Prognosis of stage I lung cancer patients through quantitative analysis of centrosomal features

Centrosome amplification leads to the loss of regulated chromosome segregation, aneuploidy, and chromosome instability and has the possibility to be a biomarker of cancer prognosis. To explore this feasibility, resected, stage I non-small cell lung cancer (NSCLC) tissues from six survivor and six fatal cases were immunostained and scanned. Regions of interest were selected to include one cell and its centrosomes. After segmentation, feature abstraction, and optimization, six nonredundant features were used for statistical analysis and classification. Two analytic methods showed that for each feature, centrosomes from survivors differed from centrosomes of fatalities, indicating sampling from different populations. The data were classified using linear discriminant analysis (LDA) and support vector machines (SVM) with 10-fold cross-validation. Classification accuracy was 74% by LDA and 79% by SVM, respectively, and further improved to 85% with bagging. Centrosome can be a biomarker for stage I NSCLC prognosis and has potential for clinical utility.