Identification of CD14 as a potential biomarker of hepatocellular carcinoma using iTRAQ quantitative proteomics
Metrics: PDF 859 views | HTML 1881 views | ?
Jiao Guo1,*, Rui Jing1,2,*, Jian-Hong Zhong3,*, Xin Dong1,4, Yun-Xi Li5, Yin-Kun Liu6, Tian-Ren Huang1 and Chun-Yan Zhang1
1Experimental Department, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, Guangxi, PR China
2Hematology Department, Affiliated Hospital of Binzhou Medical University, Yantai, Shandong, PR China
3Hepatobiliary Surgery Department, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, Guangxi, PR China
4Oncology Department, Affiliated Hospital of Binzhou Medical University, Yantai, Shandong, PR China
5Cancer Registry Department, People’s Hospital of Fusui County, Fusui, Guangxi, PR China
6Liver Cancer Institute, Zhongshan Hospital, Fudan University, Yangpu, Shanghai, PR China
*These authors have contributed equally to this work
Chun-Yan Zhang, email: firstname.lastname@example.org
Tian-Ren Huang, email: email@example.com
Yin-Kun Liu, email: firstname.lastname@example.org
Keywords: hepatocellular carcinoma (HCC), diagnosis, biomarker, iTRAQ, CD14
Received: March 26, 2017 Accepted: May 14, 2017 Published: June 28, 2017
Hepatocellular carcinoma (HCC) is one of the most common malignant tumors without effective diagnostic biomarkers. This study intended to dynamically analyze serum proteomics in different pathological stages of liver diseases, and discover potential diagnostic biomarkers for early HCC. Patients with hepatitis B virus (HBV) infection, liver cirrhosis (LC), or HCC together with healthy controls (HC) were enrolled. Proteins differentially expressed between groups were screened using isobaric tagging for relative and absolute quantitation (iTRAQ), and promising HCC biomarker candidates were subjected to bioinformatics analysis, including K-means clustering, gene ontology (GO) and string network analysis. Potential biomarkers were validated by Western blotting and enzyme-linked immunosorbent assay (ELISA), and their diagnostic performance was evaluated using receiver operating characteristic (ROC) curve analysis. Finally, 93 differentially expressed proteins were identified, of which 43 differed between HBV and HC, 70 between LC and HC, and 51 between HCC and HC. Expression levels of gelsolin (GELS) and sulfhydryl oxidase 1 (QSOX1) varied with disease state as follows: HC < HBV < LC < HCC. The reverse trend was observed with CD14. These iTRAQ results were confirmed by Western blotting and ELISA. Logistic regression and ROC curve analysis identified the optimal cut-off for alpha-fetoprotein (AFP), CD14 and AFP/CD14 was 191.4 ng/mL (AUC 0.646, 95%CI 0.467-0.825, sensitivity 31.6%, specificity 94.4%), 3.16 ng/mL (AUC 0.760, 95%CI 0.604-0.917, sensitivity 94.7%, specificity 50%) and 0.197 ng/mL (AUC 0.889, 95%CI 0.785-0.993, sensitivity 84.2%, specificity 83.3%) respectively. In conclusion, Assaying CD14 levels may complement AFP measurement for early detection of HCC.
All site content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 License.