Title: Independent Validation of Early-Stage Non-Small Cell Lung Cancer Prognostic Scores Incorporating Epigenetic and Transcriptional Biomarkers With Gene-Gene Interactions and Main Effects.

Authors: 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; Moksnes Bjaanæs, Maria; Karlsson, Anna; Planck, Maria; Wang, Rui; Staaf, Johan; Helland, Åslaug; Esteller, Manel; Wei, Yongyue; Chen, Feng; Christiani, David C

Published In Chest, (2020 08)

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.

PubMed ID: 32113923

MeSH Terms: No MeSH terms associated with this publication