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Circular RNA-encoded oncogenic E-cadherin variant promotes glioblastoma tumorigenicity through activation of EGFR–STAT3 signalling

Nature Cell Biology volume 23, pages 278–291 (2021)Cite this article

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Abstract

Activated EGFR signalling drives tumorigenicity in 50% of glioblastoma (GBM). However, EGFR-targeting therapy has proven ineffective in treating patients with GBM, indicating that there is redundant EGFR activation. Circular RNAs are covalently closed RNA transcripts that are involved in various physiological and pathological processes. Herein, we report an additional activation mechanism of EGFR signalling in GBM by an undescribed secretory E-cadherin protein variant (C-E-Cad) encoded by a circular E-cadherin (circ-E-Cad) RNA through multiple-round open reading frame translation. C-E-Cad is overexpressed in GBM and promotes glioma stem cell tumorigenicity. C-E-Cad activates EGFR independent of EGF through association with the EGFR CR2 domain using a unique 14-amino-acid carboxy terminus, thereby maintaining glioma stem cell tumorigenicity. Notably, inhibition of C-E-Cad markedly enhances the antitumour activity of therapeutic anti-EGFR strategies in GBM. Our results uncover a critical role of C-E-Cad in stimulating EGFR signalling and provide a promising approach for treating EGFR-driven GBM.

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Fig. 1: circ-E-Cad RNA is a potential coding circRNA and is overexpressed in GBM and GSCs.
Fig. 2: circ-E-Cad RNA encodes a protein through multiple rounds of translation.
Fig. 3: C-E-Cad maintains self-renewal and tumorigenicity of GSCs in vitro and in vivo.
Fig. 4: C-E-Cad promotes the activation of STAT3, PI3K–AKT and MAPK signalling in GSCs.
Fig. 5: C-E-Cad is a secretory protein that activates STAT3 through EGFR.
Fig. 6: The unique C terminus of C-E-Cad and the CR2 domain of EGFR mediate the mutual interaction.
Fig. 7: C-E-Cad independently activates EGFR and EGFRvIII.
Fig. 8: Clinical implications and applications of C-E-Cad.

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Data availability

The RNA-seq data that support the findings of this study have been deposited in the NCBI with the identifiers PRJNA525736, SRA714646 and PRJNA525736. The human GBM data were derived from the TCGA Research Network: http://cancergenome.nih.gov/. The dataset derived from this resource that supports the findings of this study is available at http://gepia.cancer-pku.cn/detail.php?gene. The CGGA data were derived from the 301 dataset available at http://www.cgga.org.cn/download.jsp. All other data supporting the findings of this study are available from the corresponding authors upon reasonable request. Source data are provided with this paper.

References

  1. Reifenberger, G., Wirsching, H. G., Knobbe-Thomsen, C. B. & Weller, M. Advances in the molecular genetics of gliomas—implications for classification and therapy. Nat. Rev. Clin. Oncol. 14, 434–452 (2017).

    Article  CAS  PubMed  Google Scholar 

  2. Aldape, K. et al. Challenges to curing primary brain tumours. Nat. Rev. Clin. Oncol. 16, 509–520 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Brennan, C. W. et al. The somatic genomic landscape of glioblastoma. Cell 155, 462–477 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Neftel, C. et al. An integrative model of cellular states, plasticity, and genetics for glioblastoma. Cell 178, 835–849.e21 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Furnari, F. B., Cloughesy, T. F., Cavenee, W. K. & Mischel, P. S. Heterogeneity of epidermal growth factor receptor signalling networks in glioblastoma. Nat. Rev. Cancer 15, 302–310 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Thorne, A. H., Zanca, C. & Furnari, F. Epidermal growth factor receptor targeting and challenges in glioblastoma. Neuro Oncol. 18, 914–918 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Westphal, M., Maire, C. L. & Lamszus, K. EGFR as a target for glioblastoma treatment: an unfulfilled promise. CNS Drugs 31, 723–735 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Prados, M. D. et al. Phase II study of erlotinib plus temozolomide during and after radiation therapy in patients with newly diagnosed glioblastoma multiforme or gliosarcoma. J. Clin. Oncol. 27, 579–584 (2009).

    Article  CAS  PubMed  Google Scholar 

  9. Guo, J. U., Agarwal, V., Guo, H. & Bartel, D. P. Expanded identification and characterization of mammalian circular RNAs. Genome Biol. 15, 409 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  10. Salzman, J., Chen, R. E., Olsen, M. N., Wang, P. L. & Brown, P. O. Cell-type specific features of circular RNA expression. PLoS Genet. 9, e1003777 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Memczak, S. et al. Circular RNAs are a large class of animal RNAs with regulatory potency. Nature 495, 333–338 (2013).

    Article  CAS  PubMed  Google Scholar 

  12. You, X. et al. Neural circular RNAs are derived from synaptic genes and regulated by development and plasticity. Nat. Neurosci. 18, 603–610 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Kristensen, L. S. et al. The biogenesis, biology and characterization of circular RNAs. Nat. Rev. Genet. 20, 675–691 (2019).

    Article  CAS  PubMed  Google Scholar 

  14. AbouHaidar, M. G., Venkataraman, S., Golshani, A., Liu, B. & Ahmad, T. Novel coding, translation, and gene expression of a replicating covalently closed circular RNA of 220 nt. Proc. Natl Acad. Sci. USA 111, 14542–14547 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Vo, J. N. et al. The landscape of circular RNA in cancer. Cell 176, 869–881.e13 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Guarnerio, J. et al. Intragenic antagonistic roles of protein and circRNA in tumorigenesis. Cell Res. 29, 628–640 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Zhang, M. et al. A peptide encoded by circular form of LINC-PINT suppresses oncogenic transcriptional elongation in glioblastoma. Nat. Commun. 9, 4475 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  18. Glazar, P., Papavasileiou, P. & Rajewsky, N. circBase: a database for circular RNAs. RNA 20, 1666–1670 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Ingolia, N. T., Brar, G. A., Rouskin, S., McGeachy, A. M. & Weissman, J. S. The ribosome profiling strategy for monitoring translation in vivo by deep sequencing of ribosome-protected mRNA fragments. Nat. Protoc. 7, 1534–1550 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. van Heesch, S. et al. The translational landscape of the human heart. Cell 178, 242–260.e29 (2019).

    Article  PubMed  Google Scholar 

  21. Alvarado, A. G. et al. Coordination of self-renewal in glioblastoma by integration of adhesion and microRNA signaling. Neuro Oncol. 18, 656–666 (2016).

    Article  CAS  PubMed  Google Scholar 

  22. Bao, S. et al. Glioma stem cells promote radioresistance by preferential activation of the DNA damage response. Nature 444, 756–760 (2006).

    Article  CAS  PubMed  Google Scholar 

  23. Suzuki, H. et al. Characterization of RNase R-digested cellular RNA source that consists of lariat and circular RNAs from pre-mRNA splicing. Nucleic Acids Res. 34, e63 (2006).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Schneider, T., Schreiner, S., Preusser, C., Bindereif, A. & Rossbach, O. Northern blot analysis of circular RNAs. Methods Mol. Biol. 1724, 119–133 (2018).

    Article  CAS  PubMed  Google Scholar 

  25. Wang, R. et al. Glioblastoma stem-like cells give rise to tumour endothelium. Nature 468, 829–833 (2010).

    Article  CAS  PubMed  Google Scholar 

  26. Zhang, M. et al. A novel protein encoded by the circular form of the SHPRH gene suppresses glioma tumorigenesis. Oncogene 37, 1805–1814 (2018).

    Article  CAS  PubMed  Google Scholar 

  27. Pamudurti, N. R. et al. Translation of circRNAs. Mol. Cell 66, 9–21.e7 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Bulstrode, H. et al. Elevated FOXG1 and SOX2 in glioblastoma enforces neural stem cell identity through transcriptional control of cell cycle and epigenetic regulators. Genes Dev. 31, 757–773 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Chuang, T. J. et al. Integrative transcriptome sequencing reveals extensive alternative trans-splicing and cis-backsplicing in human cells. Nucleic Acids Res. 46, 3671–3691 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Zhang, X. O. et al. Complementary sequence-mediated exon circularization. Cell 159, 134–147 (2014).

    Article  CAS  PubMed  Google Scholar 

  31. Zhang, J. X. et al. Unique genome-wide map of TCF4 and STAT3 targets using ChIP-seq reveals their association with new molecular subtypes of glioblastoma. Neuro Oncol. 15, 279–289 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Mogil, J. S. Stats: multiple experiments test biomedical conclusions. Nature 569, 192 (2019).

    Article  CAS  PubMed  Google Scholar 

  33. Levy, D. E. & Lee, C. K. What does Stat3 do? J. Clin. Invest. 109, 1143–1148 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Bleau, A. M. et al. PTEN/PI3K/Akt pathway regulates the side population phenotype and ABCG2 activity in glioma tumor stem-like cells. Cell Stem Cell 4, 226–235 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Wang, X. et al. MYC-regulated mevalonate metabolism maintains brain tumor-initiating cells. Cancer Res. 77, 4947–4960 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Day, B. W. et al. The dystroglycan receptor maintains glioma stem cells in the vascular niche. Acta Neuropathol. 138, 1033–1052 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Qin, M. et al. Hsa_circ_0001649: a circular RNA and potential novel biomarker for hepatocellular carcinoma. Cancer Biomark. 16, 161–169 (2016).

    Article  CAS  PubMed  Google Scholar 

  38. Hu, Q. P., Kuang, J. Y., Yang, Q. K., Bian, X. W. & Yu, S. C. Beyond a tumor suppressor: soluble E-cadherin promotes the progression of cancer. Int. J. Cancer 138, 2804–2812 (2016).

    Article  CAS  PubMed  Google Scholar 

  39. Soncin, F. et al. Abrogation of E-cadherin-mediated cell–cell contact in mouse embryonic stem cells results in reversible LIF-independent self-renewal. Stem Cells 27, 2069–2080 (2009).

    Article  CAS  PubMed  Google Scholar 

  40. Zanca, C. et al. Glioblastoma cellular cross-talk converges on NF-κB to attenuate EGFR inhibitor sensitivity. Genes Dev. 31, 1212–1227 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Vitucci, M. et al. Cooperativity between MAPK and PI3K signaling activation is required for glioblastoma pathogenesis. Neuro Oncol. 15, 1317–1329 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Akhavan, D. et al. De-repression of PDGFRβ transcription promotes acquired resistance to EGFR tyrosine kinase inhibitors in glioblastoma patients. Cancer Discov. 3, 534–547 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Jones, S. A. & Jenkins, B. J. Recent insights into targeting the IL-6 cytokine family in inflammatory diseases and cancer. Nat. Rev. Immunol. 18, 773–789 (2018).

    Article  CAS  PubMed  Google Scholar 

  44. Aldape, K., Zadeh, G., Mansouri, S., Reifenberger, G. & von Deimling, A. Glioblastoma: pathology, molecular mechanisms and markers. Acta Neuropathol. 129, 829–848 (2015).

    Article  CAS  PubMed  Google Scholar 

  45. Downward, J., Parker, P. & Waterfield, M. D. Autophosphorylation sites on the epidermal growth factor receptor. Nature 311, 483–485 (1984).

    Article  CAS  PubMed  Google Scholar 

  46. Ferguson, K. M. Structure-based view of epidermal growth factor receptor regulation. Annu. Rev. Biophys. 37, 353–373 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Comeau, S. R., Gatchell, D. W., Vajda, S. & Camacho, C. J. ClusPro: a fully automated algorithm for protein–protein docking. Nucleic Acids Res. 32, W96–W99 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Lee, T. H., Hirst, D. J., Kulkarni, K., Del Borgo, M. P. & Aguilar, M. I. Exploring molecular–biomembrane interactions with surface plasmon resonance and dual polarization interferometry technology: expanding the spotlight onto biomembrane structure. Chem. Rev. 118, 5392–5487 (2018).

    Article  CAS  PubMed  Google Scholar 

  49. Garrett, T. P. et al. Crystal structure of a truncated epidermal growth factor receptor extracellular domain bound to transforming growth factor alpha. Cell 110, 763–773 (2002).

    Article  CAS  PubMed  Google Scholar 

  50. Wells, A. et al. Ligand-induced transformation by a noninternalizing epidermal growth factor receptor. Science 247, 962–964 (1990).

    Article  CAS  PubMed  Google Scholar 

  51. Caldieri, G. et al. Reticulon 3-dependent ER–PM contact sites control EGFR nonclathrin endocytosis. Science 356, 617–624 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Mellinghoff, I. K. et al. Molecular determinants of the response of glioblastomas to EGFR kinase inhibitors. N. Engl. J. Med. 353, 2012–2024 (2005).

    Article  CAS  PubMed  Google Scholar 

  53. Vivanco, I. et al. Differential sensitivity of glioma- versus lung cancer-specific EGFR mutations to EGFR kinase inhibitors. Cancer Discov. 2, 458–471 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Lee, J. C. et al. Epidermal growth factor receptor activation in glioblastoma through novel missense mutations in the extracellular domain. PLoS Med. 3, e485 (2006).

    Article  PubMed  PubMed Central  Google Scholar 

  55. Song, X. et al. Circular RNA profile in gliomas revealed by identification tool UROBORUS. Nucleic Acids Res. 44, e87 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  56. Mellinghoff, I. K., Cloughesy, T. F. & Mischel, P. S. PTEN-mediated resistance to epidermal growth factor receptor kinase inhibitors. Clin. Cancer Res. 13, 378–381 (2007).

    Article  CAS  PubMed  Google Scholar 

  57. Fenton, T. R. et al. Resistance to EGF receptor inhibitors in glioblastoma mediated by phosphorylation of the PTEN tumor suppressor at tyrosine 240. Proc. Natl Acad. Sci. USA 109, 14164–14169 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Chen, S., Zhou, Y., Chen, Y. & Gu, J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 34, i884–i890 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  59. Salzman, J., Gawad, C., Wang, P. L., Lacayo, N. & Brown, P. O. Circular RNAs are the predominant transcript isoform from hundreds of human genes in diverse cell types. PLoS ONE 7, e30733 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Cohen, D. R. & Townsend, C. A. A dual role for a polyketide synthase in dynemicin enediyne and anthraquinone biosynthesis. Nat. Chem. 10, 231–236 (2018).

    Article  CAS  PubMed  Google Scholar 

  61. van Galen, P. et al. Reduced lymphoid lineage priming promotes human hematopoietic stem cell expansion. Cell Stem Cell 14, 94–106 (2014).

    Article  PubMed  Google Scholar 

  62. Yang, L. et al. Metadherin/astrocyte elevated gene-1 positively regulates the stability and function of forkhead box M1 during tumorigenesis. Neuro Oncol. 19, 352–363 (2017).

    CAS  PubMed  Google Scholar 

  63. Ohnishi, T., Matsumura, H., Izumoto, S., Hiraga, S. & Hayakawa, T. A novel model of glioma cell invasion using organotypic brain slice culture. Cancer Res. 58, 2935–2940 (1998).

    CAS  PubMed  Google Scholar 

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Acknowledgements

This study was approved by the IRB of the First Affiliated Hospital of Sun Yat-sen University. We gratefully thank all patients who participated in these studies. We also sincerely thank J. Rich for providing the GSCs and P. Xiang for providing the iPSC-derived human NSCs. This work was supported in part by the National Natural Science Outstanding Youth Foundation of China (81822033 to N.Z.), the National Key Research and Development Program of China (2016YFA0503000 to N.Z.), the National Natural Science Foundation of China (81572477 and 81772683 to N.Z.), the Guangdong Innovative and Entrepreneurial Research Team Program (2016ZT06S638 to B.L.), and the Lou and Jean Malnati Brain Tumor Institute at Northwestern Medicine (S.-Y.C.). We thank D. Tiek for reading, editing and commenting on this manuscript. We also thank S. Xiao and T. Huang for helping with the graphical abstract.

Author information

Author notes

  1. These authors contributed equally: Xinya Gao, Xin Xia, Fanying Li, Maolei Zhang.

Authors and Affiliations

  1. Department of Neurosurgery, The First Affiliated Hospital of Sun Yat-sen University, Guangdong Provincial Key Laboratory of Brain Function and Disease, Guangdong Translational Medicine Innovation Platform, Guangzhou, China

    Xinya Gao, Xin Xia, Fanying Li, Maolei Zhang, Huangkai Zhou, Xujia Wu, Jian Zhong, Kun Zhao & Nu Zhang

  2. Gene Denovo Biotechnology (Guangzhou), Guangzhou, China

    Huangkai Zhou

  3. Beijing Neurosurgical Institute, Capital Medical University, Beijing, China

    Zheng Zhao & Tao Jiang

  4. Department of Pathology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China

    Dawei Liu

  5. Department of Scientific Research Section, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China

    Feizhe Xiao

  6. GenomiCare Biotechnology (Shanghai), Shanghai, China

    Qiang Xu

  7. Department of Biochemistry and Molecular Biology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China

    Bo Li

  8. The Ken and Ruth Davee Department of Neurology, Lou and Jean Malnati Brain Tumor Institute, The Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA

    Shi-Yuan Cheng

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Contributions

Conceptualization: N.Z.. Data production, analysis and investigation: X.G., X.X., F.L., M.Z., K.Z., H.Z., X.W., J.Z., D.L., Q.X., F.X., N.Z. and S.-Y.C. Resources: Q.X., B.L., Z.Z. and T.J. Writing, reviewing and editing: N.Z., X.G. and S.-Y.C. Supervision: N.Z. Funding acquisition: N.Z. Comments and revision: S.-Y.C.

Corresponding authors

Correspondence to Shi-Yuan Cheng or Nu Zhang.

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Peer review information Nature Cell Biology thanks Justin Lathia, Igor Vivanco and Markus Landthaler for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Profiling of circular RNAs in GBM and NB; in GSCs and normal cells. (Related to Fig. 1).

a, Venn diagram of circRNAs derived from different genomic regions. Data was from GBM samples and paired NB. b, RNA-seq read of abundance distributions of identified circRNAs. Data originated from GBM samples and paired adjacent normal tissues. X-axis: back-spliced read numbers of circRNAs. Y-axis: abundance of circRNAs classified by different read numbers. The majority of circRNAs identified were confirmed by more than 10 reads. c, Differentially expressed circRNAs (DEcRs). Data originated from GBM samples and paired adjacent normal tissues. DEcRs with p < 0.01 and fold change > 2 were considered significant. d, Volcano diagram of DEcRs from GBM samples and paired adjacent normal tissues. Circ-E-cad RNA was highly expressed in GBM samples (p < 0.01). e, Left: 4 circRNAs with coding potential in both brain tissues and hearts. Right: 10 differentially expressed coding circRNAs with circBase annotation and their RPFs in GBM and normal brain tissues.

Extended Data Fig. 2 Expression of circ-E-cad RNA in GBM; identification of IRES in circ-E-cad RNA; characterization of the anti-C-E-cad antibody (Related to Fig. 2).

a, qPCR of the relative expression levels of 10 differential protein-coding circRNAs GBM and normal tissues, n = 44 biologically independent samples, data were presented as boxes containing the first and third quartiles. The whiskers indicate the maxima and minima. Wilcoxon test, **p = 0.005, ***p < 0.001. In GSCs and NSC/NHA. Circ-E-cad RNA had lowest expression in normal brain tissues among all candidate circRNAs, n = 3 independent experiments, data were presented as the mean ± SD, two-sided t test, the p value was detailed in Source data. b, Upper, exons 7-10 of E-cadherin formed circ-E-cad RNA. Lower left, RT-PCR of circular and linear E-cadherin RNA in GSC H2S with or without RNase R treatment.Lower right, Sanger sequencing. n = 3 independent experiments. c, Left, sketches of the strategy for circular RNA based IRES verification. Right, WT or different truncated IRES predicated in circ-E-cad RNA in circ-Rluc-IRES report vector as indicated. n = 3 independent experiments. data were presented as the mean ± SD, two-sided t test, ***p < 0.001. d, Upper, left, a Coomassie blue-stained gel; right, anti-circ-E-Cad antibody validation by IB. BL peptide, blocking peptide with the 14a.a. peptide sequence. Lower, IHC. anti-circ-E-Cad antibody validation in a clinical GBM tumor sample. n = 3 independent experiments. scale bar, 250 μm e, MS/Mass-spectra identified C-E-cad unique 14a.a. peptide sequences in GSCH2S and 387. f, IB of C-E-Cad in 14 randomly selected GBM samples (cohort 2 and cohort 3) and their paired NB. n = 3 independent experiments. g, Two-sided, Log-rank analysis of GBM patients (n = 45 biologically independent samples) from cohort 3 correlated with C-E-Cad levels (left); CGGA database with C-E-Cad levels (middle) and E-Cad levels (right).***p < 0.001.

Source data

Extended Data Fig. 3 C-E-cad, but not circ-E-cad RNA, promotes GSC self-renewal and survival. (Related to Fig. 3).

a, IB of indicated proteins in GSC4121 with indicated modifications. b, LDA assay and percentage of EdU-positive of GSC4121. c, The relative invasion depth of GSC4121. d, The percentage of SA-β-Gal positive cells of GSC387, 4121, H2S with indicated modifications. e, IB of indicated proteins in GSC387, 4121, and H2S with indicated modifications. f, Upper, BLI images of in vivo tumorigenicity using GSC4121 with indicated modifications. Lower left, tumor volumes. Lower right, Two-sided, Log-rank analysis of mice intracranially implanted with GSC4121 with indicated modifications. g, Left, a shRNA-resistant linearized C-E-cad vector and a mutated circ-E-cad RNA vector. Right, an adenine was inserted after the ATG start codon. h, qPCR of relative circ-E-cad RNA level in GSC387, 4121 and H2S with indicated modifications. i, IB of indicated proteins in GSC387 and 4121 with stable circ-E-cad RNA KD and re-expression of a linearized C-E-cad (resistant to junction shRNA), and in GSCH2S overexpressing a linearized C-E-Cad or a mutated circ-E-cad RNA (insertion A). j, LDA assay of GSC387 and 4121 with indicated modifications. k, Brain slice invasion of GSC387, 4121, and H2S with indicated modifications. l, Upper, tumor volumes of GSC387, 4121 and H2S with indicated modifications. Lower, Two-sided, Log-rank analysis of mice injected with GSC387, 4121 and H2S with indicated modifications, ***p < 0.001. In a-e,h-k, n = 3 independent experiments. In f,l, n = 5 biologically independent samples. In b-d,f,h-l, data was presented as mean ± SD. Two-sided t test, ***p < 0.001.

Source data

Extended Data Fig. 4 Flanking ALU sequences are required to form circ-E-cad RNA; C-E-Cad activates STAT3, AKT and ERK signalling and independent functions of C-E-cad and E-cadherin. (Related to Figs. 3 and 4).

a, The illustration of side flanking ALU sequences of circ-E-cad RNA and the CRISPAR/Cas9 strategy for KO downstream ALU sequences b, qPCR of circ-E-cad RNA in ALU KO GSC387 and 4121 with indicated modifications. c, IB in ALU KO GSC387 and 4121 with indicated modifications and controls. d, LDA assay in GSC387 and 4121 with indicated modifications.e. KEGG pathway enrichment analysis of circ-E-cad RNA stable KD GSC4121. f, IB of GSC4121 with indicated modifications. g, IF. p-STAT3 localization was determined in C-E-cad stable KD GSC387 4121 and in a circ-E-cad RNA or a linearized C-E-cad-overexpressing GSCH2S. scale bar, 20μm. h, LDA assay in GSC387, 4121 and GSCH2S with indicated modifications. i, IB in in GSC387, 4121 and GSCH2S with indicated modifications. j, Upper, Strategy of E-cadherin KO by CRISPAR/Cas9 system in GSC23, 17, and NSC. Lower, qPCR of Circ-E-Cad and E-Cadherin in GSC23, 17, and NSC with indicated modifications. k, IB in NSC-WT, NSC-E-Cadherin KO cells. Circ-E-Cad RNA or E-cadherin was re-expressed in the indicated cells. l, LDA assay, Edu assay and brain slice invasion assay in NSC cell lines with indicated modifications. m, The percentage of SA-β-Gal positive cells of GSC387, 4121, and H2S with indicated modifications. n, IB of senescence markers p16, p21 and apoptosis related Caspase3 and PARP of GSC387, 4121, and H2S with indicated modifications.In a-d, f-n, n = 3 independent experiments. In b,d,h,j,l,m, data were shown as mean ± SD, two-sided t test,***p < 0.001.

Source data

Extended Data Fig. 5 Recombinant C-E-cad activates EGFR. (Related to Fig. 5).

a, IB. rC-E-cad with different concentrations were used to treat indicated cells. EGF was used as a positive control. b, IB for GSCH2S and GSC17 with indicated modifications. c, The percentage of SA-β-Gal positive cells of GSCH2S and GSC17 E-cadherin KO with indicated modification. d, IB of GSCH2S and GSC17 E-cadherin KO with indicated modification. e, Mass spectrometry analysis identified EGFR peptide sequences that was pulled down by the anti-C-E-cad antibody. (IB for GSC387 and 4121 with indicated modifications were separately treated with or without rC-E-cad proteins.). g, ELISA of IL-6 level in GSC387 and 4121 with indicated modifications. h, IB. Left, GSC4121 with stable KD of EGFR, Met, PDGFRA, or IL6R and treated with or without rC-E-cad (200 ng/ml). Right. GSC4121 with stable EGFR KD were re-expressed with WT EGFR or EGFR with a Y1068A mutation, then treated with rC-E-cad. i, IB. non-GSC387 and 4121 were modified or treated as indicated. j, LDA assay for non-GSC387 and 4121 with indicated modification or treatments. k, IB. EGFR-HIS, GST-C-E-Cad and GST-C-E-Cad-△14aa was purified and GST pull down assay was applied. l, Docking analysis of C-E-cad and EGFR CR2 domain. m, Tumor volume in GSC387, 4121 and H2S with indicated modifications. n, Two-sided, Log-rank analysis of mice intracranially implanted with GSC387, 4121 and H2S with indicated modifications, ***p < 0.001o. Tumor volumes and Two-sided, Log-rank analysis of mice bearing indicated GSC tumor xenografts with 5 mice per group. ***p < 0.001In a-k, n = 3 independent experiments. In m-o, n = 5 independent experiments. In c,g,j,m.o, data were shown as mean ± SD, two-sided t test,***p < 0.001.

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Extended Data Fig. 6 C-E-cad interacts and activates EGFR. (Related to Fig. 7).

a, IF. Colocalizations of p-Y1068-EGFR and LAMP1 or Rab11 were detected in GSC 17-E-cad KO treated with EGF or recombinant C-E-cad at indicated timepoints. Scale bar, 20 µm. b, IB of EGFR and EGFRvIII expression in indicated cell lines. c, CRISPAR/Cas9-induced EGFR KO strategy. d, DNA gel electrophoresis of RT-PCR for EGFR in GSC17-WT, 17-KO, NSC-WT, and NSC-KO cells. e, IB of EGFR in GSC17-WT, 17-KO, NSC-WT, and NSC-KO cells. f, Sanger sequencing of CRISPAR/Cas9-induced EGFR KO in indicated cells. g, IB of p-STAT3, p-EGFR, STAT3, and EGFR in WT and E-cadherin KO together with EGFR KO and EGFR WT or EGFRvIII re-expressed NSCs. Recombinant C-E-cad treatment (200 ng/ml) is indicated. h, IB. p-STAT3, p-EGFR, STAT3, and EGFR in GSC 4121 with stable EGFR KD and with stable C-E-cad KD and EGFRvIII re-expression. i, IB of p-STAT3, p-EGFR, STAT3, and EGFR in WT and E-cadherin KO together with EGFR KO and EGFR WT or EGFRvIII re-expressed NSCs treated with a synthetic C-E-cad C-terminal 14 a.a. peptide (200 ng/ml) (left) or C-E-cad C-terminal mutant 14 a.a. peptide (200 ng/ml) (right). In a-b,d,e,g-i, n = 3 independent experiments.

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Extended Data Fig. 7 Clinical implication of the anti-C-E-cad antibody in vitro. (Related to Fig. 8).

a, IHC and IB. Representative C-E-cad and p-STAT3 levels were determined in GBM samples by IHC (left) and IB (right). Scale bar, 250 µm. b, Left, IB of p-STAT3 in GSC387 and 4121 cells treated with purified C-E-Cad and Nimotuzumab (N_mab). Right, IB of p-STAT3 and p-EGFR in GSC387 4121 cells treated with Nimotuzumab (N_mab) and C-E-Cad antibody. c, Cell viability was detected in GSC387 and 4121 cells treated with Nimotuzumab (N_mab) and C-E-Cad antibody, ***p < 0.001. d, GSC387 and 4121 cells treated with Nimotuzumab + C-E-Cad antibody or transfected with shRNAs targeting EGFR. The levels of p-STAT3 and p-EGFR were detected. e, Cell viability was detected in GSC387 and 4121 cells with indicated modifications, ***p < 0.001. f, IB of p-STAT3 and p-EGFR in GSC387 and 4121 cells treated with Laptinib and C-E-Cad antibody. g, Cell viability was detected in GSC387 4121 cells treated with Laptinib and C-E-Cad antibody, ***p < 0.001. h, IP-IB of indicated proteins. HEK293T cells were co-transfected with EGFR-WT/EGFR-G958V and C-E-Cad-HA, Cells were then harvested and subjected to IP assay. i, GSC387, 4121, and 17 were transfected with shRNAs targeting EGFR and re-expressed with EGFR-G958V. Cells were treated with or without C-E-Cad antibody. IB of p-EGFR was detected. j, Cell viability in GSC387,4121 and 17 cells described in (i). In 387,*p = 0.026,**p = 0.006,***p < 0.001,in 4121, *p = 0.01,**p = 0.001,***p < 0.001,in 17, *p = 0.022,**p = 0.009,***p < 0.001.In a-j. n = 3 independent experiments. In c,e,g,j, data were shown as mean ± SD, two-sided t test.

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Extended Data Fig. 8 Clinical implication of the anti-C-E-cad antibody in vivo. (Related to Fig. 8).

a, In vivo tumorigenicity assay using GSC4121 treatment with Nimotuzumab (N_mab), anti-C-E-cad antibodies or in combination, (n = 10 animals). BLI images (Left) indicated brain BITC tumor xenografts. Right, IHC of p-EGFR expression in indicated GSC tumours, scale bar, 250μm (n = 3 animals). b, Left, Relative intensity of fluorescent index of BLI that indicate tumor growth of GSC4121 brain tumor xenografts in animals treated with Nimotuzumab (N_mab), anti-C-E-cad antibodies or in combination. Data were presented as mean ± SD, two-sided t test, ***p < 0.001. Middle, Two-sided, Log-rank analysis of mice treated with indicated therapeutic strategies. Right, P values were calculated, n = 10 animals. c, In vivo tumorigenicity assay using GSC387 and 4121 and treatment with Laptinib, anti-C-E-cad antibodies or in combination. BLI images at different time point, (n = 10 animals). d, Left: Relative intensity of fluorescent index of BLI that indicate tumor growth of GSC387 and 4121 brain tumor xenografts in animals treated with Laptinib (1 μg/μl, 3 μl), anti-C-E-cad antibodies or in combination, n = 10 animals. Data were presented as mean ± SD, two-sided t test, ***p < 0.001.Middle, Two-sided, Log-rank analysis of mice treated with indicated therapeutic strategies. Right, P values were calculated, (n = 10 animals).

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Supplementary Tables 1–13

Supplementary tables for the manuscript, including lists of key reagents and precise P values.

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Gao, X., Xia, X., Li, F. et al. Circular RNA-encoded oncogenic E-cadherin variant promotes glioblastoma tumorigenicity through activation of EGFR–STAT3 signalling. Nat Cell Biol 23, 278–291 (2021). https://doi.org/10.1038/s41556-021-00639-4

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