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Journal of the National Cancer Institute Advance Access originally published online on August 8, 2007
JNCI Journal of the National Cancer Institute 2007 99(16):1257-1269; doi:10.1093/jnci/djm083
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Published by Oxford University Press 2007.

ARTICLES

Use of a Cytokine Gene Expression Signature in Lung Adenocarcinoma and the Surrounding Tissue as a Prognostic Classifier

Masahiro Seike, Nozomu Yanaihara, Elise D. Bowman, Krista A. Zanetti, Anuradha Budhu, Kensuke Kumamoto, Leah E. Mechanic, Shingo Matsumoto, Jun Yokota, Tatsuhiro Shibata, Haruhiko Sugimura, Akihiko Gemma, Shoji Kudoh, Xin W. Wang, Curtis C. Harris

Affiliations of authors: Laboratory of Human Carcinogenesis, Center for Cancer Research (MS, NY, EDB, KAZ, AB, KK, LEM, XWW, CCH) and Cancer Prevention Fellowship Program, Division of Cancer Prevention (KAZ), National Cancer Institute, National Institutes of Health, Bethesda, MD; Biology Division, National Cancer Center Research Institute, Tokyo, Japan (SM, JY); Cancer Genomics Project, National Cancer Center Research Institute, Tokyo, Japan (TS); Department of Pathology, Hamamatsu University School of Medicine, Hamamatsu, Japan (HS); Department of Pulmonary Medicine/Infection and Oncology, Nippon Medical School, Tokyo, Japan (MS, AG, SK)

Correspondence to: Curtis C. Harris, MD, Laboratory of Human Carcinogenesis, National Cancer Institute, National Institutes of Health, 37 Convent Dr, Bldg 37, Rm 3068, Bethesda, MD 20892-4258 (e-mail: curtis_harris{at}nih.gov).

Background: A 17-cytokine gene expression signature in noncancerous hepatic tissue from patients with metastatic hepatocellular carcinoma (HCC) was recently found to predict HCC metastasis and recurrence. We examined whether the cytokine gene expression profile of noncancerous lung tissue could predict the metastatic capability of adjacent lung adenocarcinoma.

Methods: We analyzed a 15–cytokine gene expression profile in noncancerous lung tissue and corresponding lung tumor tissue from 80 US lung adenocarcinoma patients using real-time quantitative reverse transcription–polymerase chain reaction. We then used unsupervised hierarchical clustering and Prediction Analysis of Microarray classification to test the prognostic ability of the 15–cytokine gene profile in the US patients and in an independent validation set comprising 50 Japanese patients with stage I disease. Survival was analyzed by the Kaplan–Meier method using the log-rank test, and univariate and multivariable Cox proportional hazards modeling were used to analyze the association of clinical variables with patient survival. All statistical tests were two-sided.

Results: A 15–cytokine gene signature in noncancerous lung tissue primarily reflected the lymph node status of 80 lung adenocarcinoma patients, whereas the gene signature of the corresponding lung tumor tissue was associated with prognosis independent of lymph node status. Cytokine Lung Adenocarcinoma Survival Signature of 11 genes (CLASS-11), a refined 11-gene signature, accurately classified patients, including those with stage I disease, according to risk of death from adenocarcinoma. CLASS-11 prognostic classification was statistically significantly associated with survival and was an independent prognostic factor for stage I patients (hazard ratio for death in the high-risk CLASS-11 group compared with the low-risk CLASS-11 reference group = 7.46, 95% confidence interval = 2.14 to 26.05; P = .002). CLASS-11 also classified patients in the validation set according to risk of recurrence.

Conclusion: CLASS-11, which consists of genes for pro- and anti-inflammatory cytokines, identifies stage I lung adenocarcinoma patients who have a poor prognosis.



CONTEXT AND CAVEATS

Prior knowledge

The finding that a unique 17-cytokine gene expression signature in noncancerous hepatic tissue from patients with metastatic hepatocellular carcinoma predicts hepatocellular carcinoma metastasis and recurrence suggests that gene expression changes in surrounding noncancerous tissue as well as in tumors can be used as biomarkers to predict prognosis and metastasis in other cancers.

Study design

Molecular profiling study of the prognostic ability of a cytokine gene profile in lung adenocarcinoma patients.

Contribution

A unique 11-cytokine gene signature that was based on expression profiling of both noncancerous lung tissue and lung tumors accurately classified stage I lung adenocarcinoma patients according to their risk of death.

Implications

This cytokine gene signature may be useful for determining which lung adenocarcinoma patients are at high risk of death and thus may benefit from adjuvant therapy.

Limitations

Patients included in the validation set had shorter follow-up and were of different ethnicity than patients in the training set.

 
Manuscript received January 8, 2007; revised June 8, 2007; accepted June 26, 2007.


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