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Published on: October 4, 2019
A Novel Pseudogene Methylation Signature to Predict Temozolomide Outcome in Non-G-CIMP Glioblastomas
Bowen Li1, Jiu Wang2, Fangfang Liu3
1Department of Biochemistry and Molecular Biology, Air Force Medical University, Xi'an, China.
Objective:
Alterations in the methylation state of pseudogenes may serve as clinically useful biomarkers of glioblastomas (GBMs) that do not have glioma-CpG island methylator phenotype (G-CIMP).
Methods:
Non-G-CIMP GBM datasets were included for evaluation, and a RISK-score signature was determined from the methylation state of pseudogene loci. Both bioinformatic and experimental analyses were performed for biological validation.
Results:
By integrating clinical information with DNA methylation microarray data, we screened a panel of eight CpGs from discovery cohorts of non-G-CIMP GBMs. Each CpG could accurately and independently predict the prognosis of patients under a treatment regime that combined radiotherapy (RT) and temozolomide (TMZ). The 8-CpG signature appeared to show opposite prognostic correlations between patients treated with RT/TMZ and those treated with RT monotherapy. The analyses further indicated that this signature had predictive value for TMZ efficacy because different survival benefits between RT/TMZ and RT therapies were observed in each risk subgroup. The incorporation of other risk factors, such as age and O-6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status, with our pseudogene methylation signature could provide precise risk classification. In vitro experimental data revealed that two locus-specific pseudogenes (ZNF767P and CLEC4GP1) may modulate TMZ resistance via distinct mechanisms in GBM cells.
Conclusion:
The biologically and clinically relevant RISK-score signature, based on pseudogene methylation loci, may offer information for predicting TMZ responses of non-G-CIMP GBMs, that is independent from, but complementary to, MGMT-based approaches.
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