Cargando…

Prognostic prediction of glioblastoma by quantitative assessment of the methylation status of the entire MGMT promoter region

BACKGROUND: O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation is reported to be a prognostic and predictive factor of alkylating chemotherapy for glioblastoma patients. Methylation specific PCR (MSP) has been most commonly used when the methylation status of MGMT is assessed. Howeve...

Descripción completa

Detalles Bibliográficos
Autores principales: Kanemoto, Manabu, Shirahata, Mitsuaki, Nakauma, Akiyo, Nakanishi, Katsumi, Taniguchi, Kazuya, Kukita, Yoji, Arakawa, Yoshiki, Miyamoto, Susumu, Kato, Kikuya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4161852/
https://www.ncbi.nlm.nih.gov/pubmed/25175833
http://dx.doi.org/10.1186/1471-2407-14-641
_version_ 1782334606449573888
author Kanemoto, Manabu
Shirahata, Mitsuaki
Nakauma, Akiyo
Nakanishi, Katsumi
Taniguchi, Kazuya
Kukita, Yoji
Arakawa, Yoshiki
Miyamoto, Susumu
Kato, Kikuya
author_facet Kanemoto, Manabu
Shirahata, Mitsuaki
Nakauma, Akiyo
Nakanishi, Katsumi
Taniguchi, Kazuya
Kukita, Yoji
Arakawa, Yoshiki
Miyamoto, Susumu
Kato, Kikuya
author_sort Kanemoto, Manabu
collection PubMed
description BACKGROUND: O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation is reported to be a prognostic and predictive factor of alkylating chemotherapy for glioblastoma patients. Methylation specific PCR (MSP) has been most commonly used when the methylation status of MGMT is assessed. However, technical obstacles have hampered the implementation of MSP-based diagnostic tests. We quantitatively analyzed the methylation status of the entire MGMT promoter region and applied this information for prognostic prediction using sequencing technology. METHODS: Between 1998 and 2012, the genomic DNA of 85 tumor samples from newly diagnosed glioblastoma patients was subjected to bisulfite treatment and subdivided into a training set, consisting of fifty-three samples, and a test set, consisting of thirty-two samples. The training set was analyzed by deep Sanger sequencing with a sequencing coverage of up to 96 clones per sample. This analysis quantitatively revealed the degree of methylation of each cytidine phosphate guanosine (CpG) site. Based on these data, we constructed a prognostic prediction system for glioblastoma patients using a supervised learning method. We then validated this prediction system by deep sequencing with a next-generation sequencer using a test set of 32 samples. RESULTS: The methylation status of the MGMT promoter was correlated with progression-free survival (PFS) in our patient population in the training set. The degree of correlation differed among the CpG sites. Using the data from the top twenty CpG sites, we constructed a prediction system for overall survival (OS) and PFS. The system successfully classified patients into good and poor prognosis groups in both the training set (OS, p = 0.0381; PFS, p = 0.00122) and the test set (OS, p = 0.0476; PFS, p = 0.0376). Conventional MSP could not predict the prognosis in either of our sets. (training set: OS; p = 0.993 PFS; p = 0.113, test set: OS; p = 0.326 PFS; p = 0.342). CONCLUSIONS: The prognostic ability of our prediction system using sequencing data was better than that of methylation-specific PCR (MSP). Advances in sequencing technologies will make this approach a plausible option for diagnoses based on MGMT promotor methylation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2407-14-641) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-4161852
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-41618522014-09-13 Prognostic prediction of glioblastoma by quantitative assessment of the methylation status of the entire MGMT promoter region Kanemoto, Manabu Shirahata, Mitsuaki Nakauma, Akiyo Nakanishi, Katsumi Taniguchi, Kazuya Kukita, Yoji Arakawa, Yoshiki Miyamoto, Susumu Kato, Kikuya BMC Cancer Research Article BACKGROUND: O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation is reported to be a prognostic and predictive factor of alkylating chemotherapy for glioblastoma patients. Methylation specific PCR (MSP) has been most commonly used when the methylation status of MGMT is assessed. However, technical obstacles have hampered the implementation of MSP-based diagnostic tests. We quantitatively analyzed the methylation status of the entire MGMT promoter region and applied this information for prognostic prediction using sequencing technology. METHODS: Between 1998 and 2012, the genomic DNA of 85 tumor samples from newly diagnosed glioblastoma patients was subjected to bisulfite treatment and subdivided into a training set, consisting of fifty-three samples, and a test set, consisting of thirty-two samples. The training set was analyzed by deep Sanger sequencing with a sequencing coverage of up to 96 clones per sample. This analysis quantitatively revealed the degree of methylation of each cytidine phosphate guanosine (CpG) site. Based on these data, we constructed a prognostic prediction system for glioblastoma patients using a supervised learning method. We then validated this prediction system by deep sequencing with a next-generation sequencer using a test set of 32 samples. RESULTS: The methylation status of the MGMT promoter was correlated with progression-free survival (PFS) in our patient population in the training set. The degree of correlation differed among the CpG sites. Using the data from the top twenty CpG sites, we constructed a prediction system for overall survival (OS) and PFS. The system successfully classified patients into good and poor prognosis groups in both the training set (OS, p = 0.0381; PFS, p = 0.00122) and the test set (OS, p = 0.0476; PFS, p = 0.0376). Conventional MSP could not predict the prognosis in either of our sets. (training set: OS; p = 0.993 PFS; p = 0.113, test set: OS; p = 0.326 PFS; p = 0.342). CONCLUSIONS: The prognostic ability of our prediction system using sequencing data was better than that of methylation-specific PCR (MSP). Advances in sequencing technologies will make this approach a plausible option for diagnoses based on MGMT promotor methylation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2407-14-641) contains supplementary material, which is available to authorized users. BioMed Central 2014-08-30 /pmc/articles/PMC4161852/ /pubmed/25175833 http://dx.doi.org/10.1186/1471-2407-14-641 Text en © Kanemoto et al.; licensee BioMed Central Ltd. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Kanemoto, Manabu
Shirahata, Mitsuaki
Nakauma, Akiyo
Nakanishi, Katsumi
Taniguchi, Kazuya
Kukita, Yoji
Arakawa, Yoshiki
Miyamoto, Susumu
Kato, Kikuya
Prognostic prediction of glioblastoma by quantitative assessment of the methylation status of the entire MGMT promoter region
title Prognostic prediction of glioblastoma by quantitative assessment of the methylation status of the entire MGMT promoter region
title_full Prognostic prediction of glioblastoma by quantitative assessment of the methylation status of the entire MGMT promoter region
title_fullStr Prognostic prediction of glioblastoma by quantitative assessment of the methylation status of the entire MGMT promoter region
title_full_unstemmed Prognostic prediction of glioblastoma by quantitative assessment of the methylation status of the entire MGMT promoter region
title_short Prognostic prediction of glioblastoma by quantitative assessment of the methylation status of the entire MGMT promoter region
title_sort prognostic prediction of glioblastoma by quantitative assessment of the methylation status of the entire mgmt promoter region
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4161852/
https://www.ncbi.nlm.nih.gov/pubmed/25175833
http://dx.doi.org/10.1186/1471-2407-14-641
work_keys_str_mv AT kanemotomanabu prognosticpredictionofglioblastomabyquantitativeassessmentofthemethylationstatusoftheentiremgmtpromoterregion
AT shirahatamitsuaki prognosticpredictionofglioblastomabyquantitativeassessmentofthemethylationstatusoftheentiremgmtpromoterregion
AT nakaumaakiyo prognosticpredictionofglioblastomabyquantitativeassessmentofthemethylationstatusoftheentiremgmtpromoterregion
AT nakanishikatsumi prognosticpredictionofglioblastomabyquantitativeassessmentofthemethylationstatusoftheentiremgmtpromoterregion
AT taniguchikazuya prognosticpredictionofglioblastomabyquantitativeassessmentofthemethylationstatusoftheentiremgmtpromoterregion
AT kukitayoji prognosticpredictionofglioblastomabyquantitativeassessmentofthemethylationstatusoftheentiremgmtpromoterregion
AT arakawayoshiki prognosticpredictionofglioblastomabyquantitativeassessmentofthemethylationstatusoftheentiremgmtpromoterregion
AT miyamotosusumu prognosticpredictionofglioblastomabyquantitativeassessmentofthemethylationstatusoftheentiremgmtpromoterregion
AT katokikuya prognosticpredictionofglioblastomabyquantitativeassessmentofthemethylationstatusoftheentiremgmtpromoterregion