Advertisement

Predictive markers for MGMT promoter methylation in glioblastomas

  • Tokunori KanazawaEmail author
  • Yasuhiro Minami
  • Masahiro Jinzaki
  • Masahiro Toda
  • Kazunari Yoshida
  • Hikaru Sasaki
ORIGINAL PAPER
  • 66 Downloads

Abstract

The promoter methylation status of the O6-methylguanine-DNA methyltransferase (MGMT) gene has been described as the most important predictor of chemotherapeutic response and patients’ survival in glioblastomas (GBs). Therefore, prediction of the MGMT promoter methylation status by imaging would help to preoperatively decide the overall treatment strategy as well as surgical strategy. This study aimed to detect imaging parameters to predict MGMT promoter methylation in GBs by using a commercially available software. We investigated three imaging features (ring enhancement, tumor location, and laterality) and apparent diffusion coefficient (ADC) parameters in 48 newly diagnosed GBs treated at Keio University Hospital in 2006 or later. For ADC, texture analyses were performed. Regions of interest (ROIs) were drawn manually with reference to contrast-enhanced areas, excluding necrotic and cystic regions. Mean ADC value and ADC histogram parameters, including kurtosis, skewness, and entropy, were compared with MGMT promoter methylation. Each parameter was evaluated to determine correlation with MGMT promoter methylation, and the parameters with significant associations with the methylation status were correlated with the MGMT-positive cell ratio determined by immunohistochemistry (IHC) analysis. The mean ADC value and ADC entropy were significantly associated with MGMT promoter methylation. The combination of mean ADC value and ADC entropy predicted MGMT promoter methylation, with a PPV of 81.2% and specificity of 88.9%. The mean ADC value and ADC entropy were negatively correlated with the MGMT-positive cell ratio in the IHC analysis. This study demonstrated that texture analyses of ADC histograms in GBs were predictive of MGMT promoter methylation.

Keywords

Glioblastoma Texture analysis ADC MGMT 

Notes

Acknowledgements

We greatly thank Ms. Naoko Tsuzaki at the Department of Neurosurgery, Keio University School of Medicine for technical assistance of laboratory works. The authors also greatly thank Dr. Takayuki Abe at the Center for Clinical Research, Department of Preventive Medicine and Public Health, Keio University School of Medicine for statistical advice.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This study was approved by the Institutional Review Board of Keio University. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Supplementary material

10143_2018_1061_MOESM1_ESM.docx (18 kb)
ESM 1 (DOCX 17 kb)
10143_2018_1061_Fig4_ESM.png (84 kb)
Fig. S2

ROC curve for MGMT promoter methylation status correlated with the mean ADC value (PNG 84 kb)

10143_2018_1061_MOESM2_ESM.tif (114 kb)
High resolution image (TIF 113 kb)
10143_2018_1061_Fig5_ESM.png (105 kb)
Fig. S3

ROC curve for MGMT promoter methylation status correlated with ADC entropy (PNG 105 kb)

10143_2018_1061_MOESM3_ESM.tif (141 kb)
High resolution image (TIF 140 kb)

References

  1. 1.
    Alvarez-Linera J (2008) 3T MRI: advances in brain imaging. Eur J Radiol 67:415–426.  https://doi.org/10.1016/j.ejrad.2008.02.045 CrossRefGoogle Scholar
  2. 2.
    Ashby LS, Smith KA, Stea B (2016) Gliadel wafer implantation combined with standard radiotherapy and concurrent followed by adjuvant temozolomide for treatment of newly diagnosed high-grade glioma: a systematic literature review. World J Surg Oncol 14:225.  https://doi.org/10.1186/s12957-016-0975-5 CrossRefGoogle Scholar
  3. 3.
    Barajas RF Jr, Hodgson JG, Chang JS, Vandenberg SR, Yeh RF, Parsa AT, McDermott MW, Berger MS, Dillon WP, Cha S (2010) Glioblastoma multiforme regional genetic and cellular expression patterns: influence on anatomic and physiologic MR imaging. Radiology 254:564–576.  https://doi.org/10.1148/radiol.09090663 CrossRefGoogle Scholar
  4. 4.
    Chang P, Grinband J et al (2018) Deep-learning convolutional neural networks accurately classify genetic mutations in gliomas. AJNR Am J Neuroradiol 39:1201–1207.  https://doi.org/10.3174/ajnr.A5667 CrossRefGoogle Scholar
  5. 5.
    Choi YS, Ahn SS, Kim DW, Chang JH, Kang SG, Kim EH, Kim SH, Rim TH, Lee SK (2016) Incremental prognostic value of ADC histogram analysis over MGMT promoter methylation status in patients with glioblastoma. Radiology 281:175–184.  https://doi.org/10.1148/radiol.2016151913 CrossRefGoogle Scholar
  6. 6.
    Coons SW, Johnson PC, Scheithauer BW, Yates AJ, Pearl DK (1997) Improving diagnostic accuracy and interobserver concordance in the classification and grading of primary gliomas. Cancer 79:1381–1393CrossRefGoogle Scholar
  7. 7.
    Drabycz S, Roldan G, de Robles P, Adler D, McIntyre JB, Magliocco AM, Cairncross JG, Mitchell JR (2010) An analysis of image texture, tumor location, and MGMT promoter methylation in glioblastoma using magnetic resonance imaging. NeuroImage 49:1398–1405.  https://doi.org/10.1016/j.neuroimage.2009.09.049 CrossRefGoogle Scholar
  8. 8.
    Dunn J, Baborie A, Alam F, Joyce K, Moxham M, Sibson R, Crooks D, Husband D, Shenoy A, Brodbelt A, Wong H, Liloglou T, Haylock B, Walker C (2009) Extent of MGMT promoter methylation correlates with outcome in glioblastomas given temozolomide and radiotherapy. Br J Cancer 101:124–131.  https://doi.org/10.1038/sj.bjc.6605127 CrossRefGoogle Scholar
  9. 9.
    Ellingson BM, Cloughesy TF, Pope WB, Zaw TM, Phillips H, Lalezari S, Nghiemphu PL, Ibrahim H, Naeini KM, Harris RJ, Lai A (2012) Anatomic localization of O6-methylguanine DNA methyltransferase (MGMT) promoter methylated and unmethylated tumors: a radiographic study in 358 de novo human glioblastomas. NeuroImage 59:908–916.  https://doi.org/10.1016/j.neuroimage.2011.09.076 CrossRefGoogle Scholar
  10. 10.
    Eoli M, Menghi F, Bruzzone MG, De Simone T, Valletta L, Pollo B, Bissola L, Silvani A, Bianchessi D, D'Incerti L, Filippini G, Broggi G, Boiardi A, Finocchiaro G (2007) Methylation of O6-methylguanine DNA methyltransferase and loss of heterozygosity on 19q and/or 17p are overlapping features of secondary glioblastomas with prolonged survival. Clin Cancer Res 13:2606–2613.  https://doi.org/10.1158/1078-0432.CCR-06-2184 CrossRefGoogle Scholar
  11. 11.
    Firbank MJ, Coulthard A, Harrison RM, Williams ED (1999) Partial volume effects in MRI studies of multiple sclerosis. Magn Reson Imaging 17:593–601CrossRefGoogle Scholar
  12. 12.
    Fukushima T, Takeshima H, Kataoka H (2009) Anti-glioma therapy with temozolomide and status of the DNA-repair gene MGMT. Anticancer Res 29:4845–4854Google Scholar
  13. 13.
    Glickman ME, Rao SR, Schultz MR (2014) False discovery rate control is a recommended alternative to Bonferroni-type adjustments in health studies. J Clin Epidemiol 67:850–857.  https://doi.org/10.1016/j.jclinepi.2014.03.012 CrossRefGoogle Scholar
  14. 14.
    Guo AC, Cummings TJ, Dash RC, Provenzale JM (2002) Lymphomas and high-grade astrocytomas: comparison of water diffusibility and histologic characteristics. Radiology 224:177–183.  https://doi.org/10.1148/radiol.2241010637 CrossRefGoogle Scholar
  15. 15.
    Gupta A, Omuro AM, Shah AD, Graber JJ, Shi W, Zhang Z, Young RJ (2012) Continuing the search for MR imaging biomarkers for MGMT promoter methylation status: conventional and perfusion MRI revisited. Neuroradiology 54:641–643.  https://doi.org/10.1007/s00234-011-0970-z CrossRefGoogle Scholar
  16. 16.
    Gupta A, Prager A, Young RJ, Shi W, Omuro AM, Graber JJ (2013) Diffusion-weighted MR imaging and MGMT methylation status in glioblastoma: a reappraisal of the role of preoperative quantitative ADC measurements. AJNR Am J Neuroradiol 34:E10–E11.  https://doi.org/10.3174/ajnr.A3467 CrossRefGoogle Scholar
  17. 17.
    Han Y, Yan LF, Wang XB, Sun YZ, Zhang X, Liu ZC, Nan HY, Hu YC, Yang Y, Zhang J, Yu Y, Sun Q, Tian Q, Hu B, Xiao G, Wang W, Cui GB (2018) Structural and advanced imaging in predicting MGMT promoter methylation of primary glioblastoma: a region of interest based analysis. BMC Cancer 18:215.  https://doi.org/10.1186/s12885-018-4114-2 CrossRefGoogle Scholar
  18. 18.
    Hegi ME, Diserens AC, Godard S, Dietrich PY, Regli L, Ostermann S, Otten P, Van Melle G, de Tribolet N, Stupp R (2004) Clinical trial substantiates the predictive value of O-6-methylguanine-DNA methyltransferase promoter methylation in glioblastoma patients treated with temozolomide. Clin Cancer Res 10:1871–1874CrossRefGoogle Scholar
  19. 19.
    Hegi ME, Diserens AC, Gorlia T, Hamou MF, de Tribolet N, Weller M, Kros JM, Hainfellner JA, Mason W, Mariani L, Bromberg JE, Hau P, Mirimanoff RO, Cairncross JG, Janzer RC, Stupp R (2005) MGMT gene silencing and benefit from temozolomide in glioblastoma. N Engl J Med 352:997–1003.  https://doi.org/10.1056/NEJMoa043331 CrossRefGoogle Scholar
  20. 20.
    Hsu CY, Lin SC, Ho HL, Chang-Chien YC, Hsu SP, Yen YS, Chen MH, Guo WY, Ho DM (2013) Exclusion of histiocytes/endothelial cells and using endothelial cells as internal reference are crucial for interpretation of MGMT immunohistochemistry in glioblastoma. Am J Surg Pathol 37:264–271.  https://doi.org/10.1097/PAS.0b013e318267b061 CrossRefGoogle Scholar
  21. 21.
    Kanas VG, Zacharaki EI, Thomas GA, Zinn PO, Megalooikonomou V, Colen RR (2017) Learning MRI-based classification models for MGMT methylation status prediction in glioblastoma. Comput Methods Prog Biomed 140:249–257.  https://doi.org/10.1016/j.cmpb.2016.12.018 CrossRefGoogle Scholar
  22. 22.
    Kanazawa T, Fujiwara H, Takahashi H, Nishiyama Y, Hirose Y, Tanaka S, Yoshida K, Sasaki H (2018) Imaging scoring systems for preoperative molecular diagnoses of lower-grade gliomas. Neurosurg Rev.  https://doi.org/10.1007/s10143-018-0981-x
  23. 23.
    Kickingereder P, Bonekamp D, Nowosielski M, Kratz A, Sill M, Burth S, Wick A, Eidel O, Schlemmer HP, Radbruch A, Debus J, Herold-Mende C, Unterberg A, Jones D, Pfister S, Wick W, von Deimling A, Bendszus M, Capper D (2016) Radiogenomics of glioblastoma: machine learning-based classification of molecular characteristics by using multiparametric and multiregional MR imaging features. Radiology 281:907–918.  https://doi.org/10.1148/radiol.2016161382 CrossRefGoogle Scholar
  24. 24.
    Kleihues P, Burger PC, Scheithauer BW (1993) Histological typing of tumors of the central nervous system, 2nd edn. Springer, BerlinCrossRefGoogle Scholar
  25. 25.
    Kleihues P, Cavanee W (2000) Pathology and genetics of tumors of the nervous system. International Agency for Research on Cancer Press, LyonGoogle Scholar
  26. 26.
    Korfiatis P, Kline TL, Coufalova L, Lachance DH, Parney IF, Carter RE, Buckner JC, Erickson BJ (2016) MRI texture features as biomarkers to predict MGMT methylation status in glioblastomas. Med Phys 43:2835–2844.  https://doi.org/10.1118/1.4948668 CrossRefGoogle Scholar
  27. 27.
    Lechapt-Zalcman E, Levallet G, Dugue AE, Vital A, Diebold MD, Menei P, Colin P, Peruzzy P, Emery E, Bernaudin M, Chapon F, Guillamo JS (2012) O(6)-methylguanine-DNA methyltransferase (MGMT) promoter methylation and low MGMT-encoded protein expression as prognostic markers in glioblastoma patients treated with biodegradable carmustine wafer implants after initial surgery followed by radiotherapy with concomitant and adjuvant temozolomide. Cancer 118:4545–4554.  https://doi.org/10.1002/cncr.27441 CrossRefGoogle Scholar
  28. 28.
    Louis DN, Ohgaki H, Wiestler OD, Cavenee WK (2007) WHO classification of tumours of the central nervous system, 4th edn. International Agency for Research on Cancer, LyonGoogle Scholar
  29. 29.
    Louis DN, Ohgaki H, Wiestler OD, Cavenee WK, Ellison DW, Figarella-Branger D, Perry A, Reifenberger G, von Deimling A (2016) WHO classification of tumours of the central nervous system. In: Revised 4th edn. International Agency for Research on Cancer, LyonGoogle Scholar
  30. 30.
    Miwa T, Hirose Y, Sasaki H, Ikeda E, Yoshida K, Kawase T (2009) Genetic characterization of adult infratentorial gliomas. J Neuro-Oncol 91:251–255.  https://doi.org/10.1007/s11060-008-9714-2 CrossRefGoogle Scholar
  31. 31.
    Moon WJ, Choi JW, Roh HG, Lim SD, Koh YC (2012) Imaging parameters of high grade gliomas in relation to the MGMT promoter methylation status: the CT, diffusion tensor imaging, and perfusion MR imaging. Neuroradiology 54:555–563.  https://doi.org/10.1007/s00234-011-0947-y CrossRefGoogle Scholar
  32. 32.
    Omuro A, DeAngelis LM (2013) Glioblastoma and other malignant gliomas: a clinical review. Jama 310:1842–1850.  https://doi.org/10.1001/jama.2013.280319 CrossRefGoogle Scholar
  33. 33.
    Ostrom QT, Gittleman H, Fulop J, Liu M, Blanda R, Kromer C, Wolinsky Y, Kruchko C, Barnholtz-Sloan JS (2015) CBTRUS statistical report: primary brain and central nervous system tumors diagnosed in the United States in 2008-2012. Neuro-Oncology 17(Suppl 4):iv1–iv62.  https://doi.org/10.1093/neuonc/nov189 CrossRefGoogle Scholar
  34. 34.
    Pope WB, Lai A, Mehta R, Kim HJ, Qiao J, Young JR, Xue X, Goldin J, Brown MS, Nghiemphu PL, Tran A, Cloughesy TF (2011) Apparent diffusion coefficient histogram analysis stratifies progression-free survival in newly diagnosed bevacizumab-treated glioblastoma. AJNR Am J Neuroradiol 32:882–889.  https://doi.org/10.3174/ajnr.A2385 CrossRefGoogle Scholar
  35. 35.
    Prayson RA, Agamanolis DP, Cohen ML, Estes ML, Kleinschmidt-DeMasters BK, Abdul-Karim F, McClure SP, Sebek BA, Vinay R (2000) Interobserver reproducibility among neuropathologists and surgical pathologists in fibrillary astrocytoma grading. J Neurol Sci 175:33–39CrossRefGoogle Scholar
  36. 36.
    Riemenschneider MJ, Hegi ME, Reifenberger G (2010) MGMT promoter methylation in malignant gliomas. Target Oncol 5:161–165.  https://doi.org/10.1007/s11523-010-0153-6 CrossRefGoogle Scholar
  37. 37.
    Romano A, Calabria LF, Tavanti F, Minniti G, Rossi-Espagnet MC, Coppola V, Pugliese S, Guida D, Francione G, Colonnese C, Fantozzi LM, Bozzao A (2013) Apparent diffusion coefficient obtained by magnetic resonance imaging as a prognostic marker in glioblastomas: correlation with MGMT promoter methylation status. Eur Radiol 23:513–520.  https://doi.org/10.1007/s00330-012-2601-4 CrossRefGoogle Scholar
  38. 38.
    Ronning PA, Helseth E, Meling TR, Johannesen TB (2012) A population-based study on the effect of temozolomide in the treatment of glioblastoma multiforme. Neuro-Oncology 14:1178–1184.  https://doi.org/10.1093/neuonc/nos153 CrossRefGoogle Scholar
  39. 39.
    Sasaki H, Hirose Y, Yazaki T, Kitamura Y, Katayama M, Kimura T, Fujiwara H, Toda M, Ohira T, Yoshida K (2015) Upfront chemotherapy and subsequent resection for molecularly defined gliomas. J Neuro-Oncol 124:127–135.  https://doi.org/10.1007/s11060-015-1817-y CrossRefGoogle Scholar
  40. 40.
    Sasaki H, Zlatescu MC, Betensky RA, Ino Y, Cairncross JG, Louis DN (2001) PTEN is a target of chromosome 10q loss in anaplastic oligodendrogliomas and PTEN alterations are associated with poor prognosis. Am J Pathol 159:359–367.  https://doi.org/10.1016/s0002-9440(10)61702-6 CrossRefGoogle Scholar
  41. 41.
    Squillaci E, Manenti G, Cova M, Di Roma M, Miano R, Palmieri G, Simonetti G (2004) Correlation of diffusion-weighted MR imaging with cellularity of renal tumours. Anticancer Res 24:4175–4179Google Scholar
  42. 42.
    Stupp R, Mason WP, van den Bent MJ, Weller M, Fisher B, Taphoorn MJ, Belanger K, Brandes AA, Marosi C, Bogdahn U, Curschmann J, Janzer RC, Ludwin SK, Gorlia T, Allgeier A, Lacombe D, Cairncross JG, Eisenhauer E, Mirimanoff RO (2005) Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. N Engl J Med 352:987–996.  https://doi.org/10.1056/NEJMoa043330 CrossRefGoogle Scholar
  43. 43.
    Stupp R, Taillibert S, Kanner AA, Kesari S, Steinberg DM, Toms SA, Taylor LP, Lieberman F, Silvani A, Fink KL, Barnett GH, Zhu JJ, Henson JW, Engelhard HH, Chen TC, Tran DD, Sroubek J, Tran ND, Hottinger AF, Landolfi J, Desai R, Caroli M, Kew Y, Honnorat J, Idbaih A, Kirson ED, Weinberg U, Palti Y, Hegi ME, Ram Z (2015) Maintenance therapy with tumor-treating fields plus temozolomide vs temozolomide alone for glioblastoma: a randomized clinical trial. Jama 314:2535–2543.  https://doi.org/10.1001/jama.2015.16669 CrossRefGoogle Scholar
  44. 44.
    Sunwoo L, Choi SH, Park CK, Kim JW, Yi KS, Lee WJ, Yoon TJ, Song SW, Kim JE, Kim JY, Kim TM, Lee SH, Kim JH, Sohn CH, Park SH, Kim IH, Chang KH (2013) Correlation of apparent diffusion coefficient values measured by diffusion MRI and MGMT promoter methylation semiquantitatively analyzed with MS-MLPA in patients with glioblastoma multiforme. J Magn Reson Imaging 37:351–358.  https://doi.org/10.1002/jmri.23838 CrossRefGoogle Scholar
  45. 45.
    Urbschat S, Sippl C, Engelhardt J, Kammers K, Oertel J, Ketter R (2017) Importance of biomarkers in glioblastomas patients receiving local BCNU wafer chemotherapy. Mol Cytogenet 10:16.  https://doi.org/10.1186/s13039-017-0317-5 CrossRefGoogle Scholar
  46. 46.
    van den Bent MJ, Baumert B, Erridge SC, Vogelbaum MA, Nowak AK, Sanson M, Brandes AA, Clement PM, Baurain JF, Mason WP, Wheeler H, Chinot OL, Gill S, Griffin M, Brachman DG, Taal W, Ruda R, Weller M, McBain C, Reijneveld J, Enting RH, Weber DC, Lesimple T, Clenton S, Gijtenbeek A, Pascoe S, Herrlinger U, Hau P, Dhermain F, van Heuvel I, Stupp R, Aldape K, Jenkins RB, Dubbink HJ, Dinjens WNM, Wesseling P, Nuyens S, Golfinopoulos V, Gorlia T, Wick W, Kros JM (2017) Interim results from the CATNON trial (EORTC study 26053-22054) of treatment with concurrent and adjuvant temozolomide for 1p/19q non-co-deleted anaplastic glioma: a phase 3, randomised, open-label intergroup study. Lancet 390:1645–1653.  https://doi.org/10.1016/s0140-6736(17)31442-3 CrossRefGoogle Scholar
  47. 47.
    Weller M, Stupp R, Reifenberger G, Brandes AA, van den Bent MJ, Wick W, Hegi ME (2010) MGMT promoter methylation in malignant gliomas: ready for personalized medicine? Nat Rev Neurol 6:39–51.  https://doi.org/10.1038/nrneurol.2009.197 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of NeurosurgeryKeio University School of MedicineTokyoJapan
  2. 2.Department of Diagnostic RadiologyKeio University School of MedicineTokyoJapan

Personalised recommendations