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Identification of lung adenocarcinoma specific dysregulated genes with diagnostic and prognostic value across 27 TCGA cancer types

As the most common histologic subtype of lung cancer, lung adenocarcinoma (LUAD) contributes to a majority of cancer-related deaths worldwide annually. In order to find specific biomarkers of LUAD that are able to distinguish LUAD from other types of cancer so as to improve the early diagnostic and...

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Autores principales: Shang, Jun, Song, Qian, Yang, Zuyi, Li, Dongyao, Chen, Wenjie, Luo, Lei, Wang, Yongkun, Yang, Jingcheng, Li, Shikang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5675633/
https://www.ncbi.nlm.nih.gov/pubmed/29152081
http://dx.doi.org/10.18632/oncotarget.19823
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author Shang, Jun
Song, Qian
Yang, Zuyi
Li, Dongyao
Chen, Wenjie
Luo, Lei
Wang, Yongkun
Yang, Jingcheng
Li, Shikang
author_facet Shang, Jun
Song, Qian
Yang, Zuyi
Li, Dongyao
Chen, Wenjie
Luo, Lei
Wang, Yongkun
Yang, Jingcheng
Li, Shikang
author_sort Shang, Jun
collection PubMed
description As the most common histologic subtype of lung cancer, lung adenocarcinoma (LUAD) contributes to a majority of cancer-related deaths worldwide annually. In order to find specific biomarkers of LUAD that are able to distinguish LUAD from other types of cancer so as to improve the early diagnostic and prognostic power in LUAD, we analyzed 10098 tumor tissue samples across 27 TCGA cancer types and identified 112 specific expressed genes in LUAD. Meantime, 8240 LUAD dysregulated genes in tumor and normal samples were identified. Combining with the results of specific expressed genes and dysregulated genes in LUAD, we found there were 70 specific dysregulated genes in LUAD (LUAD-SDGs). Then ROC curve revealed six LUAD-SDGs that may be of strong diagnostic value to predict the existence of cancer (area under curve[AUC] > 95%). Kaplan-Meier survival analysis was performed to identify 6 LUAD-SDGs associated with patients’ prognosis (P-values < 0.001). Multivariate Cox proportional hazards regression was employed to demonstrate that the six LUAD-SDGs were independent prognostic factors. Then, we used the six overall survival (OS)-related LUAD-SDGs constructing a six-gene signature. Multivariate Cox regression analysis suggested that the six-gene signature was an independent prognostic factor of other clinical variables (hazard ratio [HR] = 1.5098, 95%CI = 1.2996-1.7538, P < 0.0001). Based on our findings, we first presented the LUAD-SDGs for LUAD diagnosis and prognosis. Our results may provide efficient biomarkers to clinical diagnostic and prognostic evaluation in LUAD.
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spelling pubmed-56756332017-11-18 Identification of lung adenocarcinoma specific dysregulated genes with diagnostic and prognostic value across 27 TCGA cancer types Shang, Jun Song, Qian Yang, Zuyi Li, Dongyao Chen, Wenjie Luo, Lei Wang, Yongkun Yang, Jingcheng Li, Shikang Oncotarget Research Paper As the most common histologic subtype of lung cancer, lung adenocarcinoma (LUAD) contributes to a majority of cancer-related deaths worldwide annually. In order to find specific biomarkers of LUAD that are able to distinguish LUAD from other types of cancer so as to improve the early diagnostic and prognostic power in LUAD, we analyzed 10098 tumor tissue samples across 27 TCGA cancer types and identified 112 specific expressed genes in LUAD. Meantime, 8240 LUAD dysregulated genes in tumor and normal samples were identified. Combining with the results of specific expressed genes and dysregulated genes in LUAD, we found there were 70 specific dysregulated genes in LUAD (LUAD-SDGs). Then ROC curve revealed six LUAD-SDGs that may be of strong diagnostic value to predict the existence of cancer (area under curve[AUC] > 95%). Kaplan-Meier survival analysis was performed to identify 6 LUAD-SDGs associated with patients’ prognosis (P-values < 0.001). Multivariate Cox proportional hazards regression was employed to demonstrate that the six LUAD-SDGs were independent prognostic factors. Then, we used the six overall survival (OS)-related LUAD-SDGs constructing a six-gene signature. Multivariate Cox regression analysis suggested that the six-gene signature was an independent prognostic factor of other clinical variables (hazard ratio [HR] = 1.5098, 95%CI = 1.2996-1.7538, P < 0.0001). Based on our findings, we first presented the LUAD-SDGs for LUAD diagnosis and prognosis. Our results may provide efficient biomarkers to clinical diagnostic and prognostic evaluation in LUAD. Impact Journals LLC 2017-08-02 /pmc/articles/PMC5675633/ /pubmed/29152081 http://dx.doi.org/10.18632/oncotarget.19823 Text en Copyright: © 2017 Shang et al. http://creativecommons.org/licenses/by/3.0/ This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) (CC-BY), which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Research Paper
Shang, Jun
Song, Qian
Yang, Zuyi
Li, Dongyao
Chen, Wenjie
Luo, Lei
Wang, Yongkun
Yang, Jingcheng
Li, Shikang
Identification of lung adenocarcinoma specific dysregulated genes with diagnostic and prognostic value across 27 TCGA cancer types
title Identification of lung adenocarcinoma specific dysregulated genes with diagnostic and prognostic value across 27 TCGA cancer types
title_full Identification of lung adenocarcinoma specific dysregulated genes with diagnostic and prognostic value across 27 TCGA cancer types
title_fullStr Identification of lung adenocarcinoma specific dysregulated genes with diagnostic and prognostic value across 27 TCGA cancer types
title_full_unstemmed Identification of lung adenocarcinoma specific dysregulated genes with diagnostic and prognostic value across 27 TCGA cancer types
title_short Identification of lung adenocarcinoma specific dysregulated genes with diagnostic and prognostic value across 27 TCGA cancer types
title_sort identification of lung adenocarcinoma specific dysregulated genes with diagnostic and prognostic value across 27 tcga cancer types
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5675633/
https://www.ncbi.nlm.nih.gov/pubmed/29152081
http://dx.doi.org/10.18632/oncotarget.19823
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