MiR-522-3p inhibits proliferation and activation by regulating the expression of SLC31A1 in T cells

Blocking lactate regulation of the Grhl2/SLC31A1 axis inhibits trophoblast cuproptosis and preeclampsia development

PURPOSE

Abnormal cell death due to superficial trophoblast dysfunction caused by placental hypoxia plays a vital role in the development of preeclampsia (PE). Lactic acid stimulates gene transcription in chromatin through lactate modification of histone lysine. Nevertheless, the content and function of lactate in PE development remains largely unclear.

METHODS

The contents of lactic acid and copper in 30 PE and 30 normal placentas were determined by kit colorimetry. Real-time quantitative fluorescent PCR (qRT-PCR) and Western blot were used to detect the expression of SLC31A1 in cells and tissues. Cell proliferation, apoptosis, and invasion were detected by cell counting kit 8 (CCK-8), MTS assay, colony formation assay, and Transwell assay. The transcriptional regulation between Grhl2 and SLC31A was verified by the luciferase reporter gene method and ChIP. The H3K18la modification level was detected by ChIP-PCR.

RESULTS

Herein, we detected increased lactic acid levels in the PE placental tissue, which inhibit the proliferation and invasion of trophoblasts. Interestingly, lactic acid increases intracellular copper content by enhancing the expression of SLC31A1, a key protein of copper ion transporters. Lentivirus knockdown of SLC31A1 blocked the lactate-induced proliferation and invasion of trophoblasts by inhibiting cell cuproptosis. Mechanically, we identified that Grhl2 mediated SLC31A1 expression through transcription and participated in SLC31A1-inhibited proliferation, invasion, and cuproptosis of trophoblasts. Furthermore, the high lactate content increased Grhl2 expression by enhancing lactate modification of histone H3K18 in the Grhl2 promoter region.

CONCLUSIONS

Blocking the lactate-regulated Grhl2/SLC31A1 axis and trophoblastic cuproptosis may be a potential approach to prevent and treat PE.

The intricate dance of non-coding RNAs in myasthenia gravis pathogenesis and treatment

Myasthenia gravis (MG) stands as a perplexing autoimmune disorder affecting the neuromuscular junction, driven by a multitude of antibodies targeting postsynaptic elements. However, the mystery of MG pathogenesis has yet to be completely uncovered, and its heterogeneity also challenges diagnosis and treatment. Growing evidence shows the differential expression of non-coding RNAs (ncRNAs) in MG has played an essential role in the development of MG in recent years. Remarkably, these aberrantly expressed ncRNAs exhibit distinct profiles within diverse clinical subgroups and among patients harboring various antibody types. Furthermore, they have been implicated in orchestrating the production of inflammatory cytokines, perturbing the equilibrium of T helper 1 cells (Th1), T helper 17 cells (Th17), and regulatory T cells (Tregs), and inciting B cells to generate antibodies. Studies have elucidated that certain ncRNAs mirror the clinical severity of MG, while others may hold therapeutic significance, showcasing a propensity to return to normal levels following appropriate treatments or potentially foretelling the responsiveness to immunosuppressive therapies. Notably, the intricate interplay among these ncRNAs does not follow a linear trajectory but rather assembles into a complex network, with competing endogenous RNA (ceRNA) emerging as a prominent hub in some cases. This comprehensive review consolidates the landscape of dysregulated ncRNAs in MG, briefly delineating their pivotal role in MG pathogenesis. Furthermore, it explores their promise as prospective biomarkers, aiding in the elucidation of disease subtypes, assessment of disease severity, monitoring therapeutic responses, and as novel therapeutic targets.

Identification and immuno-infiltration analysis of cuproptosis regulators in human spermatogenic dysfunction

Introduction: Cuproptosis seems to promote the progression of diverse diseases. Hence, we explored the cuproptosis regulators in human spermatogenic dysfunction (SD), analyzed the condition of immune cell infiltration, and constructed a predictive model.

Methods: Two microarray datasets (GSE4797 and GSE45885) related to male infertility (MI) patients with SD were downloaded from the Gene Expression Omnibus (GEO) database. We utilized the GSE4797 dataset to obtain differentially expressed cuproptosis-related genes (deCRGs) between SD and normal controls. The correlation between deCRGs and immune cell infiltration status was analyzed. We also explored the molecular clusters of CRGs and the status of immune cell infiltration. Notably, weighted gene co-expression network analysis (WGCNA) was used to identify the cluster-specific differentially expressed genes (DEGs). Moreso, gene set variation analysis (GSVA) was performed to annotate the enriched genes. Subsequently, we selected an optimal machine-learning model from four models. Finally, nomograms, calibration curves, decision curve analysis (DCA), and the GSE45885 dataset were utilized to verify the predictions’ accuracy.

Results: Among SD and normal controls, we confirmed that there are deCRGs and activated immune responses. Through the GSE4797 dataset, we obtained 11 deCRGs. ATP7A, ATP7B, SLC31A1, FDX1, PDHA1, PDHB, GLS, CDKN2A, DBT, and GCSH were highly expressed in testicular tissues with SD, whereas LIAS was lowly expressed. Additionally, two clusters were identified in SD. Immune-infiltration analysis showed the existing heterogeneity of immunity at these two clusters. Cuproptosis-related molecular Cluster2 was marked by enhanced expressions of ATP7A, SLC31A1, PDHA1, PDHB, CDKN2A, DBT, and higher proportions of resting memory CD4+ T cells. Furthermore, an eXtreme Gradient Boosting (XGB) model based on 5-gene was built, which showed superior performance on the external validation dataset GSE45885 (AUC = 0.812). Therefore, the combined nomogram, calibration curve, and DCA results demonstrated the accuracy of predicting SD.

Conclusion: Our study preliminarily illustrates the relationship between SD and cuproptosis. Moreover, a bright predictive model was developed.

A Review on the Role of Non-Coding RNAs in the Pathogenesis of Myasthenia Gravis

Myasthenia gravis (MG) is an autoimmune condition related to autoantibodies against certain proteins in the postsynaptic membranes in the neuromuscular junction. This disorder has a multifactorial inheritance. The connection between environmental and genetic factors can be established by epigenetic factors, such as microRNAs (miRNAs) and long non-coding RNAs (lncRNAs). XLOC_003810, SNHG16, IFNG-AS1, and MALAT-1 are among the lncRNAs with a possible role in the pathoetiology of MG. Moreover, miR-150-5p, miR-155, miR-146a-5p, miR-20b, miR-21-5p, miR-126, let-7a-5p, and let-7f-5p are among miRNAs whose roles in the pathogenesis of MG has been assessed. In the current review, we summarize the impact of miRNAs and lncRNAs in the development or progression of MG.