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Bhetraratana M, Orozco LD, Bennett BJ, Luna K, Yang X, Lusis AJ, Araujo JA. Diesel exhaust particle extract elicits an oxPAPC-like transcriptomic profile in macrophages across multiple mouse strains. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 358:124415. [PMID: 38908672 DOI: 10.1016/j.envpol.2024.124415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 06/14/2024] [Accepted: 06/19/2024] [Indexed: 06/24/2024]
Abstract
Air pollution is a prominent cause of cardiopulmonary illness, but uncertainties remain regarding the mechanisms mediating those effects as well as individual susceptibility. Macrophages are highly responsive to particles, and we hypothesized that their responses would be dependent on their genetic backgrounds. We conducted a genome-wide analysis of peritoneal macrophages harvested from 24 inbred strains of mice from the Hybrid Mouse Diversity Panel (HMDP). Cells were treated with a DEP methanol extract (DEPe) to elucidate potential pathways that mediate acute responses to air pollution exposures. This analysis showed that 1247 genes were upregulated and 1383 genes were downregulated with DEPe treatment across strains. Pathway analysis identified oxidative stress responses among the most prominent upregulated pathways; indeed, many of the upregulated genes included antioxidants such as Hmox1, Txnrd1, Srxn1, and Gclm, with NRF2 (official gene symbol: Nfe2l2) being the most significant driver. DEPe induced a Mox-like transcriptomic profile, a macrophage subtype typically induced by oxidized phospholipids and likely dependent on NRF2 expression. Analysis of individual strains revealed consistency of overall responses to DEPe and yet differences in the degree of Mox-like polarization across the various strains, indicating DEPe × genetic interactions. These results suggest a role for macrophage polarization in the cardiopulmonary toxicity induced by air pollution.
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Affiliation(s)
- May Bhetraratana
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine at UCLA, 10833 Le Conte Ave., Los Angeles, CA, 90095, USA
| | - Luz D Orozco
- Department of Human Genetics, David Geffen School of Medicine at UCLA, 10833 Le Conte Ave., Los Angeles, CA, 90095, USA
| | - Brian J Bennett
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine at UCLA, 10833 Le Conte Ave., Los Angeles, CA, 90095, USA
| | - Karla Luna
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine at UCLA, 10833 Le Conte Ave., Los Angeles, CA, 90095, USA; Department of Biology, College of Science and Math, California State University-Northridge, 18111 Nordhoff Street, Northridge, CA, 91330, USA
| | - Xia Yang
- Department of Integrative Biology and Physiology, UCLA, 612 Charles E. Young Drive East, Los Angeles, CA, 90095, USA; Institute for Quantitative and Computational Biosciences, UCLA, 610 Charles E. Young Drive East, Los Angeles, CA, 90095, USA; Molecular Biology Institute, UCLA, 611 Charles E. Young Drive East, Los Angeles, CA, 90095, USA
| | - Aldons J Lusis
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine at UCLA, 10833 Le Conte Ave., Los Angeles, CA, 90095, USA; Department of Human Genetics, David Geffen School of Medicine at UCLA, 10833 Le Conte Ave., Los Angeles, CA, 90095, USA; Molecular Biology Institute, UCLA, 611 Charles E. Young Drive East, Los Angeles, CA, 90095, USA
| | - Jesus A Araujo
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine at UCLA, 10833 Le Conte Ave., Los Angeles, CA, 90095, USA; Molecular Biology Institute, UCLA, 611 Charles E. Young Drive East, Los Angeles, CA, 90095, USA; Department of Environmental Health Sciences, Fielding School of Public Health, UCLA, 650 Charles E. Young Dr. South, Los Angeles, CA, 90095, USA.
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2
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Deng EZ, Marino GB, Clarke DJB, Diamant I, Resnick AC, Ma W, Wang P, Ma'ayan A. Multiomics2Targets identifies targets from cancer cohorts profiled with transcriptomics, proteomics, and phosphoproteomics. CELL REPORTS METHODS 2024; 4:100839. [PMID: 39127042 DOI: 10.1016/j.crmeth.2024.100839] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 06/06/2024] [Accepted: 07/19/2024] [Indexed: 08/12/2024]
Abstract
The availability of data from profiling of cancer patients with multiomics is rapidly increasing. However, integrative analysis of such data for personalized target identification is not trivial. Multiomics2Targets is a platform that enables users to upload transcriptomics, proteomics, and phosphoproteomics data matrices collected from the same cohort of cancer patients. After uploading the data, Multiomics2Targets produces a report that resembles a research publication. The uploaded matrices are processed, analyzed, and visualized using the tools Enrichr, KEA3, ChEA3, Expression2Kinases, and TargetRanger to identify and prioritize proteins, genes, and transcripts as potential targets. Figures and tables, as well as descriptions of the methods and results, are automatically generated. Reports include an abstract, introduction, methods, results, discussion, conclusions, and references and are exportable as citable PDFs and Jupyter Notebooks. Multiomics2Targets is applied to analyze version 3 of the Clinical Proteomic Tumor Analysis Consortium (CPTAC3) pan-cancer cohort, identifying potential targets for each CPTAC3 cancer subtype. Multiomics2Targets is available from https://multiomics2targets.maayanlab.cloud/.
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Affiliation(s)
- Eden Z Deng
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY 10029, USA
| | - Giacomo B Marino
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY 10029, USA
| | - Daniel J B Clarke
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY 10029, USA
| | - Ido Diamant
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY 10029, USA
| | - Adam C Resnick
- Center for Data Driven Discovery in Biomedicine, Division of Neurosurgery, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Weiping Ma
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1498, New York, NY 10029, USA
| | - Pei Wang
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1498, New York, NY 10029, USA
| | - Avi Ma'ayan
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY 10029, USA.
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3
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Bruschi M, Granata S, Candiano G, Petretto A, Bartolucci M, Kajana X, Spinelli S, Verlato A, Provenzano M, Zaza G. Proteomic Changes Induced by the Immunosuppressant Everolimus in Human Podocytes. Int J Mol Sci 2024; 25:7336. [PMID: 39000447 PMCID: PMC11242170 DOI: 10.3390/ijms25137336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2024] [Revised: 07/01/2024] [Accepted: 07/02/2024] [Indexed: 07/16/2024] Open
Abstract
mTOR inhibitors (mTOR-Is) may induce proteinuria in kidney transplant recipients through podocyte damage. However, the mechanism has only been partially defined. Total cell lysates and supernatants of immortalized human podocytes treated with different doses of everolimus (EVE) (10, 100, 200, and 500 nM) for 24 h were subjected to mass spectrometry-based proteomics. Support vector machine and partial least squares discriminant analysis were used for data analysis. The results were validated in urine samples from 28 kidney transplant recipients receiving EVE as part of their immunosuppressive therapy. We identified more than 7000 differentially expressed proteins involved in several pathways, including kinases, cell cycle regulation, epithelial-mesenchymal transition, and protein synthesis, according to gene ontology. Among these, after statistical analysis, 65 showed an expression level significantly and directly correlated with EVE dosage. Polo-Like Kinase 1 (PLK1) content was increased, whereas osteopontin (SPP1) content was reduced in podocytes and supernatants in a dose-dependent manner and significantly correlated with EVE dose (p < 0.0001, FDR < 5%). Similar results were obtained in the urine of kidney transplant patients. This study analyzed the impact of different doses of mTOR-Is on podocytes, helping to understand not only the biological basis of their therapeutic effects but also the possible mechanisms underlying proteinuria.
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Affiliation(s)
- Maurizio Bruschi
- Laboratory of Molecular Nephrology, IRCCS Istituto Giannina Gaslini, 16147 Genoa, Italy; (M.B.); (G.C.); (X.K.); (S.S.)
- Department of Experimental Medicine (DIMES), University of Genoa, 16132 Genoa, Italy
| | - Simona Granata
- Department of Medical and Surgical Sciences, University of Foggia, 71122 Foggia, Italy;
| | - Giovanni Candiano
- Laboratory of Molecular Nephrology, IRCCS Istituto Giannina Gaslini, 16147 Genoa, Italy; (M.B.); (G.C.); (X.K.); (S.S.)
| | - Andrea Petretto
- Proteomics and Clinical Metabolomics Unit at the Core Facilities, IRCCS Istituto Giannina Gaslini, 16147 Genoa, Italy; (A.P.); (M.B.)
| | - Martina Bartolucci
- Proteomics and Clinical Metabolomics Unit at the Core Facilities, IRCCS Istituto Giannina Gaslini, 16147 Genoa, Italy; (A.P.); (M.B.)
| | - Xhuliana Kajana
- Laboratory of Molecular Nephrology, IRCCS Istituto Giannina Gaslini, 16147 Genoa, Italy; (M.B.); (G.C.); (X.K.); (S.S.)
| | - Sonia Spinelli
- Laboratory of Molecular Nephrology, IRCCS Istituto Giannina Gaslini, 16147 Genoa, Italy; (M.B.); (G.C.); (X.K.); (S.S.)
| | - Alberto Verlato
- Renal Unit, Department of Medicine, University Hospital of Verona, 37124 Verona, Italy;
| | - Michele Provenzano
- Nephrology, Dialysis and Transplantation Unit, Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, 87036 Rende, Italy;
| | - Gianluigi Zaza
- Nephrology, Dialysis and Transplantation Unit, Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, 87036 Rende, Italy;
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4
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Ajiboye BO, Fatoki TH, Akinola OG, Ajeigbe KO, Bamisaye AF, Domínguez-Martín EM, Rijo P, Oyinloye BE. In silico exploration of anti-prostate cancer compounds from differential expressed genes. BMC Urol 2024; 24:138. [PMID: 38956591 PMCID: PMC11221101 DOI: 10.1186/s12894-024-01521-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2023] [Accepted: 06/19/2024] [Indexed: 07/04/2024] Open
Abstract
Prostate cancer (PCa) is a complex and biologically diverse disease with no curative treatment options at present. This study aims to utilize computational methods to explore potential anti-PCa compounds based on differentially expressed genes (DEGs), with the goal of identifying novel therapeutic indications or repurposing existing drugs. The methods employed in this study include DEGs-to-drug prediction, pharmacokinetics prediction, target prediction, network analysis, and molecular docking. The findings revealed a total of 79 upregulated DEGs and 110 downregulated DEGs in PCa, which were used to identify drug compounds capable of reversing the dysregulated conditions (dexverapamil, emetine, parthenolide, dobutamine, terfenadine, pimozide, mefloquine, ellipticine, and trifluoperazine) at a threshold probability of 20% on several molecular targets, such as serotonin receptors 2a/2b/2c, HERG protein, adrenergic receptors alpha-1a/2a, dopamine D3 receptor, inducible nitric oxide synthase (iNOS), epidermal growth factor receptor erbB1 (EGFR), tyrosine-protein kinases, and C-C chemokine receptor type 5 (CCR5). Molecular docking analysis revealed that terfenadine binding to inducible nitric oxide synthase (-7.833 kcal.mol-1) and pimozide binding to HERG (-7.636 kcal.mol-1). Overall, binding energy ΔGbind (Total) at 0 ns was lower than that of 100 ns for both the Terfenadine-iNOS complex (-101.707 to -103.302 kcal.mol-1) and Ellipticine-TOPIIα complex (-42.229 to -58.780 kcal.mol-1). In conclusion, this study provides insight on molecular targets that could possibly contribute to the molecular mechanisms underlying PCa. Further preclinical and clinical studies are required to validate the therapeutic effectiveness of these identified drugs in PCa disease.
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Affiliation(s)
- Basiru Olaitan Ajiboye
- Phytomedicine and Molecular Toxicology Research Laboratory, Department of Biochemistry, Federal University Oye-Ekiti, Oye-Ekiti, Ekiti State, Nigeria.
| | - Toluwase Hezekiah Fatoki
- Applied Bioinformatics Research Laboratory, Department of Biochemistry, Federal University Oye-Ekiti, Oye-Ekiti, Ekiti State, Nigeria
| | - Olamilekan Ganiu Akinola
- Phytomedicine and Molecular Toxicology Research Laboratory, Department of Biochemistry, Federal University Oye-Ekiti, Oye-Ekiti, Ekiti State, Nigeria
| | - Kazeem Olasunkanmi Ajeigbe
- Department of Physiology, Faculty of Basic Medical Sciences, Federal University Oye-Ekiti, Oye-Ekiti, Ekiti State, Nigeria
| | | | - Eva-María Domínguez-Martín
- CBIOS-Universidade Lusófona's Research Center for Biosciences & Health Technologies, Lusófona University, Campo Grande 376, Lisbon, 1749-024, Portugal
- Facultad de Farmacia, Departamento de Ciencias Biomédicas (Área de Farmacología), Universidad de Alcalá de Henares, Nuevos Agentes Antitumorales, Acción Tóxica Sobre Células Leucémicas, Ctra. Madrid-Barcelona km. 33,600, Alcalá de Henares, Madrid, 28805, España
| | - Patricia Rijo
- CBIOS-Universidade Lusófona's Research Center for Biosciences & Health Technologies, Lusófona University, Campo Grande 376, Lisbon, 1749-024, Portugal
| | - Babatunji Emmanuel Oyinloye
- Phytomedicine, Biochemical Toxicology and Biotechnology Research Laboratories, Department of Biochemistry, College of Sciences, Afe Babalola University, Ado-Ekiti, Nigeria
- Biotechnology and Structural Biology (BSB) Group, Department of Biochemistry and Microbiology, University of Zululand, KwaDlangezwa, 3886, South Africa
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5
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Magni S, Sawlekar R, Capelle CM, Tslaf V, Baron A, Zeng N, Mombaerts L, Yue Z, Yuan Y, Hefeng FQ, Gonçalves J. Inferring upstream regulatory genes of FOXP3 in human regulatory T cells from time-series transcriptomic data. NPJ Syst Biol Appl 2024; 10:59. [PMID: 38811598 PMCID: PMC11137136 DOI: 10.1038/s41540-024-00387-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Accepted: 05/10/2024] [Indexed: 05/31/2024] Open
Abstract
The discovery of upstream regulatory genes of a gene of interest still remains challenging. Here we applied a scalable computational method to unbiasedly predict candidate regulatory genes of critical transcription factors by searching the whole genome. We illustrated our approach with a case study on the master regulator FOXP3 of human primary regulatory T cells (Tregs). While target genes of FOXP3 have been identified, its upstream regulatory machinery still remains elusive. Our methodology selected five top-ranked candidates that were tested via proof-of-concept experiments. Following knockdown, three out of five candidates showed significant effects on the mRNA expression of FOXP3 across multiple donors. This provides insights into the regulatory mechanisms modulating FOXP3 transcriptional expression in Tregs. Overall, at the genome level this represents a high level of accuracy in predicting upstream regulatory genes of key genes of interest.
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Affiliation(s)
- Stefano Magni
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg
| | - Rucha Sawlekar
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg
- Robotics and Artificial Intelligence, Department of Computer Science, Electrical and Space Engineering, Luleå University of Technology, Luleå, Sweden
| | - Christophe M Capelle
- Department of Infection and Immunity, Luxembourg Institute of Health, Esch-Sur-Alzette, Luxembourg
- Faculty of Science, Technology and Medicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Vera Tslaf
- Department of Infection and Immunity, Luxembourg Institute of Health, Esch-Sur-Alzette, Luxembourg
- Faculty of Science, Technology and Medicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
- Transversal Translational Medicine, Luxembourg Institute of Health, Strassen, Luxembourg
| | - Alexandre Baron
- Department of Infection and Immunity, Luxembourg Institute of Health, Esch-Sur-Alzette, Luxembourg
| | - Ni Zeng
- Department of Infection and Immunity, Luxembourg Institute of Health, Esch-Sur-Alzette, Luxembourg
| | - Laurent Mombaerts
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg
| | - Zuogong Yue
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg
| | - Ye Yuan
- School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China
| | - Feng Q Hefeng
- Department of Infection and Immunity, Luxembourg Institute of Health, Esch-Sur-Alzette, Luxembourg.
| | - Jorge Gonçalves
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg.
- Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom.
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6
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Reily C, Moldoveanu Z, Pramparo T, Hall S, Huang ZQ, Rice T, Novak L, Komers R, Jenkinson CP, Novak J. Sparsentan ameliorates glomerular hypercellularity and inflammatory-gene networks induced by IgA1-IgG immune complexes in a mouse model of IgA nephropathy. Am J Physiol Renal Physiol 2024; 326:F862-F875. [PMID: 38511222 DOI: 10.1152/ajprenal.00253.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 02/07/2024] [Accepted: 03/02/2024] [Indexed: 03/22/2024] Open
Abstract
IgA nephropathy (IgAN) is characterized by glomerular deposition of immune complexes (ICs) consisting of IgA1 with O-glycans deficient in galactose (Gd-IgA1) and Gd-IgA1-specific IgG autoantibodies. These ICs induce kidney injury, and in the absence of disease-specific therapy, up to 40% of patients with IgAN progress to kidney failure. IgA1 with its clustered O-glycans is unique to humans, which hampered development of small-animal models of IgAN. Here, we used a model wherein engineered ICs (EICs) formed from human Gd-IgA1 and recombinant human IgG autoantibody are injected into nude mice to induce glomerular injury mimicking human IgAN. In this model, we assessed the protective effects of sparsentan, a single-molecule dual endothelin angiotensin receptor antagonist (DEARA) versus vehicle on EIC-induced glomerular proliferation and dysregulation of gene expression in the kidney. Oral administration of sparsentan (60 or 120 mg/kg daily) to mice intravenously injected with EIC attenuated the EIC-induced glomerular hypercellularity. Furthermore, analysis of changes in the whole kidney transcriptome revealed that key inflammatory and proliferative biological genes and pathways that are upregulated in this EIC model of IgAN were markedly reduced by sparsentan, including complement genes, integrin components, members of the mitogen-activated protein kinase family, and Fc receptor elements. Partial overlap between mouse and human differentially expressed genes in IgAN further supported the translational aspect of the immune and inflammatory components from our transcriptional findings. In conclusion, our data indicate that in the mouse model of IgAN, sparsentan targets immune and inflammatory processes leading to protection from mesangial hypercellularity.NEW & NOTEWORTHY The mechanisms by which deposited IgA1 immune complexes cause kidney injury during early phases of IgA nephropathy are poorly understood. We used an animal model we recently developed that involves IgA1-IgG immune complex injections and determined pathways related to the induced mesangioproliferative changes. Treatment with sparsentan, a dual inhibitor of endothelin type A and angiotensin II type 1 receptors, ameliorated the induced mesangioproliferative changes and the associated alterations in the expression of inflammatory genes and networks.
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Affiliation(s)
- Colin Reily
- Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States
- Department of Microbiology, University of Alabama at Birmingham, Birmingham, Alabama, United States
| | - Zina Moldoveanu
- Department of Microbiology, University of Alabama at Birmingham, Birmingham, Alabama, United States
| | - Tiziano Pramparo
- Travere Therapeutics Incorporated, San Diego, California, United States
| | - Stacy Hall
- Department of Microbiology, University of Alabama at Birmingham, Birmingham, Alabama, United States
| | - Zhi-Qiang Huang
- Department of Microbiology, University of Alabama at Birmingham, Birmingham, Alabama, United States
| | - Terri Rice
- Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States
| | - Lea Novak
- Department of Microbiology, University of Alabama at Birmingham, Birmingham, Alabama, United States
| | - Radko Komers
- Travere Therapeutics Incorporated, San Diego, California, United States
| | - Celia P Jenkinson
- Travere Therapeutics Incorporated, San Diego, California, United States
| | - Jan Novak
- Department of Microbiology, University of Alabama at Birmingham, Birmingham, Alabama, United States
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7
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Cakir MO, Bilge U, Ghanbari A, Ashrafi GH. Regulatory Effect of Ficus carica Latex on Cell Cycle Progression in Human Papillomavirus-Positive Cervical Cancer Cell Lines: Insights from Gene Expression Analysis. Pharmaceuticals (Basel) 2023; 16:1723. [PMID: 38139849 PMCID: PMC10747314 DOI: 10.3390/ph16121723] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 12/10/2023] [Accepted: 12/11/2023] [Indexed: 12/24/2023] Open
Abstract
Cervical cancer presents a significant global health concern with high-risk human papillomaviruses (HPVs) identified as the main cause of this cancer. Although current treatment methods for cervical cancer can eliminate lesions, preventing metastatic spread and minimizing tissue damage remain a major challenge. Therefore, the development of a safer and innovative therapeutic approach is of the utmost importance. Natural products like fig latex, derived from the Ficus carica tree, have demonstrated promising anti-cancer properties when tested on cervical cancer cell lines. However, the specific mechanisms by which fig latex exerts its effects are still unknown. In this study, we conducted RNA-Seq analysis to explore how fig latex may counteract carcinogenesis in HPV-positive cervical cancer cell lines, namely, CaSki (HPV type 16-positive) and HeLa (HPV type 18-positive). Our results from this investigation indicate that fig latex influences the expression of genes associated with the development and progression of cervical cancer, including pathways related to "Nonsense-Mediated Decay (NMD)", "Cell Cycle regulation", "Transcriptional Regulation by TP53", and "Apoptotic Process". This selective impact of fig latex on cancer-related pathways suggests a potential novel therapeutic approach for HPV-related cervical cancer.
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Affiliation(s)
- Muharrem Okan Cakir
- School of Life Sciences, Pharmacy and Chemistry, Kingston University London, London KT1 2EE, UK; (M.O.C.); (A.G.)
| | - Ugur Bilge
- Department of Biostatistics and Medical Informatics, Faculty of Medicine, Akdeniz University, Antalya 07050, Turkey;
| | - Arshia Ghanbari
- School of Life Sciences, Pharmacy and Chemistry, Kingston University London, London KT1 2EE, UK; (M.O.C.); (A.G.)
| | - G. Hossein Ashrafi
- Department of Biostatistics and Medical Informatics, Faculty of Medicine, Akdeniz University, Antalya 07050, Turkey;
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8
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Kajana X, Spinelli S, Garbarino A, Balagura G, Bartolucci M, Petretto A, Pavanello M, Candiano G, Panfoli I, Bruschi M. Identification of Central Nervous System Oncologic Disease Biomarkers in EVs from Cerebrospinal Fluid (CSF) of Pediatric Patients: A Pilot Neuro-Proteomic Study. Biomolecules 2023; 13:1730. [PMID: 38136601 PMCID: PMC10741637 DOI: 10.3390/biom13121730] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 11/17/2023] [Accepted: 11/28/2023] [Indexed: 12/24/2023] Open
Abstract
Cerebrospinal fluid (CSF) is a biochemical-clinical window into the brain. Unfortunately, its wide dynamic range, low protein concentration, and small sample quantity significantly limit the possibility of using it routinely. Extraventricular drainage (EVD) of CSF allows us to solve quantitative problems and to study the biological role of extracellular vesicles (EVs). In this study, we implemented bioinformatic analysis of our previous data of EVD of CSF and its EVs obtained from congenital hydrocephalus with the aim of identifying a comprehensive list of potential tumor and non-tumor biomarkers of central nervous system diseases. Among all proteins identified, those enriched in EVs are associated with synapses, synaptosomes, and nervous system diseases including gliomas, embryonal tumors, and epilepsy. Among these EV-enriched proteins, given the broad consensus present in the recent scientific literature, we validated syntaxin-binding protein 1 (STXBP1) as a marker of malignancy in EVD of CSF and its EVs from patients with pilocytic astrocytoma and medulloblastoma. Our results show that STXBP1 is negatively enriched in EVs compared to non-tumor diseases and its downregulation correlates with adverse outcomes. Further experiments are needed to validate this and other EV markers in the blood of pediatric patients for translational medicine applications.
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Affiliation(s)
- Xhuliana Kajana
- Laboratory of Molecular Nephrology, IRCCS Istituto Giannina Gaslini, 16147 Genoa, Italy (S.S.)
| | - Sonia Spinelli
- Laboratory of Molecular Nephrology, IRCCS Istituto Giannina Gaslini, 16147 Genoa, Italy (S.S.)
| | - Andrea Garbarino
- Laboratory of Molecular Nephrology, IRCCS Istituto Giannina Gaslini, 16147 Genoa, Italy (S.S.)
| | - Ganna Balagura
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, University of Genoa, 16132 Genoa, Italy
| | - Martina Bartolucci
- Proteomics and Clinical Metabolomics Unit at the Core Facilities, IRCCS Istituto Giannina Gaslini, 16147 Genoa, Italy; (M.B.)
| | - Andrea Petretto
- Proteomics and Clinical Metabolomics Unit at the Core Facilities, IRCCS Istituto Giannina Gaslini, 16147 Genoa, Italy; (M.B.)
| | - Marco Pavanello
- Laboratory of Molecular Nephrology, IRCCS Istituto Giannina Gaslini, 16147 Genoa, Italy (S.S.)
| | - Giovanni Candiano
- Laboratory of Molecular Nephrology, IRCCS Istituto Giannina Gaslini, 16147 Genoa, Italy (S.S.)
| | - Isabella Panfoli
- Department of Pharmacy (DIFAR), School of Medical and Pharmaceutical Sciences, University of Genoa, 16132 Genoa, Italy
| | - Maurizio Bruschi
- Laboratory of Molecular Nephrology, IRCCS Istituto Giannina Gaslini, 16147 Genoa, Italy (S.S.)
- Department of Experimental Medicine (DIMES), University of Genoa, 16132 Genoa, Italy
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9
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Tian L, He M, Fan H, Zhang H, Dong X, Qiao M, Tang C, Yu Y, Chen T, Zhou N. COVID-19 of differing severity: from bulk to single-cell expression data analysis. Cell Cycle 2023; 22:1777-1797. [PMID: 37486005 PMCID: PMC10446813 DOI: 10.1080/15384101.2023.2239620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 04/03/2023] [Accepted: 06/24/2023] [Indexed: 07/25/2023] Open
Abstract
Coronavirus disease 2019 (COVID-19) is raging worldwide and causes an immense disease burden. Despite this, the biomarkers and targeting drugs of COVID-19 of differing severity remain largely unknown. Based on the GSE164805 dataset, we identified modules most critical for mild COVID-19 (mCOVID-19) and severe COVID-19 (sCOVID-19) through WGCNA, respectively. We subsequently constructed a protein-protein interaction network, and detected 16 hub genes for mCOVID-19 and 10 hub genes for sCOVID-19, followed by the prediction of upstream transcription factors (TFs) and kinases. The enrichment analysis then showed downregulation of TNFA signaling via NFKB for mCOVID-19, as well as downregulation of MYC targets V1 for sCOVID-19. Infiltration degrees of many immune cells, such as macrophages, were also sharply different between mCOVID-19 and sCOVID-19 samples. Predicted protein targeting drugs with the highest scores nearly all belong to naturally derived or synthetic glucocorticoids. For the two single-cell RNA-seq datasets, we explored the expression distribution of hub genes for mCOVID-19/sCOVID-19 in each cell type. The expression levels of PRKCA, MCM5, TYMS, RBBP4, BCL6, FLOT1, KDM6B, and TLR2 were found to be cell-type-specific. Furthermore, the expression levels of 10 hub genes for mCOVID-19 were significantly upregulated in PBMCs between eight healthy controls and eight mCOVID-19 patients at our institution. Collectively, we detected critical modules, pathways, TFs, kinases, immune cells, targeting drugs, hub genes, and their expression distributions in different cell types that may involve the pathogenesis of COVID-19 of differing severity, which may propel earlier diagnosis and more effective treatment of this intractable disease in the future.
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Affiliation(s)
- Linlin Tian
- Nanjing Municipal Center for Disease Control and Prevention, Nanjing, Jiangsu, P.R. China
| | - Min He
- Nanjing Municipal Center for Disease Control and Prevention, Nanjing, Jiangsu, P.R. China
| | - Huafeng Fan
- Nanjing Municipal Center for Disease Control and Prevention, Nanjing, Jiangsu, P.R. China
| | - Hongying Zhang
- Nanjing Municipal Center for Disease Control and Prevention, Nanjing, Jiangsu, P.R. China
| | - Xiaoxiao Dong
- Nanjing Municipal Center for Disease Control and Prevention, Nanjing, Jiangsu, P.R. China
| | - Mengkai Qiao
- Nanjing Municipal Center for Disease Control and Prevention, Nanjing, Jiangsu, P.R. China
| | - Chenyu Tang
- Nanjing Municipal Center for Disease Control and Prevention, Nanjing, Jiangsu, P.R. China
| | - Yan Yu
- Nanjing Municipal Center for Disease Control and Prevention, Nanjing, Jiangsu, P.R. China
| | - Tong Chen
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, P.R. China
| | - Nan Zhou
- Nanjing Municipal Center for Disease Control and Prevention, Nanjing, Jiangsu, P.R. China
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10
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Hills R, Mossman JA, Bratt-Leal AM, Tran H, Williams RM, Stouffer DG, Sokolova IV, Sanna PP, Loring JF, Lelos MJ. Neurite Outgrowth and Gene Expression Profile Correlate with Efficacy of Human Induced Pluripotent Stem Cell-Derived Dopamine Neuron Grafts. Stem Cells Dev 2023; 32:387-397. [PMID: 37166357 PMCID: PMC10398740 DOI: 10.1089/scd.2023.0043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Accepted: 05/08/2023] [Indexed: 05/12/2023] Open
Abstract
Transplantation of human induced pluripotent stem cell-derived dopaminergic (iPSC-DA) neurons is a promising therapeutic strategy for Parkinson's disease (PD). To assess optimal cell characteristics and reproducibility, we evaluated the efficacy of iPSC-DA neuron precursors from two individuals with sporadic PD by transplantation into a hemiparkinsonian rat model after differentiation for either 18 (d18) or 25 days (d25). We found similar graft size and dopamine (DA) neuron content in both groups, but only the d18 cells resulted in recovery of motor impairments. In contrast, we report that d25 grafts survived equally as well and produced grafts rich in tyrosine hydroxylase-positive neurons, but were incapable of alleviating any motor deficits. We identified the mechanism of action as the extent of neurite outgrowth into the host brain, with d18 grafts supporting significantly more neurite outgrowth than nonfunctional d25 grafts. RNAseq analysis of the cell preparation suggests that graft efficacy may be enhanced by repression of differentiation-associated genes by REST, defining the optimal predifferentiation state for transplantation. This study demonstrates for the first time that DA neuron grafts can survive well in vivo while completely lacking the capacity to induce recovery from motor dysfunction. In contrast to other recent studies, we demonstrate that neurite outgrowth is the key factor determining graft efficacy and our gene expression profiling revealed characteristics of the cells that may predict their efficacy. These data have implication for the generation of DA neuron grafts for clinical application.
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Affiliation(s)
- Rachel Hills
- Brain Repair Group, School of Biosciences, Cardiff University, Cardiff, United Kingdom
| | - Jim A. Mossman
- Independent Bioinformatics Consultant, Del Mar, California, USA
| | - Andres M. Bratt-Leal
- Department of Molecular Medicine, Center for Regenerative Medicine, Scripps Research, La Jolla, California, USA
- Summit for Stem Cell Foundation, San Diego, California, USA
| | - Ha Tran
- Department of Molecular Medicine, Center for Regenerative Medicine, Scripps Research, La Jolla, California, USA
- Summit for Stem Cell Foundation, San Diego, California, USA
| | - Roy M. Williams
- Department of Molecular Medicine, Center for Regenerative Medicine, Scripps Research, La Jolla, California, USA
| | - David G. Stouffer
- Department of Molecular Medicine, Center for Regenerative Medicine, Scripps Research, La Jolla, California, USA
| | - Irina V. Sokolova
- Department of Immunology and Microbiology, Scripps Research, La Jolla, California, USA
| | - Pietro P. Sanna
- Department of Immunology and Microbiology, Scripps Research, La Jolla, California, USA
| | - Jeanne F. Loring
- Department of Molecular Medicine, Center for Regenerative Medicine, Scripps Research, La Jolla, California, USA
| | - Mariah J. Lelos
- Brain Repair Group, School of Biosciences, Cardiff University, Cardiff, United Kingdom
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11
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Zhou F, Gao H, Shang L, Li J, Zhang M, Wang S, Li R, Ye L, Yang S. Oridonin promotes endoplasmic reticulum stress via TP53-repressed TCF4 transactivation in colorectal cancer. J Exp Clin Cancer Res 2023; 42:150. [PMID: 37337284 DOI: 10.1186/s13046-023-02702-4] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 05/09/2023] [Indexed: 06/21/2023] Open
Abstract
BACKGROUND The incidence of colorectal cancer and cancer death rate are increasing every year, and the affected population is becoming younger. Traditional Chinese medicine therapy has a unique effect in prolonging survival time and improving the prognosis of patients with colorectal cancer. Oridonin has been reported to have anti-cancer effects in a variety of tumors, but the exact mechanism remains to be investigated. METHODS Cell Counting Kit-8 assay (CCK8) and 5-Ethynyl-2'-deoxyuridine (EdU) staining assay, Tranwell, and Wound healing assays were performed to measure cell proliferation, invasion, and migration capacities, respectively. The protein and mRNA expression levels of various molecules were reflected by Western blot and Reverse Transcription quantitative Polymerase Chain Reaction (qRT-PCR). Transcription Factor 4 (TCF4) and its target genes were analyzed by Position Weight Matrices (PWMs) software and the Gene Expression Omnibus (GEO) database. Immunofluorescence (IF) was performed to visualize the expression and position of Endoplasmic Reticulum (ER) stress biomarkers. The morphology of the ER was demonstrated by the ER tracker-red. Reactive Oxygen Species (ROS) levels were measured using a flow cytometer (FCM) or fluorescent staining. Calcium ion (Ca2+) concentration was quantified by Fluo-3 AM staining. Athymic nude mice were modeled with subcutaneous xenografts. RESULTS Oridonin inhibited the proliferation, invasion, and migration of colorectal cancer, and this effect was weakened in a concentration-dependent manner by ER stress inhibitors. In addition, oridonin-induced colorectal tumor cells showed increased expression of ER stress biomarkers, loose morphology of ER, increased vesicles, and irregular shape. TCF4 was identified as a regulator of ER stress by PWMs software and GEO survival analysis. In vitro and in vivo experiments confirmed that TCF4 inhibited ER stress, reduced ROS production, and maintained Ca2+ homeostasis. In addition, oridonin also activated TP53 and inhibited TCF4 transactivation, further exacerbating the elevated ROS levels and calcium ion release in tumor cells and inhibiting tumorigenesis in colorectal cancer cells in vivo. CONCLUSIONS Oridonin upregulated TP53, inhibited TCF4 transactivation, and induced ER stress dysregulation in tumor cells, promoting colorectal cancer cell death. Therefore, TCF4 may be one of the important nodes for tumor cells to regulate ER stress and maintain protein synthesis homeostasis. And the inhibition of the TP53/TCF4 axis plays a key role in the anti-cancer effects of oridonin.
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Affiliation(s)
- Fangyuan Zhou
- Department of Integrated Traditional Chinese and Western Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Hubei Province, 1277 Jiefang Avenue, Wuhan, 430022, China
| | - Haiyang Gao
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Hubei Province, 1277 Jiefang Avenue, Wuhan, 430022, China
| | - Luorui Shang
- Department of Integrated Traditional Chinese and Western Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Hubei Province, 1277 Jiefang Avenue, Wuhan, 430022, China
| | - Jinxiao Li
- Department of Integrated Traditional Chinese and Western Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Hubei Province, 1277 Jiefang Avenue, Wuhan, 430022, China
| | - Mengqi Zhang
- Department of Integrated Traditional Chinese and Western Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Hubei Province, 1277 Jiefang Avenue, Wuhan, 430022, China
| | - Shuhan Wang
- Department of Integrated Traditional Chinese and Western Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Hubei Province, 1277 Jiefang Avenue, Wuhan, 430022, China
| | - Runze Li
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Hubei Province, 1277 Jiefang Avenue, Wuhan, 430022, China
| | - Lin Ye
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Hubei Province, 1277 Jiefang Avenue, Wuhan, 430022, China.
| | - Shenglan Yang
- Department of Integrated Traditional Chinese and Western Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Hubei Province, 1277 Jiefang Avenue, Wuhan, 430022, China.
- Clinical Nutrition Department, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Hubei Province, 1277 Jiefang Avenue, Wuhan, 430022, China.
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12
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Van de Graaf MW, Eggertsen TG, Zeigler AC, Tan PM, Saucerman JJ. Benchmarking of protein interaction databases for integration with manually reconstructed signalling network models. J Physiol 2023:10.1113/JP284616. [PMID: 37199469 PMCID: PMC11073820 DOI: 10.1113/jp284616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 05/10/2023] [Indexed: 05/19/2023] Open
Abstract
Protein interaction databases are critical resources for network bioinformatics and integrating molecular experimental data. Interaction databases may also enable construction of predictive computational models of biological networks, although their fidelity for this purpose is not clear. Here, we benchmark protein interaction databases X2K, Reactome, Pathway Commons, Omnipath and Signor for their ability to recover manually curated edges from three logic-based network models of cardiac hypertrophy, mechano-signalling and fibrosis. Pathway Commons performed best at recovering interactions from manually reconstructed hypertrophy (137 of 193 interactions, 71%), mechano-signalling (85 of 125 interactions, 68%) and fibroblast networks (98 of 142 interactions, 69%). While protein interaction databases successfully recovered central, well-conserved pathways, they performed worse at recovering tissue-specific and transcriptional regulation. This highlights a knowledge gap where manual curation is critical. Finally, we tested the ability of Signor and Pathway Commons to identify new edges that improve model predictions, revealing important roles of protein kinase C autophosphorylation and Ca2+ /calmodulin-dependent protein kinase II phosphorylation of CREB in cardiomyocyte hypertrophy. This study provides a platform for benchmarking protein interaction databases for their utility in network model construction, as well as providing new insights into cardiac hypertrophy signalling. KEY POINTS: Protein interaction databases are used to recover signalling interactions from previously developed network models. The five protein interaction databases benchmarked recovered well-conserved pathways, but did poorly at recovering tissue-specific pathways and transcriptional regulation, indicating the importance of manual curation. We identify new signalling interactions not previously used in the network models, including a role for Ca2+ /calmodulin-dependent protein kinase II phosphorylation of CREB in cardiomyocyte hypertrophy.
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Affiliation(s)
- Matthew W. Van de Graaf
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
- Children’s National Hospital, Washington, District of Columbia, USA
| | - Taylor G. Eggertsen
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Angela C. Zeigler
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
- Yale New Haven Hospital, New Haven, Connecticut, USA
| | - Philip M. Tan
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Jeffrey J. Saucerman
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
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13
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Banos A, Thomas K, Garantziotis P, Filia A, Malissovas N, Pieta A, Nikolakis D, Panagiotopoulos AG, Chalkia A, Petras D, Bertsias G, Boumpas DT, Vassilopoulos D. The genomic landscape of ANCA-associated vasculitis: Distinct transcriptional signatures, molecular endotypes and comparison with systemic lupus erythematosus. Front Immunol 2023; 14:1072598. [PMID: 37051253 PMCID: PMC10083368 DOI: 10.3389/fimmu.2023.1072598] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 03/13/2023] [Indexed: 03/29/2023] Open
Abstract
IntroductionAnti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitides (AAVs) present with a complex phenotype and are associated with high mortality and multi-organ involvement. We sought to define the transcriptional landscape and molecular endotypes of AAVs and compare it to systemic lupus erythematosus (SLE).MethodsWe performed whole blood mRNA sequencing from 30 patients with AAV (granulomatosis with polyangiitis/GPA and microscopic polyangiitis/MPA) combined with functional enrichment and network analysis for aberrant pathways. Key genes and pathways were validated in an independent cohort of 18 AAV patients. Co-expression network and hierarchical clustering analysis, identified molecular endotypes. Multi-level transcriptional overlap analysis to SLE was based on our published data from 142 patients.ResultsWe report here that “Pan-vasculitis” signature contained 1,982 differentially expressed genes, enriched in leukocyte differentiation, cytokine signaling, type I and type II IFN signaling and aberrant B-T cell immunity. Active disease was characterized by signatures linked to cell cycle checkpoints and metabolism pathways, whereas ANCA-positive patients exhibited a humoral immunity transcriptional fingerprint. Differential expression analysis of GPA and MPA yielded an IFN-g pathway (in addition to a type I IFN) in the former and aberrant expression of genes related to autophagy and mRNA splicing in the latter. Unsupervised molecular taxonomy analysis revealed four endotypes with neutrophil degranulation, aberrant metabolism and B-cell responses as potential mechanistic drivers. Transcriptional perturbations and molecular heterogeneity were more pronounced in SLE. Molecular analysis and data-driven clustering of AAV uncovered distinct transcriptional pathways that could be exploited for targeted therapy.DiscussionWe conclude that transcriptomic analysis of AAV reveals distinct endotypes and molecular pathways that could be targeted for therapy. The AAV transcriptome is more homogenous and less fragmented compared to the SLE which may account for its superior rates of response to therapy.
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Affiliation(s)
- Aggelos Banos
- Laboratory of Autoimmunity and Inflammation, Center for Clinical, Experimental Surgery and Translational Research, Biomedical Research Foundation of the Academy of Athens, Athens, Greece
| | - Konstantinos Thomas
- Clinical Immunology- Rheumatology Unit, 2nd Department of Medicine and Laboratory, General Hospital of Athens Ippokrateio, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Panagiotis Garantziotis
- Laboratory of Autoimmunity and Inflammation, Center for Clinical, Experimental Surgery and Translational Research, Biomedical Research Foundation of the Academy of Athens, Athens, Greece
- Department Rheumatology and Immunology, Hannover Medical School, Hannover, Germany
| | - Anastasia Filia
- Laboratory of Autoimmunity and Inflammation, Center for Clinical, Experimental Surgery and Translational Research, Biomedical Research Foundation of the Academy of Athens, Athens, Greece
| | - Nikolaos Malissovas
- Laboratory of Autoimmunity and Inflammation, Center for Clinical, Experimental Surgery and Translational Research, Biomedical Research Foundation of the Academy of Athens, Athens, Greece
| | - Antigone Pieta
- Laboratory of Autoimmunity and Inflammation, Center for Clinical, Experimental Surgery and Translational Research, Biomedical Research Foundation of the Academy of Athens, Athens, Greece
- Rheumatology and Clinical Immunology Unit, 4th Department of Internal Medicine, Attikon University Hospital, Athens, Greece
| | - Dimitrios Nikolakis
- Laboratory of Autoimmunity and Inflammation, Center for Clinical, Experimental Surgery and Translational Research, Biomedical Research Foundation of the Academy of Athens, Athens, Greece
- Amsterdam Institute for Gastroenterology Endocrinology and Metabolism, Department of Gastroenterology, Academic Medical Center, Amsterdam University Medical Centers (UMC), University of Amsterdam, Amsterdam, Netherlands
- Department of Rheumatology and Clinical Immunology, Amsterdam Rheumatology & Immunology Center (ARC), Amsterdam University Medical Centers (UMC), University of Amsterdam, Amsterdam, Netherlands
- Amsterdam Institute for Infection & Immunity, Department of Experimental Immunology, Amsterdam University Medical Centers (UMC), University of Amsterdam, Amsterdam, Netherlands
| | - Alexandros G. Panagiotopoulos
- Clinical Immunology- Rheumatology Unit, 2nd Department of Medicine and Laboratory, General Hospital of Athens Ippokrateio, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Aglaia Chalkia
- Nephrology Department, General Hospital of Athens Ippokrateio, Athens, Greece
| | - Dimitrios Petras
- Nephrology Department, General Hospital of Athens Ippokrateio, Athens, Greece
| | - George Bertsias
- Department of Rheumatology and Clinical Immunology, University Hospital of Heraklion, Medical School, University of Crete, Heraklion, Greece
- Department of Immunity, Institute of Molecular Biology and Biotechnology-Foundation of Research and Technology-Hellas (FORTH), Heraklion, Greece
| | - Dimitrios T. Boumpas
- Laboratory of Autoimmunity and Inflammation, Center for Clinical, Experimental Surgery and Translational Research, Biomedical Research Foundation of the Academy of Athens, Athens, Greece
- Rheumatology and Clinical Immunology Unit, 4th Department of Internal Medicine, Attikon University Hospital, Athens, Greece
- Joint Academic Rheumatology Program, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Dimitrios Vassilopoulos
- Clinical Immunology- Rheumatology Unit, 2nd Department of Medicine and Laboratory, General Hospital of Athens Ippokrateio, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
- Joint Academic Rheumatology Program, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
- *Correspondence: Dimitrios Vassilopoulos,
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Kamolphiwong R, Kanokwiroon K, Wongrin W, Chaiyawat P, Klangjorhor J, Settakorn J, Teeyakasem P, Sangphukieo A, Pruksakorn D. Potential target identification for osteosarcoma treatment: Gene expression re-analysis and drug repurposing. Gene X 2023; 856:147106. [PMID: 36513192 DOI: 10.1016/j.gene.2022.147106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 11/18/2022] [Accepted: 12/06/2022] [Indexed: 12/14/2022] Open
Abstract
Survival rate of osteosarcoma has remained plateaued for the past three decades. New treatment is needed to improve survival rate. Drug repurposing, a method to identify new indications of previous drugs, which saves time and cost compared to the de novo drug discovery. Data mining from gene expression profile was carried out and new potential targets were identified by using drug repurposing strategy. Selected data were newly categorized as pathophysiology and metastasis groups. Data were normalized and calculated the differential gene expression. Genes with log fold change ≥ 2 and adjusted p-value ≤ 0.05 were selected as primary candidate genes (PCGs). PCGs were further enriched to determine the secondary candidate genes (SCGs) by protein interaction analysis, upstream transcription factor and related-protein kinase identification. PCGs and SCGs were further matched with gene targeted of corresponding drugs from the Drug Repurposing Hub. A total of 778 targets were identified (360 from PCGs, and 418 from SCGs). This newly identified KLHL13 is a new candidate target based on its molecular function. KLHL13 was upregulated in clinical samples. We found 256 drugs from matching processes (50anti-cancerand206non-anticancerdrugs). Clinical trials of anti-cancer drugs from 5 targets (CDK4, BCL-2, JUN, SRC, PIK3CA) are being performed for osteosarcoma treatment. Niclosamide and synthetic PPARɣ ligands are candidates for repurposing due to the possibility based on their mechanism and pharmacology properties. Re-analysis of gene expression profile could identify new potential targets, confirm a current implication, and expand the chance of repurposing drugs for osteosarcoma treatment.
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Affiliation(s)
- Rawikant Kamolphiwong
- Department of Biomedical Sciences and Biomedical Engineering, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand
| | - Kanyanatt Kanokwiroon
- Department of Biomedical Sciences and Biomedical Engineering, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand.
| | - Weerinrada Wongrin
- Department of Statistics, Faculty of Science, Chiang Mai University, Chiang Mai, Thailand
| | - Parunya Chaiyawat
- Musculoskeletal Science and Translational Research Center, Department of Orthopaedics, Chiang Mai University, Chiang Mai, Thailand; Center of Multidisciplinary Technology for Advanced Medicine (CMUTEAM), Faculty of Medicine, Chiang Mai University, Thailand
| | - Jeerawan Klangjorhor
- Musculoskeletal Science and Translational Research Center, Department of Orthopaedics, Chiang Mai University, Chiang Mai, Thailand; Center of Multidisciplinary Technology for Advanced Medicine (CMUTEAM), Faculty of Medicine, Chiang Mai University, Thailand
| | - Jongkolnee Settakorn
- Department of Pathology, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand
| | - Pimpisa Teeyakasem
- Musculoskeletal Science and Translational Research Center, Department of Orthopaedics, Chiang Mai University, Chiang Mai, Thailand
| | - Apiwat Sangphukieo
- Center of Multidisciplinary Technology for Advanced Medicine (CMUTEAM), Faculty of Medicine, Chiang Mai University, Thailand
| | - Dumnoensun Pruksakorn
- Musculoskeletal Science and Translational Research Center, Department of Orthopaedics, Chiang Mai University, Chiang Mai, Thailand; Center of Multidisciplinary Technology for Advanced Medicine (CMUTEAM), Faculty of Medicine, Chiang Mai University, Thailand.
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15
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Vom Stein AF, Rebollido-Rios R, Lukas A, Koch M, von Lom A, Reinartz S, Bachurski D, Rose F, Bozek K, Abdallah AT, Kohlhas V, Saggau J, Zölzer R, Zhao Y, Bruns C, Bröckelmann PJ, Lohneis P, Büttner R, Häupl B, Oellerich T, Nguyen PH, Hallek M. LYN kinase programs stromal fibroblasts to facilitate leukemic survival via regulation of c-JUN and THBS1. Nat Commun 2023; 14:1330. [PMID: 36899005 PMCID: PMC10006233 DOI: 10.1038/s41467-023-36824-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 02/14/2023] [Indexed: 03/12/2023] Open
Abstract
Microenvironmental bystander cells are essential for the progression of chronic lymphocytic leukemia (CLL). We have discovered previously that LYN kinase promotes the formation of a microenvironmental niche for CLL. Here we provide mechanistic evidence that LYN regulates the polarization of stromal fibroblasts to support leukemic progression. LYN is overexpressed in fibroblasts of lymph nodes of CLL patients. LYN-deficient stromal cells reduce CLL growth in vivo. LYN-deficient fibroblasts show markedly reduced leukemia feeding capacity in vitro. Multi-omics profiling reveals that LYN regulates the polarization of fibroblasts towards an inflammatory cancer-associated phenotype through modulation of cytokine secretion and extracellular matrix composition. Mechanistically, LYN deletion reduces inflammatory signaling including reduction of c-JUN expression, which in turn augments the expression of Thrombospondin-1, which binds to CD47 thereby impairing CLL viability. Together, our findings suggest that LYN is essential for rewiring fibroblasts towards a leukemia-supportive phenotype.
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Affiliation(s)
- Alexander F Vom Stein
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf, Cologne, Germany
- Center for Molecular Medicine Cologne, University of Cologne, Cologne, Germany
- CECAD Center of Excellence on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany
| | - Rocio Rebollido-Rios
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf, Cologne, Germany
- Center for Molecular Medicine Cologne, University of Cologne, Cologne, Germany
- CECAD Center of Excellence on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany
| | - Anna Lukas
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf, Cologne, Germany
- Center for Molecular Medicine Cologne, University of Cologne, Cologne, Germany
- CECAD Center of Excellence on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany
| | - Maximilian Koch
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf, Cologne, Germany
- Center for Molecular Medicine Cologne, University of Cologne, Cologne, Germany
- CECAD Center of Excellence on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany
| | - Anton von Lom
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf, Cologne, Germany
- Center for Molecular Medicine Cologne, University of Cologne, Cologne, Germany
- CECAD Center of Excellence on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany
- Mildred Scheel School of Oncology Aachen Bonn Cologne Düsseldorf, Faculty of Medicine and University Hospital of Cologne, Cologne, Germany
| | - Sebastian Reinartz
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf, Cologne, Germany
- Center for Molecular Medicine Cologne, University of Cologne, Cologne, Germany
- CECAD Center of Excellence on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany
| | - Daniel Bachurski
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf, Cologne, Germany
- Center for Molecular Medicine Cologne, University of Cologne, Cologne, Germany
- CECAD Center of Excellence on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany
- Mildred Scheel School of Oncology Aachen Bonn Cologne Düsseldorf, Faculty of Medicine and University Hospital of Cologne, Cologne, Germany
| | - France Rose
- Center for Molecular Medicine Cologne, University of Cologne, Cologne, Germany
- University of Cologne, Institute for Biomedical Informatics, Faculty of Medicine and University Hospital Cologne, Cologne, Germany
| | - Katarzyna Bozek
- Center for Molecular Medicine Cologne, University of Cologne, Cologne, Germany
- CECAD Center of Excellence on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany
- University of Cologne, Institute for Biomedical Informatics, Faculty of Medicine and University Hospital Cologne, Cologne, Germany
| | - Ali T Abdallah
- CECAD Center of Excellence on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany
| | - Viktoria Kohlhas
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf, Cologne, Germany
- Center for Molecular Medicine Cologne, University of Cologne, Cologne, Germany
- CECAD Center of Excellence on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany
| | - Julia Saggau
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf, Cologne, Germany
- Center for Molecular Medicine Cologne, University of Cologne, Cologne, Germany
- CECAD Center of Excellence on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany
| | - Rebekka Zölzer
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf, Cologne, Germany
- Center for Molecular Medicine Cologne, University of Cologne, Cologne, Germany
- CECAD Center of Excellence on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany
| | - Yue Zhao
- Faculty of Medicine and University Hospital Cologne, Department of General, Visceral and Cancer Surgery, University of Cologne, Cologne, Germany
| | - Christiane Bruns
- Faculty of Medicine and University Hospital Cologne, Department of General, Visceral and Cancer Surgery, University of Cologne, Cologne, Germany
| | - Paul J Bröckelmann
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf, Cologne, Germany
- Mildred Scheel School of Oncology Aachen Bonn Cologne Düsseldorf, Faculty of Medicine and University Hospital of Cologne, Cologne, Germany
- Max-Planck Institute for the Biology of Ageing, Cologne, Germany
| | - Philipp Lohneis
- Reference Centre for Lymph Node Pathology and Hematopathology, Hämatopathologie Lübeck, Lübeck, Germany
- Faculty of Medicine and University Hospital Cologne, Department of Pathology, University of Cologne, Cologne, Germany
| | - Reinhard Büttner
- Faculty of Medicine and University Hospital Cologne, Department of Pathology, University of Cologne, Cologne, Germany
| | - Björn Häupl
- Department of Hematology/Oncology, Johann Wolfgang Goethe University, Frankfurt, Germany
- German Cancer Consortium (DKTK), Heidelberg, Germany
- German Cancer Research Center (DKFZ), Heidelberg, Germany
- Frankfurt Cancer Institute, Goethe University Frankfurt, Frankfurt, Germany
| | - Thomas Oellerich
- Department of Hematology/Oncology, Johann Wolfgang Goethe University, Frankfurt, Germany
- German Cancer Consortium (DKTK), Heidelberg, Germany
- German Cancer Research Center (DKFZ), Heidelberg, Germany
- Frankfurt Cancer Institute, Goethe University Frankfurt, Frankfurt, Germany
| | - Phuong-Hien Nguyen
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf, Cologne, Germany.
- Center for Molecular Medicine Cologne, University of Cologne, Cologne, Germany.
- CECAD Center of Excellence on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany.
| | - Michael Hallek
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf, Cologne, Germany.
- Center for Molecular Medicine Cologne, University of Cologne, Cologne, Germany.
- CECAD Center of Excellence on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany.
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16
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Hussien AA, Niederoest B, Bollhalder M, Goedecke N, Snedeker JG. The Stiffness-Sensitive Transcriptome of Human Tendon Stromal Cells. Adv Healthc Mater 2023; 12:e2101216. [PMID: 36509005 DOI: 10.1002/adhm.202101216] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 11/20/2022] [Indexed: 12/14/2022]
Abstract
Extracellular matrix stiffness is a major regulator of cellular states. Stiffness-sensing investigations are typically performed using cells that have acquired "mechanical memory" through prolonged conditioning in rigid environments, e.g., tissue culture plastic (TCP). This potentially masks the full extent of the matrix stiffness-driven mechanosensing programs. Here, a biomaterial composed of 2D mechanovariant silicone substrates with simplified and scalable surface biofunctionalization chemistry is developed to facilitate large-scale cell culture expansion processes. Using RNA sequencing, stiffness-mediated mechano-responses of human tendon-derived stromal cells are broadly mapped. Matrix elasticity (E.) approximating tendon microscale stiffness range (E. ≈ 35 kPa) distinctly favors transcriptional programs related to chromatin remodeling and Hippo signaling; whereas compliant stiffnesses (E. ≈ 2 kPa) are enriched in processes related to cell stemness, synapse assembly, and angiogenesis. While tendon stromal cells undergo dramatic phenotypic drift on conventional TCP, mechanovariant substrates abrogate this activation with tenogenic stiffnesses inducing a transcriptional program that strongly correlates with established tendon tissue-specific expression signature. Computational inference predicts that AKT1 and ERK1/2 are major stiffness-sensing signaling hubs. Together, these findings highlight how matrix biophysical cues may dictate the transcriptional identity of tendon cells, and how matrix mechano-reciprocity regulates diverse sets of previously underappreciated mechanosensitive processes in tendon fibroblasts.
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Affiliation(s)
- Amro A Hussien
- Institute for Biomechanics, ETH Zurich, Zurich, 8092, Switzerland.,Balgrist University Hospital, University of Zurich, Zurich, 8008, Switzerland
| | - Barbara Niederoest
- Institute for Biomechanics, ETH Zurich, Zurich, 8092, Switzerland.,Balgrist University Hospital, University of Zurich, Zurich, 8008, Switzerland
| | - Maja Bollhalder
- Institute for Biomechanics, ETH Zurich, Zurich, 8092, Switzerland.,Balgrist University Hospital, University of Zurich, Zurich, 8008, Switzerland
| | - Nils Goedecke
- Institute for Biomechanics, ETH Zurich, Zurich, 8092, Switzerland.,Balgrist University Hospital, University of Zurich, Zurich, 8008, Switzerland
| | - Jess G Snedeker
- Institute for Biomechanics, ETH Zurich, Zurich, 8092, Switzerland.,Balgrist University Hospital, University of Zurich, Zurich, 8008, Switzerland
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17
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Castillo-Velázquez R, Martínez-Morales F, Castañeda-Delgado JE, García-Hernández MH, Herrera-Mayorga V, Paredes-Sánchez FA, Rivera G, Rivas-Santiago B, Lara-Ramírez EE. Bioinformatic prediction of the molecular links between Alzheimer's disease and diabetes mellitus. PeerJ 2023; 11:e14738. [PMID: 36778155 PMCID: PMC9912946 DOI: 10.7717/peerj.14738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Accepted: 12/22/2022] [Indexed: 02/10/2023] Open
Abstract
Background Alzheimer's disease (AD) and type 2 diabetes mellitus (DM2) are chronic degenerative diseases with complex molecular processes that are potentially interconnected. The aim of this work was to predict the potential molecular links between AD and DM2 from different sources of biological information. Materials and Methods In this work, data mining of nine databases (DisGeNET, Ensembl, OMIM, Protein Data Bank, The Human Protein Atlas, UniProt, Gene Expression Omnibus, Human Cell Atlas, and PubMed) was performed to identify gene and protein information that was shared in AD and DM2. Next, the information was mapped to human protein-protein interaction (PPI) networks based on experimental data using the STRING web platform. Then, gene ontology biological process (GOBP) and pathway analyses with EnrichR showed its specific and shared biological process and pathway deregulations. Finally, potential biomarkers and drug targets were predicted with the Metascape platform. Results A total of 1,551 genes shared in AD and DM2 were identified. The highest average degree of nodes within the PPI was for DM2 (average = 2.97), followed by AD (average degree = 2.35). GOBP for AD was related to specific transcriptional and translation genetic terms occurring in neurons cells. The GOBP and pathway information for the association AD-DM2 were linked mainly to bioenergetics and cytokine signaling. Within the AD-DM2 association, 10 hub proteins were identified, seven of which were predicted to be present in plasma and exhibit pharmacological interaction with monoclonal antibodies in use, anticancer drugs, and flavonoid derivatives. Conclusion Our data mining and analysis strategy showed that there are a plenty of biological information based on experiments that links AD and DM2, which could provide a rational guide to design further diagnosis and treatment for AD and DM2.
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Affiliation(s)
- Ricardo Castillo-Velázquez
- Unidad de Investigación Biomédica de Zacatecas, Instituto Mexicano del Seguro Social, Zacatecas, Zacatecas, México,Centro de Investigación en Ciencias de la Salud y Biomedicina, Universidad Autónoma de San Luis, San Luis Potosí, San Luis Potosí, México
| | - Flavio Martínez-Morales
- Departamento de Farmacología, Facultad de Medicina, Universidad Autónoma de San Luis, San Luis Potosí, San Luis Potosí, México
| | - Julio E. Castañeda-Delgado
- Unidad de Investigación Biomédica de Zacatecas, Instituto Mexicano del Seguro Social, Zacatecas, Zacatecas, México,Investigadores por México, CONACYT, Consejo Nacional de Ciencia y Tecnología, Zacatecas, Zacatecas, México
| | - Mariana H. García-Hernández
- Unidad de Investigación Biomédica de Zacatecas, Instituto Mexicano del Seguro Social, Zacatecas, Zacatecas, México
| | - Verónica Herrera-Mayorga
- Unidad Académica Multidisciplinaria Mante, Universidad Autónoma de Tamaulipas, Mante, Tamaulipas, México
| | | | - Gildardo Rivera
- Laboratorio de Biotecnología Farmacéutica, Centro de Biotecnología Genómica, Instituto Politécnico Nacional, Reynosa, Tamaulipas, México
| | - Bruno Rivas-Santiago
- Unidad de Investigación Biomédica de Zacatecas, Instituto Mexicano del Seguro Social, Zacatecas, Zacatecas, México
| | - Edgar E. Lara-Ramírez
- Unidad de Investigación Biomédica de Zacatecas, Instituto Mexicano del Seguro Social, Zacatecas, Zacatecas, México,Laboratorio de Biotecnología Farmacéutica, Centro de Biotecnología Genómica, Instituto Politécnico Nacional, Reynosa, Tamaulipas, México
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18
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Sicotte H, Kalari KR, Qin S, Dehm SM, Bhargava V, Gormley M, Tan W, Sinnwell JP, Hillman DW, Li Y, Vedell PT, Carlson RE, Bryce AH, Jimenez RE, Weinshilboum RM, Kohli M, Wang L. Molecular Profile Changes in Patients with Castrate-Resistant Prostate Cancer Pre- and Post-Abiraterone/Prednisone Treatment. Mol Cancer Res 2022; 20:1739-1750. [PMID: 36135372 PMCID: PMC9716248 DOI: 10.1158/1541-7786.mcr-22-0099] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Revised: 07/05/2022] [Accepted: 09/02/2022] [Indexed: 01/15/2023]
Abstract
We identified resistance mechanisms to abiraterone acetate/prednisone (AA/P) in patients with metastatic castration-resistant prostate cancer (mCRPC) in the Prostate Cancer Medically Optimized Genome-Enhanced Therapy (PROMOTE) study. We analyzed whole-exome sequencing (WES) and RNA-sequencing data from 83 patients with metastatic biopsies before (V1) and after 12 weeks of AA/P treatment (V2). Resistance was determined by time to treatment change (TTTC). At V2, 18 and 11 of 58 patients had either short-term (median 3.6 months; range 1.4-4.5) or long-term (median 29 months; range 23.5-41.7) responses, respectively. Nonresponders had low expression of TGFBR3 and increased activation of the Wnt pathway, cell cycle, upregulation of AR variants, both pre- and posttreatment, with further deletion of AR inhibitor CDK11B posttreatment. Deletion of androgen processing genes, HSD17B11, CYP19A1 were observed in nonresponders posttreatment. Genes involved in cell cycle, DNA repair, Wnt-signaling, and Aurora kinase pathways were differentially expressed between the responder and non-responder at V2. Activation of Wnt signaling in nonresponder and deactivation of MYC or its target genes in responders was detected via SCN loss, somatic mutations, and transcriptomics. Upregulation of genes in the AURKA pathway are consistent with the activation of MYC regulated genes in nonresponders. Several genes in the AKT1 axis had increased mutation rate in nonresponders. We also found evidence of resistance via PDCD1 overexpression in responders. IMPLICATIONS Finally, we identified candidates drugs to reverse AA/P resistance: topoisomerase inhibitors and drugs targeting the cell cycle via the MYC/AURKA/AURKB/TOP2A and/or PI3K_AKT_MTOR pathways.
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Affiliation(s)
- Hugues Sicotte
- Division of Biomedical Statistics and Informatics, Department of Quantitative Health Sciences Research, Mayo Clinic, Rochester, Minnesota
| | - Krishna R. Kalari
- Division of Biomedical Statistics and Informatics, Department of Quantitative Health Sciences Research, Mayo Clinic, Rochester, Minnesota
| | - Sisi Qin
- Department of Pathology, The University of Chicago., Chicago, Illinois
| | - Scott M. Dehm
- Masonic Cancer Center and Departments of Laboratory Medicine and Pathology and Urology, University of Minnesota, Minneapolis, Minnesota
| | - Vipul Bhargava
- Janssen Research and Development, Spring House, Pennsylvania
| | - Michael Gormley
- Janssen Research and Development, Spring House, Pennsylvania
| | - Winston Tan
- Department of Medicine, Mayo Clinic, Jacksonville, Florida
| | - Jason P. Sinnwell
- Division of Biomedical Statistics and Informatics, Department of Quantitative Health Sciences Research, Mayo Clinic, Rochester, Minnesota
| | - David W. Hillman
- Division of Biomedical Statistics and Informatics, Department of Quantitative Health Sciences Research, Mayo Clinic, Rochester, Minnesota
| | - Ying Li
- Division of Biomedical Statistics and Informatics, Department of Quantitative Health Sciences Research, Mayo Clinic, Rochester, Minnesota
| | - Peter T. Vedell
- Division of Biomedical Statistics and Informatics, Department of Quantitative Health Sciences Research, Mayo Clinic, Rochester, Minnesota
| | - Rachel E. Carlson
- Division of Biomedical Statistics and Informatics, Department of Quantitative Health Sciences Research, Mayo Clinic, Rochester, Minnesota
| | - Alan H. Bryce
- Division of Hematology & Medical Oncology, Mayo Clinic, Rochester, Minnesota
| | | | - Richard M. Weinshilboum
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, Minnesota
| | - Manish Kohli
- Department of Internal Medicine, University of Utah and Huntsman Cancer Institute, Salt Lake City, Utah
| | - Liewei Wang
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, Minnesota
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19
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Signatures of Co-Deregulated Genes and Their Transcriptional Regulators in Lung Cancer. Int J Mol Sci 2022; 23:ijms231810933. [PMID: 36142846 PMCID: PMC9504879 DOI: 10.3390/ijms231810933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 09/13/2022] [Indexed: 11/24/2022] Open
Abstract
Despite the significant progress made towards comprehending the deregulated signatures in lung cancer, these vary from study to study. We reanalyzed 25 studies from the Gene Expression Omnibus (GEO) to detect and annotate co-deregulated signatures in lung cancer and in single-gene or single-drug perturbation experiments. We aimed to decipher the networks that these co-deregulated genes (co-DEGs) form along with their upstream regulators. Differential expression and upstream regulators were computed using Characteristic Direction and Systems Biology tools, including GEO2Enrichr and X2K. Co-deregulated gene expression profiles were further validated across different molecular and immune subtypes in lung adenocarcinoma (TCGA-LUAD) and lung adenocarcinoma (TCGA-LUSC) datasets, as well as using immunohistochemistry data from the Human Protein Atlas, before being subjected to subsequent GO and KEGG enrichment analysis. The functional alterations of the co-upregulated genes in lung cancer were mostly related to immune response regulating the cell surface signaling pathway, in contrast to the co-downregulated genes, which were related to S-nitrosylation. Networks of hub proteins across the co-DEGs consisted of overlapping TFs (SOX2, MYC, KAT2A) and kinases (MAPK14, CSNK2A1 and CDKs). Furthermore, using Connectivity Map we highlighted putative repurposing drugs, including valproic acid, betonicine and astemizole. Similarly, we analyzed the co-DEG signatures in single-gene and single-drug perturbation experiments in lung cancer cell lines. In summary, we identified critical co-DEGs in lung cancer providing an innovative framework for their potential use in developing personalized therapeutic strategies.
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20
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Chen Q, Lai Q, Jiang Y, Yao J, Chen Q, Zhang L, Wang C, Zhou Y, Deng M, Xu B. Anlotinib exerts potent antileukemic activities in Ph chromosome negative and positive B-cell acute lymphoblastic leukemia via perturbation of PI3K/AKT/mTOR pathway. Transl Oncol 2022; 25:101516. [PMID: 35985203 PMCID: PMC9418595 DOI: 10.1016/j.tranon.2022.101516] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 07/21/2022] [Accepted: 08/09/2022] [Indexed: 11/26/2022] Open
Abstract
OBJECTIVES Despite advances in the development of novel targeted therapies, the need for B-ALL alternative treatments has not been met. Anlotinib could blunt the proangiogenic activity of VEGFR, PDGFR, and FGFR, and has shown strong antitumor activities across multiple tumors. However, anlotinib cytotoxicity against B-ALL has not ever been evaluated, thus prompting us to initiate this study. METHODS Expression2Kinases program was used to identify potential treatment targets. Cell viability and apoptosis were determined by CCK-8 and Annexin V/PI staining kit, respectively. qRT-PCR and Western blotting were utilized to investigate the molecular mechanisms. In vivo antileukemia activity of Anlotinib was evaluated in a Ph+ B-ALL patient-Derived Xenograft (PDX) model. RESULTS Compared with treatment-naive B-ALL cases, RR B-ALL patients had higher activities in the VEGF/VEGFR signaling and the PI3K/AKT/mTOR pathway. Exposure of Ph- and Ph+ B-ALL cells to anlotinib resulted in significant cell viability reduction, apoptosis enhancement, and cell cycle arrest at G2/M phase. Importantly, anlotinib treatment led to remarkably decreased leukemia burdens and extended the survival period in a Ph+ B-ALL PDX model. Blockade of the role of the proangiogenic mediators, comprising VEGFR2, PDGFR-beta, and FGFR3, played a critical role in the cytotoxicity of anlotinib against Ph- and Ph+ B-ALL. Moreover, anlotinib dampened the activity of PI3K/AKT/mTOR pathway that resides in the convergence of the three mentioned proangiogenic signals. CONCLUSION This work provides impressive preclinical evidence of anlotinib against Ph- and Ph+ B-ALL and raises a rationale for future clinical evaluation of this drug in the management of Ph- and Ph+ B-ALL.
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Affiliation(s)
- Qiuling Chen
- Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, No.55, Zhenhai Road, Siming District, Xiamen, Fujian 361003, China; Key Laboratory of Xiamen for Diagnosis and Treatment of Hematological Malignancy, Xiamen 361102, China; Department of Hematology & Oncology, Fujian Children's Hospital, Fujian Branch of Shanghai Children's Medical Center, Fuzhou 350000, China
| | - Qian Lai
- Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, No.55, Zhenhai Road, Siming District, Xiamen, Fujian 361003, China; Key Laboratory of Xiamen for Diagnosis and Treatment of Hematological Malignancy, Xiamen 361102, China
| | - Yuelong Jiang
- Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, No.55, Zhenhai Road, Siming District, Xiamen, Fujian 361003, China; Key Laboratory of Xiamen for Diagnosis and Treatment of Hematological Malignancy, Xiamen 361102, China
| | - Jingwei Yao
- Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, No.55, Zhenhai Road, Siming District, Xiamen, Fujian 361003, China; Key Laboratory of Xiamen for Diagnosis and Treatment of Hematological Malignancy, Xiamen 361102, China
| | - Qinwei Chen
- Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, No.55, Zhenhai Road, Siming District, Xiamen, Fujian 361003, China; Key Laboratory of Xiamen for Diagnosis and Treatment of Hematological Malignancy, Xiamen 361102, China
| | - Li Zhang
- Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, No.55, Zhenhai Road, Siming District, Xiamen, Fujian 361003, China; Key Laboratory of Xiamen for Diagnosis and Treatment of Hematological Malignancy, Xiamen 361102, China
| | - Caiyan Wang
- Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, No.55, Zhenhai Road, Siming District, Xiamen, Fujian 361003, China; Key Laboratory of Xiamen for Diagnosis and Treatment of Hematological Malignancy, Xiamen 361102, China
| | - Yong Zhou
- Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, No.55, Zhenhai Road, Siming District, Xiamen, Fujian 361003, China; Key Laboratory of Xiamen for Diagnosis and Treatment of Hematological Malignancy, Xiamen 361102, China.
| | - Manman Deng
- Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, No.55, Zhenhai Road, Siming District, Xiamen, Fujian 361003, China; Key Laboratory of Xiamen for Diagnosis and Treatment of Hematological Malignancy, Xiamen 361102, China.
| | - Bing Xu
- Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, No.55, Zhenhai Road, Siming District, Xiamen, Fujian 361003, China; Key Laboratory of Xiamen for Diagnosis and Treatment of Hematological Malignancy, Xiamen 361102, China.
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21
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Frangou E, Garantziotis P, Grigoriou M, Banos A, Nikolopoulos D, Pieta A, Doumas SA, Fanouriakis A, Hatzioannou A, Manolakou T, Alissafi T, Verginis P, Athanasiadis E, Dermitzakis E, Bertsias G, Filia A, Boumpas DT. Cross-species transcriptome analysis for early detection and specific therapeutic targeting of human lupus nephritis. Ann Rheum Dis 2022; 81:1409-1419. [PMID: 35906002 PMCID: PMC9484391 DOI: 10.1136/annrheumdis-2021-222069] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Accepted: 04/08/2022] [Indexed: 11/25/2022]
Abstract
Objectives Patients with lupus nephritis (LN) are in urgent need for early diagnosis and therapeutic interventions targeting aberrant molecular pathways enriched in affected kidneys. Methods We used mRNA-sequencing in effector (spleen) and target (kidneys, brain) tissues from lupus and control mice at sequential time points, and in the blood from 367 individuals (261 systemic lupus erythematosus (SLE) patients and 106 healthy individuals). Comparative cross-tissue and cross-species analyses were performed. The human dataset was split into training and validation sets and machine learning was applied to build LN predictive models. Results In murine SLE, we defined a kidney-specific molecular signature, as well as a molecular signature that underlies transition from preclinical to overt disease and encompasses pathways linked to metabolism, innate immune system and neutrophil degranulation. The murine kidney transcriptome partially mirrors the blood transcriptome of patients with LN with 11 key transcription factors regulating the cross-species active LN molecular signature. Integrated protein-to-protein interaction and drug prediction analyses identified the kinases TRRAP, AKT2, CDK16 and SCYL1 as putative targets of these factors and capable of reversing the LN signature. Using murine kidney-specific genes as disease predictors and machine-learning training of the human RNA-sequencing dataset, we developed and validated a peripheral blood-based algorithm that discriminates LN patients from normal individuals (based on 18 genes) and non-LN SLE patients (based on 20 genes) with excellent sensitivity and specificity (area under the curve range from 0.80 to 0.99). Conclusions Machine-learning analysis of a large whole blood RNA-sequencing dataset of SLE patients using human orthologs of mouse kidney-specific genes can be used for early, non-invasive diagnosis and therapeutic targeting of LN. The kidney-specific gene predictors may facilitate prevention and early intervention trials.
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Affiliation(s)
- Eleni Frangou
- Laboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.,Department of Nephrology, Limassol General Hospital, Limassol, Cyprus
| | - Panagiotis Garantziotis
- Laboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.,Department of Clinical Immunology and Rheumatology, Medical University Hannover, Hannover, Germany
| | - Maria Grigoriou
- Laboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece
| | - Aggelos Banos
- Laboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece
| | - Dionysis Nikolopoulos
- Laboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece
| | - Antigone Pieta
- Laboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece
| | - Stavros A Doumas
- Laboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece
| | - Antonis Fanouriakis
- Laboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece
| | - Aikaterini Hatzioannou
- Laboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece
| | - Theodora Manolakou
- Laboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece
| | - Themis Alissafi
- Laboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece
| | - Panayotis Verginis
- Laboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece
| | - Emmanouil Athanasiadis
- Laboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece
| | - Emmanouil Dermitzakis
- Department of Genetic Medicine and Development and Institute of Genetics and Genomics of Geneva (iG3), University of Geneva Medical School, Geneve, Switzerland
| | - George Bertsias
- Laboratory of Rheumatology, Autoimmunity and Inflammation, University of Crete Medical School, Heraklion, Greece
| | - Anastasia Filia
- Laboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece
| | - Dimitrios T Boumpas
- Laboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece .,4th Department of Medicine, National and Kapodistrian University of Athens Medical School, Athens, Greece.,Medical School, University of Cyprus, Nicosia, Cyprus
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22
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Yang EJ, Park JH, Cho HJ, Hwang JA, Woo SH, Park CH, Kim SY, Park JT, Park SC, Hwang D, Lee YS. Co-inhibition of ATM and ROCK synergistically improves cell proliferation in replicative senescence by activating FOXM1 and E2F1. Commun Biol 2022; 5:702. [PMID: 35835838 PMCID: PMC9283421 DOI: 10.1038/s42003-022-03658-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 06/29/2022] [Indexed: 12/30/2022] Open
Abstract
The multifaceted nature of senescent cell cycle arrest necessitates the targeting of multiple factors arresting or promoting the cell cycle. We report that co-inhibition of ATM and ROCK by KU-60019 and Y-27632, respectively, synergistically increases the proliferation of human diploid fibroblasts undergoing replicative senescence through activation of the transcription factors E2F1 and FOXM1. Time-course transcriptome analysis identified FOXM1 and E2F1 as crucial factors promoting proliferation. Co-inhibition of the kinases ATM and ROCK first promotes the G2/M transition via FOXM1 activation, leading to accumulation of cells undergoing the G1/S transition via E2F1 activation. The combination of both inhibitors increased this effect more significantly than either inhibitor alone, suggesting synergism. Our results demonstrate a FOXM1- and E2F1-mediated molecular pathway enhancing cell cycle progression in cells with proliferative potential under replicative senescence conditions, and treatment with the inhibitors can be tested for senomorphic effect in vivo.
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Affiliation(s)
- Eun Jae Yang
- Department of New Biology, DGIST, Daegu, 42988, Republic of Korea
| | - Ji Hwan Park
- Department of New Biology, DGIST, Daegu, 42988, Republic of Korea
| | - Hyun-Ji Cho
- Department of New Biology, DGIST, Daegu, 42988, Republic of Korea
| | - Jeong-A Hwang
- Department of New Biology, DGIST, Daegu, 42988, Republic of Korea
| | - Seung-Hwa Woo
- Department of New Biology, DGIST, Daegu, 42988, Republic of Korea
| | - Chi Hyun Park
- Department of Computer Science and Engineering, Kangwon National University, Chuncheon, 24341, Republic of Korea
| | - Sung Young Kim
- Department of Biochemistry, Konkuk University School of Medicine, Seoul, 05029, Korea
| | - Joon Tae Park
- Division of Life Sciences, College of Life Sciences and Bioengineering, Incheon National University, Incheon, 22012, Republic of Korea
| | - Sang Chul Park
- Well Aging Research Center, Division of Biotechnology, DGIST, Daegu, 42988, Republic of Korea.
- The Future Life & Society Research Center, Advanced Institute of Aging Science, Chonnam National University, Gwangju, 61469, Republic of Korea.
| | - Daehee Hwang
- Department of Biological Sciences, Seoul National University, Seoul, 08826, Republic of Korea.
| | - Young-Sam Lee
- Department of New Biology, DGIST, Daegu, 42988, Republic of Korea.
- Well Aging Research Center, Division of Biotechnology, DGIST, Daegu, 42988, Republic of Korea.
- New Biology Research Center, DGIST, Daegu, 42988, Republic of Korea.
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23
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Sivadas A, Kok VC, Ng KL. Multi-omics analyses provide novel biological insights to distinguish lobular ductal types of invasive breast cancers. Breast Cancer Res Treat 2022; 193:361-379. [PMID: 35348974 DOI: 10.1007/s10549-022-06567-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Accepted: 03/12/2022] [Indexed: 02/07/2023]
Abstract
BACKGROUND Invasive lobular carcinoma (ILC) treatment is similar to invasive ductal carcinoma (IDC; now invasive carcinoma-no special type, IBC-NST), based on its intrinsic subtype. However, further investigation is required for an integrative understanding of differentially perturbed molecular patterns and pathways in these histotypes. METHODS A dataset of 780 IDC and 201 ILC samples from the TCGA-BRCA project for cross-platform multi-omics was analyzed. We leveraged a consensus approach integrating different bioinformatic algorithms to analyze mutations, CNAs, mRNA, miRNA abundance, methylation, and protein abundance to understand the complex crosstalks that distinguish ILC and IDC samples. A histotype-matched comparison was performed. We performed Cox survival analyses for prognosis based on our identified 53 histotype-specific and four discordant genes. RESULTS Approximately 90% of ILC cases were of the luminal subtype. Somatic mutations in CDH1 were higher in ILC than in IDC (FDR-adjusted p < 0.01). Fifty-three significant oncogenic or tumor-suppressive DEGs were identified in a single histotype. PPAR signaling and lipolysis regulation in adipocytes were significantly enriched in ILC tumors. CDH1 protein had the highest differential abundance (AUC: 0.85). Moreover, BTG2, GSTA2, GPR37L1, and PGBD5 amplification was associated with poorer OS in ILC compared with no alteration. RIMS2, NACA4P, MYC, ZFPM2, and POU5F1B amplification showed a lower overall survival in patients with IDC. miR-195 showed an IDC-specific downregulation, causing overexpression of CCNE1. Integrative multi-omics supervised analysis identified 296 differentially expressed genes that successfully distinguished IDC and ILC histotypes. CONCLUSIONS Our findings identify novel molecular candidates that potentially drive and modify the disease differentially among these histotypes.
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Affiliation(s)
- Ambily Sivadas
- Division of Nutrition, St. John's Research Institute, St. John's National Academy of Health Sciences, Bangalore, India
| | - Victor C Kok
- Division of Medical Oncology, Kuang Tien General Hospital Cancer Center, 117 Shatien Rd Shalu Dist, Taichung, 43303, Taiwan.
- Department of Bioinformatics and Medical Engineering, Asia University Taiwan, Taichung, 40354, Taiwan.
| | - Ka-Lok Ng
- Department of Bioinformatics and Medical Engineering, Asia University Taiwan, Taichung, 40354, Taiwan
- Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan
- Center for Artificial Intelligence and Precision Medicine Research, Asia University, Taichung, 40354, Taiwan
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24
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Kok VC, Wang CCN, Liao SH, Chen DL. Cross-Platform in-silico Analyses Exploring Tumor Immune Microenvironment with Prognostic Value in Triple-Negative Breast Cancer. BREAST CANCER: TARGETS AND THERAPY 2022. [DOI: https://doi.org/10.2147/bctt.s359346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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25
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Toolabi N, Daliri FS, Mokhlesi A, Talkhabi M. Identification of key regulators associated with colon cancer prognosis and pathogenesis. J Cell Commun Signal 2022; 16:115-127. [PMID: 33770351 PMCID: PMC8688655 DOI: 10.1007/s12079-021-00612-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Accepted: 02/25/2021] [Indexed: 12/11/2022] Open
Abstract
Colon cancer (CC) is the fourth deadliest cancer in the world. New insights into prognostication might be helpful to define the optimal adjuvant treatments for patients in routine clinical practice. Here, a microarray dataset with 30 primary tumors and 30 normal samples was analyzed using GEO2R to find differentially expressed genes (DEGs). Then, DAVID, KEGG, ChEA and X2K were used to analyze DEGs-related Gene Ontology, pathways, transcription factors (TFs) and kinases, respectively. Protein-protein interaction (PPI) networks were constructed using the STRING database and Cytoscape. The modules and hub genes of DEGs was determined through MCODE and CytoHubba plugins, and the expression of hub genes was verified using GEPIA. To find microRNAs and metabolites associated with DEGs, miRTarBase and HMDB were used, respectively. It was found that 233 and 373 genes were upregulated and downregulated in CC, respectively. GO analysis showed that the upregulated DEGs were mainly involved in mitotic nuclear division and cell division. Top 10 hub genes were identified, including AURKB, CDK1, DLGAP5, AURKA, CCNB2, CCNB1, BUB1B, CCNA2, KIF20A and BUB1. Whereas, FOMX1, E2F7, E2F1, E2F4 and AR were identified as top 5 TFs in CC. Moreover, CDK1, CDC2, MAPK14, ATM and CK2ALPHA was identified as top 5 kinases in CC. miRNAs analysis showed that Hsa-miR-215-5p hsa-miR-193b-3p, hsa-miR-192-5p and hsa-miR-16-5p could target the largest number of CC genes. Taken together, CC-related genes, especially the hub genes, TFs, and metabolites might be used as novel biomarkers for CC, as well as for diagnosis and guiding therapeutic strategies for CC.
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Affiliation(s)
- Narges Toolabi
- Department of Animal Sciences and Marine Biology, Faculty of Life Sciences and Biotechnology, Shahid Beheshti University, Tehran, Iran
| | - Fattane Sam Daliri
- Department of Animal Sciences and Marine Biology, Faculty of Life Sciences and Biotechnology, Shahid Beheshti University, Tehran, Iran
| | - Amir Mokhlesi
- Department of Animal Sciences and Marine Biology, Faculty of Life Sciences and Biotechnology, Shahid Beheshti University, Tehran, Iran
| | - Mahmood Talkhabi
- Department of Animal Sciences and Marine Biology, Faculty of Life Sciences and Biotechnology, Shahid Beheshti University, Tehran, Iran.
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26
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Kok VC, Wang CCN, Liao SH, Chen DL. Cross-Platform in-silico Analyses Exploring Tumor Immune Microenvironment with Prognostic Value in Triple-Negative Breast Cancer. BREAST CANCER (DOVE MEDICAL PRESS) 2022; 14:85-99. [PMID: 35437353 PMCID: PMC9013259 DOI: 10.2147/bctt.s359346] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Accepted: 04/05/2022] [Indexed: 02/05/2023]
Abstract
INTRODUCTION Only a proportion of triple-negative breast cancer (TNBC) is immunotherapy-responsive. We hypothesized that the tumor microenvironment (TME) influences the outcomes of TNBC and investigated the relevant signaling pathways. MATERIALS AND METHODS Immune score (IS) and stromal score (SS) were calculated using the ESTIMATE and correlated with the overall survival (OS) in TNBC. RNA-seq data from 115 TNBC samples and 112 normal adjacent tissues were retrieved. Validations in the methylation levels in 10 TNBC and five non-TNBC cell lines were obtained. Cox model overall survival (OS) validated the derived transcription factor (TF) genes in cBioPortal breast cancer patients. RESULTS SS-low predicts a higher OS compared with SS-high patients (P = 0.0081 IS-high/SS-low patients had better OS (P = 0.045) than IS-low/SS-high patients. More macrophages were polarized to the M2 state in patients with IS-low/SS-high patients (P < 0.001). Moreover, CIBERSORTx showed more CD8+ cytotoxic T-cells in IS-high/SS-low patients (p = 0.0286) and more resting NK cells in the IS-low/SS-high TME (P = 0.0108). KEGG pathway analysis revealed that overexpressed genes were enriched in the IL-17 and cytokine-cytokine receptor interaction pathways. The lncRNA DRAIC, a tumor suppressor, was consistently deactivated in the 10 TNBC cell lines. On the cBioPortal platform, we validated that 13% of ER-negative, HER2-unamplified BC harbored IL17RA deep deletion and 25% harbored TRAF3IP2 amplification. On cBioPortal datasets, the nine altered TF genes derived from the X2K analysis showed significantly worse relapse-free survival in 2377 patients and OS in 4819 invasive BC patients than in the unaltered cohort. CONCLUSION Of note, the results of this integrated in silico study can only be generalized to approximately 17% of patients with TNBC, in which infiltrating stromal cells and immune cells play a determinant prognostic role.
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Affiliation(s)
- Victor C Kok
- Division of Medical Oncology, Kuang Tien General Hospital Cancer Center, Taichung, 43303, Taiwan
- Department of Bioinformatics and Medical Engineering, Asia University, Taichung, 41354, Taiwan
- Correspondence: Victor C Kok; Charles CN Wang, Email ;
| | - Charles C N Wang
- Department of Bioinformatics and Medical Engineering, Asia University, Taichung, 41354, Taiwan
- Center for Artificial Intelligence and Precision Medicine Research, Asia University, Taichung, 41354, Taiwan
| | - Szu-Han Liao
- Department of Bioinformatics and Medical Engineering, Asia University, Taichung, 41354, Taiwan
| | - De-Lun Chen
- Department of Bioinformatics and Medical Engineering, Asia University, Taichung, 41354, Taiwan
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27
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Gao L, Zhou L, Huang X. Identification of Novel Kinase-Transcription Factor-mRNA-miRNA Regulatory Network in Nasopharyngeal Carcinoma by Bioinformatics Analysis. Int J Gen Med 2021; 14:7453-7469. [PMID: 34744455 PMCID: PMC8566004 DOI: 10.2147/ijgm.s327657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 10/05/2021] [Indexed: 12/24/2022] Open
Abstract
Purpose Nasopharyngeal carcinoma (NPC) is one of the most common malignant tumors of the head and neck. This study aimed to investigate the crucial genes and regulatory networks involved in the carcinogenesis of NPC using a bioinformatics approach. Methods Five mRNA and two miRNA expression datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and miRNAs (DEMs) between NPC and normal samples were analyzed using R software. The WebGestalt tool was used for functional enrichment analysis, and protein-protein interaction (PPI) network analysis of DEGs was performed using STRING database. Transcription factors (TFs) were predicted using TRRUST and Transcriptional Regulatory Element Database (TRED). Kinases were identified using X2Kgui. The miRNAs of DEGs were predicted using miRWalk database. A kinase-TF-mRNA-miRNA integrated network was constructed, and hub nodes were selected. The hub genes were validated using NPC datasets from the GEO and Oncomine databases. Finally, candidate small-molecule agents were predicted using CMap. Results A total of 122 DEGs and 44 DEMs were identified. DEGs were associated with the immune response, leukocyte activation, endoplasmic reticulum stress in GO analysis, and the NF-κB signaling pathway in KEGG analysis. Four significant modules were identified using PPI network analysis. Subsequently, 26 TFs, 73 kinases, and 2499 miRNAs were predicted. The predicted miRNAs were cross-referenced with DEMs, and seven overlapping miRNAs were selected. In the kinase-TF-mRNA-miRNA integrated network, eight genes (PTGS2, FN1, MMP1, PLAU, MMP3, CD19, BMP2, and PIGR) were identified as hub genes. Hub genes were validated with consistent results, indicating the reliability of our findings. Finally, six candidate small-molecule agents (phenoxybenzamine, luteolin, thioguanosine, reserpine, blebbistatin, and camptothecin) were predicted. Conclusion We identified DEGs and an NPC regulatory network involving kinases, TFs, mRNAs, and miRNAs, which might provide promising insight into the pathogenesis, treatment, and prognosis of NPC.
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Affiliation(s)
- Li Gao
- Department of Otolaryngology, Head and Neck Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Lei Zhou
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Zhongshan Hospital Affiliated to Fudan University, Shanghai, People's Republic of China
| | - Xinsheng Huang
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Zhongshan Hospital Affiliated to Fudan University, Shanghai, People's Republic of China
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28
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Biagi CAO, Cury SS, Alves CP, Rabhi N, Silva WA, Farmer SR, Carvalho RF, Batista ML. Multidimensional Single-Nuclei RNA-Seq Reconstruction of Adipose Tissue Reveals Adipocyte Plasticity Underlying Thermogenic Response. Cells 2021; 10:cells10113073. [PMID: 34831295 PMCID: PMC8618495 DOI: 10.3390/cells10113073] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Revised: 10/29/2021] [Accepted: 11/02/2021] [Indexed: 12/13/2022] Open
Abstract
Adipose tissue has been classified based on its morphology and function as white, brown, or beige/brite. It plays an essential role as a regulator of systemic metabolism through paracrine and endocrine signals. Recently, multiple adipocyte subtypes have been revealed using RNA sequencing technology, going beyond simply defined morphology but also by their cellular origin, adaptation to metabolic stress, and plasticity. Here, we performed an in-depth analysis of publicly available single-nuclei RNAseq from adipose tissue and utilized a workflow template to characterize adipocyte plasticity, heterogeneity, and secretome profiles. The reanalyzed dataset led to the identification of different subtypes of adipocytes including three subpopulations of thermogenic adipocytes, and provided a characterization of distinct transcriptional profiles along the adipocyte trajectory under thermogenic challenges. This study provides a useful resource for further investigations regarding mechanisms related to adipocyte plasticity and trans-differentiation.
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Affiliation(s)
- Carlos Alberto Oliveira Biagi
- Department of Genetics, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto 14051-140, Brazil; (C.A.O.B.J.); (W.A.S.J.)
- Center for Cell-Based Therapy (CEPID/FAPESP), National Institute of Science and Technology in Stem Cell and Cell Therapy (INCTC/CNPq), Regional Blood Center of Ribeirão Preto, Ribeirão Preto 14051-140, Brazil
- Institute for Cancer Research, IPEC, Guarapuava 85100-000, Brazil
| | - Sarah Santiloni Cury
- Department of Structural and Functional Biology, Institute of Biosciences, São Paulo State University (UNESP), Botucatu 18618-689, Brazil;
| | - Cleidson Pádua Alves
- Department of Translational Genomics, Medical Faculty, University of Cologne, 50923 Cologne, Germany;
| | - Nabil Rabhi
- Department of Biochemistry, School of Medicine, Boston University, Boston, MA 02215, USA; (N.R.); (S.R.F.)
| | - Wilson Araujo Silva
- Department of Genetics, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto 14051-140, Brazil; (C.A.O.B.J.); (W.A.S.J.)
- Center for Cell-Based Therapy (CEPID/FAPESP), National Institute of Science and Technology in Stem Cell and Cell Therapy (INCTC/CNPq), Regional Blood Center of Ribeirão Preto, Ribeirão Preto 14051-140, Brazil
| | - Stephen R. Farmer
- Department of Biochemistry, School of Medicine, Boston University, Boston, MA 02215, USA; (N.R.); (S.R.F.)
| | - Robson Francisco Carvalho
- Department of Structural and Functional Biology, Institute of Biosciences, São Paulo State University (UNESP), Botucatu 18618-689, Brazil;
- Correspondence: (R.F.C.); (M.L.B.J.)
| | - Miguel Luiz Batista
- Department of Biochemistry, School of Medicine, Boston University, Boston, MA 02215, USA; (N.R.); (S.R.F.)
- Department of Integrated Biotechnology, University of Mogi das Cruzes, São Paulo 08747-000, Brazil
- Correspondence: (R.F.C.); (M.L.B.J.)
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29
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Duan L, Liu D, Chen H, Mintz MA, Chou MY, Kotov DI, Xu Y, An J, Laidlaw BJ, Cyster JG. Follicular dendritic cells restrict interleukin-4 availability in germinal centers and foster memory B cell generation. Immunity 2021; 54:2256-2272.e6. [PMID: 34555336 PMCID: PMC8516727 DOI: 10.1016/j.immuni.2021.08.028] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2020] [Revised: 06/02/2021] [Accepted: 08/27/2021] [Indexed: 11/24/2022]
Abstract
B cells within germinal centers (GCs) enter cycles of antibody affinity maturation or exit the GC as memory cells or plasma cells. Here, we examined the contribution of interleukin (IL)-4 on B cell fate decisions in the GC. Single-cell RNA-sequencing identified a subset of light zone GC B cells expressing high IL-4 receptor-a (IL4Ra) and CD23 and lacking a Myc-associated signature. These cells could differentiate into pre-memory cells. B cell-specific deletion of IL4Ra or STAT6 favored the pre-memory cell trajectory, and provision of exogenous IL-4 in a wild-type context reduced pre-memory cell frequencies. IL-4 acted during antigen-specific interactions but also influenced bystander cells. Deletion of IL4Ra from follicular dendritic cells (FDCs) increased the availability of IL-4 in the GC, impaired the selection of affinity-matured B cells, and reduced memory cell generation. We propose that GC FDCs establish a niche that limits bystander IL-4 activity, focusing IL-4 action on B cells undergoing selection and enhancing memory cell differentiation.
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Affiliation(s)
- Lihui Duan
- Department of Microbiology and Immunology and Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Dan Liu
- Department of Microbiology and Immunology and Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Hsin Chen
- Department of Microbiology and Immunology and Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Michelle A Mintz
- Department of Microbiology and Immunology and Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Marissa Y Chou
- Department of Microbiology and Immunology and Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Dmitri I Kotov
- Division of Immunology and Pathogenesis, Department of Molecular and Cell Biology, and Howard Hughes Medical Institute, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Ying Xu
- Department of Microbiology and Immunology and Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Jinping An
- Department of Microbiology and Immunology and Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Brian J Laidlaw
- Department of Microbiology and Immunology and Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Jason G Cyster
- Department of Microbiology and Immunology and Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA 94143, USA.
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Tumor Necrosis Factor-Alpha Exacerbates Viral Entry in SARS-CoV2-Infected iPSC-Derived Cardiomyocytes. Int J Mol Sci 2021; 22:ijms22189869. [PMID: 34576032 PMCID: PMC8470197 DOI: 10.3390/ijms22189869] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 08/28/2021] [Accepted: 09/07/2021] [Indexed: 12/27/2022] Open
Abstract
The coronavirus disease 2019 (COVID-19) pandemic with high infectivity and mortality has caused severe social and economic impacts worldwide. Growing reports of COVID-19 patients with multi-organ damage indicated that severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) may also disturb the cardiovascular system. Herein, we used human induced pluripotent stem cell (iPSC)-derived cardiomyocytes (iCMs) as the in vitro platform to examine the consequence of SARS-CoV2 infection on iCMs. Differentiated iCMs expressed the primary SARS-CoV2 receptor angiotensin-converting enzyme-II (ACE2) and the transmembrane protease serine type 2 (TMPRSS2) receptor suggesting the susceptibility of iCMs to SARS-CoV2. Following the infection of iCMs with SARS-CoV2, the viral nucleocapsid (N) protein was detected in the host cells, demonstrating the successful infection. Bioinformatics analysis revealed that the SARS-CoV2 infection upregulates several inflammation-related genes, including the proinflammatory cytokine tumor necrosis factor-α (TNF-α). The pretreatment of iCMs with TNF-α for 24 h, significantly increased the expression of ACE2 and TMPRSS2, SASR-CoV2 entry receptors. The TNF-α pretreatment enhanced the entry of GFP-expressing SARS-CoV2 pseudovirus into iCMs, and the neutralization of TNF-α ameliorated the TNF-α-enhanced viral entry. Collectively, SARS-CoV2 elevated TNF-α expression, which in turn enhanced the SARS-CoV2 viral entry. Our findings suggest that, TNF-α may participate in the cytokine storm and aggravate the myocardial damage in COVID-19 patients.
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Jales Neto LH, Hounkpe BW, Fernandes GH, Takayama L, Caparbo VF, Lopes NH, Pereira AC, Pereira RM. Transcriptomic analysis of elderly women with low muscle mass: association with immune system pathway. Aging (Albany NY) 2021; 13:20992-21008. [PMID: 34493690 PMCID: PMC8457609 DOI: 10.18632/aging.203505] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Accepted: 08/24/2021] [Indexed: 06/13/2023]
Abstract
Despite the well-established association of gene expression deregulation with low muscle mass (LMM), the associated biological mechanisms remain unclear. Transcriptomic studies are capable to identify key mediators in complex diseases. We aimed to identify relevant mediators and biological mechanisms associated with age-related LMM. LMM-associated genes were detected by logistic regression using microarray data of 20 elderly women with LMM and 20 age and race-matched controls extracted from our SPAH Study (GSE152073). We performed weighted gene co-expression analysis (WGCNA) that correlated the identified gene modules with laboratorial characteristics. Gene enrichment analysis was performed and an LMM predictive model was constructed using Support Vector Machine (SVM). Overall, 821 discriminating transcripts clusters were identified (|beta coefficient| >1; p-value <0.01). From this list, 45 predictors of LMM were detected by SVM and validated with 0.7 of accuracy. Our results revealed that the well-described association of inflammation, immunity and metabolic alterations is also relevant at transcriptomic level. WGCNA highlighted a correlation of genes modules involved in immunity pathways with vitamin D level (R = 0.63, p = 0.004) and the Agatston score (R = 0.51, p = 0.02). Our study generated a predicted regulatory network and revealed significant metabolic pathways related to aging processes, showing key mediators that warrant further investigation.
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Affiliation(s)
- Levi H. Jales Neto
- Bone Metabolism Laboratory, Rheumatology Division Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Bidossessi W. Hounkpe
- Bone Metabolism Laboratory, Rheumatology Division Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Georgea H. Fernandes
- Bone Metabolism Laboratory, Rheumatology Division Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Liliam Takayama
- Bone Metabolism Laboratory, Rheumatology Division Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Valéria F. Caparbo
- Bone Metabolism Laboratory, Rheumatology Division Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Neuza H.M. Lopes
- Instituto do Coracao (InCor), Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Alexandre C. Pereira
- Laboratory of Genetics and Molecular Cardiology, Instituto do Coração (InCor), Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Rosa M.R. Pereira
- Bone Metabolism Laboratory, Rheumatology Division Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
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Caescu CI, Hansen J, Crockett B, Xiao W, Arnaud P, Spronck B, Weinberg A, Hashimoto T, Murtada SI, Borkar R, Gallo JM, Jondeau G, Boileau C, Humphrey JD, He JC, Iyengar R, Ramirez F. Inhibition of HIPK2 Alleviates Thoracic Aortic Disease in Mice With Progressively Severe Marfan Syndrome. Arterioscler Thromb Vasc Biol 2021; 41:2483-2493. [PMID: 34320838 PMCID: PMC8530207 DOI: 10.1161/atvbaha.121.316464] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Objective Despite considerable research, the goal of finding nonsurgical remedies against thoracic aortic aneurysm and acute aortic dissection remains elusive. We sought to identify a novel aortic PK (protein kinase) that can be pharmacologically targeted to mitigate aneurysmal disease in a well-established mouse model of early-onset progressively severe Marfan syndrome (MFS). Approach and Results Computational analyses of transcriptomic data derived from the ascending aorta of MFS mice predicted a probable association between thoracic aortic aneurysm and acute aortic dissection development and the multifunctional, stress-activated HIPK2 (homeodomain-interacting protein kinase 2). Consistent with this prediction, Hipk2 gene inactivation significantly extended the survival of MFS mice by slowing aneurysm growth and delaying transmural rupture. HIPK2 also ranked among the top predicted PKs in computational analyses of DEGs (differentially expressed genes) in the dilated aorta of 3 MFS patients, which strengthened the clinical relevance of the experimental finding. Additional in silico analyses of the human and mouse data sets identified the TGF (transforming growth factor)-β/Smad3 signaling pathway as a potential target of HIPK2 in the MFS aorta. Chronic treatment of MFS mice with an allosteric inhibitor of HIPK2-mediated stimulation of Smad3 signaling validated this prediction by mitigating thoracic aortic aneurysm and acute aortic dissection pathology and partially improving aortic material stiffness. Conclusions HIPK2 is a previously unrecognized determinant of aneurysmal disease and an attractive new target for antithoracic aortic aneurysm and acute aortic dissection multidrug therapy.
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MESH Headings
- Adult
- Aortic Dissection/enzymology
- Aortic Dissection/genetics
- Aortic Dissection/pathology
- Aortic Dissection/prevention & control
- Animals
- Aorta, Thoracic/drug effects
- Aorta, Thoracic/enzymology
- Aorta, Thoracic/pathology
- Aortic Aneurysm, Thoracic/enzymology
- Aortic Aneurysm, Thoracic/genetics
- Aortic Aneurysm, Thoracic/pathology
- Aortic Aneurysm, Thoracic/prevention & control
- Carrier Proteins/genetics
- Carrier Proteins/metabolism
- Dilatation, Pathologic
- Disease Models, Animal
- Disease Progression
- Fibrillin-1/genetics
- Humans
- Male
- Marfan Syndrome/complications
- Marfan Syndrome/genetics
- Mice, 129 Strain
- Mice, Inbred C57BL
- Mice, Knockout
- Protein Kinase Inhibitors/pharmacology
- Protein Serine-Threonine Kinases/antagonists & inhibitors
- Protein Serine-Threonine Kinases/genetics
- Protein Serine-Threonine Kinases/metabolism
- Severity of Illness Index
- Signal Transduction
- Smad3 Protein/metabolism
- Vascular Remodeling/drug effects
- Mice
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Affiliation(s)
- Cristina I Caescu
- Department of Pharmacological Sciences, Institute for Systems Biomedicine (C.I.C., J.H., B.C., T.H., R.I., F.R.), Icahn School of Medicine at Mount Sinai, New York
| | - Jens Hansen
- Department of Pharmacological Sciences, Institute for Systems Biomedicine (C.I.C., J.H., B.C., T.H., R.I., F.R.), Icahn School of Medicine at Mount Sinai, New York
| | - Brittany Crockett
- Department of Pharmacological Sciences, Institute for Systems Biomedicine (C.I.C., J.H., B.C., T.H., R.I., F.R.), Icahn School of Medicine at Mount Sinai, New York
| | - Wenzhen Xiao
- Division of Nephrology, Department of Medicine (W.X., J.C.H.), Icahn School of Medicine at Mount Sinai, New York
| | - Pauline Arnaud
- Département de Génétique et Centre de Référence Maladies Rares Syndrome de Marfan et Pathologies Apparentées, Assistance Publique-Hôpitaux de Paris, Hôpital Bichat, France (P.A., G.J., C.B.)
- LVTS, INSERM U1148, Université de Paris, Hôpital Bichat, France (P.A., G.J., C.B.)
| | - Bart Spronck
- Department of Biomedical Engineering, Yale University, New Haven, CT (B.S., S.-I.M., J.D.H.)
| | - Alan Weinberg
- Department of Population Health Science and Policy (A.W.), Icahn School of Medicine at Mount Sinai, New York
| | - Takeshi Hashimoto
- Department of Pharmacological Sciences, Institute for Systems Biomedicine (C.I.C., J.H., B.C., T.H., R.I., F.R.), Icahn School of Medicine at Mount Sinai, New York
| | - Sae-Il Murtada
- Department of Biomedical Engineering, Yale University, New Haven, CT (B.S., S.-I.M., J.D.H.)
| | - Roshan Borkar
- Department of Pharmaceutical Sciences, State University of New York, Buffalo (R.B., J.M.G.)
| | - James M Gallo
- Department of Pharmaceutical Sciences, State University of New York, Buffalo (R.B., J.M.G.)
| | - Guillaume Jondeau
- Département de Génétique et Centre de Référence Maladies Rares Syndrome de Marfan et Pathologies Apparentées, Assistance Publique-Hôpitaux de Paris, Hôpital Bichat, France (P.A., G.J., C.B.)
- LVTS, INSERM U1148, Université de Paris, Hôpital Bichat, France (P.A., G.J., C.B.)
| | - Catherine Boileau
- Département de Génétique et Centre de Référence Maladies Rares Syndrome de Marfan et Pathologies Apparentées, Assistance Publique-Hôpitaux de Paris, Hôpital Bichat, France (P.A., G.J., C.B.)
- LVTS, INSERM U1148, Université de Paris, Hôpital Bichat, France (P.A., G.J., C.B.)
| | - Jay D Humphrey
- Department of Biomedical Engineering, Yale University, New Haven, CT (B.S., S.-I.M., J.D.H.)
| | - John Cijiang He
- Division of Nephrology, Department of Medicine (W.X., J.C.H.), Icahn School of Medicine at Mount Sinai, New York
| | - Ravi Iyengar
- Department of Pharmacological Sciences, Institute for Systems Biomedicine (C.I.C., J.H., B.C., T.H., R.I., F.R.), Icahn School of Medicine at Mount Sinai, New York
| | - Francesco Ramirez
- Department of Pharmacological Sciences, Institute for Systems Biomedicine (C.I.C., J.H., B.C., T.H., R.I., F.R.), Icahn School of Medicine at Mount Sinai, New York
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33
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Wiedenmann S, Breunig M, Merkle J, von Toerne C, Georgiev T, Moussus M, Schulte L, Seufferlein T, Sterr M, Lickert H, Weissinger SE, Möller P, Hauck SM, Hohwieler M, Kleger A, Meier M. Single-cell-resolved differentiation of human induced pluripotent stem cells into pancreatic duct-like organoids on a microwell chip. Nat Biomed Eng 2021; 5:897-913. [PMID: 34239116 PMCID: PMC7611572 DOI: 10.1038/s41551-021-00757-2] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Accepted: 06/01/2021] [Indexed: 02/06/2023]
Abstract
Creating in vitro models of diseases of the pancreatic ductal compartment requires a comprehensive understanding of the developmental trajectories of pancreas-specific cell types. Here we report the single-cell characterization of the differentiation of pancreatic duct-like organoids (PDLOs) from human induced pluripotent stem cells (hiPSCs) on a microwell chip that facilitates the uniform aggregation and chemical induction of hiPSC-derived pancreatic progenitors. Using time-resolved single-cell transcriptional profiling and immunofluorescence imaging of the forming PDLOs, we identified differentiation routes from pancreatic progenitors through ductal intermediates to two types of mature duct-like cells and a few non-ductal cell types. PDLO subpopulations expressed either mucins or the cystic fibrosis transmembrane conductance regulator, and resembled human adult duct cells. We also used the chip to uncover ductal markers relevant to pancreatic carcinogenesis, and to establish PDLO co-cultures with stellate cells, which allowed for the study of epithelial-mesenchymal signalling. The PDLO microsystem could be used to establish patient-specific pancreatic duct models.
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Affiliation(s)
- Sandra Wiedenmann
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, Ingolstaedter Landstraße 1, 85764 Neuherberg, Germany
| | - Markus Breunig
- Department of Internal Medicine I, Ulm University Hospital, Albert-Einstein-Allee 23, 89081 Ulm, Germany
| | - Jessica Merkle
- Department of Internal Medicine I, Ulm University Hospital, Albert-Einstein-Allee 23, 89081 Ulm, Germany
| | - Christine von Toerne
- Research Unit Protein Science, Helmholtz Zentrum München, Heidemannstraße 1, 80939 Müunich, Germany
| | - Tihomir Georgiev
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, Ingolstaedter Landstraße 1, 85764 Neuherberg, Germany
| | - Michel Moussus
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, Ingolstaedter Landstraße 1, 85764 Neuherberg, Germany
| | - Lucas Schulte
- Department of Internal Medicine I, Ulm University Hospital, Albert-Einstein-Allee 23, 89081 Ulm, Germany
| | - Thomas Seufferlein
- Department of Internal Medicine I, Ulm University Hospital, Albert-Einstein-Allee 23, 89081 Ulm, Germany
| | - Michael Sterr
- Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, Ingolstaedter Landstraße 1, 85764 Neuherberg, Germany,German Center for Diabetes Research (DZD), Ingolstaedter Landstraße 1, 85764 Neuherberg, Germany
| | - Heiko Lickert
- Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, Ingolstaedter Landstraße 1, 85764 Neuherberg, Germany,German Center for Diabetes Research (DZD), Ingolstaedter Landstraße 1, 85764 Neuherberg, Germany,Institute of Stem Cell Research, Helmholtz Zentrum München, Ingolstaedter Landstraße 1, 85764 Neuherberg, Germany,Technical University of Munich, School of Medicine, Ismaninger Straße 22, 81675 Munich, Germany
| | | | - Peter Möller
- Institute for Pathology, Ulm University Hospital, Albert-Einstein-Allee 23, 89081 Ulm, Germany
| | - Stefanie M. Hauck
- Research Unit Protein Science, Helmholtz Zentrum München, Heidemannstraße 1, 80939 Müunich, Germany
| | - Meike Hohwieler
- Department of Internal Medicine I, Ulm University Hospital, Albert-Einstein-Allee 23, 89081 Ulm, Germany,Corresponding authors: ; ;
| | - Alexander Kleger
- Department of Internal Medicine I, Ulm University Hospital, Albert-Einstein-Allee 23, 89081 Ulm, Germany,Corresponding authors: ; ;
| | - Matthias Meier
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, Ingolstaedter Landstraße 1, 85764 Neuherberg, Germany,Technical University of Munich, School of Medicine, Ismaninger Straße 22, 81675 Munich, Germany,Corresponding authors: ; ;
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34
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Bonilla DA, Moreno Y, Rawson ES, Forero DA, Stout JR, Kerksick CM, Roberts MD, Kreider RB. A Convergent Functional Genomics Analysis to Identify Biological Regulators Mediating Effects of Creatine Supplementation. Nutrients 2021; 13:2521. [PMID: 34444681 PMCID: PMC8397972 DOI: 10.3390/nu13082521] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Accepted: 07/21/2021] [Indexed: 12/12/2022] Open
Abstract
Creatine (Cr) and phosphocreatine (PCr) are physiologically essential molecules for life, given they serve as rapid and localized support of energy- and mechanical-dependent processes. This evolutionary advantage is based on the action of creatine kinase (CK) isozymes that connect places of ATP synthesis with sites of ATP consumption (the CK/PCr system). Supplementation with creatine monohydrate (CrM) can enhance this system, resulting in well-known ergogenic effects and potential health or therapeutic benefits. In spite of our vast knowledge about these molecules, no integrative analysis of molecular mechanisms under a systems biology approach has been performed to date; thus, we aimed to perform for the first time a convergent functional genomics analysis to identify biological regulators mediating the effects of Cr supplementation in health and disease. A total of 35 differentially expressed genes were analyzed. We identified top-ranked pathways and biological processes mediating the effects of Cr supplementation. The impact of CrM on miRNAs merits more research. We also cautiously suggest two dose-response functional pathways (kinase- and ubiquitin-driven) for the regulation of the Cr uptake. Our functional enrichment analysis, the knowledge-based pathway reconstruction, and the identification of hub nodes provide meaningful information for future studies. This work contributes to a better understanding of the well-reported benefits of Cr in sports and its potential in health and disease conditions, although further clinical research is needed to validate the proposed mechanisms.
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Affiliation(s)
- Diego A. Bonilla
- Research Division, Dynamical Business & Science Society—DBSS International SAS, Bogotá 110861, Colombia;
- Research Group in Biochemistry and Molecular Biology, Universidad Distrital Francisco José de Caldas, Bogotá 110311, Colombia
- Research Group in Physical Activity, Sports and Health Sciences (GICAFS), Universidad de Córdoba, Montería 230002, Colombia
- kDNA Genomics, Joxe Mari Korta Research Center, University of the Basque Country UPV/EHU, 20018 Donostia-San Sebastián, Spain
| | - Yurany Moreno
- Research Division, Dynamical Business & Science Society—DBSS International SAS, Bogotá 110861, Colombia;
- Research Group in Biochemistry and Molecular Biology, Universidad Distrital Francisco José de Caldas, Bogotá 110311, Colombia
| | - Eric S. Rawson
- Department of Health, Nutrition and Exercise Science, Messiah University, Mechanicsburg, PA 17055, USA;
| | - Diego A. Forero
- Professional Program in Sport Training, School of Health and Sport Sciences, Fundación Universitaria del Área Andina, Bogotá 111221, Colombia;
| | - Jeffrey R. Stout
- Physiology of Work and Exercise Response (POWER) Laboratory, Institute of Exercise Physiology and Rehabilitation Science, University of Central Florida, Orlando, FL 32816, USA;
| | - Chad M. Kerksick
- Exercise and Performance Nutrition Laboratory, School of Health Sciences, Lindenwood University, Saint Charles, MO 63301, USA;
| | - Michael D. Roberts
- School of Kinesiology, Auburn University, Auburn, AL 36849, USA;
- Edward via College of Osteopathic Medicine, Auburn, AL 36849, USA
| | - Richard B. Kreider
- Exercise & Sport Nutrition Laboratory, Human Clinical Research Facility, Texas A&M University, College Station, TX 77843, USA;
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Kuleshov MV, Xie Z, London ABK, Yang J, Evangelista J, Lachmann A, Shu I, Torre D, Ma’ayan A. KEA3: improved kinase enrichment analysis via data integration. Nucleic Acids Res 2021; 49:W304-W316. [PMID: 34019655 PMCID: PMC8265130 DOI: 10.1093/nar/gkab359] [Citation(s) in RCA: 58] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Revised: 04/06/2021] [Accepted: 04/22/2021] [Indexed: 12/27/2022] Open
Abstract
Phosphoproteomics and proteomics experiments capture a global snapshot of the cellular signaling network, but these methods do not directly measure kinase state. Kinase Enrichment Analysis 3 (KEA3) is a webserver application that infers overrepresentation of upstream kinases whose putative substrates are in a user-inputted list of proteins. KEA3 can be applied to analyze data from phosphoproteomics and proteomics studies to predict the upstream kinases responsible for observed differential phosphorylations. The KEA3 background database contains measured and predicted kinase-substrate interactions (KSI), kinase-protein interactions (KPI), and interactions supported by co-expression and co-occurrence data. To benchmark the performance of KEA3, we examined whether KEA3 can predict the perturbed kinase from single-kinase perturbation followed by gene expression experiments, and phosphoproteomics data collected from kinase-targeting small molecules. We show that integrating KSIs and KPIs across data sources to produce a composite ranking improves the recovery of the expected kinase. The KEA3 webserver is available at https://maayanlab.cloud/kea3.
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Affiliation(s)
- Maxim V Kuleshov
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY 10029, USA
| | - Zhuorui Xie
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY 10029, USA
| | - Alexandra B K London
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY 10029, USA
| | - Janice Yang
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY 10029, USA
| | - John Erol Evangelista
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY 10029, USA
| | - Alexander Lachmann
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY 10029, USA
| | - Ingrid Shu
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY 10029, USA
| | - Denis Torre
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY 10029, USA
| | - Avi Ma’ayan
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY 10029, USA
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36
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Ergul M, Aktan F, Yildiz MT, Tutar Y. Perturbation of HSP Network in MCF-7 Breast Cancer Cell Line Triggers Inducible HSP70 Expression and Leads to Tumor Suppression. Anticancer Agents Med Chem 2021; 20:1051-1060. [PMID: 32053081 DOI: 10.2174/1871520620666200213102210] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Revised: 10/09/2019] [Accepted: 12/28/2019] [Indexed: 11/22/2022]
Abstract
BACKGROUND Heat shock protein 70 (HSP70) is constitutively expressed in normal cells but aberrantly expressed in several types of tumor cells, helping their survival in extreme conditions. Thus, specific inhibition of HSP70 in tumor cells is a promising strategy in the treatment of cancer. HSP70 has a variety of isoforms in the cellular organelles and form different functions by coordinating and cooperating with cochaperones. Cancer cells overexpress HSPs during cell growth and proliferation and HSP network provides resistance against apoptosis. The present study aimed to evaluate quantitative changes in HSPs- and cancerassociated gene expressions and their interactions in the presence of 2-phenylethyenesulfonamide (PES) in MCF-7 cells. METHODS Antiproliferative activity of PES was evaluated using the XTT assay. Inducible HSP70 (HSP70i) levels in the PES-treated cells were determined using the ELISA kit. PCR Array was performed to assess the HSPs- and cancer-pathway focused gene expression profiling. Gene network analysis was performed using the X2K, yEd (V.3.18.1) programs, and web-based gene list enrichment analysis tool Enrichr. RESULTS The results demonstrated that PES exposure increased the amount of both HSP70i gene and protein expression surprisingly. However, the expression of HSP70 isoforms as well as other co-chaperones, and 17 cancer-associated genes decreased remarkably as expected. Additionally, interaction network analysis revealed a different mechanism; PES induction of HSP70i employs a cell cycle negative regulator, RB1, which is a tumor suppressor gene. CONCLUSION PES treatment inhibited MCF-7 cell proliferation and changed several HSPs- and cancer-related gene expressions along with their interactions through a unique mechanism although it causes an interesting increase at HSP70i gene and protein expressions. RB1 gene expression may play an important role in this effect as revealed by the interaction network analysis.
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Affiliation(s)
- Mustafa Ergul
- Department of Biochemistry, Faculty of Pharmacy, Sivas Cumhuriyet University, Sivas, Turkey
| | - Fugen Aktan
- Department of Biochemistry, Faculty of Pharmacy, Ankara University, Ankara, Turkey
| | - Mehmet T Yildiz
- Division of Molecular Medicine, Hamidiye Institute of Health Sciences, University of Health Sciences, Istanbul, Turkey
| | - Yusuf Tutar
- Division of Molecular Medicine, Hamidiye Institute of Health Sciences, University of Health Sciences, Istanbul, Turkey
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37
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Blache U, Wunderli SL, Hussien AA, Stauber T, Flückiger G, Bollhalder M, Niederöst B, Fucentese SF, Snedeker JG. Inhibition of ERK 1/2 kinases prevents tendon matrix breakdown. Sci Rep 2021; 11:6838. [PMID: 33767224 PMCID: PMC7994809 DOI: 10.1038/s41598-021-85331-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Accepted: 02/26/2021] [Indexed: 12/14/2022] Open
Abstract
Tendon extracellular matrix (ECM) mechanical unloading results in tissue degradation and breakdown, with niche-dependent cellular stress directing proteolytic degradation of tendon. Here, we show that the extracellular-signal regulated kinase (ERK) pathway is central in tendon degradation of load-deprived tissue explants. We show that ERK 1/2 are highly phosphorylated in mechanically unloaded tendon fascicles in a vascular niche-dependent manner. Pharmacological inhibition of ERK 1/2 abolishes the induction of ECM catabolic gene expression (MMPs) and fully prevents loss of mechanical properties. Moreover, ERK 1/2 inhibition in unloaded tendon fascicles suppresses features of pathological tissue remodeling such as collagen type 3 matrix switch and the induction of the pro-fibrotic cytokine interleukin 11. This work demonstrates ERK signaling as a central checkpoint to trigger tendon matrix degradation and remodeling using load-deprived tissue explants.
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Affiliation(s)
- Ulrich Blache
- Department of Orthopedics, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
- Institute for Biomechanics, ETH Zurich, Zurich, Switzerland
| | - Stefania L Wunderli
- Department of Orthopedics, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
- Institute for Biomechanics, ETH Zurich, Zurich, Switzerland
| | - Amro A Hussien
- Department of Orthopedics, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
- Institute for Biomechanics, ETH Zurich, Zurich, Switzerland
| | - Tino Stauber
- Department of Orthopedics, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
- Institute for Biomechanics, ETH Zurich, Zurich, Switzerland
| | - Gabriel Flückiger
- Department of Orthopedics, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
- Institute for Biomechanics, ETH Zurich, Zurich, Switzerland
| | - Maja Bollhalder
- Department of Orthopedics, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
- Institute for Biomechanics, ETH Zurich, Zurich, Switzerland
| | - Barbara Niederöst
- Department of Orthopedics, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
- Institute for Biomechanics, ETH Zurich, Zurich, Switzerland
| | - Sandro F Fucentese
- Department of Orthopedics, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Jess G Snedeker
- Department of Orthopedics, Balgrist University Hospital, University of Zurich, Zurich, Switzerland.
- Institute for Biomechanics, ETH Zurich, Zurich, Switzerland.
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38
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Jha PK, Vijay A, Halu A, Uchida S, Aikawa M. Gene Expression Profiling Reveals the Shared and Distinct Transcriptional Signatures in Human Lung Epithelial Cells Infected With SARS-CoV-2, MERS-CoV, or SARS-CoV: Potential Implications in Cardiovascular Complications of COVID-19. Front Cardiovasc Med 2021; 7:623012. [PMID: 33521069 PMCID: PMC7844200 DOI: 10.3389/fcvm.2020.623012] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Accepted: 11/26/2020] [Indexed: 01/14/2023] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative virus for the current global pandemic known as coronavirus disease 2019 (COVID-19). SARS-CoV-2 belongs to the family of single-stranded RNA viruses known as coronaviruses, including the MERS-CoV and SARS-CoV that cause Middle East respiratory syndrome (MERS) and severe acute respiratory syndrome (SARS), respectively. These coronaviruses are associated in the way that they cause mild to severe upper respiratory tract illness. This study has used an unbiased analysis of publicly available gene expression datasets from Gene Expression Omnibus to understand the shared and unique transcriptional signatures of human lung epithelial cells infected with SARS-CoV-2 relative to MERS-CoV or SARS-CoV. A major goal was to discover unique cellular responses to SARS-CoV-2 among these three coronaviruses. Analyzing differentially expressed genes (DEGs) shared by the three datasets led to a set of 17 genes, suggesting the lower expression of genes related to acute inflammatory response (TNF, IL32, IL1A, CXCL1, and CXCL3) in SARS-CoV-2. This subdued transcriptional response to SARS-CoV-2 may cause prolonged viral replication, leading to severe lung damage. Downstream analysis of unique DEGs of SARS-CoV-2 infection revealed changes in genes related to apoptosis (NRP1, FOXO1, TP53INP1, CSF2, and NLRP1), coagulation (F3, PROS1, ITGB3, and TFPI2), and vascular function (VAV3, TYMP, TCF4, and NR2F2), which may contribute to more systemic cardiovascular complications of COVID-19 than MERS and SARS. The study has uncovered a novel set of transcriptomic signatures unique to SARS-CoV-2 infection and shared by three coronaviruses, which may guide the initial efforts in the development of prognostic or therapeutic tools for COVID-19.
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Affiliation(s)
- Prabhash Kumar Jha
- Center for Excellence in Vascular Biology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
| | - Aatira Vijay
- Department of Cardiovascular and Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States
| | - Arda Halu
- Center for Interdisciplinary Cardiovascular Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States.,Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
| | - Shizuka Uchida
- Department of Clinical Medicine, Center for RNA Medicine, Aalborg University, Copenhagen, Denmark
| | - Masanori Aikawa
- Center for Excellence in Vascular Biology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States.,Center for Interdisciplinary Cardiovascular Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States.,Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
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39
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Patrick MT, Stuart PE, Zhang H, Zhao Q, Yin X, He K, Zhou XJ, Mehta NN, Voorhees JJ, Boehnke M, Gudjonsson JE, Nair RP, Handelman SK, Elder JT, Liu DJ, Tsoi LC. Causal Relationship and Shared Genetic Loci between Psoriasis and Type 2 Diabetes through Trans-Disease Meta-Analysis. J Invest Dermatol 2020; 141:1493-1502. [PMID: 33385400 DOI: 10.1016/j.jid.2020.11.025] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 11/09/2020] [Accepted: 11/23/2020] [Indexed: 01/04/2023]
Abstract
Psoriasis and type 2 diabetes (T2D) are complex conditions with significant impacts on health. Patients with psoriasis have a higher risk of T2D (∼1.5 OR) and vice versa, controlling for body mass index; yet, there has been a limited study comparing their genetic architecture. We hypothesized that there are shared genetic components between psoriasis and T2D. Trans-disease meta-analysis was applied to 8,016,731 well-imputed genetic markers from large-scale meta-analyses of psoriasis (11,024 cases and 16,336 controls) and T2D (74,124 cases and 824,006 controls), adjusted for body mass index. We confirmed our findings in a hospital-based study (42,112 patients) and tested for causal relationships with multivariable Mendelian randomization. Mendelian randomization identified a causal relationship between psoriasis and T2D (P = 1.6 × 10‒4, OR = 1.01) and highlighted the impact of body mass index. Trans-disease meta-analysis further revealed four genome-wide significant loci (P < 5 × 10‒8) with evidence of colocalization and shared directions of effect between psoriasis and T2D not present in body mass index. The proteins coded by genes in these loci (ACTR2, ERLIN1, TRMT112, and BECN1) are connected through NF-κB signaling. Our results provide insight into the immunological components that connect immune-mediated skin conditions and metabolic diseases, independent of confounding factors.
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Affiliation(s)
- Matthew T Patrick
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Philip E Stuart
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Haihan Zhang
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, USA; Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Qingyuan Zhao
- Statistical Laboratory, Centre for Mathematical Sciences, University of Cambridge, Cambridge, United Kingdom
| | - Xianyong Yin
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Kevin He
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Xu-Jie Zhou
- Renal Division, Peking University First Hospital, Beijing, China
| | - Nehal N Mehta
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - John J Voorhees
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Michael Boehnke
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Johann E Gudjonsson
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Rajan P Nair
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Samuel K Handelman
- Division of Gastroenterology, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - James T Elder
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, USA; Ann Arbor Veterans Affairs Hospital, Ann Arbor, Michigan, USA
| | - Dajiang J Liu
- Department of Public Health Sciences, Pennsylvania State University College of Medicine, Pennsylvania, USA
| | - Lam C Tsoi
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, USA; Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor Michigan, USA.
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40
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Wang M, Luciani LL, Noh H, Mochan E, Shoemaker JE. TREAP: A New Topological Approach to Drug Target Inference. Biophys J 2020; 119:2290-2298. [PMID: 33129831 DOI: 10.1016/j.bpj.2020.10.021] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Revised: 09/08/2020] [Accepted: 10/07/2020] [Indexed: 10/23/2022] Open
Abstract
Over 50% of drugs fail in stage 3 clinical trials, many because of a poor understanding of the drug's mechanisms of action (MoA). A better comprehension of drug MoA will significantly improve research and development (R&D). Current proposed algorithms, such as ProTINA and DeMAND, can be overly complex. Additionally, they are unable to predict whether the drug-induced gene expression or the topology of the networks used to model gene regulation primarily impacts accurate drug target inference. In this work, we evaluate how network and gene expression data affect ProTINA's accuracy. We find that network topology predominantly determines the accuracy of ProTINA's predictions. We further show that the size of an interaction network and/or selecting cell-specific networks has a limited effect on accuracy. We then demonstrate that a specific network topology measure, betweenness, can be used to improve drug target prediction. Based on these results, we create a new algorithm, TREAP, that combines betweenness values and adjusted p-values for target inference. TREAP offers an alternative approach to drug target inference and is advantageous because it is not computationally demanding, provides easy-to-interpret results, and is often more accurate at predicting drug targets than current state-of-the-art approaches.
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Affiliation(s)
- Muying Wang
- Department of Chemical and Petroleum Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Lauren L Luciani
- Department of Chemical and Petroleum Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Heeju Noh
- Department of Systems Biology, Columbia University, New York, New York; Institute for Chemical and Bioengineering, ETH Zurich, Zurich, Switzerland
| | - Ericka Mochan
- Department of Chemical and Petroleum Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania; Department of Mathematics and Data Analytics, Carlow University, Pittsburgh, Pennsylvania
| | - Jason E Shoemaker
- Department of Chemical and Petroleum Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania; Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania; The McGowan Institute for Regenerative Medicine, Pittsburgh, Pennsylvania.
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Guscetti F, Nassiri S, Beebe E, Rito Brandao I, Graf R, Markkanen E. Molecular homology between canine spontaneous oral squamous cell carcinomas and human head-and-neck squamous cell carcinomas reveals disease drivers and therapeutic vulnerabilities. Neoplasia 2020; 22:778-788. [PMID: 33142242 PMCID: PMC7642746 DOI: 10.1016/j.neo.2020.10.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Revised: 10/02/2020] [Accepted: 10/04/2020] [Indexed: 12/11/2022]
Abstract
Spontaneously occurring canine oral squamous cell carcinomas (COSCC) are viewed as a useful model for human head and neck squamous cell carcinomas (HNSCC). To date however, the molecular basis of COSCC remains poorly understood. To identify changes pertinent to cancer cells in COSCC, we specifically analyzed tumor cells and matched normal epithelium from clinical formalin-fixed paraffin-embedded specimens using laser-capture-microdissection coupled with RNA-sequencing (RNAseq). Our results identify strong contributions of epithelial-to-mesenchymal transition (EMT), classical tumor-promoting (such as E2F, KRAS, MYC, mTORC1, and TGFB1 signaling) and immune-related pathways in the tumor epithelium of COSCC. Comparative analyses of COSCC with 43 paired tumor/normal HNSCC from The Cancer Genome Atlas revealed a high homology in transcriptional reprogramming, and identified processes associated with cell cycle progression, immune processes, and loss of cellular differentiation as likely central drivers of the disease. Similar to HNSCC, our analyses suggested a ZEB2-driven partial EMT in COSCC and identified selective upregulation of KRT14 and KRT17 in COSCC. Beyond homology in transcriptional signatures, we also found therapeutic vulnerabilities strongly conserved between the species: these included increased expression of PD-L1 and CTLA-4, coinciding with EMT and revealing the potential for immune checkpoint therapies, and overexpression of CDK4/6 that sensitized COSCC to treatment with palbociclib. In summary, our data significantly extend the current knowledge of molecular aberrations in COSCC and underline the potential of spontaneous COSCC as a model for HNSCC to interrogate therapeutic vulnerabilities and support translation of novel therapies from bench to bedside.
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Affiliation(s)
- Franco Guscetti
- Institute of Veterinary Pathology, Vetsuisse Faculty, University of Zürich, Zürich, Switzerland
| | - Sina Nassiri
- Bioinformatics Core Facility, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Erin Beebe
- Institute of Veterinary Pharmacology and Toxicology, Vetsuisse Faculty, University of Zürich, Zürich, Switzerland
| | - Inês Rito Brandao
- Institute of Veterinary Pathology, Vetsuisse Faculty, University of Zürich, Zürich, Switzerland
| | - Ramona Graf
- Institute of Veterinary Pathology, Vetsuisse Faculty, University of Zürich, Zürich, Switzerland
| | - Enni Markkanen
- Institute of Veterinary Pharmacology and Toxicology, Vetsuisse Faculty, University of Zürich, Zürich, Switzerland.
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Puentes PR, Henao MC, Torres CE, Gómez SC, Gómez LA, Burgos JC, Arbeláez P, Osma JF, Muñoz-Camargo C, Reyes LH, Cruz JC. Design, Screening, and Testing of Non-Rational Peptide Libraries with Antimicrobial Activity: In Silico and Experimental Approaches. Antibiotics (Basel) 2020; 9:E854. [PMID: 33265897 PMCID: PMC7759991 DOI: 10.3390/antibiotics9120854] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Revised: 11/20/2020] [Accepted: 11/23/2020] [Indexed: 12/13/2022] Open
Abstract
One of the challenges of modern biotechnology is to find new routes to mitigate the resistance to conventional antibiotics. Antimicrobial peptides (AMPs) are an alternative type of biomolecules, naturally present in a wide variety of organisms, with the capacity to overcome the current microorganism resistance threat. Here, we reviewed our recent efforts to develop a new library of non-rationally produced AMPs that relies on bacterial genome inherent diversity and compared it with rationally designed libraries. Our approach is based on a four-stage workflow process that incorporates the interplay of recent developments in four major emerging technologies: artificial intelligence, molecular dynamics, surface-display in microorganisms, and microfluidics. Implementing this framework is challenging because to obtain reliable results, the in silico algorithms to search for candidate AMPs need to overcome issues of the state-of-the-art approaches that limit the possibilities for multi-space data distribution analyses in extremely large databases. We expect to tackle this challenge by using a recently developed classification algorithm based on deep learning models that rely on convolutional layers and gated recurrent units. This will be complemented by carefully tailored molecular dynamics simulations to elucidate specific interactions with lipid bilayers. Candidate AMPs will be recombinantly-expressed on the surface of microorganisms for further screening via different droplet-based microfluidic-based strategies to identify AMPs with the desired lytic abilities. We believe that the proposed approach opens opportunities for searching and screening bioactive peptides for other applications.
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Affiliation(s)
- Paola Ruiz Puentes
- Center for Research and Formation in Artificial Intelligence, Universidad de los Andes, Bogota DC 111711, Colombia; (P.R.P.); (P.A.)
- Department of Biomedical Engineering, Universidad de los Andes, Bogota DC 111711, Colombia; (C.E.T.); (S.C.G.); (L.A.G.); (C.M.-C.)
| | - María C. Henao
- Grupo de Diseño de Productos y Procesos, Department of Chemical and Food Engineering, Universidad de los Andes, Bogota DC 111711, Colombia;
| | - Carlos E. Torres
- Department of Biomedical Engineering, Universidad de los Andes, Bogota DC 111711, Colombia; (C.E.T.); (S.C.G.); (L.A.G.); (C.M.-C.)
| | - Saúl C. Gómez
- Department of Biomedical Engineering, Universidad de los Andes, Bogota DC 111711, Colombia; (C.E.T.); (S.C.G.); (L.A.G.); (C.M.-C.)
| | - Laura A. Gómez
- Department of Biomedical Engineering, Universidad de los Andes, Bogota DC 111711, Colombia; (C.E.T.); (S.C.G.); (L.A.G.); (C.M.-C.)
| | - Juan C. Burgos
- Chemical Engineering Program, Universidad de Cartagena, Cartagena 130015, Colombia;
| | - Pablo Arbeláez
- Center for Research and Formation in Artificial Intelligence, Universidad de los Andes, Bogota DC 111711, Colombia; (P.R.P.); (P.A.)
- Department of Biomedical Engineering, Universidad de los Andes, Bogota DC 111711, Colombia; (C.E.T.); (S.C.G.); (L.A.G.); (C.M.-C.)
| | - Johann F. Osma
- Department of Electrical and Electronic Engineering, Universidad de los Andes, Bogota DC 111711, Colombia;
| | - Carolina Muñoz-Camargo
- Department of Biomedical Engineering, Universidad de los Andes, Bogota DC 111711, Colombia; (C.E.T.); (S.C.G.); (L.A.G.); (C.M.-C.)
| | - Luis H. Reyes
- Grupo de Diseño de Productos y Procesos, Department of Chemical and Food Engineering, Universidad de los Andes, Bogota DC 111711, Colombia;
| | - Juan C. Cruz
- Department of Biomedical Engineering, Universidad de los Andes, Bogota DC 111711, Colombia; (C.E.T.); (S.C.G.); (L.A.G.); (C.M.-C.)
- School of Chemical Engineering and Advanced Materials, The University of Adelaide, Adelaide 5005, Australia
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Readhead B, Haure-Mirande JV, Mastroeni D, Audrain M, Fanutza T, Kim SH, Blitzer RD, Gandy S, Dudley JT, Ehrlich ME. miR155 regulation of behavior, neuropathology, and cortical transcriptomics in Alzheimer's disease. Acta Neuropathol 2020; 140:295-315. [PMID: 32666270 PMCID: PMC8414561 DOI: 10.1007/s00401-020-02185-z] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Accepted: 06/24/2020] [Indexed: 12/19/2022]
Abstract
MicroRNAs are recognized as important regulators of many facets of physiological brain function while also being implicated in the pathogenesis of several neurological disorders. Dysregulation of miR155 is widely reported across a variety of neurodegenerative conditions, including Alzheimer's disease (AD), Parkinson's disease, amyotrophic lateral sclerosis, and traumatic brain injury. In previous work, we observed that experimentally validated miR155 gene targets were consistently enriched among genes identified as differentially expressed across multiple brain tissue and disease contexts. In particular, we found that human herpesvirus-6A (HHV-6A) suppressed miR155, recapitulating reports of miR155 inhibition by HHV-6A in infected T-cells, thyrocytes, and natural killer cells. In earlier studies, we also reported the effects of constitutive deletion of miR155 on accelerating the accumulation of Aβ deposits in 4-month-old APP/PSEN1 mice. Herein, we complete the cumulative characterization of transcriptomic, electrophysiological, neuropathological, and learning behavior profiles from 4-, 8- and 10-month-old WT and APP/PSEN1 mice in the absence or presence of miR155. We also integrated human post-mortem brain RNA-sequences from four independent AD consortium studies, together comprising 928 samples collected from six brain regions. We report that gene expression perturbations associated with miR155 deletion in mouse cortex are in aggregate observed to be concordant with AD-associated changes across these independent human late-onset AD (LOAD) data sets, supporting the relevance of our findings to human disease. LOAD has recently been formulated as the clinicopathological manifestation of a multiplex of genetic underpinnings and pathophysiological mechanisms. Our accumulated data are consistent with such a formulation, indicating that miR155 may be uniquely positioned at the intersection of at least four components of this LOAD "multiplex": (1) innate immune response pathways; (2) viral response gene networks; (3) synaptic pathology; and (4) proamyloidogenic pathways involving the amyloid β peptide (Aβ).
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Affiliation(s)
- Ben Readhead
- Arizona State University-Banner Neurodegenerative Disease Research Center, Arizona State University, Tempe, AZ, 85281, USA
- Icahn Institute of Genomic Sciences and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | | | - Diego Mastroeni
- Arizona State University-Banner Neurodegenerative Disease Research Center, Arizona State University, Tempe, AZ, 85281, USA
| | - Mickael Audrain
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Tomas Fanutza
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Soong H Kim
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Robert D Blitzer
- Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Sam Gandy
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Alzheimer's Disease Research Center, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Mount Sinai Center for Cognitive Health and NFL Neurological Care, Department of Neurology, New York, NY, 10029, USA
- James J. Peters VA Medical Center, 130 West Kingsbridge Road, New York, NY, 10468, USA
| | - Joel T Dudley
- Icahn Institute of Genomic Sciences and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
| | - Michelle E Ehrlich
- Icahn Institute of Genomic Sciences and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
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Systems level profiling of arginine starvation reveals MYC and ERK adaptive metabolic reprogramming. Cell Death Dis 2020; 11:662. [PMID: 32814773 PMCID: PMC7438517 DOI: 10.1038/s41419-020-02899-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2020] [Revised: 07/29/2020] [Accepted: 07/30/2020] [Indexed: 12/14/2022]
Abstract
Arginine auxotrophy due to the silencing of argininosuccinate synthetase 1 (ASS1) occurs in many carcinomas and in the majority of sarcomas. Arginine deiminase (ADI-PEG20) therapy exploits this metabolic vulnerability by depleting extracellular arginine, causing arginine starvation. ASS1-negative cells develop resistance to ADI-PEG20 through a metabolic adaptation that includes re-expressing ASS1. As arginine-based multiagent therapies are being developed, further characterization of the changes induced by arginine starvation is needed. In order to develop a systems-level understanding of these changes, activity-based proteomic profiling (ABPP) and phosphoproteomic profiling were performed before and after ADI-PEG20 treatment in ADI-PEG20-sensitive and resistant sarcoma cells. When integrated with metabolomic profiling, this multi-omic analysis reveals that cellular response to arginine starvation is mediated by adaptive ERK signaling and activation of the Myc–Max transcriptional network. Concomitantly, these data elucidate proteomic changes that facilitate oxaloacetate production by enhancing glutamine and pyruvate anaplerosis and altering lipid metabolism to recycle citrate for oxidative glutaminolysis. Based on the complexity of metabolic and cellular signaling interactions, these multi-omic approaches could provide valuable tools for evaluating response to metabolically targeted therapies.
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45
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Gene Regulatory Network Analysis of Perivascular Adipose Tissue of Abdominal Aortic Aneurysm Identifies Master Regulators of Key Pathogenetic Pathways. Biomedicines 2020; 8:biomedicines8080288. [PMID: 32823940 PMCID: PMC7459520 DOI: 10.3390/biomedicines8080288] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 07/30/2020] [Accepted: 08/12/2020] [Indexed: 11/19/2022] Open
Abstract
The lack of medical therapy to treat abdominal aortic aneurysm (AAA) stems from our inadequate understanding of the mechanisms underlying AAA pathogenesis. To date, the only available treatment option relies on surgical intervention, which aims to prevent AAA rupture. Identifying specific regulators of pivotal pathogenetic mechanisms would allow the development of novel treatments. With this work, we sought to identify regulatory factors associated with co-expressed genes characterizing the diseased perivascular adipose tissue (PVAT) of AAA patients, which is crucially involved in AAA pathogenesis. We applied a reverse engineering approach to identify cis-regulatory elements of diseased PVAT genes, the associated transcription factors, and upstream regulators. Finally, by analyzing the topological properties of the reconstructed regulatory disease network, we prioritized putative targets for AAA interference treatment options. Overall, we identified NFKB1, SPIB, and TBP as the most relevant transcription factors, as well as MAPK1 and GSKB3 protein kinases and RXRA nuclear receptor as key upstream regulators. We showed that these factors could regulate different co-expressed gene subsets in AAA PVAT, specifically associated with both innate and antigen-driven immune response pathways. Inhibition of these factors may represent a novel option for the development of efficient immunomodulatory strategies to treat AAA.
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Mastrogamvraki N, Zaravinos A. Signatures of co-deregulated genes and their transcriptional regulators in colorectal cancer. NPJ Syst Biol Appl 2020; 6:23. [PMID: 32737302 PMCID: PMC7395738 DOI: 10.1038/s41540-020-00144-8] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2020] [Accepted: 06/19/2020] [Indexed: 02/06/2023] Open
Abstract
The deregulated genes in colorectal cancer (CRC) vary significantly across different studies. Thus, a systems biology approach is needed to identify the co-deregulated genes (co-DEGs), explore their molecular networks, and spot the major hub proteins within these networks. We reanalyzed 19 GEO gene expression profiles to identify and annotate CRC versus normal signatures, single-gene perturbation, and single-drug perturbation signatures. We identified the co-DEGs across different studies, their upstream regulating kinases and transcription factors (TFs). Connectivity Map was used to identify likely repurposing drugs against CRC within each group. The functional changes of the co-upregulated genes in the first category were mainly associated with negative regulation of transforming growth factor β production and glomerular epithelial cell differentiation; whereas the co-downregulated genes were enriched in cotranslational protein targeting to the membrane. We identified 17 hub proteins across the co-upregulated genes and 18 hub proteins across the co-downregulated genes, composed of well-known TFs (MYC, TCF3, PML) and kinases (CSNK2A1, CDK1/4, MAPK14), and validated most of them using GEPIA2 and HPA, but also through two signature gene lists composed of the co-up and co-downregulated genes. We further identified a list of repurposing drugs that can potentially target the co-DEGs in CRC, including camptothecin, neostigmine bromide, emetine, remoxipride, cephaeline, thioridazine, and omeprazole. Similar analyses were performed in the co-DEG signatures in single-gene or drug perturbation experiments in CRC. MYC, PML, CDKs, CSNK2A1, and MAPKs were common hub proteins among all studies. Overall, we identified the critical genes in CRC and we propose repurposing drugs that could be used against them.
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Affiliation(s)
- Natalia Mastrogamvraki
- Department of Life Sciences, School of Sciences, European University Cyprus, 1516, Nicosia, Cyprus
| | - Apostolos Zaravinos
- Department of Basic Medical Sciences, College of Medicine, Member of QU Health, Qatar University, Doha, Qatar.
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An In Vitro Model of Mast Cell Recruitment and Activation by Breast Cancer Cells Supports Anti-Tumoral Responses. Int J Mol Sci 2020; 21:ijms21155293. [PMID: 32722549 PMCID: PMC7432939 DOI: 10.3390/ijms21155293] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 05/29/2020] [Accepted: 06/18/2020] [Indexed: 12/18/2022] Open
Abstract
Breast cancer (BrC) affects millions of women yearly. Mast cells (MCs) are common components of breast tumors with documented agonistic and antagonistic roles in tumor progression. Understanding the participation of MCs in BrC may lead to new therapies to control tumor growth. In this study, we looked into mechanistic models of MC responses triggered by BrC cells (BrCC), assessing both early degranulation and late transcriptional activities. We used aggressive and non-aggressive BrCC to model the progressive staging of the disease over HMC1 and LAD-2 human MC lines. We found that both MC lines were chemoattracted by all BrCC, but their activation was preferentially induced by aggressive lines, finding differences in their active transcriptional programs, both at basal level and after stimulation. Among those genes with altered expression were down-regulated SPP1, PDCD1, IL17A and TGFB1 and up-regulated KITLG and IFNG. A low expression of SPP1 and a high expression of KITLG and IFNG were associated with increased overall survival of BrC patients from public databases. The set of altered genes is more often associated with tumor stromas enriched with anti-tumoral signals, suggesting that MCs may participate in tumor control.
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48
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Fatoki TH, Ibraheem O, Ogunyemi IO, Akinmoladun AC, Ugboko HU, Adeseko CJ, Awofisayo OA, Olusegun SJ, Enibukun JM. Network analysis, sequence and structure dynamics of key proteins of coronavirus and human host, and molecular docking of selected phytochemicals of nine medicinal plants. J Biomol Struct Dyn 2020; 39:6195-6217. [PMID: 32686993 DOI: 10.1080/07391102.2020.1794971] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
The novel coronavirus of 2019 (nCoV-19) has become a pandemic, affecting over 205 nations with over 7,410,000 confirmed cases which has resulted to over 418,000 deaths worldwide. This study aimed to identify potential therapeutic compounds and phytochemicals of medicinal plants that have potential to modulate the expression network of genes that are involve in SARS-CoV-2 pathology in human host and to understand the dynamics key proteins involved in the virus-host interactions. The method used include gene network analysis, molecular docking, and sequence and structure dynamics simulations. The results identified DNA-dependent protein kinase (DNA-PK) and Protein kinase CK2 as key players in SARS-CoV-2 lifecycle. Among the predicted drugs compounds, clemizole, monorden, spironolactone and tanespimycin showed high binding energies; among the studied repurposing compounds, remdesivir, simeprevir and valinomycin showed high binding energies; among the predicted acidic compounds, acetylursolic acid and hardwickiic acid gave high binding energies; while among the studied anthraquinones and glycosides compounds, ellagitannin and friedelanone showed high binding energies against 3-Chymotrypsin-like protease (3CLpro), Papain-like protease (PLpro), helicase (nsp13), RNA-dependent RNA polymerase (nsp12), 2'-O-ribose methyltransferase (nsp16) of SARS-CoV-2 and DNA-PK and CK2alpha in human. The order of affinity for CoV proteins is 5Y3E > 6NUS > 6JYT > 2XYR > 3VB6. Finally, medicinal plants with phytochemicals such as caffeine, ellagic acid, quercetin and their derivatives could possibly remediate COVID-19.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Toluwase Hezekiah Fatoki
- Translational Bioinformatics Unit, Department of Biochemistry, Federal University Oye Ekiti, Oye Ekiti, Ekiti State, Nigeria
| | - Omodele Ibraheem
- Translational Bioinformatics Unit, Department of Biochemistry, Federal University Oye Ekiti, Oye Ekiti, Ekiti State, Nigeria
| | | | | | - Harriet U Ugboko
- Microbiology Research Unit, Department of Biological Sciences, Covenant University, Ota, Ogun State, Nigeria
| | | | - Oladoja A Awofisayo
- Department of Pharmaceutical and Medicinal Chemistry, University of Uyo, Uyo, Nigeria
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Shi XX, Wu FX, Mei LC, Wang YL, Hao GF, Yang GF. Bioinformatics toolbox for exploring protein phosphorylation network. Brief Bioinform 2020; 22:5871447. [PMID: 32666116 DOI: 10.1093/bib/bbaa134] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2020] [Revised: 05/15/2020] [Accepted: 06/02/2020] [Indexed: 01/23/2023] Open
Abstract
A clear systematic delineation of the interactions between phosphorylation sites on substrates and their effector kinases plays a fundamental role in revealing cellular activities, understanding signaling modulation mechanisms and proposing novel hypotheses. The emergence of bioinformatics tools contributes to studying phosphorylation network. Some of them feature the visualization of network, enabling more effective trace of the underlying biological problems in a clear and succinct way. In this review, we aimed to provide a toolbox for exploring phosphorylation network. We first systematically surveyed 19 tools that are available for exploring phosphorylation networks, and subsequently comparatively analyzed and summarized these tools to guide tool selection in terms of functionality, data sources, performance, network visualization and implementation, and finally briefly discussed the application cases of these tools. In different scenarios, the conclusion on the suitability of a tool for a specific user may vary. Nevertheless, easily accessible bioinformatics tools are proved to facilitate biological findings. Hopefully, this work might also assist non-specialists, students, as well as computational scientists who aim at developing novel tools in the field of phosphorylation modification.
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Affiliation(s)
- Xing-Xing Shi
- College of Chemistry, Central China Normal University (CCNU)
| | | | | | - Yu-Liang Wang
- College of Chemistry, Central China Normal University (CCNU)
| | - Ge-Fei Hao
- Bioinformatics in State Key Laboratory Breeding Base of Green Pesticide and Agricultural Bioengineering of GZU and College of Chemistry of CCNU
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50
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Pereira EJ, Burns JS, Lee CY, Marohl T, Calderon D, Wang L, Atkins KA, Wang CC, Janes KA. Sporadic activation of an oxidative stress-dependent NRF2-p53 signaling network in breast epithelial spheroids and premalignancies. Sci Signal 2020; 13:13/627/eaba4200. [PMID: 32291314 DOI: 10.1126/scisignal.aba4200] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Breast and mammary epithelial cells experience different local environments during tissue development and tumorigenesis. Microenvironmental heterogeneity gives rise to distinct cell regulatory states whose identity and importance are just beginning to be appreciated. Cellular states diversify when clonal three-dimensional (3D) spheroids are cultured in basement membrane, and one such state is associated with stress tolerance and poor response to anticancer therapeutics. Here, we found that this state was jointly coordinated by the NRF2 and p53 pathways, which were costabilized by spontaneous oxidative stress within 3D cultures. Inhibition of NRF2 or p53 individually disrupted some of the transcripts defining the regulatory state but did not yield a notable phenotype in nontransformed breast epithelial cells. In contrast, combined perturbation prevented 3D growth in an oxidative stress-dependent manner. By integrating systems models of NRF2 and p53 signaling in a single oxidative stress network, we recapitulated these observations and made predictions about oxidative stress profiles during 3D growth. NRF2 and p53 signaling were similarly coordinated in normal breast epithelial tissue and hormone-negative ductal carcinoma in situ lesions but were uncoupled in triple-negative breast cancer (TNBC), a subtype in which p53 is usually mutated. Using the integrated model, we correlated the extent of this uncoupling in TNBC cell lines with the importance of NRF2 in the 3D growth of these cell lines and their predicted handling of oxidative stress. Our results point to an oxidative stress tolerance network that is important for single cells during glandular development and the early stages of breast cancer.
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Affiliation(s)
- Elizabeth J Pereira
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA
| | - Joseph S Burns
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA
| | - Christina Y Lee
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA
| | - Taylor Marohl
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA
| | - Delia Calderon
- Biology and Chemistry Programs, California State University Channel Islands, Camarillo, CA 93012, USA
| | - Lixin Wang
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA
| | - Kristen A Atkins
- Department of Pathology, University of Virginia, Charlottesville, VA 22908, USA
| | - Chun-Chao Wang
- Institute of Molecular Medicine and Department of Medical Science, National Tsing Hua University, Hsinchu 30013, Taiwan
| | - Kevin A Janes
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA. .,Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA 22908, USA
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