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Serum Proteomics and Biomarkers in Hepatocellular Carcinoma and Chronic Liver Disease

Authors' Affiliations: ¹ Liver Center, Department of Gastroenterology and Hepatology, ² BIDMC Genomics Center and Dana-Farber/Harvard Cancer Center Proteomics Core, and ³ Division of Signal Transduction, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts

Requests for reprints: Nezam H. Afdhal, BIDMC Genomics Center, Beth Israel Deaconess Medical Center and Harvard Medical School, Harvard Institutes of Medicine, 110 Francis Street, Suite 8e, Boston, MA 02115. Phone: 617-632-1069; Fax: 617-632-1065; E-mail: nafdhal{at}bidmc.harvard.edu.

Purpose: Proteomic profiling using surface enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF MS) enables the identification of biomarkers for cancer. We evaluated the sensitivity and specificity of SELDI-TOF MS for detection of established hepatocellular cancer (HCC) and compared it against -fetoprotein (AFP), Lens culinaris agglutinin–reactive AFP (AFP-L3), and prothrombin induced by vitamin K absence-II (PIVKA-II).

Experimental Design: Forty-one patients with HCC and 51 patients with hepatitis C cirrhosis were enrolled. Serum was analyzed by SELDI-TOF MS using three Ciphergen protein array types.

Results: An 11-peak algorithm for HCC detection was identified. Using the AFP cutoff of 20 ng/mL, the sensitivity was 73% and the specificity was 71%. Using the AFP-L3 cutoff of 10% yielded a sensitivity of 63% and a specificity of 94%. Using the PIVKA-II cutoff of 125 milliabsorbance units (mAU), the sensitivity was 84% and the specificity was 69%. Overall, the sensitivity and specificity of SELDI-TOF MS for HCC were 79% and 86%, respectively. In multivariate analysis, the 11-peak SELDI profile was predictive of HCC independent of AFP, PIVKA, and AFP-L3. Among eight patients with the largest tumor size of <2 cm, SELDI-TOF MS correctly identified seven whereas AFP, AFP-L3, and PIVKA-II identified only three, one, and one, respectively. One of the 11 peaks in the SELDI-TOF MS 11-peak predictor from SELDI-TOF MS was identified as cystatin C.

Conclusions: SELDI-TOF MS accurately distinguished patients with HCC from those with hepatitis C virus cirrhosis, was more accurate than traditional biomarkers in identifying small tumors, and should be further evaluated.

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				Y. Pei, T. Zhang, V. Renault, and X. Zhang An overview of hepatocellular carcinoma study by omics-based methods Acta Biochim Biophys Sin, January 1, 2009; 41(1): 1 - 15. [Abstract] [Full Text] [PDF]