Zhang, Ruyang
Chen, Chao
Dong, Xuesi
Shen, Sipeng
Lai, Linjing
He, Jieyu
You, Dongfang
Lin, Lijuan
Zhu, Ying
Huang, Hui
Chen, Jiajin
Wei, Liangmin
Chen, Xin
Li, Yi
Guo, Yichen
Duan, Weiwei
Liu, Liya
Su, Li
Shafer, Andrea
Fleischer, Thomas
Bjaanæs, Maria Moksnes
Karlsson, Anna
Planck, Maria
Wang, Rui
Staaf, Johan
Helland, Åslaug
Esteller, M.
Wei, Yongyue
Chen, Feng
Christiani, David C.
Universitat Autònoma de Barcelona
2020
Background: 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) and 34.85% (95% CI, 26.33%-41.87%; P = 2.52 × 10) for 3- and 5-year survival, respectively, which exhibited a superior predictive ability for NSCLC survival (AUC, 0.88 [95% CI, 0.83-0.93]; and AUC, 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.
Inglés
Early stage; Interaction; Multiomics; Non-small cell lung cancer; Prognostic score
Chest ; Vol. 158 Núm. 2 (august 2020), p. 808-819
open access
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