Protein expression profile characteristic to hepatocellular carcinoma revealed by 2D-DIGE with supervised learning.

Hepatocellular carcinoma (HCC) is one of the most common and aggressive human malignancies. Although several major risks related to HCC, e.g., hepatitis B and/or hepatitis C virus infection, aflatoxin B1 exposure, alcohol drinking and genetic defects have been revealed, the molecular mechanisms leading to the initiation and progression of HCC have not been clarified. To reduce the mortality and improve the effectiveness of therapy, it is important to detect the proteins which are associated with tumor progression and may be useful as potential therapeutic or diagnosis targets. However, previous studies have not yet revealed the associations among HCC cells, histological grade and AFP. Here, we performed two-dimensional difference gel electrophoresis (2D-DIGE) combined with MS for 18 HCC patients. To focus not on individual proteins but on multiple proteins associated with pathogenesis, we introduce the supervised feature selection based on stochastic gradient boosting (SGB) for identifying protein spots that discriminate HCC/non HCC, histological grade of moderate/well and high alpha-fetoprotein (AFP)/low AFP level without arbitrariness. We detected 18, 25 and 27 protein spots associated with HCC, histological grade and AFP level, respectively. We confirmed that SGB is able to identify the known HCC-related proteins, e.g., heat shock proteins, carbonic anhydrase 2. Moreover, we identified the differentially expressed proteins associated with histological grade of HCC and AFP level and found that aldo-keto reductase 1B10 (AKR1B10) is related to well differentiated HCC, keratin 8 (KRT8) is related to both histological grade and AFP level and protein disulfide isomerase-associated 3 (PDIA3) is associated with both HCC and AFP level. Our pilot study provides new insights on understanding the pathogenesis of HCC, histological grade and AFP level.