Identification of Survival Risk and Immune-Related Characteristics of Kidney Renal Clear Cell Carcinoma

Author:

Wu Xiaobin1ORCID,Liang Yonghui2,Chen Xian1,Long Xiangyang1,Xu Wujun1,Liu Li1,Wang Binhui1,Zou Xiong3456ORCID

Affiliation:

1. The Second Affiliated Hospital, Department of Urology, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China

2. Department of Nursing, Guangxi Meiao Maternity Hospital, Nanning, Guangxi 530021, China

3. Department of Urology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, China

4. Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, 530021 Guangxi, China

5. Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning, Guangxi 530021, China

6. Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Key Laboratory of Colleges and Universities, Nanning, Guangxi 530021, China

Abstract

Background. Immunity exerts momentous functions in the progression and treatment of kidney renal clear cell carcinoma (KIRC). A better understanding of the relationship between KIRC and immunity may make a great contribution to evaluating the prognosis and immune-related therapeutic response of KIRC. Methods. A series of information such as RNA sequence, clinical data, and tumor mutation burden (TMB) of KIRC patients were downloaded through The Cancer Genome Atlas (TCGA). Next, combining the survival information and gene expression data of TCGA and Gene Expression Omnibus (GEO), we established an immune gene-related prognosis model (IGRPM) and analyzed it. Then we constructed a nomogram which was convenient for clinicians to judge the prognosis of KIRC. Last but not the least, the expressions of some genes used to construct IGRPM in early KIRC, and adjacent normal tissues were verified through real-time fluorescence quantitative polymerase chain reaction (RT-qPCR). Perl (strawberry-perl-5.30.0.1-64bit), R software (4.0.3), and GraphPad Prism 7 were used to process the relevant data. Results. The single-sample gene set enrichment analysis (ssGSEA) showed that there were significant differences in StromalScore, ImmuneScore, ESTIMATEScore, TumorPurity, 22 kinds of human immune cells infiltration, and HLA genes expression between high immunity group (Immunity_H) and low immunity group (Immunity_L). The Immunity_H expressed more immune-related genes and enriched more immune-related functions than the Immunity_L. In addition, compared with the low-risk group, the high-risk group had worse survival outcome and higher TMB. Combining IGRPM-based risk characteristic and TMB, we found that low-TMB + low-risk was the most beneficial to the survival outcome of KIRC patients. The risk characteristic based on IGRPM could be used as an independent prognostic factor for KIRC, and the nomogram constructed for evaluating the prognosis of KIRC showed excellent predictive potential. The RT-qPCR results suggested that not all the genes used to construct IGRPM showed differential expression in early KIRC compared with adjacent normal tissues, but all these genes had significant influence on the prognosis of KIRC. Conclusion. These comprehensive immune assessments and survival predictions, integrating multiple aspects of data and clinical information, can provide additional value to the current Tumor Node Metastasis staging system for risk stratification of KIRC and may facilitate the development of KIRC immunotherapy.

Funder

Key Guidance Project of Hunan Provincial Health Commission

Publisher

Hindawi Limited

Subject

Immunology,General Medicine,Immunology and Allergy

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