LncRNAS—modulators of neurovascular units in diabetic retinopathy

LncRNAs in necroptosis: Deciphering their role in cancer pathogenesis and therapy

Necroptosis, a controlled type of cell death that is different from apoptosis, has become a key figure in the aetiology of cancer and offers a possible target for treatment. A growing number of biological activities, including necroptosis, have been linked to long noncoding RNAs (lncRNAs), a varied family of RNA molecules with limited capacity to code for proteins. The complex interactions between LncRNAs and important molecular effectors of necroptosis, including mixed lineage kinase domain-like pseudokinase (MLKL) and receptor-interacting protein kinase 3 (RIPK3), will be investigated. We will explore the many methods that LncRNAs use to affect necroptosis, including protein-protein interactions, transcriptional control, and post-transcriptional modification. Additionally, the deregulation of certain LncRNAs in different forms of cancer will be discussed, highlighting their dual function in influencing necroptotic processes as tumour suppressors and oncogenes. The goal of this study is to thoroughly examine the complex role that LncRNAs play in controlling necroptotic pathways and how that regulation affects the onset and spread of cancer. In the necroptosis for cancer treatment, this review will also provide insight into the possible therapeutic uses of targeting LncRNAs. Techniques utilising LncRNA-based medicines show promise in controlling necroptotic pathways to prevent cancer from spreading and improve the effectiveness of treatment.

Circulating MicroRNAs as Potential Diagnostic Biomarkers for Diabetic Retinopathy: A Meta-Analysis

OBJECTIVE

Diabetic retinopathy (DR) is a common diabetic microvascular complication and a major cause of acquired vision loss. Finding effective biomarkers for the early identification and diagnosis of DR is crucial. This study aimed to comprehensively evaluate the accuracy of microRNAs (miRNAs) in the diagnosis of DR via a meta-analysis of previously published diagnostic studies. This study has been registered on the PROSPERO website, with the number CRD42022323238.

METHODS

We searched PubMed, Cochrane Library, Embase, Web of Science, China Wanfang database, and China Knowledge Network database to identify relevant articles published from the time of database creation to April 10, 2022. Stata 14.0 software was used to calculate the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic ratio (DOR), and area under the summary receiver operating characteristic (ROC) curve to assess the accuracy of miRNAs in the diagnosis of DR. Heterogeneity between studies was assessed using Cochran-Q test and I² statistic for quantitative analysis. The random-effect model was selected due to significant heterogeneity. Subgroup analysis and regression analysis were also performed to determine the potential sources of heterogeneity.

RESULTS

We included 25 articles detailing 52 studies with 1987 patients with DR and 1771 non-DR controls. The findings demonstrated overall sensitivity (0.82, 95% CI: 0.78 ~ 0.85), specificity (0.84, 95% CI: 0.81 ~ 0.86), PLR (5.0, 95% CI: 4.2 ~ 5.9), NLR (0.22, 95% CI: 0.18 ~ 0.26), and the area under the summary ROC curve (0.90, 95% CI: 0.87 ~ 0.92). Furthermore, we performed subgroup analysis and found that panels of multiple miRNAs could enhance the pooled sensitivity (sensitivity, specificity, and AUC values were 0.89, 0.87, and 0.94, respectively).

CONCLUSION

The meta-analysis showed that miRNAs can be used as potential diagnostic markers for DR, with high accuracy of diagnoses observed with the detection of miRNAs in plasma and serum.