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Histone H3K9 methyltransferase SETDB1 overexpression correlates with pediatric high-grade gliomas progression and prognosis

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Pediatric high-grade gliomas (pHGGs) are heterogeneous, diffuse, and highly infiltrative tumors with dismal prognosis. Aberrant post-translational histone modifications with elevated histone 3 lysine trimethylation (H3K9me3) have been recently implicated in pHGGs’ pathology, conferring to tumor heterogeneity. The present study investigates the potential involvement of H3K9me3 methyltransferase SETDB1 in the cellular function, progression, and clinical significance of pHGG. The bioinformatic analysis detected SETDB1 enrichment in pediatric gliomas compared to the normal brain, as well as positive and negative correlations with a proneural and mesenchymal signature, respectively. In our cohort of pHGGs, SETDB1 expression was significantly increased compared to pLGG and normal brain tissue and correlated with p53 expression, as well as reduced patients’ survival. In accordance, H3K9me3 levels were also elevated in pHGG compared to the normal brain and were associated with worse patient survival. Gene silencing of SETDB1 in two patient-derived pHGG cell lines showed a significant reduction in cell viability followed by reduced cell proliferation and increased apoptosis. SETDB1 silencing further reduced cell migration of pHGG cells and the expression of the mesenchymal markers N-cadherin and vimentin. mRNA analysis of epithelial–mesenchymal transition (EMT) markers upon SETDB1 silencing showed a reduction in SNAI1 levels and downregulation of CDH2 along with the EMT regulator gene MARCKS. In addition, SETDB1 silencing significantly increased the bivalent tumor suppressor gene SLC17A7 mRNA levels in both cell lines, indicating its implication in the oncogenic process.Altogether, our findings demonstrate a predominant oncogenic role of SETDB1 in pHGG which along with elevated H3K9me3 levels correlate significantly to tumor progression and inferior patients’ survival. There is evidence that targeting SETDB1 may effectively inhibit pHGG progression, providing a novel insight into the therapeutic strategies for pediatric gliomas.

Key messages

  • SETDB1 gene expression is enriched in pHGG compared to normal brain.

  • SETDB1 expression is increased in pHGG tissues and associates with reduced patients’ survival.

  • Gene silencing of SETDB1 reduces cell viability and migration.

  • SETDB1 silencing affects mesenchymal markers expression.

  • SETDB1 silencing upregulates SLC17A7 levels.

  • SETDB1 has an oncogenic role in pHGG.

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Availability of supporting data

The data that support the findings of this study are openly available in Affymetrix Human Genome U133 Plus 2.0 Array—Platform GPL570 pediatric brain samples (GSE50161) at http://r2.amc.nl, reference number [26].

References

  1. Thorbinson C, Kilday JP (2021) Childhood malignant brain tumors: balancing the bench and bedside. Cancers (Basel) 13:6099. https://doi.org/10.3390/CANCERS13236099

    Article  CAS  PubMed  Google Scholar 

  2. Jones C, Karajannis MA, Jones DTW et al (2017) Pediatric high-grade glioma: biologically and clinically in need of new thinking. Neuro Oncol 19:153–161. https://doi.org/10.1093/NEUONC/NOW101

    Article  CAS  PubMed  Google Scholar 

  3. Louis DN, Perry A, Wesseling P et al (2021) The 2021 WHO classification of tumors of the central nervous system: a summary. Neuro Oncol 23:1231–1251. https://doi.org/10.1093/neuonc/noab106

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Nikbakht H, Panditharatna E, Mikael LG et al (2016) Spatial and temporal homogeneity of driver mutations in diffuse intrinsic pontine glioma. Nat Commun 7:11185. https://doi.org/10.1038/NCOMMS11185

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Larson JD, Kasper LH, Paugh BS et al (2019) Histone H3.3 K27M accelerates spontaneous brainstem glioma and drives restricted changes in bivalent gene expression. Cancer Cell 35:140-155.e7. https://doi.org/10.1016/J.CCELL.2018.11.015

    Article  CAS  PubMed  Google Scholar 

  6. Silveira AB, Kasper LH, Fan Y et al (2019) H3.3 K27M depletion increases differentiation and extends latency of diffuse intrinsic pontine glioma growth in vivo. Acta Neuropathol 137:637–655. https://doi.org/10.1007/S00401-019-01975-4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Harutyunyan AS, Krug B, Chen H et al (2019) H3K27M induces defective chromatin spread of PRC2-mediated repressive H3K27me2/me3 and is essential for glioma tumorigenesis. Nat Commun 10:1262. https://doi.org/10.1038/S41467-019-09140-X

    Article  PubMed  PubMed Central  Google Scholar 

  8. Klonou A, Piperi C, Gargalionis AN, Papavassiliou AG (2017) Molecular basis of pediatric brain tumors. Neuromolecular Med 19:256–270. https://doi.org/10.1007/S12017-017-8455-9

    Article  CAS  PubMed  Google Scholar 

  9. Bechet D, Gielen GGH, Korshunov A et al (2014) Specific detection of methionine 27 mutation in histone 3 variants (H3K27M) in fixed tissue from high-grade astrocytomas. Acta Neuropathol 128:733–741. https://doi.org/10.1007/S00401-014-1337-4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Bender S, Tang Y, Lindroth AM et al (2013) Reduced H3K27me3 and DNA hypomethylation are major drivers of gene expression in K27M mutant pediatric high-grade gliomas. Cancer Cell 24:660–672. https://doi.org/10.1016/J.CCR.2013.10.006

    Article  CAS  PubMed  Google Scholar 

  11. Klonou A, Korkolopoulou P, Gargalionis AN et al (2021) Histone mark profiling in pediatric astrocytomas reveals prognostic significance of H3K9 trimethylation and histone methyltransferase SUV39H1. Neurotherapeutics 18:2073–2090. https://doi.org/10.1007/S13311-021-01090-X

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Chi P, Allis CD, Wang GG (2010) Covalent histone modifications–miswritten, misinterpreted and mis-erased in human cancers. Nat Rev Cancer 10:457–469. https://doi.org/10.1038/NRC2876

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Zhu Q, Pao GM, Huynh AM et al (2011) BRCA1 tumour suppression occurs via heterochromatin-mediated silencing. Nature 477:179–184. https://doi.org/10.1038/NATURE10371

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Harutyunyan AS, Chen H, Lu T et al (2020) H3K27M in gliomas causes a one-step decrease in H3K27 methylation and reduced spreading within the constraints of H3K36 methylation. Cell Rep 33:108390. https://doi.org/10.1016/J.CELREP.2020.108390

  15. Torrano J, Al Emran A, Hammerlindl H, Schaider H (2019) Emerging roles of H3K9me3, SETDB1 and SETDB2 in therapy-induced cellular reprogramming. Clin Epigenetics 11:43. https://doi.org/10.1186/s13148-019-0644-y

    Article  PubMed  PubMed Central  Google Scholar 

  16. Cruz-Tapias P, Zakharova V, Perez-Fernandez OM et al (2019) Expression of the major and pro-oncogenic H3K9 lysine methyltransferase SETDB1 in non-small cell lung cancer. Cancers (Basel) 11:1134. https://doi.org/10.3390/cancers11081134

    Article  CAS  PubMed  Google Scholar 

  17. Ryu TY, Kim K, Kim S-K et al (2019) SETDB1 regulates SMAD7 expression for breast cancer metastasis. BMB Rep 52:139–144. https://doi.org/10.5483/BMBRep.2019.52.2.235

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Chen K, Zhang F, Ding J et al (2017) Histone methyltransferase SETDB1 promotes the progression of colorectal cancer by inhibiting the expression of TP53. J Cancer 8:3318–3330. https://doi.org/10.7150/jca.20482

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Tan SL, Nishi M, Ohtsuka T, Matsui T, Takemoto K et al (2012) Essential roles of the histone methyltransferase ESET in the epigenetic control of neural progenitor cells during development. Development 139:3806–3816. https://doi.org/10.1242/dev.082198

    Article  CAS  PubMed  Google Scholar 

  20. Spyropoulou A, Gargalionis A, Dalagiorgou G et al (2014) Role of histone lysine methyltransferases SUV39H1 and SETDB1 in gliomagenesis: modulation of cell proliferation, migration, and colony formation. NeuroMolecular Med 16:70–82. https://doi.org/10.1007/s12017-013-8254-x

    Article  CAS  PubMed  Google Scholar 

  21. Sepsa A, Levidou G, Gargalionis A et al (2015) Emerging role of linker histone variant H1x as a biomarker with prognostic value in astrocytic gliomas. A multivariate analysis including trimethylation of H3K9 and H4K20. PLoS One 10:e0115101. https://doi.org/10.1371/journal.pone.0115101

  22. Smith HL, Wadhwani N, Horbinski C (2022) Major features of the 2021 WHO classification of CNS tumors. Neurotherapeutics. https://doi.org/10.1007/S13311-022-01249-0

    Article  PubMed  PubMed Central  Google Scholar 

  23. Verhaak RGW, Hoadley KA, Purdom E et al (2010) Integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR, and NF1. Cancer Cell 17:98–110. https://doi.org/10.1016/J.CCR.2009.12.020

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Griesinger AM, Birks DK, Donson AM et al (2013) Characterization of distinct immunophenotypes across pediatric brain tumor types. J Immunol 191:4880–4888. https://doi.org/10.4049/jimmunol.1301966

    Article  CAS  PubMed  Google Scholar 

  25. Klaus B, Reisenauer S (2018) An end to end workflow for differential gene expression using Affymetrix microarrays. F1000Research 5:1384. https://doi.org/10.12688/f1000research.8967.2

  26. Vandel J, Gheeraert C, Staels B et al (2020) GIANT: galaxy-based tool for interactive analysis of transcriptomic data. Sci Rep 10:19835. https://doi.org/10.1038/s41598-020-76769-w

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Gentleman RC, Carey VJ, Bates DM et al (2004) Bioconductor: open software development for computational biology and bioinformatics. Genome Biol 5:R80. https://doi.org/10.1186/gb-2004-5-10-r80

    Article  PubMed  PubMed Central  Google Scholar 

  28. R Core Team (2020) — European Environment Agency. https://www.eea.europa.eu/data-and-maps/indicators/oxygen-consuming-substances-in-rivers/r-development-core-team-2006. Accessed 24 May 2022

  29. Citing RStudio – RStudio Support. https://support.rstudio.com/hc/en-us/articles/206212048-Citing-RStudio. Accessed 24 May 2022

  30. Koster J, Volckmann R, Zwijnenburg D et al (2019) Abstract 2490: R2: genomics analysis and visualization platform. 2490–2490. https://doi.org/10.1158/1538-7445.SABCS18-2490

  31. Dabney AR (2006) ClaNC: point-and-click software for classifying microarrays to nearest centroids. Bioinformatics 22:122–123. https://doi.org/10.1093/BIOINFORMATICS/BTI756

    Article  CAS  PubMed  Google Scholar 

  32. Müller M, Rösch L, Najafi S et al (2021) Combining APR-246 and HDAC-inhibitors: a novel targeted treatment option for neuroblastoma. Cancers 13:4476. https://doi.org/10.3390/CANCERS13174476

    Article  PubMed  PubMed Central  Google Scholar 

  33. Xu J, Erdreich-Epstein A, Gonzalez-Gomez I et al (2011) Novel cell lines established from pediatric brain tumors. J Neuro-Oncology 107:269–280. https://doi.org/10.1007/S11060-011-0756-5

    Article  Google Scholar 

  34. Lin B, Lee H, Yoon J et al (2015) Global analysis of H3K4me3 and H3K27me3 profiles in glioblastoma stem cells and identification of SLC17A7 as a bivalent tumor suppressor gene. Oncotarget 6:5369–5381. https://doi.org/10.18632/oncotarget.3030

    Article  PubMed  PubMed Central  Google Scholar 

  35. Paugh B, Qu C, Jones C, Liu Z, Adamowicz-Brice M, Zhang J, Bax DA, Coyle B, Barrow J, Hargrave D et al (2010) Integrated molecular genetic profiling of pediatric high-grade gliomas reveals key differences with the adult disease. J Clin Oncol 28:3061–3068. https://doi.org/10.1200/JCO.2009.26.7252

    Article  PubMed  PubMed Central  Google Scholar 

  36. Fedele M, Cerchia L, Pegoraro S, Sgarra R, Manfioletti G (2019) Proneural-mesenchymal transition: phenotypic plasticity to acquire multitherapy resistance in glioblastoma. Int J Mol Sci 20:2746. https://doi.org/10.3390/ijms20112746

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Ogawa S, Fukuda A, Matsumoto Y, Hanyu Y, Sono M, Fukunaga Y, Masuda T, Araki O, Nagao M, Yoshikawa T et al (2020) SETDB1 inhibits p53-mediated apoptosis and is required for formation of pancreatic ductal adenocarcinomas in mice. Gastroenterology 159:682-696.e13. https://doi.org/10.1053/j.gastro.2020.04.047

    Article  CAS  PubMed  Google Scholar 

  38. Fei Q, Shang K, Zhang J et al (2015) Histone methyltransferase SETDB1 regulates liver cancer cell growth through methylation of p53. Nat Commun 6:8651. https://doi.org/10.1038/ncomms9651

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Feinberg AP (2007) Phenotypic plasticity and the epigenetics of human disease. Nature 447:433–440. https://doi.org/10.1038/NATURE05919

    Article  CAS  PubMed  Google Scholar 

  40. Wu W, Tian Y, Wan H et al (2013) Expression of β-catenin and E- and N-cadherin in human brainstem gliomas and clinicopathological correlations. Int J Neurosci 123:318–323. https://doi.org/10.3109/00207454.2012.758123

    Article  CAS  PubMed  Google Scholar 

  41. Camand E, Peglion F, Osmani N et al (2012) N-cadherin expression level modulates integrin-mediated polarity and strongly impacts on the speed and directionality of glial cell migration. J Cell Sci 125:844–857. https://doi.org/10.1242/JCS.087668

    Article  CAS  PubMed  Google Scholar 

  42. Yang W, Ying SU, Chenjian HOU et al (2019) SETDB1 induces epithelial-mesenchymal transition in breast carcinoma by directly binding with Snail promoter. Oncol Rep 41:1284–1292. https://doi.org/10.3892/or.2018.6871

    Article  CAS  PubMed  Google Scholar 

  43. Du D, Katsuno Y, Meyer D et al (2018) Smad3-mediated recruitment of the methyltransferase SETDB1/ESET controls Snail1 expression and epithelial-mesenchymal transition. EMBO Rep 19:135–155. https://doi.org/10.15252/EMBR.201744250

  44. Liu T, Xu P, Ke S et al (2022) Histone methyltransferase SETDB1 inhibits TGF-β-induced epithelial-mesenchymal transition in pulmonary fibrosis by regulating SNAI1 expression and the ferroptosis signaling pathway. Arch Biochem Biophys 715:109087. https://doi.org/10.1016/J.ABB.2021.109087

  45. Xiang W, Peng T, Ming Y et al (2019) Myristoylated alanine rich protein kinase C substrate is a potential cancer prognostic factor that regulates cell migration and invasion in glioblastoma. Oncol Rep 41:2464–2470. https://doi.org/10.3892/OR.2019.7009/HTML

    Article  CAS  PubMed  Google Scholar 

  46. Kaszak I, Witkowska-Piłaszewicz O, Niewiadomska Z et al (2020) Role of cadherins in cancer-a review. Int J Mol Sci 21:1–17. https://doi.org/10.3390/IJMS21207624

    Article  Google Scholar 

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Acknowledgements

We thank Professor Anastasia Konstantinidou (First Department of Pathology, Medical School, National and Kapodistrian University of Athens) for providing the archival normal brain tissues.

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Author notes

  1. Penelope Korkolopoulou and Angeliki-Ioanna Giannopoulou contributed equally to this work.

Authors and Affiliations

  1. Department of Biological Chemistry, Medical School, National and Kapodistrian University of Athens, 75 Mikras Asias Street - Bldg 16, 11527, Athens, Greece

    Alexia Klonou, Angeliki-Ioanna Giannopoulou, Antonios N. Gargalionis, Panagiotis Sarantis, Athanasios G. Papavassiliou & Christina Piperi

  2. First Department of Pathology, Medical School, National and Kapodistrian University of Athens, 11527, Athens, Greece

    Penelope Korkolopoulou, Dimitrios S. Kanakoglou & Andromachi Pampalou

  3. Department of Pediatric Neurosurgery, IASO Children’s Hospital, National and Kapodistrian University of Athens, 15123, Athens, Greece

    Andreas Mitsios & Spyros Sgouros

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  1. Alexia Klonou
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  2. Penelope Korkolopoulou
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Contributions

Conceptualization: Christina Piperi; methodology: Alexia Klonou, Penelope Korkolopoulou, Angeliki-Ioanna Giannopoulou, Antonios N. Gargalionis; formal analysis and investigation: Dimitrios S. Kanakoglou, Andromachi Pampalou, Panagiotis Sarantis, Andreas Mitsios, Spyros Sgouros; writing—original draft preparation: Christina Piperi, Alexia Klonou; writing—review and editing: Christina Piperi, Penelope Korkolopoulou, Athanasios G. Papavassiliou; resources: Penelope Korkolopoulou, Spyros Sgouros, Andreas Mitsios; supervision: Christina Piperi, Athanasios G. Papavassiliou.

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Correspondence to Athanasios G. Papavassiliou or Christina Piperi.

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Ethics approval and consent to participate

Approval was obtained from the ethics committee of the National and Kapodistrian University of Athens Medical School Ethics Committee (27/06/2017, 1617031069). The procedures used in this study adhere to the tenets of the Declaration of Helsinki. Informed consent was obtained from all individual participants included in the study.

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Klonou, A., Korkolopoulou, P., Giannopoulou, AI. et al. Histone H3K9 methyltransferase SETDB1 overexpression correlates with pediatric high-grade gliomas progression and prognosis. J Mol Med 101, 387–401 (2023). https://doi.org/10.1007/s00109-023-02294-8

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