Identification of potential novel biomarkers for abdominal aortic aneurysm based on comprehensive analysis of circRNA-miRNA-mRNA networks

Pathogenetic Significance of Long Non-Coding RNAs in the Development of Thoracic and Abdominal Aortic Aneurysms

Aortic aneurysm (AA) is a life-threatening condition with a high prevalence and risk of severe complications. The aim of this review was to summarize the data on the role of long non-coding RNAs (lncRNAs) in the development of AAs of various location. Within less than a decade of studies on the role of lncRNAs in AA, using experimental and bioinformatic approaches, scientists have obtained the data confirming the involvement of these molecules in metabolic pathways and pathogenetic mechanisms critical for the aneurysm development. Regardless of the location of pathological process (thoracic or abdominal aorta), AA was found to be associated with changes in the expression of various lncRNAs in the tissue of the affected vessels. The consistency of changes in the expression level of lncRNA, mRNA and microRNA in aortic tissues during AA development has been recordedand regulatory networks implicated in the AA pathogenesis in which lncRNAs act as competing endogenous RNAs (ceRNA networks) have been identified. It was found that the same lncRNA can be involved in different ceRNA networks and regulate different biochemical and cellular events; on the other hand, the same pathological process can be controlled by different lncRNAs. Despite some similarities in pathogenesis and overlapping of involved lncRNAs, the ceRNA networks described for abdominal and thoracic AA are different. Interactions between lncRNAs and other molecules, including those participating in epigenetic processes, have also been identified as potentially relevant to the AA pathogenesis. The expression levels of some lncRNAs were found to correlate with clinically significant aortic features and biochemical parameters. Identification of regulatory RNAs functionally significant in the aneurysm development is important for clarification of disease pathogenesis and will provide a basis for early diagnostics and development of new preventive and therapeutic drugs.

Construction and analysis of competing endogenous RNA network and patterns of immune infiltration in abdominal aortic aneurysm

Background

Various studies have highlighted the role of circular RNAs (circRNAs) as critical molecular regulators in cardiovascular diseases, but its role in abdominal aortic aneurysm (AAA) is unclear. This study explores the potential molecular mechanisms of AAA based on the circRNA-microRNA (miRNA)-mRNA competing endogenous RNA (ceRNA) network and immune cell infiltration patterns.

Methods

The expression profiles of circRNAs (GSE144431) and mRNAs (GSE57691 and GSE47472) were obtained from the Gene Expression Omnibus (GEO). Then, the differentially expressed circRNAs (DEcircRNAs) and mRNAs (DEmRNAs) between AAA patients and healthy control samples, and the target miRNAs of these DEmRNAs and DEcircRNAs were identified. Based on the miRNA-DEmRNAs and miRNA-DEcircRNAs pairs, the ceRNA network was constructed. Furthermore, the proportion of the 22 immune cell types in AAA patients was assessed using cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm. The expressions of key genes and immune cell infiltration were validated using clinical specimens.

Results

A total of 214 DEmRNAs were identified in the GSE57691 and GSE47472 datasets, and 517 DEcircRNAs were identified in the GSE144431 dataset. The ceRNA network included 19 circRNAs, 36 mRNAs, and 68 miRNAs. Two key genes, PPARG and FOXO1, were identified among the hub genes of the established protein-protein interaction between mRNAs in the ceRNA network. Moreover, seven types of immune cells were differentially expressed between AAA patients and healthy control samples. Hub genes in ceRNA, such as FOXO1, HSPA8, and RAB5C, positively correlated with resting CD4 memory T cells or M1 macrophages, or both.

Conclusion

In conclusion, a ceRNA interaction axis was constructed. The composition of infiltrating immune cells was analyzed in the abdominal aorta of AAA patients and healthy control samples. This may help identify potential therapeutic targets for AAA.

Circulating microRNAs in patients with aneurysmal dilatation of coronary arteries

To understand the mechanism underlying coronary artery abnormal dilatation (CAAD), the present study identified and compared the expression of circulating microRNAs (miRNAs) in three groups of patients. Group 1 included 20 patients with CAAD, Group 2 included 20 patients with angiographically confirmed coronary artery disease (CAD), and Group 3 included 20 patients with normal coronary arteries (control). miRNAs were isolated from plasma samples and were profiled using PCR arrays and miRCURY LNA Serum/Plasma Focus PCR Panels. The present study demonstrated that the plasma miRNA levels were significantly different in Group 1 compared with in Group 2 and Group 3 (fold change >2 and P<0.05). The comparison of Group 1 with Group 3 identified 21 significantly upregulated and two downregulated miRNAs in patients with CAAD compared with in the control group. Moreover, six upregulated and two downregulated miRNAs were identified in patients with CAD compared with in the controls. The third comparison revealed four upregulated and three downregulated miRNAs in Group 1, when compared with patients with CAD. In conclusion, the present study identified a specific signature of plasma miRNAs, which were upregulated and downregulated in patients with CAAD compared with in patients with CAD and control individuals.

Integrative analysis identifies key genes related to metastasis and a robust gene-based prognostic signature in uveal melanoma

PURPOSE

Uveal melanoma (UM) is an aggressive intraocular malignancy, leading to systemic metastasis in half of the patients. However, the mechanism of the high metastatic rate remains unclear. This study aimed to identify key genes related to metastasis and construct a gene-based signature for better prognosis prediction of UM patients.

METHODS

Weighted gene co-expression network analysis (WGCNA) was used to identify the co-expression of genes primarily associated with metastasis of UM. Univariate, Lasso-penalized and multivariate Cox regression analyses were performed to establish a prognostic signature for UM patients.

RESULTS

The tan and greenyellow modules were significantly associated with the metastasis of UM patients. Significant genes related to the overall survival (OS) in these two modules were then identified. Additionally, an OS-predicting signature was established. The UM patients were divided into a low- or high-risk group. The Kaplan-Meier curve indicated that high-risk patients had poorer OS than low-risk patients. The receiver operating curve (ROC) was used to validate the stability and accuracy of the final five-gene signature. Based on the signature and clinical traits of UM patients, a nomogram was established to serve in clinical practice.

CONCLUSIONS

We identified key genes involved in the metastasis of UM. A robust five-gene-based prognostic signature was constructed and validated. In addition, the gene signature-based nomogram was created that can optimize the prognosis prediction and identify possible factors causing the poor prognosis of high-risk UM patients.