Michael R. Green

X chromosome inactivation (XCI) is induced by Xist long non-coding RNA and protein-coding genes. However, the role of small non-coding RNA function in XCI remains unidentified. Our genome-wide, loss-of-function CRISPR/Cas9 screen in female fibroblasts identified microRNAs (miRNAs) as regulators of XCI. A striking finding is the identification of miR106a among the top candidates from the screen. Loss of miR106a is accompanied by altered Xist interactome, leading to dissociation and destabilization of Xist. XCI interference via miR106a inhibition has therapeutic implications for Rett syndrome (RTT) girls with a defective X-linked MECP2 gene. Here, we discovered that the inhibition of miR106a significantly improves several facets of RTT pathology: it increases the life span, enhances locomotor activity and exploratory behavior, and diminishes breathing variabilities. Our results suggest that miR106a targeting offers a feasible therapeutic strategy for RTT and other monogenic X-linked neurodevelopmental disorders.

Ewing sarcoma (ES) is an aggressive bone cancer driven by the oncogenic fusion-protein EWSR1::FLI1, which is not present in normal cells and is therefore an attractive therapeutic target. However, as a transcription factor, EWSR1::FLI1 is considered undruggable. Factors that promote EWSR1::FLI1 expression, and thus whose inhibition would reduce EWSR1::FLI1 protein levels and function, are potential drug targets. Here, using genome-scale CRISPR/Cas9 knockout screening, we identify C1GALT1, a galactosyltransferase required for the biosynthesis of many O-glycoproteins, as a factor that promotes EWSR1::FLI1 expression. We show that C1GALT1 acts by O-glycosylating the pivotal Hedgehog (Hh) signaling component Smoothened (SMO), thereby stabilizing SMO and stimulating the Hh pathway, which we find directly activates EWSR1::FLI1 transcription. Itraconazole, an FDA-approved anti-fungal agent that is known to inhibit C1GALT1, reduces EWSR1::FLI1 levels in ES cell lines and suppresses growth of ES xenografts in mice. Our study reveals a therapeutically targetable mechanism that promotes EWSR1::FLI1 expression and ES tumor growth.

Although epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (EGFRi) are approved for treating EGFR-mutant lung adenocarcinoma (LUAD), emergence of acquired resistance limits their clinical benefits. Several mechanisms for acquired resistance to EGFRi in LUAD have been identified; however, the molecular basis for this resistance remains unknown in ~30% of LUAD. Chromatin and DNA modifiers and their regulators play important roles in determining response to anticancer therapies. Therefore, to identify nongenetic mechanisms of EGFRi resistance in LUAD, we performed an epigenome-wide shRNA screen targeting 363 human epigenetic regulator genes. This screen identified loss of the transcriptional repressor chromobox homolog 5 (CBX5) as a driver of EGFRi resistance in EGFR-mutant LUAD. Loss of CBX5 confers resistance to multiple EGFRi in both cell culture and mice. We found that CBX5 loss in EGFR-mutant LUAD cells leads to increased expression of the transcription factor E2F1, which in turn stimulates expression of the antiapoptotic gene BIRC5 ( survivin ). This E2F1-mediated upregulation of BIRC5 in CBX5 -knockdown LUAD cells attenuates apoptosis induction following EGFRi treatment. Consistent with these results, knockdown of E2F1 or BIRC5 partly rescues CBX5 -knockdown-induced EGFRi resistance in cell culture and mice. EGFRi-resistant LUAD cell lines show reduced CBX5 expression compared to parental lines; however, bromo- and extra-terminal (BET)-domain inhibitors (BETi) restore CBX5 expression in these cells and sensitize them to EGFRi/BETi combination therapy. Similarly, treatment with a BIRC5 inhibitor suppresses growth of EGFRi-resistant LUAD cells. Collectively, these studies identify CBX5 loss as a driver of EGFRi resistance and reveal therapeutic opportunities for treating EGFRi-resistant LUAD.

Propagation of DNA methylation through cell division relies on the recognition of methylated cytosines by UHRF1. In reprogramming of mouse embryonic stem cells to naive pluripotency (also known as ground state), despite high levels of Uhrf1 transcript, the protein is targeted for degradation by the proteasome, leading to DNA methylation loss. We have undertaken an shRNA screen to identify the signalling pathways that converge upon UHRF1 and control its degradation, using UHRF1-GFP fluorescence as readout. Many candidates we identified are key enzymes in regulation of glucose metabolism, nucleotide metabolism and Pi3K/AKT/mTOR pathway. Unexpectedly, while downregulation of all candidates we selected for validation rescued UHRF1 protein levels, we found that in some of the cases this was not sufficient to maintain DNA methylation. This has implications for development, ageing and diseased conditions. Our study demonstrates two separate processes that regulate UHRF1 protein abundance and activity.

Enhancer of zeste homolog 2 (EZH2) is a histone H3 lysine 27 methyltransferase that has been shown to function as an oncogene in some cancers. Previous reports have largely focused on the ability of EZH2 to regulate cell-intrinsic tumor regulatory pathways as its mechanism-of-oncogenic action. However, the role that EZH2-mediated immune suppression plays in its oncogenic activity is not fully known. In particular, the role of natural killer (NK) cells in EZH2-driven tumor growth remains incompletely understood. Here, we demonstrate that genetic or pharmacological inhibition of EZH2 induces reexpression of the chemokine CXCL10 in hepatic tumor cells. We find that histone deacetylase 10 (HDAC10) is necessary for EZH2 recruitment to the CXCL10 promoter, leading to CXCL10 transcriptional repression. Critically, CXCL10 is necessary and sufficient for stimulating NK cell migration, and EZH2’s ability to inhibit NK cell migration via CXCL10 suppression is conserved in other EZH2-dependent cancers. NK cell depletion in an immunocompetent syngeneic mouse model of hepatic tumorigenesis reverses the tumor inhibitory effects of an EZH2 inhibitor (GSK343), and inhibitor-mediated reexpression of CXCL10 is required for its tumor suppressive effects in the same mouse model. Collectively, these results reveal a decisive role for NK cells and CXCL10 in mediating the oncogenic function of EZH2. Significance Hepatocellular carcinoma (HCC), a type of liver cancer, has a poor 5-y survival rate and current therapies provide only marginal clinical benefits to most HCC patients. Therefore, new therapeutic approaches are needed for HCC treatment. Natural killer (NK) cells are cells of the innate immune system that can inhibit tumor development and progression. We find that pharmacological inhibition of EZH2 results in NK cell–mediated hepatic tumor growth inhibition in mice, which occurs, in part, due to the increased expression of the chemokine CXCL10, leading to increased NK cell migration. These results have implications for EZH2-dependent tumors, in which NK cell–mediated tumor clearance can be induced using EZH2 inhibitors.

Glucocorticoid (GC) resistance remains a clinical challenge in pediatric acute lymphoblastic leukemia where response to GC is a reliable prognostic indicator. To identify GC resistance pathways, we conducted a genome-wide, survival-based, short hairpin RNA screen in murine T-cell acute lymphoblastic leukemia (T-ALL) cells. Genes identified in the screen interfere with cyclic adenosine monophosphate (cAMP) signaling and are underexpressed in GC-resistant or relapsed ALL patients. Silencing of the cAMP-activating Gnas gene interfered with GC-induced gene expression, resulting in dexamethasone resistance in vitro and in vivo. We demonstrate that cAMP signaling synergizes with dexamethasone to enhance cell death in GC-resistant human T-ALL cells. We find the E prostanoid receptor 4 expressed in T-ALL samples and demonstrate that prostaglandin E2 (PGE2) increases intracellular cAMP, potentiates GC-induced gene expression, and sensitizes human T-ALL samples to dexamethasone in vitro and in vivo. These findings identify PGE2 as a target for GC resensitization in relapsed pediatric T-ALL.

Sequence logos have been widely used as graphical representations of conserved nucleic acid and protein motifs. Due to the complexity of the amino acid (AA) alphabet, rich post-translational modification, and diverse subcellular localization of proteins, few versatile tools are available for effective identification and visualization of protein motifs. In addition, various reduced AA alphabets based on physicochemical, structural, or functional properties have been valuable in the study of protein alignment, folding, structure prediction, and evolution. However, there is lack of tools for applying reduced AA alphabets to the identification and visualization of statistically significant motifs. To fill this gap, we developed an R/Bioconductor package dagLogo, which has several advantages over existing tools. First, dagLogo allows various formats for input sets and provides comprehensive options to build optimal background models. It implements different reduced AA alphabets to group AAs of similar properties. Furthermore, dagLogo provides statistical and visual solutions for differential AA (or AA group) usage analysis of both large and small data sets. Case studies showed that dagLogo can better identify and visualize conserved protein sequence patterns from different types of inputs and can potentially reveal the biological patterns that could be missed by other logo generators.

Over the past decade, a large amount of RNA sequencing (RNA-seq) data were deposited in public repositories, and more are being produced at an unprecedented rate. However, there are few open source tools with point-and-click interfaces that are versatile and offer streamlined comprehensive analysis of RNA-seq datasets. To maximize the capitalization of these vast public resources and facilitate the analysis of RNA-seq data by biologists, we developed a web application called OneStopRNAseq for the one-stop analysis of RNA-seq data. OneStopRNAseq has user-friendly interfaces and offers workflows for common types of RNA-seq data analyses, such as comprehensive data-quality control, differential analysis of gene expression, exon usage, alternative splicing, transposable element expression, allele-specific gene expression quantification, and gene set enrichment analysis. Users only need to select the desired analyses and genome build, and provide a Gene Expression Omnibus (GEO) accession number or Dropbox links to sequence files, alignment files, gene-expression-count tables, or rank files with the corresponding metadata. Our pipeline facilitates the comprehensive and efficient analysis of private and public RNA-seq data.