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Abstract
ABSTRACT Despite a dearth of activating driver mutations in head and neck squamous cell carcinoma (HNSCC), aberrant activation of the oncogenes, epidermal growth factor receptor (EGFR), and c-Met is near-universal in human papillomavirus (HPV)-negative disease. Although EGFR activation drove the successful development of the anti-EGFR monoclonal antibody cetuximab in HNSCC, no c-Met-targeting therapy has gained regulatory approval. Inhibition of the c-Met pathway may subvert oncogenesis within the tumor-intrinsic compartment, blocking tumoral proliferation, invasion, migration, and metastasis, or the tumor-extrinsic compartment, modulating the immunosuppressive tumor microenvironment. This review discusses the rationale and current drug development strategies for targeting c-Met or its exclusive ligand hepatocyte growth factor (HGF) in HNSCC.
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Mild hyperthermia induced by gold nanorods acts as a dual-edge blade in the fate of SH-SY5Y cells via autophagy. Sci Rep 2021; 11:23984. [PMID: 34907215 PMCID: PMC8671444 DOI: 10.1038/s41598-021-02697-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Accepted: 11/22/2021] [Indexed: 02/07/2023] Open
Abstract
Unraveling unwanted side effects of nanotechnology-based therapies like photothermal therapy (PTT) is vital in translational nanomedicine. Herein, we monitored the relationship between autophagic response at the transcriptional level by using a PCR array and tumor formation ability by colony formation assay in the human neuroblastoma cell line, SH-SY5Y, 48 h after being exposed to two different mild hyperthermia (43 and 48 °C) induced by PTT. In this regard, the promotion of apoptosis and autophagy were evaluated using immunofluorescence imaging and flow cytometry analyses. Protein levels of Ki-67, P62, and LC3 were measured using ELISA. Our results showed that of 86 genes associated with autophagy, the expression of 54 genes was changed in response to PTT. Also, we showed that chaperone-mediated autophagy (CMA) and macroautophagy are stimulated in PTT. Importantly, the results of this study also showed significant changes in genes related to the crosstalk between autophagy, dormancy, and metastatic activity of treated cells. Our findings illustrated that PTT enhances the aggressiveness of cancer cells at 43 °C, in contrast to 48 °C by the regulation of autophagy-dependent manner.
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Uddin M, Ratanatharathorn A, Armstrong D, Kuan PF, Aiello AE, Bromet EJ, Galea S, Koenen KC, Luft B, Ressler KJ, Wildman DE, Nievergelt CM, Smith A. Epigenetic meta-analysis across three civilian cohorts identifies NRG1 and HGS as blood-based biomarkers for post-traumatic stress disorder. Epigenomics 2018; 10:1585-1601. [PMID: 30456986 DOI: 10.2217/epi-2018-0049] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
AIM Trauma exposure is a necessary, but not deterministic, contributor to post-traumatic stress disorder (PTSD). Epigenetic factors may distinguish between trauma-exposed individuals with versus without PTSD. MATERIALS & METHODS We conducted a meta-analysis of PTSD epigenome-wide association studies in trauma-exposed cohorts drawn from civilian contexts. Whole blood-derived DNA methylation levels were analyzed in 545 study participants, drawn from the three civilian cohorts participating in the PTSD working group of the Psychiatric Genomics Consortium. RESULTS Two CpG sites significantly associated with current PTSD in NRG1 (cg23637605) and in HGS (cg19577098). CONCLUSION PTSD is associated with differential methylation, measured in blood, within HGS and NRG1 across three civilian cohorts.
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Affiliation(s)
- Monica Uddin
- Carl R Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, 1206 West Gregory Drive, Urbana, IL 61801, USA.,Department of Psychology, University of Illinois Urbana-Champaign, 603 East Daniel St, Champaign, IL 61820, USA
| | - Andrew Ratanatharathorn
- Department of Epidemiology, Mailman School of Public Health, Columbia University, 722 West 168th St, NY 10032, USA
| | - Don Armstrong
- Carl R Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, 1206 West Gregory Drive, Urbana, IL 61801, USA
| | - Pei-Fen Kuan
- Department of Applied Mathematics & Statistics, Stony Brook University, John S Toll Drive, Stony Brook, NY 11794, USA
| | - Allison E Aiello
- Department of Epidemiology, Gillings School of Public Health, University of North Carolina, 135 Dauer Drive, Chapel Hill, NC 27599, USA
| | - Evelyn J Bromet
- Department of Psychiatry, Stony Brook University School of Medicine, 101 Nicolls Rd, Stony Brook, NY 11794, USA
| | - Sandro Galea
- Boston University School of Public Health, 715 Albany St, Boston, MA 02118, USA
| | - Karestan C Koenen
- Department of Epidemiology, Harvard TH Chan School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA.,Psychiatic & Neurodevelopmental Genetics Unit & Department of Psychiatry, Massachusetts General Hospital, Simches Research Building, 185 Cambridge Street, Boston, MA 02114, USA.,Stanley Center for Psychiatric Research, Broad Institute, Cambridge, MA 02142, USA
| | - Benjamin Luft
- Department of Medicine, Stony Brook University School of Medicine, 101 Nicolls Road, Stony Brook, NY 11794, USA
| | - Kerry J Ressler
- Department of Psychiatry, McLean Hospital, Harvard Medical School, 115 Mill Street, Belmont, MA 02478, USA
| | - Derek E Wildman
- Carl R Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, 1206 West Gregory Drive, Urbana, IL 61801, USA.,Department of Molecular & Integrative Physiology, University of Illinois at Urbana-Champaign, 407 South Goodwin Avenue, Urbana, IL 61801, USA
| | - Caroline M Nievergelt
- Department of Psychiatry, University of California San Diego School of Medicine, 9500 Gilman Dr, La Jolla, CA 92093, USA.,VA Center of Excellence for Stress & Mental Health, VA San Diego Healthcare System, 3350 La Jolla Village Drive, San Diego, CA 92161, USA
| | - Alicia Smith
- Department of Psychiatry & Behavioral Sciences & Department of Obstetrics & Gynecology, Emory University School of Medicine, 100 Woodruff Circle, Atlanta, GA 30322, USA
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Drake JR. The immunobiology of ubiquitin-dependent B cell receptor functions. Mol Immunol 2018; 101:146-154. [PMID: 29940407 DOI: 10.1016/j.molimm.2018.05.022] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2018] [Revised: 04/29/2018] [Accepted: 05/24/2018] [Indexed: 02/01/2023]
Abstract
MHC class II-restricted antigen presentation by dendritic cells is necessary for activation of naïve CD4 T cells, whereas class II-restricted antigen presentation by B lymphocytes and macrophages is important for the recruitment of CD4+ helper and regulatory T cells. Antigen presentation by B cells is also important for induction of T cell tolerance. B cells are unique among these three types of MHC class II-expressing antigen presenting cells (APC) as they constitutively express high levels of cell surface class II molecules and express a clonally restricted antigen specific receptor, the B cell receptor (BCR). Here, I review our current understanding of three major steps that underlie the processing and presentation of BCR-bound cognate antigen: (1) endocytosis of antigen-BCR (Ag-BCR) complexes, (2) Ag-BCR trafficking to intracellular antigen processing compartments and (3) generation of antigenic peptide-MHC class II complexes, with a particular focus on the role of BCR ubiquitination in each. I will highlight potential topics for future research and briefly discuss the impact of the cell biology of BCR-mediated antigen processing on the response of the B cell and T cell to the cell-cell interactions mediated by B cell-expressed peptide-class II complexes.
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Affiliation(s)
- James R Drake
- Albany Medical College, Department of Immunology and Microbial Disease, 47 New Scotland Ave., MC-151, Albany, NY 12208-3479, United States.
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Wilson JL, Dalin S, Gosline S, Hemann M, Fraenkel E, Lauffenburger DA. Pathway-based network modeling finds hidden genes in shRNA screen for regulators of acute lymphoblastic leukemia. Integr Biol (Camb) 2016; 8:761-74. [PMID: 27315426 PMCID: PMC5224708 DOI: 10.1039/c6ib00040a] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2016] [Accepted: 05/31/2016] [Indexed: 12/30/2022]
Abstract
Data integration stands to improve interpretation of RNAi screens which, as a result of off-target effects, typically yield numerous gene hits of which only a few validate. These off-target effects can result from seed matches to unintended gene targets (reagent-based) or cellular pathways, which can compensate for gene perturbations (biology-based). We focus on the biology-based effects and use network modeling tools to discover pathways de novo around RNAi hits. By looking at hits in a functional context, we can uncover novel biology not identified from any individual 'omics measurement. We leverage multiple 'omic measurements using the Simultaneous Analysis of Multiple Networks (SAMNet) computational framework to model a genome scale shRNA screen investigating Acute Lymphoblastic Leukemia (ALL) progression in vivo. Our network model is enriched for cellular processes associated with hematopoietic differentiation and homeostasis even though none of the individual 'omic sets showed this enrichment. The model identifies genes associated with the TGF-beta pathway and predicts a role in ALL progression for many genes without this functional annotation. We further experimentally validate the hidden genes - Wwp1, a ubiquitin ligase, and Hgs, a multi-vesicular body associated protein - for their role in ALL progression. Our ALL pathway model includes genes with roles in multiple types of leukemia and roles in hematological development. We identify a tumor suppressor role for Wwp1 in ALL progression. This work demonstrates that network integration approaches can compensate for off-target effects, and that these methods can uncover novel biology retroactively on existing screening data. We anticipate that this framework will be valuable to multiple functional genomic technologies - siRNA, shRNA, and CRISPR - generally, and will improve the utility of functional genomic studies.
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Affiliation(s)
- Jennifer L. Wilson
- Department of Biological Engineering , Massachusetts Institute of Technology , 77 Massachusetts Avenue , 16-343 , Cambridge MA 02139 , USA . ; ; Tel: +1-617-252-1629
| | - Simona Dalin
- Department of Biology , Massachusetts Institute of Technology , Cambridge MA 02139 , USA
| | - Sara Gosline
- Department of Biological Engineering , Massachusetts Institute of Technology , 77 Massachusetts Avenue , 16-343 , Cambridge MA 02139 , USA . ; ; Tel: +1-617-252-1629
| | - Michael Hemann
- Department of Biology , Massachusetts Institute of Technology , Cambridge MA 02139 , USA
| | - Ernest Fraenkel
- Department of Biological Engineering , Massachusetts Institute of Technology , 77 Massachusetts Avenue , 16-343 , Cambridge MA 02139 , USA . ; ; Tel: +1-617-252-1629
- Department of Biology , Massachusetts Institute of Technology , Cambridge MA 02139 , USA
| | - Douglas A. Lauffenburger
- Department of Biological Engineering , Massachusetts Institute of Technology , 77 Massachusetts Avenue , 16-343 , Cambridge MA 02139 , USA . ; ; Tel: +1-617-252-1629
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Chen J, Hou N, Zhang C, Teng Y, Cheng X, Li Z, Ren J, Zeng J, Li R, Wang W, Yang X, Lan Y. Smooth Muscle Hgs Deficiency Leads to Impaired Esophageal Motility. Int J Biol Sci 2015; 11:794-802. [PMID: 26078721 PMCID: PMC4466460 DOI: 10.7150/ijbs.12248] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2015] [Accepted: 04/13/2015] [Indexed: 02/07/2023] Open
Abstract
As a master component of endosomal sorting complex required for transport proteins, hepatocyte growth factor-regulated tyrosine kinase substrate (Hgs) participates multiple cellular behaviors. However, the physiological role of Hgs in smooth muscle cells (SMCs) is by far unknown. Here we explored the in vivo function of Hgs in SMCs by using a conditional gene knockout strategy. Hgs deficiency in SMCs uniquely led to a progressive dilatation of esophagus with a remarkable thinning muscle layer. Of note, the mutant esophagus showed a decreased contractile responsiveness to potassium chloride and acetylcholine stimulation. Furthermore, an increase in the inhibitory neurites along with an intense infiltration of T lymphocytes in the mucosa and muscle layer were observed. Consistently, Hgs deficiency in SMCs resulted in a disturbed expression of a set of genes involved in neurotrophin and inflammation, suggesting that defective SMC might be a novel source for excessive production of cytokines and chemokines which may trigger the neuronal dysplasia and ultimately contribute to the compromised esophageal motility. The data suggest potential implications in the pathogenesis of related diseases such as gastroesophageal reflux disease.
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Affiliation(s)
- Jicheng Chen
- 1. Model Organism Division, E-institutes of Shanghai Universities, Shanghai Jiaotong University, Shanghai 200025, China ; 2. State Key Laboratory of Proteomics, Collaborative Innovation Center for Cardiovascular Disorders, Genetic Laboratory of Development and Disease, Institute of Biotechnology, Beijing 100071, China
| | - Ning Hou
- 2. State Key Laboratory of Proteomics, Collaborative Innovation Center for Cardiovascular Disorders, Genetic Laboratory of Development and Disease, Institute of Biotechnology, Beijing 100071, China
| | - Chong Zhang
- 1. Model Organism Division, E-institutes of Shanghai Universities, Shanghai Jiaotong University, Shanghai 200025, China ; 2. State Key Laboratory of Proteomics, Collaborative Innovation Center for Cardiovascular Disorders, Genetic Laboratory of Development and Disease, Institute of Biotechnology, Beijing 100071, China
| | - Yan Teng
- 2. State Key Laboratory of Proteomics, Collaborative Innovation Center for Cardiovascular Disorders, Genetic Laboratory of Development and Disease, Institute of Biotechnology, Beijing 100071, China
| | - Xuan Cheng
- 2. State Key Laboratory of Proteomics, Collaborative Innovation Center for Cardiovascular Disorders, Genetic Laboratory of Development and Disease, Institute of Biotechnology, Beijing 100071, China
| | - Zhenhua Li
- 2. State Key Laboratory of Proteomics, Collaborative Innovation Center for Cardiovascular Disorders, Genetic Laboratory of Development and Disease, Institute of Biotechnology, Beijing 100071, China
| | - Jie Ren
- 3. Department of Cardiovascular Electrophysiology Research, College of Basic Medicine, Capital Medical University, Beijing 100069, China
| | - Jian Zeng
- 2. State Key Laboratory of Proteomics, Collaborative Innovation Center for Cardiovascular Disorders, Genetic Laboratory of Development and Disease, Institute of Biotechnology, Beijing 100071, China
| | - Rui Li
- 2. State Key Laboratory of Proteomics, Collaborative Innovation Center for Cardiovascular Disorders, Genetic Laboratory of Development and Disease, Institute of Biotechnology, Beijing 100071, China
| | - Wei Wang
- 3. Department of Cardiovascular Electrophysiology Research, College of Basic Medicine, Capital Medical University, Beijing 100069, China
| | - Xiao Yang
- 1. Model Organism Division, E-institutes of Shanghai Universities, Shanghai Jiaotong University, Shanghai 200025, China ; 2. State Key Laboratory of Proteomics, Collaborative Innovation Center for Cardiovascular Disorders, Genetic Laboratory of Development and Disease, Institute of Biotechnology, Beijing 100071, China
| | - Yu Lan
- 2. State Key Laboratory of Proteomics, Collaborative Innovation Center for Cardiovascular Disorders, Genetic Laboratory of Development and Disease, Institute of Biotechnology, Beijing 100071, China
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