A novel defined pyroptosis-related genes prognostic risk model for predicting the prognosis of kidney renal clear cell carcinoma
10.16098/j.issn.0529-1356.2022.05.012
- Author:
Wan-Li WANG
1
;
Wei-Nan REN
1
;
Qian ZHAO
1
;
Zhen-Yu SHI
2
;
Yong-Qiang LI
2
Author Information
1. School of Stomatology, Henan University, Grade 2018
2. Institute of Biomedical Informatics, School of Basic Medical Sciences, Henan University
- Publication Type:Journal Article
- Keywords:
Human;
Immune infiltration;
Kidney renal clear cell carcinoma;
LASSO Cox regression analysis;
Prognosis
- From:
Acta Anatomica Sinica
2022;53(5):620-627
- CountryChina
- Language:Chinese
-
Abstract:
Objective To establish a novel defined pyroptosis-related genes risk model of kidney renal clear cell carcinoma. Methods Data of 522 patients with KIRC and 72 normal tissue samples were respectively downloaded from the Cancer Genome Atlas ( TCGA) database and Genotype-Tissue Expression ( GTEx) database. Differential analysis was performed between data of TCGA and GTEx. Univariate Cox regression analysis, multivariate Cox regression analyses and LASSO Cox regression analysis were used to establish a prognostic risk model. Data from the International Cancer Genome Consortium (ICGC) database was used as an external validation cohort. Gene ontology ( GO) enrichment analysis and Kyoto Encylopedia of Genes and Genomes (KEGG) pathway analysis were used to explore the differences of gene functions and pathways between high-risk and low-risk groups. The CIBERSORT database was used to explore the immune infiltration of high-risk and low-risk groups. Results Through differential analysis, we obtained 13 differentially expressed pyroptosis-related genes. Univariate Cox regression analysis, multivariable Cox regression analyses and LASSO Cox regression analysis were used to establish a 6-gene risk model. Kaplan-Meier analysis indicated that survival time in high-risk group was shorter than low-risk group in both cohorts. The area under the curve ( AUC) was 0. 710 for 1-year, 0. 683 for 2-year, and 0. 727 for 3-year survival in the TCGA_KIRC cohort. The AUC was 0. 592 for 1-year, 0. 531 for 2-year, and 0. 545 for 3-year survival in the ICGC_RECA cohort. Independent prognostic analysis indicated that risk score was an independent prognostic factor. GO enrichment analysis and KEGG pathway analysis showed that it was mainly associated with immune and inflammatory responses. The result of tumor immune infiltration showed that the high-risk group had low infiltration levels of regulatory T cells , natural killer cells, monocytes, M2 macrophages and eosinophils and high infiltration level of B cells, CD8+T cells and follicular helper T cells. Conclusion Pyrolysis-related genes may play an important role in KIRC tumor immunity, and the 6-gene risk model can provide a forecast basis for personalized treatment of patients with KIRC.
