Evidence map›Paper›PMID 30291347›Full record

ArticleModern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc2019

A novel analytical model of MGMT methylation pyrosequencing offers improved predictive performance in patients with gliomas.

Rui-Chao Chai, Yu-Qing Liu, Ke-Nan Zhang, Fan Wu, Zheng Zhao, Kuan-Yu Wang, Tao Jiang, Yong-Zhi Wang

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Article in Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

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30citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

30 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Rui-Chao ChaiDepartment of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.ORCID http://orcid.org/0000-0003-3451-8871
Yu-Qing LiuDepartment of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Ke-Nan ZhangDepartment of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Fan WuDepartment of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Zheng ZhaoDepartment of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Kuan-Yu WangDepartment of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Tao JiangDepartment of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Yong-Zhi WangDepartment of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China. yongzhiwang_bni@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The methylation status of the promoter of MGMT gene is a crucial factor influencing clinical decision-making in patients with gliomas. MGMT pyrosequencing results are often dichotomized by a cut-off value based on an average of several tested CpGs. However, this method frequently results in a "gray zone", representing a dilemma for physicians. We therefore propose a novel analytical model for MGMT methylation pyrosequencing. MGMT CpG heterogeneity was investigated in 213 glioma patients in two tested cohorts: cohort A in which CpGs 75-82 were tested and cohort B in which CpGs 72-78 were tested. The predictive performances of the novel and traditional averaging models were compared in 135 patients who received temozolomide using receiver operating characteristic curves and Kaplan-Meier curves, and in patients stratified according to isocitrate dehydrogenase gene mutation status. The results were validated in an independent cohort of 65 consecutive patients with high-grade gliomas from the Chinese Glioma Genome Atlas database. Heterogeneity of MGMT promoter CpG methylation level was observed in most gliomas. The optimal cut-off value for each individual CpG varied from 4-16%. The current analysis defined MGMT promoter methylation as occurring when at least three CpGs exceeded their respective cut-off values. This novel analysis could accurately predict the prognosis of patients in the methylation "gray zone" according to the standard averaging method, and improved the area under the curves from 0.67, 0.76, and 0.67 to 0.70, 0.84, and 0.72 in cohorts A, B, and the validation cohort, respectively, demonstrating superiority of this analytical method in all three cohorts. Furthermore, the advantages of the novel analysis were retained regardless of WHO grade and isocitrate dehydrogenase gene mutation status. In conclusion, this novel analytical model offers an improved clinical predictive performance for MGMT pyrosequencing results and is suitable for clinical use in patients with gliomas.

Indexed as

DNA MethylationAdultBrain NeoplasmsDNA Modification MethylasesDNA Repair EnzymesFemaleGliomaHigh-Throughput Nucleotide SequencingHumansMaleMiddle AgedTumor Suppressor ProteinsDNA Modification MethylasesDNA Repair EnzymesMGMT protein, humanTumor Suppressor Proteins

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.