Skip to main content
SpringerLink
Log in

Genomic predictors of patterns of progression in glioblastoma and possible influences on radiation field design

  • Clinical Study
  • Published:
Journal of Neuro-Oncology Aims and scope Submit manuscript

Abstract

We present a retrospective investigation of the role of genomics in the prediction of central versus marginal disease progression patterns for glioblastoma (GBM). Between August 2000 and May 2010, 41 patients with GBM and gene expression and methylation data available were treated with radiotherapy with or without concurrent temozolomide. Location of disease progression was categorized as within the high dose (60 Gy) or low dose (46 Gy) volume. Samples were grouped into previously described TCGA genomic groupings: Mesenchymal (m), classical (c), proneural (pn), and neural (n); and were also classified by MGMT-Methylation status and G-Cimp methylation phenotype. Genomic groupings and methylation status were investigated as a possible predictor of disease progression in the high dose region, progression in the low dose region, and time to progression. Based on TCGA category there was no difference in OS (p = 0.26), 60 Gy progression (PN: 71 %, N: 60 %, M: 89 %, C: 83 %, p = 0.19), 46 Gy progression (PN: 57 %, N: 40 %, M: 61 %,C: 50 %, p = 0.8) or time to progression (PN: 9 months, N:15 months, M: 9 months, C: 7 months, p = 0.58). MGMT methylation predicted for improved OS (median 25 vs. 13 months, p = 0.01), improved DFS (median 13 vs. 8 months, p = 0.007) and decreased 60 Gy (p = 0.003) and 46 Gy (p = 0.006) progression. There was a cohort of MGMT methylated patients with late marginal disease progression (4/22 patients, 18 %). TCGA groups demonstrated no difference in survival or progression patterns. MGMT methylation predicted for a statistically significant decrease in in-field and marginal disease progression. There was a cohort of MGMT methylated patients with late marginal progression. Validations of these findings would have implications that could affect radiation field size.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Brennan CW, Verhaak RG, McKenna A, Campos B, Noushmehr H, Salama SR, Zheng S, Chakravarty D, Sanborn JZ, Berman SH, Beroukhim R, Bernard B, Wu CJ, Genovese G, Shmulevich I, Barnholtz-Sloan J, Zou L, Vegesna R, Shukla SA, Ciriello G, Yung WK, Zhang W, Sougnez C, Mikkelsen T, Aldape K, Bigner DD, Van Meir EG, Prados M, Sloan A, Black KL, Eschbacher J, Finocchiaro G, Friedman W, Andrews DW, Guha A, Iacocca M, O’Neill BP, Foltz G, Myers J, Weisenberger DJ, Penny R, Kucherlapati R, Perou CM, Hayes DN, Gibbs R, Marra M, Mills GB, Lander E, Spellman P, Wilson R, Sander C, Weinstein J, Meyerson M, Gabriel S, Laird PW, Haussler D, Getz G, Chin L (2013) The somatic genomic landscape of glioblastoma. Cell 155:462–477. doi:10.1016/j.cell.2013.09.034

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Qi S, Yu L, Li H, Ou Y, Qiu X, Ding Y, Han H, Zhang X (2014) Isocitrate dehydrogenase mutation is associated with tumor location and magnetic resonance imaging characteristics in astrocytic neoplasms. Oncol Lett 7:1895–1902. doi:10.3892/ol.2014.2013ol-07-06-1895

    CAS  PubMed  PubMed Central  Google Scholar 

  3. Beiko J, Suki D, Hess KR, Fox BD, Cheung V, Cabral M, Shonka N, Gilbert MR, Sawaya R, Prabhu SS, Weinberg J, Lang FF, Aldape KD, Sulman EP, Rao G, McCutcheon IE, Cahill DP (2014) IDH1 mutant malignant astrocytomas are more amenable to surgical resection and have a survival benefit associated with maximal surgical resection. Neuro Oncol 16:81–91. doi:10.1093/neuonc/not159

    Article  CAS  PubMed  Google Scholar 

  4. Walker MD, Strike TA, Sheline GE (1979) An analysis of dose-effect relationship in the radiotherapy of malignant gliomas. Int J Radiat Oncol Biol Phys 5:1725–1731

    Article  CAS  PubMed  Google Scholar 

  5. Brandes AA, Tosoni A, Franceschi E, Sotti G, Frezza G, Amista P, Morandi L, Spagnolli F, Ermani M (2009) Recurrence pattern after temozolomide concomitant with and adjuvant to radiotherapy in newly diagnosed patients with glioblastoma: correlation With MGMT promoter methylation status. J Clin Oncol 27:1275–1279. doi:10.1200/JCO.2008.19.4969

    Article  CAS  PubMed  Google Scholar 

  6. Paulsson AK, McMullen KP, Peiffer AM, Hinson WH, Kearns WT, Johnson AJ, Lesser GJ, Ellis TL, Tatter SB, Debinski W, Shaw EG, Chan MD (2014) Limited margins using modern radiotherapy techniques does not increase marginal failure rate of glioblastoma. Am J Clin Oncol 37:177–181. doi:10.1097/COC.0b013e318271ae03

    Article  PubMed  PubMed Central  Google Scholar 

  7. Liu W, Lindberg J, Sui G, Luo J, Egevad L, Li T, Xie C, Wan M, Kim ST, Wang Z, Turner AR, Zhang Z, Feng J, Yan Y, Sun J, Bova GS, Ewing CM, Yan G, Gielzak M, Cramer SD, Vessella RL, Zheng SL, Gronberg H, Isaacs WB, Xu J (2012) Identification of novel CHD1-associated collaborative alterations of genomic structure and functional assessment of CHD1 in prostate cancer. Oncogene 31:3939–3948. doi:10.1038/onc.2011.554

    Article  CAS  PubMed  Google Scholar 

  8. 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. doi:10.1016/j.ccr.2009.12.020

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Du P, Kibbe WA, Lin SM (2008) lumi: a pipeline for processing Illumina microarray. Bioinformatics 24:1547–1548. doi:10.1093/bioinformatics/btn224

    Article  CAS  PubMed  Google Scholar 

  10. Kim JW, Kim ST, Turner AR, Young T, Smith S, Liu W, Lindberg J, Egevad L, Gronberg H, Isaacs WB, Xu J (2012) Identification of new differentially methylated genes that have potential functional consequences in prostate cancer. PLoS One 7:e48455. doi:10.1371/journal.pone.0048455

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. 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. doi:10.1007/s00401-012-1016-2

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Noushmehr H, Weisenberger DJ, Diefes K, Phillips HS, Pujara K, Berman BP, Pan F, Pelloski CE, Sulman EP, Bhat KP, Verhaak RG, Hoadley KA, Hayes DN, Perou CM, Schmidt HK, Ding L, Wilson RK, Van Den Berg D, Shen H, Bengtsson H, Neuvial P, Cope LM, Buckley J, Herman JG, Baylin SB, Laird PW, Aldape K (2010) Identification of a CpG island methylator phenotype that defines a distinct subgroup of glioma. Cancer Cell 17:510–522. doi:10.1016/j.ccr.2010.03.017

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Phillips HS, Kharbanda S, Chen R, Forrest WF, Soriano RH, Wu TD, Misra A, Nigro JM, Colman H, Soroceanu L, Williams PM, Modrusan Z, Feuerstein BG, Aldape K (2006) Molecular subclasses of high-grade glioma predict prognosis, delineate a pattern of disease progression, and resemble stages in neurogenesis. Cancer Cell 9:157–173. doi:10.1016/j.ccr.2006.02.019

    Article  CAS  PubMed  Google Scholar 

  14. Chan MD, Tatter SB, Lesser G, Shaw EG (2010) Radiation oncology in brain tumors: current approaches and clinical trials in progress. Neuroimaging Clin N Am 20:401–408. doi:10.1016/j.nic.2010.04.005

    Article  PubMed  Google Scholar 

  15. Hess CF, Schaaf JC, Kortmann RD, Schabet M, Bamberg M (1994) Malignant glioma: patterns of failure following individually tailored limited volume irradiation. Radiother Oncol 30:146–149

    Article  CAS  PubMed  Google Scholar 

  16. Wallner KE, Galicich JH, Krol G, Arbit E, Malkin MG (1989) Patterns of failure following treatment for glioblastoma multiforme and anaplastic astrocytoma. Int J Radiat Oncol Biol Phys 16:1405–1409

    Article  CAS  PubMed  Google Scholar 

  17. Hochberg FH, Pruitt A (1980) Assumptions in the radiotherapy of glioblastoma. Neurology 30:907–911

    Article  CAS  PubMed  Google Scholar 

  18. McDonald MW, Shu HK, Curran WJ Jr, Crocker IR (2011) Pattern of failure after limited margin radiotherapy and temozolomide for glioblastoma. Int J Radiat Oncol Biol Phys 79:130–136. doi:10.1016/j.ijrobp.2009.10.048

    Article  CAS  PubMed  Google Scholar 

  19. Peiffer AM, Leyrer CM, Greene-Schloesser DM, Shing E, Kearns WT, Hinson WH, Tatter SB, Ip EH, Rapp SR, Robbins ME, Shaw EG, Chan MD (2013) Neuroanatomical target theory as a predictive model for radiation-induced cognitive decline. Neurology 80:747–753. doi:10.1212/WNL.0b013e318283bb0a

    Article  PubMed  PubMed Central  Google Scholar 

  20. Paulsson AK, Holmes JA, Peiffer AM, Miller LD, Liu W, Xu J, Hinson WH, Lesser GJ, Laxton AW, Tatter SB, Debinski W, Chan MD (2014) Comparison of clinical outcomes and genomic characteristics of single focus and multifocal glioblastoma. J Neurooncol 119:429–435. doi:10.1007/s11060-014-1515-1

    Article  PubMed  PubMed Central  Google Scholar 

  21. LaPlant Q, Pitter K, Young RJ, Yamada Y, Chan TA, Huse JT, Brennan CW, Beal K (2014) Radiographic features, patterns of treatment failure, and clinical outcomes in 56 cases of molecularly subtyped glioblastoma multiforme patients. Int J of Radiat Oncol, Biol, Phys 90:S281. doi:10.1016/j.ijrobp.2014.05.959

    Article  Google Scholar 

  22. Brandes AA, Franceschi E, Tosoni A, Blatt V, Pession A, Tallini G, Bertorelle R, Bartolini S, Calbucci F, Andreoli A, Frezza G, Leonardi M, Spagnolli F, Ermani M (2008) MGMT promoter methylation status can predict the incidence and outcome of pseudoprogression after concomitant radiochemotherapy in newly diagnosed glioblastoma patients. J Clin Oncol 26:2192–2197. doi:10.1200/JCO.2007.14.8163

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Radiation Oncology, UNC School of Medicine, CB 7152, 101 Manning Drive, Chapel Hill, NC, 27599-7512, USA

    Jordan A. Holmes

  2. Department of Radiation Oncology, UCSF School of Medicine, 1600 Divisadero St, San Francisco, CA, 94115, USA

    Anna K. Paulsson

  3. Department of Radiation Oncology, Wake Forest School of Medicine, Medical Center Blvd, Winston-Salem, NC, 27157, USA

    Brandi R. Page, William H. Hinson & Michael D. Chan

  4. Department of Cancer Biology, Wake Forest School of Medicine, Medical Center Blvd, Winston-Salem, NC, 27157, USA

    Lance D. Miller

  5. Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Medical Center Blvd, Winston-Salem, NC, 27157, USA

    Wennuan Liu & Jianfeng Xu

  6. Department of Medicine (Hematology & Oncology), Wake Forest School of Medicine, Medical Center Blvd, Winston-Salem, NC, 27157, USA

    Glenn J. Lesser

  7. Brain Tumor Center of Excellence, Wake Forest School of Medicine, Medical Center Blvd, Winston-Salem, NC, 27157, USA

    Glenn J. Lesser, Stephen B. Tatter, Waldemar Debinski & Michael D. Chan

  8. Department of Neurosurgery, Wake Forest School of Medicine, Medical Center Blvd, Winston-Salem, NC, 27157, USA

    Adrian W. Laxton, Stephen B. Tatter & Waldemar Debinski

Authors
  1. Jordan A. Holmes
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Anna K. Paulsson
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Brandi R. Page
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lance D. Miller
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Wennuan Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Jianfeng Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. William H. Hinson
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Glenn J. Lesser
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Adrian W. Laxton
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Stephen B. Tatter
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Waldemar Debinski
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Michael D. Chan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jordan A. Holmes.

Ethics declarations

Conflicts of interest

None.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Holmes, J.A., Paulsson, A.K., Page, B.R. et al. Genomic predictors of patterns of progression in glioblastoma and possible influences on radiation field design. J Neurooncol 124, 447–453 (2015). https://doi.org/10.1007/s11060-015-1858-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11060-015-1858-2

Keywords

Search

Navigation