Three immunomarker support vector machines-based prognostic classifiers for stage IB non-small-cell lung cancer.
OBJECTIVE
Approximately 30% of patients with stage IB non-small-cell lung cancer (NSCLC) die within 5 years after surgery. Current staging methods are inadequate for predicting the prognosis of this particular subgroup. This study identifies prognostic markers for NSCLC.


METHODS
We used computer-generated random numbers to study 148 paraffin-embedded specimens for immunohistochemical analysis. We studied gene expression in paraffin-embedded specimens of lung cancer tissue from 73 randomly selected patients with stage IB NSCLC who had undergone radical surgical resection and evaluated the association between the level of expression and survival. We used support vector machines (SVM)-based methods to develop three immunomarker-SVM-based prognostic classifiers for stage IB NSCLC. For validation, we used randomly assigned specimens from 75 other patients.


RESULTS
We devised three immunomarker-SVM-based prognostic classifiers, including SVM1, SVM2, and SVM3, to refine prognosis of stage IB NSCLC successfully. The SVM1 model integrates age, cancer cell type, and five markers, including CD34MVD, EMA, p21ras, p21WAF1, and tissue inhibitors of metalloproteinases (TIMP) -2. The SVM2 model integrates age, cancer cell type, and 19 markers, including BCL2, caspase-9, CD34MVD, low-molecular-weight cytokeratin, high-molecular-weight cytokeratin, cyclo-oxygenase-2, EMA, HER2, matrix metalloproteinases (MMP) -2, MMP-9, p16, p21ras, p21WAF1, p27kip1, p53, TIMP-1, TIMP-2, vascular endothelial growth factor (VEGF), and beta-catenin. The SVM3 model consists of SVM1 and SVM2. The three models were independent predictors of overall survival. We validated the classifiers with data from an independent cohort of 75 patients with stage IB NSCLC.


CONCLUSIONS
The three immunomarker-SVM-based prognostic characteristics are closely associated with overall survival among patients with stage IB NSCLC.
Zhu
Zhi-Hua
ZH
Department of Thoracic Oncology, Cancer Center of Sun Yat-Sen University, 651 Dongfeng Rd E, Guangzhou 510060, People's Republic of China, USA.
Sun
Bing-Yu
BY
Ma
Yun
Y
Shao
Jian-Yong
JY
Long
Hao
H
Zhang
Xu
X
Fu
Jian-Hua
JH
Zhang
Lan-Jun
LJ
Su
Xiao-Dong
XD
Wu
Qiu-Liang
QL
Ling
Peng
P
Chen
Ming
M
Xie
Ze-Ming
ZM
Hu
Yi
Y
Rong
Tie-Hua
TH
D000328:Adult; D000368:Aged; D001185:Artificial Intelligence; D014408:Biomarkers, Tumor; D002289:Carcinoma, Non-Small-Cell Lung / Q000473:pathology*; D003936:Diagnosis, Computer-Assisted; D005260:Female; D006801:Humans; D007150:Immunohistochemistry; D008175:Lung Neoplasms / Q000473:pathology*; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D020411:Oligonucleotide Array Sequence Analysis; D011379:Prognosis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016019:Survival Analysis
D014408:Biomarkers, Tumor