Screening and Identification of Potential Biomarkers for Hepatocellular Carcinoma: An Analysis of TCGA Database and Clinical Validation
Received 23 November 2019
Accepted for publication 20 February 2020
Published 17 March 2020 Volume 2020:12 Pages 1991—2000
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Seema Singh
Xianli Wei,1,* Junzi Ke,2,3,* Haonan Huang,2,3,* Shikun Zhou,2,3 Ao Guo,4 Kun Wang,2,3 Yujuan Zhan,2,3 Cong Mai,5 Weizhen Ao,3 Fuda Xie,6,7 Rongping Luo,8 Jianyong Xiao,2 Hang Wei,4 Bonan Chen2,3
1Department of Medical Instruments, Guangdong Food and Drug Vocational College, Guangzhou 510520, People’s Republic of China; 2Department of Biochemistry, Guangzhou University of Chinese Medicine, Guangzhou 510006, People’s Republic of China; 3Research Center of Integrative Medicine, School of Basic Medicine, Guangzhou University of Chinese Medicine, Guangzhou 510006, People’s Republic of China; 4School of Medical Information Engineering, Guangzhou University of Chinese Medicine, Guangzhou, People’s Republic of China; 5Department of Abdominal Surgery, Cancer Center of Guangzhou Medical University, Guangzhou 510095, People’s Republic of China; 6The Second Clinical College, Guangzhou University of Chinese Medicine, Guangzhou 510006, People’s Republic of China; 7Guangdong Provincial Academy of Chinese Medical Sciences, Guangzhou 510006, People’s Republic of China; 8School of Foreign Language, Guangdong Pharmaceutical University, Guangzhou 510006, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Bonan Chen; Hang Wei Email email@example.com; firstname.lastname@example.org
Introduction: Hepatocellular carcinoma (HCC) is the fifth most common cancer in the world. Up to now, many genes associated with HCC have not yet been identified. In this study, we screened the HCC-related genes through the integrated analysis of the TCGA database, of which the potential biomarkers were also further validated by clinical specimens. The discovery of potential biomarkers for HCC provides more opportunities for diagnostic indicators or gene-targeted therapies.
Methods: Cancer-related genes in The Cancer Genome Atlas (TCGA) HCC database were screened by a random forest (RF) classifier based on the RF algorithm. Proteins encoded by the candidate genes and other associated proteins obtained via protein–protein interaction (PPI) analysis were subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The newly identified genes were further validated in the HCC cell lines and clinical tissue specimens by Western blotting, immunofluorescence, and immunohistochemistry (IHC). Survival analysis verified the clinical value of genes.
Results: Ten genes with the best feature importance in the RF classifier were screened as candidate genes. By comprehensive analysis of PPI, GO and KEGG, these genes were confirmed to be closely related to HCC tumors. Representative NOX4 and FLVCR1 were selected for further validation by biochemical analysis which showed upregulation in both cancer cell lines and clinical tumor tissues. High expression of NOX4 or FLVCR1 in cancer cells predicts low survival.
Conclusion: Herein, we report that NOX4 and FLVCR1 are promising biomarkers for HCC that may be used as diagnostic indicators or therapeutic targets.
Keywords: hepatocellular carcinoma, biomarkers, TCGA database, NOX4, FLVCR1
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