Hybrid models identified a 12-gene signature for lung cancer prognosis and chemoresponse prediction.
BACKGROUND
Lung cancer remains the leading cause of cancer-related deaths worldwide. The recurrence rate ranges from 35-50% among early stage non-small cell lung cancer patients. To date, there is no fully-validated and clinically applied prognostic gene signature for personalized treatment.


RESULTS
From genome-wide mRNA expression profiles generated on 256 lung adenocarcinoma patients, a 12-gene signature was identified using combinatorial gene selection methods, and a risk score algorithm was developed with Naïve Bayes. The 12-gene model generates significant patient stratification in the training cohort HLM & UM (n = 256; log-rank P = 6.96e-7) and two independent validation sets, MSK (n = 104; log-rank P = 9.88e-4) and DFCI (n = 82; log-rank P = 2.57e-4), using Kaplan-Meier analyses. This gene signature also stratifies stage I and IB lung adenocarcinoma patients into two distinct survival groups (log-rank P<0.04). The 12-gene risk score is more significant (hazard ratio = 4.19, 95% CI: [2.08, 8.46]) than other commonly used clinical factors except tumor stage (III vs. I) in multivariate Cox analyses. The 12-gene model is more accurate than previously published lung cancer gene signatures on the same datasets. Furthermore, this signature accurately predicts chemoresistance/chemosensitivity to Cisplatin, Carboplatin, Paclitaxel, Etoposide, Erlotinib, and Gefitinib in NCI-60 cancer cell lines (P<0.017). The identified 12 genes exhibit curated interactions with major lung cancer signaling hallmarks in functional pathway analysis. The expression patterns of the signature genes have been confirmed in RT-PCR analyses of independent tumor samples.


CONCLUSIONS
The results demonstrate the clinical utility of the identified gene signature in prognostic categorization. With this 12-gene risk score algorithm, early stage patients at high risk for tumor recurrence could be identified for adjuvant chemotherapy; whereas stage I and II patients at low risk could be spared the toxic side effects of chemotherapeutic drugs.
Wan
Ying-Wooi
YW
Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, West Virginia, United States of America.
Sabbagh
Ebrahim
E
Raese
Rebecca
R
Qian
Yong
Y
Luo
Dajie
D
Denvir
James
J
Vallyathan
Val
V
Castranova
Vincent
V
Guo
Nancy Lan
NL
D000230:Adenocarcinoma / Q000175:diagnosis / Q000188:drug therapy / Q000235:genetics / Q000473:pathology; D000970:Antineoplastic Agents / Q000494:pharmacology / Q000627:therapeutic use; D045744:Cell Line, Tumor; D019008:Drug Resistance, Neoplasm / Q000235:genetics; D005260:Female; D020869:Gene Expression Profiling; D005819:Genetic Markers / Q000235:genetics; D006801:Humans; D008175:Lung Neoplasms / Q000175:diagnosis* / Q000188:drug therapy / Q000235:genetics* / Q000473:pathology; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D009367:Neoplasm Staging; D011379:Prognosis; D020133:Reverse Transcriptase Polymerase Chain Reaction
D000970:Antineoplastic Agents; D005819:Genetic Markers
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