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Transcriptomic analysis reveals a WNT signaling pathway-based gene signature prognostic for non-small cell carcinoma

The value of combining multiple candidate genes into a panel to improve biomarker performance is increasingly emphasized. Genes associated with WNT signaling are widely-reported to provide prognostic signatures in non-small cell carcinoma (NSCLC). Screening of genes involved in this signaling pathwa...

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Autores principales: Liu, Gang, Xie, Wenhui, Jin, Mingming, Li, Ping, Liu, Liu, Liu, Lei, Huang, Gang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7732286/
https://www.ncbi.nlm.nih.gov/pubmed/33027769
http://dx.doi.org/10.18632/aging.103724
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author Liu, Gang
Xie, Wenhui
Jin, Mingming
Li, Ping
Liu, Liu
Liu, Lei
Huang, Gang
author_facet Liu, Gang
Xie, Wenhui
Jin, Mingming
Li, Ping
Liu, Liu
Liu, Lei
Huang, Gang
author_sort Liu, Gang
collection PubMed
description The value of combining multiple candidate genes into a panel to improve biomarker performance is increasingly emphasized. Genes associated with WNT signaling are widely-reported to provide prognostic signatures in non-small cell carcinoma (NSCLC). Screening of genes involved in this signaling pathway facilitated selection of an optimal candidate biomarker gene combination and development of an NSCLC prognostic model based on expression of these genes. Risk scores derived from the model performed well in predicting survival; in the training dataset, samples achieving a high risk score exhibit a shorter survival interval (median survival time 34.8 months, 95% CI 31.1-41.0) than did samples achieving a low risk score (median survival time 72.0 months, 95% CI 59.3-87.5, p=2e-11), and exhibited higher oncogene and lower tumor suppressor gene expression. Receiver-operator characteristic curves based on three-year survival demonstrate that the model outperformed clinical prognostic indicators. In addition, the model was validated in four independent cohorts, demonstrating robust NSCLC prognostic value. Correlation analyses reveal that the model offers efficacy independent of other clinical indicators. Gene Set Enrichment Analysis (GSEA) reveals that the model reflects variable tissue functional states relevant to NSCLC biology. In summary, the signature model shows potential as a valuable and robust NSCLC prognostic indicator.
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spelling pubmed-77322862020-12-18 Transcriptomic analysis reveals a WNT signaling pathway-based gene signature prognostic for non-small cell carcinoma Liu, Gang Xie, Wenhui Jin, Mingming Li, Ping Liu, Liu Liu, Lei Huang, Gang Aging (Albany NY) Research Paper The value of combining multiple candidate genes into a panel to improve biomarker performance is increasingly emphasized. Genes associated with WNT signaling are widely-reported to provide prognostic signatures in non-small cell carcinoma (NSCLC). Screening of genes involved in this signaling pathway facilitated selection of an optimal candidate biomarker gene combination and development of an NSCLC prognostic model based on expression of these genes. Risk scores derived from the model performed well in predicting survival; in the training dataset, samples achieving a high risk score exhibit a shorter survival interval (median survival time 34.8 months, 95% CI 31.1-41.0) than did samples achieving a low risk score (median survival time 72.0 months, 95% CI 59.3-87.5, p=2e-11), and exhibited higher oncogene and lower tumor suppressor gene expression. Receiver-operator characteristic curves based on three-year survival demonstrate that the model outperformed clinical prognostic indicators. In addition, the model was validated in four independent cohorts, demonstrating robust NSCLC prognostic value. Correlation analyses reveal that the model offers efficacy independent of other clinical indicators. Gene Set Enrichment Analysis (GSEA) reveals that the model reflects variable tissue functional states relevant to NSCLC biology. In summary, the signature model shows potential as a valuable and robust NSCLC prognostic indicator. Impact Journals 2020-10-07 /pmc/articles/PMC7732286/ /pubmed/33027769 http://dx.doi.org/10.18632/aging.103724 Text en Copyright: © 2020 Liu et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Liu, Gang
Xie, Wenhui
Jin, Mingming
Li, Ping
Liu, Liu
Liu, Lei
Huang, Gang
Transcriptomic analysis reveals a WNT signaling pathway-based gene signature prognostic for non-small cell carcinoma
title Transcriptomic analysis reveals a WNT signaling pathway-based gene signature prognostic for non-small cell carcinoma
title_full Transcriptomic analysis reveals a WNT signaling pathway-based gene signature prognostic for non-small cell carcinoma
title_fullStr Transcriptomic analysis reveals a WNT signaling pathway-based gene signature prognostic for non-small cell carcinoma
title_full_unstemmed Transcriptomic analysis reveals a WNT signaling pathway-based gene signature prognostic for non-small cell carcinoma
title_short Transcriptomic analysis reveals a WNT signaling pathway-based gene signature prognostic for non-small cell carcinoma
title_sort transcriptomic analysis reveals a wnt signaling pathway-based gene signature prognostic for non-small cell carcinoma
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7732286/
https://www.ncbi.nlm.nih.gov/pubmed/33027769
http://dx.doi.org/10.18632/aging.103724
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