Glioblastoma multiforme (GBMs) are recurrent lethal brain tumours. Recurrent GBMs often exhibit mesenchymal, stem-like phenotypes that could explain their resistance to therapy. Analyses revealed that recurrent GBMs have increased tension and express high levels of glycoproteins that increase the bulkiness of the glycocalyx. Studies showed that a bulky glycocalyx potentiates integrin mechanosignalling and tissue tension and promotes a mesenchymal, stem-like phenotype in GBMs. Gain- and loss-of-function studies implicated integrin mechanosignalling as an inducer of GBM growth, survival, invasion and treatment resistance, and a mesenchymal, stem-like phenotype. Mesenchymal-like GBMs were highly contractile and expressed elevated levels of glycoproteins that expanded their glycocalyx, and they were surrounded by a stiff extracellular matrix that potentiated integrin mechanosignalling. Our findings suggest that there is a dynamic and reciprocal link between integrin mechanosignalling and a bulky glycocalyx, implying a causal link towards a mesenchymal, stem-like phenotype in GBMs. Strategies to ameliorate GBM tissue tension offer a therapeutic approach to reduce mortality due to GBM.

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  1. 1.

    Louis, D. N. et al. The 2016 World Health Organization classification of tumors of the central nervous system: a summary. Acta Neuropathol. 131, 803–820 (2016).

  2. 2.

    Yoon, S. J. et al. Tumor mesenchymal stem-like cell as a prognostic marker in primary glioblastoma. Stem Cells Int. 2016, 6756983 (2016).

  3. 3.

    Kwon, S. M. et al. Recurrent glioblastomas reveal molecular subtypes associated with mechanistic implications of drug-resistance. PLoS ONE 10, e0140528 (2015).

  4. 4.

    Wood, M. D., Reis, G. F., Reuss, D. E. & Phillips, J. J. Protein analysis of glioblastoma primary and posttreatment pairs suggests a mesenchymal shift at recurrence. J. Neuropathol. Exp. Neurol. 75, 925–935 (2016).

  5. 5.

    Phillips, H. S. et al. Molecular subclasses of high-grade glioma predict prognosis, delineate a pattern of disease progression, and resemble stages in neurogenesis. Cancer Cell 9, 157–173 (2006).

  6. 6.

    Miroshnikova, Y. A. et al. Tissue mechanics promote IDH1-dependent HIF1α-tenascin C feedback to regulate glioblastoma aggression. Nat. Cell Biol. 18, 1336–1345 (2016).

  7. 7.

    Kim, Y. & Kumar, S. CD44-mediated adhesion to hyaluronic acid contributes to mechanosensing and invasive motility. Mol. Cancer Res. 12, 1416–1429 (2014).

  8. 8.

    Butcher, D. T., Alliston, T. & Weaver, V. M. A tense situation: forcing tumour progression. Nat. Rev. Cancer 9, 108–122 (2009).

  9. 9.

    Zhang, L. et al. Hypoxia induces epithelial-mesenchymal transition via activation of SNAI1 by hypoxia-inducible factor-1alpha in hepatocellular carcinoma. BMC Cancer 13, 108 (2013).

  10. 10.

    Chen, S. et al. Hypoxia induces TWIST-activated epithelial-mesenchymal transition and proliferation of pancreatic cancer cells in vitro and in nude mice. Cancer Lett. 383, 73–84 (2016).

  11. 11.

    Leight, J. L., Wozniak, M. A., Chen, S., Lynch, M. L. & Chen, C. S. Matrix rigidity regulates a switch between TGF-β1-induced apoptosis and epithelial-mesenchymal transition. Mol. Biol. Cell 23, 781–791 (2012).

  12. 12.

    Cordenonsi, M. et al. The Hippo transducer TAZ confers cancer stem cell-related traits on breast cancer cells. Cell 147, 759–772 (2011).

  13. 13.

    Ikushima, H. et al. Autocrine TGF-β signaling maintains tumorigenicity of glioma-initiating cells through Sry-related HMG-box factors. Cell Stem Cell 5, 504–514 (2009).

  14. 14.

    Paszek, M. J. et al. The cancer glycocalyx mechanically primes integrin-mediated growth and survival. Nature 511, 319–325 (2014).

  15. 15.

    Pinho, S. S. & Reis, C. A. Glycosylation in cancer: mechanisms and clinical implications. Nat. Rev. Cancer 15, 540–555 (2015).

  16. 16.

    Wade, A. et al. Proteoglycans and their roles in brain cancer. FEBS J. 280, 2399–2417 (2013).

  17. 17.

    Varki, A., Kannagi, R. & Toole, B.P. in Essentials of Glycobiology 2nd edn (eds A. Varki et al.) Ch. 44 (Cold Spring Harbor Laboratory Press, New York, 2009).

  18. 18.

    Tinder, T. L. et al. MUC1 enhances tumor progression and contributes toward immunosuppression in a mouse model of spontaneous pancreatic adenocarcinoma. J. Immunol. 181, 3116–3125 (2008).

  19. 19.

    Woods, E. C. et al. A bulky glycocalyx fosters metastasis formation by promoting G1 cell cycle progression. eLife 6, e25752 (2017).

  20. 20.

    Kufe, D. W. Mucins in cancer: function, prognosis and therapy. Nat. Rev. Cancer 9, 874–885 (2009).

  21. 21.

    Horm, T. M. & Schroeder, J. A. MUC1 and metastatic cancer: expression, function and therapeutic targeting. Cell Adh. Migr. 7, 187–198 (2013).

  22. 22.

    Hollingsworth, M. A. & Swanson, B. J. Mucins in cancer: protection and control of the cell surface. Nat. Rev. Cancer 4, 45–60 (2004).

  23. 23.

    Thompson, C. B. et al. Enzymatic depletion of tumor hyaluronan induces antitumor responses in preclinical animal models. Mol. Cancer Ther. 9, 3052–3064 (2010).

  24. 24.

    Hingorani, S. R. et al. Phase Ib study of PEGylated recombinant human hyaluronidase and gemcitabine in patients with advanced pancreatic cancer. Clin. Cancer Res. 22, 2848–2854 (2016).

  25. 25.

    Roy, L. D. et al. MUC1 enhances invasiveness of pancreatic cancer cells by inducing epithelial to mesenchymal transition. Oncogene 30, 1449–1459 (2011).

  26. 26.

    Porsch, H. et al. Efficient TGFbeta-induced epithelial-mesenchymal transition depends on hyaluronan synthase HAS2. Oncogene 32, 4355–4365 (2013).

  27. 27.

    He, J. et al. Identification of cell surface glycoprotein markers for glioblastoma-derived stem-like cells using a lectin microarray and LC-MS/MS approach. J. Proteome Res. 9, 2565–2572 (2010).

  28. 28.

    Muramatsu, T. & Muramatsu, H. Carbohydrate antigens expressed on stem cells and early embryonic cells. Glycoconj. J. 21, 41–45 (2004).

  29. 29.

    Boheler, K. R. & Gundry, R. L. Concise review: cell surface N-linked glycoproteins as potential stem cell markers and drug targets. Stem Cells Transl Med. 6, 131–138 (2017).

  30. 30.

    Verhaak, R. G. et al. Integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR, and NF1. Cancer Cell 17, 98–110 (2010).

  31. 31.

    Pandita, A., Aldape, K. D., Zadeh, G., Guha, A. & James, C. D. Contrasting in vivo and in vitro fates of glioblastoma cell subpopulations with amplified EGFR. Genes Chromosomes Cancer 39, 29–36 (2004).

  32. 32.

    Kitange, G. J. et al. Induction of MGMT expression is associated with temozolomide resistance in glioblastoma xenografts. Neuro. Oncol. 11, 281–291 (2009).

  33. 33.

    Engler, J. R. et al. Increased microglia/macrophage gene expression in a subset of adult and pediatric astrocytomas. PLoS ONE 7, e43339 (2012).

  34. 34.

    Lakins, J. N., Chin, A. R. & Weaver, V. M. Exploring the link between human embryonic stem cell organization and fate using tension-calibrated extracellular matrix functionalized polyacrylamide gels. Methods Mol. Biol. 916, 317–350 (2012).

  35. 35.

    Barnes, J. M., Przybyla, L. & Weaver, V. M. Tissue mechanics regulate brain development, homeostasis and disease. J. Cell Sci. 130, 71–82 (2017).

  36. 36.

    Paszek, M. J. et al. Tensional homeostasis and the malignant phenotype. Cancer Cell 8, 241–254 (2005).

  37. 37.

    Weiss, W. A. et al. Genetic determinants of malignancy in a mouse model for oligodendroglioma. Cancer Res. 63, 1589–1595 (2003).

  38. 38.

    Zhuo, L. et al. hGFAP-cre transgenic mice for manipulation of glial and neuronal function in vivo. Genesis 31, 85–94 (2001).

  39. 39.

    Nishihara, S. Glycans define the stemness of naive and primed pluripotent stem cells. Glycoconj. J. 34, 737–747 (2017).

  40. 40.

    Woods, E. C., Yee, N. A., Shen, J. & Bertozzi, C. R. Glycocalyx engineering with a recycling glycopolymer that increases cell survival in vivo. Angewandte Chemie 54, 15782–15788 (2015).

  41. 41.

    Liu, F. T. & Rabinovich, G. A. Galectins as modulators of tumour progression. Nat. Rev. Cancer 5, 29–41 (2005).

  42. 42.

    Bhat, R. et al. Nuclear repartitioning of galectin-1 by an extracellular glycan switch regulates mammary morphogenesis. Proc. Natl Acad. Sci. USA 113, E4820–E4827 (2016).

  43. 43.

    Camby, I., Le Mercier, M., Lefranc, F. & Kiss, R. Galectin-1: a small protein with major functions. Glycobiology 16, 137R–157R (2006).

  44. 44.

    Belardi, B., O’Donoghue, G. P., Smith, A. W., Groves, J. T. & Bertozzi, C. R. Investigating cell surface galectin-mediated cross-linking on glycoengineered cells. J. Am. Chem. Soc. 134, 9549–9552 (2012).

  45. 45.

    Le Mercier, M. et al. Evidence of galectin-1 involvement in glioma chemoresistance. Toxicol. Appl. Pharmacol. 229, 172–183 (2008).

  46. 46.

    Le Mercier, M., Fortin, S., Mathieu, V., Kiss, R. & Lefranc, F. Galectins and gliomas. Brain Pathol. 20, 17–27 (2010).

  47. 47.

    Chen, J. et al. A restricted cell population propagates glioblastoma growth after chemotherapy. Nature 488, 522–526 (2012).

  48. 48.

    Liu, G. et al. Analysis of gene expression and chemoresistance of CD133+ cancer stem cells in glioblastoma. Mol. Cancer 5, 67 (2006).

  49. 49.

    Visvader, J. E. & Lindeman, G. J. Cancer stem cells in solid tumours: accumulating evidence and unresolved questions. Nat. Rev. Cancer 8, 755–768 (2008).

  50. 50.

    Yoshida, T., Matsuda, Y., Naito, Z. & Ishiwata, T. CD44 in human glioma correlates with histopathological grade and cell migration. Pathol. Int. 62, 463–470 (2012).

  51. 51.

    Atsumi, N. et al. Podoplanin, a novel marker of tumor-initiating cells in human squamous cell carcinoma A431. Biochem. Biophys. Res. Commun. 373, 36–41 (2008).

  52. 52.

    Dahlrot, R. H., Hermansen, S. K., Hansen, S. & Kristensen, B. W. What is the clinical value of cancer stem cell markers in gliomas? Int. J. Clin. Exp. Pathol. 6, 334–348 (2013).

  53. 53.

    Al-Hajj, M., Wicha, M. S., Benito-Hernandez, A., Morrison, S. J. & Clarke, M. F. Prospective identification of tumorigenic breast cancer cells. Proc. Natl Acad. Sci. USA 100, 3983–3988 (2003).

  54. 54.

    Underhill, C. CD44: the hyaluronan receptor. J. Cell. Sci. 103, 293–298 (1992).

  55. 55.

    Soeda, A. et al. Hypoxia promotes expansion of the CD133-positive glioma stem cells through activation of HIF-1alpha. Oncogene 28, 3949–3959 (2009).

  56. 56.

    Gilbertson, R. J. & Rich, J. N. Making a tumour’s bed: glioblastoma stem cells and the vascular niche. Nat. Rev. Cancer 7, 733–736 (2007).

  57. 57.

    Lu, K. V. et al. VEGF inhibits tumor cell invasion and mesenchymal transition through a MET/VEGFR2 complex. Cancer Cell 22, 21–35 (2012).

  58. 58.

    Kubelt, C., Hattermann, K., Sebens, S., Mehdorn, H. M. & Held-Feindt, J. Epithelial-to-mesenchymal transition in paired human primary and recurrent glioblastomas. Int. J. Oncol. 46, 2515–2525 (2015).

  59. 59.

    Dai, L. et al. Differential profiling studies of N-linked glycoproteins in glioblastoma cancer stem cells upon treatment with gamma-secretase inhibitor. Proteomics 11, 4021–4028 (2011).

  60. 60.

    Autelitano, F. et al. Identification of novel tumor-associated cell surface sialoglycoproteins in human glioblastoma tumors using quantitative proteomics. PLoS ONE 9, e110316 (2014).

  61. 61.

    Furukawa, J. et al. Comprehensive glycomics of a multistep human brain tumor Model reveals specific glycosylation patterns related to malignancy. PLoS ONE 10, e0128300 (2015).

  62. 62.

    Kolev, V. N. et al. Inhibition of FAK kinase activity preferentially targets cancer stem cells. Oncotarget 8, 51733–51747 (2017).

  63. 63.

    Laklai, H. et al. Genotype tunes pancreatic ductal adenocarcinoma tissue tension to induce matricellular fibrosis and tumor progression. Nat. Med. 22, 497–505 (2016).

  64. 64.

    Przybyla, L., Lakins, J. N., Sunyer, R., Trepat, X. & Weaver, V. M. Monitoring developmental force distributions in reconstituted embryonic epithelia. Methods 94, 101–113 (2016).

  65. 65.

    Mekhdjian, A. H. et al. Integrin-mediated traction force enhances paxillin molecular associations and adhesion dynamics that increase the invasiveness of tumor cells into a three-dimensional extracellular matrix. Mol. Biol. Cell 28, 1467–1488 (2017).

  66. 66.

    Tseng, Q. et al. Spatial organization of the extracellular matrix regulates cell-cell junction positioning. Proc. Natl Acad. Sci. USA 109, 1506–1511 (2012).

  67. 67.

    Doetsch, F., Caille, I., Lim, D. A., Garcia-Verdugo, J. M. & Alvarez-Buylla, A. Subventricular zone astrocytes are neural stem cells in the adult mammalian brain. Cell 97, 703–716 (1999).

  68. 68.

    Paszek, M. J. et al. Scanning angle interference microscopy reveals cell dynamics at the nanoscale. Nat. Methods 9, 825–827 (2012).

  69. 69.

    Barrett, A. S. et al. Hydroxylamine chemical digestion for insoluble extracellular matrix characterization. J. Proteome Res. 16, 4177–4184 (2017).

  70. 70.

    Law, C. W., Chen, Y., Shi, W. & Smyth, G. K. voom: precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol. 15, R29 (2014).

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We thank W. Weiss (UCSF) for the S100β-vErb:p53+/– mice and M. Paszek (Cornell University) for helpful discussions. Animal handling and tissue preparation was supported by L. Korets and N. Korets (UCSF). This work was supported by the following grants: US National Institutes of Health NCI R01 grants CA138818-01A1, CA192914-01, CA174929-01 and CA085482 (V.M.W.); U01 grant CA202241 (V.M.W. and F.K.); U54 grant CA163155 (V.M.W.); Ruth Kirschstein NRSA F32 CA174319 (J.M.B.); UCSF Brain Tumor Research Program T32 CA151022 (J.M.B.); NHLBI T32 HL007544 (J.C.T.); UCSF Brain Tumor SPORE Tissue Core NIH/NCI P50 CA097257 (J.J.P.); NIH 1U01CA168878 (J.J.P); NIH/NINDS R01 NS081117 (J.J.P.); CIRM grant RB5-07409 (V.M.W.); CIRM training grant TG2-01153 (L.P.); and NCI R01 CA227942 (C.R.B. and V.M.W.). This work was also supported by a grant from the Korea Health Technology R&D project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (HI14C3418). The biospecimens for multiplex immunohistochemistry were provided by Samsung Medical Center BioBank.

Author information

Author notes

  1. These authors contributed equally: J. Matthew Barnes, Shelly Kaushik.


  1. Center for Bioengineering and Tissue Regeneration, Department of Surgery, University of California San Francisco, San Francisco, CA, USA

    • J. Matthew Barnes
    • , Shelly Kaushik
    • , Russell O. Bainer
    • , FuiBoon Kai
    • , Laralynne Przybyla
    • , Jason C. Tung
    • , Ori Maller
    • , Jonathon N. Lakins
    •  & Valerie M. Weaver
  2. Institute for Refractory Cancer Research, Samsung Medical Center, Seoul, Korea

    • Jason K. Sa
    • , Mijeong Lee
    • , Hye Won Lee
    •  & Do-Hyun Nam
  3. Research Institute for Future Medicine, Samsung Medical Center, Seoul, Korea

    • Jason K. Sa
  4. Department of Chemistry and Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA

    • Elliot C. Woods
    •  & Carolyn R. Bertozzi
  5. Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Korea

    • Mijeong Lee
    •  & Do-Hyun Nam
  6. Department of Anatomy and Cell Biology, Sungkyunkwan University School of Medicine, Suwon, Korea

    • Hye Won Lee
  7. Department of Biochemistry and Molecular Genetics, University of Colorado, Denver, Aurora, CO, USA

    • Alexander S. Barrett
    •  & Kirk C. Hansen
  8. UCSF Department of Neurological Surgery, Helen Diller Cancer Center, University of California San Francisco, San Francisco, CA, USA

    • Kan V. Lu
    • , Kirsten Obernier
    • , Arturo Alvarez-Buylla
    • , Gabriele Bergers
    •  & Joanna J. Phillips
  9. Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA

    • Kirsten Obernier
    • , Arturo Alvarez-Buylla
    •  & Valerie M. Weaver
  10. Vlaams Instituut for Biotechnologie-Center for Cancer Biology and KU Leuven, Leuven, Belgium

    • Gabriele Bergers
  11. Department of Neurosurgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea

    • Do-Hyun Nam
  12. UCSF Comprehensive Cancer Center, Helen Diller Family Cancer Research Center, University of California San Francisco, San Francisco, CA, USA

    • Valerie M. Weaver
  13. Department of Anatomy, Department of Bioengineering and Therapeutic Sciences and Department of Radiation Oncology, University of California San Francisco, San Francisco, CA, USA

    • Valerie M. Weaver


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V.M.W., J.M.B. and S.K. conceived the project and wrote the manuscript. V.M.W. coordinated the project, J.M.B. and S.K. conducted the mouse studies, cell signalling work, tumour phenotype analysis and public dataset mining. J.M.B. conducted the human tissue assays. R.O.B. performed the bioinformatics analyses. J.J.P., D.-H.N., J.K.S., M.L. and H.W.L provided immunostaining expertise, pathology interpretation and biospecimen selection. C.R.B. and E.C.W. synthesized the mucin mimetic glycopolymers and provided instructions on their use. F.K. performed the scanning angle interference microscopy. L.P. performed the traction force microscopy. J.C.T. performed the atomic force microscopy experiments. J.M.B. and O.M. conducted the FACS characterization of GBMs. J.N.L. generated the V737N mouse and constructed all expression constructs. K.C.H. and A.S.B. performed the mass spectrometry and analyses. G.B. and K.V.L. provided tissue and training on mouse procedures. A.A.-B. and K.O. provided reagents and training on tissue microdissection and neural stem cell culture. V.M.W., J.M.B. and S.K. wrote the manuscript.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Valerie M. Weaver.

Integrated supplementary information

  1. Supplementary Figure 1 Increased mechanical signaling in recurrent versus primary GBM.

    Quantification of cells expressing pMLC2 in four paired primary and recurrent GBM patient samples (Nam cohort); Quantification was performed by calculating the percent of cells expressing phospho myosin light chain 2 (pMLC2), stained in red, the representative image for which is shown in Fig. 1a, in four primary and recurrent GBM patient samples, using multiplex immunohistochemistry

  2. Supplementary Figure 2 Increased mesenchymal-ness is associated with GBM aggression.

    a, Mass spectrometry analysis of human pro and mes GBM xenografts; n=7 pro and 6 mes xenograft samples; mean + sem; **p=0.009, by two-sided Mann Whitney U-test. b, RNA from additional proneural 2 (pro2) and mesenchymal 2 (mes2) patient-derived tumor xenografts was analyzed by qPCR; n=3 mice/group for GBM12 and 4 mice/group for GBM10; mean + sem; *p=0.008, 0.02 and 0.18 for Met, MMP9 and TWIST1 respectively by two-sided unpaired t-test. c, Kaplan Meier analysis of nude mice injected with human pro 2 and mes 2 GBM cells; n=10 mice/group; p-value by two-sided logrank test result shown on plots. d, Representative image (left) and quantification (right) of hypoxia using the hypoxyprobe and HIF1α transcript levels in control vs V737N pro xenograft mice; mean + sem; n=4 mice/group; p=0.34 by two-sided Mann Whitney-U test

  3. Supplementary Figure 3 Enhanced mechanosignaling induces a mesenchymal-like phenotype in GBM.

    a, PRO 2 cells were imaged on soft and stiff polyacrylamide hydrogels for 36 hours. Migration tracking was performed and velocity calculated using Manual Tracker on Image J; n=9 cells for soft and n=6 stiff conditions from three independent experiments; each point on the velocity plot (right) was derived from calculating distance/time/frame where n=132 frames/condition averaged over 9 and 6 cells on soft and stiff respectively pooled from 3 independent experiments; mean + sem; *p=1.13x10-16 by a two-sided paired t-test. b, qPCR analysis of wildtype and V737N cells on soft hydrogels for expression of mesenchymal markers from two independent experiments; data show the mean of two independent experiments. c, Lysates from mes control (scr) and FAK knockdown (shFAK) cells were analyzed for FAK transcript knockdown from two independent experiments. d and e, Immunoblotting of mes cells treated with increasing doses of FAK inhibitor (left). Mes cells treated with FAK inhibitor at indicated concentrations were lysed and analyzed for the indicated markers (right); representative of 2 experiments. f, RNA from mes cells treated with FAK inhibitor was analyzed for indicated markers; mean + sem; n= 4 independent experiments; p=0.00012, p= 0.007 and 0.002 for TNC, vimentin and LGALS1 respectively using two-sided unpaired t-test. g, qPCR analysis for markers of mesenchymal-ness in wild-type and V737N xenografted tumors; n=2 mice/group for Twist1 and 4 mice/group for all else; mean + sem. h, Top: model of transgenic tumor growth. Bottom: representative H&E staining of WT and V737N transgenic tumors; n=4 mice/group. i, WT and V737N mouse cells were derived from lentiviral transfection of the transgenic WT E/p53 tumor cells and injected into FVB/n hosts. Tumors stained for H&E and human integrin β1 (ITGB1), only expressed in cells expressing WT or V737N transgene; dashed line delineates tumor from normal brain; n=3 mice/group; scale bar 400µm for H&E (top) and 50µm for IF (bottom). j, RNA from pro syngeneic tumors was analyzed via qPCR; n=5 animals/group for FN1 and 6 animals/group for all else; mean + sem; *p= 0.032, 0.03 and 0.18 by two-sided Mann Whitney-U test. Source data in Supplementary Table 4

  4. Supplementary Figure 4 Enhanced mechanical signaling in mesenchymal tumors increases the glycocalyx bulkiness.

    a, qPCR analysis of HAS2 transcript levels in control mes scr vs shFAK mes cells. n=3 samples/group; mean + sem; p-value = 0.3 by two-sided paired t-test. b, RNA from WT and V737N pro syngeneic tumors analyzed by qPCR; n=3 and 6 mice/group for MUC1 and Has2; mean + sem; *p=0.046 and 0.14 for MUC1 and Has2 respectively by two-sided unpaired t test. c, Alcian Blue staining of WT and V737N pro syngeneic tumor sections with and without hyaluronidase (HAse) treatment (1mg/mL for 30 minutes at 37C, control samples held at 37C for 30 minutes in PBS), scale bar 250µm, representative of 3 samples per group. This experiment indicates the majority of Alcian Blue staining in these tumors is due to HA-binding. d, Representative SAIM image of mes GBM cells loaded with short (3nm) or long (90nm) glycopolymers; scale bar 10 µm; n=24 and 23 measurements for short and long glycopolymers respectively; quantification shown in Fig. 5e. e and f, Images of long and short glycopolymer decorated tumors. White lines represent delineation of tumor-normal brain boundary; n=4 mice, representative images and quantification shown in Fig. 4h; Scale bar 400 µm

  5. Supplementary Figure 5 Galectin-1 regulates mechanical and mesenchymal phenotype in GBM.

    a, Kaplan Meier analysis of Rembrandt data showing percent survival probability vs. expression level of Gal-1 in all glioma patients; n=214 GBM, 66 oligo and 145 astro; p-value by two-sided logrank test. b, Immunoblotting of lysates from WT and V737N syngeneic (top) and pro xenograft (bottom) tumors for Gal-1 protein n=3 tumors/group for xenograft, 2 tumors/group for syngeneic, FVB=normal cortex lysate. c, Glycocalyx height was measured in mes scr and shGal-1 GBM cells by scanning angle interference microscopy (SAIM); scale bar 10 µm; representative of three independent experiments. d, Scatter plot on right is derived from four independent experiments, mean + sem; each point represents measurement of glycocalyx height/frame; n=91 and 90 measurements over 10 cells for scr and shGal-1 respectively; p=0.17 by two-sided paired t-test. e, Immunoblot shows knockdown of Galectin-1 using additional shGal hairpins. shGal (1) is the main hairpin used for all in vitro and in vivo studies (clone#TRCN0000057423, Sigma Aldrich). shGal clones (2), (3) and (4) are additional hairpins validated for knockdown (clones#TRCN0000057424, TRCN0000057425 and TRCN0000057427, Sigma Aldrich). Immunoblot (left) shows validation of Galectin-1 knockdown. Immunoblot (right) shows effects on TNC, FAK, MUC1 upon Galectin-1 knockdown with clones (2) and (3); n=2 independent experiments/clone. f, Hyaluronic acid production was measured from cell supernatants expressing shGal-1 clones (1), (2) and (3); n=3 independent experiments for shGal (2) and 5 independent experiments for all others; *p=0.037, 0.033 and 0.034 for shGal clones (1), (2) and (3) respectively. g, Mes scr and shGal cells were plated on stiff hydrogels and imaged over 36 hours. Migration tracking (left) was performed using Manual Tracker; n=12 cells/condition from three independent experiments. Velocity plot (right) was derived from calculating distance/time/frame where n=120 frames/condition averaged over 12 cells; mean + sem; ***p=1.5x10-28 by two-sided paired t-test. h, qPCR analysis for performed for markers of mesenchymal-ness for RNA from scr vs shGal cells on soft hydrogels; n=2 independent experiments; source data in Supplementary Table 4

  6. Supplementary Figure 6 A bulky glycocalyx promotes a stem-like phenotype in mesenchymal GBM.

    a, Representative images of four paired human primary and recurrent patient samples (Nam cohort) stained for PDPN using multiplex IHC; Blue arrows indicate regions of PDPN expression; scale bar 50 µm. b, Cells from Supplemental Fig. 6a expressing PDPN were quantified in primary vs recurrent tumors; n=4 patients per group. c, SOX2 in short and long Mes glycopolymer tumor sections; representative of 4 mice/group; scale bar 100 µm. d, RNA from short and long Mes glycopolymer tumors was analyzed via qPCR; mean + sem; n=5 mice/group; p=0.06 and 0.2 for PDPN and Hes1 respectively by two-sided unpaired t-test. e, FACS was used to isolate CD44:podoplanin DP, CD44 single positive (SP) cells, cultured on soft or stiff hydrogels for 18 hours prior to lysis for immunoblot of the indicated markers; n=3 independent experiments. f, In vitro limiting dilution assays were performed for additional mes control (scr mes2) vs gal-1 knockdown cells (shGal mes2) for the cells numbers indicated; n= 2 independent experiments. g, In vivo limiting dilution assays were performed for mesenchymal control (Scr) vs shGal cells injected into nude mice at the rate of 100 cells/mouse. The image shows the number of non-tumor-bearing and tumor-bearing mice at the study endpoint. Quantification shown in Fig. 6m. h and i. FACS analysis of PDPN and CD44 in DP, SP, and parental (unsorted cells) populations from Mes1 and Mes2 primary GBMs immediately after the sort (“sort day”), and 5 and 10 days after the sort. The images are representative of three independent sorts. Source data in Supplementary Table 4

  7. Supplementary Figure 7 Increased local invasion in V737N expressing tumors.

    Representative images of pro ITGB1 and V737N overexpressing tumors. White lines represent delineation of tumor-normal brain boundary; n=4 mice per condition, representative images and quantification shown in Fig. 2j; Scale bar 400 µm

  8. Supplementary Figure 8 Heatmap of bulky genes differentially expressed in proneural and mesenchymal human GBM patients.

    Heat map of “bulky genes” found to be differentially expressed in proneural versus mesenchymal tumors. Few bulky genes of interest listed for simplification. A comprehensive list is available in supplemental table 1

  9. Supplementary Figure 9 Full scans of key blots.

    Unprocessed western blots for Figs. 2g, 3b, 5f and 6i

Supplementary information

  1. Supplementary Information

    Supplementary Figures 1–9 and Supplementary Table legends.

  2. Reporting Summary

  3. Supplementary Table 1

    Bulky Genes List. A list of genes characterized as ‘bulky’ based on their putative O- and N-glycosylation patterns. The table shows bulky genes for violin plots in Figs 4a and 4c, as well as the genes for Kaplan Meier analysis in Figs 1e and 4b.

  4. Supplementary Table 2

    Primer sequences. A list of all the primers used for qPCR analysis, along with their forward and reverse sequence information.

  5. Supplementary Table 3

    Antibody information. A list of all the antibodies used in this study (western blot, immunohistochemistry, immunofluorescence and flow cytometry) and information regarding these antibodies, including catalogue number, company, clone and lot numbers, and their method of validation.

  6. Supplementary Table 4

    Statistics source data. The source data is included for all figures where individual experiments were repeated twice (Figs 3e, 3h, 5e, 6h and 7g; Supplementary Figs 3b, 3g 5h and 6f). Each tab represents data (two experiments, depicted as n=1 and n=2) for a single figure panel, along with individual raw data points per repeat.

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