A novel network pharmacology approach for leukaemia differentiation therapy using Mogrify®.

Acute myeloid leukaemia (AML) is a rapidly fatal blood cancer that is characterised by the accumulation of immature myeloid cells in the blood and bone marrow as a result of blocked differentiation. Methods which identify master transcriptional regulators of AML subtype-specific leukaemia cell states and their combinations could be critical for discovering novel differentiation-inducing therapies. In this proof-of-concept study, we demonstrate a novel utility of the Mogrify® algorithm in identifying combinations of transcription factors (TFs) and drugs, which recapitulate granulocytic differentiation of the NB4 acute promyelocytic leukaemia (APL) cell line, using two different approaches. In the first approach, Connectivity Map (CMAP) analysis of these TFs and their target networks outperformed standard approaches, retrieving ATRA as the top hit. We identify dimaprit and mebendazole as a drug combination which induces myeloid differentiation. In the second approach, we show that genetic manipulation of specific Mogrify®-identified TFs (MYC and IRF1) leads to co-operative induction of APL differentiation, as does pharmacological targeting of these TFs using currently available compounds. We also show that loss of IRF1 blunts ATRA-mediated differentiation, and that MYC represses IRF1 expression through recruitment of PML-RARα, the driver fusion oncoprotein in APL, to the IRF1 promoter. Finally, we demonstrate that these drug combinations can also induce differentiation of primary patient-derived APL cells, and highlight the potential of targeting MYC and IRF1 in high-risk APL. Thus, these results suggest that Mogrify® could be used for drug discovery or repositioning in leukaemia differentiation therapy for other subtypes of leukaemia or cancers.

Widespread Translational Control of Fibrosis in the Human Heart by RNA-Binding Proteins.

BACKGROUND: Fibrosis is a common pathology in many cardiac disorders and is driven by the activation of resident fibroblasts. The global posttranscriptional mechanisms underlying fibroblast-to-myofibroblast conversion in the heart have not been explored. METHODS: Genome-wide changes of RNA transcription and translation during human cardiac fibroblast activation were monitored with RNA sequencing and ribosome profiling. We then used RNA-binding protein-based analyses to identify translational regulators of fibrogenic genes. The integration with cardiac ribosome occupancy levels of 30 dilated cardiomyopathy patients demonstrates that these posttranscriptional mechanisms are also active in the diseased fibrotic human heart. RESULTS: We generated nucleotide-resolution translatome data during the transforming growth factor ß1-driven cellular transition of human cardiac fibroblasts to myofibroblasts. This identified dynamic changes of RNA transcription and translation at several time points during the fibrotic response, revealing transient and early-responder genes. Remarkably, about one-third of all changes in gene expression in activated fibroblasts are subject to translational regulation, and dynamic variation in ribosome occupancy affects protein abundance independent of RNA levels. Targets of RNA-binding proteins were strongly enriched in posttranscriptionally regulated genes, suggesting genes such as MBNL2 can act as translational activators or repressors. Ribosome occupancy in the hearts of patients with dilated cardiomyopathy suggested the same posttranscriptional regulatory network was underlying cardiac fibrosis. Key network hubs include RNA-binding proteins such as Pumilio RNA binding family member 2 (PUM2) and Quaking (QKI) that work in concert to regulate the translation of target transcripts in human diseased hearts. Furthermore, silencing of both PUM2 and QKI inhibits the transition of fibroblasts toward profibrotic myofibroblasts in response to transforming growth factor ß1. CONCLUSIONS: We reveal widespread translational effects of transforming growth factor ß1 and define novel posttranscriptional regulatory networks that control the fibroblast-to-myofibroblast transition. These networks are active in human heart disease, and silencing of hub genes limits fibroblast activation. Our findings show the central importance of translational control in fibrosis and highlight novel pathogenic mechanisms in heart failure.

Detection of COPB2 as a KRAS synthetic lethal partner through integration of functional genomics screens.

Mutated KRAS plays an important role in many cancers. Although targeting KRAS directly is difficult, indirect inactivation via synthetic lethal partners (SLPs) is promising. Yet to date, there are no SLPs from high-throughput RNAi screening, which are supported by multiple screens. Here, we address this problem by aggregating and ranking data over three independent high-throughput screens. We integrate rankings by minimizing the displacement and by considering established methods such as RIGER and RSA.Our meta analysis reveals COPB2 as a potential SLP of KRAS with good support from all three screens. COPB2 is a coatomer subunit and its knock down has already been linked to disabled autophagy and reduced tumor growth. We confirm COPB2 as SLP in knock down experiments on pancreas and colorectal cancer cell lines.Overall, consistent integration of high throughput data can generate candidate synthetic lethal partners, which individual screens do not uncover. Concretely, we reveal and confirm that COPB2 is a synthetic lethal partner of KRAS and hence a promising cancer target. Ligands inhibiting COPB2 may, therefore, be promising new cancer drugs.

Assessing computational methods for transcription factor target gene identification based on ChIP-seq data.

Chromatin immunoprecipitation coupled with deep sequencing (ChIP-seq) has great potential for elucidating transcriptional networks, by measuring genome-wide binding of transcription factors (TFs) at high resolution. Despite the precision of these experiments, identification of genes directly regulated by a TF (target genes) is not trivial. Numerous target gene scoring methods have been used in the past. However, their suitability for the task and their performance remain unclear, because a thorough comparative assessment of these methods is still lacking. Here we present a systematic evaluation of computational methods for defining TF targets based on ChIP-seq data. We validated predictions based on 68 ChIP-seq studies using a wide range of genomic expression data and functional information. We demonstrate that peak-to-gene assignment is the most crucial step for correct target gene prediction and propose a parameter-free method performing most consistently across the evaluation tests.

Meiotic cohesin SMC1ß provides prophase I centromeric cohesion and is required for multiple synapsis-associated functions.

Cohesin subunit SMC1ß is specific and essential for meiosis. Previous studies showed functions of SMC1ß in determining the axis-loop structure of synaptonemal complexes (SCs), in providing sister chromatid cohesion (SCC) in metaphase I and thereafter, in protecting telomere structure, and in synapsis. However, several central questions remained unanswered and concern roles of SMC1ß in SCC and synapsis and processes related to these two processes. Here we show that SMC1ß substantially supports prophase I SCC at centromeres but not along chromosome arms. Arm cohesion and some of centromeric cohesion in prophase I are provided by non-phosphorylated SMC1α. Besides supporting synapsis of autosomes, SMC1ß is also required for synapsis and silencing of sex chromosomes. In absence of SMC1ß, the silencing factor γH2AX remains associated with asynapsed autosomes and fails to localize to sex chromosomes. Microarray expression studies revealed up-regulated sex chromosome genes and many down-regulated autosomal genes. SMC1ß is further required for non-homologous chromosome associations observed in absence of SPO11 and thus of programmed double-strand breaks. These breaks are properly generated in Smc1ß⁻/⁻ spermatocytes, but their repair is delayed on asynapsed chromosomes. SMC1α alone cannot support non-homologous associations. Together with previous knowledge, three main functions of SMC1ß have emerged, which have multiple consequences for spermatocyte biology: generation of the loop-axis architecture of SCs, homologous and non-homologous synapsis, and SCC starting in early prophase I.

BrainNetVis: an open-access tool to effectively quantify and visualize brain networks.

This paper presents BrainNetVis, a tool which serves brain network modelling and visualization, by providing both quantitative and qualitative network measures of brain interconnectivity. It emphasizes the needs that led to the creation of this tool by presenting similar works in the field and by describing how our tool contributes to the existing scenery. It also describes the methods used for the calculation of the graph metrics (global network metrics and vertex metrics), which carry the brain network information. To make the methods clear and understandable, we use an exemplar dataset throughout the paper, on which the calculations and the visualizations are performed. This dataset consists of an alcoholic and a control group of subjects.