To build a set of crucial biomarkers for machine learning, we combined two well-known biomarkers IL33 and ENO1 from recent HCC studies [22,23,24] with genes that showed high ratio of expression in our microarray data of TW-1/HTC, including TSPAN8, RBBP5, CD44, CD55, S100A10 and GSTA1, which all achieved high single AUC scores. Here, GSTA1 is linked to hepatocellular carcinoma.