Long non‐coding RNA MYOSLID functions as a competing endogenous RNA to regulate MCL‐1 expression by sponging miR‐29c‐3p in gastric cancer

Han, Yong Chol; Wu, Nan; Jiang, Mingzuo; Chu, Yi; Wang, Zhiyang; Líu, Hao; Cao, Jiasheng; Liu, Harry; Xu, Bing; Xie, Xin

doi:10.1111/cpr.12678

Cited by 57 publications

(42 citation statements)

References 40 publications

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“…MYOSLID acts as a ceRNA of miR-29c-3p, causing de-repression of anti-apoptotic gene MCL-1. 62 MYOSLID was also defined as potential biomarker in head and neck squamous cell carcinoma, where it promotes invasion and metastasis by modulating the epithelialmesenchymal transition. 63 SOX21-AS1 has been linked to tumor progression and defined as a prognostic marker in cervical cancer, nephroblastoma, hepatocellular carcinoma, and lung and oral cancer.…”

Section: Discussionmentioning

confidence: 99%

Proneural and mesenchymal glioma stem cells display major differences in splicing and lncRNA profiles

et al. 2020

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Therapy resistance and recurrence in high-grade gliomas are driven by their populations of glioma stem cells (GSCs). Thus, detailed molecular characterization of GSCs is needed to develop more effective therapies. We conducted a study to identify differences in the splicing profile and expression of long non-coding RNAs in proneural and mesenchymal GSC cell lines. Genes related to cell cycle, DNA repair, cilium assembly, and splicing showed the most differences between GSC subgroups. We also identified genes distinctly associated with survival among patients of mesenchymal or proneural subgroups. We determined that multiple long noncoding RNAs with increased expression in mesenchymal GSCs are associated with poor survival of glioblastoma patients. In summary, our study established critical differences between proneural and mesenchymal GSCs in splicing profiles and expression of long non-coding RNA. These splicing isoforms and lncRNA signatures may contribute to the uniqueness of GSC subgroups, thus contributing to cancer phenotypes and explaining differences in therapeutic responses.

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Section: Discussionmentioning

confidence: 99%

Proneural and mesenchymal glioma stem cells display major differences in splicing and lncRNA profiles

et al. 2020

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“…We established a protein-protein interaction (PPI) network consisting of 165 nodes and 170 edges and identified 18 hub genes by MCODE plugin in Cytoscape. The 18 hub genes have been reported to be associated with gastric cancer, which are CCND2 [27] STAT3 [28], TP53 [29], MCL1 [30], MYC [31], FOXO1 [32], FOXO3 [33], BCL2L11 [34], GSK3B [35], CDKN1A [36], CDH1 [37], PTEN [38], MTOR [39], MAPK1 [40], CASP3, CDC42[41], SMAD4 [42] and IL6 [43]. All of them were predicted target genes for hsa-miR-197-3p, hsa-miR-451a, hsa-miR-136-5p, hsa-miR-337-3p, hsa-miR-654-3p, hsa-miR-182-5p, hsa-miR-1228-3p, hsa-miR-942-5p, hsa-miR-488-3p and hsa-miR-876-3p, and all these 10 miRNAs were predicted miRNAs for hsa_circ_0001013.…”

Section: Discussionmentioning

confidence: 99%

Construction of a circRNA-miRNA-mRNA network based on differentially co-expressed circular RNA in gastric cancer tissue and plasma by bioinformatics analysis

Gong¹,

Qi²,

Fu³

et al. 2020

Preprint

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Background: Increasing evidence implicates circular RNAs (circRNAs) have been involved in human cancer progression. However, the mechanism remains unclear. In this study, we identified novel circRNAs related to gastric cancer and constructed a circRNA-miRNA-mRNA network.Methods: Microarray dataset GSE83521 and GSE93541 were obtained from Gene Expression Omnibus (GEO). Then, we used computational biology to select differentially co-expressed circRNAs in GC tissue and plasma and detected the expression of selected circRNAs in gastric cell lines by quantitative real‑time polymerase chain reaction (qRT‑PCR). We also chose the candidate miRNAs and their target genes for circRNAs through online tools. Combining the predictions of miRNAs and target mRNAs, a competing endogenous RNA regulatory network was established. Functional and pathway enrichment analyses were performed, and interactions between proteins were predicted by using String and Cytoscape. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to elucidate the possible functions of these differentially expressed circRNAs.Results: The regulatory network constructed using the microarray datasets (GSE83521 and GSE93541) contained three differentially co-expressed circRNAs (DECs). A circRNA-miRNA-mRNA network was constructed based on 3 circRNAs, 43 miRNAs and 119 mRNAs. GO and KEGG analysis showed that regulation of apoptotic signaling pathway and PI3K−Akt signaling pathway were highest degrees of enrichment respectively. We established a protein-protein interaction (PPI) network consisting of 165 nodes and 170 edges and identified hub genes by MCODE plugin in Cytoscape. Furthermore, a core circRNA-miRNA-mRNA network was constructed base on hub genes. Hsa_circ_0001013 was finally determined to play an important role in the pathogenesis of GC according to the core circRNA-miRNA-mRNA network.Conclusions: We propose a new circRNA-miRNA-mRNA network associated with the pathogenesis of GC. The network may become a new molecular biomarker and be used to develop potential therapeutic strategies for gastric cancer.

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“…Competitive endogenous RNA (ceRNA) regulatory networks are significant mechanisms by which lncRNAs may exert huge influences on cancer. In the ceRNA networks, 15‐17 lncRNAs act as endogenous molecular sponges that competitively bind to miRNAs, 18 which indirectly regulate the expression level of messenger RNA (mRNA). Numerous experiments have demonstrated that this miRNA‐regulated lncRNA and mRNA network is involved in the development, progression, and invasion of cancer 19 .…”

Section: Introductionmentioning

confidence: 99%

A ceRNA network and a potential regulatory axis in gastric cancer with different degrees of immune cell infiltration

Zhang

et al. 2020

Cancer Science

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Immune cell infiltration is an important indicator of whether tumor patients will benefit from immunotherapy. Gastric cancer is one of the most common tumors in the world, and new indicators of immunotherapy are urgently needed. The aim of this study was to construct ceRNA networks in gastric cancer with different degrees of immune cell infiltration. We analyzed the expression profiles of different gastric cancer with different degrees of immune cell infiltration retrieved from The Cancer Genome Atlas (TCGA) database and found differentially expressed lncRNAs, mRNAs, and miRNAs. A ceRNA regulatory network of gastric cancer with different degrees of immune cell infiltration was constructed using functional annotation, RNA‐RNA interaction prediction, correlation analysis, survival analysis, and other comprehensive bioinformatics methods. The interaction and correlation between ceRNAs were verified using experiments on tumor tissues and cell lines. Cell line experiments showed a potential RP11‐1094M14.8/miR‐1269a/CXCL9 axis that was consistent with the ceRNA theory. qRT‐PCR results showed that RP11‐1094M14.8 knockdown significantly reduced the expression of CXCL9, and RP11‐1094M14.8 overexpression had the opposite effect. The results of clinical analysis of gastric cancer samples showed that RP11‐1094M14.8 and CXCL9 were highly expressed in hot tumors, and CXCL9 was positively correlated with a better prognosis for patients. The constructed novel ceRNA network and the potential regulatory axis may provide a comprehensive understanding of the potential mechanisms of development in gastric cancer with different degrees of immune cell infiltration. The RP11‐1094M14.8/miR‐1269a/CXCL9 axis may serve as a potential immune‐therapeutic target for gastric cancer with different degrees of immune cell infiltration.

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Long non‐coding RNA MYOSLID functions as a competing endogenous RNA to regulate MCL‐1 expression by sponging miR‐29c‐3p in gastric cancer

Cited by 57 publications

References 40 publications

Proneural and mesenchymal glioma stem cells display major differences in splicing and lncRNA profiles

Proneural and mesenchymal glioma stem cells display major differences in splicing and lncRNA profiles

Construction of a circRNA-miRNA-mRNA network based on differentially co-expressed circular RNA in gastric cancer tissue and plasma by bioinformatics analysis

A ceRNA network and a potential regulatory axis in gastric cancer with different degrees of immune cell infiltration

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