Notch signaling pathway activation is known to contribute to the pathogenesis of a spectrum of human malignancies, including T cell leukemia. However, recent studies have implicated the Notch pathway ...as a tumor suppressor in myeloproliferative neoplasms and several solid tumors. Here we report a novel tumor suppressor role for Notch signaling in acute myeloid leukemia (AML) and demonstrate that Notch pathway activation could represent a therapeutic strategy in this disease. We show that Notch signaling is silenced in human AML samples, as well as in AML-initiating cells in an animal model of the disease. In vivo activation of Notch signaling using genetic Notch gain of function models or in vitro using synthetic Notch ligand induces rapid cell cycle arrest, differentiation, and apoptosis of AML-initiating cells. Moreover, we demonstrate that Notch inactivation cooperates in vivo with loss of the myeloid tumor suppressor Tet2 to induce AML-like disease. These data demonstrate a novel tumor suppressor role for Notch signaling in AML and elucidate the potential therapeutic use of Notch receptor agonists in the treatment of this devastating leukemia.
Cancer stem cells (CSCs) are defined by their ability to (i) fully recapitulate the tumor of origin when transplanted into immunodeficient mouse hosts, and (ii) self-renew, demonstrated by their ...ability to be serially transplanted. These properties suggest that CSCs are required for tumor maintenance and metastasis; thus, it has been predicted that CSC elimination is required for cure. This prediction has profoundly altered paradigms for cancer research, compelling investigators to prospectively isolate CSCs to characterize the molecular pathways regulating their behavior. Many potential strategies for CSC-directed therapy have been proposed, but few studies have rigorously demonstrated their efficacy using in vivo models. Herein, we highlight recent studies that demonstrate the utility of CSC-directed therapies and discuss the implications of the CSC hypothesis to experimental design and therapeutic strategies.
We synthesized “mesoscale” nanoparticles, approximately 400 nm in diameter, which unexpectedly localized selectively in renal proximal tubules and up to 7 times more efficiently in the kidney than ...other organs. Although nanoparticles typically localize in the liver and spleen, modulating their size and opsonization potential allowed for stable targeting of the kidneys through a new proposed uptake mechanism. Applying this kidney targeting strategy, we anticipate use in the treatment of renal disease and the study of renal physiology.
Despite the strong genetic basis of psychiatric disorders, the underlying molecular mechanisms are largely unmapped. RNA-binding proteins (RBPs) are responsible for most post-transcriptional ...regulation, from splicing to translation to localization. RBPs thus act as key gatekeepers of cellular homeostasis, especially in the brain. However, quantifying the pathogenic contribution of noncoding variants impacting RBP target sites is challenging. Here, we leverage a deep learning approach that can accurately predict the RBP target site dysregulation effects of mutations and discover that RBP dysregulation is a principal contributor to psychiatric disorder risk. RBP dysregulation explains a substantial amount of heritability not captured by large-scale molecular quantitative trait loci studies and has a stronger impact than common coding region variants. We share the genome-wide profiles of RBP dysregulation, which we use to identify DDHD2 as a candidate schizophrenia risk gene. This resource provides a new analytical framework to connect the full range of RNA regulation to complex disease.
Many functionally important interactions between genes and proteins involved in immunological diseases and processes are unknown. The exponential growth in public high-throughput data offers an ...opportunity to expand this knowledge. To unlock human-immunology-relevant insight contained in the global biomedical research effort, including all public high-throughput datasets, we performed immunological-pathway-focused Bayesian integration of a comprehensive, heterogeneous compendium comprising 38,088 genome-scale experiments. The distillation of this knowledge into immunological networks of functional relationships between molecular entities (ImmuNet), and tools to mine this resource, are accessible to the public at http://immunet.princeton.edu. The predictive capacity of ImmuNet, established by rigorous statistical validation, is easily accessed by experimentalists to generate data-driven hypotheses. We demonstrate the power of this approach through the identification of unique host-virus interaction responses, and we show how ImmuNet complements genetic studies by predicting disease-associated genes. ImmuNet should be widely beneficial for investigating the mechanisms of the human immune system and immunological diseases.
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•Interactive web-accessible immunology resource leverages 38,088 experiments•Powerful computational methods generate big-data-driven hypotheses for immunology•Predicts new immune pathway interactions, mechanisms, and disease-associated genes•Flexible, user-friendly platform addresses diverse immunological research questions
The large amount of publically available high-throughput data contains, in aggregate, a vast amount of immunologically relevant insight. Sealfon and colleagues report ImmuNet, a web-accessible public resource based on 38,088 experiments that allows researchers to predict gene-gene relationships relevant to the human immune system and immunological diseases.
Abstract Cancer diagnosis and management depend upon the extraction of complex information from microscopy images by pathologists, which requires time-consuming expert interpretation prone to human ...bias. Supervised deep learning approaches have proven powerful, but are inherently limited by the cost and quality of annotations used for training. Therefore, we present Histomorphological Phenotype Learning, a self-supervised methodology requiring no labels and operating via the automatic discovery of discriminatory features in image tiles. Tiles are grouped into morphologically similar clusters which constitute an atlas of histomorphological phenotypes (HP-Atlas), revealing trajectories from benign to malignant tissue via inflammatory and reactive phenotypes. These clusters have distinct features which can be identified using orthogonal methods, linking histologic, molecular and clinical phenotypes. Applied to lung cancer, we show that they align closely with patient survival, with histopathologically recognised tumor types and growth patterns, and with transcriptomic measures of immunophenotype. These properties are maintained in a multi-cancer study.
Loss of the RNA binding protein FMRP causes Fragile X Syndrome (FXS), the most common cause of inherited intellectual disability, yet it is unknown how FMRP function varies across brain regions and ...cell types and how this contributes to disease pathophysiology. Here we use conditional tagging of FMRP and CLIP (FMRP cTag CLIP) to examine FMRP mRNA targets in hippocampal CA1 pyramidal neurons, a critical cell type for learning and memory relevant to FXS phenotypes. Integrating these data with analysis of ribosome-bound transcripts in these neurons revealed CA1-enriched binding of autism-relevant mRNAs, and CA1-specific regulation of transcripts encoding circadian proteins. This contrasted with different targets in cerebellar granule neurons, and was consistent with circadian defects in hippocampus-dependent memory in
knockout mice. These findings demonstrate differential FMRP-dependent regulation of mRNAs across neuronal cell types that may contribute to phenotypes such as memory defects and sleep disturbance associated with FXS.
NOVA1 is a neuronal RNA-binding protein identified as the target antigen of a rare autoimmune disorder associated with cancer and neurological symptoms, termed paraneoplastic opsoclonus-myoclonus ...ataxia. Despite the strong association between NOVA1 and cancer, it has been unclear how NOVA1 function might contribute to cancer biology. In this study, we find that NOVA1 acts as an oncogenic factor in a GBM (glioblastoma multiforme) cell line established from a patient. Interestingly, NOVA1 and Argonaute (AGO) CLIP identified common 3' untranslated region (UTR) targets, which were down-regulated in NOVA1 knockdown GBM cells, indicating a transcriptome-wide intersection of NOVA1 and AGO-microRNA (miRNA) targets regulation. NOVA1 binding to 3'UTR targets stabilized transcripts including those encoding cholesterol homeostasis related proteins. Selective inhibition of NOVA1-RNA interactions with antisense oligonucleotides disrupted GBM cancer cell fitness. The precision of our GBM CLIP studies point to both mechanism and precise RNA sequence sites to selectively inhibit oncogenic NOVA1-RNA interactions. Taken together, we find that NOVA1 is commonly overexpressed in GBM, where it can antagonize AGO2-miRNA actions and consequently up-regulates cholesterol synthesis, promoting cell viability.
The mechanism of action of oncogenes in acute myeloid leukaemia is poorly understood. A study now shows that the fusion oncoprotein AML1-ETO regulates leukaemogenesis by increasing the expression of ...small nucleolar RNAs through post-transcriptional mechanisms, resulting in increased ribosomal RNA methylation, protein translation, and promotion of leukaemic-cell self-renewal and growth.
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