1
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Chehade G, El Hajj N, Aittaleb M, Alkailani MI, Bejaoui Y, Mahdi A, Aldaalis AAH, Verbiest M, Lelotte J, Ruiz-Reig N, Durá I, Raftopoulos C, Tajeddine N, Tissir F. DIAPH3 predicts survival of patients with MGMT-methylated glioblastoma. Front Oncol 2024; 14:1359652. [PMID: 38454929 PMCID: PMC10917989 DOI: 10.3389/fonc.2024.1359652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 02/07/2024] [Indexed: 03/09/2024] Open
Abstract
Background Glioblastoma is one of the most aggressive primary brain tumors, with a poor outcome despite multimodal treatment. Methylation of the MGMT promoter, which predicts the response to temozolomide, is a well-established prognostic marker for glioblastoma. However, a difference in survival can still be detected within the MGMT methylated group, with some patients exhibiting a shorter survival than others, emphasizing the need for additional predictive factors. Methods We analyzed DIAPH3 expression in glioblastoma samples from the cancer genome atlas (TCGA). We also retrospectively analyzed one hundred seventeen histological glioblastomas from patients operated on at Saint-Luc University Hospital between May 2013 and August 2019. We analyzed the DIAPH3 expression, explored the relationship between mRNA levels and Patient's survival after the surgical resection. Finally, we assessed the methylation pattern of the DIAPH3 promoter using a targeted deep bisulfite sequencing approach. Results We found that 36% and 1% of the TCGA glioblastoma samples exhibit copy number alterations and mutations in DIAPH3, respectively. We scrutinized the expression of DIAPH3 at single cell level and detected an overlap with MKI67 expression in glioblastoma proliferating cells, including neural progenitor-like, oligodendrocyte progenitor-like and astrocyte-like states. We quantitatively analyzed DIAPH3 expression in our cohort and uncovered a positive correlation between DIAPH3 mRNA level and patient's survival. The effect of DIAPH3 was prominent in MGMT-methylated glioblastoma. Finally, we report that the expression of DIAPH3 is at least partially regulated by the methylation of three CpG sites in the promoter region. Conclusion We propose that combining the DIAPH3 expression with MGMT methylation could offer a better prediction of survival and more adapted postsurgical treatment for patients with MGMT-methylated glioblastoma.
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Affiliation(s)
- Georges Chehade
- Université Catholique de Louvain, Institute of Neuroscience, Cellular and Molecular Division, Brussels, Belgium
| | - Nady El Hajj
- College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, Qatar
| | - Mohamed Aittaleb
- College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, Qatar
| | - Maisa I. Alkailani
- College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, Qatar
| | - Yosra Bejaoui
- College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, Qatar
| | - Asma Mahdi
- College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, Qatar
| | - Arwa A. H. Aldaalis
- College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, Qatar
| | - Michael Verbiest
- Laboratory of Population Genomics, Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Julie Lelotte
- Department of Neuropathology, Saint-Luc University Hospital, Brussels, Belgium
| | - Nuria Ruiz-Reig
- Université Catholique de Louvain, Institute of Neuroscience, Cellular and Molecular Division, Brussels, Belgium
| | - Irene Durá
- Université Catholique de Louvain, Institute of Neuroscience, Cellular and Molecular Division, Brussels, Belgium
| | | | - Nicolas Tajeddine
- Université Catholique de Louvain, Institute of Neuroscience, Cellular and Molecular Division, Brussels, Belgium
| | - Fadel Tissir
- Université Catholique de Louvain, Institute of Neuroscience, Cellular and Molecular Division, Brussels, Belgium
- College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, Qatar
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2
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Bonder MJ, Luijk R, Zhernakova DV, Moed M, Deelen P, Vermaat M, van Iterson M, van Dijk F, van Galen M, Bot J, Slieker RC, Jhamai PM, Verbiest M, Suchiman HED, Verkerk M, van der Breggen R, van Rooij J, Lakenberg N, Arindrarto W, Kielbasa SM, Jonkers I, van 't Hof P, Nooren I, Beekman M, Deelen J, van Heemst D, Zhernakova A, Tigchelaar EF, Swertz MA, Hofman A, Uitterlinden AG, Pool R, van Dongen J, Hottenga JJ, Stehouwer CDA, van der Kallen CJH, Schalkwijk CG, van den Berg LH, van Zwet EW, Mei H, Li Y, Lemire M, Hudson TJ, Slagboom PE, Wijmenga C, Veldink JH, van Greevenbroek MMJ, van Duijn CM, Boomsma DI, Isaacs A, Jansen R, van Meurs JBJ, 't Hoen PAC, Franke L, Heijmans BT. Disease variants alter transcription factor levels and methylation of their binding sites. Nat Genet 2016; 49:131-138. [PMID: 27918535 DOI: 10.1038/ng.3721] [Citation(s) in RCA: 289] [Impact Index Per Article: 36.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2015] [Accepted: 10/18/2016] [Indexed: 12/15/2022]
Abstract
Most disease-associated genetic variants are noncoding, making it challenging to design experiments to understand their functional consequences. Identification of expression quantitative trait loci (eQTLs) has been a powerful approach to infer the downstream effects of disease-associated variants, but most of these variants remain unexplained. The analysis of DNA methylation, a key component of the epigenome, offers highly complementary data on the regulatory potential of genomic regions. Here we show that disease-associated variants have widespread effects on DNA methylation in trans that likely reflect differential occupancy of trans binding sites by cis-regulated transcription factors. Using multiple omics data sets from 3,841 Dutch individuals, we identified 1,907 established trait-associated SNPs that affect the methylation levels of 10,141 different CpG sites in trans (false discovery rate (FDR) < 0.05). These included SNPs that affect both the expression of a nearby transcription factor (such as NFKB1, CTCF and NKX2-3) and methylation of its respective binding site across the genome. Trans methylation QTLs effectively expose the downstream effects of disease-associated variants.
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Affiliation(s)
- Marc Jan Bonder
- University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, the Netherlands
| | - René Luijk
- Molecular Epidemiology Section, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, the Netherlands
| | - Daria V Zhernakova
- University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, the Netherlands
| | - Matthijs Moed
- Molecular Epidemiology Section, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, the Netherlands
| | - Patrick Deelen
- University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, the Netherlands.,University of Groningen, University Medical Center Groningen, Genomics Coordination Center, Groningen, the Netherlands
| | - Martijn Vermaat
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Maarten van Iterson
- Molecular Epidemiology Section, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, the Netherlands
| | - Freerk van Dijk
- University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, the Netherlands.,University of Groningen, University Medical Center Groningen, Genomics Coordination Center, Groningen, the Netherlands
| | - Michiel van Galen
- University of Groningen, University Medical Center Groningen, Genomics Coordination Center, Groningen, the Netherlands
| | - Jan Bot
- SURFsara, Amsterdam, the Netherlands
| | - Roderick C Slieker
- Molecular Epidemiology Section, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, the Netherlands
| | - P Mila Jhamai
- Department of Internal Medicine, ErasmusMC, Rotterdam, the Netherlands
| | - Michael Verbiest
- University of Groningen, University Medical Center Groningen, Genomics Coordination Center, Groningen, the Netherlands
| | - H Eka D Suchiman
- Molecular Epidemiology Section, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, the Netherlands
| | - Marijn Verkerk
- Department of Internal Medicine, ErasmusMC, Rotterdam, the Netherlands
| | - Ruud van der Breggen
- Molecular Epidemiology Section, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, the Netherlands
| | - Jeroen van Rooij
- Department of Internal Medicine, ErasmusMC, Rotterdam, the Netherlands
| | - Nico Lakenberg
- Molecular Epidemiology Section, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, the Netherlands
| | - Wibowo Arindrarto
- Medical Statistics Section, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, the Netherlands
| | - Szymon M Kielbasa
- Sequence Analysis Support Core, Leiden University Medical Center, Leiden, the Netherlands
| | - Iris Jonkers
- University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, the Netherlands
| | - Peter van 't Hof
- Sequence Analysis Support Core, Leiden University Medical Center, Leiden, the Netherlands
| | | | - Marian Beekman
- Molecular Epidemiology Section, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, the Netherlands
| | - Joris Deelen
- Molecular Epidemiology Section, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, the Netherlands
| | - Diana van Heemst
- Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Alexandra Zhernakova
- University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, the Netherlands
| | - Ettje F Tigchelaar
- University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, the Netherlands
| | - Morris A Swertz
- University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, the Netherlands.,University of Groningen, University Medical Center Groningen, Genomics Coordination Center, Groningen, the Netherlands
| | - Albert Hofman
- Department of Epidemiology, ErasmusMC, Rotterdam, the Netherlands
| | | | - René Pool
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands
| | - Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands
| | - Jouke J Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands
| | - Coen D A Stehouwer
- Department of Internal Medicine, Maastricht University Medical Center, Maastricht, the Netherlands.,School for Cardiovascular Diseases (CARIM), Maastricht University Medical Center, Maastricht, the Netherlands
| | - Carla J H van der Kallen
- Department of Internal Medicine, Maastricht University Medical Center, Maastricht, the Netherlands.,School for Cardiovascular Diseases (CARIM), Maastricht University Medical Center, Maastricht, the Netherlands
| | - Casper G Schalkwijk
- Department of Internal Medicine, Maastricht University Medical Center, Maastricht, the Netherlands.,School for Cardiovascular Diseases (CARIM), Maastricht University Medical Center, Maastricht, the Netherlands
| | - Leonard H van den Berg
- Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Erik W van Zwet
- Medical Statistics Section, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, the Netherlands
| | - Hailiang Mei
- Sequence Analysis Support Core, Leiden University Medical Center, Leiden, the Netherlands
| | - Yang Li
- University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, the Netherlands
| | - Mathieu Lemire
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Thomas J Hudson
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.,Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | | | - P Eline Slagboom
- Molecular Epidemiology Section, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, the Netherlands
| | - Cisca Wijmenga
- University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, the Netherlands
| | - Jan H Veldink
- Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Marleen M J van Greevenbroek
- Department of Internal Medicine, Maastricht University Medical Center, Maastricht, the Netherlands.,School for Cardiovascular Diseases (CARIM), Maastricht University Medical Center, Maastricht, the Netherlands
| | - Cornelia M van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, ErasmusMC, Rotterdam, the Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands
| | - Aaron Isaacs
- School for Cardiovascular Diseases (CARIM), Maastricht University Medical Center, Maastricht, the Netherlands.,Genetic Epidemiology Unit, Department of Epidemiology, ErasmusMC, Rotterdam, the Netherlands.,Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, the Netherlands
| | - Rick Jansen
- Department of Psychiatry, VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands
| | | | - Peter A C 't Hoen
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Lude Franke
- University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, the Netherlands
| | - Bastiaan T Heijmans
- Molecular Epidemiology Section, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, the Netherlands
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van der Kleij R, Coster N, Verbiest M, van Assema P, Paulussen T, Reis R, Crone M. Implementation of intersectoral community approaches targeting childhood obesity: a systematic review. Obes Rev 2015; 16:454-72. [PMID: 25824957 DOI: 10.1111/obr.12273] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2014] [Revised: 01/19/2015] [Accepted: 02/05/2015] [Indexed: 10/23/2022]
Abstract
The implementation of intersectoral community approaches targeting childhood obesity (IACO) is considered challenging. To help overcome these challenges, an overview of the evidence to date is needed. We searched four databases to identify papers that reported on the determinants of successful implementation of IACOs, resulting in the inclusion of 25 studies. We appraised study quality with the Crowe Critical Appraisal Tool and the Quality Framework; reported implementation outcome indicators were reviewed via narrative synthesis. Quality of included studies varied. The most frequently reported indicators of implementation success were fidelity and coverage. Determinants related to the social-political context and the organization were most often cited as influencing implementation, in particular, 'collaboration between community partners', 'the availability of (human) resources' and 'time available for implementation'. The association between determinants and implementation variability was never explicated. We conclude that although some insights into the effective implementation of IACOs are present, more research is needed. Emphasis should be placed on elucidating the relationship between determinants and implementation success. Research should further focus on developing a 'golden standard' for evaluating and reporting on implementation research. These actions will improve the comparison of study outcomes and may constitute the cumulative development of knowledge about the conditions for designing evidence-based implementation strategies.
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Affiliation(s)
- R van der Kleij
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands.,Academic Workplace (AWP) Public Health Zuid-Holland Noord, Leiden, The Netherlands
| | - N Coster
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands
| | - M Verbiest
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands
| | - P van Assema
- Department of Health Promotion, NUTRIM School for Nutrition, Toxicology and Metabolism, Maastricht University Medical Center, Maastricht, The Netherlands
| | - T Paulussen
- Academic Workplace (AWP) Public Health Zuid-Holland Noord, Leiden, The Netherlands.,TNO Leiden, Leiden, The Netherlands
| | - R Reis
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands.,Academic Workplace (AWP) Public Health Zuid-Holland Noord, Leiden, The Netherlands.,Amsterdam Institute for Social Science Research, University of Amsterdam, The Netherlands
| | - M Crone
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands.,Academic Workplace (AWP) Public Health Zuid-Holland Noord, Leiden, The Netherlands
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4
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Labruijere S, Stolk L, Verbiest M, de Vries R, Garrelds IM, Eilers PHC, Danser AHJ, Uitterlinden AG, MaassenVanDenBrink A. Methylation of migraine-related genes in different tissues of the rat. PLoS One 2014; 9:e87616. [PMID: 24609082 PMCID: PMC3946422 DOI: 10.1371/journal.pone.0087616] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2013] [Accepted: 12/20/2013] [Indexed: 11/26/2022] Open
Abstract
17ß-Estradiol, an epigenetic modulator, is involved in the increased prevalence of migraine in women. Together with the prophylactic efficacy of valproate, which influences DNA methylation and histone modification, this points to the involvement of epigenetic mechanisms. Epigenetic studies are often performed on leukocytes, but it is unclear to what extent methylation is similar in other tissues. Therefore, we investigated methylation of migraine-related genes that might be epigenetically regulated (CGRP-ergic pathway, estrogen receptors, endothelial NOS, as well as MTHFR) in different migraine-related tissues and compared this to methylation in rat as well as human leukocytes. Further, we studied whether 17ß-estradiol has a prominent role in methylation of these genes. Female rats (n = 35) were ovariectomized or sham-operated and treated with 17β-estradiol or placebo. DNA was isolated and methylation was assessed through bisulphite treatment and mass spectrometry. Human methylation data were obtained using the Illumina 450k genome-wide methylation array in 395 female subjects from a population-based cohort study. We showed that methylation of the Crcp, Calcrl, Esr1 and Nos3 genes is tissue-specific and that methylation in leukocytes was not correlated to that in other tissues. Interestingly, the interindividual variation in methylation differed considerably between genes and tissues. Furthermore we showed that methylation in human leukocytes was similar to that in rat leukocytes in our genes of interest, suggesting that rat may be a good model to study human DNA methylation in tissues that are difficult to obtain. In none of the genes a significant effect of estradiol treatment was observed.
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Affiliation(s)
- Sieneke Labruijere
- Dept. of Internal Medicine, Div. of Pharmacology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Lisette Stolk
- Dept. of Internal Medicine, Genetics Laboratory, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Michael Verbiest
- Dept. of Internal Medicine, Genetics Laboratory, Erasmus Medical Center, Rotterdam, The Netherlands
| | - René de Vries
- Dept. of Internal Medicine, Div. of Pharmacology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Ingrid M. Garrelds
- Dept. of Internal Medicine, Div. of Pharmacology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Paul H. C. Eilers
- Dept. of Biostatistics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - A. H. Jan Danser
- Dept. of Internal Medicine, Div. of Pharmacology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - André G. Uitterlinden
- Dept. of Internal Medicine, Genetics Laboratory, Erasmus Medical Center, Rotterdam, The Netherlands
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