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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. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "LncRNA MYLK-AS1 facilitates tumor progression and angiogenesis by targeting miR-424-5p/E2F7 axis and activating VEGF R-2 signaling pathway in hepatocellular carcinoma." The correction states that an incorrect additional file was uploaded with the original article, but the correct file has now been processed and uploaded. The correction does not impact the overall findings or conclusions of the article. The document also includes a link to supplementary material and a note from the publisher stating their neutrality regarding jurisdictional claims and institutional affiliations. The authors of the article are Fei Teng, Ju-Xiang Zhang, Qi-Meng Chang, Xu-Bo Wu, Wei-Guo Tang, Jian-Fa Wang, Jin-Feng Feng, Zi-Ping Zhang, and Zhi-Qiu Hu. [Extracted from the article]