Hepatic tumor has different cell types, such as hepatocellular carcinoma, cholangiocarcinoma, bile duct cystadenocarcinoma, combined hepatocellular and cholangiocarcinoma, hepatoblastoma, undifferentiated carcinoma, hepatic angiomyolipoma, while different biomarkers have been developed and investigated for diagnosis, tumor progression, and prognosis of them [23–26]. It is also well recognized that biomarkers which may play important roles in physiologic and pathologic processes are important for diagnosis, prognosis, and prediction of HCC. Human serum contains LMW protein/peptides, which could be used as biomarker candidates,such as fibrinogen α-chain fibrinogen alpha, albumin and apolipoprotein A1 [27, 28].
Compared to genomic approaches, proteomic analysis has the advantage of detecting co-translational and post-translational modifications of proteins which may have important biological functions . MS is one of the most important techniques in proteomic analysis. MALDI-TOF MS is widely used in proteomics biomarker research due to its high sensitivity and high quality in analysis of peptides, proteins and large organic molecules [27–29].
HCC is one of the most common cancers in the world. Although AFP is a widely used serological marker for detection of HCC, its sensitivity and specificity are not optimal and it may also increase in patients with acute and chronic viral hepatitis, liver cirrhosis, and toxic injury [8, 9]. Therefore, use of AFP in the screening of early HCC is challenged and a new method for HCC early diagnosis is badly needed.
At present, serum or plasma proteomic analysis has been widely used to compare tumor patients with healthy controls. This technique can also be applied to HCC serum or plasma markers research. Looi KS et al. (2008) applied a proteomic approach (two-dimension gel electrophoresis and liquid chromatography-tandem mass spectrometry) to immune-screen sera from patients with HCC and pre-HCC conditions such as liver cirrhosis and chronic hepatitis as well as sera from normal individuals, and identified 28 HCC-associated tumor antigens, such as heat shock protein 60 (HSP60) and heat shock protein 70 (HSP70) . Mas VR et al. (2009) used Thermo linear ion-trap mass spectrometer (LTQ) coupled with a high performance liquid chromatography electrospray ionization tandem mass spectrometry (HPLC-ESI-MS/MS) and SEQUEST database search algorithms for peptide sequence identification. They found that 18 proteins from HCC patients showed significant changes compared with proteins from patients with HCV-cirrhosis and early HCV-HCC .
In the study, serum samples were divided into four groups (HCC, LC, CH and normal controls). MB-WCX was used for purification of LMW proteins/peptides in these serum samples. Peptides profile spectra were detected by MALDI-TOF MS and analyzed by ClinProt Tools software 2.2. We found 49 (HCC group), 33 (LC group) and 37 (CH group) peaks were significantly different from those in healthy controls (p < 0.001). All these peak differences may be associated with pathologic processes, specific immunity response or some risk factors, and may become potential biomarkers in early diagnosis. In addition, when comparing HCC patients with healthy controls, Liu T et al. (2011) reported 9 significant discrimination peaks at m/z 2862.79, 8862.77, 8931.95, 3935.62, 8141.78, 5248.47, 3955.45, 7765.78 and 1944.91 , which are close to 2863.11, 8867.91, 8931.25, 3935.27, 8138.19, 5247.62, 3955.8, 7763.84 and 1945.42 detected in the present study. In fact, a single biomarker has an inherent specificity and sensitivity that can not be improved, but multiple biomarkers can be combined to achieve improved clinical performance. In the study a diagnostic model generated by SNN algorithm analysis comprised 11 potential biomarkers (m/z: 5247.62, 7637.05, 1450.87, 4054.21, 1073.37, 3883.64, 5064.37, 4644.96, 5805.51, 1866.47 and 6579.6). Using this established diagnostic model, HCC, LC and CH patients could be distinguished from healthy controls; However, the HCC, LC or CH group could not be accurately identified using the model probably due to the small number of the patients enrolled in the study. Therefore, a large number of patients should be enrolled in the further study to establish a diagnostic model that is effective enough to distinguish among the three diseases.
Now, we are making investigation on these 11 m/z peaks that are co-expressed in hepatocellular carcinoma and other liver-related diseases in order to identity and characterize these biomarkers. In future research, we will validate them by western blot or ELISA technology and try to find a correlation with histopathology findings and cancer staging. Furthermore, we will reveal the biological roles of these proteins/peptides in the pathogenesis and processes of HCC.