Bioinformatics Analysis of Autophagy-Related Genes in Kidney Transplantation.

Abstract

Introduction: Autophagy related genes (ARGs) may play important roles in various biological processes involving kidney transplantation (KT); however, their expression characteristics are rarely used to study the relationship between autophagy and prognosis in KT patients. This study aims to construct a new autophagy related gene feature based on high-throughput sequencing datasets.

Methods: Differentially expressed ARGs (DEARGs) were identified in KT patients based on the Gene Expression Omnibus (GEO) database. Gene Ontology (GO)and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to explore potential biological and pathological functions of DEARGs. Univariate and Lasso Cox regression analyses identified survival-related DEARGs and established a prognostic gene signature whose performance was evaluated by Kaplan-Meier curve and receiver operating characteristic (ROC). Moreover, the prognostic value of the gene signature was further validated in 48 KT patients from the GSE21374 dataset.  Results. A total of 28 common DEARGs were identified between rejection and non-rejection samples in 3 datasets, including GSE21374, GSE36059, and GSE48581. GO and KEGG enrichment analyses showed that DEARGs were mainly involved in regulating apoptotic processes. In addition, we identified and validated 7 DEARGs (CASP1, CASP3, FKBP1A, RAB11A, NFKB1, RGS19, and CCL2) as the prognostic signatures. The Kaplan-Meier (K-M) analysis showed that the survival rate of the high-risk patients was significantly lower than that of the low-risk patients.

Conclusion: The effectiveness of autophagy related features was validated by using 48 KT patients in the GSE21374 dataset, and establishing and confirming a new ARG signal with independent survival prognostic value for KT patients.