Circular RNA hsa_circ_0005114‑miR‑142‑3p/miR‑590‑5p-adenomatous polyposis coli protein axis as a potential target for treatment of glioma

Wei,Bo; Wang,Le; Zhao,Jingwei

doi:10.3892/ol.2020.12320

Circular RNA hsa_circ_0005114‑miR‑142‑3p/miR‑590‑5p-adenomatous polyposis coli protein axis as a potential target for treatment of glioma

Authors:
- Bo Wei
- Le Wang
- Jingwei Zhao
View Affiliations

Affiliations: Department of Neurosurgery, China‑Japan Union Hospital of Jilin University, Changchun, Jilin 130033, P.R. China, Department of Ophthalmology, The First Hospital of Jilin University, Jilin University, Changchun, Jilin 130021, P.R. China
Published online on: November 19, 2020 https://doi.org/10.3892/ol.2020.12320
Article Number: 58
Copyright: © Wei et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )

Metrics: Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )

Cited By (CrossRef): 0 citations Loading Articles...

Abstract

Glioma is the most common type of brain tumor and is associated with a high mortality rate. Despite recent advances in treatment options, the overall prognosis in patients with glioma remains poor. Studies have suggested that circular (circ)RNAs serve important roles in the development and progression of glioma and may have potential as therapeutic targets. However, the expression profiles of circRNAs and their functions in glioma have rarely been studied. The present study aimed to screen differentially expressed circRNAs (DECs) between glioma and normal brain tissues using sequencing data collected from the Gene Expression Omnibus database (GSE86202 and GSE92322 datasets) and explain their mechanisms based on the competing endogenous (ce)RNA regulatory hypothesis. In total, 424 commonly downregulated DECs (with the Gene_symbol annotated in the circBase database) in these two datasets were identified. Using the CircInteractome and Starbase databases, 18 micro (mi)RNAs (miRs) were predicted to interact with DECs, while 22 glioma‑related genes obtained from the Comparative Toxicogenomics Database were predicted to be regulated by 15 miRNAs via the miRwalk 2.0 database. A ceRNA network was established based on 115 DECs, 15 miRNAs and 22 mRNAs. LinkedOmics online analysis using The Cancer Genome Atlas (TCGA) data showed that hsa-miR-142-3p/hsa‑miR‑590‑5p and their target gene adenomatous polyposis coli protein (APC) were all significantly associated with overall survival rate and their prognosis trend was opposite, revealing that high expression levels of hsa‑miR‑142‑3p/hsa‑miR‑590‑5 were associated with a poor overall survival rate, while high APC expression with a good overall survival rate. UALCAN analysis using TCGA data of glioblastoma multiforme and the GSE25632 and GSE103229 microarray datasets showed that hsa‑miR‑142‑3p/hsa‑miR‑590‑5p was upregulated and APC was downregulated. Thus, hsa-miR-142-3p/hsa-miR-590-5p-APC-related circ/ceRNA axes may be important in glioma, and hsa_circ_0005114 interacted with both of these miRNAs. Functional analysis showed that hsa_circ_0005114 was involved in insulin secretion, while APC was associated with the Wnt signaling pathway. In conclusion, hsa_circ_0005114-miR-142-3p/miR-590-5p‑APC ceRNA axes may be potential targets for the treatment of glioma.

View Figures

View References

1	Ryan CS, Juhn YJ, Kaur H, Wi CI, Ryu E, King KS and Lachance DH: Long-term incidence of glioma in Olmsted County, Minnesota, and disparities in postglioma survival rate: A population-based study. Neurooncol Pract. 7:288–298. 2020.PubMed/NCBI
2	Sehmer EA, Hall GJ, Greenberg DC, O'Hara C, Wallingford SC, Wright KA and Green AC: Incidence of glioma in a northwestern region of England, 2006–2010. Neuro Oncol. 16:971–974. 2014. View Article : Google Scholar : PubMed/NCBI
3	Larjavaara S, Mäntylä R, Salminen T, Haapasalo H, Raitanen J, Jääskeläinen J and Auvinen A: Incidence of gliomas by anatomic location. Neuro Oncol. 9:319–325. 2007. View Article : Google Scholar : PubMed/NCBI
4	Rasmussen BK, Hansen S, Laursen RJ, Kosteljanetz M, Schultz H, Nørgård BM, Guldberg R and Gradel KO: Epidemiology of glioma: Clinical characteristics, symptoms, and predictors of glioma patients grade I–IV in the the Danish Neuro-Oncology Registry. J Neurooncol. 135:571–579. 2017. View Article : Google Scholar : PubMed/NCBI
5	Piñeros M, Sierra MS, Izarzugaza MI and Forman D: Descriptive epidemiology of brain and central nervous system cancers in Central and South America. Cancer Epidemiol. 44 (Suppl 1):S141–S149. 2016. View Article : Google Scholar : PubMed/NCBI
6	Ebbesen KK, Kjems J and Hansen TB: Circular RNAs: Identification, biogenesis and function. Biochim Biophys Acta. 1859:163–168. 2016. View Article : Google Scholar : PubMed/NCBI
7	Yu CY and Kuo HC: The emerging roles and functions of circular RNAs and their generation. J Biomed Sci. 26:292019. View Article : Google Scholar : PubMed/NCBI
8	Belousova EA, Filipenko ML and Kushlinskii NE: Circular RNA: New regulatory molecules. Bull Exp Biol Med. 164:803–815. 2018. View Article : Google Scholar : PubMed/NCBI
9	Zhou J, Wang H, Chu J, Huang Q, Li G, Yan Y, Xu T, Chen J and Wang Y: Circular RNA hsa_circ_0008344 regulates glioblastoma cell proliferation, migration, invasion, and apoptosis. J Clin Lab Anal. 32:e224542018. View Article : Google Scholar : PubMed/NCBI
10	Wang Y, Sui X, Zhao H, Cong L, Li Y, Xin T, Guo M and Hao W: Decreased circular RNA hsa_circ_0001649 predicts unfavorable prognosis in glioma and exerts oncogenic properties in vitro and in vivo. Gene. 676:117–122. 2018. View Article : Google Scholar : PubMed/NCBI
11	Zhan L, Mu Z, Yang M, Zhang T and Qian L: Elevation of circ-ITX1 upregulates interleukin 17 receptor D expression via sponging miR8a and facilitates cell progression in glioma. J Cell Biochem. 120:16495–16502. 2019. View Article : Google Scholar : PubMed/NCBI
12	Yi C, Li H, Li D, Qin X, Wang J, Liu Y, Liu Z and Zhang J: Upregulation of circular RNA circ_0034642 indicates unfavorable prognosis in glioma and facilitates cell proliferation and invasion via the miR-1205/BATF3 axis. J Cell Biochem. 120:13737–13744. 2019. View Article : Google Scholar : PubMed/NCBI
13	Xiong J, Wang T, Tang H, Lv Z and Liang P: Circular RNA circMAN2B2 facilitates glioma progression by regulating the miR-1205/S100A8 axis. J Cell Physiol. 234:22996–23004. 2019. View Article : Google Scholar : PubMed/NCBI
14	Duan X, Liu D, Wang Y and Chen Z: Circular RNA hsa_circ_0074362 promotes glioma cell proliferation, migration, and invasion by attenuating the inhibition of miR-1236-3p on HOXB7 expression. DNA Cell Biol. 37:917–924. 2018. View Article : Google Scholar : PubMed/NCBI
15	Li X and Diao H: Circular RNA circ_0001946 acts as a competing endogenous RNA to inhibit glioblastoma progression by modulating miR-671-5p and CDR1. J Cell Physiol. 234:13807–13819. 2019. View Article : Google Scholar : PubMed/NCBI
16	Yuan Y, Li J, Xiang W, Liu Y and Mao Q: Analyzing the interactions of mRNAs, miRNAs, lncRNAs and circRNAs to predict competing endogenous RNA networks in glioblastoma. J Neurooncol. 137:493–502. 2018. View Article : Google Scholar : PubMed/NCBI
17	Zhu J, Ye J, Zhang L, Xia L, Hu H, Jiang H, Wan Z, Sheng F, Ma Y, Li W, et al: Differential expression of circular RNAs in glioblastoma multiforme and its correlation with prognosis. Transl Oncol. 10:271–279. 2017. View Article : Google Scholar : PubMed/NCBI
18	Glažar P, Papavasileiou P and Rajewsky N: circBase: A database for circular RNAs. RNA. 20:1666–1670. 2014. View Article : Google Scholar : PubMed/NCBI
19	Nikolayeva O and Robinson MD: edgeR for Differential RNA-seq and ChIP-seq analysis: An application to stem cell biology. Methods Mol Biol. 1150:45–79. 2014. View Article : Google Scholar : PubMed/NCBI
20	R Development Core Team, . R: A language and environment for statistical computing. 2015, simplehttp://www.r-project.org/February 10–2015
21	Dudekula DB, Panda AC, Grammatikakis I, De S, Abdelmohsen K and Gorospe M: CircInteractome: A web tool for exploring circular RNAs and their interacting proteins and microRNAs. RNA Biol. 13:34–42. 2016. View Article : Google Scholar : PubMed/NCBI
22	Li JH, Liu S, Zhou H, Qu LH and Yang JH: Starbase v2.0: Decoding miRNA-ceRNA, miRNA-ncRNA and protein-RNA interaction networks from large-scale clip-seq data. Nucleic Acids Res. 42((Database issue)): D92–D97. 2014. View Article : Google Scholar : PubMed/NCBI
23	Dweep H and Gretz N: miRWalk2.0: A comprehensive atlas of microRNA-target interactions. Nat Methods. 12:6972015. View Article : Google Scholar : PubMed/NCBI
24	Davis AP, Grondin CJ, Johnson RJ, Sciaky D, McMorran R, Wiegers J, Wiegers TC and Mattingly CJ: The Comparative Toxicogenomics Database: Update 2019. Nucleic Acids Res. 47:D948–D954. 2019. View Article : Google Scholar : PubMed/NCBI
25	Kohl M, Wiese S and Warscheid B: Cytoscape: Software for visualization and analysis of biological networks. Methods Mol Biol. 696:291–303. 2011. View Article : Google Scholar : PubMed/NCBI
26	Yu G, Wang LG, Han Y and He QY: clusterProfiler: An R package for comparing biological themes among gene clusters. OMICS. 16:284–287. 2012. View Article : Google Scholar : PubMed/NCBI
27	Ferreira JA: The Benjamini-Hochberg method in the case of discrete test statistics. Int J Biostat. 3:112007. View Article : Google Scholar
28	Vasaikar SV, Straub P, Wang J and Zhang B: LinkedOmics: Analyzing multi-omics data within and across 32 cancer types. Nucleic Acids Res. 46((Database issue)): D956–D963. 2017.
29	Chandrashekar DS, Bashel B, Balasubramanya SAH, Creighton CJ, Ponce-Rodriguez I, Chakravarthi BVSK and Varambally S: UALCAN: A portal for facilitating tumor subgroup gene expression and survival analyses. Neoplasia. 19:649–658. 2017. View Article : Google Scholar : PubMed/NCBI
30	Zhang W, Zhang J, Hoadley K, Kushwaha D, Ramakrishnan V, Li S, Kang C, You Y, Jiang C, Song SW, et al: miR-181d: A predictive glioblastoma biomarker that downregulates MGMT expression. Neuro Oncol. 14:712–719. 2012. View Article : Google Scholar : PubMed/NCBI
31	Lu J, Zhang PY, Li P, Xie JW, Wang JB, Lin JX, Chen QY, Cao LL, Huang CM and Zheng CH: Circular RNA hsa_circ_0001368 suppresses the progression of gastric cancer by regulating miR-6506-5p/FOXO3 axis. Biochem Biophys Res Commun. 512:29–33. 2019. View Article : Google Scholar : PubMed/NCBI
32	Mukasa A, Ueki K, Ge X, Ishikawa S, Ide T, Fujimaki T, Nishikawa R, Asai A, Kirino T and Aburatani H: Selective expression of a subset of neuronal genes in oligodendroglioma with chromosome 1p loss. Brain Pathol. 14:34–42. 2010. View Article : Google Scholar
33	Kashima Y, Miki T, Shibasaki T, Ozaki N, Miyazaki M, Yano H and Seino S: Critical role of cAMP-GEFII-Rim2 complex in incretin-potentiated insulin secretion. J Biol Chem. 276:46046–46053. 2001. View Article : Google Scholar : PubMed/NCBI
34	Fujimoto K, Shibasaki T, Yokoi N, Kashima Y, Matsumoto M, Sasaki T, Tajima N, Iwanaga T and Seino S: Piccolo, a Ca2+ sensor in pancreatic beta-cells. Involvement of cAMP-GEFII.Rim2. Piccolo complex in cAMP-dependent exocytosis. J Biol Chem. 277:50497–50502. 2002. View Article : Google Scholar : PubMed/NCBI
35	Sani I and Albanese A: Endocrine long-term follow-up of children with neurofibromatosis type 1 and optic pathway glioma. Horm Res Paediatr. 87:178–188. 2017. View Article : Google Scholar
36	Masanori A, Takayoshi T, Koji M, Yumi A, Ken-Ichi S and Hironobu S: Prevalence of obesity, hyperlipemia and insulin resistance in children with suprasellar brain tumors. Clin Pediatr Endocrinol. 16:1–9. 2007. View Article : Google Scholar : PubMed/NCBI
37	Anjom-Shoae J, Shayanfar M, Mohammad-Shirazi M, Sadeghi O, Sharifi G, Siassi F and Esmaillzadeh A: Dietary insulin index and insulin load in relation to glioma: Findings from a case-control study. Nutr Neurosci. 29:1–9. 2019. View Article : Google Scholar
38	Gong Y, Ma Y, Sinyuk M, Loganathan S, Thompson RC, Sarkaria JN, Chen W, Lathia JD, Mobley BC, Clark SW and Wang J: Insulin-mediated signaling promotes proliferation and survival of glioblastoma through Akt activation. Neuro Oncol. 18:48–57. 2016. View Article : Google Scholar : PubMed/NCBI
39	Yang BC, Wang YS, Wang CH, Lin HH, Tang MJ and Yang TL: Transient apoptosis elicited by insulin in serum-starved glioma cells involves Fas/Fas-L and Bcl-2. Cell Biol Int. 23:533–540. 1999. View Article : Google Scholar : PubMed/NCBI
40	Jia G, Tang Y, Deng G, Fang D, Xie J, Yan L and Chen Z: miR-590-5p promotes liver cancer growth and chemotherapy resistance through directly targeting FOXO1. Am J Transl Res. 11:2181–2193. 2019.PubMed/NCBI
41	Kim CW, Oh ET, Kim JM, Park JS, Lee DH, Lee JS, Kim KK and Park HJ: Hypoxia-induced microRNA-590-5p promotes colorectal cancer progression by modulating matrix metalloproteinase activity. Cancer Lett. 416:31–41. 2018. View Article : Google Scholar : PubMed/NCBI
42	Shen B, Yu S, Zhang Y, Yuan Y, Li X, Zhong J and Feng J: miR-590-5p regulates gastric cancer cell growth and chemosensitivity through RECK and the AKT/ERK pathway. Onco Targets Ther. 9:6009–6019. 2016. View Article : Google Scholar : PubMed/NCBI
43	Chu Y, Ouyang Y, Wang F, Zheng A, Bai L, Han L, Chen Y and Wang H: MicroRNA-590 promotes cervical cancer cell growth and invasion by targeting CHL1. J Cell Biochem. 115:847–853. 2014. View Article : Google Scholar : PubMed/NCBI
44	Jiang X, Xiang G, Wang Y, Zhang L, Yang X, Cao L, Peng H, Xue P and Chen D: MicroRNA-590-5p regulates proliferation and invasion in human hepatocellular carcinoma cells by targeting TGF-β RII. Mol Cells. 33:545–551. 2012. View Article : Google Scholar : PubMed/NCBI
45	Chen L, Wang W, Zhu S, Jin X, Wang J, Zhu J and Zhou Y: MicroRNA-590-3p enhances the radioresistance in glioblastoma cells by targeting LRIG1. Exp Ther Med. 14:1818–1824. 2017. View Article : Google Scholar : PubMed/NCBI
46	Li Y, Chen D, Jin L, Liu J, Li Y, Su Z, Qi Z, Shi M, Jiang Z, Yang S, et al: Oncogenic microRNA-142-3p is associated with cellular migration, proliferation and apoptosis in renal cell carcinoma. Oncol Lett. 11:1235–12341. 2016. View Article : Google Scholar : PubMed/NCBI
47	Qi X, Li J, Zhou C, Lv C and Tian M: miR-142-3p suppresses SOCS6 expression and promotes cell proliferation in nasopharyngeal carcinoma. Cell Physiol Biochem. 36:1743–1752. 2015. View Article : Google Scholar : PubMed/NCBI
48	Gao X, Xu W, Lu T, Zhou J, Ge X and Hua D: MicroRNA-142-3p promotes cellular invasion of colorectal cancer cells by activation of RAC1. Technol Cancer Res Treat. 17:15330338187905082018. View Article : Google Scholar : PubMed/NCBI
49	Lin RJ, Xiao DW, Liao LD, Chen T, Xie ZF, Huang WZ, Wang WS, Jiang TF, Wu BL, Li EM and Xu LY: miR-142-3p as a potential prognostic biomarker for esophageal squamous cell carcinoma. J Surg Oncol. 105:175–182. 2012. View Article : Google Scholar : PubMed/NCBI
50	Hankey W, Frankel WL and Groden J: Functions of the APC tumor suppressor protein dependent and independent of canonical WNT signaling: Implications for therapeutic targeting. Cancer Metastasis Rev. 37:159–172. 2018. View Article : Google Scholar : PubMed/NCBI
51	Naseri Z, Oskuee RK, Jaafari MR and Forouzandeh Moghadam M: Exosome-mediated delivery of functionally active miRNA-142-3p inhibitor reduces tumorigenicity of breast cancer in vitro and in vivo. Int J Nanomedicine. 13:7727–7747. 2018. View Article : Google Scholar : PubMed/NCBI
52	Wu S, Liu W and Zhou L: miR-590-3p regulates osteogenic differentiation of human mesenchymal stem cells by regulating APC gene. Biochem Biophys Res Commun. 478:1582–1587. 2016. View Article : Google Scholar : PubMed/NCBI
53	Saito-Diaz K, Benchabane H, Tiwari A, Tian A, Li B, Thompson JJ, Hyde AS, Sawyer LM, Jodoin JN, Santos E, et al: APC inhibits ligand-independent Wnt signaling by the clathrin endocytic pathway. Dev Cell. 44:566–581.e8. 2018. View Article : Google Scholar : PubMed/NCBI
54	Ghosh N, Hossain U, Mandal A and Sil PC: The Wnt signaling pathway: A potential therapeutic target against cancer. Ann N Y Acad Sci. 1443:54–74. 2019. View Article : Google Scholar : PubMed/NCBI
55	Cole JM, Simmons K and Prosperi JR: Effect of adenomatous polyposis coli loss on tumorigenic potential in pancreatic ductal adenocarcinoma. Cells. 8:10842019. View Article : Google Scholar
56	Wang Y, Cao C, Fang D and Hu Y: Role of APC-mediated MDR-1/CLCX-1 signaling pathway in ovarian tumors. J Biol Regul Homeost Agents. 32:529–536. 2018.PubMed/NCBI
57	Zhang Y, Guo L, Li Y, Feng GH, Teng F, Li W and Zhou Q: MicroRNA-494 promotes cancer progression and targets adenomatous polyposis coli in colorectal cancer. Mol Cancer. 17:12018. View Article : Google Scholar : PubMed/NCBI
58	Li D, Wang Z, Chen Z, Lin L, Wang Y, Sailike D, Luo K, Du G, Xiang X and Jiafu GD: MicroRNA-106a-5p facilitates human glioblastoma cell proliferation and invasion by targeting adenomatosis polyposis coli protein. Biochem Biophys Res Commun. 481:245–250. 2016. View Article : Google Scholar : PubMed/NCBI