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EGFR ligand shifts the role of EGFR from oncogene to tumour suppressor in EGFR-amplified glioblastoma by suppressing invasion through BIN3 upregulation

Nature Cell Biology volume 24, pages 1291–1305 (2022)Cite this article

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Abstract

The epidermal growth factor receptor (EGFR) is a prime oncogene that is frequently amplified in glioblastomas. Here we demonstrate a new tumour-suppressive function of EGFR in EGFR-amplified glioblastomas regulated by EGFR ligands. Constitutive EGFR signalling promotes invasion via activation of a TAB1–TAK1–NF-κB–EMP1 pathway, resulting in large tumours and decreased survival in orthotopic models. Ligand-activated EGFR promotes proliferation and surprisingly suppresses invasion by upregulating BIN3, which inhibits a DOCK7-regulated Rho GTPase pathway, resulting in small hyperproliferating non-invasive tumours and improved survival. Data from The Cancer Genome Atlas reveal that in EGFR-amplified glioblastomas, a low level of EGFR ligands confers a worse prognosis, whereas a high level of EGFR ligands confers an improved prognosis. Thus, increased EGFR ligand levels shift the role of EGFR from oncogene to tumour suppressor in EGFR-amplified glioblastomas by suppressing invasion. The tumour-suppressive function of EGFR can be activated therapeutically using tofacitinib, which suppresses invasion by increasing EGFR ligand levels and upregulating BIN3.

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Fig. 1: Ligand-induced EGFR signalling inhibits invasion through upregulation of BIN3.
Fig. 2: EGFR levels determine the invasion response to EGFR ligand via BIN3 regulation.
Fig. 3: BIN3 inhibits invasiveness of glioma cells through its interaction with DOCK7.
Fig. 4: TGFα overexpression prolongs survival, reduces invasiveness and increases proliferation in an orthotopic GBM mouse model.
Fig. 5: Constitutive EGFR signalling induces a TAB1–TAK1–p65–EMP1 pathway.
Fig. 6: Tofacitinib inhibits invasion of glioma cells by EGR1-mediated BIN3 upregulation.
Fig. 7: Tofacitinib prolongs survival, reduces invasiveness and increases proliferation in an orthotopic GBM mouse model.
Fig. 8: TCGA analysis of EGFR and EGFR ligands in GBM.

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Data availability

RNA-seq and whole-exome-sequencing data that support the findings of this study have been deposited in the NCBI Sequence Read Archive with the accession numbers PRJNA812870 and PRJNA827815. Publicly available whole-exome-sequencing data from the NCBI Sequence Read Archive under accession number PRJNA543854 (SRX5870263) were used. Previously published microarray data are available in Supplementary Table 1 of the publication by Ramnarain and colleagues1. Mass spectrometry data have been deposited in https://massive.ucsd.edu/ with the dataset identifier MSV000089272. The human GBM data were derived from the TCGA Research Network: http://cancergenome.nih.gov/. Source data are provided with this paper. All other data supporting the findings of this study are available from the corresponding author on reasonable request.

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Acknowledgements

This work was supported in part by funding from the Department of Veteran’s Affairs (grant no. 2I01BX002559-08) and the National Institutes of Health (grant nos 1R01CA244212-01A1 and 1R01NS119225-01A1) to A.A.H. D.E.G. is supported by a National Cancer Institute (NCI) Midcareer Investigator Award in Patient-Oriented Research (grant no. K24CA201543-01). S.B. is supported by grants from the National Institutes of Health (grant nos R01CA258381 and R01CA246807) and the National Aeronautics and Space Administration (grant no. 80NSSC20K0732). C.-M.C.’s research is supported by NIH grant no. 1RO1CA251698 and CPRIT grant no. RP190077. D.Z. was supported by NIH grant no. R01 CA194578, S.K.M. is supported by awards from the Cancer Prevention and Research Institute of Texas (grant no. RR190034) and the NCI (grant no. K22CA237752). Research reported in this publication was supported in part by the Harold C. Simmons Comprehensive Cancer Center’s Biomarker Research Core, which are supported by NCI Cancer Center Support Grant 1P30 CA142543–03. J.N.S. was supported by the MIT/Mayo Physical Sciences Center for Drug Distribution and Efficacy in Brain Tumours (grant no. U54CA210180). We acknowledge NIH shared instrumentation grant no. 1S10OD023552-01 that funded the MRI equipment. We thank S. -Y. Cheng (Northwestern University) for the GSC11 cells. We thank D. -H. Kim (Johns Hopkins University) for advice on the use of patterned nanosurfaces.

Author information

Authors and Affiliations

  1. Department of Neurology, University of Texas Southwestern Medical Center, Dallas, TX, USA

    Gao Guo, Ke Gong, Nicole Beckley, Yue Zhang, Xiaoyao Yang, Arifa Nayab, Jennifer Jenks, Michael Youssef, Edward Pan & Amyn A. Habib

  2. Hubei Province Key Laboratory of Allergy and Immunology and Department of Immunology, School of Basic Medical Sciences, Taikang Medical School, Wuhan University, Wuhan, China

    Ke Gong

  3. Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA

    Rati Chkheidze, Kimmo J. Hatanpaa & Prasad Koduru

  4. Department of Neurosurgery, University of Texas Southwestern Medical Center, Dallas, TX, USA

    Tomas Garzon-Muvdi, Bryan Wohlfeld, Toral Patel, Bruce Mickey & Kalil Abdullah

  5. Eugene McDermott Center for Human Growth and Development, University of Texas Southwestern Medical Center, Dallas, TX, USA

    Adwait Amod Sathe, Yan Liu, Chao Xing & David E. Gerber

  6. Department of Population and Data Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA

    Chao Xing

  7. Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX, USA

    Chao Xing

  8. Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, USA

    Shwu-Yuan Wu, Cheng-Ming Chiang, David E. Gerber & Amyn A. Habib

  9. Department of Biochemistry, University of Texas Southwestern Medical Center, Dallas, TX, USA

    Shwu-Yuan Wu & Cheng-Ming Chiang

  10. Department of Pharamacology, University of Texas Southwestern Medical Center, Dallas, TX, USA

    Shwu-Yuan Wu & Cheng-Ming Chiang

  11. Department of Neurosurgery, University of Texas Health San Antonio, San Antonio, TX, USA

    Bipasha Mukherjee & Sandeep Burma

  12. Department of Biochemistry and Structural Biology, University of Texas Health San Antonio, San Antonio, TX, USA

    Sandeep Burma

  13. Division of Hematology–Oncology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA

    David E. Gerber

  14. Department of Quantitative Heath Sciences, Mayo Clinic, Rochester, MN, USA

    Shulan Tian

  15. Department of Radiation Oncology, Mayo Clinic, Rochester, MN, USA

    Jann N. Sarkaria

  16. Department of Pediatrics and Children’s Medical Center Research Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA

    Samuel K. McBrayer

  17. Departments of Biomedical Engineering and Cancer Biology, Wake Forest School of Medicine, Winston Salem, NC, USA

    Dawen Zhao

  18. Peter O’Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA

    Amyn A. Habib

  19. VA North Texas Health Care System, Dallas, TX, USA

    Amyn A. Habib

Authors
  1. Gao Guo
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  2. Ke Gong
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Contributions

G.G. and A.A.H. designed experiments. G.G., K.G., N.B., Y.Z., X.Y., A.N., J.J., T.G.-M., P.K., S.-Y.W. and C.-M.C. performed or assisted with experiments. J.N.S., R.C., K.J.H., K.A., S.K.M., B. Mickey, B.W. and T.P. provided cell lines, PDX or human tissue specimens. Bioinformatics analyses were conducted by K.G., C.X., A.A.S. and Y.L. G.G., D.E.G., B. Mukherjee, S.B., S.T., D.Z., C.-M.C., E.P., M.Y. and A.A.H. analysed data. G.G. and A.A.H. wrote the manuscript. Study conception and supervision was conducted by A.A.H.

Corresponding author

Correspondence to Amyn A. Habib.

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Competing interests

The Department of Veteran’s Affairs has filed a patent (PCT/US2021/018716) on the use of tofacitinib in GBM, with A.A.H. as the inventor. The other authors declare no competing interests.

Peer review

Peer review information

Nature Cell Biology thanks Igor Vivanco, Nu Zhang and William A. Weiss 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 Ligand-induced EGFR signalling suppresses invasion, while constitutive EGFR signalling induces invasion.

a, PDXs and neurospheres used in the study. b, Matrigel invasion assay of cells in the presence or absence of EGF(50 ng/ml). c, Immunoblot of EGFR expression. d, Matrigel invasion assay of cells treated with EGF for the indicated times. e, Matrigel invasion assay of GBM12 with various EGFR ligands. f, Immunoblot of the indicated proteins in GBM12 treated with EGFR ligands. g-h, Similar experiments in GBM6. i-j, Immunoblot of pEGFR and pERK in EGFR siRNA knockdown cells and in U251 and GS622 cells treated with vehicle or EGF for 5 min. k, Matrigel invasion assay of GBM6 treated with erlotinib (1 µM) for the indicated times. l, Efficacy of erlotinib was analysed by Western blot. m-n, Matrigel invasion assay of cells treated with the indicated concentrations of erlotinib. o, Immunoblot demonstrating efficacy of erlotinib (Erl). p, Matrigel invasion assay of GBM12 with IgG or cetuximab. q, Immunoblot of pEGFR and EGFR expression in GBM12 treated with EGF, IgG or Cetuximab (5 min.). r, Matrigel invasion assay of EGFRwt-overexpressing GBM14 with IgG or cetuximab. s, Immunoblot of the indicated proteins in EGFR overexpressing GBM14 treated with EGF, IgG or cetuximab for 48 h. t, Immunoblot of the indicated proteins in EGFR overexpressing GBM14 treated with or without EGF. u, Quantification of Western blot band intensity with actin as the reference protein. v, Matrigel invasion assay of GBM12 with the indicated drugs. w, Immunoblot of EGFR and pEGFR in cetuximab pretreated GBM12 with the indicated drugs. x, Matrigel invasion assay of EGFRvIII overexpressing GBM14 in the presence or absence of EGF. y, Immunoblot of EGFR and pEGFR in EGFRvIII overexpressing GBM14 treated with vehicle or EGF for 5 min. z, Representative static images showing progression of invasion in cells with EGF. aa, Quantification of invasion distance of neurospheres. Western blot images are representative of three independent biological replicates. Actin served as the loading control. Data are represented as mean ± SEM from three independent experiments. Statistical significance was determined by two-tailed one-sample Student’s t-test (b, d, k, p, u), or by one-way ANOVA adjusted by Bonferroni’s correction (e, g, m, n, r, v, x), or by two-tailed unpaired Student’s t-test (aa). *P<0.05, **P< 0.01, ***P< 0.001, ****P< 0.001, n.s. not significant. Numerical source data, statistic, exact P values and unprocessed blots are available as Source Data.

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Extended Data Fig. 2 Suppression of invasion induced by EGF is mediated by an EGFR-BIN3-DOCK7 pathway.

a, Immunoblot of pFAK and FAK expression in cells treated with EGF (50 ng/ml) for the indicated times. b, Annexin V/PI positive staining assay of cells treated with EGF. c, BrdU incorporation assay of cells transiently transfected with empty or EGFRwt expression vectors. d, Overexpression of EGFRwt in cells was analysed by Western blot. e, Volcano plot of differentially expressed genes as assessed by RNA-seq in vehicle or EGF treated GBM12. Significantly upregulated BIN3 is highlighted in green (Fold change=2.1, p=0.03). f, BrdU incorporation assay of cells transiently transfected with empty or BIN3 vectors. g, Annexin V/PI positive staining assay of cells transiently transfected with empty or BIN3 expression vectors. h, BIN3 overexpression in cells was analysed by Western blot. i, Matrigel invasion assay of DOCK7 overexpressing cells. Cells were infected with control or DOCK7 lentiviral activation particles, and 72 h after infection invasion assay was performed in the presence or absence of EGF. j, Immunoblot of the indicated proteins in DOCK7 overexpressing cells treated with EGF for 24 h. k, Matrigel invasion assay of cells transiently transfected with empty, Myc-RhoA or Myc-Cdc42 expression vectors in the presence or absence of EGF. l-m, Overexpression of Myc-RhoA and Myc-Cdc42 was analzyed by Western blot. The Western blot images are representative of three independent biological replicates. Actin served as the loading control. The numbers below the blots indicate the relative band intensity of protein against that of actin. Data are represented as mean ± SEM from three independent experiments. Statistical significance was determined by two-way ANOVA adjusted by Bonferroni’s correction (b, g, i, k), or by two-tailed unpaired Student’s t-test (c, f). *P<0.05, **P< 0.01, ***P< 0.001, n.s. not significant. Numerical source data, statistic, exact P values and unprocessed blots are available as Source Data.

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Extended Data Fig. 3 Regulation and biological effects of BIN3.

a, Matrigel invasion of BIN3 overexpressing cells in the presence or absence of EGF (50 ng/ml). b, BIN3 overexpression was analysed by Western blot. c, Schematic diagram of the putative EGR binding sites in BIN3 promoter region together with the corresponding ChIP-qPCR amplicons. d, EGR1 luciferase reporter activity in multiple lines treated with EGF. e, Percentage input done by ChIP-qPCR to assess the EGR1 occupancy of BIN3 gene in multiple lines treated with vehicle (V) or EGF for 24 h. IgG was used as negative control. f, Matrigel invasion assay of Cdc42 or RhoA siRNA knockdown in multiple lines. g-h, Knockdown efficiency of RhoA and Cdc42 siRNA was analysed by Western blot. i, Immunoblot of Cdc42-GTP and total Cdc42 expression in DOCK7 siRNA knockdown cells. j, Cell viability assay of control and DOCK7 siRNA knockdown multiple lines. k, Knockdown efficiency of DOCK7 was analysed by Western blot. l, Immunoblot of Rac1 expression in multiple lines. m, Matrigel invasion assay of cells in the presence or absence of HGF (20 ng/ml). n, Immunoblot of pMet and Met expression in cells treated with HGF for 1 h. o, Immunoblot of immunoprecipitated extracts from cells treated with HGF for 24 h. p, Immunoblot of RhoA-GTP expression in cells treated with HGF (20 ng/ml) for 24 h. The Western blot images are representative of three independent biological replicates. The numbers below the blots indicate the relative band intensity of protein against that of actin. Actin served as the loading control. The numbers below the blots indicate the relative band intensity of protein against that of actin. Data are represented as mean ± SEM from three independent experiments. Statistical significance was determined by two-way ANOVA adjusted by Bonferroni’s correction (a, e), or by two-tailed one- sample Student’s t-test (d, j), or one-way ANOVA adjusted by Bonferroni’s correction (f). *P<0.05, **P< 0.01, ***P< 0.001, ****P< 0.001, n.s. not significant. Numerical source data, statistic, exact P values and unprocessed blots are available as Source Data.

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Extended Data Fig. 4 EGFR ligand overexpression prolongs survival, reduces invasiveness and increases proliferation in orthotopic glioblastoma mouse model.

a, Immunoblot of the indicated proteins in GBM9 stably transfected with empty (GBM9V) or TGFα expression vector (GBM9TGFα). b, Immunoblot of EGFR expression in cells stably transfected with empty, TGFα, or BIN3 expression vectors. c, EGFR copy numbers in cells described in b. d, Immunoblot of EGFR expression in multiple lines cultured in 10% serum for the indicated times. e, EGFR copy numbers in cells described in d. f, Matrigel invasion assay of cells cultured in 10% serum for 8 weeks in the presence or absence of EGF. g, Kaplan–Meier survival curves of mice with GBM9V and GBM9TGFα tumours (n=8/group). h-i, H&E staining, SMI-31 immunostaining (black arrow)and quantification of SMI-31 counts in mouse tumours. j-k, Ki67 immunostaining and quantification of Ki67 positive cells in mouse tumours. l, Immunoblot of EGFR expression in various tumours. m, EGFR copy numbers in mouse tumours compared to fresh explants cultures. n, Immunoblot of BIN3 expression in cells stably overexpressing BIN3 or empty vector. o, Matrigel invasion assay of multiple lines. p, Kaplan–Meier survival curves of mice with GBM12V and GBM12BIN3 tumours (n=8/group). q-r, H&E staining, SMI-31 immunostaining and quantification of SMI-31 counts in mouse tumours. s, ELISA for EGF in GBM12 stably transfected with EGF overexpressing or empty vector. t, Immunoblot of the indicated proteins in EGF-overexpressing GBM12 clones. u, Kaplan–Meier survival curves of mice with GBM12V and GBM12EGF (GBM12EGF_02) tumours (n=6/group). v, H&E staining, SMI-31 immunostaining and quantification of SMI-31 counts in mouse tumours. x-y, Ki67 immunostaining and quantification of Ki67 postive cells in mouse tumours. z-aa, Representative TUNEL staining (black arrows) and quantification of TUNEL positive cells in GBM12 orthotopic tumours from vehicle or EGF treated mice. bb-cc, Representative TUNEL staining and quantification of TUNEL positive cells in mouse tumours. Scale bars: 50 µM. Western blot images are representative of three independent biological replicates. Actin served as the loading control. Data are represented as mean ± SEM from three independent experiments. Statistical significance was determined by one-way ANOVA adjusted by Bonferroni’s correction (c, e, m,s), or by two-tailed one-sample Student’s t-test (f, o), or two-tailed unpaired Student’s t-test (i, k, r, w, y, aa, cc). *P<0.05, **P< 0.01, ***P< 0.001, ****P< 0.001, n.s. not significant. Numerical source data, statistic, exact P values and unprocessed blots are available as Source Data.

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Extended Data Fig. 5 Biological effects of EGFR and STAT activation in GBM cells.

a, The allele frequency of EGFRwt and EGFRvIII in GBM6 and GBM9. b, Matrigel invasion assay of EGFRwt or EGFRvIII overexpressing GBM14 with or without EGF (50 ng/ml). c, Immunoblot of the indicated proteins in EGFRwt or vIII overexpressing GBM14 cells treated with EGF (24 h). d, Matrigel invasion assay of EGFRwt and vIII overexpressing GBM14 with or without of EGF.WT(w): weak expression of WT; WT(s): strong expression of WT. e, Immunoblot of the indicated proteins in EGFRwt and vIII overexpressing GBM14 treated with EGF (24 h). f, Immunoblot of immunoprecipitated extracts from cells treated with EGF (30 min.). g, Immunoblot of the indicated proteins in cells treated with EGF (30 min.). h, BrdU incorporation assay of Shc siRNA knockdown cells treated with EGF. i, Immunoblot of the indicated proteins in Shc siRNA knockdown cells treated with EGF (30 min.). j, BrdU incorporation assay of cells treated with EGF, U0126 or a combination. k, Immunoblot of the indicated proteins in cells treated with EGF or U0126 or a combination (30 min.). l, BrdU incorporation assay of ERK siRNA knockdown cells treated with EGF. m, Knockdown efficiency of ERK was analysed by Western blot. n, Immunoblot of different Tyr resides of pEGFR in multiple lines treated with EGF (30 min.). o, Quantification of Western blot band intensity with actin as reference. p, Immunoblot of the indicated proteins in cells treated with tofacitinib (Tof.). q, ELISA for HB-EGF in the supernatant of STAT1 siRNA knockdown GBM12. r, Immunoblot of pEGFR and pSTAT1 in STAT1 siRNA knockdown GBM12. s, Matrigel invasion assay of control or STAT1 siRNA knockdown GBM12. t, ELISA for BTC in the supernatants of GBM12 treated with tofacitinib (72 h). u, Matrigel invasion assay of STAT3 overexpressing GBM12 in response to tofacitinib. v, Immunoblot of the indicated proteins in STAT3 overexpressing cells treated with tofacitinib. w, Immunoblot of BIN3 in multiple lines treated with EGF, tofacitinib or both (48 h). x, Matrigel invasion assay with EGF or tofacitinib or both. y-aa, Ki67 immunostaining and quantification of KI67 positive cells in GBM12 and GBM9 tumours from tofacitinib treated mice. Scale bars: 50 µM. The Western blot images are representative of three independent biological replicates. Actin served as the loading control. The numbers below the blots indicate the relative band intensity of protein against that of actin. Data are represented as mean ± SEM from three independent experiments. Statistical significance was determined by two-way ANOVA adjusted by Bonferroni’s correction (b, d, h, j, l, u), or by two-tailed one-sample Student’s t-test (o, s), or by two-tailed unpaired Student’s t-test (q, aa), or by one-way ANOVA adjusted by Bonferroni’s correction (x). *P<0.05, **P< 0.01, ***P< 0.001, ****P< 0.001, n.s. not significant. Numerical source data, statistic, exact P values and unprocessed blots are available as Source Data.

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Extended Data Fig. 6 EGF and tofacitinib suppress migration in single-cell analysis.

a, Time-lapse migration speed in GBM12 before and after addition of vehicle (n=67) or EGF (50 ng/ml)(n=63). b, Quantification of migration velocity of GBM12 before and after addition of vehicle or EGF. Cell migration velocity was calculated over a period of 6 h. c, Representative static time-lapse images of the same cell migration before and after addition of EGF. d, Percentage of cell migration speed before and after addition of EGF. e, Time-lapse migration speed in GBM12 before and after addition of vehicle (n=81) or tofacitinib (1 µM) (n=89). f, Quantification of migration velocity of GBM12 before and after addition of vehicle or tofacitinib. g, Representative static time-lapse images of the same cell migration before and after addition of tofacitinib. h, Percentage of cell migration speed before and after addition of tofacitinib. i, Time-lapse migration speed in GBM22 before and after addition of vehicle (n=57) or EGF (n=74). j, Quantification of migration velocity of GBM22 before and after addition of vehicle or EGF. k, Representative static time-lapse images of the same cell migration before and after addition of EGF. l, Percentage of cell migration speed before and after addition of EGF. m, Time-lapse migration speed in GBM22 before and after addition of vehicle (n=61) or tofacitinib (n=53). n, Quantification of migration velocity of GBM22 before and after addition of vehicle or tofacitinib. o, Representative static time-lapse images of the same cell migration before and after addition of tofacitinib. p, Percentage of cell migration speed before and after addition of tofacitinib. Scale bars: 10 µM (c, g, k and o). Whiskers of the boxplot mark the 5th and 95th percentiles, the box marks the 25th to the 75th percentiles with the median (b, f, j, m). **P < 0.001, **** P < 0.0001, n.s. not significant, P values were determined using two-tailed Wilcoxon matched pair tests (b, f, j, n). The results are representative of two independently repeated experiments. Numerical source data, statistic and exact P values are available as Source Data.

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Extended Data Fig. 7 EGFR ligands, EGFR, BIN3 and Sp1 expression in human glioblastoma.

a-c, ELISA for HB-EGF, TGFα and EGF in human glioblastoma lysates. d, Representative immunohistochemical staining of HB-EGF in human glioblastoma. e, Summary of HB-EGF staining in high and low cellular areas across the tissue sections from 20 samples. Score 0 and 1 are defined as low, 2 and 3 are defined as moderate/high. Staining intensity in the two areas were compared using Fisher’s exact test. f, Representative EGFR immunostaining in high cellular (central) and low cellular (infiltrating) areas of human glioblastoma. g, Summary of EGFR staining of the tissue sections from 20 samples. h, Representative Sp1 immunostaining in high cellular and low cellular areas of human glioblastoma. i, Summary of Sp1 staining of the tissue sections from 20 samples. j-l, Ivy Atlas distribution of EGFR, HB-EGF and Sp1 mRNA expression in central and infiltrating areas of human GBM. m, Representative images of fluorescent double staining of HB-EGF (green) and Sp1 (red) in human GBM tissue sections. n, ELISA for HB-EGF in multiple lines transiently transfected with empty or HA-Sp1 vectors. o, HA-Sp1 overexpression was analysed by Western blot. p, ELISA for HB-EGF in Sp1 siRNA knockdown cells. q, Sp1 siRNA knockdown was analysed by Western blotting. r, Overall survival (OS) analysis according to BIN3 mRNA levels in classical GBM patients with amplified EGFR. s, Immunoblot of BIN3 expression in human glioblastoma extracts. t, Scatter plot of HB-EGF and BIN3 expression in human glioblastoma lysates (n=36). u, Kaplan–Meier curves of survival rates for high and low levels of BIN3 assessed by Western blot. The Western blot images are representative of three independent biological replicates. Actin served as the loading control. The numbers below the blots indicate the relative band intensity of protein against that of actin. Scale bars: 50 µM.Data are represented as mean ± SEM from three independent experiments. Significance was determined by Kolmogorov–Smimov test (j, k, l), or by two-tailed unpaired Student’s t-test (n, p), or by log-rank test (r, u). **P< 0.01, ****P< 0.001, n.s. not significant. Numerical source data, statistic, exact P values and unprocessed blots are available as Source Data.

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Supplementary information

Supplementary Information

Gating strategy for flow cytometry used to quantify the ratio of Annexin V+ apoptosis/necrosis cells in Fig. 6r,s and Extended Data Fig. 2b,g.

Reporting Summary

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Supplementary Table 1

File contains a workbook with multiple tabs assigned to Supplementary Tables 1–3.

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Guo, G., Gong, K., Beckley, N. et al. EGFR ligand shifts the role of EGFR from oncogene to tumour suppressor in EGFR-amplified glioblastoma by suppressing invasion through BIN3 upregulation. Nat Cell Biol 24, 1291–1305 (2022). https://doi.org/10.1038/s41556-022-00962-4

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