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