Rosenberger, A., Muttray, N., Hung, R.J. et al. (37 more authors) (2022) Gene–gene interaction of AhRwith and within the Wntcascade affects susceptibility to lung cancer. European Journal of Medical Research, 27. 14. ISSN 2047-783X
Abstract
Background:
Aberrant Wnt signalling, regulating cell development and stemness, influences the development of many cancer types. The Aryl hydrocarbon receptor (AhR) mediates tumorigenesis of environmental pollutants. Complex interaction patterns of genes assigned to AhR/Wnt-signalling were recently associated with lung cancer susceptibility.
Aim:
To assess the association and predictive ability of AhR/Wnt-genes with lung cancer in cases and controls of European descent.
Methods:
Odds ratios (OR) were estimated for genomic variants assigned to the Wnt agonist and the antagonistic genes DKK2, DKK3, DKK4, FRZB, SFRP4 and Axin2. Logistic regression models with variable selection were trained, validated and tested to predict lung cancer, at which other previously identified SNPs that have been robustly associated with lung cancer risk could also enter the model. Furthermore, decision trees were created to investigate variant × variant interaction. All analyses were performed for overall lung cancer and for subgroups.
Results:
No genome-wide significant association of AhR/Wnt-genes with overall lung cancer was observed, but within the subgroups of ever smokers (e.g., maker rs2722278 SFRP4; OR = 1.20; 95% CI 1.13–1.27; p = 5.6 × 10–10) and never smokers (e.g., maker rs1133683 Axin2; OR = 1.27; 95% CI 1.19–1.35; p = 1.0 × 10–12). Although predictability is poor, AhR/Wnt-variants are unexpectedly overrepresented in optimized prediction scores for overall lung cancer and for small cell lung cancer. Remarkably, the score for never-smokers contained solely two AhR/Wnt-variants. The optimal decision tree for never smokers consists of 7 AhR/Wnt-variants and only two lung cancer variants.
Conclusions:
The role of variants belonging to Wnt/AhR-pathways in lung cancer susceptibility may be underrated in main-effects association analysis. Complex interaction patterns in individuals of European descent have moderate predictive capacity for lung cancer or subgroups thereof, especially in never smokers.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2022. Open Access: This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data. |
Keywords: | Susceptibility; Association; Gene–gene integration; Prediction; Polygenic risk score; Decision trees; Never smoker; Small cell lung cancer |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > Department of Human Metabolism (Sheffield) The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > Department of Oncology (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 07 Mar 2022 14:43 |
Last Modified: | 07 Mar 2022 14:43 |
Status: | Published |
Publisher: | BioMed Central |
Refereed: | Yes |
Identification Number: | 10.1186/s40001-022-00638-7 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:184460 |