Epigenome‐wide three‐way interaction study identifies a complex pattern between TRIM27, KIAA0226, and smoking associated with overall survival of early‐stage NSCLC
The interaction between DNA methylation of tripartite motif containing 27 (cg05293407TRIM27) and smoking has previously been identified to reveal histologically heterogeneous effects of TRIM27 DNA methylation on early‐stage non‐small‐cell lung cancer (NSCLC) survival. However, to understand the comp...
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| Published in | Molecular oncology Vol. 16; no. 3; pp. 717 - 731 |
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| Main Authors | , , , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English Norwegian |
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United States
John Wiley & Sons, Inc
01.02.2022
John Wiley and Sons Inc Wiley |
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| Abstract | The interaction between DNA methylation of tripartite motif containing 27 (cg05293407TRIM27) and smoking has previously been identified to reveal histologically heterogeneous effects of TRIM27 DNA methylation on early‐stage non‐small‐cell lung cancer (NSCLC) survival. However, to understand the complex mechanisms underlying NSCLC progression, we searched three‐way interactions. A two‐phase study was adopted to identify three‐way interactions in the form of pack‐year of smoking (number of cigarettes smoked per day × number of years smoked) × cg05293407TRIM27 × epigenome‐wide DNA methylation CpG probe. Two CpG probes were identified with FDR‐q ≤ 0.05 in the discovery phase and P ≤ 0.05 in the validation phase: cg00060500KIAA0226 and cg17479956EXT2. Compared to a prediction model with only clinical information, the model added 42 significant three‐way interactions using a looser criterion (discovery: FDR‐q ≤ 0.10, validation: P ≤ 0.05) had substantially improved the area under the receiver operating characteristic curve (AUC) of the prognostic prediction model for both 3‐year and 5‐year survival. Our research identified the complex interaction effects among multiple environment and epigenetic factors, and provided therapeutic target for NSCLC patients.
We performed a two‐phase designed epigenome‐wide three‐way gene‐smoking interaction study of NSCLC survival and identified two CpG probes (cg00060500KIAA0226 and cg17479956EXT2), together with pack‐year of smoking and cg05293407TRIM27, exhibiting significant three‐way interaction effects. Meanwhile, these significant three‐way interactions substantially improved the area under the receiver operating characteristic curve (AUC) of the prognostic prediction model for both 3‐ and 5‐year survival. |
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| AbstractList | The interaction between DNA methylation of tripartite motif containing 27 (cg05293407TRIM27) and smoking has previously been identified to reveal histologically heterogeneous effects of TRIM27 DNA methylation on early‐stage non‐small‐cell lung cancer (NSCLC) survival. However, to understand the complex mechanisms underlying NSCLC progression, we searched three‐way interactions. A two‐phase study was adopted to identify three‐way interactions in the form of pack‐year of smoking (number of cigarettes smoked per day × number of years smoked) × cg05293407TRIM27 × epigenome‐wide DNA methylation CpG probe. Two CpG probes were identified with FDR‐q ≤ 0.05 in the discovery phase and P ≤ 0.05 in the validation phase: cg00060500KIAA0226 and cg17479956EXT2. Compared to a prediction model with only clinical information, the model added 42 significant three‐way interactions using a looser criterion (discovery: FDR‐q ≤ 0.10, validation: P ≤ 0.05) had substantially improved the area under the receiver operating characteristic curve (AUC) of the prognostic prediction model for both 3‐year and 5‐year survival. Our research identified the complex interaction effects among multiple environment and epigenetic factors, and provided therapeutic target for NSCLC patients.
We performed a two‐phase designed epigenome‐wide three‐way gene‐smoking interaction study of NSCLC survival and identified two CpG probes (cg00060500KIAA0226 and cg17479956EXT2), together with pack‐year of smoking and cg05293407TRIM27, exhibiting significant three‐way interaction effects. Meanwhile, these significant three‐way interactions substantially improved the area under the receiver operating characteristic curve (AUC) of the prognostic prediction model for both 3‐ and 5‐year survival. The interaction between DNA methylation of tripartite motif containing 27 (cg05293407 TRIM27 ) and smoking has previously been identified to reveal histologically heterogeneous effects of TRIM27 DNA methylation on early‐stage non‐small‐cell lung cancer (NSCLC) survival. However, to understand the complex mechanisms underlying NSCLC progression, we searched three‐way interactions. A two‐phase study was adopted to identify three‐way interactions in the form of pack‐year of smoking (number of cigarettes smoked per day × number of years smoked) × cg05293407 TRIM27 × epigenome‐wide DNA methylation CpG probe. Two CpG probes were identified with FDR‐ q ≤ 0.05 in the discovery phase and P ≤ 0.05 in the validation phase: cg00060500 KIAA0226 and cg17479956 EXT2 . Compared to a prediction model with only clinical information, the model added 42 significant three‐way interactions using a looser criterion (discovery: FDR‐ q ≤ 0.10, validation: P ≤ 0.05) had substantially improved the area under the receiver operating characteristic curve (AUC) of the prognostic prediction model for both 3‐year and 5‐year survival. Our research identified the complex interaction effects among multiple environment and epigenetic factors, and provided therapeutic target for NSCLC patients. The interaction between DNA methylation of tripartite motif containing 27 (cg05293407TRIM27) and smoking has previously been identified to reveal histologically heterogeneous effects of TRIM27 DNA methylation on early‐stage non‐small‐cell lung cancer (NSCLC) survival. However, to understand the complex mechanisms underlying NSCLC progression, we searched three‐way interactions. A two‐phase study was adopted to identify three‐way interactions in the form of pack‐year of smoking (number of cigarettes smoked per day × number of years smoked) × cg05293407TRIM27 × epigenome‐wide DNA methylation CpG probe. Two CpG probes were identified with FDR‐q ≤ 0.05 in the discovery phase and P ≤ 0.05 in the validation phase: cg00060500KIAA0226 and cg17479956EXT2. Compared to a prediction model with only clinical information, the model added 42 significant three‐way interactions using a looser criterion (discovery: FDR‐q ≤ 0.10, validation: P ≤ 0.05) had substantially improved the area under the receiver operating characteristic curve (AUC) of the prognostic prediction model for both 3‐year and 5‐year survival. Our research identified the complex interaction effects among multiple environment and epigenetic factors, and provided therapeutic target for NSCLC patients. The interaction between DNA methylation of tripartite motif containing 27 (cg05293407TRIM27 ) and smoking has previously been identified to reveal histologically heterogeneous effects of TRIM27 DNA methylation on early-stage non-small-cell lung cancer (NSCLC) survival. However, to understand the complex mechanisms underlying NSCLC progression, we searched three-way interactions. A two-phase study was adopted to identify three-way interactions in the form of pack-year of smoking (number of cigarettes smoked per day × number of years smoked) × cg05293407TRIM27 × epigenome-wide DNA methylation CpG probe. Two CpG probes were identified with FDR-q ≤ 0.05 in the discovery phase and P ≤ 0.05 in the validation phase: cg00060500KIAA0226 and cg17479956EXT2 . Compared to a prediction model with only clinical information, the model added 42 significant three-way interactions using a looser criterion (discovery: FDR-q ≤ 0.10, validation: P ≤ 0.05) had substantially improved the area under the receiver operating characteristic curve (AUC) of the prognostic prediction model for both 3-year and 5-year survival. Our research identified the complex interaction effects among multiple environment and epigenetic factors, and provided therapeutic target for NSCLC patients.The interaction between DNA methylation of tripartite motif containing 27 (cg05293407TRIM27 ) and smoking has previously been identified to reveal histologically heterogeneous effects of TRIM27 DNA methylation on early-stage non-small-cell lung cancer (NSCLC) survival. However, to understand the complex mechanisms underlying NSCLC progression, we searched three-way interactions. A two-phase study was adopted to identify three-way interactions in the form of pack-year of smoking (number of cigarettes smoked per day × number of years smoked) × cg05293407TRIM27 × epigenome-wide DNA methylation CpG probe. Two CpG probes were identified with FDR-q ≤ 0.05 in the discovery phase and P ≤ 0.05 in the validation phase: cg00060500KIAA0226 and cg17479956EXT2 . Compared to a prediction model with only clinical information, the model added 42 significant three-way interactions using a looser criterion (discovery: FDR-q ≤ 0.10, validation: P ≤ 0.05) had substantially improved the area under the receiver operating characteristic curve (AUC) of the prognostic prediction model for both 3-year and 5-year survival. Our research identified the complex interaction effects among multiple environment and epigenetic factors, and provided therapeutic target for NSCLC patients. The interaction between DNA methylation of tripartite motif containing 27 (cg05293407 TRIM27 ) and smoking has previously been identified to reveal histologically heterogeneous effects of TRIM27 DNA methylation on early‐stage non‐small‐cell lung cancer (NSCLC) survival. However, to understand the complex mechanisms underlying NSCLC progression, we searched three‐way interactions. A two‐phase study was adopted to identify three‐way interactions in the form of pack‐year of smoking (number of cigarettes smoked per day × number of years smoked) × cg05293407 TRIM27 × epigenome‐wide DNA methylation CpG probe. Two CpG probes were identified with FDR‐ q ≤ 0.05 in the discovery phase and P ≤ 0.05 in the validation phase: cg00060500 KIAA0226 and cg17479956 EXT2 . Compared to a prediction model with only clinical information, the model added 42 significant three‐way interactions using a looser criterion (discovery: FDR‐ q ≤ 0.10, validation: P ≤ 0.05) had substantially improved the area under the receiver operating characteristic curve (AUC) of the prognostic prediction model for both 3‐year and 5‐year survival. Our research identified the complex interaction effects among multiple environment and epigenetic factors, and provided therapeutic target for NSCLC patients. We performed a two‐phase designed epigenome‐wide three‐way gene‐smoking interaction study of NSCLC survival and identified two CpG probes (cg00060500 KIAA0226 and cg17479956 EXT2 ), together with pack‐year of smoking and cg05293407 TRIM27 , exhibiting significant three‐way interaction effects. Meanwhile, these significant three‐way interactions substantially improved the area under the receiver operating characteristic curve (AUC) of the prognostic prediction model for both 3‐ and 5‐year survival. The interaction between DNA methylation of tripartite motif containing 27 (cg05293407[sub.TRIM27]) and smoking has previously been identified to reveal histologically heterogeneous effects of TRIM27 DNA methylation on early-stage non-small-cell lung cancer (NSCLC) survival. However, to understand the complex mechanisms underlying NSCLC progression, we searched three-way interactions. A two-phase study was adopted to identify three-way interactions in the form of pack-year of smoking (number of cigarettes smoked per day × number of years smoked) × cg05293407[sub.TRIM27] × epigenome-wide DNA methylation CpG probe. Two CpG probes were identified with FDR-q ≤ 0.05 in the discovery phase and P ≤ 0.05 in the validation phase: cg00060500[sub.KIAA0226] and cg17479956[sub.EXT2]. Compared to a prediction model with only clinical information, the model added 42 significant three-way interactions using a looser criterion (discovery: FDR-q ≤ 0.10, validation: P ≤ 0.05) had substantially improved the area under the receiver operating characteristic curve (AUC) of the prognostic prediction model for both 3-year and 5-year survival. Our research identified the complex interaction effects among multiple environment and epigenetic factors, and provided therapeutic target for NSCLC patients. The interaction between DNA methylation of tripartite motif containing 27 (cg05293407 ) and smoking has previously been identified to reveal histologically heterogeneous effects of TRIM27 DNA methylation on early-stage non-small-cell lung cancer (NSCLC) survival. However, to understand the complex mechanisms underlying NSCLC progression, we searched three-way interactions. A two-phase study was adopted to identify three-way interactions in the form of pack-year of smoking (number of cigarettes smoked per day × number of years smoked) × cg05293407 × epigenome-wide DNA methylation CpG probe. Two CpG probes were identified with FDR-q ≤ 0.05 in the discovery phase and P ≤ 0.05 in the validation phase: cg00060500 and cg17479956 . Compared to a prediction model with only clinical information, the model added 42 significant three-way interactions using a looser criterion (discovery: FDR-q ≤ 0.10, validation: P ≤ 0.05) had substantially improved the area under the receiver operating characteristic curve (AUC) of the prognostic prediction model for both 3-year and 5-year survival. Our research identified the complex interaction effects among multiple environment and epigenetic factors, and provided therapeutic target for NSCLC patients. |
| Audience | Academic |
| Author | Zhang, Ruyang Christiani, David C. Shen, Sipeng Lin, Lijuan Li, Yi Helland, Åslaug Esteller, Manel Staaf, Johan Su, Li Planck, Maria Chen, Feng Shafer, Andrea Karlsson, Anna Bjaanæs, Maria Moksnes Ji, Xinyu Fan, Juanjuan Wei, Yongyue |
| AuthorAffiliation | 6 Department of Cancer Genetics Institute for Cancer Research Oslo University Hospital Oslo Norway 4 China International Cooperation Center for Environment and Human Health Nanjing Medical University Nanjing China 1 Department of Biostatistics Center for Global Health School of Public Health Nanjing Medical University Nanjing China 9 Josep Carreras Leukaemia Research Institute Barcelona Spain 2 Department of Biostatistics University of Michigan Ann Arbor MI USA 8 Institute of Clinical Medicine University of Oslo Oslo Norway 14 Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment Cancer Center Collaborative Innovation Center for Cancer Personalized Medicine Nanjing Medical University Nanjing China 13 State Key Laboratory of Reproductive Medicine Nanjing Medical University Nanjing China 3 Department of Environmental Health Harvard T.H. Chan School of Public Health Boston MA USA 11 Institucio Catalana de Recerca i Estudis Avançats Barcelona Spain 10 Centro de Investigacion Biomedica en Re |
| AuthorAffiliation_xml | – name: 13 State Key Laboratory of Reproductive Medicine Nanjing Medical University Nanjing China – name: 2 Department of Biostatistics University of Michigan Ann Arbor MI USA – name: 3 Department of Environmental Health Harvard T.H. Chan School of Public Health Boston MA USA – name: 11 Institucio Catalana de Recerca i Estudis Avançats Barcelona Spain – name: 12 Physiological Sciences Department School of Medicine and Health Sciences University of Barcelona Barcelona Spain – name: 1 Department of Biostatistics Center for Global Health School of Public Health Nanjing Medical University Nanjing China – name: 5 Pulmonary and Critical Care Division Department of Medicine Massachusetts General Hospital and Harvard Medical School Boston MA USA – name: 4 China International Cooperation Center for Environment and Human Health Nanjing Medical University Nanjing China – name: 10 Centro de Investigacion Biomedica en Red Cancer Madrid Spain – name: 14 Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment Cancer Center Collaborative Innovation Center for Cancer Personalized Medicine Nanjing Medical University Nanjing China – name: 8 Institute of Clinical Medicine University of Oslo Oslo Norway – name: 9 Josep Carreras Leukaemia Research Institute Barcelona Spain – name: 6 Department of Cancer Genetics Institute for Cancer Research Oslo University Hospital Oslo Norway – name: 7 Division of Oncology Department of Clinical Sciences Lund and CREATE Health Strategic Center for Translational Cancer Research Lund University Lund Sweden |
| Author_xml | – sequence: 1 givenname: Xinyu surname: Ji fullname: Ji, Xinyu organization: Nanjing Medical University – sequence: 2 givenname: Lijuan surname: Lin fullname: Lin, Lijuan organization: Nanjing Medical University – sequence: 3 givenname: Juanjuan surname: Fan fullname: Fan, Juanjuan organization: Nanjing Medical University – sequence: 4 givenname: Yi surname: Li fullname: Li, Yi organization: University of Michigan – sequence: 5 givenname: Yongyue surname: Wei fullname: Wei, Yongyue organization: Nanjing Medical University – sequence: 6 givenname: Sipeng surname: Shen fullname: Shen, Sipeng organization: Nanjing Medical University – sequence: 7 givenname: Li surname: Su fullname: Su, Li organization: Harvard T.H. Chan School of Public Health – sequence: 8 givenname: Andrea surname: Shafer fullname: Shafer, Andrea organization: Massachusetts General Hospital and Harvard Medical School – sequence: 9 givenname: Maria Moksnes orcidid: 0000-0001-7126-9064 surname: Bjaanæs fullname: Bjaanæs, Maria Moksnes organization: Oslo University Hospital – sequence: 10 givenname: Anna surname: Karlsson fullname: Karlsson, Anna organization: Lund University – sequence: 11 givenname: Maria surname: Planck fullname: Planck, Maria organization: Lund University – sequence: 12 givenname: Johan surname: Staaf fullname: Staaf, Johan organization: Lund University – sequence: 13 givenname: Åslaug surname: Helland fullname: Helland, Åslaug organization: University of Oslo – sequence: 14 givenname: Manel orcidid: 0000-0003-4490-6093 surname: Esteller fullname: Esteller, Manel organization: University of Barcelona – sequence: 15 givenname: Ruyang orcidid: 0000-0003-3861-4297 surname: Zhang fullname: Zhang, Ruyang email: zhangruyang@njmu.edu.cn organization: Nanjing Medical University – sequence: 16 givenname: Feng surname: Chen fullname: Chen, Feng email: fengchen@njmu.edu.cn organization: Nanjing Medical University – sequence: 17 givenname: David C. surname: Christiani fullname: Christiani, David C. organization: Massachusetts General Hospital and Harvard Medical School |
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| Copyright | 2021 The Authors. published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies. 2021 The Authors. Molecular Oncology published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies. COPYRIGHT 2022 John Wiley & Sons, Inc. 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. info:eu-repo/semantics/openAccess |
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| Keywords | prognostic prediction DNA methylation overall survival three-way interaction non-small-cell lung cancer |
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| License | Attribution 2021 The Authors. Molecular Oncology published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
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| Notes | David C. Christiani Senior author who supervised the work. Xinyu Ji, Lijuan Lin and Juanjuan Fan contributed equally to this work. ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
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| Snippet | The interaction between DNA methylation of tripartite motif containing 27 (cg05293407TRIM27) and smoking has previously been identified to reveal... The interaction between DNA methylation of tripartite motif containing 27 (cg05293407 ) and smoking has previously been identified to reveal histologically... The interaction between DNA methylation of tripartite motif containing 27 (cg05293407 TRIM27 ) and smoking has previously been identified to reveal... The interaction between DNA methylation of tripartite motif containing 27 (cg05293407[sub.TRIM27]) and smoking has previously been identified to reveal... The interaction between DNA methylation of tripartite motif containing 27 (cg05293407TRIM27 ) and smoking has previously been identified to reveal... The interaction between DNA methylation of tripartite motif containing 27 (cg05293407 TRIM27 ) and smoking has previously been identified to reveal... |
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| SubjectTerms | Analysis Autophagy-Related Proteins - genetics Basic Medicine Biotechnology industry Cancer and Oncology Cancer och onkologi Carcinoma, Non-Small-Cell Lung - genetics Carcinoma, Non-Small-Cell Lung - mortality Cell survival Cigarettes Clinical Medicine CpG islands CpG Islands - genetics Deoxyribonucleic acid DNA DNA Methylation DNA probes DNA-Binding Proteins - genetics Epigenesis, Genetic Epigenetic inheritance Epigenetics Epigenome Gene expression Genome-Wide Association Study Genomes Humans Klinisk medicin Lung cancer Lung cancer, Non-small cell Lung Neoplasms - genetics Lung Neoplasms - mortality Medical and Health Sciences Medical Genetics Medicin och hälsovetenskap Medicinsk genetik Medicinska och farmaceutiska grundvetenskaper Mortality Non-small cell lung carcinoma non‐small‐cell lung cancer Norway Nuclear Proteins - genetics overall survival Patient outcomes Prediction models prognostic prediction Quality control Smoking Smoking - genetics Spain Squamous cell carcinoma Sweden Therapeutic targets three‐way interaction Tumors United States |
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| Title | Epigenome‐wide three‐way interaction study identifies a complex pattern between TRIM27, KIAA0226, and smoking associated with overall survival of early‐stage NSCLC |
| URI | https://onlinelibrary.wiley.com/doi/abs/10.1002%2F1878-0261.13167 https://www.ncbi.nlm.nih.gov/pubmed/34932879 https://www.proquest.com/docview/2624580207 https://www.proquest.com/docview/2612735547/abstract/ http://hdl.handle.net/10852/90960 https://pubmed.ncbi.nlm.nih.gov/PMC8807353 https://lup.lub.lu.se/record/52602e54-76b4-4fa8-8dc3-f06fe35f02d2 https://doaj.org/article/f987d620e07840b28fadb06cb458f7d7 |
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