Aim: We aimed to identify potent CpG signatures predicting temozolomide (TMZ) response in glioblastomas (GBMs) that do not have the glioma-CpG island methylator phenotype (G-CIMP) but have a methylated promoter of MGMT (meMGMT). Materials & methods: Different datasets of non-G-CIMP meMGMT GBMs with molecular and clinical data were analyzed. Results: A panel of 77 TMZ efficacy-related CpGs and a seven-CpG risk signature were identified and validated for distinguishing differential outcomes to radiotherapy plus TMZ versus radiotherapy alone in non-G-CIMP meMGMT GBMs. An integrated classification scheme was also proposed for refining a MGMT-based TMZ-guiding approach in all G-CIMP-GBMs. Conclusion: The CpG signatures may serve as promising predictive biomarker candidates for guiding optimal TMZ usage in non-G-CIMP meMGMT GBMs.
Keywords: DNA methylation; glioblastoma; methylated MGMT; predictive biomarker; temozolomide.
Glioblastomas that do not have the glioma-CpG island methylator phenotype (G-CIMP) but have a methylated promoter of the MGMT gene (meMGMT) show considerable variability in their response to temozolomide (TMZ). Powerful biomarkers that provide predictive information on optimal TMZ decision-making can be clinically useful. This study has identified and validated a panel of 77 TMZ efficacy-related CpGs and a seven-CpG risk signature for predicting TMZ usage in non-G-CIMP meMGMT glioblastomas. An integrated classification scheme is proposed for refining a MGMT-based TMZ-guiding approach in non-G-CIMP glioblastomas.