Plasma Circular RNAs hsa_circ_0001953 and hsa_circ_0009024 as Diagnostic Biomarkers for Active Tuberculosis

Su, Rigu; Qing, Cheng; Peng, Yingquan; Luo, Qing; Li, Junming

doi:10.3389/fmicb.2018.02010

Cited by 42 publications

(35 citation statements)

References 39 publications

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“…[22][23][24][25][26][27] Given these observations about their disease-related functions, and in light of both their strong biological stability and their widespread presence in blood, it is not surprising that there are many recently reported and ongoing efforts to develop new diagnostics technologies based on the use of circRNAs as biomarkers (eg, in diagnosing hepatocellular carcinoma, epithelial ovarian cancer, and active tuberculosis). [28][29][30] Here, aiming to identify potential CAP-related cir-cRNAs in the peripheral blood for use as diagnostic biomarkers, we used microarrays to profile an initial discovery cohort of CAP patients (n = 6) and matched controls (n = 6). Subsequently, using samples from a much larger independent validation cohort (30 patients vs 30 controls), we validated the differentially accumulated circRNAs from the array analysis using quantitative polymerase chain reaction (qPCR) and ultimately identified an extremely informative panel of circRNA biomarkers present in peripheral blood that perform well as sensitive and specific biomarkers for diagnosing CAP.…”

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confidence: 99%

Blood circRNAs as biomarkers for the diagnosis of community‐acquired pneumonia

Zhao¹,

Zheng

Hao³

et al. 2019

J of Cellular Biochemistry

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Circular RNAs (circRNAs) have been reported as effective diagnostic and therapeutic biomarkers in many diseases, but the potential of using this easy‐to‐monitor and highly stable materials for diagnosing Community‐acquired pneumonia (CAP) remains unexplored. Here, aiming to identify potential CAP‐related circRNAs in peripheral blood and seeking to deepen the understanding of how circRNA‐miRNA‐mRNA regulatory networks may contribute to CAP, we applied microarrays profiling analysis and identified 8296 differentially expressed (DE) circRNAs between patients with CAP (n = 6) and healthy controls (n = 6). Subsequently, we validated the accumulation trends for the top 100 DE circRNAs based on qPCR in an independent validation cohort (30 patients vs 30 controls), and ultimately identified a panel of four circRNAs that perform extremely well as sensitive and specific biomarkers for diagnosing CAP: hsa_circ_0018429 (area under the curve [AUC] = 0.8216), hsa_circ_0026579 (AUC = 0.7733), hsa_circ_0125357 (AUC = 0.7730), and hsa_circ_0099188 (AUC = 0.6978); combined as a panel (AUC = 0.8776). In addition, hsa_circ_0026579 exhibited good performance in differentiating viral from bacterial or mixed infection, with an AUC of 0.863. We also identified 10 miRNAs that most likely to interact with these four circRNAs, and then predicted 205 mRNA target genes. The KEGG pathway enrichment analysis suggested highly plausible functional implications related to inflammation and to virus‐infection‐related signaling pathways (such as HTLV‐1 infection and hepatitis B infection). Thus, we generated a genetic network of potential CAP‐related regulatory interactions that should inform future hypothesis‐driven research into the causes and potential treatment of this widespread and frequently fatal disease.

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confidence: 99%

Blood circRNAs as biomarkers for the diagnosis of community‐acquired pneumonia

Zhao¹,

Zheng

Hao³

et al. 2019

J of Cellular Biochemistry

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“…Therefore, biological markers with satisfactory efficiency for early diagnosis and therapy are desperately needed. With the development of microarray technology, we are able to efficiently screen for changes in gene expression in lung adenocarcinoma, and this approach has been proven to be a very useful method for screening early stage biomarkers in both malignant and benign diseases (33)(34)(35).…”

Section: Discussionmentioning

confidence: 99%

Identification of lung adenocarcinoma biomarkers based on bioinformatic analysis and human samples

et al. 2020

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Lung adenocarcinoma is one of the most common malignant tumors worldwide. Although efforts have been made to clarify its pathology, the underlying molecular mechanisms of lung adenocarcinoma are still not clear. The microarray datasets GSE75037, GSE63459 and GSE32863 were downloaded from the Gene Expression Omnibus (GEO) database to identify biomarkers for effective lung adenocarcinoma diagnosis and therapy. The differentially expressed genes (DEGs) were identified by GEO2R, and function enrichment analyses were conducted using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO). The STRING database and Cytoscape software were used to construct and analyze the protein-protein interaction network (PPI). We identified 376 DEGs, consisting of 83 upregulated genes and 293 downregulated genes. Functional and pathway enrichment showed that the DEGs were mainly focused on regulation of cell proliferation, the transforming growth factor β receptor signaling pathway, cell adhesion, biological adhesion, and responses to hormone stimulus. Sixteen hub genes were identified and biological process analysis showed that these 16 hub genes were mainly involved in the M phase, cell cycle phases, the mitotic cell cycle, and nuclear division. We further confirmed the two genes with the highest node degree, DNA topoisomerase IIα (TOP2A) and aurora kinase A (AURKA), in lung adenocarcinoma cell lines and human samples. Both these genes were upregulated and associated with larger tumor size. Upregulation of AURKA in particular, was associated with lymphatic metastasis. In summary, identification of the DEGs and hub genes in our research enables us to elaborate the molecular mechanisms underlying the genesis and progression of lung adenocarcinoma and identify potential targets for the diagnosis and treatment of lung adenocarcinoma.

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“…Circ_103809 was weakly expressed in CRC and its elevation suppressed CRC cell growth, cell cycle process and metastasis and facilitated apoptosis via targeting miR-532-3p [20]. As a novel identified circRNA, circ_0003528 has been demonstrated to be upregulated in tuberculosis patients [21,22]. However, the effects of circSEC24A in CRC have not been addressed.…”

Section: Discussionmentioning

confidence: 99%

CircSEC24A promotes colorectal cancer progression by regulating miR-488-3p/TMEM106B axis

Hu¹,

Peng²,

Cao³

2020

Preprint

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Background: Currently, more and more circular RNAs (circRNAs) have been identified to exert their functions in tumor progression, including colorectal cancer (CRC). However, the role of circSEC24A (circ_0003528) in CRC remains unknown.Methods: Quantitative real-time polymerase chain reaction (qRT-PCR) was conducted to determine the levels of circSEC24A, SEC24A and microRNA-488-3p (miR-488-3p). The characterization of circSEC24A was investigated by Actinomycin D and RNase R digestion assays. 3-(4, 5-dimethyl-2-thiazolyl)-2, 5-diphenyl-2-H-tetrazolium bromide (MTT) assay was used to assess cell proliferation. Flow cytometry analysis was adopted for cell apoptosis and cell cycle process. Transwell assay was employed to evaluate cell migration and invasion. Western blot assay was performed to determine protein levels. Dual-luciferase reporter assay was utilized to explore the relationship between miR-488-3p and circSEC24A or transmembrane protein 106B (TMEM106B). Murine xenograft model was constructed to explore the effect of circSEC24A in vivo .Results: CircSEC24A level was increased in CRC tissues and cells. CircSEC24A deficiency impeded cell proliferation, cell cycle process, migration and invasion and induced apoptosis in CRC cells in vitro and blocked tumorigenesis in vivo . MiR-488-3p was a target of circSEC24A and miR-488-3p was downregulated in CRC tissues and cells. The inhibitory effect of circSEC24A silencing on CRC cell progression was restored by miR-488-3p inhibition. Moreover, TMEM106B could be negatively regulated by miR-488-3p via acting as a downstream gene of miR-488-3p. MiR-488-3p overexpression decelerated CRC cell progression by targeting TMEM106B.Conclusion: CircSEC24A facilitated CRC progression by regulating miR-488-3p/TMEM106B axis, which might provide a promising treatment approach for CRC.

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Plasma Circular RNAs hsa_circ_0001953 and hsa_circ_0009024 as Diagnostic Biomarkers for Active Tuberculosis

Cited by 42 publications

References 39 publications

Blood circRNAs as biomarkers for the diagnosis of community‐acquired pneumonia

Blood circRNAs as biomarkers for the diagnosis of community‐acquired pneumonia

Identification of lung adenocarcinoma biomarkers based on bioinformatic analysis and human samples

CircSEC24A promotes colorectal cancer progression by regulating miR-488-3p/TMEM106B axis

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