METTL3 is frequently up-regulated in human HCC and contributes to HCC progression. METTL3 represses SOCS2 expression in HCC through an m6A-YTHDF2-dependent mechanism. Our findings suggest an important mechanism of epigenetic alteration in liver carcinogenesis. (Hepatology 2018;67:2254-2270).
Liver cancer is a common cancer worldwide. Although the etiological factors of liver carcinogenesis are well defined, the underlying molecular mechanisms remain largely elusive. Epigenetic deregulations, such as aberrant DNA methylation and histone modifications, play a critical role in liver carcinogenesis. Analogous to DNA and core histone proteins, reversible chemical modifications on mRNA have recently been recognized as important regulatory mechanisms to control gene expression. N6-methyladenosine (m6A) is the most prevalent internal mRNA modification in mammalian cells. m6A modification is important for controlling many cellular and biological processes. Deregulation of m6A modification has been recently implicated in human carcinogenesis, including liver cancer. In this review, we summarize the recent findings on m6A regulation and its biological impacts in normal and cancer cells. We will focus on the deregulation of m6A modification and m6A regulators in liver diseases and liver cancers. We will highlight the clinical relevance of m6A deregulation in liver cancer. We will also discuss the potential of exploiting m6A modification for cancer diagnosis and therapeutics.
Hypoxia is commonly found in cancers. Hypoxia, due to the lack of oxygen (O2) as the electron recipient, causes inefficient electron transfer through the electron transport chain at the mitochondria leading to accumulation of reactive oxygen species (ROS) which could create irreversible cellular damages. Through hypoxia-inducible factor 1 (HIF-1) which elicits various molecular events, cells are able to overcome low O2. Knowledge about the new molecular mechanisms governed by HIF-1 is important for new therapeutic interventions targeting hypoxic tumors. Using hepatocellular carcinoma (HCC) as a model, we revealed that the HIF-1 and the Notch signaling pathways cross-talk to control mitochondrial biogenesis of cancer cells to maintain REDOX balance. From transcriptome sequencing, we found that HEY1, a transcriptional repressor, in the NOTCH pathway was consistently induced by hypoxia in HCC cell lines. We identified a strong hypoxia response element (HRE) in HEY1 by chromatin immunoprecipitation (ChIP) and luciferase reporter assays. Transcriptome and ChIP sequencing further identified PINK1, a gene essential for mitochondrial biogenesis, as a novel transcriptional target of HEY1. HCC cells with HEY1 knockdown re-expressed PINK1. HEY1 and PINK1 expressions inversely correlated in human HCC samples. Overexpression of HEY1 and under-expression of PINK1 were detected in human HCC and associated with poor clinical outcomes. Functionally, we found that overexpression of HEY1 or knockdown of PINK1 consistently reduced mitochondrial cristae, mitochondrial mass, oxidative stress level, and increased HCC growth.
Pharmacologic perturbation projects, such as Connectivity Map (CMap) and Library of Integrated Network-based Cellular Signatures (LINCS), have produced many perturbed expression data, providing enormous opportunities for computational therapeutic discovery. However, there is no consensus on which methodologies and parameters are the most optimal to conduct such analysis. Aiming to fill this gap, new benchmarking standards were developed to quantitatively evaluate drug retrieval performance. Investigations of potential factors influencing drug retrieval were conducted based on these standards. As a result, we determined an optimal approach for LINCS data-based therapeutic discovery. With this approach, homoharringtonine (HHT) was identified to be a candidate agent with potential therapeutic and preventive effects on liver cancer. The antitumor and antifibrotic activity of HHT was validated experimentally using subcutaneous xenograft tumor model and carbon tetrachloride (CCL4)-induced liver fibrosis model, demonstrating the reliability of the prediction results. In summary, our findings will not only impact the future applications of LINCS data but also offer new opportunities for therapeutic intervention of liver cancer.
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