Skip to main content
Log in

Noncoding RNAs as potential biomarkers for DIPG diagnosis and prognosis: XIST and XIST-210 involvement

  • Research Article
  • Published:
Clinical and Translational Oncology Aims and scope Submit manuscript

Abstract

Purpose

Diffuse intrinsic pontine gliomas (DIPGs) are the most fatal primary brainstem tumors in pediatric patients. The identification of new molecular features, mediating their formation and progression, as non-coding RNAs (ncRNAs), would be of great importance for the development of effective treatments.

Methods

We analyzed the DIPGs transcriptome with the HTA2.0 array and it was compared with pediatric non-brainstem astrocytoma expression profiles (GSE72269).

Results

More than 50% of the differentially expressed transcripts were ncRNAs and based on this, we proposed a DIPGs ncRNA signature. LncRNAs XIST and XIST-210, and the HBII-52 and HBII-85 snoRNA clusters were markedly downregulated in DIPGs. qPCR assays demonstrated XIST downregulation in all non-brainstem astrocytomas, in a gender, age, and brain location-independent manner, as well as in DIPGs affecting boys; however, DIPGs affecting girls showed both downregulation and upregulation of XIST. Girls’ with longer survival positively correlated with XIST expression.

Conclusions

The involvement of ncRNAs in DIPGs is imminent and their expression profile is useful to differentiate them from non-neoplastic tissues and non-brain stem astrocytomas, which suggests their potential use as DIPG biomarkers. In fact, XIST and XIST-210 are potential DIPG prognostic biomarkers.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Saratsis AM, Kambhampati M, Snyder K, et al. Comparative multidimensional molecular analyses of pediatric diffuse intrinsic pontine glioma reveals distinct molecular subtypes. Acta Neuropathol. 2014;127:881–95.

    Article  CAS  Google Scholar 

  2. Frazier JL, Lee J, Thomale UW, et al. Treatment of diffuse intrinsic brainstem gliomas: failed approaches and future strategies. J Neurosurg Pediatr. 2009;3:259–69.

    Article  Google Scholar 

  3. Jansen MH, van Vuurden DG, Vandertop WP, Kaspers GJ. Diffuse intrinsic pontine gliomas: a systematic update on clinical trials and biology. Cancer Treat Rev. 2012;38:27–35.

    Article  CAS  Google Scholar 

  4. Koncar RF, Dey BR, Stanton AJ, et al. Identification of novel RAS signaling therapeutic vulnerabilities in diffuse intrinsic pontine gliomas. Cancer Res. 2019;79:4026–41.

    Article  CAS  Google Scholar 

  5. Pfaff E, El Damaty A, Balasubramanian GP, et al. Brainstem biopsy in pediatric diffuse intrinsic pontine glioma in the era of precision medicine: the INFORM study experience. Eur J Cancer. 2019;114:27–35.

    Article  Google Scholar 

  6. Bartels U, Hawkins C, Vezina G, et al. Proceedings of the diffuse intrinsic pontine glioma (DIPG) Toronto Think Tank: advancing basic and translational research and cooperation in DIPG. J Neurooncol. 2011;105:119–25.

    Article  Google Scholar 

  7. Lapin DH, Tsoli M, Ziegler DS. Genomic insights into diffuse intrinsic pontine glioma. Front Oncol. 2007;7:57.

    Google Scholar 

  8. Castel D, Philippe C, Calmon R, et al. Histone H3F3A and HIST1H3B K27M mutations define two subgroups of diffuse intrinsic pontine gliomas with different prognosis and phenotypes. Acta Neuropathol. 2015;130:815–27.

    Article  CAS  Google Scholar 

  9. Mackay A, Burford A, Carvalho D, et al. Integrated molecular meta-analysis of 1,000 pediatric high-grade and diffuse intrinsic pontine glioma. Cancer Cell. 2017;32(520–537):e5.

    Google Scholar 

  10. Buczkowicz P, Hoeman C, Rakopoulos P, et al. Genomic analysis of diffuse intrinsic pontine gliomas identifies three molecular subgroups and recurrent activating ACVR1 mutations. Nat Genet. 2014;46:451–6.

    Article  CAS  Google Scholar 

  11. Mackay A, Burford A, Molinari V, et al. Molecular, pathological, radiological, and immune profiling of non-brainstem pediatric high-grade glioma from the HERBY phase II randomized trial. Cancer Cell. 2018;33(5):829–42.

    Article  CAS  Google Scholar 

  12. Anastasiadou E, Jacob LS, Slack FJ. Non-coding RNA networks in cancer. Nat Rev Cancer. 2018;18:5–18.

    Article  CAS  Google Scholar 

  13. Long S, Li G. Comprehensive analysis of a long non-coding RNA-mediated competitive endogenous RNA network in glioblastoma multiforme. Exp Ther Med. 2019;18:1081–90.

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Liu Y, Liu H, Zhang D. Identification of novel long non-coding RNA in diffuse intrinsic pontine gliomas by expression profile analysis. Oncol Lett. 2018;16:6401–6.

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Jha P, Agrawal R, Pathak P, et al. Genome-wide small non-coding RNA profiling of pediatric high-grade gliomas reveals deregulation of several miRNAs, identifies downregulation of snoRNA cluster HBII-52 and delineates H3F3A and TP53 mutant-specific miRNAs and snoRNAs. Int J Cancer. 2015;137:2343–53.

    Article  CAS  Google Scholar 

  16. Ruiz Esparza-Garrido R, Velázquez-Flores MÁ, Diegopérez-Ramírez J, et al. A proteomic approach of pediatric astrocytomas: MiRNAs and network insight. J Proteom. 2013;94:162–75.

    Article  CAS  Google Scholar 

  17. Ruiz Esparza-Garrido R, Rodríguez-Corona JM, López-Aguilar JE, et al. Differentially expressed long non-coding RNAs were predicted to be involved in the control of signaling pathways in pediatric astrocytoma. Mol Neurobiol. 2017;54:6598–608.

    Article  CAS  Google Scholar 

  18. Bechet D, Gielen GGH, Korshunov A, et al. Specific detection of methionine 27 mutation in histone 3 variants (H3K27M) in Fixed tissue from high-grade astrocytomas. Acta Neuropathol. 2014;128:733–41.

    Article  CAS  Google Scholar 

  19. Li J, Ma W, Zeng P, et al. LncTar: a tool for predicting the RNA targets of long noncoding RNAs. Brief Bioinform. 2015;16:806–12.

    Article  CAS  Google Scholar 

  20. Vlachos IS, Zagganas K, Paraskevopoulou MD, et al. DIANA miRPath v3.0: deciphering microRNA function with experimental support. Nucleic Acids Res. 2015;43:W460–W466466.

    Article  CAS  Google Scholar 

  21. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(−Delta Delta C(T)) Method. Methods. 2015;25:402–8.

    Article  Google Scholar 

  22. Marchese FP, Raimondi I, Huarte M. The multidimensional mechanisms of long non-coding RNA function. Genome Biol. 2017;18:206.

    Article  Google Scholar 

  23. Jarroux J, Morillon A, Pinskaya M. History, discovery and classification of lncRNAs. Adv Exp Med Biol. 2017;1008:1–46.

    Article  CAS  Google Scholar 

  24. Chen YK, Yen Y. The ambivalent role of lncRNA xist in carcinogenesis. Stem Cell Rev. 2019;15:314–23.

    Article  CAS  Google Scholar 

  25. Yildirim E, Kirby JE, Brown DE, et al. Xist RNA is a potent suppressor of hematologic cancer in mice. Cell. 2013;152:727–42.

    Article  CAS  Google Scholar 

  26. Xing F, Liu Y, Wu SY, et al. Loss of XIST in breast cancer activates MSN-c-met and reprograms microglia via exosomal miRNA to promote brain metastasis. Cancer Res. 2018;78:4316–30.

    Article  CAS  Google Scholar 

  27. Yang Z, Jiang X, Jiang X, Zhao H. X-inactive-specific transcript: a long non-coding RNA with complex roles in human cancers. Gene. 2018;679:28–35.

    Article  CAS  Google Scholar 

  28. Du P, Zhao H, Peng R, et al. LncRNA-XIST interacts with miR-29c to modulate the chemoresistance of glioma cell to TMZ through DNA mismatch repair pathway. Biosci Res 2017;37.

  29. Pan X, Chen L, Feng KY, et al. Analysis of expression pattern of snoRNAs in different cancer types with machine learning algorithms. Int J Mol Sci. 2017;20.

  30. Cavaillé J. Box C/D small nucleolar RNA genes and the Prader–Willi syndrome: a complex interplay. Wiley Interdiscip Rev. 2017;8 (RNA)

  31. Enfield KS, Martinez VD, Marshall EA, et al. Deregulation of small non-coding RNAs at the DLK1-DIO3 imprinted locus predicts lung cancer patient outcome. Oncotarget. 2006;7:80957–66.

    Article  Google Scholar 

Download references

Acknowledgements

We thank Miguel Araujo and Elizabeth Morales for their technical support. This research was supported by FIS/IMSS/PROT/G17/1673 from the Instituto Mexicano del Seguro Social (IMSS). Special thanks to SINTAGMA TRANSLATIONS for English language correction.

Author information

Authors and Affiliations

Authors

Contributions

RRE and MV designed the study, performed the experiments, and analyzed the data. Also, these authors wrote and reviewed the manuscript. JR performed the bioinformatic analysis and reviewed the final version of the manuscript. JL, GR, and GS provided the samples and the clinical data of the patients included in the study. They also reviewed the final version of the manuscript. GS performed the immunohistopathological and immunohistochemical analysis, and reviewed the final version of the manuscript.

Corresponding author

Correspondence to R. Ruiz Esparza-Garrido.

Ethics declarations

Conflict of interest

All authors declare no conflict of interest.

Ethical standard

The project has the approval of the hospital de Pediatría, Centro Médico Nacional Siglo XXI, IMSS: Ethics in Security Research (R-2014-3603-247) which is in accordance with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Research involving human participants or animals

This article does not contain any studies with animals performed by any of the authors.

Informed consent

Written consent forms were obtained from participants who provided fresh samples of tissue for the HTA 2.0 array and the qPCR component of the study.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Velázquez-Flores, M.Á., Rodríguez-Corona, J.M., López-Aguilar, J.E. et al. Noncoding RNAs as potential biomarkers for DIPG diagnosis and prognosis: XIST and XIST-210 involvement. Clin Transl Oncol 23, 501–513 (2021). https://doi.org/10.1007/s12094-020-02443-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12094-020-02443-2

Keywords

Navigation