Tubule-specific protein nanocages potentiate targeted renal fibrosis therapy

Platelet membrane biomimetic nanoparticle-targeted delivery of TGF-β1 siRNA attenuates renal inflammation and fibrosis

The progression of renal fibrosis to end-stage renal disease (ESRD) is significantly influenced by transforming growth factor-beta (TGF-beta) signal pathway. This study aimed to develop nanoparticles (PMVs@PLGA complexes) with platelet membrane camouflage, which can transport interfering RNA to target and regulate the TGF-β1 pathway in damaged renal tissues. The aim is to reduce the severity of acute kidney injury and to reduce fibrosis in chronic kidney disease. Hence, we formulated PMVs@TGF-β1-siRNA NP complexes and employed them for both in vitro and in vivo therapy. From the experimental findings we know that the PMVs@siRNA NPs could effectively target the kidneys in unilateral ureteral obstruction (UUO) mice and ischemia/reperfusion injury (I/R) mice. In animal models of treatment, PMVs@siRNA NP complexes effectively decreased the expression of TGF-β1 and mitigated inflammation and fibrosis in the kidneys by blocking the TGF-β1/Smad3 pathway. Therefore, these PMVs@siRNA NP complexes can serve as a promising biological delivery system for treating kidney diseases.

Protein and peptide-based renal targeted drug delivery systems

Renal diseases have become an increasingly concerned public health problem in the world. Kidney-targeted drug delivery has profound transformative potential on increasing renal efficacy and reducing extra-renal toxicity. Protein and peptide-based kidney targeted drug delivery systems have garnered more and more attention due to its controllable synthesis, high biocompatibility and low immunogenicity. At the same time, the targeting methods based on protein/peptide are also abundant, including passive renal targeting based on macromolecular protein and active targeting mediated by renal targeting peptide. Here, we review the application and the drug loading strategy of different proteins or peptides in targeted drug delivery, including the ferritin family, albumin, low molecular weight protein (LMWP), different peptide sequence and antibodies. In addition, we summarized the factors influencing passive and active targeting in drug delivery system, the main receptors related to active targeting in different kidney diseases, and a variety of nano forms of proteins based on the controllable synthesis of proteins.

FOSL2 participates in renal fibrosis via SGK1-mediated epithelial-mesenchymal transition of proximal tubular epithelial cells

Background

Fos-related antigen 2 (FOSL2) plays a facilitative role in fibrotic disease; however, its role in renal fibrosis remains unclear. This study aimed to clarify the role and underlying mechanisms of FOSL2 in renal fibrosis.

Methods

Upregulated genes in unilateral ureteral obstruction (UUO)-injured kidneys were screened in Gene Expression Omnibus (GEO) databases, and overlapping genes were identified using Venn diagram software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed for these genes. The UUO-induced mouse model and transforming growth factor-β1 (TGF-β1)-induced cell model were used for the in vivo and in vitro studies.

Results

A total of 43 commonly upregulated genes were identified. GO and KEGG pathway analyses indicated that FOSL2 may be involved in fibrosis. Furthermore, FOSL2 was confirmed to be upregulated in UUO-injured kidneys and TGF-β1-induced cells. Knockdown of FOSL2 ameliorated interstitial fibrosis, extracellular matrix deposition, and epithelial-mesenchymal transition via the downregulation of fibronectin, α-smooth muscle actin (α-SMA), collagen type I (Col1a1 and Col1a2), and Col5a1 and upregulation of E-cadherin. Bioinformatics analysis revealed that serum/glucocorticoid regulated kinase 1 (SGK1) may be regulated by FOSL2 and involved in renal fibrosis. Further experiments confirmed that TGF-β1 enhanced SGK1 expression and transcription, which were reversed by FOSL2 silencing. Moreover, FOSL2 was bound to the SGK1 promoter, and SGK1 overexpression reversed the effects of FOSL2 silencing in TGF-β1-induced cells.

Conclusion

FOSL2 plays an essential role in promoting renal fibrosis in an SGK1-dependent manner, and targeting the FOSL2/SGK1 signaling axis may offer a potential strategy for the treatment of renal fibrosis.

Integrated bioinformatical analysis, machine learning and in vitro experiment-identified m6A subtype, and predictive drug target signatures for diagnosing renal fibrosis

Renal biopsy is the gold standard for defining renal fibrosis which causes calcium deposits in the kidneys. Persistent calcium deposition leads to kidney inflammation, cell necrosis, and is related to serious kidney diseases. However, it is invasive and involves the risk of complications such as bleeding, especially in patients with end-stage renal diseases. Therefore, it is necessary to identify specific diagnostic biomarkers for renal fibrosis. This study aimed to develop a predictive drug target signature to diagnose renal fibrosis based on m6A subtypes. We then performed an unsupervised consensus clustering analysis to identify three different m6A subtypes of renal fibrosis based on the expressions of 21 m6A regulators. We evaluated the immune infiltration characteristics and expression of canonical immune checkpoints and immune-related genes with distinct m6A modification patterns. Subsequently, we performed the WGCNA analysis using the expression data of 1,611 drug targets to identify 474 genes associated with the m6A modification. 92 overlapping drug targets between WGCNA and DEGs (renal fibrosis vs. normal samples) were defined as key drug targets. A five target gene predictive model was developed through the combination of LASSO regression and stepwise logistic regression (LASSO-SLR) to diagnose renal fibrosis. We further performed drug sensitivity analysis and extracellular matrix analysis on model genes. The ROC curve showed that the risk score (AUC = 0.863) performed well in diagnosing renal fibrosis in the training dataset. In addition, the external validation dataset further confirmed the outstanding predictive performance of the risk score (AUC = 0.755). These results indicate that the risk model has an excellent predictive performance for diagnosing the disease. Furthermore, our results show that this 5-target gene model is significantly associated with many drugs and extracellular matrix activities. Finally, the expression levels of both predictive signature genes EGR1 and PLA2G4A were validated in renal fibrosis and adjacent normal tissues by using qRT-PCR and Western blot method.