TY - JOUR
T1 - Serum proteomics and biomarkers in hepatocellular carcinoma and chronic liver disease
AU - Zinkin, Noah T.
AU - Grall, Franck
AU - Bhaskar, Killimangalam
AU - Otu, Hasan H.
AU - Spentzos, Dimitrios
AU - Kalmowitz, Brett
AU - Wells, Meghan
AU - Guerrero, Manuel
AU - Asara, John M.
AU - Libermann, Towia A.
AU - Afdhal, Nezam H.
N1 - Copyright:
Copyright 2008 Elsevier B.V., All rights reserved.
PY - 2008/1/15
Y1 - 2008/1/15
N2 - 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 α-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-TOFMS 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.
AB - 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 α-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-TOFMS 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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U2 - 10.1158/1078-0432.CCR-07-0586
DO - 10.1158/1078-0432.CCR-07-0586
M3 - Article
C2 - 18223221
AN - SCOPUS:38949145743
VL - 14
SP - 470
EP - 477
JO - Clinical Cancer Research
JF - Clinical Cancer Research
SN - 1078-0432
IS - 2
ER -