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

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

Zhang, Ruyang (författare): Nanjing University,Nanjing Medical University,Harvard University

Chen, Chao (författare): Nanjing Medical University

Dong, Xuesi (författare): Harvard University,Southeast University, Nanjing,Nanjing Medical University

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Shen, Sipeng (författare): Nanjing Medical University,Harvard University

Lai, Linjing (författare): Nanjing Medical University

He, Jieyu (författare): Nanjing Medical University

You, Dongfang (författare): Harvard University,Nanjing Medical University

Lin, Lijuan (författare): Harvard University,Nanjing Medical University

Zhu, Ying (författare): Nanjing Medical University

Huang, Hui (författare): Nanjing Medical University

Chen, Jiajin (författare): Nanjing Medical University

Wei, Liangmin (författare): Nanjing Medical University

Chen, Xin (författare): Nanjing Medical University

Li, Yi (författare): University of Michigan

Guo, Yichen (författare): Harvard University

Duan, Weiwei (författare): Nanjing Medical University

Liu, Liya (författare): Ningbo University

Su, Li (författare): Harvard University

Shafer, Andrea (författare): Massachusetts General Hospital,Harvard University

Fleischer, Thomas (författare): Oslo university hospital

Moksnes Bjaanæs, Maria (författare): Oslo university hospital

Karlsson, Anna (författare): Lund University,Lunds universitet,Medicinsk strålningsfysik, Malmö,Forskargrupper vid Lunds universitet,Medical Radiation Physics, Malmö,Lund University Research Groups

Planck, Maria (författare): Lund University,Lunds universitet,Forskningsgrupp Lungcancer,Forskargrupper vid Lunds universitet,LUCC: Lunds universitets cancercentrum,Övriga starka forskningsmiljöer,Research Group Lung Cancer,Lund University Research Groups,LUCC: Lund University Cancer Centre,Other Strong Research Environments

Wang, Rui (författare): Nanjing University,Jinling Hospital, Nanjing

Staaf, Johan (författare): Lund University,Lunds universitet,Forskningsgrupp Lungcancer,Forskargrupper vid Lunds universitet,LUCC: Lunds universitets cancercentrum,Övriga starka forskningsmiljöer,Research Group Lung Cancer,Lund University Research Groups,LUCC: Lund University Cancer Centre,Other Strong Research Environments

Helland, Åslaug (författare): University of Oslo,Oslo university hospital

Esteller, Manel (författare): Catalan Institution for Research and Advanced Studies,Josep Carreras Leukaemia Research Institute (IJC),University of Barcelona,Spanish Center for Biomedical Research Network in Oncology (CIBERONC)

Wei, Yongyue (författare): Nanjing Medical University,Harvard University

Chen, Feng (författare): Nanjing Medical University

Christiani, David C. (författare): Massachusetts General Hospital,Harvard University

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Elsevier BV, 2020
2020
Engelska 12 s.
Ingår i: Chest. - : Elsevier BV. - 0012-3692. ; 158:2, s. 808-819

Relaterad länk:: http://dx.doi.org/10... (free); visa fler...; http://journal.chest...; https://lup.lub.lu.s...; https://doi.org/10.1...; visa färre...

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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.

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MEDICIN OCH HÄLSOVETENSKAP: MEDICIN OCH HÄLS ...; och Klinisk medicin; och Cancer och onkol ...

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

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