Screening and Identification of Potential Biomarkers for Hepatocellular Carcinoma: An Analysis of TCGA Database and Clinical Validation
| Autor: | Rongping Luo, Ao Guo, Kun Wang, Junzi Ke, Yujuan Zhan, Xianli Wei, Cong Mai, Haonan Huang, Hang Wei, Jianyong Xiao, Shikun Zhou, Bonan Chen, Weizhen Ao, Fuda Xie |
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| Rok vydání: | 2020 |
| Předmět: |
0301 basic medicine
Candidate gene medicine.diagnostic_test Database Biology Immunofluorescence computer.software_genre medicine.disease digestive system diseases 03 medical and health sciences 030104 developmental biology 0302 clinical medicine Oncology 030220 oncology & carcinogenesis Hepatocellular carcinoma Cancer cell medicine Immunohistochemistry KEGG Gene computer Survival analysis |
| Zdroj: | Cancer Management and Research. 12:1991-2000 |
| ISSN: | 1179-1322 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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