1
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Watson SS, Duc B, Kang Z, de Tonnac A, Eling N, Font L, Whitmarsh T, Massara M, Bodenmiller B, Hausser J, Joyce JA. Microenvironmental reorganization in brain tumors following radiotherapy and recurrence revealed by hyperplexed immunofluorescence imaging. Nat Commun 2024; 15:3226. [PMID: 38622132 PMCID: PMC11018859 DOI: 10.1038/s41467-024-47185-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 03/22/2024] [Indexed: 04/17/2024] Open
Abstract
The tumor microenvironment plays a crucial role in determining response to treatment. This involves a series of interconnected changes in the cellular landscape, spatial organization, and extracellular matrix composition. However, assessing these alterations simultaneously is challenging from a spatial perspective, due to the limitations of current high-dimensional imaging techniques and the extent of intratumoral heterogeneity over large lesion areas. In this study, we introduce a spatial proteomic workflow termed Hyperplexed Immunofluorescence Imaging (HIFI) that overcomes these limitations. HIFI allows for the simultaneous analysis of > 45 markers in fragile tissue sections at high magnification, using a cost-effective high-throughput workflow. We integrate HIFI with machine learning feature detection, graph-based network analysis, and cluster-based neighborhood analysis to analyze the microenvironment response to radiation therapy in a preclinical model of glioblastoma, and compare this response to a mouse model of breast-to-brain metastasis. Here we show that glioblastomas undergo extensive spatial reorganization of immune cell populations and structural architecture in response to treatment, while brain metastases show no comparable reorganization. Our integrated spatial analyses reveal highly divergent responses to radiation therapy between brain tumor models, despite equivalent radiotherapy benefit.
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Affiliation(s)
- Spencer S Watson
- Department of Oncology, University of Lausanne, Lausanne, Switzerland.
- Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland.
- Agora Cancer Research Center, Lausanne, 1011, Switzerland.
- L. Lundin and Family Brain Tumor Research Center, Departments of Oncology and Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, Lausanne, 1011, Switzerland.
| | - Benoit Duc
- Department of Oncology, University of Lausanne, Lausanne, Switzerland
- Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland
- Agora Cancer Research Center, Lausanne, 1011, Switzerland
- L. Lundin and Family Brain Tumor Research Center, Departments of Oncology and Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, Lausanne, 1011, Switzerland
| | - Ziqi Kang
- Department of Cellular and Molecular Biology, Karolinska Institutet and SciLifeLab, Stockholm, Sweden
| | - Axel de Tonnac
- Department of Cellular and Molecular Biology, Karolinska Institutet and SciLifeLab, Stockholm, Sweden
| | - Nils Eling
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
- Institute for Molecular Health Sciences, ETH Zurich, Zurich, Switzerland
| | - Laure Font
- Department of Oncology, University of Lausanne, Lausanne, Switzerland
- École Polytechnique Fédérale Lausanne, Lausanne, Switzerland
| | - Tristan Whitmarsh
- Machine Intelligence Laboratory, Department of Engineering, University of Cambridge, Cambridge, UK
| | - Matteo Massara
- Department of Oncology, University of Lausanne, Lausanne, Switzerland
- Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland
- Agora Cancer Research Center, Lausanne, 1011, Switzerland
- L. Lundin and Family Brain Tumor Research Center, Departments of Oncology and Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, Lausanne, 1011, Switzerland
| | - Bernd Bodenmiller
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
- Institute for Molecular Health Sciences, ETH Zurich, Zurich, Switzerland
| | - Jean Hausser
- Department of Cellular and Molecular Biology, Karolinska Institutet and SciLifeLab, Stockholm, Sweden
| | - Johanna A Joyce
- Department of Oncology, University of Lausanne, Lausanne, Switzerland.
- Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland.
- Agora Cancer Research Center, Lausanne, 1011, Switzerland.
- L. Lundin and Family Brain Tumor Research Center, Departments of Oncology and Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, Lausanne, 1011, Switzerland.
- Cancer Research UK, Cancer Grand Challenges iMAXT Consortium, University of Cambridge, Cambridge, UK.
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2
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González-Solares EA, Dariush A, González-Fernández C, Küpcü Yoldaş A, Molaeinezhad A, Al Sa’d M, Smith L, Whitmarsh T, Millar N, Chornay N, Falciatori I, Fatemi A, Goodwin D, Kuett L, Mulvey CM, Páez Ribes M, Qosaj F, Roth A, Vázquez-García I, Watson SS, Windhager J, Aparicio S, Bodenmiller B, Boyden E, Caldas C, Harris O, Shah SP, Tavaré S, Bressan D, Hannon GJ, Walton NA. Imaging and Molecular Annotation of Xenographs and Tumours (IMAXT): High throughput data and analysis infrastructure. Biol Imaging 2023; 3:e11. [PMID: 38487685 PMCID: PMC10936408 DOI: 10.1017/s2633903x23000090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 12/21/2022] [Accepted: 03/08/2023] [Indexed: 03/17/2024]
Abstract
With the aim of producing a 3D representation of tumors, imaging and molecular annotation of xenografts and tumors (IMAXT) uses a large variety of modalities in order to acquire tumor samples and produce a map of every cell in the tumor and its host environment. With the large volume and variety of data produced in the project, we developed automatic data workflows and analysis pipelines. We introduce a research methodology where scientists connect to a cloud environment to perform analysis close to where data are located, instead of bringing data to their local computers. Here, we present the data and analysis infrastructure, discuss the unique computational challenges and describe the analysis chains developed and deployed to generate molecularly annotated tumor models. Registration is achieved by use of a novel technique involving spherical fiducial marks that are visible in all imaging modalities used within IMAXT. The automatic pipelines are highly optimized and allow to obtain processed datasets several times quicker than current solutions narrowing the gap between data acquisition and scientific exploitation.
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Affiliation(s)
| | - Ali Dariush
- Institute of Astronomy, University of Cambridge, Cambridge, United Kingdom
- CRUK Cambridge Institute, Li Ka Shing Centre, University of Cambridge, Cambridge, United Kingdom
| | | | | | | | - Mohammad Al Sa’d
- Institute of Astronomy, University of Cambridge, Cambridge, United Kingdom
| | - Leigh Smith
- Institute of Astronomy, University of Cambridge, Cambridge, United Kingdom
| | - Tristan Whitmarsh
- Institute of Astronomy, University of Cambridge, Cambridge, United Kingdom
| | - Neil Millar
- Institute of Astronomy, University of Cambridge, Cambridge, United Kingdom
| | - Nicholas Chornay
- Institute of Astronomy, University of Cambridge, Cambridge, United Kingdom
| | - Ilaria Falciatori
- CRUK Cambridge Institute, Li Ka Shing Centre, University of Cambridge, Cambridge, United Kingdom
| | - Atefeh Fatemi
- CRUK Cambridge Institute, Li Ka Shing Centre, University of Cambridge, Cambridge, United Kingdom
| | - Daniel Goodwin
- McGovern Institute, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
- McGovern Institute, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Laura Kuett
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
- Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
| | - Claire M. Mulvey
- CRUK Cambridge Institute, Li Ka Shing Centre, University of Cambridge, Cambridge, United Kingdom
| | - Marta Páez Ribes
- CRUK Cambridge Institute, Li Ka Shing Centre, University of Cambridge, Cambridge, United Kingdom
| | - Fatime Qosaj
- CRUK Cambridge Institute, Li Ka Shing Centre, University of Cambridge, Cambridge, United Kingdom
| | - Andrew Roth
- Department of Computer Science, University of British Columbia, Vancouver, BC, Canada
| | - Ignacio Vázquez-García
- Herbert and Florence Irving Institute for Cancer Dynamics, Columbia University, New York, NY, USA
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Spencer S. Watson
- Department of Oncology and Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland
| | - Jonas Windhager
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
- Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
| | - Samuel Aparicio
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Bernd Bodenmiller
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
- Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
| | - Ed Boyden
- McGovern Institute, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
- McGovern Institute, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
- Howard Hughes Medical Institute, Department of Physics, Harvard University, Cambridge, MA, USA
- Howard Hughes Medical Institute, Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Carlos Caldas
- CRUK Cambridge Institute, Li Ka Shing Centre, University of Cambridge, Cambridge, United Kingdom
- Cambridge Breast Unit, Addenbrooke’s Hospital, Cambridge University Hospital NHS Foundation Trust and NIHR Cambridge Biomedical Research Centre, Cambridge, United Kingdom
| | | | - Sohrab P. Shah
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Simon Tavaré
- CRUK Cambridge Institute, Li Ka Shing Centre, University of Cambridge, Cambridge, United Kingdom
- Herbert and Florence Irving Institute for Cancer Dynamics, Columbia University, New York, NY, USA
- New York Genome Center, New York, NY, USA
| | | | - Dario Bressan
- CRUK Cambridge Institute, Li Ka Shing Centre, University of Cambridge, Cambridge, United Kingdom
| | - Gregory J. Hannon
- CRUK Cambridge Institute, Li Ka Shing Centre, University of Cambridge, Cambridge, United Kingdom
| | - Nicholas A. Walton
- Institute of Astronomy, University of Cambridge, Cambridge, United Kingdom
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3
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Garay JP, Smith R, Devlin K, Hollern DP, Liby T, Liu M, Boddapati S, Watson SS, Esch A, Zheng T, Thompson W, Babcock D, Kwon S, Chin K, Heiser L, Gray JW, Korkola JE. Sensitivity to targeted therapy differs between HER2-amplified breast cancer cells harboring kinase and helical domain mutations in PIK3CA. Breast Cancer Res 2021; 23:81. [PMID: 34344439 PMCID: PMC8336338 DOI: 10.1186/s13058-021-01457-0] [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] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2021] [Accepted: 07/18/2021] [Indexed: 12/01/2022] Open
Abstract
BACKGROUND HER2-amplified breast cancer is a clinically defined subtype of breast cancer for which there are multiple viable targeted therapies. Resistance to these targeted therapies is a common problem, but the mechanisms by which resistance occurs remain incompletely defined. One mechanism that has been proposed is through mutation of genes in the PI3-kinase pathway. Intracellular signaling from the HER2 pathway can occur through PI3-kinase, and mutations of the encoding gene PIK3CA are known to be oncogenic. Mutations in PIK3CA co-occur with HER2-amplification in ~ 20% of cases within the HER2-amplified subtype. METHODS We generated isogenic knockin mutants of each PIK3CA hotspot mutation in HER2-amplified breast cancer cells using adeno-associated virus-mediated gene targeting. Isogenic clones were analyzed using a combinatorial drug screen to determine differential responses to HER2-targeted therapy. Western blot analysis and immunofluorescence uncovered unique intracellular signaling dynamics in cells resistant to HER2-targeted therapy. Subsequent combinatorial drug screens were used to explore neuregulin-1-mediated resistance to HER2-targeted therapy. Finally, results from in vitro experiments were extrapolated to publicly available datasets. RESULTS Treatment with HER2-targeted therapy reveals that mutations in the kinase domain (H1047R) but not the helical domain (E545K) increase resistance to lapatinib. Mechanistically, sustained AKT signaling drives lapatinib resistance in cells with the kinase domain mutation, as demonstrated by staining for the intracellular product of PI3-kinase, PIP3. This resistance can be overcome by co-treatment with an inhibitor to the downstream kinase AKT. Additionally, knockout of the PIP3 phosphatase, PTEN, phenocopies this result. We also show that neuregulin-1, a ligand for HER-family receptors, confers resistance to cells harboring either hotspot mutation and modulates response to combinatorial therapy. Finally, we show clinical evidence that the hotspot mutations have distinct expression profiles related to therapeutic resistance through analysis of TCGA and METABRIC data cohorts. CONCLUSION Our results demonstrate unique intracellular signaling differences depending on which mutation in PIK3CA the cell harbors. Only mutations in the kinase domain fully activate the PI3-kinase signaling pathway and maintain downstream signaling in the presence of HER2 inhibition. Moreover, we show there is potentially clinical importance in understanding both the PIK3CA mutational status and levels of neuregulin-1 expression in patients with HER2-amplified breast cancer treated with targeted therapy and that these problems warrant further pre-clinical and clinical testing.
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Affiliation(s)
- Joseph P Garay
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
| | - Rebecca Smith
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
| | - Kaylyn Devlin
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
| | - Daniel P Hollern
- Department of Genetics, University of North Carolina, Chapel Hill, Chapel Hill, NC, USA
| | - Tiera Liby
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
| | - Moqing Liu
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
| | - Shanta Boddapati
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
| | - Spencer S Watson
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
| | - Amanda Esch
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
| | - Ting Zheng
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
| | - Wallace Thompson
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
| | - Darcie Babcock
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
| | - Sunjong Kwon
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
| | - Koei Chin
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
| | - Laura Heiser
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
| | - Joe W Gray
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA.
| | - James E Korkola
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA.
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4
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Huang AH, Watson SS, Wang L, Baker BM, Akiyama H, Brigande JV, Schweitzer R. Requirement for scleraxis in the recruitment of mesenchymal progenitors during embryonic tendon elongation. Development 2019; 146:dev.182782. [PMID: 31540914 DOI: 10.1242/dev.182782] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2019] [Accepted: 09/11/2019] [Indexed: 12/16/2022]
Abstract
The transcription factor scleraxis (Scx) is required for tendon development; however, the function of Scx is not fully understood. Although Scx is expressed by all tendon progenitors and cells, only long tendons are disrupted in the Scx -/- mutant; short tendons appear normal and the ability of muscle to attach to skeleton is not affected. We recently demonstrated that long tendons are formed in two stages: first, by muscle anchoring to skeleton via a short tendon anlage; and second, by rapid elongation of the tendon in parallel with skeletal growth. Through lineage tracing, we extend these observations to all long tendons and show that tendon elongation is fueled by recruitment of new mesenchymal progenitors. Conditional loss of Scx in mesenchymal progenitors did not affect the first stage of anchoring; however, new cells were not recruited during elongation and long tendon formation was impaired. Interestingly, for tenocyte recruitment, Scx expression was required only in the recruited cells and not in the recruiting tendon. The phenotype of Scx mutants can thus be understood as a failure of tendon cell recruitment during tendon elongation.
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Affiliation(s)
- Alice H Huang
- Research Division, Shriners Hospital for Children, Portland, OR 97239, USA .,Department of Orthopaedics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Spencer S Watson
- Research Division, Shriners Hospital for Children, Portland, OR 97239, USA
| | - Lingyan Wang
- Oregon Hearing Research Center, Oregon Health & Science University, Portland, OR 97239, USA
| | - Brendon M Baker
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
| | - Haruhiko Akiyama
- Department of Orthopaedics, Gifu University, Gifu City 501-1194, Japan
| | - John V Brigande
- Oregon Hearing Research Center, Oregon Health & Science University, Portland, OR 97239, USA
| | - Ronen Schweitzer
- Research Division, Shriners Hospital for Children, Portland, OR 97239, USA
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5
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Watson SS, Dane M, Chin K, Tatarova Z, Liu M, Liby T, Thompson W, Smith R, Nederlof M, Bucher E, Kilburn D, Whitman M, Sudar D, Mills GB, Heiser LM, Jonas O, Gray JW, Korkola JE. Microenvironment-Mediated Mechanisms of Resistance to HER2 Inhibitors Differ between HER2+ Breast Cancer Subtypes. Cell Syst 2018; 6:329-342.e6. [PMID: 29550255 PMCID: PMC5927625 DOI: 10.1016/j.cels.2018.02.001] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2017] [Revised: 08/16/2017] [Accepted: 02/02/2018] [Indexed: 01/19/2023]
Abstract
Extrinsic signals are implicated in breast cancer resistance to HER2-targeted tyrosine kinase inhibitors (TKIs). To examine how microenvironmental signals influence resistance, we monitored TKI-treated breast cancer cell lines grown on microenvironment microarrays composed of printed extracellular matrix proteins supplemented with soluble proteins. We tested ~2,500 combinations of 56 soluble and 46 matrix microenvironmental proteins on basal-like HER2+ (HER2E) or luminal-like HER2+ (L-HER2+) cells treated with the TKIs lapatinib or neratinib. In HER2E cells, hepatocyte growth factor, a ligand for MET, induced resistance that could be reversed with crizotinib, an inhibitor of MET. In L-HER2+ cells, neuregulin1-β1 (NRG1β), a ligand for HER3, induced resistance that could be reversed with pertuzumab, an inhibitor of HER2-HER3 heterodimerization. The subtype-specific responses were also observed in 3D cultures and murine xenografts. These results, along with bioinformatic pathway analysis and siRNA knockdown experiments, suggest different mechanisms of resistance specific to each HER2+ subtype: MET signaling for HER2E and HER2-HER3 heterodimerization for L-HER2+ cells.
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MESH Headings
- Animals
- Antineoplastic Agents/pharmacology
- Breast Neoplasms/drug therapy
- Cell Line, Tumor
- Databases, Genetic
- Drug Resistance, Neoplasm/drug effects
- Drug Resistance, Neoplasm/genetics
- Enzyme Inhibitors/pharmacology
- Female
- Gene Expression Regulation, Neoplastic/drug effects
- Genes, erbB-2/drug effects
- Genes, erbB-2/genetics
- Genes, erbB-2/physiology
- High-Throughput Screening Assays/methods
- Humans
- Lapatinib/pharmacology
- MCF-7 Cells
- Mice
- Protein Kinase Inhibitors/pharmacology
- Protein-Tyrosine Kinases/antagonists & inhibitors
- Proto-Oncogene Proteins c-met/antagonists & inhibitors
- Quinazolines/pharmacology
- Quinolines/pharmacology
- Receptor, ErbB-2/antagonists & inhibitors
- Receptor, ErbB-3/antagonists & inhibitors
- Signal Transduction/drug effects
- Tumor Microenvironment/drug effects
- Tumor Microenvironment/genetics
- Tumor Microenvironment/physiology
- Xenograft Model Antitumor Assays
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Affiliation(s)
- Spencer S Watson
- Department of Biomedical Engineering, Knight Cancer Institute, OHSU Center for Spatial Systems Biomedicine, Oregon Health and Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239, USA
| | - Mark Dane
- Department of Biomedical Engineering, Knight Cancer Institute, OHSU Center for Spatial Systems Biomedicine, Oregon Health and Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239, USA
| | - Koei Chin
- Department of Biomedical Engineering, Knight Cancer Institute, OHSU Center for Spatial Systems Biomedicine, Oregon Health and Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239, USA
| | - Zuzana Tatarova
- Department of Biomedical Engineering, Knight Cancer Institute, OHSU Center for Spatial Systems Biomedicine, Oregon Health and Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239, USA
| | - Moqing Liu
- Department of Biomedical Engineering, Knight Cancer Institute, OHSU Center for Spatial Systems Biomedicine, Oregon Health and Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239, USA
| | - Tiera Liby
- Department of Biomedical Engineering, Knight Cancer Institute, OHSU Center for Spatial Systems Biomedicine, Oregon Health and Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239, USA
| | - Wallace Thompson
- Department of Biomedical Engineering, Knight Cancer Institute, OHSU Center for Spatial Systems Biomedicine, Oregon Health and Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239, USA
| | - Rebecca Smith
- Department of Biomedical Engineering, Knight Cancer Institute, OHSU Center for Spatial Systems Biomedicine, Oregon Health and Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239, USA
| | - Michel Nederlof
- Department of Biomedical Engineering, Knight Cancer Institute, OHSU Center for Spatial Systems Biomedicine, Oregon Health and Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239, USA; Quantitative Imaging Systems LLC, 1410 NW Kearney Street, #1114, Portland, OR 97209, USA
| | - Elmar Bucher
- Department of Biomedical Engineering, Knight Cancer Institute, OHSU Center for Spatial Systems Biomedicine, Oregon Health and Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239, USA
| | - David Kilburn
- Department of Biomedical Engineering, Knight Cancer Institute, OHSU Center for Spatial Systems Biomedicine, Oregon Health and Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239, USA
| | - Matthew Whitman
- Department of Radiology, Brigham & Women's Hospital, Harvard Medical School, 75 Francis St, Boston, MA 02115, USA
| | - Damir Sudar
- Department of Biomedical Engineering, Knight Cancer Institute, OHSU Center for Spatial Systems Biomedicine, Oregon Health and Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239, USA; Quantitative Imaging Systems LLC, 1410 NW Kearney Street, #1114, Portland, OR 97209, USA
| | - Gordon B Mills
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA
| | - Laura M Heiser
- Department of Biomedical Engineering, Knight Cancer Institute, OHSU Center for Spatial Systems Biomedicine, Oregon Health and Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239, USA
| | - Oliver Jonas
- Department of Radiology, Brigham & Women's Hospital, Harvard Medical School, 75 Francis St, Boston, MA 02115, USA
| | - Joe W Gray
- Department of Biomedical Engineering, Knight Cancer Institute, OHSU Center for Spatial Systems Biomedicine, Oregon Health and Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239, USA.
| | - James E Korkola
- Department of Biomedical Engineering, Knight Cancer Institute, OHSU Center for Spatial Systems Biomedicine, Oregon Health and Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239, USA.
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6
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Behrman EL, Watson SS, O'Brien KR, Heschel MS, Schmidt PS. Seasonal variation in life history traits in two Drosophila species. J Evol Biol 2015; 28:1691-704. [PMID: 26174167 DOI: 10.1111/jeb.12690] [Citation(s) in RCA: 59] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2015] [Revised: 06/30/2015] [Accepted: 07/01/2015] [Indexed: 01/16/2023]
Abstract
Seasonal environmental heterogeneity is cyclic, persistent and geographically widespread. In species that reproduce multiple times annually, environmental changes across seasonal time may create different selection regimes that may shape the population ecology and life history adaptation in these species. Here, we investigate how two closely related species of Drosophila in a temperate orchard respond to environmental changes across seasonal time. Natural populations of Drosophila melanogaster and Drosophila simulans were sampled at four timepoints from June through November to assess seasonal change in fundamental aspects of population dynamics as well as life history traits. D. melanogaster exhibit pronounced change across seasonal time: early in the season, the population is inferred to be uniformly young and potentially represents the early generation following overwintering survivorship. D. melanogaster isofemale lines derived from the early population and reared in a common garden are characterized by high tolerance to a variety of stressors as well as a fast rate of development in the laboratory environment that declines across seasonal time. In contrast, wild D. simulans populations were inferred to be consistently heterogeneous in age distribution across seasonal collections; only starvation tolerance changed predictably over seasonal time in a parallel manner as in D. melanogaster. These results suggest fundamental differences in population and evolutionary dynamics between these two taxa associated with seasonal heterogeneity in environmental parameters and associated selection pressures.
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Affiliation(s)
- E L Behrman
- Department of Biology, University of Pennsylvania, Philadelphia, PA, USA
| | - S S Watson
- Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - K R O'Brien
- Department of Biology, University of Pennsylvania, Philadelphia, PA, USA.,School of Biological Sciences, University of Nebraska, Lincoln, NE, USA
| | - M S Heschel
- Department of Organismal Biology & Ecology, Colorado College, Colorado Springs, CO, USA
| | - P S Schmidt
- Department of Biology, University of Pennsylvania, Philadelphia, PA, USA
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7
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Huang AH, Riordan TJ, Pryce B, Weibel JL, Watson SS, Long F, Lefebvre V, Harfe BD, Stadler HS, Akiyama H, Tufa SF, Keene DR, Schweitzer R. Musculoskeletal integration at the wrist underlies the modular development of limb tendons. Development 2015; 142:2431-41. [PMID: 26062940 DOI: 10.1242/dev.122374] [Citation(s) in RCA: 68] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2015] [Accepted: 06/02/2015] [Indexed: 01/18/2023]
Abstract
The long tendons of the limb extend from muscles that reside in the zeugopod (arm/leg) to their skeletal insertions in the autopod (paw). How these connections are established along the length of the limb remains unknown. Here, we show that mouse limb tendons are formed in modular units that combine to form a functional contiguous structure; in muscle-less limbs, tendons develop in the autopod but do not extend into the zeugopod, and in the absence of limb cartilage the zeugopod segments of tendons develop despite the absence of tendons in the autopod. Analyses of cell lineage and proliferation indicate that distinct mechanisms govern the growth of autopod and zeugopod tendon segments. To elucidate the integration of these autopod and zeugopod developmental programs, we re-examined early tendon development. At E12.5, muscles extend across the full length of a very short zeugopod and connect through short anlagen of tendon progenitors at the presumptive wrist to their respective autopod tendon segment, thereby initiating musculoskeletal integration. Zeugopod tendon segments are subsequently generated by proximal elongation of the wrist tendon anlagen, in parallel with skeletal growth, underscoring the dependence of zeugopod tendon development on muscles for tendon anchoring. Moreover, a subset of extensor tendons initially form as fused structures due to initial attachment of their respective wrist tendon anlage to multiple muscles. Subsequent individuation of these tendons depends on muscle activity. These results establish an integrated model for limb tendon development that provides a framework for future analyses of tendon and musculoskeletal phenotypes.
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Affiliation(s)
- Alice H Huang
- Research Division, Shriners Hospital for Children, Portland, OR 97209, USA
| | - Timothy J Riordan
- Research Division, Shriners Hospital for Children, Portland, OR 97209, USA
| | - Brian Pryce
- Research Division, Shriners Hospital for Children, Portland, OR 97209, USA
| | - Jennifer L Weibel
- Research Division, Shriners Hospital for Children, Portland, OR 97209, USA
| | - Spencer S Watson
- Research Division, Shriners Hospital for Children, Portland, OR 97209, USA
| | - Fanxin Long
- Department of Orthopaedics, Washington University, St Louis, MO 63110, USA
| | - Veronique Lefebvre
- Department of Cellular and Molecular Medicine, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Brian D Harfe
- Department of Molecular Genetics and Microbiology and the Genetics Institute, University of Florida, Gainesville, FL 32611, USA
| | - H Scott Stadler
- Research Division, Shriners Hospital for Children, Portland, OR 97209, USA
| | - Haruhiko Akiyama
- Department of Orthopaedics, Gifu University, Gifu City, 501-1193, Japan
| | - Sara F Tufa
- Research Division, Shriners Hospital for Children, Portland, OR 97209, USA
| | - Douglas R Keene
- Research Division, Shriners Hospital for Children, Portland, OR 97209, USA
| | - Ronen Schweitzer
- Research Division, Shriners Hospital for Children, Portland, OR 97209, USA
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Slotwinski JA, Garboczi EJ, Stutzman PE, Ferraris CF, Watson SS, Peltz MA. Characterization of Metal Powders Used for Additive Manufacturing. J Res Natl Inst Stand Technol 2014; 119:460-93. [PMID: 26601040 PMCID: PMC4487284 DOI: 10.6028/jres.119.018] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 08/12/2014] [Indexed: 05/18/2023]
Abstract
Additive manufacturing (AM) techniques can produce complex, high-value metal parts, with potential applications as critical parts, such as those found in aerospace components. The production of AM parts with consistent and predictable properties requires input materials (e.g., metal powders) with known and repeatable characteristics, which in turn requires standardized measurement methods for powder properties. First, based on our previous work, we assess the applicability of current standardized methods for powder characterization for metal AM powders. Then we present the results of systematic studies carried out on two different powder materials used for additive manufacturing: stainless steel and cobalt-chrome. The characterization of these powders is important in NIST efforts to develop appropriate measurements and standards for additive materials and to document the property of powders used in a NIST-led additive manufacturing material round robin. An extensive array of characterization techniques was applied to these two powders, in both virgin and recycled states. The physical techniques included laser diffraction particle size analysis, X-ray computed tomography for size and shape analysis, and optical and scanning electron microscopy. Techniques sensitive to structure and chemistry, including X-ray diffraction, energy dispersive analytical X-ray analysis using the X-rays generated during scanning electron microscopy, and X-Ray photoelectron spectroscopy were also employed. The results of these analyses show how virgin powder changes after being exposed to and recycled from one or more Direct Metal Laser Sintering (DMLS) additive manufacturing build cycles. In addition, these findings can give insight into the actual additive manufacturing process.
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Pryce BA, Watson SS, Murchison ND, Staverosky JA, Dünker N, Schweitzer R. Recruitment and maintenance of tendon progenitors by TGFbeta signaling are essential for tendon formation. Development 2009; 136:1351-61. [PMID: 19304887 DOI: 10.1242/dev.027342] [Citation(s) in RCA: 302] [Impact Index Per Article: 20.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Tendons and ligaments mediate the attachment of muscle to bone and of bone to bone to provide connectivity and structural integrity in the musculoskeletal system. We show that TGFbeta signaling plays a major role in the formation of these tissues. TGFbeta signaling is a potent inducer of the tendon progenitor (TNP) marker scleraxis both in organ culture and in cultured cells, and disruption of TGFbeta signaling in Tgfb2(-/-);Tgfb3(-/-) double mutant embryos or through inactivation of the type II TGFbeta receptor (TGFBR2; also known as TbetaRII) results in the loss of most tendons and ligaments in the limbs, trunk, tail and head. The induction of scleraxis-expressing TNPs is not affected in mutant embryos and the tendon phenotype is first manifested at E12.5, a developmental stage in which TNPs are positioned between the differentiating muscles and cartilage, and in which Tgfb2 or Tgfb3 is expressed both in TNPs and in the differentiating muscles and cartilage. TGFbeta signaling is thus essential for maintenance of TNPs, and we propose that it also mediates the recruitment of new tendon cells by differentiating muscles and cartilage to establish the connections between tendon primordia and their respective musculoskeletal counterparts, leading to the formation of an interconnected and functionally integrated musculoskeletal system.
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Affiliation(s)
- Brian A Pryce
- Shriners Hospital for Children, Research Division, Portland, OR 97239, USA
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Staverosky JA, Pryce BA, Watson SS, Schweitzer R. Tubulin polymerization-promoting protein family member 3, Tppp3, is a specific marker of the differentiating tendon sheath and synovial joints. Dev Dyn 2009; 238:685-92. [PMID: 19235716 DOI: 10.1002/dvdy.21865] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
Tppp3, a member of the Tubulin polymerization-promoting protein family, is an intrinsically unstructured protein that induces tubulin polymerization. We show that Tppp3 is a distinct marker in the developing musculoskeletal system. In tendons, Tppp3 is expressed in cells at the circumference of the developing tendons, likely the progenitors of connective tissues that surround tendons: the tendon sheath, epitenon, and paratenon. These tissues form an elastic sleeve around tendons and provide lubrication to minimize friction between tendons and surrounding tissues. Tppp3 is the first molecular marker of the tendon sheath, opening the door for direct examination of these tissues. Tppp3 is also expressed in forming synovial joints. The onset of Tppp3 expression in joints coincides with cavitation, representing a molecular marker that can be used to indicate this stage in joint transition in joint differentiation. In late embryonic stages, Tppp3 expression highlights other demarcation lines that surround differentiating tissues in the forelimb.
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Affiliation(s)
- Julia A Staverosky
- Shriners Hospital for Children, Research Division, Portland, Oregon 97239, USA
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Liu W, Watson SS, Schweitzer R, Jiang R. Targeted disruption of the Mohawk homeobox gene results in tendon defects in mice. Dev Biol 2008. [DOI: 10.1016/j.ydbio.2008.05.119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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Longcope JC, Watson SS. Brain tumors in infants. N Engl J Med 1993; 329:1964. [PMID: 8247065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
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Cook JD, Watson SS, Simpson KM, Lipschitz DA, Skikne BS. The effect of high ascorbic acid supplementation on body iron stores. Blood 1984; 64:721-6. [PMID: 6466873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
The level of assimilation of dietary iron is believed to have an important influence on iron status. To examine the effect of enhancing the availability of dietary iron on iron balance, 17 adult volunteer subjects were given 2 g of ascorbic acid daily with meals for 16 weeks. Serum ferritin levels before and after the study averaged 46 and 43 micrograms/L, respectively, indicating a negligible effect on iron stores. When vitamin C supplementation was continued for an additional 20 months in five iron-replete and four iron-deficient subjects, serum ferritin determinations again failed to indicate any significant effect of the vitamin C on iron reserves. These findings were not explained by intestinal adaptation to the enhancing effect of the vitamin, because radioisotopic measurements of nonheme iron absorption showed no reduction in the enhancing effect of 1 g of ascorbic acid after four months of megadoses of vitamin C. It is concluded that altering the availability of nonheme dietary iron has little effect on iron status when the diet contains substantial amounts of meat.
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