Objective To appraise and compare
protein expression profiles in sera of
patients without or with
recurrence following
liver transplantation for
hepatocellular carcinoma (HCC) using
SELDI-TOF-MS technique,and establish the diagnostic and predictive model.
Methods A total of 76 sera (41 from
disease free survival patients and 35 from
recurrence individuals) were collected pretransplantation and differentially expressed
proteins were identified by
SELDI-TOF-MS. The intensity values for each peak were analyzed by
Biomarker Wizard
Software to screen
serum proteome biomarkers related to the
recurrence post-
transplantation. By using
Biomarker Patterns
Software, the
classification trees were generate. from randomly selected samples (30
fingerprints obtained from each group). The
sensitivity and specificity of best
decision tree were then chosen for blind test with 16 samples (5 from
recurrence individuals and 11 from
recurrence-free
survival patients). Results There were significant differences only in
tumor size and the presence of vascular invasion between
recurrence group and
recurrence-free
survival group (P<0.05). According to
serum protein fingerprints, a total of 368
protein peaks were identified at the mass-to-
charge ratio (M/Z) value ranging from 2000 to 300 00. There were 22 significant differential
proteins between two groups. Among them, 9
proteins were up-regulated and 13
proteins were down-regulated -espectively in
recurrence group. The intensity values of differential
proteins were input into BPS for
classification tree analysis and the best performing
tree could distinguish two groups successfully. As a result of blind assessment for this model,a
sensitivity of 80.0 % (4/5) and
specificity of 72.7 % (8/11) were obtained. Conclusion Some of differential
proteins screened by
SELDI-TOF-MS technique in the
serum may be correlated with the
prognoses of
liver transplantation patients with HCC. The
decision tree may be useful for the clinical application of formulating the indication for
liver transplantation, detecting extrahepatic
micrometastasis and setting up the diagnostic and
treatment strategies.