Abstract
Hepatocellular carcinoma (HCC) is one of the most common and aggressive cancers and is associated with a poor survival rate. Clinically, the level of alpha-fetoprotein (AFP) has been used as a biomarker for the diagnosis of HCC. The discovery of useful biomarkers for HCC, focused solely on the proteome, has been difficult; thus, wide-ranging global data mining of genomic and proteomic databases from previous reports would be valuable in screening biomarker candidates. Further, multiple reaction monitoring (MRM), based on triple quadrupole mass spectrometry, has been effective with regard to high-throughput verification, complementing antibody-based verification pipelines. In this study, global data mining was performed using 5 types of HCC data to screen for candidate biomarker proteins: cDNA microarray, copy number variation, somatic mutation, epigenetic, and quantitative proteomics data. Next, we applied MRM to verify HCC candidate biomarkers in individual serum samples from 3 groups: a healthy control group, patients who have been diagnosed with HCC (Before HCC treatment group), and HCC patients who underwent locoregional therapy (After HCC treatment group). After determining the relative quantities of the candidate proteins by MRM, we compared their expression levels between the 3 groups, identifying 4 potential biomarkers: the actin-binding protein anillin (ANLN), filamin-B (FLNB), complementary C4-A (C4A), and AFP. The combination of 2 markers (ANLN, FLNB) improved the discrimination of the before HCC treatment group from the healthy control group compared with AFP. We conclude that the combination of global data mining and MRM verification enhances the screening and verification of potential HCC biomarkers. This efficacious integrative strategy is applicable to the development of markers for cancer and other diseases.
Highlights
Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide and the third leading cancer-related cause of death [1]
Since many HCCs are asymptomatic before the development of end stage disease, regular surveillance for HCC is mandatory for patients with chronic hepatitis or cirrhosis to detect a tumor at an early stage and to improve patients’ outcomes after curative treatment [2]
It is important to obtain a wide range of candidate proteins in the biomarker discovery stage, because most candidates fail to be verified in a large number of clinical samples
Summary
Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide and the third leading cancer-related cause of death [1]. Most practice guidelines recommend routine surveillance for HCC using ultrasonography and serum tumor markers, such as alpha-fetoprotein (AFP). [3,4,5] the use of AFP as a single biomarker for HCC is challenging due to its limited specificity and sensitivity. Tumor biomarkers are defined as substances that reflect current cancer status or predict its future characteristics. Biomarkers are potentially useful for screening cancers and determining their prognosis, predicting therapeutic efficacy [6]. The most commonly used serum marker of HCC is AFP, which has a reported sensitivity of 39% to 65% and specificity of 65% to 94%; approximately one-third of early-stage HCC patients with small tumors (,3 cm) have normal levels of AFP [2,7]. There is an urgent clinical need to identify new biomarkers that classify HCC more accurately
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