CCN2 Activates RIPK3, NLRP3 Inflammasome, and NRF2/Oxidative Pathways Linked to Kidney Inflammation

Screening and identification of key biomarkers associated with endometriosis using bioinformatics and next-generation sequencing data analysis

Background

Endometriosis is a common cause of endometrial-type mucosa outside the uterine cavity with symptoms such as painful periods, chronic pelvic pain, pain with intercourse and infertility. However, the early diagnosis of endometriosis is still restricted. The purpose of this investigation is to identify and validate the key biomarkers of endometriosis.

Methods

Next-generation sequencing dataset GSE243039 was obtained from the Gene Expression Omnibus database, and differentially expressed genes (DEGs) between endometriosis and normal control samples were identified. After screening of DEGs, gene ontology (GO) and REACTOME pathway enrichment analyses were performed. Furthermore, a protein–protein interaction (PPI) network was constructed and modules were analyzed using the Human Integrated Protein–Protein Interaction rEference database and Cytoscape software, and hub genes were identified. Subsequently, a network between miRNAs and hub genes, and network between TFs and hub genes were constructed using the miRNet and NetworkAnalyst tool, and possible key miRNAs and TFs were predicted. Finally, receiver operating characteristic curve analysis was used to validate the hub genes.

Results

A total of 958 DEGs, including 479 upregulated genes and 479 downregulated genes, were screened between endometriosis and normal control samples. GO and REACTOME pathway enrichment analyses of the 958 DEGs showed that they were mainly involved in multicellular organismal process, developmental process, signaling by GPCR and muscle contraction. Further analysis of the PPI network and modules identified 10 hub genes, including vcam1, snca, prkcb, adrb2, foxq1, mdfi, actbl2, prkd1, dapk1 and actc1. Possible target miRNAs, including hsa-mir-3143 and hsa-mir-2110, and target TFs, including tcf3 (transcription factor 3) and clock (clock circadian regulator), were predicted by constructing a miRNA-hub gene regulatory network and TF-hub gene regulatory network.

Conclusions

This investigation used bioinformatics techniques to explore the potential and novel biomarkers. These biomarkers might provide new ideas and methods for the early diagnosis, treatment and monitoring of endometriosis.

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.