Skip to content
2000
image of Identification of a ceRNA Network Regulating Malignant Transformation of Isocitrate Dehydrogenase Mutant Astrocytoma: An Integrated Bioinformatics Study

Abstract

Introduction

Astrocytoma is the most common glioma, accounting for about 65% of glioblastoma. Its malignant transformation is also one of the important causes of patient mortality, making it the most prevalent and difficult to treat in primary brain tumours. However, little is known about the underlying mechanisms of this transformation.

Methods

In this study, we established a ceRNA network to screen out the potential regulatory pathways involved in the malignant transformation of IDH-mutant astrocytomas. Firstly, the Chinese Glioma Genome Atlas (CGGA) was employed to compare the expression levels of the differential expressed genes (DEGs) in astrocytomas. Then, the ceRNA-regulated network was constructed based on the interaction of lncRNA-miRNA-mRNA. The Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to explore the main functions of the differentially expressed genes. COX regression analysis and log-rank test were combined to screen the ceRNA network further. In addition, quantitative real-time PCR (qRT-PCR) was conducted to identify the potential regulatory mechanisms of malignant transformation in IDH-mutant astrocytoma.

Results

A ceRNA network with 34 lncRNAs, 29 miRNAs, and 71 mRNAs. GO and KEGG analyses results suggested that DEGs were associated with tumor-associated molecular functions and pathways. In addition, we screened two ceRNA regulatory networks using Cox regression analysis and log-rank test. QRT-PCR assay identified the NAA11/hsa-miR-142-3p/GS1-39E22.2 regulatory axis of the ceRNA network to be associated with the malignant transformation of IDH-mutant astrocytoma.

Conclusion

The discovery of this mechanism deepens our understanding of the molecular mechanisms of malignant transformation in astrocytomas and provides new perspectives for exploring glioma progression and targeted therapies.

Loading

Article metrics loading...

/content/journals/cad/10.2174/0115734099293010240810181446
2025-01-06
2025-01-30
Loading full text...

Full text loading...

References

  1. Sayegh E.T. Oh T. Fakurnejad S. Oyon D.E. Bloch O. Parsa A.T. Principles of surgery for malignant astrocytomas. Semin. Oncol. 2014 41 4 523 531 10.1053/j.seminoncol.2014.06.011 25173144
    [Google Scholar]
  2. Miller J.J. Targeting IDH-Mutant Glioma. Neurotherapeutics 2022 19 6 1724 1732 10.1007/s13311‑022‑01238‑3 35476295
    [Google Scholar]
  3. Louis D.N. Perry A. Wesseling P. Brat D.J. Cree I.A. Figarella-Branger D. Hawkins C. Ng H.K. Pfister S.M. Reifenberger G. Soffietti R. von Deimling A. Ellison D.W. The 2021 WHO classification of tumors of the central nervous system: A summary. Neuro-oncol. 2021 23 8 1231 1251 10.1093/neuonc/noab106 34185076
    [Google Scholar]
  4. Persico P. Lorenzi E. Losurdo A. Dipasquale A. Di Muzio A. Navarria P. Pessina F. Politi L.S. Lombardi G. Santoro A. Simonelli M. Precision oncology in lower-grade gliomas: Promises and pitfalls of therapeutic strategies targeting IDH-mutations. Cancers (Basel) 2022 14 5 1125 10.3390/cancers14051125 35267433
    [Google Scholar]
  5. Karreth F.A. Pandolfi P.P. ceRNA cross-talk in cancer: When ce-bling rivalries go awry. Cancer Discov. 2013 3 10 1113 1121 10.1158/2159‑8290.CD‑13‑0202 24072616
    [Google Scholar]
  6. Perron G. Jandaghi P. Moslemi E. Nishimura T. Rajaee M. Alkallas R. Lu T. Riazalhosseini Y. Najafabadi H.S. Pan-cancer analysis of mRNA stability for decoding tumour post-transcriptional programs. Commun. Biol. 2022 5 1 851 10.1038/s42003‑022‑03796‑w 35987939
    [Google Scholar]
  7. Salmena L Poliseno L Tay Y Kats L Pandolfi PP A ceRNA hypothesis: The Rosetta Stone of a hidden RNA language? Cell 2011 146 3 353 8 10.1016/j.cell.2011.07.014
    [Google Scholar]
  8. Su X. Xing J. Wang Z. Chen L. Cui M. Jiang B. microRNAs and ceRNAs: RNA networks in pathogenesis of cancer. Chin. J. Cancer Res. 2013 25 2 235 239 10.3978/j.issn.1000‑9604.2013.03.08 23592905
    [Google Scholar]
  9. Wang Y. Liu X. Guan G. Xiao Z. Zhao W. Zhuang M. Identification of a Five-Pseudogene Signature for Predicting Survival and Its ceRNA Network in Glioma. Front. Oncol. 2019 9 1059 10.3389/fonc.2019.01059 31681595
    [Google Scholar]
  10. Peng Q. Li R. Li Y. Xu X. Ni W. Lin H. Ning L. Prediction of a competing endogenous RNA co‐expression network as a prognostic marker in glioblastoma. J. Cell. Mol. Med. 2020 24 22 13346 13355 10.1111/jcmm.15957 33047898
    [Google Scholar]
  11. Huang L. Li X. Ye H. Liu Y. Liang X. Yang C. Hua L. Yan Z. Zhang X. Long non-coding RNA NCK1-AS1 promotes the tumorigenesis of glioma through sponging microRNA-138-2-3p and activating the TRIM24/Wnt/β-catenin axis. J. Exp. Clin. Cancer Res. 2020 39 1 63 10.1186/s13046‑020‑01567‑1 32293515
    [Google Scholar]
  12. Li Y. Peng L. Cao X. Yang K. Wang Z. Xiao Y. Xiao H. Qian C. Liu H. The Long Non-Coding RNA HOXC-AS3 Promotes Glioma Progression by Sponging miR-216 to Regulate F11R Expression. Front. Oncol. 2022 12 845009 10.3389/fonc.2022.845009 35402226
    [Google Scholar]
  13. Zhao Z. Zhang K.N. Wang Q. Li G. Zeng F. Zhang Y. Wu F. Chai R. Wang Z. Zhang C. Zhang W. Bao Z. Jiang T. Chinese Glioma Genome Atlas (CGGA): A Comprehensive Resource with Functional Genomic Data from Chinese Glioma Patients. Genomics Proteomics Bioinformatics 2021 19 1 1 12 10.1016/j.gpb.2020.10.005 33662628
    [Google Scholar]
  14. Ohgaki H. Kleihues P. The definition of primary and secondary glioblastoma. Clin. Cancer Res. 2013 19 4 764 772 10.1158/1078‑0432.CCR‑12‑3002 23209033
    [Google Scholar]
  15. Frankish A. Carbonell-Sala S. Diekhans M. Jungreis I. Loveland J.E. Mudge J.M. Sisu C. Wright J.C. Arnan C. Barnes I. Banerjee A. Bennett R. Berry A. Bignell A. Boix C. Calvet F. Cerdán-Vélez D. Cunningham F. Davidson C. Donaldson S. Dursun C. Fatima R. Giorgetti S. Giron C.G. Gonzalez J.M. Hardy M. Harrison P.W. Hourlier T. Hollis Z. Hunt T. James B. Jiang Y. Johnson R. Kay M. Lagarde J. Martin F.J. Gómez L.M. Nair S. Ni P. Pozo F. Ramalingam V. Ruffier M. Schmitt B.M. Schreiber J.M. Steed E. Suner M.M. Sumathipala D. Sycheva I. Uszczynska-Ratajczak B. Wass E. Yang Y.T. Yates A. Zafrulla Z. Choudhary J.S. Gerstein M. Guigo R. Hubbard T.J.P. Kellis M. Kundaje A. Paten B. Tress M.L. Flicek P. GENCODE: Reference annotation for the human and mouse genomes in 2023. Nucleic Acids Res. 2023 51 D1 D942 D949 10.1093/nar/gkac1071 36420896
    [Google Scholar]
  16. Love M.I. Huber W. Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014 15 12 550 10.1186/s13059‑014‑0550‑8 25516281
    [Google Scholar]
  17. Ritchie M.E. Phipson B. Wu D. Hu Y. Law C.W. Shi W. Smyth G.K. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015 43 7 e47 10.1093/nar/gkv007 25605792
    [Google Scholar]
  18. Kolde R. Pretty Heatmaps. 2018 Available From: https://cran.r-project.org/web/packages/pheatmap/pheatmap.pdf 2022
  19. Karagkouni D. Paraskevopoulou M.D. Tastsoglou S. Skoufos G. Karavangeli A. Pierros V. Zacharopoulou E. Hatzigeorgiou A.G. DIANA-LncBase v3: Indexing experimentally supported miRNA targets on non-coding transcripts. Nucleic Acids Res. 2019 48 D1 gkz1036 10.1093/nar/gkz1036 31732741
    [Google Scholar]
  20. Li J.H. Liu S. Zhou H. Qu L.H. Yang J.H. starBase v2.0: Decoding miRNA-ceRNA, miRNA-ncRNA and protein–RNA interaction networks from large-scale CLIP-Seq data. Nucleic Acids Res. 2014 42 D1 D92 D97 10.1093/nar/gkt1248 24297251
    [Google Scholar]
  21. Shannon P. Markiel A. Ozier O. Baliga N.S. Wang J.T. Ramage D. Amin N. Schwikowski B. Ideker T. Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res. 2003 13 11 2498 2504 10.1101/gr.1239303 14597658
    [Google Scholar]
  22. Wu T. Hu E. Xu S. Chen M. Guo P. Dai Z. Feng T. Zhou L. Tang W. Zhan L. Fu X. Liu S. Bo X. Yu G. clusterProfiler 4.0: A universal enrichment tool for interpreting omics data. Innovation 2021 2 3 100141 10.1016/j.xinn.2021.100141 34557778
    [Google Scholar]
  23. Yu G. Wang L.G. Han Y. He Q.Y. clusterProfiler: An R package for comparing biological themes among gene clusters. OMICS 2012 16 5 284 287 10.1089/omi.2011.0118 22455463
    [Google Scholar]
  24. Alboukadel M.K. Drawing Survival Curves using 'ggplot2'. 2021 Available From: https://cloud.r-project.org/web/packages/survminer/survminer.pdf 2022
  25. Tay Y Rinn J Pandolfi PP The multilayered complexity of ceRNA crosstalk and competition. Nature 2014 505 7483 344 52 10.1038/nature12986
    [Google Scholar]
  26. Hirtz A. Rech F. Dubois-Pot-Schneider H. Dumond H. Astrocytoma: A Hormone-Sensitive Tumor? Int. J. Mol. Sci. 2020 21 23 9114 10.3390/ijms21239114 33266110
    [Google Scholar]
  27. Kristensen B.W. Priesterbach-Ackley L.P. Petersen J.K. Wesseling P. Molecular pathology of tumors of the central nervous system. Ann. Oncol. 2019 30 8 1265 1278 10.1093/annonc/mdz164 31124566
    [Google Scholar]
  28. Louis D.N. Perry A. Reifenberger G. von Deimling A. Figarella-Branger D. Cavenee W.K. Ohgaki H. Wiestler O.D. Kleihues P. Ellison D.W. The 2016 World Health Organization Classification of Tumors of the Central Nervous System: A summary. Acta Neuropathol. 2016 131 6 803 820 10.1007/s00401‑016‑1545‑1 27157931
    [Google Scholar]
  29. Chan J.J. Tay Y. Noncoding RNA:RNA Regulatory Networks in Cancer. Int. J. Mol. Sci. 2018 19 5 1310 10.3390/ijms19051310 29702599
    [Google Scholar]
  30. Chen P.Y. Li X.D. Ma W.N. Li H. Li M.M. Yang X.Y. Li S.Y. Comprehensive Transcriptomic Analysis and Experimental Validation Identify lncRNA HOXA-AS2/miR-184/COL6A2 as the Critical ceRNA Regulation Involved in Low-Grade Glioma Recurrence. OncoTargets Ther. 2020 13 4999 5016 10.2147/OTT.S245896 32581558
    [Google Scholar]
  31. Brat D.J. Aldape K. Colman H. Figrarella-Branger D. Fuller G.N. Giannini C. Holland E.C. Jenkins R.B. Kleinschmidt-DeMasters B. Komori T. Kros J.M. Louis D.N. McLean C. Perry A. Reifenberger G. Sarkar C. Stupp R. van den Bent M.J. von Deimling A. Weller M. cIMPACT-NOW update 5: Recommended grading criteria and terminologies for IDH-mutant astrocytomas. Acta Neuropathol. 2020 139 3 603 608 10.1007/s00401‑020‑02127‑9 31996992
    [Google Scholar]
  32. Liu Y. Tavana O. Gu W. p53 modifications: Exquisite decorations of the powerful guardian. J. Mol. Cell Biol. 2019 11 7 564 577 10.1093/jmcb/mjz060 31282934
    [Google Scholar]
  33. Zhao Q.S. Ying J.B. Jing J.J. Wang S.S. LncRNA FOXD2-AS1 stimulates glioma progression through inhibiting P53. Eur. Rev. Med. Pharmacol. Sci. 2020 24 8 4382 4388 10.26355/eurrev_202004_21019 32373975
    [Google Scholar]
  34. Yu B.X. Zou L. Li S. Du Y.L. LncRNA SAMD12-AS1 down-regulates P53 to promote malignant progression of glioma. Eur. Rev. Med. Pharmacol. Sci. 2019 23 19 8456 8467 10.26355/eurrev_201910_19158 31646576
    [Google Scholar]
  35. Sun X. Klingbeil O. Lu B. Wu C. Ballon C. Ouyang M. Wu X.S. Jin Y. Hwangbo Y. Huang Y.H. Somerville T.D.D. Chang K. Park J. Chung T. Lyons S.K. Shi J. Vogel H. Schulder M. Vakoc C.R. Mills A.A. BRD8 maintains glioblastoma by epigenetic reprogramming of the p53 network. Nature 2023 613 7942 195 202 10.1038/s41586‑022‑05551‑x 36544023
    [Google Scholar]
  36. Hu S. Cai J. Fang H. Chen Z. Zhang J. Cai R. RPS14 promotes the development and progression of glioma via p53 signaling pathway. Exp. Cell Res. 2023 423 1 113451 10.1016/j.yexcr.2022.113451 36535509
    [Google Scholar]
  37. Akhavan D. Cloughesy T.F. Mischel P.S. mTOR signaling in glioblastoma: Lessons learned from bench to bedside. Neuro-oncol. 2010 12 8 882 889 10.1093/neuonc/noq052 20472883
    [Google Scholar]
  38. Chai C. Song L.J. Han S.Y. Li X.Q. Li M. Retracted: Micro RNA ‐21 promotes glioma cell proliferation and inhibits senescence and apoptosis by targeting SPRY 1 via the PTEN / PI 3K/ AKT signaling pathway. CNS Neurosci. Ther. 2018 24 5 369 380 10.1111/cns.12785 29316313
    [Google Scholar]
  39. Ni W. Xia Y. Bi Y. Wen F. Hu D. Luo L. FoxD2-AS1 promotes glioma progression by regulating miR-185-5P/HMGA2 axis and PI3K/AKT signaling pathway. Aging (Albany NY) 2019 11 5 1427 1439 10.18632/aging.101843 30860979
    [Google Scholar]
  40. Li H. Liu J. Qin X. Sun J. Liu Y. Jin F. Function of Long Noncoding RNAs in Glioma Progression and Treatment Based on the Wnt/β-Catenin and PI3K/AKT Signaling Pathways. Cell. Mol. Neurobiol. 2023 43 8 3929 3942 10.1007/s10571‑023‑01414‑9 37747595
    [Google Scholar]
  41. Wang J. Zhu S. Meng N. He Y. Lu R. Yan G.R. ncRNA-encoded peptides or proteins and cancer. Mol. Ther. 2019 27 10 1718 1725 10.1016/j.ymthe.2019.09.001 31526596
    [Google Scholar]
  42. Li H. Wang M. Zhou H. Lu S. Zhang B. Long noncoding RNA EBLN3P promotes the progression of liver cancer via alteration of microRNA-144-3p/DOCK4 signal. Cancer Manag. Res. 2020 12 9339 9349 10.2147/CMAR.S261976 33061623
    [Google Scholar]
  43. Stackhouse CT Gillespie GY Willey CD Exploring the roles of lncRNAs in GBM pathophysiology and their therapeutic potential. Cells 2020 9 11 2369 10.3390/cells9112369
    [Google Scholar]
  44. Wei B. Wang L. Zhao J. Circular RNA hsa_circ_0005114‑miR‑142‑3p/miR‑590‑5p-adenomatous polyposis coli protein axis as a potential target for treatment of glioma. Oncol. Lett. 2020 21 1 58 10.3892/ol.2020.12320 33281969
    [Google Scholar]
  45. Zhang S. Yue W. Xie Y. Liu L. Li S. Dang W. Xin S. Yang L. Zhai X. Cao P. Lu J. The four‑microRNA signature identified by bioinformatics analysis predicts the prognosis of nasopharyngeal carcinoma patients. Oncol. Rep. 2019 42 5 1767 1780 10.3892/or.2019.7316 31545473
    [Google Scholar]
  46. Bazrgar M. Mirmotalebisohi S.A. Ahmadi M. Azimi P. Dargahi L. Zali H. Ahmadiani A. Comprehensive analysis of l nc RNA ‐associated ce RNA network reveals novel potential prognostic regulatory axes in glioblastoma multiforme. J. Cell. Mol. Med. 2024 28 11 e18392 10.1111/jcmm.18392 38864705
    [Google Scholar]
  47. Zhang G. Tao X. Ji B. Gong J. Long non-coding RNA COX10-AS1 promotes glioma progression by competitively binding miR-1-3p to regulate ORC6 expression. Neuroscience 2024 540 68 76 10.1016/j.neuroscience.2023.09.020 38244670
    [Google Scholar]
  48. Huang X. Wang Z. Song M. Huan H. Cai Z. Wu B. Shen J. Zhou Y.L. Shi J. CircIQGAP1 regulates RCAN1 and RCAN2 through the mechanism of ceRNA and promotes the growth of malignant glioma. Pharmacol. Res. 2023 197 106979 10.1016/j.phrs.2023.106979 37918583
    [Google Scholar]
/content/journals/cad/10.2174/0115734099293010240810181446
Loading
/content/journals/cad/10.2174/0115734099293010240810181446
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test