Abstract:Background: Hepatocellular carcinoma (HCC) accounts for the majority of liver cancer, with the incidence and mortality rates increasing every year. Despite the improvement of clinical management, substantial challenges remain due to its high recurrence rates and short survival period. This study aimed to identify potential diagnostic and prognostic biomarkers in HCC through bioinformatic analysis.Methods: Datasets from GEO and TCGA databases were used for the bioinformatic analysis. Gene Ontology (GO) and Kyot… Show more
“…Accumulating evidence indicates that ceRNA regulatory networks play a role in the biological processes of HCC development, such as proliferation, metastasis, epithelial-to-mesenchymal transition (EMT), and chemoresistance [30] . In our study, we by performed sequencing analysis and constructed a total of 5 ceRNA network maps of highly expressed circRNAs that included 5 circRNAs, 15 miRNAs, and 278 mRNAs.…”
Objective
An increasing number of circular RNAs (circRNAs) have been identified as emerging competing endogenous RNAs (ceRNAs) that play important roles in hepatocellular carcinoma (HCC), but numerous circRNAs remain unexplored. The aim of this study was to explore the mechanism of action of differentially expressed circRNAs and their ceRNA networks in HCC.
Methods
Second-generation sequencing technology was used to analyse the expression of circRNAs in cancerous and paired paraneoplastic tissues from five patients with HCC. The circRNAs with a P value of less than 0.01, with an original signal value greater than 100 and ranked among the top ten upregulated circRNAs were selected and validated by quantitative reverse transcription polymerase chain reaction (qRT‒PCR) in paired cancer and paraneoplastic tissues from another 34 HCC patients. The downstream miRNAs and mRNAs of the circRNAs were explored through database analysis, and finally, the ceRNA networks and circRNA–miRNA–mRNA axes based on these ten circRNAs were constructed.
Results
By sequencing, we identified 9658 differentially expressed circRNAs on all chromosomes, of which 3862 were significantly upregulated and 5796 were significantly downregulated. RT-qPCR was performed to validate the top ten upregulated circRNAs, and the results were generally consistent with the sequencing results. After qRT‒PCR validation, five circRNAs (hsa_circ_0079875, hsa_circ0091580, hsa_circ0091581, hsa_circ0004788 and hsa_circ_0059730) were selected for further analysis. First, the downstream miRNAs and mRNAs of these five circRNAs were predicted to construct circRNA-miRNA‒mRNA network diagrams. The 1482 upregulated mRNAs identified in the GEPIA database overlapped with the 278 mRNAs in the ceRNA networks, and 14 overlapping genes were identified. Further bioinformatics analysis revealed four mRNAs (ADSL, AP3B1, MAPRE1, and TRNP1) and five circRNA–miRNA–mRNA axes that were negatively correlated with HCC prognosis.
Conclusions
Numerous differentially expressed circRNAs exist in HCC, and most can regulate the biological behaviour of HCC through circRNA-miRNA‒mRNA networks. Bioinformatics analysis showed that the ceRNA regulatory axes in HCC have high diagnostic and prognostic value and deserve further exploration. This study aims to provide new research ideas related to HCC pathogenesis and treatment options.
“…Accumulating evidence indicates that ceRNA regulatory networks play a role in the biological processes of HCC development, such as proliferation, metastasis, epithelial-to-mesenchymal transition (EMT), and chemoresistance [30] . In our study, we by performed sequencing analysis and constructed a total of 5 ceRNA network maps of highly expressed circRNAs that included 5 circRNAs, 15 miRNAs, and 278 mRNAs.…”
Objective
An increasing number of circular RNAs (circRNAs) have been identified as emerging competing endogenous RNAs (ceRNAs) that play important roles in hepatocellular carcinoma (HCC), but numerous circRNAs remain unexplored. The aim of this study was to explore the mechanism of action of differentially expressed circRNAs and their ceRNA networks in HCC.
Methods
Second-generation sequencing technology was used to analyse the expression of circRNAs in cancerous and paired paraneoplastic tissues from five patients with HCC. The circRNAs with a P value of less than 0.01, with an original signal value greater than 100 and ranked among the top ten upregulated circRNAs were selected and validated by quantitative reverse transcription polymerase chain reaction (qRT‒PCR) in paired cancer and paraneoplastic tissues from another 34 HCC patients. The downstream miRNAs and mRNAs of the circRNAs were explored through database analysis, and finally, the ceRNA networks and circRNA–miRNA–mRNA axes based on these ten circRNAs were constructed.
Results
By sequencing, we identified 9658 differentially expressed circRNAs on all chromosomes, of which 3862 were significantly upregulated and 5796 were significantly downregulated. RT-qPCR was performed to validate the top ten upregulated circRNAs, and the results were generally consistent with the sequencing results. After qRT‒PCR validation, five circRNAs (hsa_circ_0079875, hsa_circ0091580, hsa_circ0091581, hsa_circ0004788 and hsa_circ_0059730) were selected for further analysis. First, the downstream miRNAs and mRNAs of these five circRNAs were predicted to construct circRNA-miRNA‒mRNA network diagrams. The 1482 upregulated mRNAs identified in the GEPIA database overlapped with the 278 mRNAs in the ceRNA networks, and 14 overlapping genes were identified. Further bioinformatics analysis revealed four mRNAs (ADSL, AP3B1, MAPRE1, and TRNP1) and five circRNA–miRNA–mRNA axes that were negatively correlated with HCC prognosis.
Conclusions
Numerous differentially expressed circRNAs exist in HCC, and most can regulate the biological behaviour of HCC through circRNA-miRNA‒mRNA networks. Bioinformatics analysis showed that the ceRNA regulatory axes in HCC have high diagnostic and prognostic value and deserve further exploration. This study aims to provide new research ideas related to HCC pathogenesis and treatment options.
“…It is well known that ncRNAs account for the majority of the human transcriptome, including miRNAs, lncRNAs, and circRNAs. MicroRNAs are single-stranded RNAs and participate in a series of physiological and pathological processes by facilitating post-transcriptional regulation of the target genes [ 76 ]. Numerous abnormally expressing miRNAs are associated with HCC initiation and progression [ 76 , 77 ].…”
Section: Characteristics and Classification Of Rnasmentioning
confidence: 99%
“…MicroRNAs are single-stranded RNAs and participate in a series of physiological and pathological processes by facilitating post-transcriptional regulation of the target genes [ 76 ]. Numerous abnormally expressing miRNAs are associated with HCC initiation and progression [ 76 , 77 ]. Various studies have exposed the biological roles of lncRNAs as regulators of transcription, modulators of mRNA processing, and organizers of nuclear domains [ 76 , 77 , 78 , 79 ].…”
Section: Characteristics and Classification Of Rnasmentioning
confidence: 99%
“…Numerous abnormally expressing miRNAs are associated with HCC initiation and progression [ 76 , 77 ]. Various studies have exposed the biological roles of lncRNAs as regulators of transcription, modulators of mRNA processing, and organizers of nuclear domains [ 76 , 77 , 78 , 79 ]. Compared with linear RNAs, circRNAs are more stable to exonuclease and ribonuclease, with conserved structure and stable sequence and tissue specificity [ 78 , 79 ].…”
Section: Characteristics and Classification Of Rnasmentioning
Hepatocellular carcinoma (HCC) is the most common and serious type of primary liver cancer. HCC patients have a high death rate and poor prognosis due to the lack of clear signs and inadequate treatment interventions. However, the molecular pathways that underpin HCC pathogenesis remain unclear. Long non-coding RNAs (lncRNAs), a new type of RNAs, have been found to play important roles in HCC. LncRNAs have the ability to influence gene expression and protein activity. Dysregulation of lncRNAs has been linked to a growing number of liver disorders, including HCC. As a result, improved understanding of lncRNAs could lead to new insights into HCC etiology, as well as new approaches for the early detection and treatment of HCC. The latest results with respect to the role of lncRNAs in controlling multiple pathways of HCC were summarized in this study. The processes by which lncRNAs influence HCC advancement by interacting with chromatin, RNAs, and proteins at the epigenetic, transcriptional, and post-transcriptional levels were examined. This critical review also highlights recent breakthroughs in lncRNA signaling pathways in HCC progression, shedding light on the potential applications of lncRNAs for HCC diagnosis and therapy.
“…Long non-coding RNAs (lncRNAs) are a class of non-coding RNAs more than 200 nucleotides in length. LncRNAs can act as competing endogenous RNA (ceRNA) that sponges and blocks the effect of miRNAs, a class of ncRNA that suppresses target genes expression at their translational level by binding to their 3′ untranslated regions (3′ UTR) [ 9 ]. Furthermore, lncRNAs could interact with DNA, RNA, protein molecules and/or their complexes, acting as an essential regulator in transcriptional, post-transcriptional, and chromatin remodeling regulations [ 10 ].…”
Long non-coding RNAs (lncRNAs) are critical regulators in various biological processes involved in the hallmarks of cancer. Maternally expressed gene 3 (MEG3) is lncRNA that regulates target genes through transcription, translation, post-translational modification, and epigenetic regulation. MEG3 has been known as a tumor suppressor, and its downregulation could be found in various cancers. Furthermore, clinical studies revealed that impaired MEG3 expression is associated with poor prognosis and drug resistance. MEG3 exerts its tumor suppressive effect by suppressing various cancer hallmarks and preventing cells from acquiring cancer-specific characteristics; as it could suppress tumor cells proliferation, invasion, metastasis, and angiogenesis; it also could promote tumor cell death and regulate tumor cell metabolic reprogramming. Hence, MEG3 is a potential prognostic marker, and overexpressing MEG3 might become a potential antitumor therapeutic strategy. Herein, we summarize recent knowledge regarding the role of MEG3 in regulating tumor hallmarks as well as the underlying molecular mechanisms. Furthermore, we also discuss the clinical importance of MEG3, as well as their potential in tumor prognosis and antitumor therapeutic strategies.
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