Identification of FOS as a Candidate Risk Gene for Liver Cancer by Integrated Bioinformatic Analysis

17Citations
Citations of this article
7Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Liver cancer is a lethal disease that is associated with poor prognosis. In order to identify the functionally important genes associated with liver cancer that may reveal novel therapeutic avenues, we performed integrated analysis to profile miRNA and mRNA expression levels for liver tumors compared to normal samples in The Cancer Genome Atlas (TCGA) database. We identified 405 differentially expressed genes and 233 differentially expressed miRNAs in tumor samples compared with controls. In addition, we also performed the pathway analysis and found that mitogen-activated protein kinases (MAPKs) and G-protein coupled receptor (GPCR) pathway were two of the top significant pathway nodes dysregulated in liver cancer. Furthermore, by examining these signaling networks, we discovered that FOS (Fos proto-oncogene, AP-1 transcription factor subunit), LAMC2 (laminin subunit gamma 2), and CALML3 (calmodulin like 3) were the most significant gene nodes with high degrees involved in liver cancer. The expression and disease prediction accuracy of FOS, LAMC2, CALML3, and their interacting miRNAs were further performed using a HCC cohort. Finally, we investigated the prognostic significance of FOS in another HCC cohort. Patients with higher FOS expression displayed significantly shorter time to recurrence (TTR) and overall survival (OS) compared with patients with lower expression. Collectively, our study demonstrates that FOS is a potential prognostic marker for liver cancer that may reveal a novel therapeutic avenue in this lethal disease.

Cite

CITATION STYLE

APA

Hu, J. W., Ding, G. Y., Fu, P. Y., Tang, W. G., Sun, Q. M., Zhu, X. D., … Huang, C. (2020). Identification of FOS as a Candidate Risk Gene for Liver Cancer by Integrated Bioinformatic Analysis. BioMed Research International, 2020. https://doi.org/10.1155/2020/6784138

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free