ISSN: 1837-9664Journal of Cancer
Global reach, higher impact
J Cancer 2023; 14(17):3335-3350. doi:10.7150/jca.88467 This issue Cite
Research Paper
Prognosis, Immune Microenvironment Infiltration and Immunotherapy Response in Clear Cell Renal Cell Carcinoma Based on Cuproptosis-related Immune Checkpoint Gene Signature
1. Department of Urology, Shengjing Hospital of China Medical University, Shenyang 110004, Liaoning, China.
2. Department of Gynecology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
3. Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China.
Abstract
Background: Immune checkpoint genes (ICGs), which are the cornerstone of immunotherapy, influence the incidence and progression of clear cell renal cell carcinoma (ccRCC). It is important to note that there is not much data in the literature to determine how cuproptosis and antitumor immunity are related.
Methods: On the basis of The Cancer Genome Atlas ccRCC dataset (n=526), cuproptosis-related ICGs (CICGs) were used to identify distinct molecular subtypes. Using the Cox regression method, a risk signature was constructed and externally validated using the ICGC (n=91) and primary ccRCC subgroups of GSE22541 (n=24). The molecular and immune characteristics and efficacy of immunotherapy in the subgroups defined by the risk score were investigated. Four risk CICGs were verified through in vitro experiment.
Results: We identified two unique molecular subgroups with substantial prognostic differences based on 17 CICGs. The two subtypes clearly differ in terms of the tumor immune microenvironment (TME). A predictive risk signature (CD276, HLA-E, LGALS9, and TNFRSF18) was created and externally confirmed, and their expressions were validated by realtime PCR. The multivariate Cox regression analysis demonstrated that this signature could independently predict survival. Thus, a credible nomogram incorporating the signature, age, stage, and grade was constructed, and discrimination was confirmed using the C-index, calibration curve, and decision curve analyses. The underlying implications for immune checkpoint inhibitors, the landscape of the TME, and single-cell level localization are depicted. In addition, its accuracy in forecasting actual immunotherapeutic results has been proven (CheckMate025 and TCGA-SKCM cohorts). The sensitivity of the two risk groups to various drug-targeted therapy methods was analyzed.
Conclusions: The data provided here provide the groundwork for creating customized therapeutic options for individuals with ccRCC. The findings also suggested that researching the cuproptosis-based pathway might improve ccRCC patient better prognosis, development of anti-tumor immunity, and therapeutic strategies for immunotherapy.
Keywords: immune checkpoint, cuproptosis, clear cell renal cell carcinoma, immune microenvironment, prognosis, immune therapy.
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