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Identification of cancer risk assessment signature in patients with chronic obstructive pulmonary disease and exploration of the potential key genes

It is essential to assess the cancer risk for patients with chronic obstructive pulmonary disease (COPD). Comparing gene expression data from patients with lung cancer (a total of 506 samples) and those with cancer-adjacent normal lung tissues (a total of 370 samples), we generated a qualitative tra...

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Autores principales: Guan, Qingzhou, Zhao, Peng, Tian, Yange, Yang, Liping, Zhang, Zhenzhen, Li, Jiansheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9415445/
https://www.ncbi.nlm.nih.gov/pubmed/35993327
http://dx.doi.org/10.1080/07853890.2022.2112070
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author Guan, Qingzhou
Zhao, Peng
Tian, Yange
Yang, Liping
Zhang, Zhenzhen
Li, Jiansheng
author_facet Guan, Qingzhou
Zhao, Peng
Tian, Yange
Yang, Liping
Zhang, Zhenzhen
Li, Jiansheng
author_sort Guan, Qingzhou
collection PubMed
description It is essential to assess the cancer risk for patients with chronic obstructive pulmonary disease (COPD). Comparing gene expression data from patients with lung cancer (a total of 506 samples) and those with cancer-adjacent normal lung tissues (a total of 370 samples), we generated a qualitative transcriptional signature consisting of 2046 gene pairs. The signature was verified in an evaluation dataset comprising 18 subjects with severe disease and 52 subjects with moderate disease (Wilcoxon rank-sum test; p = 7.33 × 10(−5)). Similar results were obtained in other independent datasets. Among the gene pairs in the signature, 326 COPD stage-related gene pairs were identified based on Spearman’s rank correlation tests and those gene pairs comprised 368 unique genes. Of these 368 genes, 16 genes were significantly dysregulated in COPD rat model data compared with control data. Some of these genes (Dhx16, Upf2, Notch3, Sec61a1, Dyrk2, and Hmmr KEY MESSAGES: A cancer risk assessment signature was identified in patients with COPD. The signature is insensitive to batch effects and is well verified. COPD key genes identified in this study might play a crucial role in TCM treatment and cancer prevention.
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spelling pubmed-94154452022-08-27 Identification of cancer risk assessment signature in patients with chronic obstructive pulmonary disease and exploration of the potential key genes Guan, Qingzhou Zhao, Peng Tian, Yange Yang, Liping Zhang, Zhenzhen Li, Jiansheng Ann Med Medical Genetics & Genomics It is essential to assess the cancer risk for patients with chronic obstructive pulmonary disease (COPD). Comparing gene expression data from patients with lung cancer (a total of 506 samples) and those with cancer-adjacent normal lung tissues (a total of 370 samples), we generated a qualitative transcriptional signature consisting of 2046 gene pairs. The signature was verified in an evaluation dataset comprising 18 subjects with severe disease and 52 subjects with moderate disease (Wilcoxon rank-sum test; p = 7.33 × 10(−5)). Similar results were obtained in other independent datasets. Among the gene pairs in the signature, 326 COPD stage-related gene pairs were identified based on Spearman’s rank correlation tests and those gene pairs comprised 368 unique genes. Of these 368 genes, 16 genes were significantly dysregulated in COPD rat model data compared with control data. Some of these genes (Dhx16, Upf2, Notch3, Sec61a1, Dyrk2, and Hmmr KEY MESSAGES: A cancer risk assessment signature was identified in patients with COPD. The signature is insensitive to batch effects and is well verified. COPD key genes identified in this study might play a crucial role in TCM treatment and cancer prevention. Taylor & Francis 2022-08-20 /pmc/articles/PMC9415445/ /pubmed/35993327 http://dx.doi.org/10.1080/07853890.2022.2112070 Text en © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Medical Genetics & Genomics
Guan, Qingzhou
Zhao, Peng
Tian, Yange
Yang, Liping
Zhang, Zhenzhen
Li, Jiansheng
Identification of cancer risk assessment signature in patients with chronic obstructive pulmonary disease and exploration of the potential key genes
title Identification of cancer risk assessment signature in patients with chronic obstructive pulmonary disease and exploration of the potential key genes
title_full Identification of cancer risk assessment signature in patients with chronic obstructive pulmonary disease and exploration of the potential key genes
title_fullStr Identification of cancer risk assessment signature in patients with chronic obstructive pulmonary disease and exploration of the potential key genes
title_full_unstemmed Identification of cancer risk assessment signature in patients with chronic obstructive pulmonary disease and exploration of the potential key genes
title_short Identification of cancer risk assessment signature in patients with chronic obstructive pulmonary disease and exploration of the potential key genes
title_sort identification of cancer risk assessment signature in patients with chronic obstructive pulmonary disease and exploration of the potential key genes
topic Medical Genetics & Genomics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9415445/
https://www.ncbi.nlm.nih.gov/pubmed/35993327
http://dx.doi.org/10.1080/07853890.2022.2112070
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