© The Author 2007. Published by Oxford University Press.
ARTICLES |
A 25-Signal Proteomic Signature and Outcome for Patients With Resected Non–Small-Cell Lung Cancer
Affiliations of authors: Institute for Advanced Research, Nagoya University, Nagoya, Aichi, Japan (KY); Division of Molecular Carcinogenesis, Center for Neurological Diseases and Cancer, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan (KY, ST, YS, TT); Departments of Pathology and Molecular Diagnostics (YY) and Thoracic Surgery (TM), Aichi Cancer Center Hospital, Nagoya, Aichi, Japan
Correspondence to: Kiyoshi Yanagisawa, MD, PhD, Institute for Advanced Research, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Aichi 464-8601, Japan (e-mail: kyana{at}med.nagoya-u.ac.jp).
Background: Among patients with non–small-cell lung cancer (NSCLC), those with poor prognosis cannot be distinguished from those with good prognosis.
Methods: Matrix-assisted laser desorption–ionization mass spectrometry was used to analyze protein profiles of 174 specimens from NSCLC tumors and 27 specimens from normal lung tissue and to derive a prognosis-associated proteomic signature. Frozen resected tissue specimens were randomly divided into a training set (116 NSCLC and 20 normal lung specimens) and an independent, blinded validation set (58 NSCLC and seven normal lung specimens). Mass spectrometry signals from training set specimens that were differentially associated with specimens from patients with a high risk of recurrence (i.e., who died within 5 years of surgical treatment because of relapse) compared with those from patients with a low risk of recurrence (i.e., alive with no symptoms of relapse after a median follow-up of 89 months) were selected by use of the Fisher's exact test, the Kruskal–Wallis test, and the significance analysis of microarray test. These signals were used to build an individualized, weighted voting–based prognostic signature. The signature was then validated in the independent dataset. Survival was assessed by multivariable Cox regression analysis. Proteins corresponding to individual signals were identified by ion-trap mass spectrometry coupled with high-performance liquid chromatography. All statistical tests were two-sided.
Results: From 2630 mass spectrometry signals from specimens in the training cohort, we derived a signature of 25 signals that was associated with both relapse-free survival and overall survival. Among stage I NSCLC patients in the validation set, the signature was statistically significantly associated with both overall survival (hazard ratio [HR] of death for patients in the high-risk group compared with those in the low-risk group = 61.1, 95% confidence interval [CI] = 8.9 to 419.2, P<.001) and relapse-free survival (HR of relapse = 11.7, 95% CI = 3.1 to 44.8, P<.001). Proteins corresponding to signals in the signature were identified that had various cellular functions, including ribosomal protein L26-like 1, acylphosphatase, and phosphoprotein enriched in astrocytes 15.
Conclusions: We defined a mass spectrometry signature that was associated with survival among NSCLC patients and appeared to distinguish those with poor prognosis from those with good prognosis.
| CONTEXT AND CAVEATS Prior knowledge Patients with non–small-cell lung cancer (NSCLC) who have poor prognosis cannot be distinguished from those with good prognosis. Study design A training set–validation set design was used to derive a proteomic signature that was associated with prognosis. Tissues were tumor and normal lung tissues from NSCLC patients with a high risk of recurrence or with a low risk of recurrence. Contribution A signature of 25 mass spectrometry signals was derived that could statistically significantly distinguish NSCLC tumors with good prognosis from those with poor prognosis. Implications The 25-signal proteomic signature may be useful to distinguish NSCLC patients with good prognosis from those with poor prognosis. Determination of the roles of the proteins represented in the proteomic signature in NSCLC tumorigenesis and progression may lead to improved treatment for NSCLC. Limitations Approximately half of proteins contributing to the proteomic signature have been identified. Additional resources are needed for the identification of proteins in matrix-assisted laser desorption–ionization mass spectrometry signals. Mass spectrometry signals are limited to relatively highly abundant proteins with a low molecular weight.
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Manuscript received August 23, 2006; revised March 20, 2007; accepted April 24, 2007.
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J Natl Cancer Inst 2007 99: 825.
J Natl Cancer Inst 2007 99: 825.