Ming Shi1, Min-Shan Chen1, Karthik Sekar2, Chee-Kiat Tan3, London Lucien Ooi4, Kam M Hui5. 1. Department of Hepatobiliary Oncology, Sun Yat-Sen University Cancer Center, Guangzhou 510060, PR China. 2. Division of Cellular and Molecular Research, Humphrey Oei Institute of Cancer Research, National Cancer Centre, Singapore 169610, Singapore. 3. Department of Gastroenterology and Hepatology, Singapore General Hospital, Singapore 169608, Singapore. 4. Division of Surgical Oncology, National Cancer Centre, Singapore 169610, Singapore. 5. Division of Cellular and Molecular Research, Humphrey Oei Institute of Cancer Research, National Cancer Centre, Singapore 169610, Singapore; Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore; Institute of Molecular and Cell Biology, A(∗)STAR, Biopolis Drive Proteos, Singapore 138673, Singapore; Program in Cancer and Stem Cell Biology, Duke-NUS Graduate Medical School, Singapore 169857, Singapore. Electronic address: cmrhkm@nccs.com.sg.
Abstract
BACKGROUND: Identifying early stages of disease in high-risk individuals for the development of hepatocellular carcinoma (HCC) would greatly improve the clinical outcomes of these individuals. The aim of this study was to develop a blood-based gene set that could identify early-stage HCC. METHODS: Comprehensive gene expression profiling of purified RNA of peripheral blood mononuclear cells (PBMC) was performed using microarrays. Gene signatures were developed through bioinformatics-driven approaches and their diagnostic value was evaluated by custom-designed, quantitative, multiplex polymerase chain reaction (PCR) assays. RESULTS: Bioinformatics-driven analysis of microarray data derived from PBMC RNA samples of patients with HCC (N=10), pancreatic cancer (N=3), gastric cancer (N=3) and 10 normal individuals identified six genes that were differentially expressed in HCC. Subsequent multiplex-PCR validation and univariate analyses performed with an independent cohort of 114 HCC patients, 48 normal individuals and 14 patients with chronic hepatitis B (CHB) validated that three genes, namely Chemokine (C-X-C motif) receptor 2 (CXCR2), C-C chemokine receptor type 2 (CCR2) and E1A-Binding Protein P400 (EP400), were able to identify HCC individually with accuracies of 82.4%, 78.4% and 65%, respectively. In combination, these three genes gave an area under the curve (AUC) of 0.96 (95% confidence interval (CI), 0.93-0.99) using multivariate logistic regression and yielded a sensitivity of 93% and a specificity of 89%. When these three genes were used in combination with alpha-fetoprotein (AFP) to predict HCC, the accuracy of predicting HCC improved slightly with an AUC of 0.99 (95% CI, 0.98-1.0), sensitivity of 93% and specificity of 95%. CONCLUSIONS: CXCR2, CCR2 and EP400 can provide a promising non-invasive multiplex PCR diagnostic assay to monitor high-risk individuals for the development of HCC.
BACKGROUND: Identifying early stages of disease in high-risk individuals for the development of hepatocellular carcinoma (HCC) would greatly improve the clinical outcomes of these individuals. The aim of this study was to develop a blood-based gene set that could identify early-stage HCC. METHODS: Comprehensive gene expression profiling of purified RNA of peripheral blood mononuclear cells (PBMC) was performed using microarrays. Gene signatures were developed through bioinformatics-driven approaches and their diagnostic value was evaluated by custom-designed, quantitative, multiplex polymerase chain reaction (PCR) assays. RESULTS: Bioinformatics-driven analysis of microarray data derived from PBMC RNA samples of patients with HCC (N=10), pancreatic cancer (N=3), gastric cancer (N=3) and 10 normal individuals identified six genes that were differentially expressed in HCC. Subsequent multiplex-PCR validation and univariate analyses performed with an independent cohort of 114 HCC patients, 48 normal individuals and 14 patients with chronic hepatitis B (CHB) validated that three genes, namely Chemokine (C-X-C motif) receptor 2 (CXCR2), C-C chemokine receptor type 2 (CCR2) and E1A-Binding Protein P400 (EP400), were able to identify HCC individually with accuracies of 82.4%, 78.4% and 65%, respectively. In combination, these three genes gave an area under the curve (AUC) of 0.96 (95% confidence interval (CI), 0.93-0.99) using multivariate logistic regression and yielded a sensitivity of 93% and a specificity of 89%. When these three genes were used in combination with alpha-fetoprotein (AFP) to predict HCC, the accuracy of predicting HCC improved slightly with an AUC of 0.99 (95% CI, 0.98-1.0), sensitivity of 93% and specificity of 95%. CONCLUSIONS:CXCR2, CCR2 and EP400 can provide a promising non-invasive multiplex PCR diagnostic assay to monitor high-risk individuals for the development of HCC.
Authors: Lap Ho; Patricia A Bloom; Joan G Vega; Shrishailam Yemul; Wei Zhao; Libby Ward; Evan Savage; Robert Rooney; Divyen H Patel; Giulio Maria Pasinetti Journal: Neuromolecular Med Date: 2016-03-17 Impact factor: 3.843
Authors: Francesco Bellissimo; Marilia Rita Pinzone; Bruno Cacopardo; Giuseppe Nunnari Journal: World J Gastroenterol Date: 2015-11-14 Impact factor: 5.742