A strategy for the comparative analysis of serum proteomes for the discovery of biomarkers for hepatocellular carcinoma.
Abstract
Many of the emerging technologies for the global evaluation of gene expression, at both the RNA and protein level, are being applied to the problem of finding biomarkers for human disease progression. These analyses can be made difficult, however, by variation between samples that arises from both technical and nondisease related physiological or genetic causes. In an effort to identify serum polypeptides whose presence or absence correlates with the clinical status of patients at high risk for hepatocellular carcinoma (HCC), we have developed a strategy that helps to focus the analysis on meaningful changes in protein levels above the background of variation. For the current study we divided the patient population into four clinically defined diagnostic groups that represent a generally increasing risk for HCC. Chronic infection with hepatitis B virus (HBV) is a major risk factor for HCC and our groups included patients with no indication of liver disease (healthy), those with inactive chronic HBV, those with active chronic HBV, and patients with a diagnosis of HCC and history of chronic HBV infection. Serum polypeptides from these patients were first analyzed in two-dimensional gels by combining the serum from patients in each of the four groups to generate composite gel profiles. Analysis of these composite gels allowed us to identify two relatively abundant features that were reduced in the HCC group as compared to the healthy group. Tryptic fragment mass fingerprinting identified the features as a carboxy terminal fragment of complement C3 and an isoform of apolipoprotein A1. These two features were examined by two-dimensional gel electrophoresis of serum from each individual in the four groups in order to verify that the inter-group differences seen in composite gels reported changes in abundance for most members of the group, rather than extreme changes for a small fraction of the group. These preliminary studies suggest that a proteomic methodology can be used for the identification of serum biomarkers for HCC and other liver disease.
EDRN PI Authors
Medline Author List
- Block TM
- Dwek R
- Evans AA
- London WT
- Seeholzer SH
- Shumpert D
- Steel LF
- Trotter M