CircPAG1 interacts with miR-211-5p to promote the E2F3 expression and inhibit the high glucose-induced cell apoptosis and oxidative stress in diabetic cataract

Ameliorating effect of the aldose reductase inhibitor 1-Acetyl-5-phenyl-1 H-pyrrol-3-ylacetate on galactose-induced cataract

Diabetes mellitus, as a common chronic disease, easily leads to significant changes in the structure of the eye, among which diabetic cataract is particularly common. Although surgery is the main treatment for this complication, it may be accompanied by postoperative complications. Therefore, it is particularly important to develop specific drugs for diabetic cataract, aiming to fundamentally reduce its incidence and reduce the need for surgery. At present, the greatest challenge is to develop therapeutic agents with multiple synergistic effects based on the complex pathogenesis of cataract. 1-Acetyl-5-phenyl-1 H-pyrrol-3-ylacetate (APPA) is designed based on the pathological mechanism as a potential drug to alleviate the occurrence of diabetic cataract. Our observations suggest that APPA is more effective than bendazaclysine in alleviating high galactose-induced oxidative stress (The malondialdehyde content in the APPA group and bendazaclysine group was significantly reduced to 0.45-fold and 0.58-fold compared to the high galactose-induced group, respectively.) and apoptosis (The apoptosis rate in the APPA group and bendazaclysine group was significantly reduced to 0.28-fold and 0.35-fold compared to the high galactose-induced group, respectively.) in lens epithelial cells by increasing antioxidant enzyme activity, and restoring mitochondrial homeostasis. Mechanistic studies have shown that APPA restoration of mitochondrial homeostasis is mediated through the SIRT1-PGC-1α pathway. In the galactose-induced cataract rat model, APPA is effective in alleviating the occurrence of galactose-induced cataract. In conclusion, APPA with multiple synergistic functions may be a potential drug to alleviate the occurrence of diabetic cataract, and it has a wider range of indications than benzydalysine.

Mechanistic and therapeutic perspectives of non-coding RNA-modulated apoptotic signaling in diabetic retinopathy

Diabetic retinopathy (DR), a significant and vision-endangering complication associated with diabetes mellitus, constitutes a substantial portion of acquired instances of preventable blindness. The progression of DR appears to prominently feature the loss of retinal cells, encompassing neural retinal cells, pericytes, and endothelial cells. Therefore, mitigating the apoptosis of retinal cells in DR could potentially enhance the therapeutic approach for managing the condition by suppressing retinal vascular leakage. Recent advancements have highlighted the crucial regulatory roles played by non-coding RNAs (ncRNAs) in diverse biological processes. Recent advancements have highlighted that non-coding RNAs (ncRNAs), including microRNAs (miRNAs), circular RNAs (circRNAs), and long non-coding RNAs (lncRNAs), act as central regulators in a wide array of biogenesis and biological functions, exerting control over gene expression associated with histogenesis and cellular differentiation within ocular tissues. Abnormal expression and activity of ncRNAs has been linked to the regulation of diverse cellular functions such as apoptosis, and proliferation. This implies a potential involvement of ncRNAs in the development of DR. Notably, ncRNAs and apoptosis exhibit reciprocal regulatory interactions, jointly influencing the destiny of retinal cells. Consequently, a thorough investigation into the complex relationship between apoptosis and ncRNAs is crucial for developing effective therapeutic and preventative strategies for DR. This review provides a fundamental comprehension of the apoptotic signaling pathways associated with DR. It then delves into the mutual relationship between apoptosis and ncRNAs in the context of DR pathogenesis. This study advances our understanding of the pathophysiology of DR and paves the way for the development of novel therapeutic strategies.

circSKA3 promotes colorectal cancer metastases through miR-1238 and methylation

Colorectal cancer (CRC) is becoming one of the most common cancers overworld, which causes a high rate of death in patients. circRNAs are non-coding RNAs(ncRNAs), which have been reported to be involved in the development of many cancers, including CRC. However, the exact mechanism that how circRNAs function through in CRC remains unclear. In this study, we firstly used GEO database and bioinformatic methods to identify the significant changed circRNAs, with circSKA3 being the most significantly upregulated circRNAs in CRC tissues. PCR results further confirmed higher expression of circSKA3 in CRC patients. CCK-8, scratch, and transwell assays indicated that circSKA3 could promote the proliferation, migration, and invasion of CRC cell lines for cell detection. Dual-luciferase assays were carried out to detect the downstream targets of circSKA3, and a binding site between circSKA3 and miR-1238 was identified and miR-1238 could also combine with YTHDF2. Overexpression of YTHDF2 rescued the decreased cell proliferation, migration, and invasion caused by miR-1238 overexpression. RIP assay further indicated that YTHDF2 could decrease the methylation of STAT5A. In summary, our study found that circSKA3 was upregulated in CRC tissues comparing with normal tissues. circSKA3 could increase the expression ofYTHDF2 through sponging miR-1238 to decrease the methylation of STAT5A, which could provide a novel target for CRC treatment.

Ectopic circSTK39 Expression Ameliorates Hydrogen Peroxide-Induced Human Lens Epithelial Cell Apoptosis and Oxidative Stress through the miR-125a-5p/ERCC6 Pathway

PURPOSE

More and more studies suggest that circular RNA (circRNA) is involved in the pathogenesis of age-related cataract (ARC). CircSTK39, a circular RNA, has inhibitory effects on cancer progression. However, there is no data regarding the role of circSTK39 in ARC occurrence and the underlying mechanism.

METHODS

ARC cell model was established by inducing lens epithelial cells (SRA01/04) using hydrogen peroxide (H₂O₂). CircSTK39, microRNA-125a-5p (miR-125a-5p), and ERCC excision repair 6, chromatin remodeling factor (ERCC6) expression were detected by quantitative real-time polymerase chain reaction. Western blot was conducted to assess protein expression. Cell viability, proliferation, and apoptosis were investigated by cell counting kit-8 assay, 5-Ethynyl-29-deoxyuridine assay, and flow cytometry analysis, respectively. Oxidative stress was evaluated using commercial kits. Dual-luciferase reporter assay, RNA immunoprecipitation assay, and RNA pull-down assay were used to identify the relationship between miR-125a-5p and circSTK39 or ERCC6.

RESULTS

CircSTK39 and ERCC6 expression were significantly downregulated, but miR-125a-5p expression was upregulated in the lens tissues of ARC patients and H₂O₂-treated SRA01/04 cells. H₂O₂ treatment led to decreased cell proliferation and increased cell apoptosis and oxidative stress, accompanied by the increases of C-caspase3 and Bax expression and the decrease of Bcl-2 expression; however, these effects were reversed after circSTK39 overexpression. MiR-125a-5p was found to participate in H₂O₂-triggered cell damage by interacting with circSTK39. Additionally, ERCC6 silencing inhibited circSTK39 overexpression-mediated action. Importantly, circSTK39 regulated ERCC6 expression by interaction with miR-125a-5p in H₂O₂-treated SRA01/04 cells.

CONCLUSION

The increased expression of circSTK39 ameliorated H₂O₂-induced SRA01/04 cell injury through the miR-125a-5p/ERCC6 pathway.

The Differential Expression of Circular RNAs and the Role of circAFF1 in Lens Epithelial Cells of High-Myopic Cataract

High-myopic cataract (HMC) is a complex cataract with earlier onset and more rapid progress than age-related cataract (ARC). Circular RNAs (circRNAs) have been implicated in many diseases. However, their involvement in HMC remain largely unexplored. To investigate the role of dysregulated circRNAs in HMC, lens epithelium samples from 24 HMC and 24 ARC patients were used for whole transcriptome sequencing. Compared with ARC, HMC had 3687 uniquely expressed circRNAs and 1163 significantly differentially expressed circRNAs (DEcRs) (|log₂FC| > 1, p < 0.05). A putative circRNA-miRNA-mRNA network was constructed based on correlation analysis. We validated the differential expression of 3 DEcRs by quantitative polymerase chain reaction (qPCR) using different sets of samples. We further investigated the role of circAFF1 in cultured lens epithelial cells (LECs) and found that the overexpression of circAFF1 promoted cell proliferation, migration and inhibited apoptosis. We also showed that circAFF1 upregulated Tropomyosin 1 (TPM1) expression by sponging miR-760, which was consistent with the network prediction. Collectively, our study suggested the involvement of circRNAs in the pathogenesis of HMC and provide a resource for further study on this topic.

KGDCMI: A New Approach for Predicting circRNA–miRNA Interactions From Multi-Source Information Extraction and Deep Learning

Emerging evidence has revealed that circular RNA (circRNA) is widely distributed in mammalian cells and functions as microRNA (miRNA) sponges involved in transcriptional and posttranscriptional regulation of gene expression. Recognizing the circRNA–miRNA interaction provides a new perspective for the detection and treatment of human complex diseases. Compared with the traditional biological experimental methods used to predict the association of molecules, which are limited to the small-scale and are time-consuming and laborious, computing models can provide a basis for biological experiments at low cost. Considering that the proposed calculation model is limited, it is necessary to develop an effective computational method to predict the circRNA–miRNA interaction. This study thus proposed a novel computing method, named KGDCMI, to predict the interactions between circRNA and miRNA based on multi-source information extraction and fusion. The KGDCMI obtains RNA attribute information from sequence and similarity, capturing the behavior information in RNA association through a graph-embedding algorithm. Then, the obtained feature vector is extracted further by principal component analysis and sent to the deep neural network for information fusion and prediction. At last, KGDCMI obtains the prediction accuracy (area under the curve [AUC] = 89.30% and area under the precision–recall curve [AUPR] = 87.67%). Meanwhile, with the same dataset, KGDCMI is 2.37% and 3.08%, respectively, higher than the only existing model, and we conducted three groups of comparative experiments, obtaining the best classification strategy, feature extraction parameters, and dimensions. In addition, in the performed case study, 7 of the top 10 interaction pairs were confirmed in PubMed. These results suggest that KGDCMI is a feasible and useful method to predict the circRNA–miRNA interaction and can act as a reliable candidate for related RNA biological experiments.