Genome-wide expression changes mediated by A-to-I RNA editing correlate with hepatic oncogenesis

A Comprehensive Evaluation of the Effects of RNA-Editing Proteins ADAR and ADARB1 on the Expression of the Drug-Metabolizing Enzymes in HepaRG Cells

Two RNA-editing proteins, the adenosine deaminase acting on RNA, ADAR, and ADARB1, broadly regulate gene expression in editing-dependent and editing-independent manners. Previous studies showed that the expression of the drug-metabolizing cytochrome P450s (P450s) and UDP glucuronosyltransferases (UGTs) changes upon knockdown (KD) of ADAR or ADARB1 in different hepatic cell lines. To systematically survey the effects of these two ADARs on the expression of P450s and UGTs, we used small interfering RNA in HepaRG cells and tested the association between the expression of the P450s and ADARs in a liver sample cohort (n = 246). KD of ADAR increased the expression of the CYP3As and CYP2C9 and reduced the expression of the others, whereas KD of ADARB1 reduced the expression of nearly all genes tested. ADAR KD also suppressed the induction of most P450s, whereas ADARB1 KD had mixed effects depending on the inducer/gene combination. P450 expression was positively associated with both ADARs in liver samples, consistent with the KD results. However, after adjusting for the expression of transcription factors (TFs) known to regulate P450 expression, the associations disappeared, indicating that the effects of ADAR or ADARB1 primarily occur through TFs. Moreover, we found that the expression of normally spliced CYP3A5 transcripts is increased in both KDs, indicating a direct effect of the ADARs on promoting the usage of the cryptic splice site generated by CYP3A5*3. Taken together, our results revealed the nonoverlapping regulatory effects of ADAR and ADARB1 and supported their broad roles in controlling the expression of drug-metabolizing enzymes in the liver. SIGNIFICANCE STATEMENT: Here, this study systematically surveyed the roles of ADAR and ADARB1 in both basal and induced expression of drug-metabolizing enzymes and assessed their coexpression in liver samples. This study's results support that ADAR and ADARB1 regulate the expression of the drug-metabolizing enzymes in the liver, suggesting that factors affecting ADAR expression also have the potential to impact drug metabolism.

Neoantigens: promising targets for cancer therapy

Recent advances in neoantigen research have accelerated the development and regulatory approval of tumor immunotherapies, including cancer vaccines, adoptive cell therapy and antibody-based therapies, especially for solid tumors. Neoantigens are newly formed antigens generated by tumor cells as a result of various tumor-specific alterations, such as genomic mutation, dysregulated RNA splicing, disordered post-translational modification, and integrated viral open reading frames. Neoantigens are recognized as non-self and trigger an immune response that is not subject to central and peripheral tolerance. The quick identification and prediction of tumor-specific neoantigens have been made possible by the advanced development of next-generation sequencing and bioinformatic technologies. Compared to tumor-associated antigens, the highly immunogenic and tumor-specific neoantigens provide emerging targets for personalized cancer immunotherapies, and serve as prospective predictors for tumor survival prognosis and immune checkpoint blockade responses. The development of cancer therapies will be aided by understanding the mechanism underlying neoantigen-induced anti-tumor immune response and by streamlining the process of neoantigen-based immunotherapies. This review provides an overview on the identification and characterization of neoantigens and outlines the clinical applications of prospective immunotherapeutic strategies based on neoantigens. We also explore their current status, inherent challenges, and clinical translation potential.

Hepatitis B virus (HBV) codon adapts well to the gene expression profile of liver cancer: an evolutionary explanation for HBV's oncogenic role

Due to the evolutionary arms race between hosts and viruses, viruses must adapt to host translation systems to rapidly synthesize viral proteins. Highly expressed genes in hosts have a codon bias related to tRNA abundance, the primary RNA translation rate determinant. We calculated the relative synonymous codon usage (RSCU) of three hepatitis viruses (HAV, HBV, and HCV), SARS-CoV-2, 30 human tissues, and hepatocellular carcinoma (HCC). After comparing RSCU between viruses and human tissues, we calculated the codon adaptation index (CAI) of viral and human genes. HBV and HCV showed the highest correlations with HCC and the normal liver, while SARS-CoV-2 had the strongest association with lungs. In addition, based on HCC RSCU, the CAI of HBV and HCV genes was the highest. HBV and HCV preferentially adapt to the tRNA pool in HCC, facilitating viral RNA translation. After an initial trigger, rapid HBV/HCV translation and replication may change normal liver cells into HCC cells. Our findings reveal a novel perspective on virus-mediated oncogenesis.

Unifying Different Cancer Theories in a Unique Tumour Model: Chronic Inflammation and Deaminases as Meeting Points

The increase in cancer incidences shows that there is a need to better understand tumour heterogeneity to achieve efficient treatments. Interestingly, there are several common features among almost all types of cancers, with chronic inflammation induction and deaminase dysfunctions singled out. Deaminases are a family of enzymes with nucleotide-editing capacity, which are classified into two main groups: DNA-based and RNA-based. Remarkably, a close relationship between inflammation and the dysregulation of these molecules has been widely documented, which may explain the characteristic intratumor heterogeneity, both at DNA and transcriptional levels. Indeed, heterogeneity in cancer makes it difficult to establish a unique tumour progression model. Currently, there are three main cancer models—stochastic, hierarchic, and dynamic—although there is no consensus on which one better resembles cancer biology because they are usually overly simplified. Here, to accurately explain tumour progression, we propose interactions among chronic inflammation, deaminases dysregulation, intratumor genetic heterogeneity, cancer phenotypic plasticity, and even the previously proposed appearance of cancer stem-like cell populations in the edges of advanced solid tumour masses (instead of being the cells of origin of primary malignancies). The new tumour development model proposed in this study does not contradict previously accepted models and it may open up a window to interesting therapeutic approaches.