Construction and validation of a chemokine-related gene signature associated with prognosis, clinical significance, and immune microenvironment characteristics in cervical cancer
Abstract Background Cervical cancer (CC) remains a prevalent malignancy with significant mortality among women, highlighting the urgent need for reliable prognostic tools. While chemokines have emerged as pivotal regulators in tumor progression, their potential in constructing prognostic models for...
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| Format: | Article |
| Language: | English |
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Springer
2025-06-01
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| Series: | Discover Oncology |
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| Online Access: | https://doi.org/10.1007/s12672-025-02973-7 |
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| author | Tianjiao Huang Renshuang Cao Cong Gao Jie Luo Zhiyu Zhou Kun Ma |
| author_facet | Tianjiao Huang Renshuang Cao Cong Gao Jie Luo Zhiyu Zhou Kun Ma |
| author_sort | Tianjiao Huang |
| collection | DOAJ |
| description | Abstract Background Cervical cancer (CC) remains a prevalent malignancy with significant mortality among women, highlighting the urgent need for reliable prognostic tools. While chemokines have emerged as pivotal regulators in tumor progression, their potential in constructing prognostic models for CC remains underexplored. This study aimed to develop a chemokine-related gene signature for outcome prediction and therapeutic guidance in CC patients. Methods Transcriptomic data from The Cancer Genome Atlas (TCGA) cervical cancer cohort were analyzed to identify differentially expressed chemokine-related genes. Prognostic genes were screened through univariate Cox, multivariate Cox, and LASSO regression analyses, followed by the development of a risk stratification model. The model’s clinical relevance was evaluated by assessing its correlations with clinicopathological features, immune profiles, pathway enrichment, and therapeutic responses. A nomogram integrating risk scores and clinical parameters was constructed for survival prediction. Results A nine-gene signature (CCL17, CXCL8, TNF, FOXP3, CXCL1, CCL20, ITGA5, CXCL3, CCR7) was established as an independent prognostic indicator. Kaplan–Meier analysis revealed significantly shorter overall survival (OS) and progression-free survival (PFS) in high-risk patients compared to low-risk counterparts (P < 0.05). Multivariate Cox regression confirmed the signature’s independence from conventional clinical variables (P < 0.05). The nomogram demonstrated robust predictive accuracy, with 1-, 3-, and 5-year survival AUC values of 0.805, 0.729, and 0.710, respectively. Distinct immune cell infiltration patterns were observed between risk groups, with low-risk patients exhibiting enhanced potential for immunotherapy and chemotherapy responsiveness. Conclusion This study presents a clinically applicable prognostic model based on chemokine-related genes, providing insights for risk stratification and therapeutic decision-making in CC. Further validation through multicenter cohorts and mechanistic investigations of the identified genes are warranted to advance precision oncology strategies. |
| format | Article |
| id | doaj-art-2d298ef8fb674da2a36b9a1fa6a7029e |
| institution | OA Journals |
| issn | 2730-6011 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Springer |
| record_format | Article |
| series | Discover Oncology |
| spelling | doaj-art-2d298ef8fb674da2a36b9a1fa6a7029e2025-08-20T02:37:14ZengSpringerDiscover Oncology2730-60112025-06-0116111910.1007/s12672-025-02973-7Construction and validation of a chemokine-related gene signature associated with prognosis, clinical significance, and immune microenvironment characteristics in cervical cancerTianjiao Huang0Renshuang Cao1Cong Gao2Jie Luo3Zhiyu Zhou4Kun Ma5The First School of Clinical Medicine, Heilongjiang University of Chinese MedicineRespiratory Department, Wangjing Hospital of China Academy of Chinese Medical SciencesChina Academy of Chinese Medical Sciences, Xiyuan HospitalChina Academy of Chinese Medical Sciences, Xiyuan HospitalGraduate School, Tianjin University of Traditional Chinese MedicineChina Academy of Chinese Medical Sciences, Xiyuan HospitalAbstract Background Cervical cancer (CC) remains a prevalent malignancy with significant mortality among women, highlighting the urgent need for reliable prognostic tools. While chemokines have emerged as pivotal regulators in tumor progression, their potential in constructing prognostic models for CC remains underexplored. This study aimed to develop a chemokine-related gene signature for outcome prediction and therapeutic guidance in CC patients. Methods Transcriptomic data from The Cancer Genome Atlas (TCGA) cervical cancer cohort were analyzed to identify differentially expressed chemokine-related genes. Prognostic genes were screened through univariate Cox, multivariate Cox, and LASSO regression analyses, followed by the development of a risk stratification model. The model’s clinical relevance was evaluated by assessing its correlations with clinicopathological features, immune profiles, pathway enrichment, and therapeutic responses. A nomogram integrating risk scores and clinical parameters was constructed for survival prediction. Results A nine-gene signature (CCL17, CXCL8, TNF, FOXP3, CXCL1, CCL20, ITGA5, CXCL3, CCR7) was established as an independent prognostic indicator. Kaplan–Meier analysis revealed significantly shorter overall survival (OS) and progression-free survival (PFS) in high-risk patients compared to low-risk counterparts (P < 0.05). Multivariate Cox regression confirmed the signature’s independence from conventional clinical variables (P < 0.05). The nomogram demonstrated robust predictive accuracy, with 1-, 3-, and 5-year survival AUC values of 0.805, 0.729, and 0.710, respectively. Distinct immune cell infiltration patterns were observed between risk groups, with low-risk patients exhibiting enhanced potential for immunotherapy and chemotherapy responsiveness. Conclusion This study presents a clinically applicable prognostic model based on chemokine-related genes, providing insights for risk stratification and therapeutic decision-making in CC. Further validation through multicenter cohorts and mechanistic investigations of the identified genes are warranted to advance precision oncology strategies.https://doi.org/10.1007/s12672-025-02973-7Cervical cancerChemokine-related genesPrognostic modelImmunotherapy |
| spellingShingle | Tianjiao Huang Renshuang Cao Cong Gao Jie Luo Zhiyu Zhou Kun Ma Construction and validation of a chemokine-related gene signature associated with prognosis, clinical significance, and immune microenvironment characteristics in cervical cancer Discover Oncology Cervical cancer Chemokine-related genes Prognostic model Immunotherapy |
| title | Construction and validation of a chemokine-related gene signature associated with prognosis, clinical significance, and immune microenvironment characteristics in cervical cancer |
| title_full | Construction and validation of a chemokine-related gene signature associated with prognosis, clinical significance, and immune microenvironment characteristics in cervical cancer |
| title_fullStr | Construction and validation of a chemokine-related gene signature associated with prognosis, clinical significance, and immune microenvironment characteristics in cervical cancer |
| title_full_unstemmed | Construction and validation of a chemokine-related gene signature associated with prognosis, clinical significance, and immune microenvironment characteristics in cervical cancer |
| title_short | Construction and validation of a chemokine-related gene signature associated with prognosis, clinical significance, and immune microenvironment characteristics in cervical cancer |
| title_sort | construction and validation of a chemokine related gene signature associated with prognosis clinical significance and immune microenvironment characteristics in cervical cancer |
| topic | Cervical cancer Chemokine-related genes Prognostic model Immunotherapy |
| url | https://doi.org/10.1007/s12672-025-02973-7 |
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