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Title: Independent validation of early-stage NSCLC prognostic scores incorporating epigenetic and transcriptional biomarkers with gene-gene interactions and main effects
Author: 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, Manel
Wei, Yongyue
Chen, Feng
Christiani, David C.
Keywords: Càncer de pulmó
Cèl·lules canceroses
Marcadors tumorals
Lung cancer
Cancer cells
Tumor markers
Issue Date: 1-Aug-2020
Publisher: American College of Chest Physicians
Abstract: 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 × 10-17) 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.
Note: Reproducció del document publicat a:
It is part of: Chest, 2020, vol. 158, num. 2, p. 808-819
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ISSN: 0012-3692
Appears in Collections:Articles publicats en revistes (Ciències Fisiològiques)

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