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.

Postoperative serum proteomic profiles may predict metastatic relapse in high-risk primary breast cancer patients receiving adjuvant chemotherapy

“…Interestingly, some of the identified biomarkers in our study were found to be modulated by various cancer diseases in other serum-based proteomic studies. Thus, haptoglobin was found upregulated in serum of ovarian, oesophageal and small-cell lung cancer patients (Steel et al, 2003;Ahmed et al, 2004;Bharti et al, 2004), while complement C3 and apolipoprotein A1 (Steel et al, 2003;Zhang et al, 2004) were found downmodulated in liver or ovarian cancer. However, these studies were dedicated to the identification of serum biomarkers associated to cancer diagnosis, rather than prediction of clinical outcome.…”

Classification of cancer types by measuring variants of host response proteins using SELDI serum assays

“…In spite of many efforts to overcome this broad dynamic range problem, most proteomic biomarker discovery studies have nevertheless described relatively abundant host response proteins as candidate biomarkers. 3,4 The host response comprises a cascade of inflammatory signals that can be triggered by very small inciting events, e.g., a localized infection or a small tumor, and that leads to up-and downregulation of a group of circulating proteins often called acute phase reactants. [5][6][7] These proteins are mostly synthesized by the liver and include albumin, transthyretin, retinol binding proteins, clotting proteins, lipoproteins, c-reactive protein and immune mediators, among others.…”

Proteomics for the early detection and treatment of hepatocellular carcinoma

“…Many protein cleavage fragments, including the N-terminal end of glypican-3 (Hippo et al, 2004), the C-terminal end of vitronectin (Paradis et al, 2005), a fragment of complement C3 (Steel et al, 2003) and the N-terminal ends of calreticulin and of PDIA3 (Chignard and Beretta, 2004), have been reported to be specific to HCC. Also reported in HCC were specific isoforms of apolipoprotein A1 (Steel et al, 2003;Fernandez-Irigoyen et al, 2005), variants of aldehyde dehydrogenase isozymes (Park et al, 2002a) and hyperfucosylation of Golgi Protein 73 (Block et al, 2005). It is estimated that there are more than 100 different post-translational modifications (e.g., glycosylation, phosphorylation, oxidation) (Krishna and Wold, 1988;Yang, 2005), although only a few have yet been studied in HCC.…”