Figure 1. A schematic diagram of this novel systems biology-based gene expression classifier for HCC diagnosis.

First, the genes differentially expressed in HCC tissues relative to their corresponding non-tumor tissues were filtered by a corrected Q value cut-off and Concept filters in the Oncomine platform. The identified genes that are common among different microarray datasets were chosen as the candidate genes. Then, their networks were analyzed by GeneGO Meta-Core software and the hub genes were chosen. After that, HCC diagnostic classifier was constructed by PLS modeling based on the microarray gene expression data of the hub genes. Finally, the diagnostic performance of this classifier was evaluated by predictive accuracy and area under ROC curve.