Serum peptidome patterns of hepatocellular carcinoma based on magnetic bead separation and mass spectrometry analysis

Abstract

Background/Aims: The only hope for a cure from hepatocellular carcinoma (HCC) rests on early diagnosis. The present study aims to determine serum peptidome patterns for early diagnosis of HCC. Materials and Methods: To identify novel peptidome patterns for diagnosing HCC, serum from31 healthy volunteers and 32 HCC patients were subjected to a comparative proteomic analysis using a ClinProt Kit combined with mass spectrometry (MS). This approach allows the determination of peptidome patterns that are able to differentiate the HCC from healthy volunteers. For further validation, the diagnostic and differential diagnostic capabilities of the peptidome patterns were verified blindly by an independent group of sera consisted of 31 HCC, 23 liver fibrosis and 33 healthy volunteers. Results: A Quick Classifier Algorithm was used to construct the peptidome patterns for the identification of HCC from the control samples. One of the identified peaks at m/z 7771 was used to construct the peptidome patterns with almost 100% accuracy. Furthermore, the peptidome patterns could also differentiate the validation group with high accuracy. Conclusion: These results suggest that the ClinProt Kit combined with MS achieves significantly high accuracy for HCC diagnosis and differential diagnosis.