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

Autor/a

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

Fecha de publicación

2020

Resumen

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.

Tipo de documento

Article

Lengua

Inglés

Materias y palabras clave

Early stage; Interaction; Multiomics; Non-small cell lung cancer; Prognostic score

Publicado por

 

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Derechos

open access

Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.

https://creativecommons.org/licenses/by-nc-nd/4.0/

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