PURPOSE: More than 60% of patients with hepatocellular carcinoma (HCC) do not receive curative therapy as a result of late clinical presentation and diagnosis. We aimed to identify plasma microRNAs for diagnosing hepatitis B virus (HBV) -related HCC. PATIENTS AND METHODS: Plasma microRNA expression was investigated with three independent cohorts including 934 participants (healthy, chronic hepatitis B, cirrhosis, and HBV-related HCC), recruited between August 2008 and June 2010. First, we used microarray to screen 723 microRNAs in 137 plasma samples for diagnosing HCC. Quantitative reverse-transcriptase polymerase chain reaction assay was then applied to evaluate the expression of selected microRNAs. A logistic regression model was constructed using a training cohort (n = 407) and then validated using an independent cohort (n = 390). Area under the receiver operating characteristic curve (AUC) was used to evaluate diagnostic accuracy. RESULTS: We identified a microRNA panel (miR-122, miR-192, miR-21, miR-223, miR-26a, miR-27a and miR-801) that provided a high diagnostic accuracy of HCC (AUC = 0.864 and 0.888 for training and validation data set, respectively). The satisfactory diagnostic performance of the microRNA panel persisted regardless of disease status (AUCs for Barcelona Clinic Liver Cancer stages 0, A, B, and C were 0.888, 0.888, 0.901, and 0.881, respectively). The microRNA panel can also differentiate HCC from healthy (AUC = 0.941), chronic hepatitis B (AUC = 0.842), and cirrhosis (AUC = 0.884), respectively. CONCLUSION: We found a plasma microRNA panel that has considerable clinical value in diagnosing early-stage HCC. Thus, patients who would have otherwise missed the curative treatment window can benefit from optimal therapy.
PURPOSE: More than 60% of patients with hepatocellular carcinoma (HCC) do not receive curative therapy as a result of late clinical presentation and diagnosis. We aimed to identify plasma microRNAs for diagnosing hepatitis B virus (HBV) -related HCC. PATIENTS AND METHODS: Plasma microRNA expression was investigated with three independent cohorts including 934 participants (healthy, chronic hepatitis B, cirrhosis, and HBV-related HCC), recruited between August 2008 and June 2010. First, we used microarray to screen 723 microRNAs in 137 plasma samples for diagnosing HCC. Quantitative reverse-transcriptase polymerase chain reaction assay was then applied to evaluate the expression of selected microRNAs. A logistic regression model was constructed using a training cohort (n = 407) and then validated using an independent cohort (n = 390). Area under the receiver operating characteristic curve (AUC) was used to evaluate diagnostic accuracy. RESULTS: We identified a microRNA panel (miR-122, miR-192, miR-21, miR-223, miR-26a, miR-27a and miR-801) that provided a high diagnostic accuracy of HCC (AUC = 0.864 and 0.888 for training and validation data set, respectively). The satisfactory diagnostic performance of the microRNA panel persisted regardless of disease status (AUCs for Barcelona Clinic Liver Cancer stages 0, A, B, and C were 0.888, 0.888, 0.901, and 0.881, respectively). The microRNA panel can also differentiate HCC from healthy (AUC = 0.941), chronic hepatitis B (AUC = 0.842), and cirrhosis (AUC = 0.884), respectively. CONCLUSION: We found a plasma microRNA panel that has considerable clinical value in diagnosing early-stage HCC. Thus, patients who would have otherwise missed the curative treatment window can benefit from optimal therapy.
Authors: Mukesh Verma; Scott Rogers; Rao L Divi; Sheri D Schully; Stefanie Nelson; L Joseph Su; Sharon A Ross; Susan Pilch; Deborah M Winn; Muin J Khoury Journal: Cancer Epidemiol Biomarkers Prev Date: 2013-12-10 Impact factor: 4.254