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已发表论文
基于与低密度脂蛋白受体相关蛋白相关的 mRNA 对肾透明细胞癌预后特征的鉴定与验证：对肿瘤免疫微环境、突变模式及个性化治疗策略的见解
Authors Xie L, Zhou Y, Hu Z, Zhang S, Fan M, Huang X, Zhang W , Liu Z
Received 28 May 2025
Accepted for publication 26 November 2025
Published 26 December 2025 Volume 2025:18 Pages 7875—7892
DOI https://doi.org/10.2147/IJGM.S543310
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Ching-Hsien Chen
Lei Xie,1 Yajie Zhou,1 Zijian Hu,1 Shuwen Zhang,2,3 Minghu Fan,4 Xin Huang,4 Wenxiong Zhang,1 Zhihong Liu4
1Department of Thoracic Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, People’s Republic of China; 2Department of Urology Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, People’s Republic of China; 3Jiangxi Medical College, Nanchang University, Nanchang, 330006, People’s Republic of China; 4Department of Oncology, Yingtan 184 Hospital, China Rongtong Medical Healthcare Group Co. Ltd., Yingtan, 335000, People’s Republic of China
Correspondence: Zhihong Liu, Department of Oncology, Yingtan 184 Hospital, China Rongtong Medical Healthcare Group, No. 4 Hudong Road, Yuehu District, Yingtan, 335000, People’s Republic of China, Email 19007012757@163.com
Background: Low-density lipoprotein receptor-related protein (LRP) is integral to protein synthesis and contributes significantly to tumor initiation and growth. However, the role of LRP-related mRNAs (LRPMRs) in KIRC progression remains unclear. Our study investigates the potential use of LRPMRs as prognostic markers in patients with KIRC.
Methods: Clinical and transcriptomic data of KIRC patients were obtained from The Cancer Genome Atlas (TCGA) database for model construction and performance evaluation. A nomogram integrating clinical characteristics and the risk model was then established. To explore the clinical significance and underlying mechanisms, we analyzed the tumor microenvironment (TME), evaluated tumor mutational burden (TMB), performed gene set enrichment analysis, and predicted drug sensitivity. The mRNA expression was assessed using RT-qPCR.
Results: A six-LRPMR-based model was developed and provided significant prognostic information. Kaplan-Meier analysis demonstrated worse survival outcomes for high-risk (H-R) patients (p < 0.001). A nomogram incorporating the risk model showed improved predictive accuracy compared with the clinical model alone (AUC = 0.761). GSEA highlighted proximal tubule transport and propanoate metabolism pathways as significantly enriched in the low-risk (L-R) group, while the H-R group displayed enrichment in CD22-mediated BCR regulation and FCGR activation pathways. Higher TMB in the H-R cohort predicted a poor prognosis. TME analysis suggested that H-R patients may respond less favorably to immunotherapy. Drug sensitivity analysis indicated that H-R patients were more sensitive to Staurosporine and Sabutoclax, whereas L-R patients were more sensitive to dihydrorotenone and osimertinib. RT-qPCR validated differential mRNA expression between KIRC and normal cells.
Conclusion: This six-LRPMR-based prognostic model provides valuable insights for prognosis assessment and personalized treatment selection in KIRC.
Keywords: low-density lipoprotein receptor-related protein, mRNAs, kidney renal clear cell carcinoma, prognostic model, nomogram
1Department of Thoracic Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, People’s Republic of China; 2Department of Urology Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, People’s Republic of China; 3Jiangxi Medical College, Nanchang University, Nanchang, 330006, People’s Republic of China; 4Department of Oncology, Yingtan 184 Hospital, China Rongtong Medical Healthcare Group Co. Ltd., Yingtan, 335000, People’s Republic of China
Correspondence: Zhihong Liu, Department of Oncology, Yingtan 184 Hospital, China Rongtong Medical Healthcare Group, No. 4 Hudong Road, Yuehu District, Yingtan, 335000, People’s Republic of China, Email 19007012757@163.com
Background: Low-density lipoprotein receptor-related protein (LRP) is integral to protein synthesis and contributes significantly to tumor initiation and growth. However, the role of LRP-related mRNAs (LRPMRs) in KIRC progression remains unclear. Our study investigates the potential use of LRPMRs as prognostic markers in patients with KIRC.
Methods: Clinical and transcriptomic data of KIRC patients were obtained from The Cancer Genome Atlas (TCGA) database for model construction and performance evaluation. A nomogram integrating clinical characteristics and the risk model was then established. To explore the clinical significance and underlying mechanisms, we analyzed the tumor microenvironment (TME), evaluated tumor mutational burden (TMB), performed gene set enrichment analysis, and predicted drug sensitivity. The mRNA expression was assessed using RT-qPCR.
Results: A six-LRPMR-based model was developed and provided significant prognostic information. Kaplan-Meier analysis demonstrated worse survival outcomes for high-risk (H-R) patients (p < 0.001). A nomogram incorporating the risk model showed improved predictive accuracy compared with the clinical model alone (AUC = 0.761). GSEA highlighted proximal tubule transport and propanoate metabolism pathways as significantly enriched in the low-risk (L-R) group, while the H-R group displayed enrichment in CD22-mediated BCR regulation and FCGR activation pathways. Higher TMB in the H-R cohort predicted a poor prognosis. TME analysis suggested that H-R patients may respond less favorably to immunotherapy. Drug sensitivity analysis indicated that H-R patients were more sensitive to Staurosporine and Sabutoclax, whereas L-R patients were more sensitive to dihydrorotenone and osimertinib. RT-qPCR validated differential mRNA expression between KIRC and normal cells.
Conclusion: This six-LRPMR-based prognostic model provides valuable insights for prognosis assessment and personalized treatment selection in KIRC.
Keywords: low-density lipoprotein receptor-related protein, mRNAs, kidney renal clear cell carcinoma, prognostic model, nomogram