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Yang XM, Wang XQ, Hu LP, Feng MX, Zhou YQ, Li DX, Li J, Miao XC, Zhang YL, Yao LL, Nie HZ, Huang S, Xia Q, Zhang XL, Jiang SH, Zhang ZG. Nucleolar HEAT Repeat Containing 1 Up-regulated by the Mechanistic Target of Rapamycin Complex 1 Signaling Promotes Hepatocellular Carcinoma Growth by Dominating Ribosome Biogenesis and Proteome Homeostasis. Gastroenterology 2023; 165:629-646. [PMID: 37247644 DOI: 10.1053/j.gastro.2023.05.029] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Revised: 04/14/2023] [Accepted: 05/12/2023] [Indexed: 05/31/2023]
Abstract
BACKGROUND & AIMS Hyperactivation of ribosome biogenesis leads to hepatocyte transformation and plays pivotal roles in hepatocellular carcinoma (HCC) development. We aimed to identify critical ribosome biogenesis proteins that are overexpressed and crucial in HCC progression. METHODS HEAT repeat containing 1 (HEATR1) expression and clinical correlations were analyzed using The Cancer Genome Atlas and Gene Expression Omnibus databases and further evaluated by immunohistochemical analysis of an HCC tissue microarray. Gene expression was knocked down by small interfering RNA. HEATR1-knockdown cells were subjected to viability, cell cycle, and apoptosis assays and used to establish subcutaneous and orthotopic tumor models. Chromatin immunoprecipitation and quantitative polymerase chain reaction were performed to detect the association of candidate proteins with specific DNA sequences. Endogenous coimmunoprecipitation combined with mass spectrometry was used to identify protein interactions. We performed immunoblot and immunofluorescence assays to detect and localize proteins in cells. The nucleolus ultrastructure was detected by transmission electron microscopy. Click-iT (Thermo Fisher Scientific) RNA imaging and puromycin incorporation assays were used to measure nascent ribosomal RNA and protein synthesis, respectively. Proteasome activity, 20S proteasome foci formation, and protein stability were evaluated in HEATR1-knockdown HCC cells. RESULTS HEATR1 was the most up-regulated gene in a set of ribosome biogenesis mediators in HCC samples. High expression of HEATR1 was associated with poor survival and malignant clinicopathologic features in patients with HCC and contributed to HCC growth in vitro and in vivo. HEATR1 expression was regulated by the transcription factor specificity protein 1, which can be activated by insulin-like growth factor 1-mammalian target of rapamycin complex 1 signaling in HCC cells. HEATR1 localized predominantly in the nucleolus, bound to ribosomal DNA, and was associated with RNA polymerase I transcription/processing factors. Knockdown of HEATR1 disrupted ribosomal RNA biogenesis and impaired nascent protein synthesis, leading to reduced cytoplasmic proteasome activity and inhibitory-κB/nuclear factor-κB signaling. Moreover, HEATR1 knockdown induced nucleolar stress with increased nuclear proteasome activity and inactivation of the nucleophosmin 1-MYC axis. CONCLUSIONS Our study revealed that HEATR1 is up-regulated by insulin-like growth factor 1-mammalian target of rapamycin complex 1-specificity protein 1 signaling in HCC and functions as a crucial regulator of ribosome biogenesis and proteome homeostasis to promote HCC development.
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Affiliation(s)
- Xiao-Mei Yang
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiao-Qi Wang
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Li-Peng Hu
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ming-Xuan Feng
- Department of Transplantation and Hepatic Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yao-Qi Zhou
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Dong-Xue Li
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jun Li
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiao-Cao Miao
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yan-Li Zhang
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lin-Li Yao
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hui-Zhen Nie
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shan Huang
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qiang Xia
- Department of Transplantation and Hepatic Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xue-Li Zhang
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Shu-Heng Jiang
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Zhi-Gang Zhang
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
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2
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Ni C, Buszczak M. The homeostatic regulation of ribosome biogenesis. Semin Cell Dev Biol 2023; 136:13-26. [PMID: 35440410 PMCID: PMC9569395 DOI: 10.1016/j.semcdb.2022.03.043] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 03/30/2022] [Accepted: 03/31/2022] [Indexed: 12/22/2022]
Abstract
The continued integrity of biological systems depends on a balance between interdependent elements at the molecular, cellular, and organismal levels. This is particularly true for the generation of ribosomes, which influence almost every aspect of cell and organismal biology. Ribosome biogenesis (RiBi) is an energetically demanding process that involves all three RNA polymerases, numerous RNA processing factors, chaperones, and the coordinated expression of 79-80 ribosomal proteins (r-proteins). Work over the last several decades has revealed that the dynamic regulation of ribosome production represents a major mechanism by which cells maintain homeostasis in response to changing environmental conditions and acute stress. More recent studies suggest that cells and tissues within multicellular organisms exhibit dramatically different levels of ribosome production and protein synthesis, marked by the differential expression of RiBi factors. Thus, distinct bottlenecks in the RiBi process, downstream of rRNA transcription, may exist within different cell populations of multicellular organisms during development and in adulthood. This review will focus on our current understanding of the mechanisms that link the complex molecular process of ribosome biogenesis with cellular and organismal physiology. We will discuss diverse topics including how different steps in the RiBi process are coordinated with one another, how MYC and mTOR impact RiBi, and how RiBi levels change between stem cells and their differentiated progeny. In turn, we will also review how regulated changes in ribosome production itself can feedback to influence cell fate and function.
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Affiliation(s)
- Chunyang Ni
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390-9148, USA
| | - Michael Buszczak
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390-9148, USA.
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3
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de Bree LCJ, Mourits VP, Koeken VA, Moorlag SJ, Janssen R, Folkman L, Barreca D, Krausgruber T, Fife-Gernedl V, Novakovic B, Arts RJ, Dijkstra H, Lemmers H, Bock C, Joosten LA, van Crevel R, Benn CS, Netea MG. Circadian rhythm influences induction of trained immunity by BCG vaccination. J Clin Invest 2021; 130:5603-5617. [PMID: 32692732 DOI: 10.1172/jci133934] [Citation(s) in RCA: 82] [Impact Index Per Article: 27.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Accepted: 07/14/2020] [Indexed: 12/20/2022] Open
Abstract
BACKGROUNDThe antituberculosis vaccine bacillus Calmette-Guérin (BCG) reduces overall infant mortality. Induction of innate immune memory, also termed trained immunity, contributes toward protection against heterologous infections. Since immune cells display oscillations in numbers and function throughout the day, we investigated the effect of BCG administration time on the induction of trained immunity.METHODSEighteen volunteers were vaccinated with BCG at 6 pm and compared with 36 age- and sex-matched volunteers vaccinated between 8 am and 9 am. Peripheral blood mononuclear cells were stimulated with Staphylococcus aureus and Mycobacterium tuberculosis before, as well as 2 weeks and 3 months after, BCG vaccination. Cytokine production was measured to assess the induction of trained immunity and adaptive responses, respectively. Additionally, the influence of vaccination time on induction of trained immunity was studied in an independent cohort of 302 individuals vaccinated between 8 am and 12 pm with BCG.RESULTSCompared with evening vaccination, morning vaccination elicited both a stronger trained immunity and adaptive immune phenotype. In a large cohort of 302 volunteers, early morning vaccination resulted in a superior cytokine production capacity compared with later morning. A cellular, rather than soluble, substrate of the circadian effect of BCG vaccination was demonstrated by the enhanced capacity to induce trained immunity in vitro in morning- compared with evening-isolated monocytes.CONCLUSIONSBCG vaccination in the morning induces stronger trained immunity and adaptive responses compared with evening vaccination. Future studies should take vaccine administration time into account when studying specific and nonspecific effects of vaccines; early morning should be the preferred moment of BCG administration.FUNDINGThe Netherlands Organization for Scientific Research, the European Research Council, and the Danish National Research Foundation.
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Affiliation(s)
- L Charlotte J de Bree
- Radboud Center for Infectious Diseases and Department of Internal Medicine, Radboud University Medical Center, Nijmegen, Netherlands.,Bandim Health Project, OPEN, Institute of Clinical Research, University of Southern Denmark/Odense University Hospital, Odense, Denmark.,Danish Institute for Advanced Study, University of Southern Denmark, Odense, Denmark
| | - Vera P Mourits
- Radboud Center for Infectious Diseases and Department of Internal Medicine, Radboud University Medical Center, Nijmegen, Netherlands
| | - Valerie Acm Koeken
- Radboud Center for Infectious Diseases and Department of Internal Medicine, Radboud University Medical Center, Nijmegen, Netherlands
| | - Simone Jcfm Moorlag
- Radboud Center for Infectious Diseases and Department of Internal Medicine, Radboud University Medical Center, Nijmegen, Netherlands
| | - Robine Janssen
- Radboud Center for Infectious Diseases and Department of Internal Medicine, Radboud University Medical Center, Nijmegen, Netherlands
| | - Lukas Folkman
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Daniele Barreca
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Thomas Krausgruber
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Victoria Fife-Gernedl
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Boris Novakovic
- Epigenetics Research, Murdoch Children's Research Institute, Parkville, Australia and Department of Paediatrics, University of Melbourne, Melbourne, Australia
| | - Rob Jw Arts
- Radboud Center for Infectious Diseases and Department of Internal Medicine, Radboud University Medical Center, Nijmegen, Netherlands
| | - Helga Dijkstra
- Radboud Center for Infectious Diseases and Department of Internal Medicine, Radboud University Medical Center, Nijmegen, Netherlands
| | - Heidi Lemmers
- Radboud Center for Infectious Diseases and Department of Internal Medicine, Radboud University Medical Center, Nijmegen, Netherlands
| | - Christoph Bock
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.,Department of Laboratory Medicine, Medical University of Vienna, Vienna, Austria
| | - Leo Ab Joosten
- Radboud Center for Infectious Diseases and Department of Internal Medicine, Radboud University Medical Center, Nijmegen, Netherlands
| | - Reinout van Crevel
- Radboud Center for Infectious Diseases and Department of Internal Medicine, Radboud University Medical Center, Nijmegen, Netherlands
| | - Christine S Benn
- Bandim Health Project, OPEN, Institute of Clinical Research, University of Southern Denmark/Odense University Hospital, Odense, Denmark.,Danish Institute for Advanced Study, University of Southern Denmark, Odense, Denmark
| | - Mihai G Netea
- Radboud Center for Infectious Diseases and Department of Internal Medicine, Radboud University Medical Center, Nijmegen, Netherlands.,Department for Genomics and Immunoregulation, Life and Medical Sciences Institute (LIMES), University of Bonn, Bonn, Germany
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Petibon C, Malik Ghulam M, Catala M, Abou Elela S. Regulation of ribosomal protein genes: An ordered anarchy. WILEY INTERDISCIPLINARY REVIEWS-RNA 2020; 12:e1632. [PMID: 33038057 PMCID: PMC8047918 DOI: 10.1002/wrna.1632] [Citation(s) in RCA: 49] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 09/08/2020] [Accepted: 09/23/2020] [Indexed: 02/06/2023]
Abstract
Ribosomal protein genes are among the most highly expressed genes in most cell types. Their products are generally essential for ribosome synthesis, which is the cornerstone for cell growth and proliferation. Many cellular resources are dedicated to producing ribosomal proteins and thus this process needs to be regulated in ways that carefully balance the supply of nascent ribosomal proteins with the demand for new ribosomes. Ribosomal protein genes have classically been viewed as a uniform interconnected regulon regulated in eukaryotic cells by target of rapamycin and protein kinase A pathway in response to changes in growth conditions and/or cellular status. However, recent literature depicts a more complex picture in which the amount of ribosomal proteins produced varies between genes in response to two overlapping regulatory circuits. The first includes the classical general ribosome‐producing program and the second is a gene‐specific feature responsible for fine‐tuning the amount of ribosomal proteins produced from each individual ribosomal gene. Unlike the general pathway that is mainly controlled at the level of transcription and translation, this specific regulation of ribosomal protein genes is largely achieved through changes in pre‐mRNA splicing efficiency and mRNA stability. By combining general and specific regulation, the cell can coordinate ribosome production, while allowing functional specialization and diversity. Here we review the many ways ribosomal protein genes are regulated, with special focus on the emerging role of posttranscriptional regulatory events in fine‐tuning the expression of ribosomal protein genes and its role in controlling the potential variation in ribosome functions. This article is categorized under:Translation > Ribosome Biogenesis Translation > Ribosome Structure/Function Translation > Translation Regulation
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Affiliation(s)
- Cyrielle Petibon
- Département de microbiologie et d'infectiologie, Universite de Sherbrooke, Faculté de Médecine et des Sciences de la Santé, Sherbrooke, Quebec, Canada
| | - Mustafa Malik Ghulam
- Département de microbiologie et d'infectiologie, Universite de Sherbrooke, Faculté de Médecine et des Sciences de la Santé, Sherbrooke, Quebec, Canada
| | - Mathieu Catala
- Département de microbiologie et d'infectiologie, Universite de Sherbrooke, Faculté de Médecine et des Sciences de la Santé, Sherbrooke, Quebec, Canada
| | - Sherif Abou Elela
- Département de microbiologie et d'infectiologie, Universite de Sherbrooke, Faculté de Médecine et des Sciences de la Santé, Sherbrooke, Quebec, Canada
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Ravi V, Jain A, Khan D, Ahamed F, Mishra S, Giri M, Inbaraj M, Krishna S, Sarikhani M, Maity S, Kumar S, Shah RA, Dave P, Pandit AS, Rajendran R, Desingu PA, Varshney U, Das S, Kolthur-Seetharam U, Rajakumari S, Singh M, Sundaresan NR. SIRT6 transcriptionally regulates global protein synthesis through transcription factor Sp1 independent of its deacetylase activity. Nucleic Acids Res 2019; 47:9115-9131. [PMID: 31372634 PMCID: PMC6755095 DOI: 10.1093/nar/gkz648] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2018] [Revised: 06/30/2019] [Accepted: 07/31/2019] [Indexed: 01/12/2023] Open
Abstract
Global protein synthesis is emerging as an important player in the context of aging and age-related diseases. However, the intricate molecular networks that regulate protein synthesis are poorly understood. Here, we report that SIRT6, a nuclear-localized histone deacetylase represses global protein synthesis by transcriptionally regulating mTOR signalling via the transcription factor Sp1, independent of its deacetylase activity. Our results suggest that SIRT6 deficiency increases protein synthesis in mice. Further, multiple lines of in vitro evidence suggest that SIRT6 negatively regulates protein synthesis in a cell-autonomous fashion and independent of its catalytic activity. Mechanistically, SIRT6 binds to the zinc finger DNA binding domain of Sp1 and represses its activity. SIRT6 deficiency increased the occupancy of Sp1 at key mTOR signalling gene promoters resulting in enhanced expression of these genes and activation of the mTOR signalling pathway. Interestingly, inhibition of either mTOR or Sp1 abrogated the increased protein synthesis observed under SIRT6 deficient conditions. Moreover, pharmacological inhibition of mTOR restored cardiac function in muscle-specific SIRT6 knockout mice, which spontaneously develop cardiac hypertrophy. Overall, these findings have unravelled a new layer of regulation of global protein synthesis by SIRT6, which can be potentially targeted to combat aging-associated diseases like cardiac hypertrophy.
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Affiliation(s)
- Venkatraman Ravi
- Department of Microbiology and Cell Biology, Indian Institute of Science, Bengaluru, India
| | - Aditi Jain
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bengaluru, India
| | - Danish Khan
- Department of Microbiology and Cell Biology, Indian Institute of Science, Bengaluru, India
| | - Faiz Ahamed
- Department of Microbiology and Cell Biology, Indian Institute of Science, Bengaluru, India
| | - Sneha Mishra
- Department of Microbiology and Cell Biology, Indian Institute of Science, Bengaluru, India
| | - Malyasree Giri
- Molecular Biophysics Unit, Indian Institute of Science, Bengaluru, India
| | - Meena Inbaraj
- Department of Microbiology and Cell Biology, Indian Institute of Science, Bengaluru, India
| | - Swati Krishna
- Department of Microbiology and Cell Biology, Indian Institute of Science, Bengaluru, India
| | - Mohsen Sarikhani
- Department of Microbiology and Cell Biology, Indian Institute of Science, Bengaluru, India
| | - Sangeeta Maity
- Department of Microbiology and Cell Biology, Indian Institute of Science, Bengaluru, India
| | - Shweta Kumar
- Department of Microbiology and Cell Biology, Indian Institute of Science, Bengaluru, India
| | - Riyaz Ahmad Shah
- Department of Microbiology and Cell Biology, Indian Institute of Science, Bengaluru, India
| | - Pratik Dave
- Department of Microbiology and Cell Biology, Indian Institute of Science, Bengaluru, India
| | - Anwit S Pandit
- Department of Microbiology and Cell Biology, Indian Institute of Science, Bengaluru, India
| | - Rajprabu Rajendran
- Department of Molecular Reproduction, Development and Genetics, Indian Institute of Science, Bengaluru, India
| | - Perumal A Desingu
- Department of Microbiology and Cell Biology, Indian Institute of Science, Bengaluru, India
| | - Umesh Varshney
- Department of Microbiology and Cell Biology, Indian Institute of Science, Bengaluru, India
| | - Saumitra Das
- Department of Microbiology and Cell Biology, Indian Institute of Science, Bengaluru, India
| | | | - Sona Rajakumari
- Department of Molecular Reproduction, Development and Genetics, Indian Institute of Science, Bengaluru, India
| | - Mahavir Singh
- Molecular Biophysics Unit, Indian Institute of Science, Bengaluru, India.,NMR Research Centre, Indian Institute of Science, Bengaluru, India
| | - Nagalingam R Sundaresan
- Department of Microbiology and Cell Biology, Indian Institute of Science, Bengaluru, India.,Centre for BioSystems Science and Engineering, Indian Institute of Science, Bengaluru, India
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Lewis CS, Thomas HE, Orr-Asman M, Green LC, Boody RE, Matiash K, Karve A, Hisada YM, Davis HW, Qi X, Mercer C, Lucas FV, Aronow BJ, Mackman N, Versteeg HH, Bogdanov VY. mTOR kinase inhibition reduces tissue factor expression and growth of pancreatic neuroendocrine tumors. J Thromb Haemost 2019; 17:169-182. [PMID: 30472780 PMCID: PMC6345540 DOI: 10.1111/jth.14342] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2018] [Indexed: 12/22/2022]
Abstract
Essentials Tissue factor (TF) isoforms are expressed in pancreatic neuroendocrine tumors (pNET). TF knockdown inhibits proliferation of human pNET cells in vitro. mTOR kinase inhibitor sapanisertib/MLN0128 suppresses TF expression in human pNET cells. Sapanisertib suppresses TF expression and activity and reduces the growth of pNET tumors in vivo. SUMMARY: Background Full-length tissue factor (flTF) and alternatively spliced TF (asTF) contribute to growth and spread of pancreatic ductal adenocarcinoma. It is unknown, however, if flTF and/or asTF contribute to the pathobiology of pancreatic neuroendocrine tumors (pNETs). Objective To assess TF expression in pNETs and the effects of mTOR complex 1/2 (mTORC1/2) inhibition on pNET growth. Methods Human pNET specimens were immunostained for TF. Human pNET cell lines QGP1 and BON were evaluated for TF expression and responsiveness to mTOR inhibition. shRNA were used to knock down TF in BON. TF cofactor activity was assessed using a two-step FXa generation assay. TF promoter activity was assessed using transient transfection of human TF promoter-driven reporter constructs into cells. Mice bearing orthotopic BON tumors were treated with the mTORC1/2 ATP site competitive inhibitor sapanisertib/MLN0128 (3 mg kg-1 , oral gavage) for 34 days. Results Immunostaining of pNET tissue revealed flTF and asTF expression. BON and QGP1 expressed both TF isoforms, with BON exhibiting higher levels. shRNA directed against TF suppressed BON proliferation in vitro. Treatment of BON with sapanisertib inhibited mTOR signaling and suppressed TF levels. BON tumors grown in mice treated with sapanisertib had significantly less TF protein and cofactor activity, and were smaller compared with tumors grown in control mice. Conclusions TF isoforms are expressed in pNETs. Sapanisertib suppresses TF mRNA and protein expression as well as TF cofactor activity in vitro and in vivo. Thus, further studies are warranted to evaluate the clinical utility of TF-suppressing mTORC1/2 inhibitor sapanisertib in pNET management.
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Affiliation(s)
- Clayton S Lewis
- Division of Hematology/Oncology, Department of Internal Medicine, University of Cincinnati College of Medicine
| | - Hala Elnakat Thomas
- Division of Hematology/Oncology, Department of Internal Medicine, University of Cincinnati College of Medicine
| | - Melissa Orr-Asman
- Division of Hematology/Oncology, Department of Internal Medicine, University of Cincinnati College of Medicine
| | - Lisa C Green
- Division of Hematology/Oncology, Department of Internal Medicine, University of Cincinnati College of Medicine
| | - Rachel E Boody
- Division of Hematology/Oncology, Department of Internal Medicine, University of Cincinnati College of Medicine
| | - Kateryna Matiash
- Division of Hematology/Oncology, Department of Internal Medicine, University of Cincinnati College of Medicine
| | - Aniruddha Karve
- Division of Hematology/Oncology, Department of Internal Medicine, University of Cincinnati College of Medicine
| | - Yohei M. Hisada
- Division of Hematology/Oncology, Department of Medicine, University of North Carolina at Chapel Hill
| | - Harold W Davis
- Division of Hematology/Oncology, Department of Internal Medicine, University of Cincinnati College of Medicine
| | - Xiaoyang Qi
- Division of Hematology/Oncology, Department of Internal Medicine, University of Cincinnati College of Medicine
| | - Carol Mercer
- Division of Hematology/Oncology, Department of Internal Medicine, University of Cincinnati College of Medicine
| | - Fred V Lucas
- Department of Pathology & Laboratory Medicine, University of Cincinnati College of Medicine
| | - Bruce J. Aronow
- Computational Medicine and Division of Biomedical Informatics, Cincinnati Children’s Hospital and Medical Center
| | - Nigel Mackman
- Division of Hematology/Oncology, Department of Medicine, University of North Carolina at Chapel Hill
| | - Henri H Versteeg
- Einthoven Laboratory for Experimental Vascular Medicine, Department of Internal Medicine, Leiden University Medical Center
| | - Vladimir Y Bogdanov
- Division of Hematology/Oncology, Department of Internal Medicine, University of Cincinnati College of Medicine
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Awasthi A, Nain V, Puria R. MYOD and HAND transcription factors have conserved recognition sites in mTOR promoter: insights from in silico analysis. Interdiscip Sci 2018; 11:329-335. [PMID: 29411313 DOI: 10.1007/s12539-018-0284-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2017] [Revised: 01/02/2018] [Accepted: 01/24/2018] [Indexed: 11/28/2022]
Abstract
mTOR regulates multiple cellular processes that are critical for proper maintenance of cell growth and development. However, mechanisms and factors responsible for transcriptional regulation of mTOR are partially known. To identify different transcription factor binding sites in promoter region of mTOR, we performed in silico phylogenetic foot printing analysis of diverse set of human orthologs. Phylogenetic tree for the orthologs was generated to establish the evolutionary relationships among them. Conserved binding sites among the species were predicted by tool MEME. The predicted conserved sites were further analyzed for binding of transcription factors by MatInspector program. Predicted TFs were then integrated with known physical interactions and coexpression data to decipher the important transcriptional regulators of mTOR signaling. Our study suggests that motifs AGGCGGG (+ 15 to + 21) and GGCGGC (+ 60 to + 65) are highly conserved across the species and are recognition sequence for HAND and MYOD transcription factors, respectively. Also these two transcription factors show direct physical interaction in protein-protein interaction map, indicating their regulatory role on expression of mTOR for control of myogenesis. Our study provides novel clues on differential regulation of mTOR under diverse environmental conditions.
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Affiliation(s)
- Ankita Awasthi
- School of Biotechnology, Gautam Buddha University, Gautam Budh Nagar, Greater Noida, 201312, India
| | - Vikrant Nain
- School of Biotechnology, Gautam Buddha University, Gautam Budh Nagar, Greater Noida, 201312, India.
| | - Rekha Puria
- School of Biotechnology, Gautam Buddha University, Gautam Budh Nagar, Greater Noida, 201312, India.
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8
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Erdogan CS, Mørup-Lendal M, Dalgaard LT, Vang O. Sirtuin 1 independent effects of resveratrol in INS-1E β-cells. Chem Biol Interact 2017; 264:52-60. [PMID: 28108221 DOI: 10.1016/j.cbi.2017.01.008] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2016] [Revised: 12/22/2016] [Accepted: 01/16/2017] [Indexed: 11/26/2022]
Abstract
Resveratrol (Resv), a natural polyphenol, is suggested to have various health benefits including improved insulin sensitivity. Resv activates Sirtuin (Sirt1) in several species and tissues. Sirt1 is a protein deacetylase with an important role in ageing, metabolism and β-cell function. In insulinoma β-cells (INS-1E), Resv is previously shown to improve glucose-stimulated insulin secretion in a Sirt1-dependent mechanism and to protect against β-cell dedifferentiation in non-human primates, while inducing hypertrophy in myoblasts. Mammalian (mechanistic) Target of Rapamycin (mTOR), is a key regulator of cellular metabolism and regulates the cell size, β-cell survival and proliferation. In order to understand the interaction of Sirt1 and mTOR cascade activity with Resv-induced changes in the INS-1E cell line, we generated stable Sirt1-down-regulated INS-1E cells, and analysed Sirt1-dependent effects of Resv with respect to mTOR cascade activity. Sirt1-knockdown (KD) had a significant increase in cell size compared to negative-control (NEG CTR) cells. Resveratrol treatment increased cell size in both cell types in a dose-dependent manner at 24 h (Resv conc: 15-60 μM), and decreased the cell number (Resv conc: 30-60 μM). Cell area was increased in NEG CTR cells (Resv conc: 60 μM) at 24 h and KD cells at 48 h (Resv conc: 15-60 μM). Rapamycin, a specific mTOR inhibitor, counteracted the Resv-induced cell enlargement (both cell diameter and area). Furthermore, Sirt1-downregulation by itself did not affect the mTOR cascade activities as measured by Western blotting for total and phosphorylated Akt and mTOR. Rapamycin decreased the mTORC1 activity, while increasing the pAkt levels. Resveratrol did not interfere with the mTOR activity or with Sirt1 expression. Altogether, this work indicates that Sirt1 is a negative regulator of cell size. Moreover, the effect of Resv on cell size increase is mTOR-cascade dependent.
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Affiliation(s)
- Cihan S Erdogan
- Department of Science and Environment, Roskilde University, Roskilde, Denmark
| | | | - Louise T Dalgaard
- Department of Science and Environment, Roskilde University, Roskilde, Denmark
| | - Ole Vang
- Department of Science and Environment, Roskilde University, Roskilde, Denmark.
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Polouliakh N, Nock R. An Advanced Omic Approach to Identify Co-Regulated Clusters and Transcription Regulation Network with AGCT and SHOE Methods. Methods Mol Biol 2017; 1598:373-389. [PMID: 28508373 DOI: 10.1007/978-1-4939-6952-4_19] [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] [Indexed: 06/07/2023]
Abstract
To obtain the global picture of genetic machinery for massive high-throughput gene expression data, novel data-driven unsupervised learning approaches are becoming essentially important. For this purpose, basic analytic workflow has been established and should include two steps: first, unsupervised clustering to identify genes with similar behavior upon exposure to a signal, and second, identification of transcription factors regulating those genes. In this chapter, we will describe an advanced tool that can be used for analyzing and characterizing large-scale time-series gene expression composed of a two-step approach. For the first step, we developed an original method "A Geometric Clustering Tool" (AGCT) that unveils the complex architecture of large-scale time-series gene expression data in a real-time manner using cutting edge techniques of low dimension manifold learning, data clustering, and visualization. For the second step, we established an original method "Sequence Homology in Eukaryotes" (SHOE) executing comparative genomic analysis on humans, mice, and rats.
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Affiliation(s)
- Natalia Polouliakh
- Sony Computer Science Laboratories, Inc., 3-14-13 Hogashigotanda, Shinagawa-ku, Tokyo, 141-0022, Japan
- Department of Ophthalmology and Visual Sciences, Yokohama City University Graduate School of Medicine, 3-9 Fukuura, Kanazawa-ku, Yokohama, Japan
| | - Richard Nock
- Data61 & the Australian National University, Locked Bag 9013, Alexandria, NSW, 1435, Australia
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Pin E, Henjes F, Hong MG, Wiklund F, Magnusson P, Bjartell A, Uhlén M, Nilsson P, Schwenk JM. Identification of a Novel Autoimmune Peptide Epitope of Prostein in Prostate Cancer. J Proteome Res 2016; 16:204-216. [PMID: 27700103 DOI: 10.1021/acs.jproteome.6b00620] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
There is a demand for novel targets and approaches to diagnose and treat prostate cancer (PCA). In this context, serum and plasma samples from a total of 609 individuals from two independent patient cohorts were screened for IgG reactivity against a sum of 3833 human protein fragments. Starting from planar protein arrays with 3786 protein fragments to screen 80 patients with and without PCA diagnosis, 161 fragments (4%) were chosen for further analysis based on their reactivity profiles. Adding 71 antigens from literature, the selection of antigens was corroborated for their reactivity in a set of 550 samples using suspension bead arrays. The antigens prostein (SLC45A3), TATA-box binding protein (TBP), and insulin-like growth factor 2 mRNA binding protein 2 (IGF2BP2) showed higher reactivity in PCA patients with late disease compared with early disease. Because of its prostate tissue specificity, we focused on prostein and continued with mapping epitopes of the 66-mer protein fragment using patient samples. Using bead-based assays and 15-mer peptides, a minimal peptide epitope was identified and refined by alanine scanning to the KPxAPFP. Further sequence alignment of this motif revealed homology to transmembrane protein 79 (TMEM79) and TGF-beta-induced factor 2 (TGIF2), thus providing a reasoning for cross-reactivity found in females. A comprehensive workflow to discover and validate IgG reactivity against prostein and homologous targets in human serum and plasma was applied. This study provides useful information when searching for novel biomarkers or drug targets that are guided by the reactivity of the immune system against autoantigens.
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Affiliation(s)
- Elisa Pin
- Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH - Royal Institute of Technology , 171 65 Solna, Sweden
| | - Frauke Henjes
- Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH - Royal Institute of Technology , 171 65 Solna, Sweden
| | - Mun-Gwan Hong
- Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH - Royal Institute of Technology , 171 65 Solna, Sweden
| | - Fredrik Wiklund
- Department of Medical Epidemiology and Biostatistics (MEB), Karolinska Institutet , 171 77 Stockholm, Sweden
| | - Patrik Magnusson
- Department of Medical Epidemiology and Biostatistics (MEB), Karolinska Institutet , 171 77 Stockholm, Sweden
| | - Anders Bjartell
- Department of Translational Medicine, Division of Urological Cancers, Skåne University Hospital Malmö, Lund University , 205 02 Malmö, Sweden
| | - Mathias Uhlén
- Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH - Royal Institute of Technology , 171 65 Solna, Sweden
| | - Peter Nilsson
- Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH - Royal Institute of Technology , 171 65 Solna, Sweden
| | - Jochen M Schwenk
- Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH - Royal Institute of Technology , 171 65 Solna, Sweden
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