Screening of lncRNA-miRNA-mRNA Coexpression Regulatory Networks Involved in Acute Traumatic Coagulation Dysfunction Based on CTD, GeneCards, and PharmGKB Databases

From diagnosis to therapy: The transformative role of lncRNAs in eye cancer management

The genomic era has brought about a transformative shift in our comprehension of cancer, unveiling the intricate molecular landscape underlying disease development. Eye cancers (ECs), encompassing diverse malignancies affecting ocular tissues, pose distinctive challenges in diagnosis and management. Long non-coding RNAs (lncRNAs), an emerging category of non-coding RNAs, are pivotal actors in the genomic intricacies of eye cancers. LncRNAs have garnered recognition for their multifaceted roles in gene expression regulation and influence on many cellular processes. Many studies support that the lncRNAs have a role in developing various cancers. Recent investigations have pinpointed specific lncRNAs associated with ECs, including retinoblastoma and uveal melanoma. These lncRNAs exert control over critical pathways governing tumor initiation, progression, and metastasis, endowing them with the ability to function as evaluation, predictive, and therapeutic indicators. The article aims to synthesize the existing information concerning the functions of lncRNAs in ECs, elucidating their regulatory mechanisms and clinical significance. By delving into the lncRNAs' expanding relevance in the modulation of oncogenic and tumor-suppressive networks, we gain a deeper understanding of the molecular complexities intrinsic to these diseases. In our exploration of the genomic intricacies of ECs, lncRNAs introduce a fresh perspective, providing an opportunity to function as clinical and therapeutic indicators, and they also have therapeutic benefits that show promise for advancing the treatment of ECs. This comprehensive review bridges the intricate relationship between lncRNAs and ECs within the context of the genomic era.

circ_0001274 Competitively Binds miR-143-3p to Upregulate VWF Expression to Improve Acute Traumatic Coagulopathy

Accumulating evidence has noted the circRNA-microRNA- (circRNA-miRNA-) mRNA competing endogenous RNA (ceRNA) regulatory network in disease development and progression. The current study explored the ceRNA network in acute traumatic coagulopathy (ATC). Potential ATC-related genes were screened, and upstream miRNAs and circRNAs of VWF (the candidate target) were assayed through database searching and high-throughput sequencing technology. circ_0001274/miR-143-3p/VWF ceRNA regulatory network was constructed and validated. The expression of circ_0001274/miR-143-3p/VWF was determined in the peripheral blood samples from ATC patients and ATC mouse models. Online database and circRNA sequencing analysis results identified VWF as a key gene in ATC as supported by assays and that VWF was lowly expressed in ATC patients and mice. Further experiments demonstrated that miR-143-3p could target and inhibit VWF, and circ_0001274 could competitively sponge miR-143-3p. Functionally, circ_0001274 could competitively sequester miR-143-3p to upregulate VWF expression, potentially improving ATC. Our study highlights the critical role of circ_0001274/miR-143-3p/VWF axis in improving ATC.

The Intricate Role of Non-Coding RNAs in Sepsis-Associated Disseminated Intravascular Coagulation

Disseminated Intravascular Coagulation (DIC) is a type of tissue and organ dysregulation in sepsis, due mainly to the effect of the inflammation on the coagulation system. Unfortunately, the underlying molecular mechanisms that lead to this disorder are not fully understood. Moreover, current biomarkers for DIC, including biological and clinical parameters, generally provide a poor diagnosis and prognosis. In recent years, non-coding RNAs have been studied as promising and robust biomarkers for a variety of diseases. Thus, their potential in the diagnosis and prognosis of DIC should be further studied. Specifically, the relationship between the coagulation cascade and non-coding RNAs should be established. In this review, microRNAs, long non-coding RNAs, and circular RNAs are studied in relation to DIC. Specifically, the axis between these non-coding RNAs and the corresponding affected pathway has been identified, including inflammation, alteration of the coagulation cascade, and endothelial damage. The main affected pathway identified is PI3K/AKT/mTOR axis, where several ncRNAs participate in its regulation, including miR-122-5p which is sponged by circ_0005963, ciRS-122, and circPTN, and miR-19a-3p which is modulated by circ_0000096 and circ_0063425. Additionally, both miR-223 and miR-24 were found to affect the PI3K/AKT pathway and were regulated by lncGAS5 and lncKCNQ1OT1, respectively. Thus, this work provides a useful pipeline of inter-connected ncRNAs that future research on their impact on DIC can further explore.

Potential Predictive Value of miR-125b-5p, miR-155-5p and Their Target Genes in the Course of COVID-19

Purpose

This study aimed to provide new biomarkers for predicting the disease course of COVID-19 by analyzing the dynamic changes of microRNA (miRNA) and its target gene expression in the serum of COVID-19 patients at different stages.

Methods

Serum samples were collected from all COVID-19 patients at three time points: the acute stage, the turn-negative stage, and the recovery stage. The expression level of miRNA and the target mRNA was measured by Quantitative Real-Time Polymerase Chain Reaction (RT-qPCR). The classification tree model was established to predict the disease course, and the prediction efficiency of independent variables in the model was analyzed using the receiver operating characteristic (ROC) curve.

Results

The expression of miR-125b-5p and miR-155-5p was significantly up-regulated in the acute stage and gradually decreased in the turn-negative and recovery stages. The expression of the target genes CDH5, STAT3, and TRIM32 gradually down-regulated in the acute, turn-negative, and recovery stages. MiR-125b-5p, miR-155-5p, STAT3, and TRIM32 constituted a classification tree model with 100% accuracy of prediction and AUC >0.7 for identification and prediction in all stages.

Conclusion

MiR-125b-5p, miR-155-5p, STAT3, and TRIM32 could be useful biomarkers to predict the time nodes of the acute, turn-negative, and recovery stages of COVID-19.