Definition and review on a category of long non-coding RNA: Atherosclerosis-associated circulating lncRNA (ASCLncRNA)

The prognostic potential of long noncoding RNA XIST in cardiovascular diseases: a review

There is a significant mortality rate associated with cardiovascular disease despite advances in treatment. long Non-coding RNAs (lncRNAs) play a critical role in many biological processes and their dysregulation is associated with a wide range of diseases in which their downstream pathways are disrupted. A lncRNA X-inactive specific transcript (XIST) is well known as a factor that regulates the physiological process of chromosome dosage compensation for females. According to recent studies, lncRNA XIST is involved in a variety of cellular processes, including apoptosis, proliferation, invasion, metastasis, oxidative stress and inflammation, through molecular networks with microRNAs and their downstream targets in neoplastic and non-neoplastic diseases. Because these cellular processes play a role in the pathogenesis of cardiovascular diseases, we aim to investigate the role that lncRNA XIST plays in this process. Additionally, we wish to determine whether it is a prognostic factor or a potential therapeutic target in these diseases.

The Lnc-RNA APPAT Suppresses Human Aortic Smooth Muscle Cell Proliferation and Migration by Interacting With MiR-647 and FGF5 in Atherosclerosis

PURPOSE

LncRNA-Atherosclerotic plaque pathogenesis-associated transcript (APPAT) could be detected in circulating blood and has been demonstrated to correlate with the development of atherosclerosis in our previous work. It could be a potential noninvasive biomarker for earlier diagnoses of clinical cardiovascular disease. Moreover, the expression of miR-647 increased in ox-LDL-treated vascular smooth muscle cells and peripheral blood of patients with coronary heart disease. A negative correlation between APPAT and miR-647 was confirmed, and FGF5 was screened as molecular target of miR-647. However, it is largely unclear how APPAT, miR-647, and FGF5 interact and function in disease development. Here, we aim to explore the underlying molecular mechanism in this progression.

MATERIALS AND METHODS

APPAT, miR-647, and FGF5 expression levels were detected by quantitative reverse transcription polymerase chain reaction; cell proliferation was detected by EdU incorporation assay; cell migration was detected by wound-healing assay; the molecular interaction of APPAT/FGF5 with miR-647 was verified by dual-luciferase reporter assay; the western blot was performed to determine the gene expression at protein levels; subcellular localizations of APPAT and miR-647 were observed by fluorescence in situ hybridization; cytosolic and nucleus fractionation assay was performed to further detect the distribution of miR-647.

RESULTS

APPAT and miR-647 have inverse effects on human aortic smooth muscle cells' (HASMCs) proliferation and migration. APPAT negatively regulated the cell activity, whereas miR-647 did it in a positive way (p<0.05). Three pairs of molecular interplay were found: mutual negative regulation between APPAT and miR-647, APPAT downregulated FGF5, miR-647 regulation on FGF5 (p<0.05). Subcellular location assay confirmed the molecular interaction of APPAT and miR-647.

CONCLUSIONS

APPAT could suppress the migration and proliferation of ox-LDL-treated HASMCs via interacting with miR-647 and FGF5. We revealed a nontypical competing endogenous RNA mechanism of long noncoding RNA in the progression of atherosclerosis.

An autophagy-related long non-coding RNA prognostic model and related immune research for female breast cancer

Introduction

Breast cancer (BRCA) is the most common malignancy among women worldwide. It was widely accepted that autophagy and the tumor immune microenvironment play an important role in the biological process of BRCA. Long non-coding RNAs (lncRNAs), as vital regulatory molecules, are involved in the occurrence and development of BRCA. The aim of this study was to assess the prognosis of BRCA by constructing an autophagy-related lncRNA (ARlncRNA) prognostic model and to provide individualized guidance for the treatment of BRCA.

Methods

The clinical data and transcriptome data of patients with BRCA were acquired from the Cancer Genome Atlas database (TCGA), and autophagy-related genes were obtained from the human autophagy database (HADb). ARlncRNAs were identified by conducting co‑expression analysis. Univariate and multivariate Cox regression analysis were performed to construct an ARlncRNA prognostic model. The prognostic model was evaluated by Kaplan-Meier survival analysis, plotting risk curve, Independent prognostic analysis, clinical correlation analysis and plotting ROC curves. Finally, the tumor immune microenvironment of the prognostic model was studied.

Results

10 ARlncRNAs(AC090912.1, LINC01871, AL358472.3, AL122010.1, SEMA3B-AS1, BAIAP2-DT, MAPT-AS1, DNAH10OS, AC015819.1, AC090198.1) were included in the model. Kaplan-Meier survival analysis of the prognostic model showed that the overall survival(OS) of the low-risk group was significantly better than that of the high-risk group (p< 0.001). Multivariate Cox regression analyses suggested that the prognostic model was an independent prognostic factor for BRCA (HR = 1.788, CI = 1.534-2.084, p < 0.001). ROCs of 1-, 3- and 5-year survival revealed that the AUC values of the prognostic model were all > 0.7, with values of 0.779, 0.746, and 0.731, respectively. In addition, Gene Set Enrichment Analysis (GSEA) suggested that several tumor-related pathways were enriched in the high-risk group, while several immune‑related pathways were enriched in the low-risk group. Patients in the low-risk group had higher immune scores and their immune cells and immune pathways were more active. Patients in the low-risk group had higher PD-1 and CTLA-4 levels and received more benefits from immune checkpoint inhibitors (ICIs) therapy.

Discussion

The ARlncRNA prognostic model showed good performance in predicting the prognosis of patients with BRCA and is of great significance to guide the individualized treatment of these patients.

LncRNA UCA1, miR-26a, and miR-195 in coronary heart disease patients: Correlation with stenosis degree, cholesterol levels, inflammatory cytokines, and cell adhesion molecules

Background

Long noncoding RNA urothelial cancer‐associated 1 (lnc‐UCA1) targets microRNA‐26a (miR‐26a) and microRNA‐195 (miR‐195) to participate in coronary heart disease (CHD) progression via regulation of vascular smooth muscle cell and microvascular endothelial cell viability and mobility. Therefore, this study set out to further explore the relationship between lnc‐UCA1 and miR‐26a and miR‐195, along with their roles in the management of patients with CHD.

Methods

One hundred and thirty‐six CHD patients and 70 age‐/gender‐matched controls were recruited in this case‐control study. Their peripheral blood mononuclear cell samples were collected for lnc‐UCA1, miR‐26a, and miR‐195 measurement. Furthermore, serum samples from CHD patients were obtained for inflammatory cytokines and cell adhesion molecules measurement. The Gensini score was used to evaluate the stenosis severity in CHD patients.

Results

Lnc‐UCA1 expression tend to be increased, while miR‐26a and miR‐195 expressions were reduced in patients with CHD compared to that of controls (all p < 0.001). In CHD patients, lnc‐UCA1 was negatively correlated with miR‐26a (p < 0.001) and miR‐195 (p = 0.014). Besides, lnc‐UCA1 was positively correlated with Gensini score (p < 0.001), total cholesterol (p = 0.019), low‐density lipoprotein cholesterol (p = 0.002), and C‐reactive protein (p < 0.001), while miR‐26a (p < 0.001) and miR‐195 (p = 0.002) were negatively correlated with Gensini score. What's more, lnc‐UCA1 was positively correlated with tumor necrosis factor (TNF)‐α (p = 0.004), interleukin (IL)‐1β (p = 0.041), vascular cell adhesion molecule‐1 (VCAM‐1) (p = 0.010), and intercellular adhesion molecule‐1 (ICAM‐1) (p < 0.001). While miR‐26a was negatively correlated with some of the individual inflammatory cytokines and cell adhesion molecules.

Conclusion

Lnc‐UCA1, miR‐26a, and miR‐195 may serve as potential biomarkers for CHD management.