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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals
2020
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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. |
format | Online Article Text |
id | pubmed-7732286 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Impact Journals |
record_format | MEDLINE/PubMed |
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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