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Zhao N, Ruan M, Koestler DC, Lu J, Marsit CJ, Kelsey KT, Platz EA, Michaud DS. Epigenome-wide scan identifies differentially methylated regions for lung cancer using pre-diagnostic peripheral blood. Epigenetics 2021; 17:460-472. [PMID: 34008478 DOI: 10.1080/15592294.2021.1923615] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022] Open
Abstract
BACKGROUND DNA methylation markers have been associated with lung cancer risk and may identify aetiologically relevant genomic regions, or alternatively, be markers of disease risk factors or biological processes associated with disease development. METHODS In a nested case-control study, we measured blood leukocyte DNA methylation levels in pre-diagnostic samples collected from 430 participants (208 cases; 222 controls) in the 1989 CLUE II cohort. We compared DNA methylation levels with case/control status to identify novel genomic regions, both single CpG sites and differentially methylated regions (DMRs), while controlling for known DNA methylation changes associated with smoking using a previously described pack-years-based smoking methylation score. Stratification analyses were conducted over time from blood draw to diagnosis, histology, and smoking status. RESULTS We identified 16 single CpG sites and 40 DMRs significantly associated with lung cancer risk (q < 0.05). The identified genomic regions were associated with genes including H19, HOXA3/HOXA4, RUNX3, BRICD5, PLXNB2, and RP13. For the single CpG sites, the strongest association was noted for cg09736286 in the DIABLO gene (OR [for 1 SD] = 2.99, 95% CI: 1.95-4.59, P-value = 4.81 × 10-7). We found that CpG sites in the HOXA3/HOXA4 region were hypermethylated in cases compared to controls. CONCLUSION The single CpG sites and DMRs that we identified represented significant measurable differences in lung cancer risk, providing potential biomarkers for lung cancer risk stratification. Future studies will need to examine whether these regions are causally related to lung cancer.
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Affiliation(s)
- Naisi Zhao
- Department of Public Health & Community Medicine, Tufts University School of Medicine, Tufts University, Boston, MA, USA
| | - Mengyuan Ruan
- Department of Public Health & Community Medicine, Tufts University School of Medicine, Tufts University, Boston, MA, USA
| | - Devin C Koestler
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS, USA.,University of Kansas Cancer Center, University of Kansas Medical Center, Kansas City, KS, USA
| | - Jiayun Lu
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Carmen J Marsit
- Department of Environmental Health and Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Karl T Kelsey
- Department of Epidemiology, Brown University, Providence, RI, USA.,Department of Pathology and Laboratory Medicine, Brown University, Providence, RI, USA
| | - Elizabeth A Platz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.,The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD, USA
| | - Dominique S Michaud
- Department of Public Health & Community Medicine, Tufts University School of Medicine, Tufts University, Boston, MA, USA.,Department of Epidemiology, Brown University, Providence, RI, USA
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Sandanger TM, Nøst TH, Guida F, Rylander C, Campanella G, Muller DC, van Dongen J, Boomsma DI, Johansson M, Vineis P, Vermeulen R, Lund E, Chadeau-Hyam M. DNA methylation and associated gene expression in blood prior to lung cancer diagnosis in the Norwegian Women and Cancer cohort. Sci Rep 2018; 8:16714. [PMID: 30425263 PMCID: PMC6233189 DOI: 10.1038/s41598-018-34334-6] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2018] [Accepted: 10/08/2018] [Indexed: 12/20/2022] Open
Abstract
The majority of lung cancer is caused by tobacco smoking, and lung cancer-relevant epigenetic markers have been identified in relation to smoking exposure. Still, smoking-related markers appear to mediate little of the effect of smoking on lung cancer. Thus in order to identify disease-relevant markers and enhance our understanding of pathways, a wide search is warranted. Through an epigenome-wide search within a case-control study (131 cases, 129 controls) nested in a Norwegian prospective cohort of women, we found 25 CpG sites associated with lung cancer. Twenty-three were classified as associated with smoking (LC-AwS), and two were classified as unassociated with smoking (LC-non-AwS), as they remained associated with lung cancer after stringent adjustment for smoking exposure using the comprehensive smoking index (CSI): cg10151248 (PC, CSI-adjusted odds ratio (OR) = 0.34 [0.23-0.52] per standard deviation change in methylation) and cg13482620 (B3GNTL1, CSI-adjusted OR = 0.33 [0.22-0.50]). Analysis among never smokers and a cohort of smoking-discordant twins confirmed the classification of the two LC-non-AwS CpG sites. Gene expression profiles demonstrated that the LC-AwS CpG sites had different enriched pathways than LC-non-AwS sites. In conclusion, using blood-derived DNA methylation and gene expression profiles from a prospective lung cancer case-control study in women, we identified 25 CpG lung cancer markers prior to diagnosis, two of which were LC-non-AwS markers and related to distinct pathways.
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Affiliation(s)
- Torkjel Manning Sandanger
- Department of Community Medicine, Faculty of Health Sciences, UiT - The Arctic University of Norway, Tromsø, Norway.
| | - Therese Haugdahl Nøst
- Department of Community Medicine, Faculty of Health Sciences, UiT - The Arctic University of Norway, Tromsø, Norway
| | - Florence Guida
- MRC/PHE Centre for Environmental Health, Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
- Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| | - Charlotta Rylander
- Department of Community Medicine, Faculty of Health Sciences, UiT - The Arctic University of Norway, Tromsø, Norway
| | - Gianluca Campanella
- MRC/PHE Centre for Environmental Health, Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
| | - David C Muller
- MRC/PHE Centre for Environmental Health, Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
| | - Jenny van Dongen
- Netherlands Twin Register, Vrije Universiteit, Department of Biological Psychology, Amsterdam, The Netherlands
| | - Dorret I Boomsma
- Netherlands Twin Register, Vrije Universiteit, Department of Biological Psychology, Amsterdam, The Netherlands
| | - Mattias Johansson
- Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| | - Paolo Vineis
- MRC/PHE Centre for Environmental Health, Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
- Italian Institute for Genomic Medicine (IIGM), Turin, Italy
| | - Roel Vermeulen
- MRC/PHE Centre for Environmental Health, Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
- Institute for Risk Assessment Sciences (IRAS), Division of Environmental Epidemiology, Utrecht University, Utrecht, The Netherlands
| | - Eiliv Lund
- Department of Community Medicine, Faculty of Health Sciences, UiT - The Arctic University of Norway, Tromsø, Norway
| | - Marc Chadeau-Hyam
- MRC/PHE Centre for Environmental Health, Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
- Institute for Risk Assessment Sciences (IRAS), Division of Environmental Epidemiology, Utrecht University, Utrecht, The Netherlands
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Costa RL, Boroni M, Soares MA. Distinct co-expression networks using multi-omic data reveal novel interventional targets in HPV-positive and negative head-and-neck squamous cell cancer. Sci Rep 2018; 8:15254. [PMID: 30323202 PMCID: PMC6189122 DOI: 10.1038/s41598-018-33498-5] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2018] [Accepted: 09/19/2018] [Indexed: 12/25/2022] Open
Abstract
The human papillomavirus (HPV) is present in a significant fraction of head-and-neck squamous cell cancer (HNSCC). The main goal of this study was to identify distinct co-expression patterns between HPV+ and HPV- HNSCC and to provide insights into potential regulatory mechanisms/effects within the analyzed networks. We selected cases deposited in The Cancer Genome Atlas database comprising data of gene expression, methylation profiles and mutational patterns, in addition to clinical information. The intersection among differentially expressed and differentially methylated genes showed the negative correlations between the levels of methylation and expression, suggesting that these genes have their expression levels regulated by methylation alteration patterns in their promoter. Weighted correlation network analysis was used to identify co-expression modules and a systematic approach was applied to refine them and identify key regulatory elements integrating results from the other omics. Three distinct co-expression modules were associated with HPV status and molecular signatures. Validation using independent studies reporting biological experimental data converged for the most significant genes in all modules. This study provides insights into complex genetic and epigenetic particularities in the development and progression of HNSCC according to HPV status, and contribute to unveiling specific genes/pathways as novel therapeutic targets in HNSCC.
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Affiliation(s)
- Raquel L Costa
- Programa de Oncovirologia, Instituto Nacional de Câncer, Rio de Janeiro, Brazil.
- Bioinformatics and Computational Biology Lab, Instituto Nacional de Câncer, Rio de Janeiro, Brazil.
| | - Mariana Boroni
- Bioinformatics and Computational Biology Lab, Instituto Nacional de Câncer, Rio de Janeiro, Brazil
| | - Marcelo A Soares
- Programa de Oncovirologia, Instituto Nacional de Câncer, Rio de Janeiro, Brazil
- Department of Genetics, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
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