Network-based approach identified cell cycle genes as predictor of overall survival in lung adenocarcinoma patients.
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.
Department of Epidemiology, College of Preventive Medicine, Third Military Medical University, Chongqing, People's Republic of China.
Yafei
Y
Li
Hui
H
Tang
Zhifu
Z
Sun
Aaron O
AO
Bungum
Eric S
ES
Edell
Wilma L
WL
Lingle
Shawn M
SM
Stoddard
Mingrui
M
Zhang
Jin
J
Jen
Ping
P
Yang
Liang
L
Wang
D000230:Adenocarcinoma / Q000235:genetics* / Q000473:pathology; D000368:Aged; D000369:Aged, 80 and over; D018797:Cell Cycle Proteins / Q000235:genetics*; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D053263:Gene Regulatory Networks; D006801:Humans; D008175:Lung Neoplasms / Q000235:genetics* / Q000473:pathology; D008297:Male; D008869:Microtubule-Associated Proteins / Q000235:genetics; D008875:Middle Aged; D008957:Models, Genetic; D009687:Nuclear Proteins / Q000235:genetics; D020411:Oligonucleotide Array Sequence Analysis; D011237:Predictive Value of Tests; D011379:Prognosis; D017346:Protein Serine-Threonine Kinases / Q000235:genetics; D016019:Survival Analysis; D013997:Time Factors; D044763:Ubiquitin-Conjugating Enzymes / Q000235:genetics
D018797:Cell Cycle Proteins; D008869:Microtubule-Associated Proteins; D009687:Nuclear Proteins; C122167:TPX2 protein, human; C105156:UBE2C protein, human; D044763:Ubiquitin-Conjugating Enzymes; C484610:MELK protein, human; D017346:Protein Serine-Threonine Kinases