LncRNA OIP5-AS1 Signatures as a Biomarker of Gestational Diabetes Mellitus and a Regulator on Trophoblast Cells

LncRNA OIP5-AS1 mediated miR-28-5p provides promising support for the diagnosis and prognosis of cholangiocarcinoma

BACKGROUND

Long non-coding RNAs (lncRNAs) are major research factors in a variety of diseases, and lncRNA OIP5-AS1 (OIP5-AS1) was shown to mediate the progression of various tumors. This paper discusses how OIP5-AS1 could potentially be used for diagnosing and prognosticating cholangiocarcinoma (CHOL).

METHODS

The ENROCI project evaluated the OIP5-AS1 expression in CHOL samples and confirmed it using RT-qPCR. A bioinformatics database predicted the target gene of OIP5-AS1 in CHOL, which was then confirmed by luciferase activity assays. The CCK-8 and Transwell methods were employed to detect the changes in CHOL cell growth and migration levels after OIP5-AS1 knockdown. ROC and Kaplan-Meier curves were plotted to examine the diagnostic and prognostic functions of OIP5-AS1.

RESULTS

In CHOL tissues and cells, OIP5-AS1 was enhanced compared to the controls. Reducing OIP5-AS1 hampered the regulatory capacity of CHOL cells, and miR-28-5p inhibitor repaired this inhibition. Notably, OIP5-AS1 was observed to sponge and downregulate miR-28-5p, exhibiting high sensitivity and specificity (84.4% and 81.3%) in CHOL. G3BP1 was a direct target of miR-28-5p. Decreased OIP5-AS1 level was beneficial for survival (HR = 2.391, P = 0.024).

CONCLUSION

OIP5-AS1 targets and negatively mediates miR-28-5p/G3BP1 axis to promote the activity of CHOL cells, which may be a potential marker for diagnosis and prognosis of CHOL patients.

The Value of lncRNAs as a Biomarker for the Diagnosis of Gestational Diabetes: A Meta-Analysis

Gestational diabetes mellitus (GDM) is a common metabolic disorder in pregnancy and leads to serious harm to the mother and the fetus. A variety of lncRNAs play a key role in GDM. This meta-analysis was performed to explore the potential value of lncRNAs in GDM diagnosis. Articles correlated with lncRNA and GDM were screened from Embase, Medline, EBSCO, PubMed, Chinese National Knowledge Infrastructure, and WanFang databases. Summary receiver operator characteristic (SROC) was performed to evaluate the pooled area under curve (AUC). Forest plot was conducted to calculate the sensitivity, specificity, diagnostic likelihood ratio (LR), diagnostic score, and diagnostic odds ratio (DOR). Deeks' funnel plot was utilized to evaluate the publication bias. Eleven articles containing 12 tests (1060 GDM patients and 1066 controls) were included in this meta-analysis. AUC (0.89, 95%CI=0.86-0.92), sensitivity (0.84, 95%CI=0.80-0.87), and specificity (0.81, 95%CI=0.77-0.85)of the SROC curve showed a high diagnostic value of lncRNA for GDM. Positive LR (PLR 4.40, 95%CI=3.45-5.60) and negative LR (NLR 0.20, 95%CI=0.15-0.26) results indicated that the diagnosis of lncRNA for GDM had low clinical utility. Diagnostic score (3.09, 95%CI=2.62-3.57) and DOR (22.04, 95%CI=13.68-35.51) results suggested lncRNAs have good discriminative effect on GDM. Heterogeneity was significantly higher, but not induced by the subgroups. LncRNAs had high diagnostic value and good discriminative effect for GDM, but the clinical utility was not high. This meta-analysis study offers a potential target for GDM diagnosis.

The role of ncRNA regulatory mechanisms in diseases-case on gestational diabetes

Non-coding RNAs (ncRNAs) are a class of RNA molecules that do not have the potential to encode proteins. Meanwhile, they can occupy a significant portion of the human genome and participate in gene expression regulation through various mechanisms. Gestational diabetes mellitus (GDM) is a pathologic condition of carbohydrate intolerance that begins or is first detected during pregnancy, making it one of the most common pregnancy complications. Although the exact pathogenesis of GDM remains unclear, several recent studies have shown that ncRNAs play a crucial regulatory role in GDM. Herein, we present a comprehensive review on the multiple mechanisms of ncRNAs in GDM along with their potential role as biomarkers. In addition, we investigate the contribution of deep learning-based models in discovering disease-specific ncRNA biomarkers and elucidate the underlying mechanisms of ncRNA. This might assist community-wide efforts to obtain insights into the regulatory mechanisms of ncRNAs in disease and guide a novel approach for early diagnosis and treatment of disease.

Non-coding RNAs in diabetes mellitus and diabetic cardiovascular disease

More than 10% of the world's population already suffers from varying degrees of diabetes mellitus (DM), but there is still no cure for the disease. Cardiovascular disease (CVD) is one of the most common and dangerous of the many health complications that can be brought on by DM, and has become the leading cause of death in people with diabetes. While research on DM and associated CVD is advancing, the specific mechanisms of their development are still unclear. Given the threat of DM and CVD to humans, the search for new predictive markers and therapeutic ideas is imminent. Non-coding RNAs (ncRNAs) have been a popular subject of research in recent years. Although they do not encode proteins, they play an important role in living organisms, and they can cause disease when their expression is abnormal. Numerous studies have observed aberrant ncRNAs in patients with DM complications, suggesting that they may play an important role in the development of DM and CVD and could potentially act as biomarkers for diagnosis. There is additional evidence that treatment with existing drugs for DM, such as metformin, alters ncRNA expression levels, suggesting that regulation of ncRNA expression may be a key mechanism in future DM treatment. In this review, we assess the role of ncRNAs in the development of DM and CVD, as well as the evidence for ncRNAs as potential therapeutic targets, and make use of bioinformatics to analyze differential ncRNAs with potential functions in DM.

Circulating non-coding RNAs as biomarkers in coronary artery disease

Coronary artery disease (CAD) is a leading cause of mortality worldwide. Atherosclerosis involves an interplay of different pathological mechanisms, such as progressive inflammation, abnormal lipid metabolism, and oxidative stress, and as such represents the basic pathological phenomenon underlying CAD. Atherosclerotic plaque narrows the lumen of coronary arteries, creating an ischemic environment for the heart muscle, which finally leads to clinical complications, such as acute myocardial infarction. Currently, there are no biomarkers that could predict plaque stability or major adverse cardiovascular events (MACE). Numerous functional non-coding RNA (ncRNA) species influence basic cellular functions, and as such play a role in the development and progression of CAD. Of these ncRNAs, micro RNAs (miRNAs) and long non-coding RNAs (lncRNAs) are the most investigated. Considering that ncRNAs detected in extracellular fluids can originate from different cells, circulating ncRNAs are being intensively investigated as potential biomarkers in the diagnosis and prognosis of CAD. In the following paper, we provide current insights into potential molecular mechanisms by which miRNAs and lncRNAs contribute to the pathology of CAD and discuss their potential role as biomarkers in diagnosis and prognosis of disease.