Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/174837
Full metadata record
DC FieldValueLanguage
dc.contributor.authorZhang, Ruyang-
dc.contributor.authorChen, Chao-
dc.contributor.authorDong, Xuesi-
dc.contributor.authorShen, Sipeng-
dc.contributor.authorLai, Linjing-
dc.contributor.authorHe, Jieyu-
dc.contributor.authorYou, Dongfang-
dc.contributor.authorLin, Lijuan-
dc.contributor.authorZhu, Ying-
dc.contributor.authorHuang, Hui-
dc.contributor.authorChen, Jiajin-
dc.contributor.authorWei, Liangmin-
dc.contributor.authorChen, Xin-
dc.contributor.authorLi, Yi-
dc.contributor.authorGuo, Yichen-
dc.contributor.authorDuan, Weiwei-
dc.contributor.authorLiu, Liya-
dc.contributor.authorSu, Li-
dc.contributor.authorShafer, Andrea-
dc.contributor.authorFleischer, Thomas-
dc.contributor.authorBjaanæs, Maria Moksnes-
dc.contributor.authorKarlsson, Anna-
dc.contributor.authorPlanck, Maria-
dc.contributor.authorWang, Rui-
dc.contributor.authorStaaf, Johan-
dc.contributor.authorHelland, Åslaug-
dc.contributor.authorEsteller, Manel-
dc.contributor.authorWei, Yongyue-
dc.contributor.authorChen, Feng-
dc.contributor.authorChristiani, David C.-
dc.date.accessioned2021-03-09T15:26:05Z-
dc.date.available2021-03-09T15:26:05Z-
dc.date.issued2020-08-01-
dc.identifier.issn0012-3692-
dc.identifier.urihttp://hdl.handle.net/2445/174837-
dc.description.abstractBackground: 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.-
dc.format.extent12 p.-
dc.format.mimetypeapplication/pdf-
dc.language.isoeng-
dc.publisherAmerican College of Chest Physicians-
dc.relation.isformatofReproducció del document publicat a: https://doi.org/10.1016/j.chest.2020.01.048-
dc.relation.ispartofChest, 2020, vol. 158, num. 2, p. 808-819-
dc.relation.urihttps://doi.org/10.1016/j.chest.2020.01.048-
dc.rightscc by (c) Zhang et al, 2020-
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.sourceArticles publicats en revistes (Ciències Fisiològiques)-
dc.subject.classificationCàncer de pulmó-
dc.subject.classificationCèl·lules canceroses-
dc.subject.classificationMarcadors tumorals-
dc.subject.classificationEpigenètica-
dc.subject.otherLung cancer-
dc.subject.otherCancer cells-
dc.subject.otherTumor markers-
dc.subject.otherEpigenetics-
dc.titleIndependent validation of early-stage NSCLC prognostic scores incorporating epigenetic and transcriptional biomarkers with gene-gene interactions and main effects-
dc.typeinfo:eu-repo/semantics/article-
dc.typeinfo:eu-repo/semantics/publishedVersion-
dc.identifier.idgrec700094-
dc.date.updated2021-03-09T15:26:05Z-
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess-
dc.identifier.pmid32113923-
Appears in Collections:Articles publicats en revistes (Ciències Fisiològiques)

Files in This Item:
File Description SizeFormat 
700094.pdf1.27 MBAdobe PDFView/Open


This item is licensed under a Creative Commons License Creative Commons