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, R. (Department of Medical Oncology. Jinling Hospital. School of Medicine. Nanjing University)
Chen, C. (Department of Biostatistics. Center for Global Health. School of Public Health. Nanjing Medical University)
Dong, X. (Department of Epidemiology and Biostatistics. School of Public Health. Southeast University)
Shen, S. (China International Cooperation Center for Environment and Human Health. Nanjing Medical University)
Lai, L. (Department of Biostatistics. Center for Global Health. School of Public Health. Nanjing Medical University)
He, J. (Department of Biostatistics. Center for Global Health. School of Public Health. Nanjing Medical University)
You, D. (Department of Environmental Health. Harvard T. H. Chan School of Public Health)
Lin, L. (Department of Environmental Health. Harvard T. H. Chan School of Public Health)
Zhu, Y. (Department of Biostatistics. Center for Global Health. School of Public Health. Nanjing Medical University)
Huang, H. (Department of Biostatistics. Center for Global Health. School of Public Health. Nanjing Medical University)
Chen, J. (Department of Biostatistics. Center for Global Health. School of Public Health. Nanjing Medical University)
Wei, Liangmin (Department of Biostatistics. Center for Global Health. School of Public Health. Nanjing Medical University)
Chen, X. (Department of Biostatistics. Center for Global Health. School of Public Health. Nanjing Medical University)
Li, Y. (Department of Biostatistics. University of Michigan)
Guo, Y. (Department of Biostatistics. Harvard T. H. Chan School of Public Health)
Duan, W. (Department of Bioinformatics. School of Biomedical Engineering and Informatics. Nanjing Medical University)
Liu, L. (Department of Preventive Medicine. Medical School of Ningbo University)
Su, L. (Department of Environmental Health. Harvard T. H. Chan School of Public Health)
Shafer, A. (Harvard Medical School)
Fleischer, T. (Department of Cancer Genetics. Institute for Cancer Research. Oslo University Hospital)
Moksnes Bjaanæs, M. (Department of Cancer Genetics. Institute for Cancer Research. Oslo University Hospital)
Karlsson, A. (Division of Oncology and Pathology. Department of Clinical Sciences. Lund and CREATE Health Strategic Center for Translational Cancer Research. Lund University)
Planck, M. (Division of Oncology and Pathology. Department of Clinical Sciences. Lund and CREATE Health Strategic Center for Translational Cancer Research. Lund University)
Wang, R. (Department of Medical Oncology. Jinling Hospital. School of Medicine. Nanjing University)
Staaf, J. (Division of Oncology and Pathology. Department of Clinical Sciences. Lund and CREATE Health Strategic Center for Translational Cancer Research. Lund University)
Helland, Å. (Institute of Clinical Medicine. University of Oslo)
Esteller, M. (Universitat de Barcelona. Facultat de Medicina i Ciències de la Salut)
Wei, Y. (China International Cooperation Center for Environment and Human Health. Nanjing Medical University)
Chen, F. (Jiangsu Key Laboratory of Cancer Biomarkers. Prevention and Treatment. Cancer Center. Collaborative Innovation Center for Cancer Personalized Medicine. Nanjing Medical University)
Christiani, David C (Harvard Medical School)
Universitat Autònoma de Barcelona

Data:	2020
Resum:	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.
Drets:	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.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Early stage ; Interaction ; Multiomics ; Non-small cell lung cancer ; Prognostic score
Publicat a:	Chest, Vol. 158 Núm. 2 (august 2020) , p. 808-819, ISSN 1931-3543

DOI: 10.1016/j.chest.2020.01.048
PMID: 32113923

12 p, 1.2 MB

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Documents de recerca > Documents dels grups de recerca de la UAB > Centres i grups de recerca (producció científica) > Ciències de la salut i biociències > Institut d'Investigació en Ciencies de la Salut Germans Trias i Pujol (IGTP)
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