Showing papers by "Howard Hughes Medical Institute published in 2017"
TL;DR: Evaluating the efficacy of PD-1 blockade in patients with advanced mismatch repair–deficient cancers across 12 different tumor types showed that colorectal cancers with mismatch repair deficiency were sensitive to immune checkpoint blockade with antibodies to programmed death receptor–1 (PD-1).
Abstract: The genomes of cancers deficient in mismatch repair contain exceptionally high numbers of somatic mutations. In a proof-of-concept study, we previously showed that colorectal cancers with mismatch repair deficiency were sensitive to immune checkpoint blockade with antibodies to programmed death receptor–1 (PD-1). We have now expanded this study to evaluate the efficacy of PD-1 blockade in patients with advanced mismatch repair–deficient cancers across 12 different tumor types. Objective radiographic responses were observed in 53% of patients, and complete responses were achieved in 21% of patients. Responses were durable, with median progression-free survival and overall survival still not reached. Functional analysis in a responding patient demonstrated rapid in vivo expansion of neoantigen-specific T cell clones that were reactive to mutant neopeptides found in the tumor. These data support the hypothesis that the large proportion of mutant neoantigens in mismatch repair–deficient cancers make them sensitive to immune checkpoint blockade, regardless of the cancers’ tissue of origin.
4,569 citations
TL;DR: Adenine base editors (ABEs) that mediate the conversion of A•T to G•C in genomic DNA are described and a transfer RNA adenosine deaminase is evolved to operate on DNA when fused to a catalytically impaired CRISPR–Cas9 mutant.
Abstract: The spontaneous deamination of cytosine is a major source of transitions from C•G to T•A base pairs, which account for half of known pathogenic point mutations in humans. The ability to efficiently convert targeted A•T base pairs to G•C could therefore advance the study and treatment of genetic diseases. The deamination of adenine yields inosine, which is treated as guanine by polymerases, but no enzymes are known to deaminate adenine in DNA. Here we describe adenine base editors (ABEs) that mediate the conversion of A•T to G•C in genomic DNA. We evolved a transfer RNA adenosine deaminase to operate on DNA when fused to a catalytically impaired CRISPR-Cas9 mutant. Extensive directed evolution and protein engineering resulted in seventh-generation ABEs that convert targeted A•T base pairs efficiently to G•C (approximately 50% efficiency in human cells) with high product purity (typically at least 99.9%) and low rates of indels (typically no more than 0.1%). ABEs introduce point mutations more efficiently and cleanly, and with less off-target genome modification, than a current Cas9 nuclease-based method, and can install disease-correcting or disease-suppressing mutations in human cells. Together with previous base editors, ABEs enable the direct, programmable introduction of all four transition mutations without double-stranded DNA cleavage.
2,451 citations
TL;DR: It is proposed that gene regulatory networks are sufficiently interconnected such that all genes expressed in disease-relevant cells are liable to affect the functions of core disease-related genes and that most heritability can be explained by effects on genes outside core pathways.
2,257 citations
TL;DR: The expanded CMap is reported, made possible by a new, low-cost, high-throughput reduced representation expression profiling method that is shown to be highly reproducible, comparable to RNA sequencing, and suitable for computational inference of the expression levels of 81% of non-measured transcripts.
1,943 citations
TL;DR: Roles for mRNA modification in nearly every aspect of the mRNA life cycle, as well as in various cellular, developmental, and disease processes are revealed.
1,855 citations
TL;DR: This refined analysis has identified, among others, a previously unknown dendritic cell population that potently activates T cells and reclassify pDCs as the originally described “natural interferon-producing cells (IPCs)” with weaker T cell proliferation induction ability.
Abstract: INTRODUCTION Dendritic cells (DCs) and monocytes consist of multiple specialized subtypes that play a central role in pathogen sensing, phagocytosis, and antigen presentation. However, their identities and interrelationships are not fully understood, as these populations have historically been defined by a combination of morphology, physical properties, localization, functions, developmental origins, and expression of a restricted set of surface markers. RATIONALE To overcome this inherently biased strategy for cell identification, we performed single-cell RNA sequencing of ~2400 cells isolated from healthy blood donors and enriched for HLA-DR + lineage − cells. This single-cell profiling strategy and unbiased genomic classification, together with follow-up profiling and functional and phenotypic characterization of prospectively isolated subsets, led us to identify and validate six DC subtypes and four monocyte subtypes, and thus revise the taxonomy of these cells. RESULTS Our study reveals: 1) A new DC subset, representing 2 to 3% of the DC populations across all 10 donors tested, characterized by the expression of AXL , SIGLEC1 , and SIGLEC6 antigens, named AS DCs. The AS DC population further divides into two populations captured in the traditionally defined plasmacytoid DC (pDC) and CD1C + conventional DC (cDC) gates. This split is further reflected through AS DC gene expression signatures spanning a spectrum between cDC-like and pDC-like gene sets. Although AS DCs share properties with pDCs, they more potently activate T cells. This discovery led us to reclassify pDCs as the originally described “natural interferon-producing cells (IPCs)” with weaker T cell proliferation induction ability. 2) A new subdivision within the CD1C + DC subset: one defined by a major histocompatibility complex class II–like gene set and one by a CD14 + monocyte–like prominent gene set. These CD1C + DC subsets, which can be enriched by combining CD1C with CD32B, CD36, and CD163 antigens, can both potently induce T cell proliferation. 3) The existence of a circulating and dividing cDC progenitor giving rise to CD1C + and CLEC9A + DCs through in vitro differentiation assays. This blood precursor is defined by the expression of CD100 + CD34 int and observed at a frequency of ~0.02% of the LIN – HLA-DR + fraction. 4) Two additional monocyte populations: one expressing classical monocyte genes and cytotoxic genes, and the other with unknown functions. 5) Evidence for a relationship between blastic plasmacytoid DC neoplasia (BPDCN) cells and healthy DCs. CONCLUSION Our revised taxonomy will enable more accurate functional and developmental analyses as well as immune monitoring in health and disease. The discovery of AS DCs within the traditionally defined pDC population explains many of the cDC properties previously assigned to pDCs, highlighting the need to revisit the definition of pDCs. Furthermore, the discovery of blood cDC progenitors represents a new therapeutic target readily accessible in the bloodstream for manipulation, as well as a new source for better in vitro DC generation. Although the current results focus on DCs and monocytes, a similar strategy can be applied to build a comprehensive human immune cell atlas.
1,468 citations
TL;DR: In this article, the authors profiled transcriptomes of ∼6,000 single cells from 18 head and neck squamous cell carcinoma (HNSCC) patients, including five matched pairs of primary tumors and lymph node metastases.
1,425 citations
TL;DR: The Trainable Weka Segmentation (TWS), a machine learning tool that leverages a limited number of manual annotations in order to train a classifier and segment the remaining data automatically, is introduced.
Abstract: Summary State-of-the-art light and electron microscopes are capable of acquiring large image datasets, but quantitatively evaluating the data often involves manually annotating structures of interest. This process is time-consuming and often a major bottleneck in the evaluation pipeline. To overcome this problem, we have introduced the Trainable Weka Segmentation (TWS), a machine learning tool that leverages a limited number of manual annotations in order to train a classifier and segment the remaining data automatically. In addition, TWS can provide unsupervised segmentation learning schemes (clustering) and can be customized to employ user-designed image features or classifiers. Availability and implementation TWS is distributed as open-source software as part of the Fiji image processing distribution of ImageJ at http://imagej.net/Trainable_Weka_Segmentation . Contact ignacio.arganda@ehu.eus. Supplementary information Supplementary data are available at Bioinformatics online.
1,416 citations
[...]
Howard Hughes Medical Institute1, Broad Institute2, Massachusetts Institute of Technology3, Wellcome Trust Sanger Institute4, University of Cambridge5, European Bioinformatics Institute6, Harvard University7, Weizmann Institute of Science8, University of Zurich9, Laboratory of Molecular Biology10, Utrecht University11, École Polytechnique Fédérale de Lausanne12, University of Pennsylvania13, German Cancer Research Center14, Heidelberg University15, Ludwig Maximilian University of Munich16, John Radcliffe Hospital17, Newcastle University18, Stanford University19, University of Oxford20, University of California, San Francisco21, Allen Institute for Brain Science22, Karolinska Institutet23, Royal Institute of Technology24, Icahn School of Medicine at Mount Sinai25, University of Cape Town26, University Medical Center Groningen27, Radboud University Nijmegen28, Kettering University29, University of Edinburgh30, Babraham Institute31, New York University32, Netherlands Cancer Institute33, Ragon Institute of MGH, MIT and Harvard34, University of Texas Health Science Center at Houston35, Technische Universität München36, Technical University of Denmark37, University of California, Berkeley38, King's College London39, California Institute of Technology40
TL;DR: An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease.
Abstract: The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community.
1,391 citations
TL;DR: N6-adenosine methylation directs mRNAs to distinct fates by grouping them for differential processing, translation and decay in processes such as cell differentiation, embryonic development and stress responses.
Abstract: The recent discovery of reversible mRNA methylation has opened a new realm of post-transcriptional gene regulation in eukaryotes. The identification and functional characterization of proteins that specifically recognize RNA N6-methyladenosine (m6A) unveiled it as a modification that cells utilize to accelerate mRNA metabolism and translation. N6-adenosine methylation directs mRNAs to distinct fates by grouping them for differential processing, translation and decay in processes such as cell differentiation, embryonic development and stress responses. Other mRNA modifications, including N1-methyladenosine (m1A), 5-methylcytosine (m5C) and pseudouridine, together with m6A form the epitranscriptome and collectively code a new layer of information that controls protein synthesis.
1,369 citations
01 Apr 2017
TL;DR: In this paper, the authors performed single-cell RNA sequencing of ~2400 cells isolated from healthy blood donors and enriched for HLA-DR + lineage − cells, which led them to identify and validate six Dendritic cells (DCs) and four monocyte subtypes.
Abstract: INTRODUCTION Dendritic cells (DCs) and monocytes consist of multiple specialized subtypes that play a central role in pathogen sensing, phagocytosis, and antigen presentation. However, their identities and interrelationships are not fully understood, as these populations have historically been defined by a combination of morphology, physical properties, localization, functions, developmental origins, and expression of a restricted set of surface markers. RATIONALE To overcome this inherently biased strategy for cell identification, we performed single-cell RNA sequencing of ~2400 cells isolated from healthy blood donors and enriched for HLA-DR + lineage − cells. This single-cell profiling strategy and unbiased genomic classification, together with follow-up profiling and functional and phenotypic characterization of prospectively isolated subsets, led us to identify and validate six DC subtypes and four monocyte subtypes, and thus revise the taxonomy of these cells. RESULTS Our study reveals: 1) A new DC subset, representing 2 to 3% of the DC populations across all 10 donors tested, characterized by the expression of AXL , SIGLEC1 , and SIGLEC6 antigens, named AS DCs. The AS DC population further divides into two populations captured in the traditionally defined plasmacytoid DC (pDC) and CD1C + conventional DC (cDC) gates. This split is further reflected through AS DC gene expression signatures spanning a spectrum between cDC-like and pDC-like gene sets. Although AS DCs share properties with pDCs, they more potently activate T cells. This discovery led us to reclassify pDCs as the originally described “natural interferon-producing cells (IPCs)” with weaker T cell proliferation induction ability. 2) A new subdivision within the CD1C + DC subset: one defined by a major histocompatibility complex class II–like gene set and one by a CD14 + monocyte–like prominent gene set. These CD1C + DC subsets, which can be enriched by combining CD1C with CD32B, CD36, and CD163 antigens, can both potently induce T cell proliferation. 3) The existence of a circulating and dividing cDC progenitor giving rise to CD1C + and CLEC9A + DCs through in vitro differentiation assays. This blood precursor is defined by the expression of CD100 + CD34 int and observed at a frequency of ~0.02% of the LIN – HLA-DR + fraction. 4) Two additional monocyte populations: one expressing classical monocyte genes and cytotoxic genes, and the other with unknown functions. 5) Evidence for a relationship between blastic plasmacytoid DC neoplasia (BPDCN) cells and healthy DCs. CONCLUSION Our revised taxonomy will enable more accurate functional and developmental analyses as well as immune monitoring in health and disease. The discovery of AS DCs within the traditionally defined pDC population explains many of the cDC properties previously assigned to pDCs, highlighting the need to revisit the definition of pDCs. Furthermore, the discovery of blood cDC progenitors represents a new therapeutic target readily accessible in the bloodstream for manipulation, as well as a new source for better in vitro DC generation. Although the current results focus on DCs and monocytes, a similar strategy can be applied to build a comprehensive human immune cell atlas.
TL;DR: TP53 is the most frequently mutated gene in human cancer and must be interpreted to understand how cell type, mutation profile, and epigenetic cell state dictate outcomes, and how might it restore its tumor-suppressive activities in cancer.
Cornell University1, Paris Descartes University2, University of Massachusetts Medical School3, Spanish National Research Council4, University of Rome Tor Vergata5, Boston Children's Hospital6, University of Pittsburgh7, National Scientific and Technical Research Council8, National University of Cuyo9, Albert Einstein College of Medicine10, University of California, San Francisco11, University of New Mexico12, University of Split13, Goethe University Frankfurt14, University of Helsinki15, University of Salento16, German Cancer Research Center17, Virginia Commonwealth University18, St. Jude Children's Research Hospital19, Discovery Institute20, Harvard University21, University of Tromsø22, Eötvös Loránd University23, Hungarian Academy of Sciences24, New York University25, University of Vienna26, Babraham Institute27, University of South Australia28, University of Texas Southwestern Medical Center29, Howard Hughes Medical Institute30, University of Oviedo31, University of Graz32, National Institutes of Health33, City University of New York34, Queens College35, University of Tokyo36, University of Zurich37, Novartis38, Austrian Academy of Sciences39, University of Groningen40, University of Cambridge41, University of Padua42, University of Oxford43, University of Bern44, University of Oslo45, University of Crete46, Foundation for Research & Technology – Hellas47, Francis Crick Institute48, Osaka University49, Icahn School of Medicine at Mount Sinai50
TL;DR: A panel of leading experts in the field attempts here to define several autophagy‐related terms based on specific biochemical features to formulate recommendations that facilitate the dissemination of knowledge within and outside the field of autophagic research.
Abstract: Over the past two decades, the molecular machinery that underlies autophagic responses has been characterized with ever increasing precision in multiple model organisms. Moreover, it has become clear that autophagy and autophagy-related processes have profound implications for human pathophysiology. However, considerable confusion persists about the use of appropriate terms to indicate specific types of autophagy and some components of the autophagy machinery, which may have detrimental effects on the expansion of the field. Driven by the overt recognition of such a potential obstacle, a panel of leading experts in the field attempts here to define several autophagy-related terms based on specific biochemical features. The ultimate objective of this collaborative exchange is to formulate recommendations that facilitate the dissemination of knowledge within and outside the field of autophagy research.
TL;DR: All three YTHDF proteins may act in an integrated and cooperative manner to impact fundamental biological processes related to m6A RNA methylation in the cytoplasm.
Abstract: N6-methyladenosine (m6A) is the most abundant internal modification in eukaryotic messenger RNAs (mRNAs), and plays important roles in cell differentiation and tissue development. It regulates multiple steps throughout the RNA life cycle including RNA processing, translation, and decay, via the recognition by selective binding proteins. In the cytoplasm, m6A binding protein YTHDF1 facilitates translation of m6A-modified mRNAs, and YTHDF2 accelerates the decay of m6A-modified transcripts. The biological function of YTHDF3, another cytoplasmic m6A binder of the YTH (YT521-B homology) domain family, remains unknown. Here, we report that YTHDF3 promotes protein synthesis in synergy with YTHDF1, and affects methylated mRNA decay mediated through YTHDF2. Cells deficient in all three YTHDF proteins experience the most dramatic accumulation of m6A-modified transcripts. These results indicate that together with YTHDF1 and YTHDF2, YTHDF3 plays critical roles to accelerate metabolism of m6A-modified mRNAs in the cytoplasm. All three YTHDF proteins may act in an integrated and cooperative manner to impact fundamental biological processes related to m6A RNA methylation.
TL;DR: The authors profiled almost 50,000 single cells from an individual Caenorhabditis elegans larval stage and were able to identify and recover information from different, even rare, cell types and develop combinatorial indexing strategies to profile the transcriptomes of single cells or nuclei.
Abstract: To resolve cellular heterogeneity, we developed a combinatorial indexing strategy to profile the transcriptomes of single cells or nuclei, termed sci-RNA-seq (single-cell combinatorial indexing RNA sequencing). We applied sci-RNA-seq to profile nearly 50,000 cells from the nematode Caenorhabditis elegans at the L2 larval stage, which provided >50-fold “shotgun” cellular coverage of its somatic cell composition. From these data, we defined consensus expression profiles for 27 cell types and recovered rare neuronal cell types corresponding to as few as one or two cells in the L2 worm. We integrated these profiles with whole-animal chromatin immunoprecipitation sequencing data to deconvolve the cell type–specific effects of transcription factors. The data generated by sci-RNA-seq constitute a powerful resource for nematode biology and foreshadow similar atlases for other organisms.
TL;DR: This work uncovers a critical function for ALKBH5 and provides insight into critical roles of m6A methylation in glioblastoma and a long non-coding RNA antisense to FOXM1 (FOXM1-AS) promotes the interaction of AL KBH5 withFOXM1 nascent transcripts.
TL;DR: Recent advances in biochemical and structural studies have revealed mechanistic insights into how TET and TDG mediate active DNA demethylation and many regulatory mechanisms of this process have been identified.
Abstract: A key mode of regulating DNA methylation is through active demethylation driven by TET-mediated oxidation of 5-methylcytosine (5mC). This Review discusses our latest understanding of the mechanisms and regulation of active DNA demethylation, and the roles of active demethylation (and the oxidized 5mC intermediates) in gene regulation, genome stability, development and disease.
TL;DR: Vulnerability to ferroptic cell death induced by inhibition of a lipid peroxidase pathway as a feature of therapy-resistant cancer cells across diverse mesenchymal cell-state contexts is identified.
Abstract: Cancer cells can assume different biological states, which can affect their resistance to therapies. A mesenchymal phenotype has been associated with drug resistance but the mechanism behind this state is not well understood. Stuart Schreiber and colleagues now show that tumour cells with a mesenchymal phenotype are selectively sensitive to inhibition of GPX4, an enzyme that alters lipid metabolism. GPX4 dissipates lipid peroxides and therefore prevents the iron-mediated reactions which induce ferroptotic cell death. These findings offer new perspectives on targeting cancers that have undergone a transition to a mesenchymal state to evade other therapeutic agents.
TL;DR: It is shown that FTO, as an m6A demethylase, plays a critical oncogenic role in acute myeloid leukemia (AML) and provides profound insights into leukemogenesis and drug response.
TL;DR: Recent developments that extend the generality, DNA specificity, product selectivity, and fundamental capabilities of natural CRISPR systems are described.
TL;DR: M6A sequencing reveals that knockdown of METTL3 or METTL14 induced changes in mRNA m6A enrichment and altered mRNA expression of genes with critical biological functions in GSCs, identified as promising therapeutic targets for glioblastoma.
TL;DR: It is demonstrated that a similar therapy-resistant cell state underlies the behaviour of persister cells derived from a wide range of cancers and drug treatments, and it is suggested that targeting of GPX4 may represent a therapeutic strategy to prevent acquired drug resistance.
Abstract: Acquired drug resistance prevents cancer therapies from achieving stable and complete responses. Emerging evidence implicates a key role for non-mutational drug resistance mechanisms underlying the survival of residual cancer 'persister' cells. The persister cell pool constitutes a reservoir from which drug-resistant tumours may emerge. Targeting persister cells therefore presents a therapeutic opportunity to impede tumour relapse. We previously found that cancer cells in a high mesenchymal therapy-resistant cell state are dependent on the lipid hydroperoxidase GPX4 for survival. Here we show that a similar therapy-resistant cell state underlies the behaviour of persister cells derived from a wide range of cancers and drug treatments. Consequently, we demonstrate that persister cells acquire a dependency on GPX4. Loss of GPX4 function results in selective persister cell ferroptotic death in vitro and prevents tumour relapse in mice. These findings suggest that targeting of GPX4 may represent a therapeutic strategy to prevent acquired drug resistance.
TL;DR: In this article, the authors studied the relationship between the number of normal stem cell divisions and the risk of 17 cancer types in 69 countries throughout the world and revealed a strong correlation (median = 0.80) between cancer incidence and normal stem cells divisions in all countries, regardless of their environment.
Abstract: Cancers are caused by mutations that may be inherited, induced by environmental factors, or result from DNA replication errors (R). We studied the relationship between the number of normal stem cell divisions and the risk of 17 cancer types in 69 countries throughout the world. The data revealed a strong correlation (median = 0.80) between cancer incidence and normal stem cell divisions in all countries, regardless of their environment. The major role of R mutations in cancer etiology was supported by an independent approach, based solely on cancer genome sequencing and epidemiological data, which suggested that R mutations are responsible for two-thirds of the mutations in human cancers. All of these results are consistent with epidemiological estimates of the fraction of cancers that can be prevented by changes in the environment. Moreover, they accentuate the importance of early detection and intervention to reduce deaths from the many cancers arising from unavoidable R mutations.
TL;DR: It is demonstrated that each organelle has a characteristic distribution and dispersion pattern in three-dimensional space and that there is a reproducible pattern of contacts among the six organelles, that is affected by microtubule and cell nutrient status.
Abstract: Using confocal and lattice light sheet microscopy, the authors perform systems-level analysis of the organelle interactome in live cells, allowing them to visualize the frequency and locality of up to five-way interactions between different organelles. Various cell components, or organelles, make contacts that are not mediated by trafficking vesicles, and which result in changes to their physical behaviour, biochemical composition and functionality. Imaging is a powerful tool for studying inter-organelle contact sites, but work by Jennifer Lippincott-Schwartz and colleagues take such analysis to a new level. Using confocal and lattice light sheet microscopy, as well as a multispectral image acquisition and analysis method, they perform systems-level analysis of the organelle interactome in live cells. The approach allows them to visualize the frequency and locality of up to five-way interactions among six different organelles (endoplasmic reticulum, Golgi, lysosome, peroxisome, mitochondria and lipid droplet), providing unexpected insights into the dynamics of these interactions. The method could prove a useful tool for further analysis of non-vesicular communication within the cell. The organization of the eukaryotic cell into discrete membrane-bound organelles allows for the separation of incompatible biochemical processes, but the activities of these organelles must be coordinated. For example, lipid metabolism is distributed between the endoplasmic reticulum for lipid synthesis, lipid droplets for storage and transport, mitochondria and peroxisomes for β-oxidation, and lysosomes for lipid hydrolysis and recycling1,2,3,4,5. It is increasingly recognized that organelle contacts have a vital role in diverse cellular functions5,6,7,8. However, the spatial and temporal organization of organelles within the cell remains poorly characterized, as fluorescence imaging approaches are limited in the number of different labels that can be distinguished in a single image9. Here we present a systems-level analysis of the organelle interactome using a multispectral image acquisition method that overcomes the challenge of spectral overlap in the fluorescent protein palette. We used confocal and lattice light sheet10 instrumentation and an imaging informatics pipeline of five steps to achieve mapping of organelle numbers, volumes, speeds, positions and dynamic inter-organelle contacts in live cells from a monkey fibroblast cell line. We describe the frequency and locality of two-, three-, four- and five-way interactions among six different membrane-bound organelles (endoplasmic reticulum, Golgi, lysosome, peroxisome, mitochondria and lipid droplet) and show how these relationships change over time. We demonstrate that each organelle has a characteristic distribution and dispersion pattern in three-dimensional space and that there is a reproducible pattern of contacts among the six organelles, that is affected by microtubule and cell nutrient status. These live-cell confocal and lattice light sheet spectral imaging approaches are applicable to any cell system expressing multiple fluorescent probes, whether in normal conditions or when cells are exposed to disturbances such as drugs, pathogens or stress. This methodology thus offers a powerful descriptive tool and can be used to develop hypotheses about cellular organization and dynamics.
TL;DR: It is shown that the m6A-binding protein YTHDC1 mediates export of methylated mRNA from the nucleus to the cytoplasm in HeLa cells, and supports an emerging paradigm of m 6A as a distinct biochemical entity for selective processing and metabolism of mammalian mRNAs.
Abstract: N6-methyladenosine (m6A) is the most abundant internal modification of eukaryotic messenger RNA (mRNA) and plays critical roles in RNA biology. The function of this modification is mediated by m6A-selective 'reader' proteins of the YTH family, which incorporate m6A-modified mRNAs into pathways of RNA metabolism. Here, we show that the m6A-binding protein YTHDC1 mediates export of methylated mRNA from the nucleus to the cytoplasm in HeLa cells. Knockdown of YTHDC1 results in an extended residence time for nuclear m6A-containing mRNA, with an accumulation of transcripts in the nucleus and accompanying depletion within the cytoplasm. YTHDC1 interacts with the splicing factor and nuclear export adaptor protein SRSF3, and facilitates RNA binding to both SRSF3 and NXF1. This role for YTHDC1 expands the potential utility of chemical modification of mRNA, and supports an emerging paradigm of m6A as a distinct biochemical entity for selective processing and metabolism of mammalian mRNAs.
TL;DR: In vitro and in vivo human prostate cancer models are used to show that these tumors can develop resistance to the antiandrogen drug enzalutamide by a phenotypic shift from androgen receptor–dependent luminal epithelial cells to AR-independent basal-like cells.
Abstract: Some cancers evade targeted therapies through a mechanism known as lineage plasticity, whereby tumor cells acquire phenotypic characteristics of a cell lineage whose survival no longer depends on the drug target. We use in vitro and in vivo human prostate cancer models to show that these tumors can develop resistance to the antiandrogen drug enzalutamide by a phenotypic shift from androgen receptor (AR)–dependent luminal epithelial cells to AR-independent basal-like cells. This lineage plasticity is enabled by the loss of TP53 and RB1 function, is mediated by increased expression of the reprogramming transcription factor SOX2, and can be reversed by restoring TP53 and RB1 function or by inhibiting SOX2 expression. Thus, mutations in tumor suppressor genes can create a state of increased cellular plasticity that, when challenged with antiandrogen therapy, promotes resistance through lineage switching.
TL;DR: Studying mouse models, it is demonstrated that Rb1 loss facilitates lineage plasticity and metastasis of prostate adenocarcinoma initiated by Pten mutation and Clinically relevant Ezh2 inhibitors restore androgen receptor expression and sensitivity to antiandrogen therapy.
Abstract: Prostate cancer relapsing from antiandrogen therapies can exhibit variant histology with altered lineage marker expression, suggesting that lineage plasticity facilitates therapeutic resistance. The mechanisms underlying prostate cancer lineage plasticity are incompletely understood. Studying mouse models, we demonstrate that Rb1 loss facilitates lineage plasticity and metastasis of prostate adenocarcinoma initiated by Pten mutation. Additional loss of Trp53 causes resistance to antiandrogen therapy. Gene expression profiling indicates that mouse tumors resemble human prostate cancer neuroendocrine variants; both mouse and human tumors exhibit increased expression of epigenetic reprogramming factors such as Ezh2 and Sox2. Clinically relevant Ezh2 inhibitors restore androgen receptor expression and sensitivity to antiandrogen therapy. These findings uncover genetic mutations that enable prostate cancer progression; identify mouse models for studying prostate cancer lineage plasticity; and suggest an epigenetic approach for extending clinical responses to antiandrogen therapy.
TL;DR: The results reveal the SPI1-METTL14-MYB/MYC signaling axis in myelopoiesis and leukemogenesis and highlight the critical roles of METTL14 and m6A modification in normal and malignant hematopoiedis.
TL;DR: It is reported that the Treg transcription factor Foxp3 reprograms T cell metabolism by suppressing Myc and glycolysis, enhancing oxidative phosphorylation, and increasing nicotinamide adenine dinucleotide oxidation, which allows Tregs a metabolic advantage in low-glucose, lactate-rich environments.
TL;DR: A mechanism for the progression of subclinical hepatic insulin resistance to overt fasting hyperglycaemia in type 2 diabetes mellitus is proposed and the therapeutic potential of strategies that target hepatosteatosis, hyperglucagonaemia and adipose lipolysis is considered.
Abstract: The liver is crucial for the maintenance of normal glucose homeostasis - it produces glucose during fasting and stores glucose postprandially. However, these hepatic processes are dysregulated in type 1 and type 2 diabetes mellitus, and this imbalance contributes to hyperglycaemia in the fasted and postprandial states. Net hepatic glucose production is the summation of glucose fluxes from gluconeogenesis, glycogenolysis, glycogen synthesis, glycolysis and other pathways. In this Review, we discuss the in vivo regulation of these hepatic glucose fluxes. In particular, we highlight the importance of indirect (extrahepatic) control of hepatic gluconeogenesis and direct (hepatic) control of hepatic glycogen metabolism. We also propose a mechanism for the progression of subclinical hepatic insulin resistance to overt fasting hyperglycaemia in type 2 diabetes mellitus. Insights into the control of hepatic gluconeogenesis by metformin and insulin and into the role of lipid-induced hepatic insulin resistance in modifying gluconeogenic and net hepatic glycogen synthetic flux are also discussed. Finally, we consider the therapeutic potential of strategies that target hepatosteatosis, hyperglucagonaemia and adipose lipolysis.