Mechanics-guided developmental fate patterning.
Nat Mater. 2018 Jul;17(7):571-572
Authors: Tewary M, Zandstra PW
PMID: 29941948 [PubMed - in process]
Mechanics-guided developmental fate patterning.
Nat Mater. 2018 Jul;17(7):571-572
Authors: Tewary M, Zandstra PW
PMID: 29941948 [PubMed - in process]
A multiprotein supercomplex controlling oncogenic signalling in lymphoma.
Nature. 2018 Jun 20;:
Authors: Phelan JD, Young RM, Webster DE, Roulland S, Wright GW, Kasbekar M, Shaffer AL, Ceribelli M, Wang JQ, Schmitz R, Nakagawa M, Bachy E, Huang DW, Ji Y, Chen L, Yang Y, Zhao H, Yu X, Xu W, Palisoc MM, Valadez RR, Davies-Hill T, Wilson WH, Chan WC, Jaffe ES, Gascoyne RD, Campo E, Rosenwald A, Ott G, Delabie J, Rimsza LM, Rodriguez FJ, Estephan F, Holdhoff M, Kruhlak MJ, Hewitt SM, Thomas CJ, Pittaluga S, Oellerich T, Staudt LM
B cell receptor (BCR) signaling has emerged as a therapeutic target in B cell lymphomas, but inhibiting this pathway in diffuse large B cell lymphoma (DLBCL) has benefited only a subset of patients1. Gene expression profiling identified two major DLBCL subtypes, known as germinal center (GC) B cell-like (GCB) and activated B cell-like (ABC)2,3, with inferior outcomes following immunochemotherapy in ABC. Autoantigens drive BCR-dependent activation of NF-κB in ABC DLBCL through a kinase cascade of SYK, BTK and PKCβ to promote the assembly of the CARD11-BCL10-MALT1 (CBM) adapter complex that recruits and activates IκB kinase (IKK)4-6. Genome sequencing revealed gain-of-function mutations targeting the CD79A and CD79B BCR subunits and the Toll-like receptor (TLR) signaling adapter MYD885,7, with MYD88L265P being the most prevalent isoform. In a clinical trial, the BTK inhibitor, ibrutinib, produced responses in 37% of ABC cases1. The most striking response rate (80%) was observed in tumors with both CD79B and MYD88L265P mutations, but how these mutations cooperate to promote dependence on BCR signaling remains unclear. Herein, we used genome-wide CRISPR-Cas9 screening and functional proteomics to understand the molecular basis of exceptional clinical responses to ibrutinib. We discovered a new mode of oncogenic BCR signaling in ibrutinib-responsive cell lines and biopsies, coordinated by a multiprotein supercomplex formed by MYD88, TLR9, and the BCR (My-T-BCR). The My-T-BCR co-localizes with mTOR on endolysosomes, where it drives pro-survival NF-κB and mTOR signaling. Inhibitors of BCR and mTOR signaling cooperatively decreased My-T-BCR supercomplex formation and function, providing mechanistic insight into their synergistic toxicity for My-T-BCR+ DLBCL cells. My-T-BCR complexes characterized ibrutinib-responsive malignancies and distinguished ibrutinib responders from non-responders. Our data provide a roadmap for the rational deployment of oncogenic signaling inhibitors in molecularly-defined subsets of DLBCL.
PMID: 29925955 [PubMed - as supplied by publisher]
Mammary molecular portraits reveal lineage-specific features and progenitor cell vulnerabilities.
J Cell Biol. 2018 Jun 19;:
Authors: Casey AE, Sinha A, Singhania R, Livingstone J, Waterhouse P, Tharmapalan P, Cruickshank J, Shehata M, Drysdale E, Fang H, Kim H, Isserlin R, Bailey S, Medina T, Deblois G, Shiah YJ, Barsyte-Lovejoy D, Hofer S, Bader G, Lupien M, Arrowsmith C, Knapp S, De Carvalho D, Berman H, Boutros PC, Kislinger T, Khokha R
The mammary epithelium depends on specific lineages and their stem and progenitor function to accommodate hormone-triggered physiological demands in the adult female. Perturbations of these lineages underpin breast cancer risk, yet our understanding of normal mammary cell composition is incomplete. Here, we build a multimodal resource for the adult gland through comprehensive profiling of primary cell epigenomes, transcriptomes, and proteomes. We define systems-level relationships between chromatin-DNA-RNA-protein states, identify lineage-specific DNA methylation of transcription factor binding sites, and pinpoint proteins underlying progesterone responsiveness. Comparative proteomics of estrogen and progesterone receptor-positive and -negative cell populations, extensive target validation, and drug testing lead to discovery of stem and progenitor cell vulnerabilities. Top epigenetic drugs exert cytostatic effects; prevent adult mammary cell expansion, clonogenicity, and mammopoiesis; and deplete stem cell frequency. Select drugs also abrogate human breast progenitor cell activity in normal and high-risk patient samples. This integrative computational and functional study provides fundamental insight into mammary lineage and stem cell biology.
PMID: 29921600 [PubMed - as supplied by publisher]
GeneMANIA update 2018.
Nucleic Acids Res. 2018 Jun 15;:
Authors: Franz M, Rodriguez H, Lopes C, Zuberi K, Montojo J, Bader GD, Morris Q
GeneMANIA (http://genemania.org) is a flexible user-friendly web site for generating hypotheses about gene function, analyzing gene lists and prioritizing genes for functional assays. Given a query gene list, GeneMANIA finds functionally similar genes using a wealth of genomics and proteomics data. In this mode, it weights each functional genomic dataset according to its predictive value for the query. Another use of GeneMANIA is gene function prediction. Given a single query gene, GeneMANIA finds genes likely to share function with it based on their interactions with it. Enriched Gene Ontology categories among this set can point to the function of the gene. Nine organisms are currently supported (Arabidopsis thaliana, Caenorhabditis elegans, Danio rerio, Drosophila melanogaster, Escherichia coli, Homo sapiens, Mus musculus, Rattus norvegicus and Saccharomyces cerevisiae). Hundreds of data sets and hundreds of millions of interactions have been collected from GEO, BioGRID, IRefIndex and I2D, as well as organism-specific functional genomics data sets. Users can customize their search by selecting specific data sets to query and by uploading their own data sets to analyze. We have recently updated the user interface to GeneMANIA to make it more intuitive and make more efficient use of visual space. GeneMANIA can now be used effectively on a variety of devices.
PMID: 29912392 [PubMed - as supplied by publisher]
Lipophilicity of the Cystic Fibrosis drug, Ivacaftor, and its destabilizing effect on the major CF-causing mutation: F508del.
Mol Pharmacol. 2018 Jun 14;:
Authors: Chin S, Hung M, Won A, Wu YS, Ahmadi S, Yang D, Elmallah S, Toutah K, Hamilton CM, Young RN, Viirre RD, Yip CM, Bear CE
The major Cystic Fibrosis (CF) causing mutation, the deletion of phenylalanine at position 508 (F508del) at the cystic fibrosis transmembrane conductance regulator (CFTR), occurs in approximately 90% of the CF population. Recently, a combination therapy, comprising a corrector (VX-809) that rescues the processing defects of F508del-CFTR and a potentiator (VX-770) that rescues mutant channel activity, was approved for CF patients homozygous for this mutation. However, clinical studies revealed that the efficacy of this drug on lung function was modest and variable amongst patients. It has been proposed that this modest effect may partially relate to a destabilizing effect of VX-770 on mutant protein. In the current studies, we observed a similar concentration-dependent destabilizing effect of VX-770 on F508del-CFTR and on other ion transporters. We found that the relative destabilizing effect of a panel of VX-770 derivatives correlated with their predicted lipophilicity. Given the importance of CFTR association with lipid rafts, we were prompted to determine if VX-770 directly disrupted lipid rafts. Polarized total internal reflection fluorescence microscopy on a supported lipid bilayer model shows that VX-770, and not its less lipophilic derivative, increased the fluidity of and reorganized the membrane. In summary, our findings support the claim that VX-770 modulates CFTR stability via interaction with membrane lipids.
PMID: 29903751 [PubMed - as supplied by publisher]
Genetic Network Complexity Shapes Background-Dependent Phenotypic Expression.
Trends Genet. 2018 Jun 11;:
Authors: Hou J, van Leeuwen J, Andrews BJ, Boone C
The phenotypic consequences of a given mutation can vary across individuals. This so-called background effect is widely observed, from mutant fitness of loss-of-function variants in model organisms to variable disease penetrance and expressivity in humans; however, the underlying genetic basis often remains unclear. Taking insights gained from recent large-scale surveys of genetic interaction and suppression analyses in yeast, we propose that the genetic network context for a given mutation may shape its propensity of exhibiting background-dependent phenotypes. We argue that further efforts in systematically mapping the genetic interaction networks beyond yeast will provide not only key insights into the functional properties of genes, but also a better understanding of the background effects and the (un)predictability of traits in a broader context.
PMID: 29903533 [PubMed - as supplied by publisher]
Neural stem cell heterogeneity in the mammalian forebrain.
Prog Neurobiol. 2018 Jun 11;:
Authors: Adams KV, Morshead CM
The brain was long considered an organ that underwent very little change after development. It is now well established that the mammalian central nervous system contains neural stem cells that generate progeny that are capable of making new neurons, astrocytes, and oligodendrocytes throughout life. The field has advanced rapidly as it strives to understand the basic biology of these precursor cells, and explore their potential to promote brain repair. The purpose of this review is to present current knowledge about the diversity of neural stem cells in vitro and in vivo, and highlight distinctions between neural stem cell populations, throughout development, and within the niche. A comprehensive understanding of neural stem cell heterogeneity will provide insights into the cellular and molecular regulation of neural development and lifelong neurogenesis, and will guide the development of novel strategies to promote regeneration and neural repair.
PMID: 29902499 [PubMed - as supplied by publisher]
Map of synthetic rescue interactions for the Fanconi anemia DNA repair pathway identifies USP48.
Nat Commun. 2018 Jun 11;9(1):2280
Authors: Velimezi G, Robinson-Garcia L, Muñoz-Martínez F, Wiegant WW, Ferreira da Silva J, Owusu M, Moder M, Wiedner M, Rosenthal SB, Fisch KM, Moffat J, Menche J, van Attikum H, Jackson SP, Loizou JI
Defects in DNA repair can cause various genetic diseases with severe pathological phenotypes. Fanconi anemia (FA) is a rare disease characterized by bone marrow failure, developmental abnormalities, and increased cancer risk that is caused by defective repair of DNA interstrand crosslinks (ICLs). Here, we identify the deubiquitylating enzyme USP48 as synthetic viable for FA-gene deficiencies by performing genome-wide loss-of-function screens across a panel of human haploid isogenic FA-defective cells (FANCA, FANCC, FANCG, FANCI, FANCD2). Thus, as compared to FA-defective cells alone, FA-deficient cells additionally lacking USP48 are less sensitive to genotoxic stress induced by ICL agents and display enhanced, BRCA1-dependent, clearance of DNA damage. Consequently, USP48 inactivation reduces chromosomal instability of FA-defective cells. Our results highlight a role for USP48 in controlling DNA repair and suggest it as a potential target that could be therapeutically exploited for FA.
PMID: 29891926 [PubMed - in process]
The budding yeast RSC complex maintains ploidy by promoting spindle pole body insertion.
J Cell Biol. 2018 Jun 06;:
Authors: Sing TL, Hung MP, Ohnuki S, Suzuki G, San Luis BJ, McClain M, Unruh JR, Yu Z, Ou J, Marshall-Sheppard J, Huh WK, Costanzo M, Boone C, Ohya Y, Jaspersen SL, Brown GW
Ploidy is tightly regulated in eukaryotic cells and is critical for cell function and survival. Cells coordinate multiple pathways to ensure replicated DNA is segregated accurately to prevent abnormal changes in chromosome number. In this study, we characterize an unanticipated role for the Saccharomyces cerevisiae "remodels the structure of chromatin" (RSC) complex in ploidy maintenance. We show that deletion of any of six nonessential RSC genes causes a rapid transition from haploid to diploid DNA content because of nondisjunction events. Diploidization is accompanied by diagnostic changes in cell morphology and is stably maintained without further ploidy increases. We find that RSC promotes chromosome segregation by facilitating spindle pole body (SPB) duplication. More specifically, RSC plays a role in distributing two SPB insertion factors, Nbp1 and Ndc1, to the new SPB. Thus, we provide insight into a role for a SWI/SNF family complex in SPB duplication and ploidy maintenance.
PMID: 29875260 [PubMed - as supplied by publisher]
Transfer learning for biomedical named entity recognition with neural networks.
Bioinformatics. 2018 Jun 01;:
Authors: Giorgi JM, Bader GD
Motivation: The explosive increase of biomedical literature has made information extraction an increasingly important tool for biomedical research. A fundamental task is the recognition of biomedical named entities in text (BNER) such as genes/proteins, diseases, and species. Recently, a domain-independent method based on deep learning and statistical word embeddings, called long short-term memory network-conditional random field (LSTM-CRF), has been shown to outperform state-of-the-art entity-specific BNER tools. However, this method is dependent on gold-standard corpora (GSCs) consisting of hand-labeled entities, which tend to be small but highly reliable. An alternative to GSCs are silver-standard corpora (SSCs), which are generated by harmonizing the annotations made by several automatic annotation systems. SSCs typically contain more noise than GSCs but have the advantage of containing many more training examples. Ideally, these corpora could be combined to achieve the benefits of both, which is an opportunity for transfer learning. In this work, we analyze to what extent transfer learning improves upon state-of-the-art results for BNER.
Results: We demonstrate that transferring a deep neural network (DNN) trained on a large, noisy SSC to a smaller, but more reliable GSC significantly improves upon state-of-the-art results for BNER. Compared to a state-of-the-art baseline evaluated on 23 GSCs covering four different entity classes, transfer learning results in an average reduction in error of approximately 11%. We found transfer learning to be especially beneficial for target data sets with a small number of labels (approximately 6000 or less).
Availability and implementation: Source code for the LSTM-CRF is available athttps://github.com/Franck-Dernoncourt/NeuroNER/ and links to the corpora are available athttps://github.com/BaderLab/Transfer-Learning-BNER-Bioinformatics-2018/.
Supplementary information: Supplementary data are available at Bioinformatics online.
PMID: 29868832 [PubMed - as supplied by publisher]