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...
Autores principales: | , , , , , , , , |
---|---|
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 |