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oai:recercat.cat:2445/1748372025-12-05T09:20:29Zcom_2072_1057col_2072_478799col_2072_478917

Independent validation of early-stage NSCLC prognostic scores incorporating epigenetic and transcriptional biomarkers with gene-gene interactions and main effects 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. Càncer de pulmó Cèl·lules canceroses Marcadors tumorals Epigenètica Lung cancer Cancer cells Tumor markers Epigenetics 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. 2021-03-09T15:26:05Z 2021-03-09T15:26:05Z 2020-08-01 2021-03-09T15:26:05Z info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion 0012-3692 https://hdl.handle.net/2445/174837 700094 32113923 eng Reproducció del document publicat a: https://doi.org/10.1016/j.chest.2020.01.048 Chest, 2020, vol. 158, num. 2, p. 808-819 https://doi.org/10.1016/j.chest.2020.01.048 cc by (c) Zhang et al, 2020 http://creativecommons.org/licenses/by-nc-nd/3.0/es/ info:eu-repo/semantics/openAccess 12 p. application/pdf American College of Chest Physicians Articles publicats en revistes (Ciències Fisiològiques)