A Novel Pseudogene Methylation Signature to Predict Temozolomide Outcome in Non-G-CIMP Glioblastomas

  • J Oncol. 2022 Jun 6:2022:6345160. doi: 10.1155/2022/6345160.
Bowen Li  1 ,  Jiu Wang  2 ,  Fangfang Liu  3 ,  Rui Li  1 ,  Weihong Hu  1 ,  Amandine Etcheverry  4 ,  Marc Aubry  4 ,  Jean Mosser  4 ,  Anan Yin  2  5 ,  Xiang Zhang  2 ,  Yuanming Wu  1 ,  Kun Chen  6 ,  Yalong He  2 ,  Li Wang  7
Affiliations
  • 1. Department of Biochemistry and Molecular Biology, Air Force Medical University, Xi'an, China.
  • 2. Department of Neurosurgery, Xijing Institute of Clinical Neuroscience, Xijing Hospital, Air Force Medical University, Xi'an, China.
  • 3. Institute of Neurosciences, Air Force Medical University, Xi'an, China.
  • 4. CNRS, UMR 6290, Institut de Génétique et Développement de Rennes (IGdR), Rennes F-35043, France.
  • 5. Department of Plastic and Reconstructive Surgery, Xijing Hospital, Air Force Medical University, Xi'an, China.
  • 6. Department of Anatomy, Histology and Embryology and K.K. Leung Brain Research Centre, Air Force Medical University, Xi'an, China.
  • 7. School of Aerospace Medicine, Air Force Medical University, Xi'an, China.
PMID: 35712126 DOI: 10.1155/2022/6345160
Abstract

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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