E-prostanoid 3 receptor deficiency on myeloid cells protects against ischemic acute kidney injury via breaking the auto-amplification loop of necroinflammation

The emerging role of regulated cell death in ischemia and reperfusion-induced acute kidney injury: current evidence and future perspectives

Renal ischemia‒reperfusion injury (IRI) is one of the main causes of acute kidney injury (AKI), which is a potentially life-threatening condition with a high mortality rate. IRI is a complex process involving multiple underlying mechanisms and pathways of cell injury and dysfunction. Additionally, various types of cell death have been linked to IRI, including necroptosis, apoptosis, pyroptosis, and ferroptosis. These processes operate differently and to varying degrees in different patients, but each plays a role in the various pathological conditions of AKI. Advances in understanding the underlying pathophysiology will lead to the development of new therapeutic approaches that hold promise for improving outcomes for patients with AKI. This review provides an overview of the recent research on the molecular mechanisms and pathways underlying IRI-AKI, with a focus on regulated cell death (RCD) forms such as necroptosis, pyroptosis, and ferroptosis. Overall, targeting RCD shows promise as a potential approach to treating IRI-AKI.

Necroptosis-related genes allow novel insights into predicting graft loss and diagnosing delayed graft function in renal transplantation

Ischemia-reperfusion injury (IRI) is an inevitable pathophysiological phenomenon in kidney transplantation. Necroptosis is an undoubtedly important contributing mechanism in renal IRI. We first screened differentially expressed necroptosis-related genes (DENRGs) from public databases. Eight DENRGs were validated by independent datasets and verified by qRT-PCR in a rat IRI model. We used univariate and multivariate Cox regression analyses to establish a prognostic signature, and graft survival analysis was performed. Immune infiltrating landscape analysis and gene set enrichment analysis (GSEA) were performed to understand the underlying mechanisms of graft loss, which suggested that necroptosis may aggravate the immune response, resulting in graft loss. Subsequently, a delayed graft function (DGF) diagnostic signature was constructed using the Least Absolute Shrinkage and Selection Operator (LASSO) and exhibited robust efficacy in validation datasets. After comprehensively analyzing DENRGs during IRI, we successfully constructed a prognostic signature and DGF predictive signature, which may provide clinical insights for kidney transplant.

Regulated necrosis role in inflammation and repair in acute kidney injury

Acute kidney injury (AKI) frequently occurs in patients with chronic kidney disease (CKD) and in turn, may cause or accelerate CKD. Therapeutic options in AKI are limited and mostly relate to replacement of kidney function until the kidneys recover spontaneously. Furthermore, there is no treatment that prevents the AKI-to-CKD transition. Regulated necrosis has recently emerged as key player in kidney injury. Specifically, there is functional evidence for a role of necroptosis, ferroptosis or pyroptosis in AKI and the AKI-to-CKD progression. Regulated necrosis may be proinflammatory and immunogenic, triggering subsequent waves of regulated necrosis. In a paradigmatic murine nephrotoxic AKI model, a first wave of ferroptosis was followed by recruitment of inflammatory cytokines such as TWEAK that, in turn, triggered a secondary wave of necroptosis which led to persistent kidney injury and decreased kidney function. A correct understanding of the specific forms of regulated necrosis, their timing and intracellular molecular pathways may help design novel therapeutic strategies to prevent or treat AKI at different stages of the condition, thus improving patient survival and the AKI-to-CKD transition. We now review key regulated necrosis pathways and their role in AKI and the AKI-to-CKD transition both at the time of the initial insult and during the repair phase following AKI.

Identification of potential necroinflammation-associated necroptosis-related biomarkers for delayed graft function and renal allograft failure: a machine learning-based exploration in the framework of predictive, preventive, and personalized medicine

Delayed graft function (DGF) is one of the key post-operative challenges for a subset of kidney transplantation (KTx) patients. Graft survival is significantly lower in recipients who have experienced DGF than in those who have not. Assessing the risk of chronic graft injury, predicting graft rejection, providing personalized treatment, and improving graft survival are major strategies for predictive, preventive, and personalized medicine (PPPM/3PM) to promote the development of transplant medicine. However, since PPPM aims to accurately identify disease by integrating multiple omics, current methods to predict DGF and graft survival can still be improved. Renal ischemia/reperfusion injury (IRI) is a pathological process experienced by all KTx recipients that can result in varying occurrences of DGF, chronic rejection, and allograft failure depending on its severity. During this process, a necroinflammation-mediated necroptosis-dependent secondary wave of cell death significantly contributes to post-IRI tubular cell loss. In this article, we obtained the expression matrices and corresponding clinical data from the GEO database. Subsequently, nine differentially expressed necroinflammation-associated necroptosis-related genes (NiNRGs) were identified by correlation and differential expression analysis. The subtyping of post-KTx IRI samples relied on consensus clustering; the grouping of prognostic risks and the construction of predictive models for DGF (the area under the receiver operating characteristic curve (AUC) of the internal validation set and the external validation set were 0.730 and 0.773, respectively) and expected graft survival after a biopsy (the internal validation set's 1-year AUC: 0.770; 2-year AUC: 0.702; and 3-year AUC: 0.735) were based on the least absolute shrinkage and selection operator regression algorithms. The results of the immune infiltration analysis showed a higher infiltration abundance of myeloid immune cells, especially neutrophils, macrophages, and dendritic cells, in the cluster A subtype and prognostic high-risk groups. Therefore, in the framework of PPPM, this work provides a comprehensive exploration of the early expression landscape, related pathways, immune features, and prognostic impact of NiNRGs in post-KTx patients and assesses their capabilities as.predictors of post-KTx DGF and graft loss,targets of the vicious loop between regulated tubular cell necrosis and necroinflammation for targeted secondary and tertiary prevention, andreferences for personalized immunotherapy.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-023-00320-w.