60 research outputs found

    Clustering phenotype populations by genome-wide RNAi and multiparametric imaging

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    How to predict gene function from phenotypic cues is a longstanding question in biology.Using quantitative multiparametric imaging, RNAi-mediated cell phenotypes were measured on a genome-wide scale.On the basis of phenotypic ‘neighbourhoods', we identified previously uncharacterized human genes as mediators of the DNA damage response pathway and the maintenance of genomic integrity.The phenotypic map is provided as an online resource at http://www.cellmorph.org for discovering further functional relationships for a broad spectrum of biological modul

    Modeling the cognitive effects of diet discontinuation in adults with phenylketonuria (PKU) using pegvaliase therapy in PAH-deficient mice

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    Existing phenylalanine hydroxylase (PAH)-deficient mice strains are useful models of untreated or late-treated human phenylketonuria (PKU), as most contemporary therapies can only be initiated after weaning and the pups have already suffered irreversible consequences of chronic hyperphenylalaninemia (HPA) during early brain development. Therefore, we sought to evaluate whether enzyme substitution therapy with pegvaliase initiated near birth and administered repetitively to C57Bl/6-Pahenu2/enu2 mice would prevent HPA-related behavioral and cognitive deficits and form a model for early-treated PKU. The main results of three reported experiments are: 1) lifelong weekly pegvaliase treatment prevented the cognitive deficits associated with HPA in contrast to persisting deficits in mice treated with pegvaliase only as adults. 2) Cognitive deficits reappear in mice treated with weekly pegvaliase from birth but in which pegvaliase is discontinued at 3 months age. 3) Twice weekly pegvaliase injection also prevented cognitive deficits but again cognitive deficits emerged in early-treated animals following discontinuation of pegvaliase treatment during adulthood, particularly in females. In all studies, pegvaliase treatment was associated with complete correction of brain monoamine neurotransmitter content and with improved overall growth of the mice as measured by body weight. Mean total brain weight however remained low in all PAH deficient mice regardless of treatment. Application of enzyme substitution therapy with pegvaliase, initiated near birth and continued into adulthood, to PAH-deficient Pahenu2/enu2 mice models contemporary early-treated human PKU. This model will be useful for exploring the differential pathophysiologic effects of HPA at different developmental stages of the murine brain. Keywords: Behavior; Cognition; Dopamine; Hyperphenylalaninemia; Pegvaliase; Phenylalanine hydroxylase; Phenylketonuria; Serotonin; Tryptophan; Tryptophan hydroxylase; Tyrosine; Tyrosine hydroxylase

    MUC1 alters oncogenic events and transcription in human breast cancer cells

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    INTRODUCTION: MUC1 is an oncoprotein whose overexpression correlates with aggressiveness of tumors and poor survival of cancer patients. Many of the oncogenic effects of MUC1 are believed to occur through interaction of its cytoplasmic tail with signaling molecules. As expected for a protein with oncogenic functions, MUC1 is linked to regulation of proliferation, apoptosis, invasion, and transcription. METHODS: To clarify the role of MUC1 in cancer, we transfected two breast cancer cell lines (MDA-MB-468 and BT-20) with small interfering (si)RNA directed against MUC1 and analyzed transcriptional responses and oncogenic events (proliferation, apoptosis and invasion). RESULTS: Transcription of several genes was altered after transfection of MUC1 siRNA, including decreased MAP2K1 (MEK1), JUN, PDGFA, CDC25A, VEGF and ITGAV (integrin α(v)), and increased TNF, RAF1, and MMP2. Additional changes were seen at the protein level, such as increased expression of c-Myc, heightened phosphorylation of AKT, and decreased activation of MEK1/2 and ERK1/2. These were correlated with cellular events, as MUC1 siRNA in the MDA-MB-468 line decreased proliferation and invasion, and increased stress-induced apoptosis. Intriguingly, BT-20 cells displayed similar levels of apoptosis regardless of siRNA, and actually increased proliferation after MUC1 siRNA. CONCLUSION: These results further the growing knowledge of the role of MUC1 in transcription, and suggest that the regulation of MUC1 in breast cancer may be more complex than previously appreciated. The differences between these two cell lines emphasize the importance of understanding the context of cell-specific signaling events when analyzing the oncogenic functions of MUC1, and caution against generalizing the results of individual cell lines without adequate confirmation in intact biological systems

    Sequencing of prostate cancers identifies new cancer genes, routes of progression and drug targets

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    Prostate cancer represents a substantial clinical challenge because it is difficult to predict outcome and advanced disease is often fatal. We sequenced the whole genomes of 112 primary and metastatic prostate cancer samples. From joint analysis of these cancers with those from previous studies (930 cancers in total), we found evidence for 22 previously unidentified putative driver genes harboring coding mutations, as well as evidence for NEAT1 and FOXA1 acting as drivers through noncoding mutations. Through the temporal dissection of aberrations, we identified driver mutations specifically associated with steps in the progression of prostate cancer, establishing, for example, loss of CHD1 and BRCA2 as early events in cancer development of ETS fusion-negative cancers. Computational chemogenomic (canSAR) analysis of prostate cancer mutations identified 11 targets of approved drugs, 7 targets of investigational drugs, and 62 targets of compounds that may be active and should be considered candidates for future clinical trials

    A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns.

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    In cancer, the primary tumour's organ of origin and histopathology are the strongest determinants of its clinical behaviour, but in 3% of cases a patient presents with a metastatic tumour and no obvious primary. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we train a deep learning classifier to predict cancer type based on patterns of somatic passenger mutations detected in whole genome sequencing (WGS) of 2606 tumours representing 24 common cancer types produced by the PCAWG Consortium. Our classifier achieves an accuracy of 91% on held-out tumor samples and 88% and 83% respectively on independent primary and metastatic samples, roughly double the accuracy of trained pathologists when presented with a metastatic tumour without knowledge of the primary. Surprisingly, adding information on driver mutations reduced accuracy. Our results have clinical applicability, underscore how patterns of somatic passenger mutations encode the state of the cell of origin, and can inform future strategies to detect the source of circulating tumour DNA

    Analysis of the genetic phylogeny of multifocal prostate cancer identifies multiple independent clonal expansions in neoplastic and morphologically normal prostate tissue.

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    Genome-wide DNA sequencing was used to decrypt the phylogeny of multiple samples from distinct areas of cancer and morphologically normal tissue taken from the prostates of three men. Mutations were present at high levels in morphologically normal tissue distant from the cancer, reflecting clonal expansions, and the underlying mutational processes at work in morphologically normal tissue were also at work in cancer. Our observations demonstrate the existence of ongoing abnormal mutational processes, consistent with field effects, underlying carcinogenesis. This mechanism gives rise to extensive branching evolution and cancer clone mixing, as exemplified by the coexistence of multiple cancer lineages harboring distinct ERG fusions within a single cancer nodule. Subsets of mutations were shared either by morphologically normal and malignant tissues or between different ERG lineages, indicating earlier or separate clonal cell expansions. Our observations inform on the origin of multifocal disease and have implications for prostate cancer therapy in individual cases

    Exome-wide association study to identify rare variants influencing COVID-19 outcomes : Results from the Host Genetics Initiative

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    Publisher Copyright: Copyright: © 2022 Butler-Laporte et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Host genetics is a key determinant of COVID-19 outcomes. Previously, the COVID-19 Host Genetics Initiative genome-wide association study used common variants to identify multiple loci associated with COVID-19 outcomes. However, variants with the largest impact on COVID-19 outcomes are expected to be rare in the population. Hence, studying rare variants may provide additional insights into disease susceptibility and pathogenesis, thereby informing therapeutics development. Here, we combined whole-exome and whole-genome sequencing from 21 cohorts across 12 countries and performed rare variant exome-wide burden analyses for COVID-19 outcomes. In an analysis of 5,085 severe disease cases and 571,737 controls, we observed that carrying a rare deleterious variant in the SARS-CoV-2 sensor toll-like receptor TLR7 (on chromosome X) was associated with a 5.3-fold increase in severe disease (95% CI: 2.75–10.05, p = 5.41x10-7). This association was consistent across sexes. These results further support TLR7 as a genetic determinant of severe disease and suggest that larger studies on rare variants influencing COVID-19 outcomes could provide additional insights.Peer reviewe

    Exome-wide association study to identify rare variants influencing COVID-19 outcomes: Results from the Host Genetics Initiative

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    Minimal information for studies of extracellular vesicles (MISEV2023): From basic to advanced approaches

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    Extracellular vesicles (EVs), through their complex cargo, can reflect the state of their cell of origin and change the functions and phenotypes of other cells. These features indicate strong biomarker and therapeutic potential and have generated broad interest, as evidenced by the steady year-on-year increase in the numbers of scientific publications about EVs. Important advances have been made in EV metrology and in understanding and applying EV biology. However, hurdles remain to realising the potential of EVs in domains ranging from basic biology to clinical applications due to challenges in EV nomenclature, separation from non-vesicular extracellular particles, characterisation and functional studies. To address the challenges and opportunities in this rapidly evolving field, the International Society for Extracellular Vesicles (ISEV) updates its 'Minimal Information for Studies of Extracellular Vesicles', which was first published in 2014 and then in 2018 as MISEV2014 and MISEV2018, respectively. The goal of the current document, MISEV2023, is to provide researchers with an updated snapshot of available approaches and their advantages and limitations for production, separation and characterisation of EVs from multiple sources, including cell culture, body fluids and solid tissues. In addition to presenting the latest state of the art in basic principles of EV research, this document also covers advanced techniques and approaches that are currently expanding the boundaries of the field. MISEV2023 also includes new sections on EV release and uptake and a brief discussion of in vivo approaches to study EVs. Compiling feedback from ISEV expert task forces and more than 1000 researchers, this document conveys the current state of EV research to facilitate robust scientific discoveries and move the field forward even more rapidly
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