Urine α-fetoprotein and orosomucoid 1 as biomarkers of hepatitis B virus-associated hepatocellular carcinoma

Abstract

Hepatocellular carcinoma (HCC) is the sixth common malignant tumor worldwide, but current efficient and convenient screening methods remain lacking. This study aimed to discover a diagnostic or a screening biomarker from the urine of hepatitis B virus (HBV)-related HCC patients. We used iTRAQ coupled with mass spectrometry to identify candidate urinary proteins in a discovery cohort (n = 40). The selected proteins were confirmed using ELISA in a validation cohort (n = 140). Diagnostic performance of the selected proteins was assessed using receiver operating characteristic (ROC) and qualitative diagnostic analysis. A total of 96 differentially expressed proteins were identified. Urinary α-fetoprotein (u-AFP) and orosomucoid 1 (u-ORM1) were selected as target proteins by bioinformatics analysis and were significantly higher in HCC than in non-HCC patients, as validated by Western blot analysis and ELISA. u-AFP had a strong correlation with serum AFP-L3 (Pearson’s r = 0.944, P < 0.0001), indicating that u-AFP may be derived from circulating blood. The area under the curve (AUC) of u-AFP was 0.795 with a sensitivity of 62.5% and a specificity of 95.4%, which showed no significantly difference with serum AFP (se-AFP). The AUC was 0.864 as u-AFP and u-ORM1 were combined, and they performed much better than u-AFP or u-ORM1 alone. Qualitative diagnostic analysis showed that the positive predictive value of u-AFP was 90.1% and the diagnostic sensitivity of parallel combination of u-AFP and u-ORM1 was 85.1%. Taken together, AFP and ORM1 in the urine may be used as a diagnostic or screening biomarker of HCC, and studies on large samples are needed to validate the result. NEW & NOTEWORTHY This study provides a novel way to find biomarkers of hepatocellular carcinoma (HCC) and a new perspective of α-fetoprotein clinical application. The urine reagent strips may be helpful in high epidemic areas of HCC and in low-resource settings.