EHMT1 protein binds to nuclear factor-κB p50 and represses gene expression.

Transcriptional homeostasis relies on the balance between positive and negative regulation of gene transcription. Methylation of histone H3 lysine 9 (H3K9) is commonly correlated with gene repression. Here, we report that a euchromatic H3K9 methyltransferase, EHMT1, functions as a negative regulator in both the NF-κB- and type I interferon-mediated gene induction pathways. EHMT1 catalyzes H3K9 methylation at promoters of NF-κB target genes. Moreover, EHMT1 interacts with p50, and, surprisingly, p50 appears to repress the expression of type I interferon genes and genes activated by type I interferons by recruiting EHMT1 to catalyze H3K9 methylation at their promoter regions. Silencing the expression of EHMT1 by RNA interference enhances expression of a subset NF-κB-regulated genes, augments interferon production, and augments antiviral immunity.

SPIN-AI: A Deep Learning Model That Identifies Spatially Predictive Genes.

Spatially resolved sequencing technologies help us dissect how cells are organized in space. Several available computational approaches focus on the identification of spatially variable genes (SVGs), genes whose expression patterns vary in space. The detection of SVGs is analogous to the identification of differentially expressed genes and permits us to understand how genes and associated molecular processes are spatially distributed within cellular niches. However, the expression activities of SVGs fail to encode all information inherent in the spatial distribution of cells. Here, we devised a deep learning model, Spatially Informed Artificial Intelligence (SPIN-AI), to identify spatially predictive genes (SPGs), whose expression can predict how cells are organized in space. We used SPIN-AI on spatial transcriptomic data from squamous cell carcinoma (SCC) as a proof of concept. Our results demonstrate that SPGs not only recapitulate the biology of SCC but also identify genes distinct from SVGs. Moreover, we found a substantial number of ribosomal genes that were SPGs but not SVGs. Since SPGs possess the capability to predict spatial cellular organization, we reason that SPGs capture more biologically relevant information for a given cellular niche than SVGs. Thus, SPIN-AI has broad applications for detecting SPGs and uncovering which biological processes play important roles in governing cellular organization.

Gene utility recapitulates chromosomal aberrancies in advanced stage neuroblastoma.

Neuroblastoma (NB) is the most common extracranial solid tumor in children. Although only a few recurrent somatic mutations have been identified, chromosomal abnormalities, including the loss of heterozygosity (LOH) at the chromosome 1p and gains of chromosome 17q, are often seen in the high-risk cases. The biological basis and evolutionary forces that drive such genetic abnormalities remain enigmatic. Here, we conceptualize the Gene Utility Model (GUM) that seeks to identify genes driving biological signaling via their collective gene utilities and apply it to understand the impact of those differentially utilized genes on constraining the evolution of NB karyotypes. By employing a computational process-guided flow algorithm to model gene utility in protein-protein networks that built based on transcriptomic data, we conducted several pairwise comparative analyses to uncover genes with differential utilities in stage 4 NBs with distinct classification. We then constructed a utility karyotype by mapping these differentially utilized genes to their respective chromosomal loci. Intriguingly, hotspots of the utility karyotype, to certain extent, can consistently recapitulate the major chromosomal abnormalities of NBs and also provides clues to yet identified predisposition sites. Hence, our study not only provides a new look, from a gene utility perspective, into the known chromosomal abnormalities detected by integrative genomic sequencing efforts, but also offers new insights into the etiology of NB and provides a framework to facilitate the identification of novel therapeutic targets for this devastating childhood cancer.

A Knowledge-Based Discovery Approach Couples Artificial Neural Networks With Weight Engineering to Uncover Immune-Related Processes Underpinning Clinical Traits of Breast Cancer.

Immune-related processes are important in underpinning the properties of clinical traits such as prognosis and drug response in cancer. The possibility to extract knowledge learned by artificial neural networks (ANNs) from omics data to explain cancer clinical traits is a very attractive subject for novel discovery. Recent studies using a version of ANNs called autoencoders revealed their capability to store biologically meaningful information indicating that autoencoders can be utilized as knowledge discovery platforms aside from their initial assigned use for dimensionality reduction. Here, we devise an innovative weight engineering approach and ANN platform called artificial neural network encoder (ANNE) using an autoencoder and apply it to a breast cancer dataset to extract knowledge learned by the autoencoder model that explains clinical traits. Intriguingly, the extracted biological knowledge in the form of gene-gene associations from ANNE shows immune-related components such as chemokines, carbonic anhydrase, and iron metabolism that modulate immune-related processes and the tumor microenvironment play important roles in underpinning breast cancer clinical traits. Our work shows that biological "knowledge" learned by an ANN model is indeed encoded as weights throughout its neuronal connections, and it is possible to extract learned knowledge via a novel weight engineering approach to uncover important biological insights.

Zebrafish Model of Neuroblastoma Metastasis.

Zebrafish has emerged as an important animal model to study human diseases, especially cancer. Along with the robust transgenic and genome editing technologies applied in zebrafish modeling, the ease of maintenance, high-yield productivity, and powerful live imaging altogether make the zebrafish a valuable model system to study metastasis and cellular and molecular bases underlying this process in vivo. The first zebrafish neuroblastoma (NB) model of metastasis was developed by overexpressing two oncogenes, MYCN and LMO1, under control of the dopamine-beta-hydroxylase (dßh) promoter. Co-overexpressed MYCN and LMO1 led to the reduced latency and increased penetrance of neuroblastomagenesis, as well as accelerated distant metastasis of tumor cells. This new model reliably reiterates many key features of human metastatic NB, including involvement of clinically relevant and metastasis-associated genetic alterations; natural and spontaneous development of metastasis in vivo; and conserved sites of metastases. Therefore, the zebrafish model possesses unique advantages to dissect the complex process of tumor metastasis in vivo.

Zebrafish as a Neuroblastoma Model: Progress Made, Promise for the Future.

For nearly a decade, researchers in the field of pediatric oncology have been using zebrafish as a model for understanding the contributions of genetic alternations to the pathogenesis of neuroblastoma (NB), and exploring the molecular and cellular mechanisms that underlie neuroblastoma initiation and metastasis. In this review, we will enumerate and illustrate the key advantages of using the zebrafish model in NB research, which allows researchers to: monitor tumor development in real-time; robustly manipulate gene expression (either transiently or stably); rapidly evaluate the cooperative interactions of multiple genetic alterations to disease pathogenesis; and provide a highly efficient and low-cost methodology to screen for effective pharmaceutical interventions (both alone and in combination with one another). This review will then list some of the common challenges of using the zebrafish model and provide strategies for overcoming these difficulties. We have also included visual diagram and figures to illustrate the workflow of cancer model development in zebrafish and provide a summary comparison of commonly used animal models in cancer research, as well as key findings of cooperative contributions between MYCN and diverse singling pathways in NB pathogenesis.

Identification and characterization of a novel Epstein-Barr Virus-encoded circular RNA from LMP-2 Gene.

Epstein-Barr virus (EBV) has been recently found to generate novel circular RNAs (circRNAs) through backsplicing. However, comprehensive catalogs of EBV circRNAs in other cell lines and their functional characterization are still lacking. In this study, we have identified a list of putative EBV circRNAs in GM12878, an EBV-transformed lymphoblastoid cell line, with a significant majority encoded from the EBV latent genes. A novel EBV circRNA derived from the exon 5 of LMP-2 gene which exhibited highest prevalence, was further validated using RNase R assay and Sanger sequencing. This circRNA, which we term circLMP-2_e5, can be universally detected in a panel of EBV-positive cell lines modelling different latency programs. It ranges from lower expression in nasopharyngeal carcinoma (NPC) cells to higher expression in B cells, and is localized to both the cytoplasm and the nucleus. We provide evidence that circLMP-2_e5 is expressed concomitantly with its cognate linear LMP-2 RNA upon EBV lytic reactivation, and may be produced as a result of exon skipping, with its circularization possibly occurring without the involvement of cis elements in the short flanking introns. Furthermore, we show that circLMP-2_e5 is not involved in regulating cell proliferation, host innate immune response, its linear parental transcripts, or EBV lytic reactivation. Taken together, our study expands the current repertoire of putative EBV circRNAs, broadens our understanding of the biology of EBV circRNAs, and lays the foundation for further investigation of their function in the EBV life cycle and disease development.

GAS7 Deficiency Promotes Metastasis in MYCN-Driven Neuroblastoma.

One of the greatest barriers to curative treatment of neuroblastoma is its frequent metastatic outgrowth prior to diagnosis, especially in cases driven by amplification of the MYCN oncogene. However, only a limited number of regulatory proteins that contribute to this complex MYCN-mediated process have been elucidated. Here we show that the growth arrest-specific 7 (GAS7) gene, located at chromosome band 17p13.1, is preferentially deleted in high-risk MYCN-driven neuroblastoma. GAS7 expression was also suppressed in MYCN-amplified neuroblastoma lacking 17p deletion. GAS7 deficiency led to accelerated metastasis in both zebrafish and mammalian models of neuroblastoma with overexpression or amplification of MYCN. Analysis of expression profiles and the ultrastructure of zebrafish neuroblastoma tumors with MYCN overexpression identified that GAS7 deficiency led to (i) downregulation of genes involved in cell-cell interaction, (ii) loss of contact among tumor cells as critical determinants of accelerated metastasis, and (iii) increased levels of MYCN protein. These results provide the first genetic evidence that GAS7 depletion is a critical early step in the cascade of events culminating in neuroblastoma metastasis in the context of MYCN overexpression. SIGNIFICANCE: Heterozygous deletion or MYCN-mediated repression of GAS7 in neuroblastoma releases an important brake on tumor cell dispersion and migration to distant sites, providing a novel mechanism underlying tumor metastasis in MYCN-driven neuroblastoma.See related commentary by Menard, p. 2815.

JMJD8 is a novel endoplasmic reticulum protein with a JmjC domain.

Jumonji C (JmjC) domain-containing proteins have been shown to regulate cellular processes by hydroxylating or demethylating histone and non-histone targets. JMJD8 belongs to the JmjC domain-only family that was recently shown to be involved in angiogenesis and TNF-induced NF-κB signaling. Here, we employed bioinformatic analysis and immunofluorescence microscopy to examine the physiological properties of JMJD8. We demonstrated that JMJD8 localizes to the lumen of endoplasmic reticulum and that JMJD8 forms dimers or oligomers in vivo. Furthermore, we identified potential JMJD8-interacting proteins that are known to regulate protein complex assembly and protein folding. Taken together, this work demonstrates that JMJD8 is the first JmjC domain-containing protein found in the lumen of the endoplasmic reticulum that may function in protein complex assembly and protein folding.

Identification of 5-Methoxy-2-(Diformylmethylidene)-3,3-Dimethylindole as an Anti-Influenza A Virus Agent.

Influenza virus is estimated to cause 3-5 million severe complications and about 250-500 thousand deaths per year. Different kinds of anti-influenza virus drugs have been developed. However, the emergence of drug resistant strains has presented a big challenge for efficient antiviral therapy. Indole derivatives have been shown to exhibit both antiviral and anti-inflammatory activities. In this study, we adopted a cell-based system to screen for potential anti-IAV agents. Four indole derivatives (named 525A, 526A, 527A and 528A) were subjected to the antiviral screening, of which 526A was selected for further investigation. We reported that pre-treating cells with 526A protects cells from IAV infection. Furthermore, 526A inhibits IAV replication by inhibiting the expression of IAV genes. Interestingly, 526A suppresses the activation of IRF3 and STAT1 in host cells and thus represses the production of type I interferon response and cytokines in IAV-infected cells. Importantly, 526A also partially blocks the activation of RIG-I pathway. Taken together, these results suggest that 526A may be a potential anti-influenza A virus agent.

JMJD8 is a positive regulator of TNF-induced NF-κB signaling.

TNF-induced signaling mediates pleiotropic biological consequences including inflammation, immunity, cell proliferation and apoptosis. Misregulation of TNF signaling has been attributed as a major cause of chronic inflammatory diseases and cancer. Jumonji domain-containing protein 8 (JMJD8) belongs to the JmjC family. However, only part of the family members has been described as hydroxylase enzymes that function as histone demethylases. Here, we report that JMJD8 positively regulates TNF-induced NF-κB signaling. Silencing the expression of JMJD8 using RNA interference (RNAi) greatly suppresses TNF-induced expression of several NF-κB-dependent genes. Furthermore, knockdown of JMJD8 expression reduces RIP ubiquitination, IKK kinase activity, delays IκBα degradation and subsequently blocks nuclear translocation of p65. In addition, JMJD8 deficiency enhances TNF-induced apoptosis. Taken together, these findings indicate that JMJD8 functions as a positive regulator of TNF-induced NF-κB signaling.

A cell-based screening system for anti-influenza A virus agents.

Emerging of drug resistant influenza A virus (IAV) has been a big challenge for anti-IAV therapy. In this study, we describe a relatively easy and safe cell-based screening system for anti-IAV replication inhibitors using a non-replicative strain of IAV. A nickel (II) complex of polyhydroxybenzaldehyde N4-thiosemicarbazone (NiPT5) was recently found to exhibit anti-inflammatory activity in vivo and in vitro. NiPT5 impedes the signaling cascades that lead to the activation of NF-κB in response to different stimuli, such as LPS and TNFα. Using our cell-based screening system, we report that pretreating cells with NiPT5 protects cells from influenza A virus (IAV) and vesicular stomatitis virus (VSV) infection. Furthermore, NiPT5 inhibits replication of IAV by inhibiting transcription and translation of vRNAs of IAV. Additionally, NiPT5 reduces IAV-induced type I interferon response and cytokines production. Moreover, NiPT5 prevents activation of NF-κB, and IRF3 in response to IAV infection. These results demonstrate that NiPT5 is a potent antiviral agent that inhibits the early phase of IAV replication.

Inhibition of euchromatic histone methyltransferase 1 and 2 sensitizes chronic myeloid leukemia cells to interferon treatment.

BACKGROUND: H3K9 methylation is one of the essential histone post-translational modifications for heterochromatin formation and transcriptional repression. Recently, several studies have demonstrated that H3K9 methylation negatively regulates the type I interferon response. RESULTS: We report the application of EHMT1 and EHMT2 specific chemical inhibitors to sensitize CML cell lines to interferon and imatinib treatments. Inhibition of EHMT1 and EHMT2 with BIX01294 enhances the cytotoxicity of IFNα2a in four CML cell lines, K562, KCL22, BV173 and KT1 cells. Chromatin immunoprecipitation assay shows that BIX01294 treatment enhances type I interferon response by reducing H3K9me2 at the promoters of interferon-stimulated genes. Additionally, BIX01294 treatment augments IFNα2a- and imatinib-mediated apoptosis in CML cell lines. Moreover, our data suggest that the expression level of EHMT1 and EHMT2 inversely correlates with the type I interferon responsiveness in CML cell lines. CONCLUSIONS: Our study sheds light on the role of EHMT1 and EHMT2 as potential targets in improving the efficacy of standard treatments of CML.

Epstein-Barr virus-encoded latent membrane protein-1 upregulates 14-3-3σ and Reprimo to confer G(2)/M phase cell cycle arrest.

Epstein-Barr virus (EBV) is a ubiquitous tumor-causing virus which infects more than 90% of the world population asymptomatically. Recent studies suggest that LMP-1, -2A and -2B cooperate in the tumorigenesis of EBV-associated epithelial cancers such as nasopharygeal carcinoma, oral and gastric cancer. In this study, LMPs were expressed in the HEK293T cell line to reveal their oncogenic mechanism via investigation on their involvement in the regulation of the cell cycle and genes that are involved. LMPs were expressed in HEK293T in single and co-expression manner. The transcription of cell cycle arrest genes were examined via real-time PCR. Cell cycle progression was examined via flow cytometry. 14-3-3σ and Reprimo were upregulated in all LMP-1 expressing cells. Moreover, cell cycle arrest at G(2)/M progression was detected in all LMP-1 expressing cells. Therefore, we conclude that LMP-1 may induce cell cycle arrest at G(2)/M progression via upregulation of 14-3-3σ and Reprimo.