Skip to main content
Log in

Analysis of immunobiologic markers in primary and recurrent glioblastoma

  • Laboratory Investigation
  • Published:
Journal of Neuro-Oncology Aims and scope Submit manuscript

Abstract

Glioblastoma (GBM) generates a varied immune response and understanding the immune microenvironment may lead to novel immunotherapy treatments modalities. The goal of this study was to evaluate the expression of immunologic markers of potential clinical significance in primary versus recurrent GBM and assess the relationship between these markers and molecular characteristics of GBM. Human GBM samples were evaluated and analyzed with immunohistochemistry for multiple immunobiologic markers (CD3, CD8, FoxP3, CD68, CD163, PD1, PDL1, CTLA4, CD70). Immunoreactivity was analyzed using Aperio software. Degree of strong positive immunoreactivity within the tumor was compared to patient and tumor characteristics including age, gender, MGMT promoter methylation status, and ATRX, p53, and IDH1 mutation status. Additionally, the TCGA database was used to perform similar analysis of these factors in GBM using RNA-seq by expectation–maximization. Using odds ratios, IDH1 mutated GBM had statistically significant decreased expression of CD163 and CD70 and a trend for decreased PD1, CTLA4, and Foxp3. ATRX-mutated GBMs exhibited statistically significant increased CD3 immunoreactivity, while those with p53 mutations were found to have significantly increased CTLA4 immunoreactivity. The odds of having strong CD8 and CD68 reactivity was significantly less in MGMT methylated tumors. No significant difference was identified in any immune marker between the primary and recurrent GBM, nor was a significant change in immunoreactivity identified among age intervals. TCGA analysis corroborated findings related to the differential immune profile of IDH1 mutant, p53 mutant, and MGMT unmethylated tumors. Immunobiologic markers have greater association with the molecular characteristics of the tumor than with primary/recurrent status or age.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Stupp R, Hegi ME, Gorlia T, Erridge SC, Perry J, Hong YK, Aldape KD, Lhermitte B, Pietsch T, Grujicic D, Steinbach JP, Wick W, Tarnawski R, Nam DH, Hau P, Weyerbrock A, Taphoorn MJ, Shen CC, Rao N, Thurzo L, Herrlinger U, Gupta T, Kortmann RD, Adamska K, McBain C, Brandes AA, Tonn JC, Schnell O, Wiegel T, Kim CY, Nabors LB, Reardon DA, van den Bent MJ, Hicking C, Markivskyy A, Picard M, Weller M (2014) Cilengitide combined with standard treatment for patients with newly diagnosed glioblastoma with methylated MGMT promoter (CENTRIC EORTC 26071–22072 study): a multicentre, randomised, open-label, phase 3 trial. Lancet Oncol 15:1100–1108. https://doi.org/10.1016/s1470-2045(14)70379-1

    Article  CAS  PubMed  Google Scholar 

  2. Chinot OL, Wick W, Mason W, Henriksson R, Saran F, Nishikawa R, Carpentier AF, Hoang-Xuan K, Kavan P, Cernea D, Brandes AA, Hilton M, Abrey L, Cloughesy T (2014) Bevacizumab plus radiotherapy-temozolomide for newly diagnosed glioblastoma. N Engl J Med 370:709–722. https://doi.org/10.1056/NEJMoa1308345

    Article  CAS  PubMed  Google Scholar 

  3. Weathers SP, Han X, Liu DD, Conrad CA, Gilbert MR, Loghin ME, O’Brien BJ, Penas-Prado M, Puduvalli VK, Tremont-Lukats I, Colen RR, Yung WK, de Groot JF (2016) A randomized phase II trial of standard dose bevacizumab versus low dose bevacizumab plus lomustine (CCNU) in adults with recurrent glioblastoma. J Neuro-Oncol 129:487–494. https://doi.org/10.1007/s11060-016-2195-9

    Article  CAS  Google Scholar 

  4. Patel AP, Tirosh I, Trombetta JJ, Shalek AK, Gillespie SM, Wakimoto H, Cahill DP, Nahed BV, Curry WT, Martuza RL, Louis DN, Rozenblatt-Rosen O, Suva ML, Regev A, Bernstein BE (2014) Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma. Science 344:1396–1401. https://doi.org/10.1126/science.1254257

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Kitano H (2004) Cancer as a robust system: implications for anticancer therapy. Nat Rev Cancer 4:227–235. https://doi.org/10.1038/nrc1300

    Article  CAS  PubMed  Google Scholar 

  6. Inman S (2016) Rintega (Rindopepimut) misses survival endpoint in phase 3 glioblastoma trial. Cure Accessed 5 Dec 2017

  7. Green J (2013) ImmunoCellular therapeutics phase II study demonstrates that glioblastoma patients live longer without disease progression when treated with ICT-107. Immunocellular therapeutics Ltd. http://investors.imuc.com/releasedetail.cfm?ReleaseID=813442

  8. Abernathy A (2017) Bristol-Myers Squibb announces results from checkmate—143, a phase 3 study of Opdivo (nivolumab) in patients with glioblastoma multiforme. Bristol-Myers Squibb. https://news.bms.com/press-release/bmy/bristol-myers-squibb-announces-results-checkmate-143-phase-3-study-opdivo-nivoluma

  9. Yang I, Han SJ, Sughrue ME, Tihan T, Parsa AT (2011) Immune cell infiltrate differences in pilocytic astrocytoma and glioblastoma: evidence of distinct immunological microenvironments that reflect tumor biology. J Neurosurg 115:505–511. https://doi.org/10.3171/2011.4.jns101172

    Article  CAS  PubMed  Google Scholar 

  10. Hewedi IH, Radwan NA, Shash LS, Elserry TH (2013) Perspectives on the immunologic microenvironment of astrocytomas. Cancer Manag Res 5:293–299. https://doi.org/10.2147/cmar.s48942

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Sayour EJ, McLendon P, McLendon R, De Leon G, Reynolds R, Kresak J, Sampson JH, Mitchell DA (2015) Increased proportion of FoxP3 + regulatory T cells in tumor infiltrating lymphocytes is associated with tumor recurrence and reduced survival in patients with glioblastoma. Cancer Immunol Immunother 64:419–427. https://doi.org/10.1007/s00262-014-1651-7

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Bady P, Sciuscio D, Diserens AC, Bloch J, van den Bent MJ, Marosi C, Dietrich PY, Weller M, Mariani L, Heppner FL, McDonald DR, Lacombe D, Stupp R, Delorenzi M, Hegi ME (2012) MGMT methylation analysis of glioblastoma on the Infinium methylation BeadChip identifies two distinct CpG regions associated with gene silencing and outcome, yielding a prediction model for comparisons across datasets, tumor grades, and CIMP-status. Acta Neuropathol 124:547–560. https://doi.org/10.1007/s00401-012-1016-2

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Harell FE (2015) Regression modeling strategies: with applications to linear models, logistic and ordinal regression, and survival analysis. Springer, New York

    Book  Google Scholar 

  14. Verhaak RG, Hoadley KA, Purdom E, Wang V, Qi Y, Wilkerson MD, Miller CR, Ding L, Golub T, Mesirov JP, Alexe G, Lawrence M, O’Kelly M, Tamayo P, Weir BA, Gabriel S, Winckler W, Gupta S, Jakkula L, Feiler HS, Hodgson JG, James CD, Sarkaria JN, Brennan C, Kahn A, Spellman PT, Wilson RK, Speed TP, Gray JW, Meyerson M, Getz G, Perou CM, Hayes DN (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 

  15. Louis DN, Perry A, Burger P, Ellison DW, Reifenberger G, von Deimling A, Aldape K, Brat D, Collins VP, Eberhart C, Figarella-Branger D, Fuller GN, Giangaspero F, Giannini C, Hawkins C, Kleihues P, Korshunov A, Kros JM, Beatriz Lopes M, Ng HK, Ohgaki H, Paulus W, Pietsch T, Rosenblum M, Rushing E, Soylemezoglu F, Wiestler O, Wesseling P (2014) International Society Of Neuropathology–Haarlem consensus guidelines for nervous system tumor classification and grading. Brain Pathol (Zurich Switzerland) 24:429–435. https://doi.org/10.1111/bpa.12171

    Article  Google Scholar 

  16. Louis DN, Perry A, Reifenberger G, von Deimling A, Figarella-Branger D, Cavenee WK, Ohgaki H, Wiestler OD, Kleihues P, Ellison DW (2016) The 2016 World Health Organization classification of tumors of the central nervous system: a summary. Acta Neuropathol 131:803–820. https://doi.org/10.1007/s00401-016-1545-1

    Article  PubMed  Google Scholar 

  17. Kmiecik J, Poli A, Brons NH, Waha A, Eide GE, Enger PO, Zimmer J, Chekenya M (2013) Elevated CD3+ and CD8+ tumor-infiltrating immune cells correlate with prolonged survival in glioblastoma patients despite integrated immunosuppressive mechanisms in the tumor microenvironment and at the systemic level. J Neuroimmunol 264:71–83. https://doi.org/10.1016/j.jneuroim.2013.08.013

    Article  CAS  PubMed  Google Scholar 

  18. Wang Z, Zhang C, Liu X, Wang Z, Sun L, Li G, Liang J, Hu H, Liu Y, Zhang W, Jiang T (2016) Molecular and clinical characterization of PD-L1 expression at transcriptional level via 976 samples of brain glioma. Oncoimmunology 5:e1196310. https://doi.org/10.1080/2162402x.2016.1196310

    Article  PubMed  PubMed Central  Google Scholar 

  19. Conroy S, Kruyt FA, Joseph JV, Balasubramaniyan V, Bhat KP, Wagemakers M, Enting RH, Walenkamp AM, den Dunnen WF (2014) Subclassification of newly diagnosed glioblastomas through an immunohistochemical approach. PLoS ONE 9:e115687. https://doi.org/10.1371/journal.pone.0115687

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This work was funded by the Florida Center for Brain Tumor Research. We would like to acknowledge Barbara Frentzen for her work in obtaining samples for analysis through the FCBTR.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Maryam Rahman.

Electronic supplementary material

Below is the link to the electronic supplementary material.

11060_2017_2732_MOESM1_ESM.tif

Supplementary Figure 1. Effect of Recurrent versus Primary tumor status on immune marker expression. Circled odds ratio point estimates differ significantly from one at α=0.05 (TIF 190 KB)

11060_2017_2732_MOESM2_ESM.tif

Supplementary Figure 2. Change in Immune Marker Expression per 10-Year Age Increase. Circled odds ratio point estimates differ significantly from one at α=0.05 (TIF 192 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rahman, M., Kresak, J., Yang, C. et al. Analysis of immunobiologic markers in primary and recurrent glioblastoma. J Neurooncol 137, 249–257 (2018). https://doi.org/10.1007/s11060-017-2732-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11060-017-2732-1

Keywords

Navigation