Lack of sensitive and specific biomarkers is a major reason for the high rate of hepatocellular carcinoma (HCC) related mortality. The aim of this study was to use surface-enhanced laser desorption/ionization-time-of-flight mass spectroscopy (SELDI-TOF-MS) technology to identify potential protein patterns specific for HCC. Eighty-one patients with hepatitis B-related HCC and 80 healthy controls were randomly divided into a training set (48 HCC, 47 controls) and a testing set (33 HCC, 33 controls). Serum proteomic profiles were measured using SELDI-TOF-MS. A classification tree was established by Biomarker Pattern Software. Candidate biomarkers were separated by HPLC and identified by MALDI-MS/MS and database searching. Forty-eight HCC cases, 54 liver cirrhosis cases and 42 healthy people were clinically validated using candidate biomarkers by SELDI-Immunoassay. Two up-regulated protein peaks were automatically chosen as a classification tree in the training set. These biomarkers were identified as thrombin light chain and growth related oncogene-alpha (GRO-alpha). The sensitivity and specificity of this classification tree were 89.6%. The multivariate model using the two biomarkers and AFP resulted in a sensitivity of 91.7% and specificity of 92.7%, which was significantly better than that of alpha-fetoprotein alone. We conclude that thrombin light chain and GRO-alpha are potential biomarkers of HCC.