1
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Banerjee P, Mehta AR, Nirujogi RS, Cooper J, James OG, Nanda J, Longden J, Burr K, McDade K, Salzinger A, Paza E, Newton J, Story D, Pal S, Smith C, Alessi DR, Selvaraj BT, Priller J, Chandran S. Cell-autonomous immune dysfunction driven by disrupted autophagy in C9orf72-ALS iPSC-derived microglia contributes to neurodegeneration. Sci Adv 2023; 9:eabq0651. [PMID: 37083530 PMCID: PMC10121169 DOI: 10.1126/sciadv.abq0651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Accepted: 03/20/2023] [Indexed: 05/03/2023]
Abstract
Although microglial activation is widely found in amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), the underlying mechanism(s) are poorly understood. Here, using human-induced pluripotent stem cell-derived microglia-like cells (hiPSC-MG) harboring the most common ALS/FTD mutation (C9orf72, mC9-MG), gene-corrected isogenic controls (isoC9-MG), and C9orf72 knockout hiPSC-MG (C9KO-MG), we show that reduced C9ORF72 protein is associated with impaired phagocytosis and an exaggerated immune response upon stimulation with lipopolysaccharide. Analysis of the C9ORF72 interactome revealed that C9ORF72 interacts with regulators of autophagy and functional studies showed impaired initiation of autophagy in mC9-MG and C9KO-MG. Coculture studies with motor neurons (MNs) demonstrated that the autophagy deficit in mC9-MG drives increased vulnerability of mC9-MNs to excitotoxic stimulus. Pharmacological activation of autophagy ameliorated both cell-autonomous functional deficits in hiPSC-MG and MN death in MG-MN coculture. Together, these findings reveal an important role for C9ORF72 in regulating immune homeostasis and identify dysregulation in myeloid cells as a contributor to neurodegeneration in ALS/FTD.
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Affiliation(s)
- Poulomi Banerjee
- UK Dementia Research Institute at University of Edinburgh, University of Edinburgh, Edinburgh bioQuarter, Chancellor’s Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
- Euan MacDonald Centre for MND Research, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Arpan R. Mehta
- UK Dementia Research Institute at University of Edinburgh, University of Edinburgh, Edinburgh bioQuarter, Chancellor’s Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
- Euan MacDonald Centre for MND Research, University of Edinburgh, Edinburgh EH16 4SB, UK
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Raja S. Nirujogi
- Medical Research Council (MRC) Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, Dow Street, Dundee DD1 5EH, UK
| | - James Cooper
- UK Dementia Research Institute at University of Edinburgh, University of Edinburgh, Edinburgh bioQuarter, Chancellor’s Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
- Euan MacDonald Centre for MND Research, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Owen G. James
- UK Dementia Research Institute at University of Edinburgh, University of Edinburgh, Edinburgh bioQuarter, Chancellor’s Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
- Euan MacDonald Centre for MND Research, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Jyoti Nanda
- UK Dementia Research Institute at University of Edinburgh, University of Edinburgh, Edinburgh bioQuarter, Chancellor’s Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
- Euan MacDonald Centre for MND Research, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - James Longden
- UK Dementia Research Institute at University of Edinburgh, University of Edinburgh, Edinburgh bioQuarter, Chancellor’s Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Karen Burr
- UK Dementia Research Institute at University of Edinburgh, University of Edinburgh, Edinburgh bioQuarter, Chancellor’s Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
- Euan MacDonald Centre for MND Research, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Karina McDade
- UK Dementia Research Institute at University of Edinburgh, University of Edinburgh, Edinburgh bioQuarter, Chancellor’s Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
- Edinburgh Brain Bank, Academic Department of Neuropathology, University of Edinburgh, Edinburgh, UK
- Edinburgh Pathology, University of Edinburgh, Edinburgh, UK
| | - Andrea Salzinger
- UK Dementia Research Institute at University of Edinburgh, University of Edinburgh, Edinburgh bioQuarter, Chancellor’s Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
- Euan MacDonald Centre for MND Research, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Evdokia Paza
- UK Dementia Research Institute at University of Edinburgh, University of Edinburgh, Edinburgh bioQuarter, Chancellor’s Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Judith Newton
- Euan MacDonald Centre for MND Research, University of Edinburgh, Edinburgh EH16 4SB, UK
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - David Story
- UK Dementia Research Institute at University of Edinburgh, University of Edinburgh, Edinburgh bioQuarter, Chancellor’s Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
- Euan MacDonald Centre for MND Research, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Suvankar Pal
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
- Euan MacDonald Centre for MND Research, University of Edinburgh, Edinburgh EH16 4SB, UK
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Colin Smith
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
- Euan MacDonald Centre for MND Research, University of Edinburgh, Edinburgh EH16 4SB, UK
- Edinburgh Brain Bank, Academic Department of Neuropathology, University of Edinburgh, Edinburgh, UK
- Edinburgh Pathology, University of Edinburgh, Edinburgh, UK
| | - Dario R. Alessi
- Medical Research Council (MRC) Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, Dow Street, Dundee DD1 5EH, UK
| | - Bhuvaneish T. Selvaraj
- UK Dementia Research Institute at University of Edinburgh, University of Edinburgh, Edinburgh bioQuarter, Chancellor’s Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
- Euan MacDonald Centre for MND Research, University of Edinburgh, Edinburgh EH16 4SB, UK
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Josef Priller
- UK Dementia Research Institute at University of Edinburgh, University of Edinburgh, Edinburgh bioQuarter, Chancellor’s Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
- Department of Psychiatry and Psychotherapy; School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
- Neuropsychiatry, Charité–Universitätsmedizin Berlin and DZNE, Charitéplatz 1, 10117 Berlin, Germany
| | - Siddharthan Chandran
- UK Dementia Research Institute at University of Edinburgh, University of Edinburgh, Edinburgh bioQuarter, Chancellor’s Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
- Euan MacDonald Centre for MND Research, University of Edinburgh, Edinburgh EH16 4SB, UK
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh EH16 4SB, UK
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2
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Rifai OM, Longden J, O'Shaughnessy J, Sewell MDE, Pate J, McDade K, Daniels MJ, Abrahams S, Chandran S, McColl BW, Sibley CR, Gregory JM. Random forest modelling demonstrates microglial and protein misfolding features to be key phenotypic markers in C9orf72-ALS. J Pathol 2022; 258:366-381. [PMID: 36070099 PMCID: PMC9827842 DOI: 10.1002/path.6008] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 08/17/2022] [Accepted: 09/05/2022] [Indexed: 01/19/2023]
Abstract
Clinical heterogeneity observed across patients with amyotrophic lateral sclerosis (ALS) is a known complicating factor in identifying potential therapeutics, even within cohorts with the same mutation, such as C9orf72 hexanucleotide repeat expansions (HREs). Thus, further understanding of pathways underlying this heterogeneity is essential for appropriate ALS trial stratification and the meaningful assessment of clinical outcomes. It has been shown that both inflammation and protein misfolding can influence ALS pathogenesis, such as the manifestation or severity of motor or cognitive symptoms. However, there has yet to be a systematic and quantitative assessment of immunohistochemical markers to interrogate the potential relevance of these pathways in an unbiased manner. To investigate this, we extensively characterised features of commonly used glial activation and protein misfolding stains in thousands of images of post-mortem tissue from a heterogeneous cohort of deeply clinically profiled patients with a C9orf72 HRE. Using a random forest model, we show that microglial staining features are the most accurate classifiers of disease status in our panel and that clinicopathological relationships exist between microglial activation status, TDP-43 pathology, and language dysfunction. Furthermore, we detected spatially resolved changes in fused in sarcoma (FUS) staining, suggesting that liquid-liquid phase shift of this aggregation-prone RNA-binding protein may be important in ALS caused by a C9orf72 HRE. Interestingly, no one feature alone significantly impacted the predictiveness of the model, indicating that the collective examination of all features, or a combination of several features, is what allows the model to be predictive. Our findings provide further support to the hypothesis of dysfunctional immune regulation and proteostasis in the pathogenesis of C9-ALS and provide a framework for digital analysis of commonly used neuropathological stains as a tool to enrich our understanding of clinicopathological relationships within and between cohorts. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
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Affiliation(s)
- Olivia M Rifai
- Translational Neuroscience PhD Programme, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.,Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.,UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK.,Euan MacDonald Centre for Motor Neurone Disease Research, University of Edinburgh, Edinburgh, UK.,Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - James Longden
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Judi O'Shaughnessy
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.,UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK.,Euan MacDonald Centre for Motor Neurone Disease Research, University of Edinburgh, Edinburgh, UK
| | - Michael DE Sewell
- Translational Neuroscience PhD Programme, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.,UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Judith Pate
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.,Euan MacDonald Centre for Motor Neurone Disease Research, University of Edinburgh, Edinburgh, UK
| | - Karina McDade
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.,UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK.,Euan MacDonald Centre for Motor Neurone Disease Research, University of Edinburgh, Edinburgh, UK
| | | | - Sharon Abrahams
- Euan MacDonald Centre for Motor Neurone Disease Research, University of Edinburgh, Edinburgh, UK.,Human Cognitive Neuroscience-Psychology, School of Philosophy, Psychology and Language Sciences, University of Edinburgh, Edinburgh, UK
| | - Siddharthan Chandran
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.,UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK.,Euan MacDonald Centre for Motor Neurone Disease Research, University of Edinburgh, Edinburgh, UK
| | - Barry W McColl
- UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Christopher R Sibley
- Euan MacDonald Centre for Motor Neurone Disease Research, University of Edinburgh, Edinburgh, UK.,Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK.,Institute of Quantitative Biology, Biochemistry and Biotechnology, School of Biological Sciences, University of Edinburgh, Edinburgh, UK.,Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
| | - Jenna M Gregory
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.,UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK.,Euan MacDonald Centre for Motor Neurone Disease Research, University of Edinburgh, Edinburgh, UK.,Institute of Medical Sciences, University of Aberdeen, Aberdeen, UK
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3
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Seeger M, Longden J, Klipp E, Linding R. Deep Hidden Physics Modeling of Cell Signaling Networks. Curr Genomics 2021; 22:239-243. [PMID: 35273456 PMCID: PMC8822227 DOI: 10.2174/1389202922666210614131236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Revised: 03/23/2021] [Accepted: 04/07/2021] [Indexed: 11/22/2022] Open
Abstract
According to the WHO, cancer is the second most common cause of death worldwide.
The social and economic damage caused by cancer is high and rising. In Europe, the annual direct
medical expenses alone amount to more than €129 billion. This results in an urgent need for new
and sustainable therapeutics, which has currently not been met by the pharmaceutical industry; only
3.4% of cancer drugs entering Phase I clinical trials get to market. Phosphorylation sites are parts
of the core machinery of kinase signaling networks, which are known to be dysfunctional in all types
of cancer. Indeed, kinases are the second most common drug target yet. However, these inhibitors
block all functions of a protein, and they commonly lead to the development of resistance and increased
toxicity. To facilitate global and mechanistic modeling of cancer and clinically relevant cell
signaling networks, the community will have to develop sophisticated data-driven deep-learning and
mechanistic computational models that generate in silico probabilistic predictions of molecular signaling
network rearrangements causally implicated in cancer.
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Affiliation(s)
- Martin Seeger
- Rewire Tx, Humboldt- Universitätzu Berlin, Invalidenstr. 42, 10115 Berlin, Germany
| | - James Longden
- Rewire Tx, Humboldt- Universitätzu Berlin, Invalidenstr. 42, 10115 Berlin, Germany
| | - Edda Klipp
- Rewire Tx, Humboldt- Universitätzu Berlin, Invalidenstr. 42, 10115 Berlin, Germany
| | - Rune Linding
- Rewire Tx, Humboldt- Universitätzu Berlin, Invalidenstr. 42, 10115 Berlin, Germany
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4
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Marwick JA, Elliott RJR, Longden J, Makda A, Hirani N, Dhaliwal K, Dawson JC, Carragher NO. Application of a High-Content Screening Assay Utilizing Primary Human Lung Fibroblasts to Identify Antifibrotic Drugs for Rapid Repurposing in COVID-19 Patients. SLAS Discov 2021; 26:1091-1106. [PMID: 34078171 PMCID: PMC8458684 DOI: 10.1177/24725552211019405] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Lung imaging and autopsy reports among COVID-19 patients show elevated lung scarring (fibrosis). Early data from COVID-19 patients as well as previous studies from severe acute respiratory syndrome, Middle East respiratory syndrome, and other respiratory disorders show that the extent of lung fibrosis is associated with a higher mortality, prolonged ventilator dependence, and poorer long-term health prognosis. Current treatments to halt or reverse lung fibrosis are limited; thus, the rapid development of effective antifibrotic therapies is a major global medical need that will continue far beyond the current COVID-19 pandemic. Reproducible fibrosis screening assays with high signal-to-noise ratios and disease-relevant readouts such as extracellular matrix (ECM) deposition (the hallmark of fibrosis) are integral to any antifibrotic therapeutic development. Therefore, we have established an automated high-throughput and high-content primary screening assay measuring transforming growth factor-β (TGFβ)-induced ECM deposition from primary human lung fibroblasts in a 384-well format. This assay combines longitudinal live cell imaging with multiparametric high-content analysis of ECM deposition. Using this assay, we have screened a library of 2743 small molecules representing approved drugs and late-stage clinical candidates. Confirmed hits were subsequently profiled through a suite of secondary lung fibroblast phenotypic screening assays quantifying cell differentiation, proliferation, migration, and apoptosis. In silico target prediction and pathway network analysis were applied to the confirmed hits. We anticipate this suite of assays and data analysis tools will aid the identification of new treatments to mitigate against lung fibrosis associated with COVID-19 and other fibrotic diseases.
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Affiliation(s)
- John A Marwick
- Cancer Research UK Edinburgh Centre, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.,Centre for Inflammation Research, Queens Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Richard J R Elliott
- Cancer Research UK Edinburgh Centre, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - James Longden
- Center for Clinical Brain Sciences, Chancellors Building, University of Edinburgh, Edinburgh, UK
| | - Ashraff Makda
- Cancer Research UK Edinburgh Centre, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Nik Hirani
- Centre for Inflammation Research, Queens Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Kevin Dhaliwal
- Centre for Inflammation Research, Queens Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - John C Dawson
- Cancer Research UK Edinburgh Centre, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Neil O Carragher
- Cancer Research UK Edinburgh Centre, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
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5
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Madsen RR, Longden J, Knox RG, Robin X, Völlmy F, Macleod KG, Moniz LS, Carragher NO, Linding R, Vanhaesebroeck B, Semple RK. NODAL/TGFβ signalling mediates the self-sustained stemness induced by PIK3CAH1047R homozygosity in pluripotent stem cells. Dis Model Mech 2021; 14:dmm048298. [PMID: 33514588 PMCID: PMC7969366 DOI: 10.1242/dmm.048298] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Accepted: 01/20/2021] [Indexed: 12/13/2022] Open
Abstract
Activating PIK3CA mutations are known 'drivers' of human cancer and developmental overgrowth syndromes. We recently demonstrated that the 'hotspot' PIK3CAH1047R variant exerts unexpected allele dose-dependent effects on stemness in human pluripotent stem cells (hPSCs). In this study, we combine high-depth transcriptomics, total proteomics and reverse-phase protein arrays to reveal potentially disease-related alterations in heterozygous cells, and to assess the contribution of activated TGFβ signalling to the stemness phenotype of homozygous PIK3CAH1047R cells. We demonstrate signalling rewiring as a function of oncogenic PI3K signalling strength, and provide experimental evidence that self-sustained stemness is causally related to enhanced autocrine NODAL/TGFβ signalling. A significant transcriptomic signature of TGFβ pathway activation in heterozygous PIK3CAH1047R was observed but was modest and was not associated with the stemness phenotype seen in homozygous mutants. Notably, the stemness gene expression in homozygous PIK3CAH1047R hPSCs was reversed by pharmacological inhibition of NODAL/TGFβ signalling, but not by pharmacological PI3Kα pathway inhibition. Altogether, this provides the first in-depth analysis of PI3K signalling in hPSCs and directly links strong PI3K activation to developmental NODAL/TGFβ signalling. This work illustrates the importance of allele dosage and expression when artificial systems are used to model human genetic disease caused by activating PIK3CA mutations. This article has an associated First Person interview with the first author of the paper.
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Affiliation(s)
- Ralitsa R. Madsen
- Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh EH16 4TJ, UK
- Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge CB2 0QQ, UK
- The National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge CB2 0QQ, UK
| | - James Longden
- Biotech Research and Innovation Centre, University of Copenhagen, DK-2200 Copenhagen, Denmark
- Theoretical Biophysics, Institute of Biology, Humboldt-Universität zu Berlin, 10115Berlin, Germany
| | - Rachel G. Knox
- Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge CB2 0QQ, UK
- The National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge CB2 0QQ, UK
| | - Xavier Robin
- Biotech Research and Innovation Centre, University of Copenhagen, DK-2200 Copenhagen, Denmark
| | - Franziska Völlmy
- Biotech Research and Innovation Centre, University of Copenhagen, DK-2200 Copenhagen, Denmark
| | - Kenneth G. Macleod
- Edinburgh Cancer Research UK Centre, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road South, Edinburgh EH4 2XR, UK
| | - Larissa S. Moniz
- University College London Cancer Institute, Paul O'Gorman Building, University College London, London WC1E 6BT, UK
| | - Neil O. Carragher
- Edinburgh Cancer Research UK Centre, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road South, Edinburgh EH4 2XR, UK
| | - Rune Linding
- Biotech Research and Innovation Centre, University of Copenhagen, DK-2200 Copenhagen, Denmark
- Theoretical Biophysics, Institute of Biology, Humboldt-Universität zu Berlin, 10115Berlin, Germany
| | - Bart Vanhaesebroeck
- University College London Cancer Institute, Paul O'Gorman Building, University College London, London WC1E 6BT, UK
| | - Robert K. Semple
- Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh EH16 4TJ, UK
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6
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Longden J, Robin X, Engel M, Ferkinghoff-Borg J, Kjær I, Horak ID, Pedersen MW, Linding R. Deep neural networks identify signaling mechanisms of ErbB-family drug resistance from a continuous cell morphology space. Cell Rep 2021; 34:108657. [PMID: 33472071 DOI: 10.1016/j.celrep.2020.108657] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2018] [Revised: 01/20/2020] [Accepted: 12/28/2020] [Indexed: 01/21/2023] Open
Abstract
It is well known that the development of drug resistance in cancer cells can lead to changes in cell morphology. Here, we describe the use of deep neural networks to analyze this relationship, demonstrating that complex cell morphologies can encode states of signaling networks and unravel cellular mechanisms hidden to conventional approaches. We perform high-content screening of 17 cancer cell lines, generating more than 500 billion data points from ∼850 million cells. We analyze these data using a deep learning model, resulting in the identification of a continuous 27-dimension space describing all of the observed cell morphologies. From its morphology alone, we could thus predict whether a cell was resistant to ErbB-family drugs, with an accuracy of 74%, and predict the potential mechanism of resistance, subsequently validating the role of MET and insulin-like growth factor 1 receptor (IGF1R) as drivers of cetuximab resistance in in vitro models of lung and head/neck cancer.
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Affiliation(s)
- James Longden
- Biotech Research & Innovation Centre, University of Copenhagen, Copenhagen, 2200, Denmark.
| | - Xavier Robin
- Biotech Research & Innovation Centre, University of Copenhagen, Copenhagen, 2200, Denmark
| | - Mathias Engel
- Biotech Research & Innovation Centre, University of Copenhagen, Copenhagen, 2200, Denmark; Niels Bohr Institute, University of Copenhagen, Copenhagen, 2200, Denmark
| | | | - Ida Kjær
- Symphogen A/S, Ballerup, 2750, Denmark
| | | | | | - Rune Linding
- Biotech Research & Innovation Centre, University of Copenhagen, Copenhagen, 2200, Denmark; Theoretical Biophysics, Humboldt-Universität zu Berlin, Berlin, 10115, Germany; Rewire Tx, Humboldt-Universität zu Berlin, Berlin, 10115, Germany.
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7
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Engel M, Longden J, Ferkinghoff-Borg J, Robin X, Saginc G, Linding R. Bowhead: Bayesian modelling of cell velocity during concerted cell migration. PLoS Comput Biol 2018; 14:e1005900. [PMID: 29309407 PMCID: PMC5774831 DOI: 10.1371/journal.pcbi.1005900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2017] [Revised: 01/19/2018] [Accepted: 11/27/2017] [Indexed: 11/28/2022] Open
Abstract
Cell migration is a central biological process that requires fine coordination of molecular events in time and space. A deregulation of the migratory phenotype is also associated with pathological conditions including cancer where cell motility has a causal role in tumor spreading and metastasis formation. Thus cell migration is of critical and strategic importance across the complex disease spectrum as well as for the basic understanding of cell phenotype. Experimental studies of the migration of cells in monolayers are often conducted with 'wound healing' assays. Analysis of these assays has traditionally relied on how the wound area changes over time. However this method does not take into account the shape of the wound. Given the many options for creating a wound healing assay and the fact that wound shape invariably changes as cells migrate this is a significant flaw. Here we present a novel software package for analyzing concerted cell velocity in wound healing assays. Our method encompasses a wound detection algorithm based on cell confluency thresholding and employs a Bayesian approach in order to estimate concerted cell velocity with an associated likelihood. We have applied this method to study the effect of siRNA knockdown on the migration of a breast cancer cell line and demonstrate that cell velocity can track wound healing independently of wound shape and provides a more robust quantification with significantly higher signal to noise ratios than conventional analyses of wound area. The software presented here will enable other researchers in any field of cell biology to quantitatively analyze and track live cell migratory processes and is therefore expected to have a significant impact on the study of cell migration, including cancer relevant processes. Installation instructions, documentation and source code can be found at http://bowhead.lindinglab.science licensed under GPLv3.
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Affiliation(s)
- Mathias Engel
- Biotech Research and Innovation Centre, University of Copenhagen, Copenhagen, Denmark
- Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark
| | - James Longden
- Biotech Research and Innovation Centre, University of Copenhagen, Copenhagen, Denmark
| | | | - Xavier Robin
- Biotech Research and Innovation Centre, University of Copenhagen, Copenhagen, Denmark
| | - Gaye Saginc
- Biotech Research and Innovation Centre, University of Copenhagen, Copenhagen, Denmark
| | - Rune Linding
- Biotech Research and Innovation Centre, University of Copenhagen, Copenhagen, Denmark
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8
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Creixell P, Schoof EM, Simpson CD, Longden J, Miller CJ, Lou HJ, Perryman L, Cox TR, Zivanovic N, Palmeri A, Wesolowska-Andersen A, Helmer-Citterich M, Ferkinghoff-Borg J, Itamochi H, Bodenmiller B, Erler JT, Turk BE, Linding R. Kinome-wide decoding of network-attacking mutations rewiring cancer signaling. Cell 2015; 163:202-17. [PMID: 26388441 PMCID: PMC4644236 DOI: 10.1016/j.cell.2015.08.056] [Citation(s) in RCA: 100] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2014] [Revised: 04/09/2015] [Accepted: 08/12/2015] [Indexed: 12/17/2022]
Abstract
Cancer cells acquire pathological phenotypes through accumulation of mutations that perturb signaling networks. However, global analysis of these events is currently limited. Here, we identify six types of network-attacking mutations (NAMs), including changes in kinase and SH2 modulation, network rewiring, and the genesis and extinction of phosphorylation sites. We developed a computational platform (ReKINect) to identify NAMs and systematically interpreted the exomes and quantitative (phospho-)proteomes of five ovarian cancer cell lines and the global cancer genome repository. We identified and experimentally validated several NAMs, including PKCγ M501I and PKD1 D665N, which encode specificity switches analogous to the appearance of kinases de novo within the kinome. We discover mutant molecular logic gates, a drift toward phospho-threonine signaling, weakening of phosphorylation motifs, and kinase-inactivating hotspots in cancer. Our method pinpoints functional NAMs, scales with the complexity of cancer genomes and cell signaling, and may enhance our capability to therapeutically target tumor-specific networks. Mutations perturbing signaling networks are systematically classified and interpreted Several such functional mutations are identified in cancer and experimentally validated The results suggest that a single point mutant can have profound signaling effects Systematic interpretation of genomic data may assist future precision-medicine efforts
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Affiliation(s)
- Pau Creixell
- Department of Systems Biology, Technical University of Denmark, 2800 Lyngby, Denmark
| | - Erwin M Schoof
- Department of Systems Biology, Technical University of Denmark, 2800 Lyngby, Denmark
| | - Craig D Simpson
- Biotech Research and Innovation Centre (BRIC), University of Copenhagen (UCPH), 2200 Copenhagen, Denmark
| | - James Longden
- Biotech Research and Innovation Centre (BRIC), University of Copenhagen (UCPH), 2200 Copenhagen, Denmark
| | - Chad J Miller
- Department of Pharmacology, Yale University School of Medicine, New Haven, CT 06520, USA
| | - Hua Jane Lou
- Department of Pharmacology, Yale University School of Medicine, New Haven, CT 06520, USA
| | - Lara Perryman
- Biotech Research and Innovation Centre (BRIC), University of Copenhagen (UCPH), 2200 Copenhagen, Denmark
| | - Thomas R Cox
- Biotech Research and Innovation Centre (BRIC), University of Copenhagen (UCPH), 2200 Copenhagen, Denmark
| | - Nevena Zivanovic
- Institute of Molecular Life Sciences, University of Zurich, 8057 Zurich, Switzerland
| | - Antonio Palmeri
- Centre for Molecular Bioinformatics, University of Rome Tor Vergata, 00133 Rome, Italy
| | | | | | - Jesper Ferkinghoff-Borg
- Biotech Research and Innovation Centre (BRIC), University of Copenhagen (UCPH), 2200 Copenhagen, Denmark
| | | | - Bernd Bodenmiller
- Institute of Molecular Life Sciences, University of Zurich, 8057 Zurich, Switzerland
| | - Janine T Erler
- Biotech Research and Innovation Centre (BRIC), University of Copenhagen (UCPH), 2200 Copenhagen, Denmark
| | - Benjamin E Turk
- Department of Pharmacology, Yale University School of Medicine, New Haven, CT 06520, USA
| | - Rune Linding
- Department of Systems Biology, Technical University of Denmark, 2800 Lyngby, Denmark; Biotech Research and Innovation Centre (BRIC), University of Copenhagen (UCPH), 2200 Copenhagen, Denmark.
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9
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Robin X, Creixell P, Radetskaya O, Santini CC, Longden J, Linding R. Personalized network-based treatments in oncology. Clin Pharmacol Ther 2013; 94:646-50. [PMID: 23995267 DOI: 10.1038/clpt.2013.171] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2013] [Accepted: 08/16/2013] [Indexed: 11/09/2022]
Abstract
Network medicine aims at unraveling cell signaling networks to propose personalized treatments for patients suffering from complex diseases. In this short review, we show the relevance of network medicine to cancer treatment by outlining the potential convergence points of the most recent technological and scientific developments in both drug design and signaling network analysis.
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Affiliation(s)
- X Robin
- Cellular Signal Integration Group (C-SIG), Center for Biological Sequence Analysis (CBS), Department of Systems Biology, Technical University of Denmark (DTU), Lyngby, Denmark
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10
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Kiss DL, Longden J, Fechner GA, Avery VM. The functional antagonist Met-RANTES: a modified agonist that induces differential CCR5 trafficking. Cell Mol Biol Lett 2009; 14:537-47. [PMID: 19448977 PMCID: PMC6275935 DOI: 10.2478/s11658-009-0017-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2008] [Accepted: 05/06/2009] [Indexed: 11/20/2022] Open
Abstract
CC chemokine receptor 5 (CCR5) is a pro-inflammatory chemokine receptor that is expressed on cells of the immune system, and specializes in cell migration in response to inflammation and tissue damage. Due to its key role in cell communication and migration, this receptor is involved in various inflammatory and autoimmune diseases, in addition to HIV infection. Met-RANTES is a modified CCR5 ligand that has previously been shown to antagonize CCR5 activation and function in response to its natural ligands in vitro. In vivo, Met-RANTES is able to reduce inflammation in models of induced inflammatory and autoimmune diseases. However, due to the fact that Met-RANTES is also capable of partial agonist activity regarding receptor signaling and internalization, it is clear that Met-RANTES does not function as a conventional receptor antagonist. To further elucidate the effect of Met-RANTES on CCR5, receptor trafficking was investigated in a CHO-CCR5-GFP cell line using the Opera confocal plate reader. The internalization response of CCR5 was quantified, and showed that Met-RANTES internalized CCR5 in a slower, less potent manner than the agonists CCL3 and CCL5. Fluorescent organelle labeling and live cell imaging showed CCL3 and CCL5 caused CCR5 to traffic through sorting endosomes, recycling endosomes and the Golgi apparatus. In contrast, Met-RANTES caused CCR5 to traffic through sorting endosomes and the Golgi apparatus in a manner that was independent of recycling endosomes. As receptor trafficking impacts on cell surface expression and the ability of the receptor to respond to more ligand, this information may indicate an alternative regulation of CCR5 by Met-RANTES that allows the modified ligand to reduce inflammation through stimulation of a pro-inflammatory receptor.
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Affiliation(s)
- Debra L. Kiss
- Discovery Biology, Eskitis Institute for Cell and Molecular Therapies, Brisbane Innovation Park, Griffith University, Don Young Road, Nathan, QLD 4111 Australia
| | - James Longden
- Discovery Biology, Eskitis Institute for Cell and Molecular Therapies, Brisbane Innovation Park, Griffith University, Don Young Road, Nathan, QLD 4111 Australia
| | - Gregory A. Fechner
- Discovery Biology, Eskitis Institute for Cell and Molecular Therapies, Brisbane Innovation Park, Griffith University, Don Young Road, Nathan, QLD 4111 Australia
| | - Vicky M. Avery
- Discovery Biology, Eskitis Institute for Cell and Molecular Therapies, Brisbane Innovation Park, Griffith University, Don Young Road, Nathan, QLD 4111 Australia
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11
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Kamath P, Longden J, Stack C, Mayer A. A randomised prospective trial to compare the efficacy of bolus versus continuous nasogastric feeding in paediatric intensive care. Crit Care 2009. [PMCID: PMC4084028 DOI: 10.1186/cc7306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
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12
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Davis RA, Barnes EC, Longden J, Avery VM, Healy PC. Isolation, structure elucidation and cytotoxic evaluation of endiandrin B from the Australian rainforest plant Endiandra anthropophagorum. Bioorg Med Chem 2008; 17:1387-92. [PMID: 19138858 DOI: 10.1016/j.bmc.2008.12.030] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2008] [Revised: 12/03/2008] [Accepted: 12/05/2008] [Indexed: 11/30/2022]
Abstract
Chemical investigations of the DCM extract from the roots of Endiandra anthropophagorum resulted in the isolation of a new cyclobutane lignan endiandrin B (1), together with the known natural products, endiandrin A (2), and (-)-dihydroguaiaretic acid (3). The structure of 1 was determined by extensive spectroscopic analyses, and confirmed by single crystal X-ray crystallography. Methylation of 1 using diazomethane afforded the previously reported natural product, cinbalansan (4). All compounds were evaluated for their cytotoxicity towards human lung carcinoma cells (A549) using high-content screening. (-)-Dihydroguaiaretic acid (3) was found to be the most potent cytotoxin against the A549 lung carcinoma cell line, with an IC(50) value of 7.49 microM.
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Affiliation(s)
- Rohan A Davis
- Eskitis Institute for Cell and Molecular Therapies, Griffith University, Brisbane, QLD 4111, Australia.
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13
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Davis RA, Longden J, Avery VM, Healy PC. The isolation, structure determination and cytotoxicity of the new fungal metabolite, trichodermamide C. Bioorg Med Chem Lett 2008; 18:2836-9. [DOI: 10.1016/j.bmcl.2008.03.090] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2008] [Revised: 03/27/2008] [Accepted: 03/31/2008] [Indexed: 11/16/2022]
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Purvis OW, Longden J, Shaw G, Chimonides PDJ, Jeffries TE, Jones GC, Mikhailova IN, Williamson BJ. Biogeochemical signatures in the lichen Hypogymnia physodes in the mid Urals. J Environ Radioact 2006; 90:151-62. [PMID: 16887244 DOI: 10.1016/j.jenvrad.2006.06.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/20/2006] [Revised: 06/14/2006] [Accepted: 06/18/2006] [Indexed: 05/11/2023]
Abstract
Multi-element content and uranium (U) isotopes were investigated in the lichen Hypogymnia physodes (native and transplants) sampled across a 60-km transect, centred on Karabash smelter town, from Turgoyak Lake (SW) to Kyshtym (NE) to investigate the origin of U. Kyshtym was the site of a major nuclear accident in 1957. (234)U/(238)U activity ratios in native thalli sampled during July 2001 were within the natural isotopic ratio in minerals. Uranium/thorium (U/Th) ratios were higher in native thalli towards the NE (average 0.73) than those in the SW (average 0.57). Element signatures in native thalli and transplants suggest U was derived from fossil fuel combustion from Karabash and sources lying further to the east. Systematic and significant U enrichment indicative of a nuclear fuel cycle source was not detected in any sample. Element signatures in epiphytic lichen transplants and native thalli provide a powerful method to evaluate U deposition.
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Affiliation(s)
- O W Purvis
- Department of Botany, Natural History Museum, Cromwell Road, London SW7 5BD, UK.
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