Zhang, RuyangChen, ChaoDong, XuesiShen, SipengLai, LinjingHe, JieyuYou, DongfangLin, LijuanZhu, YingHuang, HuiChen, JiajinWei, LiangminChen, XinLi, YiGuo, YichenDuan, WeiweiLiu, LiyaSu, LiShafer, AndreaFleischer, ThomasBjaanæs, Maria MoksnesKarlsson, AnnaPlanck, MariaWang, RuiStaaf, JohanHelland, ÅslaugEsteller, ManelWei, YongyueChen, FengChristiani, David C.2021-03-092021-03-092020-08-010012-3692https://hdl.handle.net/2445/174837Background: DNA methylation and gene expression are promising biomarkers of various cancers, including non-small cell lung cancer (NSCLC). Besides the main effects of biomarkers, the progression of complex diseases is also influenced by gene-gene (G×G) interactions. Research question: would screening the functional capacity of biomarkers on the basis of main effects or interactions, using multiomics data, improve the accuracy of cancer prognosis? Study design and methods: biomarker screening and model validation were used to construct and validate a prognostic prediction model. NSCLC prognosis-associated biomarkers were identified on the basis of either their main effects or interactions with two types of omics data. A prognostic score incorporating epigenetic and transcriptional biomarkers, as well as clinical information, was independently validated. Results: twenty-six pairs of biomarkers with G×G interactions and two biomarkers with main effects were significantly associated with NSCLC survival. Compared with a model using clinical information only, the accuracy of the epigenetic and transcriptional biomarker-based prognostic model, measured by area under the receiver operating characteristic curve (AUC), increased by 35.38% (95% CI, 27.09%-42.17%; P = 5.10 × 10-17) and 34.85% (95% CI, 26.33%-41.87%; P = 2.52 × 10-18) for 3- and 5-year survival, respectively, which exhibited a superior predictive ability for NSCLC survival (AUC3 year, 0.88 [95% CI, 0.83-0.93]; and AUC5 year, 0.89 [95% CI, 0.83-0.93]) in an independent Cancer Genome Atlas population. G×G interactions contributed a 65.2% and 91.3% increase in prediction accuracy for 3- and 5-year survival, respectively. Interpretation: the integration of epigenetic and transcriptional biomarkers with main effects and G×G interactions significantly improves the accuracy of prognostic prediction of early-stage NSCLC survival.12 p.application/pdfengcc by (c) Zhang et al, 2020http://creativecommons.org/licenses/by-nc-nd/3.0/es/Càncer de pulmóCèl·lules cancerosesMarcadors tumoralsEpigenèticaLung cancerCancer cellsTumor markersEpigeneticsinfo:eu-repo/semantics/article7000942021-03-09info:eu-repo/semantics/openAccess32113923