Immune Checkpoint-Related Gene Prognostic Signature Characterizes the Immunosuppressive Microenvironment and Predicts Immunotherapy Response in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) shows heterogeneous responses to immune checkpoint inhibitors (ICIs). We aimed to develop an immune checkpoint-related gene (ICRG) signature for risk stratification, tumor microenvironment characterization, and immunotherapy prediction. Transcriptomic and clinical data from two independent ccRCC cohorts were used for consensus clustering and construction of a prognostic ICRG signature via LASSO and Cox regression, validated internally and externally. Tumor microenvironment and immunotherapy response were assessed using ESTIMATE, ssGSEA, TIDE, and the IMmotion150 trial. LIPA function was tested in vitro. A four-gene signature (SIGLEC8, TNFSF13B, C1S, LIPA) stratified patients into high- and low-risk groups with significantly different overall survival (p < 0.001) and consistent 5-year AUC of 0.70–0.78. High-risk patients displayed an immunosuppressive microenvironment with T-cell exhaustion and upregulated checkpoints. Risk score correlated with reduced benefit from combined immunotherapy and targeted therapy (p < 0.01) and shorter progression-free survival (p = 0.0035). LIPA overexpression suppressed proliferation, migration, and invasion in CAKI-1 and CAKI-2 renal carcinoma cells. This ICRG signature serves as a potential prognostic biomarker and may aid in predicting immunotherapy response. Furthermore, LIPA showed tumor-suppressive potential, providing a rationale for future personalized treatment strategies.

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Publication Details

Journal
International Journal of Molecular Sciences
Published
2026-11-11
DOI
https://doi.org/10.3390/ijms272210115
Primary Topic
Cancer Immunotherapy and Biomarkers
Type
article
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article

Immune Checkpoint-Related Gene Prognostic Signature Characterizes the Immunosuppressive Microenvironment and Predicts Immunotherapy Response in Clear Cell Renal Cell Carcinoma

Feng Yue, Jun Pang, Lei Dai, Hao Yuan et al.
International Journal of Molecular Sciences
Cancer Immunotherapy and Biomarkers
article

Immune Checkpoint-Related Gene Prognostic Signature Characterizes the Immunosuppressive Microenvironment and Predicts Immunotherapy Response in Clear Cell Renal Cell Carcinoma

Feng Yue, Jun Pang, Lei Dai, Hao Yuan, Lei Zheng, Jun Li
article en

Abstract

Clear cell renal cell carcinoma (ccRCC) shows heterogeneous responses to immune checkpoint inhibitors (ICIs). We aimed to develop an immune checkpoint-related gene (ICRG) signature for risk stratification, tumor microenvironment characterization, and immunotherapy prediction. Transcriptomic and clinical data from two independent ccRCC cohorts were used for consensus clustering and construction of a prognostic ICRG signature via LASSO and Cox regression, validated internally and externally. Tumor microenvironment and immunotherapy response were assessed using ESTIMATE, ssGSEA, TIDE, and the IMmotion150 trial. LIPA function was tested in vitro. A four-gene signature (SIGLEC8, TNFSF13B, C1S, LIPA) stratified patients into high- and low-risk groups with significantly different overall survival (p < 0.001) and consistent 5-year AUC of 0.70–0.78. High-risk patients displayed an immunosuppressive microenvironment with T-cell exhaustion and upregulated checkpoints. Risk score correlated with reduced benefit from combined immunotherapy and targeted therapy (p < 0.01) and shorter progression-free survival (p = 0.0035). LIPA overexpression suppressed proliferation, migration, and invasion in CAKI-1 and CAKI-2 renal carcinoma cells. This ICRG signature serves as a potential prognostic biomarker and may aid in predicting immunotherapy response. Furthermore, LIPA showed tumor-suppressive potential, providing a rationale for future personalized treatment strategies.

International Journal of Molecular SciencesVol. 27(22)
Sun Yat-sen University (CN), The Seventh Affiliated Hospital of Sun Yat-sen University (CN), Guangzhou Medical University (CN)
Cancer Immunotherapy and Biomarkers
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