Network-based approach identified cell cycle genes as predictor of overall survival in lung adenocarcinoma patients

Yafei Li, Hui Tang, Zhifu D Sun, Aaron O. Bungum, Eric Edell, Wilma L. Lingle, Shawn M. Stoddard, Mingrui Zhang, Jin Jen, Ping Yang, Liang Wang

Research output: Contribution to journalArticle

20 Citations (Scopus)

Abstract

Lung adenocarcinoma is the most common type of primary lung cancer. The purpose of this study was to delineate gene expression patterns for survival prediction in lung adenocarcinoma. Gene expression profiles of 82 (discovery set) and 442 (validation set 1) lung adenocarcinoma tumor tissues were analyzed using a systems biology-based network approach. We also examined the expression profiles of 78 adjacent normal lung tissues from 82 patients. We found a significant correlation of an expression module with overall survival (adjusted hazard ratio or HR. =1.71; 95% CI. =1.06-2.74 in discovery set; adjusted HR. =1.26; 95% CI. =1.08-1.49 in validation set 1). This expression module contained genes enriched in the biological process of the cell cycle. Interestingly, the cell cycle gene module and overall survival association were also significant in normal lung tissues (adjusted HR. =1.91; 95% CI, 1.32-2.75). From these survival-related modules, we further defined three hub genes (UBE2C, TPX2, and MELK) whose expression-based risk indices were more strongly associated with poor 5-year survival (HR. =3.85, 95% CI. =1.34-11.05 in discovery set; HR. =1.72, 95% CI. =1.21-2.46 in validation set 1; and HR. =3.35, 95% CI. =1.08-10.04 in normal lung set). The 3-gene prognostic result was further validated using 92 adenocarcinoma tumor samples (validation set 2); patients with a high-risk gene signature have a 1.52-fold increased risk (95% CI, 1.02-2.24) of death than patients with a low-risk gene signature. These results suggest that a network-based approach may facilitate discovery of key genes that are closely linked to survival in patients with lung adenocarcinoma.

Original languageEnglish (US)
Pages (from-to)91-98
Number of pages8
JournalLung Cancer
Volume80
Issue number1
DOIs
StatePublished - Apr 2013

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cdc Genes
Survival
Gene Regulatory Networks
Lung
Genes
Biological Phenomena
Systems Biology
Genetic Association Studies
Transcriptome
Adenocarcinoma of lung
Lung Neoplasms
Neoplasms
Cell Cycle
Adenocarcinoma
Gene Expression

Keywords

  • Cell cycle
  • Gene expression profiling
  • Lung cancer
  • Survival
  • Systems biology

ASJC Scopus subject areas

  • Oncology
  • Pulmonary and Respiratory Medicine
  • Cancer Research

Cite this

Network-based approach identified cell cycle genes as predictor of overall survival in lung adenocarcinoma patients. / Li, Yafei; Tang, Hui; Sun, Zhifu D; Bungum, Aaron O.; Edell, Eric; Lingle, Wilma L.; Stoddard, Shawn M.; Zhang, Mingrui; Jen, Jin; Yang, Ping; Wang, Liang.

In: Lung Cancer, Vol. 80, No. 1, 04.2013, p. 91-98.

Research output: Contribution to journalArticle

Li, Yafei ; Tang, Hui ; Sun, Zhifu D ; Bungum, Aaron O. ; Edell, Eric ; Lingle, Wilma L. ; Stoddard, Shawn M. ; Zhang, Mingrui ; Jen, Jin ; Yang, Ping ; Wang, Liang. / Network-based approach identified cell cycle genes as predictor of overall survival in lung adenocarcinoma patients. In: Lung Cancer. 2013 ; Vol. 80, No. 1. pp. 91-98.
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abstract = "Lung adenocarcinoma is the most common type of primary lung cancer. The purpose of this study was to delineate gene expression patterns for survival prediction in lung adenocarcinoma. Gene expression profiles of 82 (discovery set) and 442 (validation set 1) lung adenocarcinoma tumor tissues were analyzed using a systems biology-based network approach. We also examined the expression profiles of 78 adjacent normal lung tissues from 82 patients. We found a significant correlation of an expression module with overall survival (adjusted hazard ratio or HR. =1.71; 95{\%} CI. =1.06-2.74 in discovery set; adjusted HR. =1.26; 95{\%} CI. =1.08-1.49 in validation set 1). This expression module contained genes enriched in the biological process of the cell cycle. Interestingly, the cell cycle gene module and overall survival association were also significant in normal lung tissues (adjusted HR. =1.91; 95{\%} CI, 1.32-2.75). From these survival-related modules, we further defined three hub genes (UBE2C, TPX2, and MELK) whose expression-based risk indices were more strongly associated with poor 5-year survival (HR. =3.85, 95{\%} CI. =1.34-11.05 in discovery set; HR. =1.72, 95{\%} CI. =1.21-2.46 in validation set 1; and HR. =3.35, 95{\%} CI. =1.08-10.04 in normal lung set). The 3-gene prognostic result was further validated using 92 adenocarcinoma tumor samples (validation set 2); patients with a high-risk gene signature have a 1.52-fold increased risk (95{\%} CI, 1.02-2.24) of death than patients with a low-risk gene signature. These results suggest that a network-based approach may facilitate discovery of key genes that are closely linked to survival in patients with lung adenocarcinoma.",
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