney renal clear cell carcinoma |
| title_full | A novel glycogene-related signature for prognostic prediction and immune microenvironment assessment in kidney renal clear cell carcinoma |
| title_fullStr | A novel glycogene-related signature for prognostic prediction and immune microenvironment assessment in kidney renal clear cell carcinoma |
| title_full_unstemmed | A novel glycogene-related signature for prognostic prediction and immune microenvironment assessment in kidney renal clear cell carcinoma |
| title_short | A novel glycogene-related signature for prognostic prediction and immune microenvironment assessment in kidney renal clear cell carcinoma |
| title_sort | novel glycogene related signature for prognostic prediction and immune microenvironment assessment in kidney renal clear cell carcinoma |
| topic | Glycogene signature KIRC immune microenvironment prognosis |
| url | https://www.tandfonline.com/doi/10.1080/07853890.2025.2495762 |
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