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Creating and Utilizing an Immune-Related Gene Prognosis Framework for Kidney Clear Cell Carcinoma

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DOI: 10.23977/medbm.2024.020113 | Downloads: 5 | Views: 122


Jiahui Luo 1, Qingbo Zhou 2


1 The Fourth School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China
2 Department of Internal Medicine, Shaoxing Yuecheng People's Hospital, Shaoxing, China

Corresponding Author

Jiahui Luo


In this study, we initially classified renal cell carcinoma (ccRCC) samples into three distinct clusters based on immune expression patterns, utilizing an analysis of immunomodulatory genes. Through comprehensive examination of the differential genes across these clusters, a prognostic risk assessment framework was developed, aimed at determining risk levels to assist in prognostic evaluation and targeted therapy for ccRCC patients. Employing a consensus clustering method, 435 shared differential genes were pinpointed, predominantly associated with a range of immunomodulation pathways, through examining the immunomodulatory gene expressions in TCGA-KIRC patient samples. Furthermore, a univariate COX regression analysis allowed for the identification of 152 genes with significant prognostic associations, from which 11 pivotal genes were selected for the model through LASSO regression analysis. Utilizing these identified genes, a new prognostic risk assessment tool was crafted, and its predictive efficiency was confirmed via analysis of ROC curves. This newly developed prognostic tool, focusing on immunomodulatory genes, underwent thorough validation against external datasets, thereby enhancing the precision of clinical prognosis evaluations for ccRCC patients. 


Immunomodulatory Genes, Renal clear cell carcinoma, Prognostic model, Consensus clustering, Prognostic model


Jiahui Luo, Qingbo Zhou, Creating and Utilizing an Immune-Related Gene Prognosis Framework for Kidney Clear Cell Carcinoma. MEDS Basic Medicine (2024) Vol. 2: 102-108. DOI:


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