Oncotarget

Research Papers:

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

Jun Shang, Qian Song, Zuyi Yang, Dongyao Li, Wenjie Chen, Lei Luo, Yongkun Wang, Jingcheng Yang and Shikang Li _

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Oncotarget. 2017; 8:87292-87306. https://doi.org/10.18632/oncotarget.19823

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Abstract

Jun Shang1,*, Qian Song1,*, Zuyi Yang2,*, Dongyao Li1, Wenjie Chen1, Lei Luo1, Yongkun Wang1, Jingcheng Yang1 and Shikang Li1

1Department of Thoracic and Cardiovascular Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, P. R. China

2Department of Hematology, The First Affiliated Hospital of Soochow University, Suzhou 215006, P. R. China

*These authors have contributed equally to this work

Correspondence to:

Shikang Li, email: [email protected]

Jingcheng Yang, email: [email protected]

Keywords: RNA-seq, diagnosis, prognosis, lung adenocarcinoma

Received: April 14, 2017    Accepted: June 18, 2017    Published: August 02, 2017

ABSTRACT

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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