Background: T cell-mediated rejection is an important factor affecting early transplant kidney survival. Ferroptosis has been shown to play a pathogenic role in a variety of diseases, which was not reported in TCMR. Here we developed a model for assessing activation of ferroptosis-related genes in TCMR to find a better screening method and explore the contribution of ferroptosis in TCMR.
Methods: We performed unsupervised consensus clustering according to expression of ferroptosis-related genes based on RNA-seq data from kidney transplant biopsies, and developed an assessment model characterized by ferroptosis gene expression through PCA, which was evaluated in multiple external datasets as well as blood and urine samples. Pathway enrichment and immune cell infiltration analysis were used to explore the possible targets and pathways involved in ferroptosis and TCMR.
Results: A ferroptosis gene expression scoring model was established. The diagnostic specificity and sensitivity of TCMR in renal biopsy samples were both over 80%, AUC = 0.843, and AUC was around 0.8 in multi-dataset validation, and was also close to 0.7 in blood and urine samples, while in predicting of graft survival at 3 years, scoring model had a good prognostic effect as well. Pathway enrichment and PPI network speculated that TLR4, CD44, IFNG, etc. may be the key genes of ferroptosis in TCMR.
Conclusions: Ferroptosis scoring model could better diagnose TCMR and predict graft loss, and could be used as a potential screening method in blood and urine samples. We speculate that ferroptosis plays an important role in TCMR.
Keywords: Allograft rejection; Ferroptosis; Kidney transplantation; Medical bioinformatics; TCMR.
© 2023. The Author(s).