<p>Identification of circRNA-miRNA-mRNA Networks for Exploring the Fundamental Mechanism in Lung Adenocarcinoma</p>

Abstract

Background: Circular RNAs (circRNAs) were elucidated to act as competing endogenous RNAs (ceRNAs) and to play significant roles in cancer initiation and progression. We aimed to identify the important circRNAs in lung adenocarcinoma and intended to predict the functions of them via the bioinformatics analysis. Methods: We extracted data from three Gene Expression Omnibus (GEO) datasets, GSE101586, GSE101684, and GSE104854, and identified the common differentially expressed circRNAs. Agarose gel electrophoresis and Sanger sequencing were used to verify these significant circRNAs. Then, qRT-PCR was performed to validate the expression through matched tissues and cell lines. Afterwards, a ceRNA network was constructed and functional analysis was performed to predict the potential mechanisms of circRNAs. Results: Five circRNAs (hsa_circ_0072088, hsa_circ_0082564, hsa_circ_0008274, hsa_-circ_0000519 and hsa_circ_0003528) were identified differentially expressed in the three datasets. Following the Agarose gel electrophoresis and qRT-PCR validation, hsa_circ_0072088 and hsa_-circ_0008274 were chosen for further analysis. A ceRNA network of hsa_circ_0072088 and hsa_circ_0008274 was built based on the CSCD/TargetScan/MiRTarbase/StarBase 3.0. Then, the functional analysis showed that several meaningful terms were identified, such as "epithelial to mesenchymal transition (EMT)", "Cellular response to TGF-β stimulus", "MAPK signaling pathway", and "PI3K-AKT signaling pathway". Finally, several significant circRNA/miRNA/mRNA regulatory axes, which were predicted relating to cancer progress, were noted from the network. Conclusion: We identified significant circRNAs and meaningful circRNA-miRNA-mRNA networks to provide novel insight into pathogenesis and therapy of lung adenocarcinoma.

Construction and comprehensive analysis of a ceRNA network to reveal potential prognostic biomarkers for lung adenocarcinoma

“…Ten DEcircRNAs (5 upregulated and 5 downregulated) were signi cantly overlapped in two datasets, indicating important roles of circRNAs in LUAD. Moreover, hsa_circ_0000519 (circRNA-002178), hsa_circ_0072088 were identi ed, which were signi cantly upregulated in LUAD, and JunFeng Wang et al revealed that circRNA-002178 could act as a miRNA sponge to promote PDL1/PD1 expression in LUAD [35], Liming Liang et al con rmed that hsa_circ_0072088 were found differentially upregulated expression in LUAD with matched normal tissues by qRT-PCR with a P value < 0.05 [36]. However, circRNA-002178 was not in our ceRNA network based on our criteria (see methods).…”

Differential Expression and Bioinformatics Analysis of circRNA in Non-small Cell Lung Cancer

“…For example, Li et al (2020) used the same public datasets as this study, they took the union of GSE101586, GSE101684, and GSE11214 to identify differentially expressed circRNAs among NSCLC and healthy individuals for early diagnosis of NSCLC. Liang et al (2020) used the intersection of GSE101586, GSE101684 microarrays and GSE104854 high-throughput sequencing data to exploring the aberrant circRNAs and their potential molecular function in LUAD. Although the two GEO microarrays were same as ours, since high-throughput sequencing data and microarray data are different types, the results obtained by overlapping were different.…”

Construction and Analysis of a circRNA-Mediated ceRNA Network in Lung Adenocarcinoma

“…Although studies have reported the construction of circRNA-miRNA-mRNA regulatory networks in LUAD [17,18], the current understanding of circRNA-related ceRNA networks in LUAD is limited, and further study is needed. In this study, we identi ed a potential circRNA-miRNA-mRNA ceRNA regulatory network in LUAD.…”