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05343nam a2201117Ia 4500 |
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10-1186-s40001-022-00638-7 |
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|a 09492321 (ISSN)
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|a Gene–gene interaction of AhRwith and within the Wntcascade affects susceptibility to lung cancer
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|b BioMed Central Ltd
|c 2022
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|z View Fulltext in Publisher
|u https://doi.org/10.1186/s40001-022-00638-7
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|a 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. © 2022, The Author(s).
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|a adult
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|a AhR gene
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|a aromatic hydrocarbon receptor
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|a Article
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|a Association
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|a Axin2 gene
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|a cancer risk
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|a cancer susceptibility
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|a controlled study
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|a decision tree
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|a Decision trees
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|a DKK2 gene
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|a DKK3 gene
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|a DKK4 gene
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|a European
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|a female
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|a FRZB gene
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|a gene
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|a gene interaction
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|a Gene–gene integration
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|a genetic variability
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|a genome-wide association study
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|a human
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|a human tissue
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|a lung cancer
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|a major clinical study
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|a male
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|a middle aged
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|a never smoker
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|a Never smoker
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|a Polygenic risk score
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|a Prediction
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|a predictive value
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|a secreted frizzled related protein 4
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|a SFRP4 gene
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|a single nucleotide polymorphism
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|a small cell lung cancer
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|a Small cell lung cancer
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|a smoking
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|a Susceptibility
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|a Wnt gene
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|a Wnt protein
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|a Albanes, D.
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|a Aldrich, M.C.
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|a Amos, C.I.
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|a Andrew, A.S.
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|a Arnold, S.M.
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|a Bickeböller, H.
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|a Bojesen, S.E.
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|a Brennan, P.
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|a Caporaso, N.E.
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|a Chen, C.
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|a Christiani, D.C.
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|a Cox, A.
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|a Davies, M.P.A.
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|a Doherty, J.A.
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|a Duell, E.J.
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|a Fernández-Tardón, G.
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|a Field, J.K.
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|a Goodman, G.E.
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|a Haugen, A.
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|a Hung, R.J.
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|a Johansson, M.
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|a Kiemeney, L.A.
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|a Lam, S.
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|a Landi, M.T.
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|a Lazarus, P.
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|a Le Marchand, L.
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|a Liloglou, T.
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|a Liu, G.
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|a Muley, T.R.
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|a Muttray, N.
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|a Rennert, G.
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|a Risch, A.
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|a Rosenberger, A.
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|a Schabath, M.B.
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|a Shete, S.S.
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|a Tardon, A.
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|a Taylor, F.
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|a The INTEGRAL-ILCCO Consortium
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|a Wendel, B.
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|a Woll, P.J.
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|a Zienolddiny, S.
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|t European Journal of Medical Research
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