RESUMO
Thyroid cancer (TC) is the most common endocrine cancer, accounting for 1.7% of all cancer cases. It has been reported that the existing approach to diagnosing TC is problematic. Therefore, it is essential to develop molecular biomarkers to improve the accuracy of the diagnosis. This study aimed to screen hub lncRNAs in the ceRNA network (ceRNET) connected to TC formation and progression based on the overall survival rate. In this study, first, RNA-seq data from the GDC database were collected. A package called edgeR in R programming language was then used to obtain differentially expressed lncRNAs (DElncRNAs), miRNAs (DEmiRNAs), and mRNAs (DEmRNAs) in TC patients' samples compared to normal samples. Second, DEmRNAs were analyzed for their functional enrichment. Third, to identify RNAs associated with overall survival, the overall survival of these RNAs was analyzed using the Kaplan-Meier plotter database to create a survival associated with the ceRNA network (survival-related ceRNET). Next, the GeneMANIA plugin was used to construct a PPI network to better understand survival-related DEmRNA interactions. The survival ceRNET was then visualized with the Cytoscape software, and hub genes, including hub lncRNAs and hub mRNAs, were identified using the CytoHubba plugin. We found 45 DElncRNAs, 28 DEmiRNAs, and 723 DEmRNAs among thyroid tumor tissue and non-tumor tissue samples. According to KEGG, GO and DO analyses, 723 DEmRNAs were mainly enriched in cancer-related pathways. Importantly, the results found that ten DElncRNAs, four DEmiRNAs, and 68 DEmRNAs are associated with overall survival. In this account, the PPI network was constructed for 68 survival-related DEmRNAs, and ADAMTS9, DTX4, and CLDN10 were identified as hub genes. The ceRNET was created by combining six lncRNAs, 109 miRNAs, and 22 mRNAs related to survival using Cytoscape. in this network, ten hub RNAs were identified by the CytoHubba plugin, including mRNAs (CTXND1, XKRX, IGFBP2, ENTPD1, GALNT7, ADAMTS9) and lncRNAs (AC090673.1, AL162511.1, LINC02454, AL365259.1). This study suggests that three lncRNAs, including AL162511.1, AC090673.1, and AL365259.1, could be reliable diagnostic biomarkers for TC. The findings of this study provide a basis for future studies on the therapeutic potential of these lncRNAs.
RESUMO
AIM: Chronic heart failure (CHF) can be classified as heart failure with preserved ejection fraction (HFpEF) or with reduced ejection fraction (HFrEF). Currently, there is an unmet need for a minimally invasive diagnostic tool for different forms of CHF. We aimed to investigate the diagnostic potential of circulating microRNAs (miRNAs) for the detection of different CHF forms via a systematic review and meta-analysis approach. METHODS AND RESULTS: Comprehensive search on Medline, Web of Science, Scopus, and EMBASE identified 45 relevant studies which were used for qualitative assessment. Out of these, 29 studies were used for qualitative and quantitative assessment and allowed to identify a miRNA panel able to detect HFrEF and HFpEF with areas under the curve (AUC) of 0.86 and 0.79, respectively. A panel of eight miRNAs (hsa-miR-18b-3p, hsa-miR-21-5p, hsa-miR-22-3p, hsa-miR-92b-3p, hsa-miR-129-5p, hsa-miR-320a-5p, hsa-miR-423-5p, and hsa-miR-675-5p) detected HFrEF cases with a sensitivity of 0.85, specificity of 0.88 and AUC of 0.91. A panel of seven miRNAs (hsa-miR-19b-3p, hsa-miR-30c-5p, hsa-miR-206, hsa-miR-221-3p, hsa-miR-328-5p, hsa-miR-375-3p, and hsa-miR-424-5p) identified HFpEF cases with a sensitivity of 0.82 and a specificity of 0.61. CONCLUSIONS: Although conventional biomarkers (N-terminal pro-B-type natriuretic peptide and B-type natriuretic peptide) presented a better performance in detecting CHF patients, the results presented here pointed towards specific miRNA panels with potential additive values to circulating natriuretic peptides in the diagnosis of different classes of CHF. Equally important, miRNAs alone showed a reasonable capacity for 'ruling out' patients with HFrEF or HFpEF. Additional studies with large populations are required to confirm the diagnostic potential of miRNAs for sub-classes of CHF.
