Fig. 2.

Predicting the outcomes of neuroblastoma without gene selection. A, plot of the top three principal components (PC) of the 56 neuroblastoma samples using all quality-filtered 37,920 clones demonstrates some separation according to the clinical outcome. Red spheres represent poor-outcome patients, whereas blue spheres represent good-outcome patients. B, artificial neural network voting results for outcome prediction of the 49 unique neuroblastoma patients using 37,920 clones without any additional clone selection in a leave-one-out prediction scheme. (Samples labels: St, stage; NA, MYCN nonamplified; A, MYCN amplified, followed by sample name). Seven replicated samples (NB1, NB2, NB3, NB4, NB207, NB209, and NB210) were excluded for this analysis. Symbols, ANN average committee votes for each sample, whereas the length of the horizontal lines represents the SE. Red triangles, poor-outcome, and blue circles, good-outcome neuroblastomas. Vertical line at 0.5 is the decision boundary for outcome prediction (i.e., good signature < 0.5, poor signature >0.5). C, Kaplan-Meier curves of survival probability for the 49 neuroblastoma patients derived from the results in B. D, Kaplan-Meier curves of survival probability for the 49 neuroblastoma patients using the current Children’s Oncology Group risk stratification.