Blood-based DNA methylation markers for lung cancer prediction
Objective Screening high-risk individuals with low-dose CT reduces mortality from lung cancer, but many lung cancers occur in individuals who are not eligible for screening. Risk biomarkers may be useful to refine risk models and improve screening eligibility criteria. We evaluated if blood-based DN...
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| Format: | Article |
| Language: | English |
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BMJ Publishing Group
2024-07-01
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| Series: | BMJ Oncology |
| Online Access: | https://bmjoncology.bmj.com/content/3/1/e000334.full |
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| author | Marc Chadeau-Hyam Paolo Vineis Caroline Relton Mattias Johansson Gianluca Severi Roger L Milne Melissa C Southey Pierre-Antoine Dugué Florence Guida Mikael Johansson Torkjel Sandanger Justina Ucheojor Onwuka Ryan Langdon Therese Haugdahl Nøst Hilary A. Robbins Matthew Suderman |
| author_facet | Marc Chadeau-Hyam Paolo Vineis Caroline Relton Mattias Johansson Gianluca Severi Roger L Milne Melissa C Southey Pierre-Antoine Dugué Florence Guida Mikael Johansson Torkjel Sandanger Justina Ucheojor Onwuka Ryan Langdon Therese Haugdahl Nøst Hilary A. Robbins Matthew Suderman |
| author_sort | Marc Chadeau-Hyam |
| collection | DOAJ |
| description | Objective Screening high-risk individuals with low-dose CT reduces mortality from lung cancer, but many lung cancers occur in individuals who are not eligible for screening. Risk biomarkers may be useful to refine risk models and improve screening eligibility criteria. We evaluated if blood-based DNA methylation markers can improve a traditional lung cancer prediction model.Methods and analysis This study used four prospective cohorts with blood samples collected prior to lung cancer diagnosis. The study was restricted to participants with a history of smoking, and one control was individually matched to each lung cancer case using incidence density sampling by cohort, sex, date of blood collection, age and smoking status. To train a DNA methylation-based risk score, we used participants from Melbourne Collaborative Cohort Study-Australia (n=648) and Northern Sweden Health and Disease Study-Sweden (n=380) based on five selected CpG sites. The risk discriminative performance of the methylation score was subsequently validated in participants from European Investigation into Cancer and Nutrition-Italy (n=267) and Norwegian Women and Cancer-Norway (n=185) and compared with that of the questionnaire-based PLCOm2012 lung cancer risk model.Results The area under the receiver operating characteristic curve (AUC) for the PLCOm2012 model in the validation studies was 0.70 (95% CI: 0.65 to 0.75) compared with 0.73 (95% CI: 0.68 to 0.77) for the methylation score model (Pdifference=0.07). Incorporating the methylation score with the PLCOm2012 model did not improve the risk discrimination (AUC: 0.73, 95% CI: 0.68 to 0.77, Pdifference=0.73).Conclusions This study suggests that the methylation-based risk prediction score alone provides similar lung cancer risk-discriminatory performance as the questionnaire-based PLCOm2012 risk model. |
| format | Article |
| id | doaj-art-31adadfff44f48119b68988cdec01203 |
| institution | Kabale University |
| issn | 2752-7948 |
| language | English |
| publishDate | 2024-07-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Oncology |
| spelling | doaj-art-31adadfff44f48119b68988cdec012032025-01-30T10:20:14ZengBMJ Publishing GroupBMJ Oncology2752-79482024-07-013110.1136/bmjonc-2024-000334Blood-based DNA methylation markers for lung cancer predictionMarc Chadeau-Hyam0Paolo Vineis1Caroline Relton2Mattias Johansson3Gianluca Severi4Roger L Milne5Melissa C Southey6Pierre-Antoine Dugué7Florence Guida8Mikael Johansson9Torkjel Sandanger10Justina Ucheojor Onwuka11Ryan Langdon12Therese Haugdahl Nøst13Hilary A. Robbins14Matthew Suderman15MRC Centre for Environment and Health, Imperial College London, London, UKprofessor of epidemiologyMRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, Bristol, UKGenomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, FranceParis-Saclay University, UVSQ, Inserm, Gustave Roussy, Exposome and Heredity team, CESP, F-94805, Villejuif, FrancePrecision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, AustraliaPrecision Medicine, Monash University School of Clinical Sciences at Monash Health, Clayton, Victoria, AustraliaCancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, AustraliaGenomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, FranceDepartment of Radiation Sciences Oncology, Umeå University, Umea, SwedenDepartment of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromso, Troms, NorwayGenomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, FrancePopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK1 Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, NorwayGenomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, FranceMRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, Bristol, UKObjective Screening high-risk individuals with low-dose CT reduces mortality from lung cancer, but many lung cancers occur in individuals who are not eligible for screening. Risk biomarkers may be useful to refine risk models and improve screening eligibility criteria. We evaluated if blood-based DNA methylation markers can improve a traditional lung cancer prediction model.Methods and analysis This study used four prospective cohorts with blood samples collected prior to lung cancer diagnosis. The study was restricted to participants with a history of smoking, and one control was individually matched to each lung cancer case using incidence density sampling by cohort, sex, date of blood collection, age and smoking status. To train a DNA methylation-based risk score, we used participants from Melbourne Collaborative Cohort Study-Australia (n=648) and Northern Sweden Health and Disease Study-Sweden (n=380) based on five selected CpG sites. The risk discriminative performance of the methylation score was subsequently validated in participants from European Investigation into Cancer and Nutrition-Italy (n=267) and Norwegian Women and Cancer-Norway (n=185) and compared with that of the questionnaire-based PLCOm2012 lung cancer risk model.Results The area under the receiver operating characteristic curve (AUC) for the PLCOm2012 model in the validation studies was 0.70 (95% CI: 0.65 to 0.75) compared with 0.73 (95% CI: 0.68 to 0.77) for the methylation score model (Pdifference=0.07). Incorporating the methylation score with the PLCOm2012 model did not improve the risk discrimination (AUC: 0.73, 95% CI: 0.68 to 0.77, Pdifference=0.73).Conclusions This study suggests that the methylation-based risk prediction score alone provides similar lung cancer risk-discriminatory performance as the questionnaire-based PLCOm2012 risk model.https://bmjoncology.bmj.com/content/3/1/e000334.full |
| spellingShingle | Marc Chadeau-Hyam Paolo Vineis Caroline Relton Mattias Johansson Gianluca Severi Roger L Milne Melissa C Southey Pierre-Antoine Dugué Florence Guida Mikael Johansson Torkjel Sandanger Justina Ucheojor Onwuka Ryan Langdon Therese Haugdahl Nøst Hilary A. Robbins Matthew Suderman Blood-based DNA methylation markers for lung cancer prediction BMJ Oncology |
| title | Blood-based DNA methylation markers for lung cancer prediction |
| title_full | Blood-based DNA methylation markers for lung cancer prediction |
| title_fullStr | Blood-based DNA methylation markers for lung cancer prediction |
| title_full_unstemmed | Blood-based DNA methylation markers for lung cancer prediction |
| title_short | Blood-based DNA methylation markers for lung cancer prediction |
| title_sort | blood based dna methylation markers for lung cancer prediction |
| url | https://bmjoncology.bmj.com/content/3/1/e000334.full |
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