1
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Cortez Cardoso Penha R, Sexton Oates A, Senkin S, Park HA, Atkins J, Holcatova I, Hornakova A, Savic S, Ognjanovic S, Świątkowska B, Lissowska J, Zaridze D, Mukeria A, Janout V, Chabrier A, Cahais V, Cuenin C, Scelo G, Foll M, Herceg Z, Brennan P, Smith-Byrne K, Alcala N, Mckay JD. Understanding the biological processes of kidney carcinogenesis: an integrative multi-omics approach. Mol Syst Biol 2024; 20:1282-1302. [PMID: 39592856 PMCID: PMC11612429 DOI: 10.1038/s44320-024-00072-3] [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: 06/14/2024] [Revised: 10/10/2024] [Accepted: 10/21/2024] [Indexed: 11/28/2024] Open
Abstract
Biological mechanisms related to cancer development can leave distinct molecular fingerprints in tumours. By leveraging multi-omics and epidemiological information, we can unveil relationships between carcinogenesis processes that would otherwise remain hidden. Our integrative analysis of DNA methylome, transcriptome, and somatic mutation profiles of kidney tumours linked ageing, epithelial-mesenchymal transition (EMT), and xenobiotic metabolism to kidney carcinogenesis. Ageing process was represented by associations with cellular mitotic clocks such as epiTOC2, SBS1, telomere length, and PBRM1 and SETD2 mutations, which ticked faster as tumours progressed. We identified a relationship between BAP1 driver mutations and the epigenetic upregulation of EMT genes (IL20RB and WT1), correlating with increased tumour immune infiltration, advanced stage, and poorer patient survival. We also observed an interaction between epigenetic silencing of the xenobiotic metabolism gene GSTP1 and tobacco use, suggesting a link to genotoxic effects and impaired xenobiotic metabolism. Our pan-cancer analysis showed these relationships in other tumour types. Our study enhances the understanding of kidney carcinogenesis and its relation to risk factors and progression, with implications for other tumour types.
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Affiliation(s)
- Ricardo Cortez Cardoso Penha
- Genomic Epidemiology branch, International Agency for Research on Cancer/World Health Organization (IARC/WHO), Lyon, 69366, France
| | - Alexandra Sexton Oates
- Genomic Epidemiology branch, International Agency for Research on Cancer/World Health Organization (IARC/WHO), Lyon, 69366, France
| | - Sergey Senkin
- Genomic Epidemiology branch, International Agency for Research on Cancer/World Health Organization (IARC/WHO), Lyon, 69366, France
| | - Hanla A Park
- Genomic Epidemiology branch, International Agency for Research on Cancer/World Health Organization (IARC/WHO), Lyon, 69366, France
| | - Joshua Atkins
- Cancer Epidemiology Unit, University of Oxford, Oxford, Oxford, OX3 7LF, UK
| | - Ivana Holcatova
- Institute of Public Health & Preventive Medicine, Charles University, Prague, 15000, Czechia
| | - Anna Hornakova
- Institute of Hygiene and Epidemiology, Charles University, Prague, 12800, Czechia
| | - Slavisa Savic
- Department of Urology, Kliničko-Bolnički Centar Dr Dragiša Mišović, Belgrade, Serbia
| | - Simona Ognjanovic
- International Organization for Cancer Prevention and Research, Belgrade, 11070, Serbia
| | - Beata Świątkowska
- Department of Environmental Epidemiology, Nofer Institute of Occupational Medicine, Łódź, 90-950, Poland
| | - Jolanta Lissowska
- Maria Sklodowska-Curie National Research Institute of Oncology, Warszawa, 00-001, Poland
| | - David Zaridze
- N.N. Blokhin Cancer Research Center, Moscow, 115478, Russia
| | - Anush Mukeria
- N.N. Blokhin Cancer Research Center, Moscow, 115478, Russia
| | - Vladimir Janout
- Faculty of Health Sciences, Palacký University Olomouc, 77900, Olomouc, Czechia
| | - Amelie Chabrier
- Genomic Epidemiology branch, International Agency for Research on Cancer/World Health Organization (IARC/WHO), Lyon, 69366, France
| | - Vincent Cahais
- Epigenomics and Mechanisms Branch, International Agency for Research on Cancer/World Health Organization (IARC/WHO), Lyon, 69366, France
| | - Cyrille Cuenin
- Epigenomics and Mechanisms Branch, International Agency for Research on Cancer/World Health Organization (IARC/WHO), Lyon, 69366, France
| | - Ghislaine Scelo
- The Observational & Pragmatic Research Institute, Midview City, 573969, Singapore
| | - Matthieu Foll
- Genomic Epidemiology branch, International Agency for Research on Cancer/World Health Organization (IARC/WHO), Lyon, 69366, France
| | - Zdenko Herceg
- Epigenomics and Mechanisms Branch, International Agency for Research on Cancer/World Health Organization (IARC/WHO), Lyon, 69366, France
| | - Paul Brennan
- Genomic Epidemiology branch, International Agency for Research on Cancer/World Health Organization (IARC/WHO), Lyon, 69366, France
| | - Karl Smith-Byrne
- Cancer Epidemiology Unit, University of Oxford, Oxford, Oxford, OX3 7LF, UK
| | - Nicolas Alcala
- Genomic Epidemiology branch, International Agency for Research on Cancer/World Health Organization (IARC/WHO), Lyon, 69366, France
| | - James D Mckay
- Genomic Epidemiology branch, International Agency for Research on Cancer/World Health Organization (IARC/WHO), Lyon, 69366, France.
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2
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Damodaran AP, Gavard O, Gagné JP, Rogalska ME, Behera AK, Mancini E, Bertolin G, Courtheoux T, Kumari B, Cailloce J, Mereau A, Poirier GG, Valcárcel J, Gonatopoulos-Pournatzis T, Watrin E, Prigent C. Proteomic study identifies Aurora-A-mediated regulation of alternative splicing through multiple splicing factors. J Biol Chem 2024; 301:108000. [PMID: 39551136 DOI: 10.1016/j.jbc.2024.108000] [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: 09/28/2023] [Revised: 11/06/2024] [Accepted: 11/08/2024] [Indexed: 11/19/2024] Open
Abstract
The cell cycle regulator Aurora-A kinase presents an attractive target for cancer therapies, though its inhibition is also associated with toxic side effects. To gain a more nuanced understanding of Aurora-A function, we applied shotgun proteomics to identify 407 specific protein partners, including several splicing factors. Supporting a role in alternative splicing, we found that Aurora-A localizes to nuclear speckles, the storehouse of splicing proteins. Aurora-A interacts with and phosphorylates splicing factors both in vitro and in vivo, suggesting that it regulates alternative splicing by modulating the activity of these splicing factors. Consistently, Aurora-A inhibition significantly impacts the alternative splicing of 505 genes, with RNA motif analysis revealing an enrichment for Aurora-A interacting splicing factors. Additionally, we observed a significant positive correlation between the splicing events regulated by Aurora-A and those modulated by its interacting splicing factors. An interesting example is represented by CLK1 exon 4, which appears to be regulated by Aurora-A through SRSF3. Collectively, our findings highlight a broad role of Aurora-A in the regulation of alternative splicing.
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Affiliation(s)
- Arun Prasath Damodaran
- Univ Rennes, CNRS, Institut de Génétique et Développement de Rennes (IGDR) UMR6290, Équipe labellisée LNCC 2014, Rennes, France; RNA Biology Laboratory, Center for Cancer Research (CCR), National Cancer Institute (NCI), National Institutes of Health (NIH), Frederick, Maryland, USA.
| | - Olivia Gavard
- Univ Rennes, CNRS, Institut de Génétique et Développement de Rennes (IGDR) UMR6290, Équipe labellisée LNCC 2014, Rennes, France
| | - Jean-Philippe Gagné
- Department of Molecular Biology, Medical Biochemistry and Pathology, Laval University Cancer Research Center, Québec City, Quebec, Canada; CHU de Québec Research Center, CHUL Pavilion, Oncology Division, Québec City, Quebec, Canada
| | - Malgorzata Ewa Rogalska
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Amit K Behera
- RNA Biology Laboratory, Center for Cancer Research (CCR), National Cancer Institute (NCI), National Institutes of Health (NIH), Frederick, Maryland, USA
| | - Estefania Mancini
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Giulia Bertolin
- Univ Rennes, CNRS, Institut de Génétique et Développement de Rennes (IGDR) UMR6290, Équipe labellisée LNCC 2014, Rennes, France
| | - Thibault Courtheoux
- Univ Rennes, CNRS, Institut de Génétique et Développement de Rennes (IGDR) UMR6290, Équipe labellisée LNCC 2014, Rennes, France
| | - Bandana Kumari
- RNA Biology Laboratory, Center for Cancer Research (CCR), National Cancer Institute (NCI), National Institutes of Health (NIH), Frederick, Maryland, USA
| | - Justine Cailloce
- Univ Rennes, CNRS, Institut de Génétique et Développement de Rennes (IGDR) UMR6290, Équipe labellisée LNCC 2014, Rennes, France
| | - Agnès Mereau
- Univ Rennes, CNRS, Institut de Génétique et Développement de Rennes (IGDR) UMR6290, Équipe labellisée LNCC 2014, Rennes, France
| | - Guy G Poirier
- Department of Molecular Biology, Medical Biochemistry and Pathology, Laval University Cancer Research Center, Québec City, Quebec, Canada; CHU de Québec Research Center, CHUL Pavilion, Oncology Division, Québec City, Quebec, Canada
| | - Juan Valcárcel
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; Institut Catalá de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Thomas Gonatopoulos-Pournatzis
- RNA Biology Laboratory, Center for Cancer Research (CCR), National Cancer Institute (NCI), National Institutes of Health (NIH), Frederick, Maryland, USA.
| | - Erwan Watrin
- Univ Rennes, CNRS, Institut de Génétique et Développement de Rennes (IGDR) UMR6290, Équipe labellisée LNCC 2014, Rennes, France.
| | - Claude Prigent
- Univ Rennes, CNRS, Institut de Génétique et Développement de Rennes (IGDR) UMR6290, Équipe labellisée LNCC 2014, Rennes, France; Centre de Recherche de Biologie cellulaire de Montpellier (CRBM), University of Montpellier, CNRS, Montpellier, France.
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3
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Safieddine A, Benassy MN, Bonte T, Slimani F, Pourcelot O, Kress M, Ernoult-Lange M, Courel M, Coleno E, Imbert A, Laine A, Godebert AM, Vinit A, Blugeon C, Chevreux G, Gautheret D, Walter T, Bertrand E, Bénard M, Weil D. Cell-cycle-dependent mRNA localization in P-bodies. Mol Cell 2024; 84:4191-4208.e7. [PMID: 39368464 DOI: 10.1016/j.molcel.2024.09.011] [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: 12/04/2023] [Revised: 07/05/2024] [Accepted: 09/10/2024] [Indexed: 10/07/2024]
Abstract
Understanding the dynamics of RNA targeting to membraneless organelles is essential to disentangle their functions. Here, we investigate how P-bodies (PBs) evolve during cell-cycle progression in HEK293 cells. PB purification across the cell cycle uncovers widespread changes in their RNA content, partly uncoupled from cell-cycle-dependent changes in RNA expression. Single-molecule fluorescence in situ hybridization (FISH) shows various mRNA localization patterns in PBs peaking in G1, S, or G2, with examples illustrating the timely capture of mRNAs in PBs when their encoded protein becomes dispensable. Rather than directly reflecting absence of translation, cyclic mRNA localization in PBs can be controlled by RBPs, such as HuR in G2, and by RNA features. Indeed, while PB mRNAs are AU rich at all cell-cycle phases, they are specifically longer in G1, possibly related to post-mitotic PB reassembly. Altogether, our study supports a model where PBs are more than a default location for excess untranslated mRNAs.
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Affiliation(s)
- Adham Safieddine
- Sorbonne Université, CNRS, Institut de Biologie Paris Seine (IBPS), Laboratoire de Biologie du Développement, 75005 Paris, France.
| | - Marie-Noëlle Benassy
- Sorbonne Université, CNRS, Institut de Biologie Paris Seine (IBPS), Laboratoire de Biologie du Développement, 75005 Paris, France
| | - Thomas Bonte
- Centre for Computational Biology (CBIO), Mines Paris, PSL University, 75006 Paris, France; Institut Curie, PSL University, 75005 Paris, France; INSERM, U900, 75005 Paris, France
| | - Floric Slimani
- Institut de Génétique Humaine, University of Montpellier, CNRS, 34090 Montpellier, France
| | - Oriane Pourcelot
- Institut de Génétique Humaine, University of Montpellier, CNRS, 34090 Montpellier, France
| | - Michel Kress
- Sorbonne Université, CNRS, Institut de Biologie Paris Seine (IBPS), Laboratoire de Biologie du Développement, 75005 Paris, France
| | - Michèle Ernoult-Lange
- Sorbonne Université, CNRS, Institut de Biologie Paris Seine (IBPS), Laboratoire de Biologie du Développement, 75005 Paris, France
| | - Maïté Courel
- Sorbonne Université, CNRS, Institut de Biologie Paris Seine (IBPS), Laboratoire de Biologie du Développement, 75005 Paris, France
| | - Emeline Coleno
- Institut de Génétique Humaine, University of Montpellier, CNRS, 34090 Montpellier, France
| | - Arthur Imbert
- Centre for Computational Biology (CBIO), Mines Paris, PSL University, 75006 Paris, France
| | - Antoine Laine
- Institute for Integrative Biology of the Cell, UMR 9198, CEA, CNRS, Université Paris-Saclay, 91190 Gif-Sur-Yvette, France
| | - Annie Munier Godebert
- Research Center Saint-Antoine (CRSA), CISA Flow Cytometry Facility, UMRS 938, Sorbonne University, F-75012 Paris, France
| | - Angelique Vinit
- Research Center Saint-Antoine (CRSA), CISA Flow Cytometry Facility, UMRS 938, Sorbonne University, F-75012 Paris, France
| | - Corinne Blugeon
- GenomiqueENS, Institut de Biologie de l'ENS (IBENS), Département de biologie, École normale supérieure, CNRS, INSERM, Université PSL, 75005 Paris, France
| | - Guillaume Chevreux
- Université Paris Cité, CNRS, Institut Jacques Monod, 75013 Paris, France
| | - Daniel Gautheret
- Institute for Integrative Biology of the Cell, UMR 9198, CEA, CNRS, Université Paris-Saclay, 91190 Gif-Sur-Yvette, France
| | - Thomas Walter
- Centre for Computational Biology (CBIO), Mines Paris, PSL University, 75006 Paris, France; Institut Curie, PSL University, 75005 Paris, France; INSERM, U900, 75005 Paris, France
| | - Edouard Bertrand
- Institut de Génétique Humaine, University of Montpellier, CNRS, 34090 Montpellier, France
| | - Marianne Bénard
- Sorbonne Université, CNRS, Institut de Biologie Paris Seine (IBPS), Laboratoire de Biologie du Développement, 75005 Paris, France
| | - Dominique Weil
- Sorbonne Université, CNRS, Institut de Biologie Paris Seine (IBPS), Laboratoire de Biologie du Développement, 75005 Paris, France.
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4
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Liu H, Zhan L, Zhao J, Zhang S, Yin H, Hou Z, Huang G. Paper Spray Ionization Mass Spectrometry Coupled with Paper-Based Three-Dimensional Tumor Model for Rapid Metabolic Gradient Profiling. Anal Chem 2024; 96:16706-16714. [PMID: 39387545 DOI: 10.1021/acs.analchem.4c03007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2024]
Abstract
The tumor microenvironment (TME), especially with its complicated metabolic characteristics, will dynamically affect the proliferation, migration, and drug response of tumor cells. Rapid metabolic analysis brings out a deeper understanding of the TME, while the susceptibility and environmental dependence of metabolites extremely hinder real-time metabolic profiling since the TME is easily disrupted. Here, we directly integrated paper spray ionization mass spectrometry with a paper-based three-dimensional (3D) tumor model, realizing the rapid capture of metabolic gradients. The entire procedure, from sample preparation to mass spectrometry detection, took less than 4 min, which was able to provide metabolic results close to real time and contributed to understanding the real metabolic processes. At present, our method successfully detected 160 metabolites; notably, over 40 significantly gradient metabolites were revealed across the six layers of the paper-based 3D tumor model. At least 22 gradient metabolites were reported to be associated with cell viability. This strategy was powerful enough to rapidly profile metabolic gradients of a paper-based 3D tumor model for revealing cell viability changes from a metabolomics perspective.
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Affiliation(s)
- Huimin Liu
- Department of Cardiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230001, China
- Key Laboratory of Precision and Intelligent Chemistry, University of Science and Technology of China, Hefei, Anhui 230026, China
- School of Chemistry and Materials Science, University of Science and Technology of China, Hefei, Anhui 230001, China
| | - Liujuan Zhan
- Department of Cardiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230001, China
- Key Laboratory of Precision and Intelligent Chemistry, University of Science and Technology of China, Hefei, Anhui 230026, China
- School of Chemistry and Materials Science, University of Science and Technology of China, Hefei, Anhui 230001, China
| | - Jia Zhao
- Department of Cardiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230001, China
- Key Laboratory of Precision and Intelligent Chemistry, University of Science and Technology of China, Hefei, Anhui 230026, China
- School of Chemistry and Materials Science, University of Science and Technology of China, Hefei, Anhui 230001, China
| | - Shan Zhang
- Department of Cardiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230001, China
- Key Laboratory of Precision and Intelligent Chemistry, University of Science and Technology of China, Hefei, Anhui 230026, China
- School of Chemistry and Materials Science, University of Science and Technology of China, Hefei, Anhui 230001, China
| | - Hao Yin
- Instruments Center for Physical Science, University of Science and Technology of China, Hefei 230026, China
| | - Zhuanghao Hou
- Department of Cardiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230001, China
- Key Laboratory of Precision and Intelligent Chemistry, University of Science and Technology of China, Hefei, Anhui 230026, China
- School of Chemistry and Materials Science, University of Science and Technology of China, Hefei, Anhui 230001, China
| | - Guangming Huang
- Department of Cardiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230001, China
- Key Laboratory of Precision and Intelligent Chemistry, University of Science and Technology of China, Hefei, Anhui 230026, China
- School of Chemistry and Materials Science, University of Science and Technology of China, Hefei, Anhui 230001, China
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5
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Chen T, Zhang B, Xie H, Huang C, Wu Q. GRHL2 regulates keratinocyte EMT-MET dynamics and scar formation during cutaneous wound healing. Cell Death Dis 2024; 15:748. [PMID: 39402063 PMCID: PMC11473813 DOI: 10.1038/s41419-024-07121-7] [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: 05/01/2024] [Revised: 09/19/2024] [Accepted: 09/27/2024] [Indexed: 10/17/2024]
Abstract
After cutaneous wounds successfully heal, keratinocytes that underwent the epithelial-mesenchymal transition (EMT) regain their epithelial characteristics, while in scar tissue, epidermal cells persist in a mesenchymal state. However, the regulatory mechanisms governing this reversion are poorly understood, and the impact of persistent mesenchymal-like epidermal cells in scar tissue remains unclear. In the present study, we found that during wound healing, the regulatory factor GRHL2 is highly expressed in normal epidermal cells, downregulated in EMT epidermal cells, and upregulated again during the process of mesenchymal-epithelial transition (MET). We further demonstrated that interfering with GRHL2 expression in epidermal cells can effectively induce the EMT. Conversely, the overexpression of GRHL2 in EMT epidermal cells resulted in partial reversion of the EMT to an epithelial state. To investigate the effects of failed MET in epidermal cells on skin wound healing, we interfered with GRHL2 expression in epidermal cells surrounding the cutaneous wound. The results demonstrated that the persistence of epidermal cells in the mesenchymal state promoted fibrosis in scar tissue, manifested by increased thickness of scar tissue, deposition of collagen and fibronectin, as well as the activation of myofibroblasts. Furthermore, the miR-200s/Zeb1 axis was perturbed in GRHL2 knockdown keratinocytes, and transfection with miR-200s analogs promoted the reversion of EMT in epidermal cells, which indicates that they mediate the EMT process in keratinocytes. These results suggest that restoration of the epithelial state in epidermal cells following the EMT is essential to wound healing, providing potential therapeutic targets for preventing scar formation.
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Affiliation(s)
- Tianying Chen
- MOE Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China
| | - Bo Zhang
- MOE Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China
| | - Hanqi Xie
- MOE Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China
| | - Chenyu Huang
- Department of Dermatology, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, 102218, China.
| | - Qiong Wu
- MOE Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
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Pasello M, Laginestra MA, Manara MC, Landuzzi L, Ruzzi F, Maioli M, Pellegrini E, De Feo A, Lollini P, Scotlandi K. CD99 contributes to the EWS::FLI1 transcriptome by specifically affecting FOXM1-targets involved in the G2/M cell cycle phase, thus influencing the Ewing sarcoma genetic landscape. J Cell Commun Signal 2024; 18:e12047. [PMID: 39524141 PMCID: PMC11544636 DOI: 10.1002/ccs3.12047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Revised: 07/19/2024] [Accepted: 07/22/2024] [Indexed: 11/16/2024] Open
Abstract
Ewing sarcoma (EwS), a highly aggressive malignancy affecting children and young adults, is primarily driven by a distinctive oncogenic fusion, the EWSR1-ETS, whose activity is a key source of epigenetic and clinical heterogeneity. CD99 is constantly present in EwS cells, known to modulate the EwS genetic profile and tumor malignancy. However, the relevance of CD99 alone, or in association with EWSR1-ETS chimeras, is poorly understood. We explored the dynamic relationship between CD99 and EWS::FLI1, the main fusion observed in EwS, by means of model systems with inducible expression of either molecule. The transcriptomic dynamics of cells with or without expression of EWS::FLI1 or CD99 were analyzed and correlated with tumor cell growth. The CD99-associated EwS gene profile was found to have commonalities with the profile induced by EWS::FLI1, but also peculiar differences. Both EWS::FLI1 and CD99 are regulated targets of the DREAM complex, but the CD99 expression specifically impacted genes that are the targets of FOXM1 and are involved in the setting of the G2/M phase of the cell cycle. Most CD99-regulated FOXM1-targeted genes were found to correlate with bad prognosis in two public clinical datasets (R2 platform), further supporting the clinical relevance of CD99-mediated regulation of EwS gene expression.
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Affiliation(s)
- Michela Pasello
- Laboratory of Experimental OncologyIRCCS Istituto Ortopedico RizzoliBolognaItaly
| | | | | | - Lorena Landuzzi
- Laboratory of Experimental OncologyIRCCS Istituto Ortopedico RizzoliBolognaItaly
| | - Francesca Ruzzi
- Laboratory of Immunology and Biology of MetastasisDepartment of Medical and Surgical Sciences (DIMEC)University of BolognaBolognaItaly
| | - Margherita Maioli
- Department of PathologyIRCCS Istituto Ortopedico RizzoliBolognaItaly
| | - Evelin Pellegrini
- Laboratory of Experimental OncologyIRCCS Istituto Ortopedico RizzoliBolognaItaly
| | - Alessandra De Feo
- Laboratory of Experimental OncologyIRCCS Istituto Ortopedico RizzoliBolognaItaly
| | - Pier‐Luigi Lollini
- Laboratory of Immunology and Biology of MetastasisDepartment of Medical and Surgical Sciences (DIMEC)University of BolognaBolognaItaly
| | - Katia Scotlandi
- Laboratory of Experimental OncologyIRCCS Istituto Ortopedico RizzoliBolognaItaly
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7
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Wen C, Cao L, Wang S, Xu W, Yu Y, Zhao S, Yang F, Chen ZJ, Zhao S, Yang Y, Qin Y. MCM8 interacts with DDX5 to promote R-loop resolution. EMBO J 2024; 43:3044-3071. [PMID: 38858601 PMCID: PMC11251167 DOI: 10.1038/s44318-024-00134-0] [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: 08/12/2023] [Revised: 05/17/2024] [Accepted: 05/21/2024] [Indexed: 06/12/2024] Open
Abstract
MCM8 has emerged as a core gene in reproductive aging and is crucial for meiotic homologous recombination repair. It also safeguards genome stability by coordinating the replication stress response during mitosis, but its function in mitotic germ cells remains elusive. Here we found that disabling MCM8 in mice resulted in proliferation defects of primordial germ cells (PGCs) and ultimately impaired fertility. We further demonstrated that MCM8 interacted with two known helicases DDX5 and DHX9, and loss of MCM8 led to R-loop accumulation by reducing the retention of these helicases at R-loops, thus inducing genome instability. Cells expressing premature ovarian insufficiency-causative mutants of MCM8 with decreased interaction with DDX5 displayed increased R-loop levels. These results show MCM8 interacts with R-loop-resolving factors to prevent R-loop-induced DNA damage, which may contribute to the maintenance of genome integrity of PGCs and reproductive reserve establishment. Our findings thus reveal an essential role for MCM8 in PGC development and improve our understanding of reproductive aging caused by genome instability in mitotic germ cells.
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Affiliation(s)
- Canxin Wen
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Reproductive Medicine, Institute of Women, Children and Reproductive Health, Shandong University, Jinan, Shandong, 250012, China
- National Research Center for Assisted Reproductive Technology and Reproductive Genetics, Shandong University, Jinan, Shandong, 250012, China
- Key Laboratory of Reproductive Endocrinology (Shandong University), Ministry of Education, Jinan, Shandong, 250012, China
- Shandong Technology Innovation Center for Reproductive Health, Jinan, Shandong, 250012, China
- Shandong Provincial Clinical Research Center for Reproductive Health, Jinan, Shandong, 250012, China
- Shandong Key Laboratory of Reproductive Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250012, China
- Research Unit of Gametogenesis and Health of ART-Offspring, Chinese Academy of Medical Sciences (No.2021RU001), Jinan, Shandong, 250012, China
| | - Lili Cao
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Reproductive Medicine, Institute of Women, Children and Reproductive Health, Shandong University, Jinan, Shandong, 250012, China
- National Research Center for Assisted Reproductive Technology and Reproductive Genetics, Shandong University, Jinan, Shandong, 250012, China
- Key Laboratory of Reproductive Endocrinology (Shandong University), Ministry of Education, Jinan, Shandong, 250012, China
- Shandong Technology Innovation Center for Reproductive Health, Jinan, Shandong, 250012, China
- Shandong Provincial Clinical Research Center for Reproductive Health, Jinan, Shandong, 250012, China
- Shandong Key Laboratory of Reproductive Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250012, China
- Research Unit of Gametogenesis and Health of ART-Offspring, Chinese Academy of Medical Sciences (No.2021RU001), Jinan, Shandong, 250012, China
| | - Shuhan Wang
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Reproductive Medicine, Institute of Women, Children and Reproductive Health, Shandong University, Jinan, Shandong, 250012, China
- National Research Center for Assisted Reproductive Technology and Reproductive Genetics, Shandong University, Jinan, Shandong, 250012, China
- Key Laboratory of Reproductive Endocrinology (Shandong University), Ministry of Education, Jinan, Shandong, 250012, China
- Shandong Technology Innovation Center for Reproductive Health, Jinan, Shandong, 250012, China
- Shandong Provincial Clinical Research Center for Reproductive Health, Jinan, Shandong, 250012, China
- Shandong Key Laboratory of Reproductive Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250012, China
- Research Unit of Gametogenesis and Health of ART-Offspring, Chinese Academy of Medical Sciences (No.2021RU001), Jinan, Shandong, 250012, China
| | - Weiwei Xu
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Reproductive Medicine, Institute of Women, Children and Reproductive Health, Shandong University, Jinan, Shandong, 250012, China
- National Research Center for Assisted Reproductive Technology and Reproductive Genetics, Shandong University, Jinan, Shandong, 250012, China
- Key Laboratory of Reproductive Endocrinology (Shandong University), Ministry of Education, Jinan, Shandong, 250012, China
- Shandong Technology Innovation Center for Reproductive Health, Jinan, Shandong, 250012, China
- Shandong Provincial Clinical Research Center for Reproductive Health, Jinan, Shandong, 250012, China
- Shandong Key Laboratory of Reproductive Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250012, China
- Research Unit of Gametogenesis and Health of ART-Offspring, Chinese Academy of Medical Sciences (No.2021RU001), Jinan, Shandong, 250012, China
| | - Yongze Yu
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Reproductive Medicine, Institute of Women, Children and Reproductive Health, Shandong University, Jinan, Shandong, 250012, China
- National Research Center for Assisted Reproductive Technology and Reproductive Genetics, Shandong University, Jinan, Shandong, 250012, China
- Key Laboratory of Reproductive Endocrinology (Shandong University), Ministry of Education, Jinan, Shandong, 250012, China
- Shandong Technology Innovation Center for Reproductive Health, Jinan, Shandong, 250012, China
- Shandong Provincial Clinical Research Center for Reproductive Health, Jinan, Shandong, 250012, China
- Shandong Key Laboratory of Reproductive Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250012, China
- Research Unit of Gametogenesis and Health of ART-Offspring, Chinese Academy of Medical Sciences (No.2021RU001), Jinan, Shandong, 250012, China
| | - Simin Zhao
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Reproductive Medicine, Institute of Women, Children and Reproductive Health, Shandong University, Jinan, Shandong, 250012, China
- National Research Center for Assisted Reproductive Technology and Reproductive Genetics, Shandong University, Jinan, Shandong, 250012, China
- Key Laboratory of Reproductive Endocrinology (Shandong University), Ministry of Education, Jinan, Shandong, 250012, China
- Shandong Technology Innovation Center for Reproductive Health, Jinan, Shandong, 250012, China
- Shandong Provincial Clinical Research Center for Reproductive Health, Jinan, Shandong, 250012, China
- Shandong Key Laboratory of Reproductive Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250012, China
- Research Unit of Gametogenesis and Health of ART-Offspring, Chinese Academy of Medical Sciences (No.2021RU001), Jinan, Shandong, 250012, China
| | - Fan Yang
- Advanced Medical Research Institute, Meili Lake Translational Research Park, Cheeloo College of Medicine, Shandong University, Jinan, China
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Shandong University, Jinan, Shandong, 250012, China
| | - Zi-Jiang Chen
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Reproductive Medicine, Institute of Women, Children and Reproductive Health, Shandong University, Jinan, Shandong, 250012, China
- National Research Center for Assisted Reproductive Technology and Reproductive Genetics, Shandong University, Jinan, Shandong, 250012, China
- Key Laboratory of Reproductive Endocrinology (Shandong University), Ministry of Education, Jinan, Shandong, 250012, China
- Shandong Technology Innovation Center for Reproductive Health, Jinan, Shandong, 250012, China
- Shandong Provincial Clinical Research Center for Reproductive Health, Jinan, Shandong, 250012, China
- Shandong Key Laboratory of Reproductive Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250012, China
- Research Unit of Gametogenesis and Health of ART-Offspring, Chinese Academy of Medical Sciences (No.2021RU001), Jinan, Shandong, 250012, China
- Shanghai Key Laboratory for Assisted Reproduction and Reproductive Genetics, Shanghai, China
- Department of Reproductive Medicine, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shidou Zhao
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Reproductive Medicine, Institute of Women, Children and Reproductive Health, Shandong University, Jinan, Shandong, 250012, China.
- National Research Center for Assisted Reproductive Technology and Reproductive Genetics, Shandong University, Jinan, Shandong, 250012, China.
- Key Laboratory of Reproductive Endocrinology (Shandong University), Ministry of Education, Jinan, Shandong, 250012, China.
- Shandong Technology Innovation Center for Reproductive Health, Jinan, Shandong, 250012, China.
- Shandong Provincial Clinical Research Center for Reproductive Health, Jinan, Shandong, 250012, China.
- Shandong Key Laboratory of Reproductive Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250012, China.
- Research Unit of Gametogenesis and Health of ART-Offspring, Chinese Academy of Medical Sciences (No.2021RU001), Jinan, Shandong, 250012, China.
| | - Yajuan Yang
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Reproductive Medicine, Institute of Women, Children and Reproductive Health, Shandong University, Jinan, Shandong, 250012, China.
- National Research Center for Assisted Reproductive Technology and Reproductive Genetics, Shandong University, Jinan, Shandong, 250012, China.
- Key Laboratory of Reproductive Endocrinology (Shandong University), Ministry of Education, Jinan, Shandong, 250012, China.
- Shandong Technology Innovation Center for Reproductive Health, Jinan, Shandong, 250012, China.
- Shandong Provincial Clinical Research Center for Reproductive Health, Jinan, Shandong, 250012, China.
- Shandong Key Laboratory of Reproductive Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250012, China.
- Research Unit of Gametogenesis and Health of ART-Offspring, Chinese Academy of Medical Sciences (No.2021RU001), Jinan, Shandong, 250012, China.
| | - Yingying Qin
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Reproductive Medicine, Institute of Women, Children and Reproductive Health, Shandong University, Jinan, Shandong, 250012, China.
- National Research Center for Assisted Reproductive Technology and Reproductive Genetics, Shandong University, Jinan, Shandong, 250012, China.
- Key Laboratory of Reproductive Endocrinology (Shandong University), Ministry of Education, Jinan, Shandong, 250012, China.
- Shandong Technology Innovation Center for Reproductive Health, Jinan, Shandong, 250012, China.
- Shandong Provincial Clinical Research Center for Reproductive Health, Jinan, Shandong, 250012, China.
- Shandong Key Laboratory of Reproductive Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250012, China.
- Research Unit of Gametogenesis and Health of ART-Offspring, Chinese Academy of Medical Sciences (No.2021RU001), Jinan, Shandong, 250012, China.
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8
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Neyton LPA, Patel RK, Sarma A, Willmore A, Haller SC, Kangelaris KN, Eckalbar WL, Erle DJ, Krummel MF, Hendrickson CM, Woodruff PG, Langelier CR, Calfee CS, Fragiadakis GK. Distinct pulmonary and systemic effects of dexamethasone in severe COVID-19. Nat Commun 2024; 15:5483. [PMID: 38942804 PMCID: PMC11213873 DOI: 10.1038/s41467-024-49756-2] [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: 07/28/2023] [Accepted: 06/18/2024] [Indexed: 06/30/2024] Open
Abstract
Dexamethasone is the standard of care for critically ill patients with COVID-19, but the mechanisms by which it decreases mortality and its immunological effects in this setting are not understood. Here we perform bulk and single-cell RNA sequencing of samples from the lower respiratory tract and blood, and assess plasma cytokine profiling to study the effects of dexamethasone on both systemic and pulmonary immune cell compartments. In blood samples, dexamethasone is associated with decreased expression of genes associated with T cell activation, including TNFSFR4 and IL21R. We also identify decreased expression of several immune pathways, including major histocompatibility complex-II signaling, selectin P ligand signaling, and T cell recruitment by intercellular adhesion molecule and integrin activation, suggesting these are potential mechanisms of the therapeutic benefit of steroids in COVID-19. We identify additional compartment- and cell- specific differences in the effect of dexamethasone that are reproducible in publicly available datasets, including steroid-resistant interferon pathway expression in the respiratory tract, which may be additional therapeutic targets. In summary, we demonstrate compartment-specific effects of dexamethasone in critically ill COVID-19 patients, providing mechanistic insights with potential therapeutic relevance. Our results highlight the importance of studying compartmentalized inflammation in critically ill patients.
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Affiliation(s)
- Lucile P A Neyton
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, CA, USA
| | - Ravi K Patel
- UCSF CoLabs, University of California San Francisco, San Francisco, CA, USA
| | - Aartik Sarma
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, CA, USA
| | - Andrew Willmore
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, CA, USA
| | - Sidney C Haller
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, CA, USA
| | | | - Walter L Eckalbar
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, CA, USA
- UCSF CoLabs, University of California San Francisco, San Francisco, CA, USA
| | - David J Erle
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, CA, USA
- UCSF CoLabs, University of California San Francisco, San Francisco, CA, USA
- Department of Medicine, University of California, San Francisco, CA, USA
- Lung Biology Center, University of California, San Francisco, CA, USA
| | - Matthew F Krummel
- Department of Pathology, University of California, San Francisco, CA, USA
| | - Carolyn M Hendrickson
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, CA, USA
| | - Prescott G Woodruff
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, CA, USA
| | - Charles R Langelier
- Chan Zuckerberg Biohub, San Francisco, CA, USA
- Division of Infectious Diseases, University of California, San Francisco, CA, USA
| | - Carolyn S Calfee
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, CA, USA
- Department of Medicine, University of California, San Francisco, CA, USA
- Department of Anesthesia, University of California, San Francisco, CA, USA
| | - Gabriela K Fragiadakis
- UCSF CoLabs, University of California San Francisco, San Francisco, CA, USA.
- Division of Rheumatology, University of California, San Francisco, CA, USA.
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9
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Bush SJ, Nikola R, Han S, Suzuki S, Yoshida S, Simons BD, Goriely A. Adult Human, but Not Rodent, Spermatogonial Stem Cells Retain States with a Foetal-like Signature. Cells 2024; 13:742. [PMID: 38727278 PMCID: PMC11083513 DOI: 10.3390/cells13090742] [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: 03/19/2024] [Revised: 04/17/2024] [Accepted: 04/21/2024] [Indexed: 05/13/2024] Open
Abstract
Spermatogenesis involves a complex process of cellular differentiation maintained by spermatogonial stem cells (SSCs). Being critical to male reproduction, it is generally assumed that spermatogenesis starts and ends in equivalent transcriptional states in related species. Based on single-cell gene expression profiling, it has been proposed that undifferentiated human spermatogonia can be subclassified into four heterogenous subtypes, termed states 0, 0A, 0B, and 1. To increase the resolution of the undifferentiated compartment and trace the origin of the spermatogenic trajectory, we re-analysed the single-cell (sc) RNA-sequencing libraries of 34 post-pubescent human testes to generate an integrated atlas of germ cell differentiation. We then used this atlas to perform comparative analyses of the putative SSC transcriptome both across human development (using 28 foetal and pre-pubertal scRNA-seq libraries) and across species (including data from sheep, pig, buffalo, rhesus and cynomolgus macaque, rat, and mouse). Alongside its detailed characterisation, we show that the transcriptional heterogeneity of the undifferentiated spermatogonial cell compartment varies not only between species but across development. Our findings associate 'state 0B' with a suppressive transcriptomic programme that, in adult humans, acts to functionally oppose proliferation and maintain cells in a ready-to-react state. Consistent with this conclusion, we show that human foetal germ cells-which are mitotically arrested-can be characterised solely as state 0B. While germ cells with a state 0B signature are also present in foetal mice (and are likely conserved at this stage throughout mammals), they are not maintained into adulthood. We conjecture that in rodents, the foetal-like state 0B differentiates at birth into the renewing SSC population, whereas in humans it is maintained as a reserve population, supporting testicular homeostasis over a longer reproductive lifespan while reducing mutagenic load. Together, these results suggest that SSCs adopt differing evolutionary strategies across species to ensure fertility and genome integrity over vastly differing life histories and reproductive timeframes.
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Affiliation(s)
- Stephen J. Bush
- MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 9DS, UK
| | - Rafail Nikola
- MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 9DS, UK
| | - Seungmin Han
- Wellcome Trust/Cancer Research UK Gurdon Institute, University of Cambridge, Cambridge CB2 1QN, UK
| | - Shinnosuke Suzuki
- Division of Germ Cell Biology, National Institute for Basic Biology, National Institutes of Natural Sciences, 5-1 Higashiyama, Myodaiji, Okazaki 444-8787, Japan
- Graduate Institute for Advanced Studies, SOKENDAI, 5-1 Higashiyama, Myodaiji, Okazaki 444-8787, Japan
| | - Shosei Yoshida
- Division of Germ Cell Biology, National Institute for Basic Biology, National Institutes of Natural Sciences, 5-1 Higashiyama, Myodaiji, Okazaki 444-8787, Japan
- Graduate Institute for Advanced Studies, SOKENDAI, 5-1 Higashiyama, Myodaiji, Okazaki 444-8787, Japan
| | - Benjamin D. Simons
- Wellcome Trust/Cancer Research UK Gurdon Institute, University of Cambridge, Cambridge CB2 1QN, UK
- Wellcome—MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge CB2 0AW, UK
- Department of Applied Mathematics and Theoretical Physics, Centre for Mathematical Science, University of Cambridge, Cambridge CB3 0WA, UK
| | - Anne Goriely
- MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 9DS, UK
- NIHR Biomedical Research Centre, Oxford OX3 7JX, UK
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10
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He JY, Kim YJ, Mennillo E, Rusu I, Bain J, Rao AA, Andersen C, Law K, Yang H, Tsui J, Shen A, Davidson B, Kushnoor D, Shi Y, Fan F, Cheung A, Zhang L, Fong L, Combes AJ, Pisco AO, Kattah MG, Oh DY. Dysregulation of CD4 + and CD8 + resident memory T, myeloid, and stromal cells in steroid-experienced, checkpoint inhibitor colitis. J Immunother Cancer 2024; 12:e008628. [PMID: 38642938 PMCID: PMC11033653 DOI: 10.1136/jitc-2023-008628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/20/2024] [Indexed: 04/22/2024] Open
Abstract
BACKGROUND Colitis caused by checkpoint inhibitors (CPI) is frequent and is treated with empiric steroids, but CPI colitis mechanisms in steroid-experienced or refractory disease are unclear. METHODS Using colon biopsies and blood from predominantly steroid-experienced CPI colitis patients, we performed multiplexed single-cell transcriptomics and proteomics to nominate contributing populations. RESULTS CPI colitis biopsies showed enrichment of CD4+resident memory (RM) T cells in addition to CD8+ RM and cytotoxic CD8+ T cells. Matching T cell receptor (TCR) clonotypes suggested that both RMs are progenitors that yield cytotoxic effectors. Activated, CD38+ HLA-DR+ CD4+ RM and cytotoxic CD8+ T cells were enriched in steroid-experienced and a validation data set of steroid-naïve CPI colitis, underscoring their pathogenic potential across steroid exposure. Distinct from ulcerative colitis, CPI colitis exhibited perturbed stromal metabolism (NAD+, tryptophan) impacting epithelial survival and inflammation. Endothelial cells in CPI colitis after anti-TNF and anti-cytotoxic T-lymphocyte-associated antigen 4 (anti-CTLA-4) upregulated the integrin α4β7 ligand molecular vascular addressin cell adhesion molecule 1 (MAdCAM-1), which may preferentially respond to vedolizumab (anti-α4β7). CONCLUSIONS These findings nominate CD4+ RM and MAdCAM-1+ endothelial cells for targeting in specific subsets of CPI colitis patients.
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Affiliation(s)
- Jun Yan He
- Division of Hematology/Oncology, Department of Medicine, University of California, San Francisco, San Francisco, California, USA
| | - Yang-Joon Kim
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Elvira Mennillo
- Division of Gastroenterology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Iulia Rusu
- Division of Gastroenterology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Jared Bain
- Division of Gastroenterology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Arjun A Rao
- CoLabs, University of California, San Francisco, San Francisco, California, USA
| | | | - Karen Law
- Division of Hematology/Oncology, Department of Medicine, University of California, San Francisco, San Francisco, California, USA
| | - Hai Yang
- Division of Hematology/Oncology, Department of Medicine, University of California, San Francisco, San Francisco, California, USA
| | - Jessica Tsui
- CoLabs, University of California, San Francisco, San Francisco, California, USA
| | - Alan Shen
- CoLabs, University of California, San Francisco, San Francisco, California, USA
| | - Brittany Davidson
- CoLabs, University of California, San Francisco, San Francisco, California, USA
| | - Divyashree Kushnoor
- CoLabs, University of California, San Francisco, San Francisco, California, USA
| | - Yimin Shi
- Division of Hematology/Oncology, Department of Medicine, University of California, San Francisco, San Francisco, California, USA
| | - Frances Fan
- Division of Hematology/Oncology, Department of Medicine, University of California, San Francisco, San Francisco, California, USA
| | - Alexander Cheung
- Division of Hematology/Oncology, Department of Medicine, University of California, San Francisco, San Francisco, California, USA
| | - Li Zhang
- Division of Hematology/Oncology, Department of Medicine, University of California, San Francisco, San Francisco, California, USA
| | - Lawrence Fong
- Division of Hematology/Oncology, Department of Medicine, University of California, San Francisco, San Francisco, California, USA
| | - Alexis J Combes
- Division of Gastroenterology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- CoLabs, University of California, San Francisco, San Francisco, California, USA
- Department of Pathology, University of California, San Francisco, San Francisco, California, USA
- ImmunoX Initiative, University of California, San Francisco, San Francisco, California, USA
| | | | - Michael G Kattah
- Division of Gastroenterology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - David Y Oh
- Division of Hematology/Oncology, Department of Medicine, University of California, San Francisco, San Francisco, California, USA
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11
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Zhou Y, Panhale A, Shvedunova M, Balan M, Gomez-Auli A, Holz H, Seyfferth J, Helmstädter M, Kayser S, Zhao Y, Erdogdu NU, Grzadzielewska I, Mittler G, Manke T, Akhtar A. RNA damage compartmentalization by DHX9 stress granules. Cell 2024; 187:1701-1718.e28. [PMID: 38503283 DOI: 10.1016/j.cell.2024.02.028] [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: 07/05/2023] [Revised: 10/24/2023] [Accepted: 02/22/2024] [Indexed: 03/21/2024]
Abstract
Biomolecules incur damage during stress conditions, and damage partitioning represents a vital survival strategy for cells. Here, we identified a distinct stress granule (SG), marked by dsRNA helicase DHX9, which compartmentalizes ultraviolet (UV)-induced RNA, but not DNA, damage. Our FANCI technology revealed that DHX9 SGs are enriched in damaged intron RNA, in contrast to classical SGs that are composed of mature mRNA. UV exposure causes RNA crosslinking damage, impedes intron splicing and decay, and triggers DHX9 SGs within daughter cells. DHX9 SGs promote cell survival and induce dsRNA-related immune response and translation shutdown, differentiating them from classical SGs that assemble downstream of translation arrest. DHX9 modulates dsRNA abundance in the DHX9 SGs and promotes cell viability. Autophagy receptor p62 is activated and important for DHX9 SG disassembly. Our findings establish non-canonical DHX9 SGs as a dedicated non-membrane-bound cytoplasmic compartment that safeguards daughter cells from parental RNA damage.
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Affiliation(s)
- Yilong Zhou
- Max Planck Institute of Immunobiology and Epigenetics, Freiburg, Germany
| | - Amol Panhale
- Max Planck Institute of Immunobiology and Epigenetics, Freiburg, Germany
| | - Maria Shvedunova
- Max Planck Institute of Immunobiology and Epigenetics, Freiburg, Germany
| | - Mirela Balan
- Max Planck Institute of Immunobiology and Epigenetics, Freiburg, Germany
| | | | - Herbert Holz
- Max Planck Institute of Immunobiology and Epigenetics, Freiburg, Germany
| | - Janine Seyfferth
- Max Planck Institute of Immunobiology and Epigenetics, Freiburg, Germany
| | - Martin Helmstädter
- EMcore, Renal Division, Department of Medicine, University Freiburg, Hospital Freiburg, University Faculty of Medicine, Freiburg, Germany
| | - Séverine Kayser
- EMcore, Renal Division, Department of Medicine, University Freiburg, Hospital Freiburg, University Faculty of Medicine, Freiburg, Germany
| | - Yuling Zhao
- Max Planck Institute of Immunobiology and Epigenetics, Freiburg, Germany; Faculty of Biology, University of Freiburg, Freiburg, Germany; International Max Planck Research School for Molecular and Cellular Biology (IMPRS-MCB), Freiburg, Germany
| | - Niyazi Umut Erdogdu
- Max Planck Institute of Immunobiology and Epigenetics, Freiburg, Germany; Faculty of Biology, University of Freiburg, Freiburg, Germany; International Max Planck Research School for Molecular and Cellular Biology (IMPRS-MCB), Freiburg, Germany
| | - Iga Grzadzielewska
- Max Planck Institute of Immunobiology and Epigenetics, Freiburg, Germany; Faculty of Biology, University of Freiburg, Freiburg, Germany; International Max Planck Research School for Molecular and Cellular Biology (IMPRS-MCB), Freiburg, Germany
| | - Gerhard Mittler
- Max Planck Institute of Immunobiology and Epigenetics, Freiburg, Germany
| | - Thomas Manke
- Max Planck Institute of Immunobiology and Epigenetics, Freiburg, Germany
| | - Asifa Akhtar
- Max Planck Institute of Immunobiology and Epigenetics, Freiburg, Germany.
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12
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Litsios A, Grys BT, Kraus OZ, Friesen H, Ross C, Masinas MPD, Forster DT, Couvillion MT, Timmermann S, Billmann M, Myers C, Johnsson N, Churchman LS, Boone C, Andrews BJ. Proteome-scale movements and compartment connectivity during the eukaryotic cell cycle. Cell 2024; 187:1490-1507.e21. [PMID: 38452761 PMCID: PMC10947830 DOI: 10.1016/j.cell.2024.02.014] [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: 09/12/2023] [Revised: 12/01/2023] [Accepted: 02/12/2024] [Indexed: 03/09/2024]
Abstract
Cell cycle progression relies on coordinated changes in the composition and subcellular localization of the proteome. By applying two distinct convolutional neural networks on images of millions of live yeast cells, we resolved proteome-level dynamics in both concentration and localization during the cell cycle, with resolution of ∼20 subcellular localization classes. We show that a quarter of the proteome displays cell cycle periodicity, with proteins tending to be controlled either at the level of localization or concentration, but not both. Distinct levels of protein regulation are preferentially utilized for different aspects of the cell cycle, with changes in protein concentration being mostly involved in cell cycle control and changes in protein localization in the biophysical implementation of the cell cycle program. We present a resource for exploring global proteome dynamics during the cell cycle, which will aid in understanding a fundamental biological process at a systems level.
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Affiliation(s)
- Athanasios Litsios
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON M5S 3E1, Canada
| | - Benjamin T Grys
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON M5S 3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Oren Z Kraus
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON M5S 3E1, Canada; Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON M5S 3G4, Canada
| | - Helena Friesen
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON M5S 3E1, Canada
| | - Catherine Ross
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON M5S 3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Myra Paz David Masinas
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON M5S 3E1, Canada
| | - Duncan T Forster
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON M5S 3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Mary T Couvillion
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Stefanie Timmermann
- Institute of Molecular Genetics and Cell Biology, Department of Biology, Ulm University, Ulm 89081, Germany
| | - Maximilian Billmann
- Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN 55455, USA; Institute of Human Genetics, University of Bonn, School of Medicine and University Hospital Bonn, Bonn, Germany
| | - Chad Myers
- Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN 55455, USA
| | - Nils Johnsson
- Institute of Molecular Genetics and Cell Biology, Department of Biology, Ulm University, Ulm 89081, Germany
| | | | - Charles Boone
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON M5S 3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada; RIKEN Center for Sustainable Resource Science, Wako 351-0198 Saitama, Japan.
| | - Brenda J Andrews
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON M5S 3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada.
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13
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Dolfini D, Gnesutta N, Mantovani R. Expression and function of NF-Y subunits in cancer. Biochim Biophys Acta Rev Cancer 2024; 1879:189082. [PMID: 38309445 DOI: 10.1016/j.bbcan.2024.189082] [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: 11/13/2023] [Revised: 01/29/2024] [Accepted: 01/31/2024] [Indexed: 02/05/2024]
Abstract
NF-Y is a Transcription Factor (TF) targeting the CCAAT box regulatory element. It consists of the NF-YB/NF-YC heterodimer, each containing an Histone Fold Domain (HFD), and the sequence-specific subunit NF-YA. NF-YA expression is associated with cell proliferation and absent in some post-mitotic cells. The review summarizes recent findings impacting on cancer development. The logic of the NF-Y regulome points to pro-growth, oncogenic genes in the cell-cycle, metabolism and transcriptional regulation routes. NF-YA is involved in growth/differentiation decisions upon cell-cycle re-entry after mitosis and it is widely overexpressed in tumors, the HFD subunits in some tumor types or subtypes. Overexpression of NF-Y -mostly NF-YA- is oncogenic and decreases sensitivity to anti-neoplastic drugs. The specific roles of NF-YA and NF-YC isoforms generated by alternative splicing -AS- are discussed, including the prognostic value of their levels, although the specific molecular mechanisms of activity are still to be deciphered.
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Affiliation(s)
- Diletta Dolfini
- Dipartimento di Bioscienze, Università degli Studi di Milano, Via Celoria 26, Milano 20133, Italy
| | - Nerina Gnesutta
- Dipartimento di Bioscienze, Università degli Studi di Milano, Via Celoria 26, Milano 20133, Italy
| | - Roberto Mantovani
- Dipartimento di Bioscienze, Università degli Studi di Milano, Via Celoria 26, Milano 20133, Italy.
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14
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Mennillo E, Kim YJ, Lee G, Rusu I, Patel RK, Dorman LC, Flynn E, Li S, Bain JL, Andersen C, Rao A, Tamaki S, Tsui J, Shen A, Lotstein ML, Rahim M, Naser M, Bernard-Vazquez F, Eckalbar W, Cho SJ, Beck K, El-Nachef N, Lewin S, Selvig DR, Terdiman JP, Mahadevan U, Oh DY, Fragiadakis GK, Pisco A, Combes AJ, Kattah MG. Single-cell and spatial multi-omics highlight effects of anti-integrin therapy across cellular compartments in ulcerative colitis. Nat Commun 2024; 15:1493. [PMID: 38374043 PMCID: PMC10876948 DOI: 10.1038/s41467-024-45665-6] [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: 01/21/2023] [Accepted: 01/30/2024] [Indexed: 02/21/2024] Open
Abstract
Ulcerative colitis (UC) is driven by immune and stromal subsets, culminating in epithelial injury. Vedolizumab (VDZ) is an anti-integrin antibody that is effective for treating UC. VDZ is known to inhibit lymphocyte trafficking to the intestine, but its broader effects on other cell subsets are less defined. To identify the inflammatory cells that contribute to colitis and are affected by VDZ, we perform single-cell transcriptomic and proteomic analyses of peripheral blood and colonic biopsies in healthy controls and patients with UC on VDZ or other therapies. Here we show that VDZ treatment is associated with alterations in circulating and tissue mononuclear phagocyte (MNP) subsets, along with modest shifts in lymphocytes. Spatial multi-omics of formalin-fixed biopsies demonstrates trends towards increased abundance and proximity of MNP and fibroblast subsets in active colitis. Spatial transcriptomics of archived specimens pre-treatment identifies epithelial-, MNP-, and fibroblast-enriched genes related to VDZ responsiveness, highlighting important roles for these subsets in UC.
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Affiliation(s)
- Elvira Mennillo
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | | | - Gyehyun Lee
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Iulia Rusu
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Ravi K Patel
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
- CoLabs, University of California San Francisco, San Francisco, CA, USA
| | | | - Emily Flynn
- CoLabs, University of California San Francisco, San Francisco, CA, USA
| | - Stephanie Li
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Jared L Bain
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Christopher Andersen
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
- CoLabs, University of California San Francisco, San Francisco, CA, USA
| | - Arjun Rao
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
- CoLabs, University of California San Francisco, San Francisco, CA, USA
| | - Stanley Tamaki
- CoLabs, University of California San Francisco, San Francisco, CA, USA
| | - Jessica Tsui
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
- CoLabs, University of California San Francisco, San Francisco, CA, USA
- Department of Pathology, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Alan Shen
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
- CoLabs, University of California San Francisco, San Francisco, CA, USA
- Department of Pathology, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Madison L Lotstein
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
- CoLabs, University of California San Francisco, San Francisco, CA, USA
| | - Maha Rahim
- Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Mohammad Naser
- Biological Imaging Development CoLab, University of California San Francisco, San Francisco, CA, USA
| | | | - Walter Eckalbar
- CoLabs, University of California San Francisco, San Francisco, CA, USA
| | - Soo-Jin Cho
- Department of Pathology, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Kendall Beck
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Najwa El-Nachef
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Sara Lewin
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Daniel R Selvig
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Jonathan P Terdiman
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Uma Mahadevan
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - David Y Oh
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
- Division of Hematology/Oncology, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Gabriela K Fragiadakis
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
- CoLabs, University of California San Francisco, San Francisco, CA, USA
| | | | - Alexis J Combes
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
- CoLabs, University of California San Francisco, San Francisco, CA, USA
- Department of Pathology, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Michael G Kattah
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA.
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15
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Mennillo E, Kim YJ, Lee G, Rusu I, Patel RK, Dorman LC, Flynn E, Li S, Bain JL, Andersen C, Rao A, Tamaki S, Tsui J, Shen A, Lotstein ML, Rahim M, Naser M, Bernard-Vazquez F, Eckalbar W, Cho SJ, Beck K, El-Nachef N, Lewin S, Selvig DR, Terdiman JP, Mahadevan U, Oh DY, Fragiadakis GK, Pisco A, Combes AJ, Kattah MG. Single-cell and spatial multi-omics highlight effects of anti-integrin therapy across cellular compartments in ulcerative colitis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.01.21.525036. [PMID: 36711576 PMCID: PMC9882264 DOI: 10.1101/2023.01.21.525036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
Ulcerative colitis (UC) is driven by immune and stromal subsets, culminating in epithelial injury. Vedolizumab (VDZ) is an anti-integrin antibody that is effective for treating UC. VDZ is known to inhibit lymphocyte trafficking to the intestine, but its broader effects on other cell subsets are less defined. To identify the inflammatory cells that contribute to colitis and are affected by VDZ, we performed single-cell transcriptomic and proteomic analyses of peripheral blood and colonic biopsies in healthy controls and patients with UC on VDZ or other therapies. Here we show that VDZ treatment is associated with alterations in circulating and tissue mononuclear phagocyte (MNP) subsets, along with modest shifts in lymphocytes. Spatial multi-omics of formalin-fixed biopsies demonstrates trends towards increased abundance and proximity of MNP and fibroblast subsets in active colitis. Spatial transcriptomics of archived specimens pre-treatment identifies epithelial-, MNP-, and fibroblast-enriched genes related to VDZ responsiveness, highlighting important roles for these subsets in UC.
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16
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Brennan K, Espín-Pérez A, Chang S, Bedi N, Saumyaa S, Shin JH, Plevritis SK, Gevaert O, Sunwoo JB, Gentles AJ. Loss of p53-DREAM-mediated repression of cell cycle genes as a driver of lymph node metastasis in head and neck cancer. Genome Med 2023; 15:98. [PMID: 37978395 PMCID: PMC10656821 DOI: 10.1186/s13073-023-01236-w] [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: 01/14/2023] [Accepted: 09/20/2023] [Indexed: 11/19/2023] Open
Abstract
BACKGROUND The prognosis for patients with head and neck cancer (HNC) is poor and has improved little in recent decades, partially due to lack of therapeutic options. To identify effective therapeutic targets, we sought to identify molecular pathways that drive metastasis and HNC progression, through large-scale systematic analyses of transcriptomic data. METHODS We performed meta-analysis across 29 gene expression studies including 2074 primary HNC biopsies to identify genes and transcriptional pathways associated with survival and lymph node metastasis (LNM). To understand the biological roles of these genes in HNC, we identified their associated cancer pathways, as well as the cell types that express them within HNC tumor microenvironments, by integrating single-cell RNA-seq and bulk RNA-seq from sorted cell populations. RESULTS Patient survival-associated genes were heterogenous and included drivers of diverse tumor biological processes: these included tumor-intrinsic processes such as epithelial dedifferentiation and epithelial to mesenchymal transition, as well as tumor microenvironmental factors such as T cell-mediated immunity and cancer-associated fibroblast activity. Unexpectedly, LNM-associated genes were almost universally associated with epithelial dedifferentiation within malignant cells. Genes negatively associated with LNM consisted of regulators of squamous epithelial differentiation that are expressed within well-differentiated malignant cells, while those positively associated with LNM represented cell cycle regulators that are normally repressed by the p53-DREAM pathway. These pro-LNM genes are overexpressed in proliferating malignant cells of TP53 mutated and HPV + ve HNCs and are strongly associated with stemness, suggesting that they represent markers of pre-metastatic cancer stem-like cells. LNM-associated genes are deregulated in high-grade oral precancerous lesions, and deregulated further in primary HNCs with advancing tumor grade and deregulated further still in lymph node metastases. CONCLUSIONS In HNC, patient survival is affected by multiple biological processes and is strongly influenced by the tumor immune and stromal microenvironments. In contrast, LNM appears to be driven primarily by malignant cell plasticity, characterized by epithelial dedifferentiation coupled with EMT-independent proliferation and stemness. Our findings postulate that LNM is initially caused by loss of p53-DREAM-mediated repression of cell cycle genes during early tumorigenesis.
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Affiliation(s)
- Kevin Brennan
- Stanford Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, CA, USA.
| | - Almudena Espín-Pérez
- Stanford Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, CA, USA
| | - Serena Chang
- Department of Otolaryngology - Head and Neck Surgery, Stanford University School of Medicine, Stanford, USA
| | - Nikita Bedi
- Department of Otolaryngology - Head and Neck Surgery, Stanford University School of Medicine, Stanford, USA
| | - Saumyaa Saumyaa
- Department of Otolaryngology - Head and Neck Surgery, Stanford University School of Medicine, Stanford, USA
| | - June Ho Shin
- Department of Otolaryngology - Head and Neck Surgery, Stanford University School of Medicine, Stanford, USA
| | - Sylvia K Plevritis
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Olivier Gevaert
- Stanford Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - John B Sunwoo
- Department of Otolaryngology - Head and Neck Surgery, Stanford University School of Medicine, Stanford, USA
| | - Andrew J Gentles
- Stanford Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, CA, USA.
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.
- Department of Pathology, Stanford University, Stanford, CA, USA.
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17
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Liu BW, Sun N, Lin H, Zhou XJ, Ma HY, Wang X, Cao XC, Yu Y. The p53/ZEB1-PLD3 feedback loop regulates cell proliferation in breast cancer. Cell Death Dis 2023; 14:751. [PMID: 37978168 PMCID: PMC10656518 DOI: 10.1038/s41419-023-06271-4] [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: 01/31/2023] [Revised: 10/26/2023] [Accepted: 11/03/2023] [Indexed: 11/19/2023]
Abstract
Breast cancer is the most prevalent cancer globally, endangering women's physical and mental health. Phospholipase D3 (PLD3) belongs to the phosphodiesterase family (PLD). PLD3 is related to insulin-mediated phosphorylation of the AKT pathway, suggesting that it may play a role in the occurrence and development of malignant tumors. This study may further explore the molecular mechanism of PLD3 inhibiting breast cancer cell proliferation. In this study, we demonstrated that PLD3 and miR-6796 are co-expressed in breast cancer. PLD3 can bind with CDK1 and inhibit its expression, leading to mitotic arrest and inhibiting breast cancer proliferation. Wild-type p53 regulates PLD3 and miR-6796 expression by competitively binding to the PLD3 promoter with ZEB1. DNMT3B, as the target gene of miR-6796, is recruited into the PLD3 promoter by combining with ZEB1 to regulate the DNA methylation of the PLD3 promoter and ultimately affect PLD3 and miR-6796 expression. In conclusion, we revealed the role and molecular mechanism of PLD3 and its embedded miR-6796 in breast cancer proliferation, providing clues and a theoretical foundation for future research and development of therapeutic targets and prognostic markers for breast cancer.
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Affiliation(s)
- Bo-Wen Liu
- The First Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, 300060, China
- Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Tianjin, 300060, China
- Key Laboratory of Cancer Prevention and Therapy, Tianjin, 300060, China
- Tianjin's Clinical Research Center for Cancer, Tianjin, 300060, China
| | - Ning Sun
- The First Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, 300060, China
- Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Tianjin, 300060, China
- Key Laboratory of Cancer Prevention and Therapy, Tianjin, 300060, China
- Tianjin's Clinical Research Center for Cancer, Tianjin, 300060, China
- Department of Thyroid and Breast Surgery, The Second Hospital of Tianjin Medical University, Tianjin, 300211, China
| | - Hui Lin
- The First Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, 300060, China
- Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Tianjin, 300060, China
- Key Laboratory of Cancer Prevention and Therapy, Tianjin, 300060, China
- Tianjin's Clinical Research Center for Cancer, Tianjin, 300060, China
- Department of Surgical Oncology, Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Wenzhou, Zhejiang, 317099, China
| | - Xue-Jie Zhou
- The First Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, 300060, China
- Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Tianjin, 300060, China
- Key Laboratory of Cancer Prevention and Therapy, Tianjin, 300060, China
- Tianjin's Clinical Research Center for Cancer, Tianjin, 300060, China
| | - Hai-Yan Ma
- The First Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, 300060, China
- Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Tianjin, 300060, China
- Key Laboratory of Cancer Prevention and Therapy, Tianjin, 300060, China
- Tianjin's Clinical Research Center for Cancer, Tianjin, 300060, China
| | - Xin Wang
- The First Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, 300060, China
- Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Tianjin, 300060, China
- Key Laboratory of Cancer Prevention and Therapy, Tianjin, 300060, China
- Tianjin's Clinical Research Center for Cancer, Tianjin, 300060, China
| | - Xu-Chen Cao
- The First Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, 300060, China.
- Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Tianjin, 300060, China.
- Key Laboratory of Cancer Prevention and Therapy, Tianjin, 300060, China.
- Tianjin's Clinical Research Center for Cancer, Tianjin, 300060, China.
| | - Yue Yu
- The First Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, 300060, China.
- Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Tianjin, 300060, China.
- Key Laboratory of Cancer Prevention and Therapy, Tianjin, 300060, China.
- Tianjin's Clinical Research Center for Cancer, Tianjin, 300060, China.
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18
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Li K, Xu K, Liu S, He Y, Tan M, Mao Y, Yang Y, Wu J, Feng Q, Luo Z, Cai K. All-in-One Engineering Multifunctional Nanoplatforms for Sensitizing Tumor Low-Temperature Photothermal Therapy In Vivo. ACS NANO 2023; 17:20218-20236. [PMID: 37838975 DOI: 10.1021/acsnano.3c05991] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/17/2023]
Abstract
Low-temperature photothermal therapy (PTT) is a noninvasive method that harnesses the photothermal effect at low temperatures to selectively eliminate tumor cells, while safeguarding normal tissues, minimizing thermal damage, and enhancing treatment safety. First we evaluated the transcriptome of tumor cells at the gene level following low-temperature treatment and observed significant enrichment of genes involved in cell cycle and heat response-related signaling pathways. To address this challenge, we have developed an engineering multifunctional nanoplatform that offered an all-in-one strategy for efficient sensitization of low-temperature PTT. Specifically, we utilized MoS2 nanoparticles as the photothermal core to generate low temperature (40-48 °C). The nanoplatform was coated with DPA to load CPT-11 and Fe2+ and was further modified with PEG and iRGD to enhance tumor specificity (MoS2/Fe@CPT-11-PEG-iRGD). Laser- and acid-triggered release of CPT-11 can significantly increase intracellular H2O2 content, cooperate with Fe2+ ions to increase intracellular lipid ROS content, and activate ferroptosis. Furthermore, CPT-11 induced cell cycle arrest in the temperature-sensitive S-phase, and increased lipid ROS levels contributed to the degradation of HSPs protein expression. This synergistic approach could effectively induce tumor cell death by the sensitized low-temperature PTT and the combination of ferroptosis and chemotherapy. Our nanoplatform can also maximize tumor cell eradication and prolong the survival time of tumor-bearing mice in vivo. The multifunctional approach will provide more possibilities for clinical applications of low-temperature PTT and potential avenues for the development of multiple tumor treatments.
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Affiliation(s)
- Ke Li
- Key Laboratory of Biorheological Science and Technology, Ministry of Education College of Bioengineering, Chongqing University, Chongqing 400044, P. R. China
- Thomas Lord Department of Mechanical Engineering and Materials Science, Duke University, Durham, North Carolina 27708, United States
| | - Kun Xu
- Key Laboratory of Biorheological Science and Technology, Ministry of Education College of Bioengineering, Chongqing University, Chongqing 400044, P. R. China
| | - Shaopeng Liu
- Key Laboratory of Biorheological Science and Technology, Ministry of Education College of Bioengineering, Chongqing University, Chongqing 400044, P. R. China
| | - Ye He
- Thomas Lord Department of Mechanical Engineering and Materials Science, Duke University, Durham, North Carolina 27708, United States
| | - Meijun Tan
- Key Laboratory of Biorheological Science and Technology, Ministry of Education College of Bioengineering, Chongqing University, Chongqing 400044, P. R. China
| | - Yulan Mao
- Key Laboratory of Biorheological Science and Technology, Ministry of Education College of Bioengineering, Chongqing University, Chongqing 400044, P. R. China
| | - Yulu Yang
- Key Laboratory of Biorheological Science and Technology, Ministry of Education College of Bioengineering, Chongqing University, Chongqing 400044, P. R. China
| | - Jing Wu
- Key Laboratory of Biorheological Science and Technology, Ministry of Education College of Bioengineering, Chongqing University, Chongqing 400044, P. R. China
| | - Qian Feng
- Key Laboratory of Biorheological Science and Technology, Ministry of Education College of Bioengineering, Chongqing University, Chongqing 400044, P. R. China
| | - Zhong Luo
- School of Life Science, Chongqing University, Chongqing 400044, P. R. China
| | - Kaiyong Cai
- Key Laboratory of Biorheological Science and Technology, Ministry of Education College of Bioengineering, Chongqing University, Chongqing 400044, P. R. China
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19
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Sarén T, Ramachandran M, Gammelgård G, Lövgren T, Mirabello C, Björklund ÅK, Wikström K, Hashemi J, Freyhult E, Ahlström H, Amini RM, Hagberg H, Loskog A, Enblad G, Essand M. Single-Cell RNA Analysis Reveals Cell-Intrinsic Functions of CAR T Cells Correlating with Response in a Phase II Study of Lymphoma Patients. Clin Cancer Res 2023; 29:4139-4152. [PMID: 37540566 PMCID: PMC10570681 DOI: 10.1158/1078-0432.ccr-23-0178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 06/22/2023] [Accepted: 08/02/2023] [Indexed: 08/06/2023]
Abstract
PURPOSE Although CD19 chimeric antigen receptor T cells (CAR-T) therapy has shown remarkable success in B-cell malignancies, a substantial fraction of patients do not obtain a long-term clinical response. This could be influenced by the quality of the individual CAR-T infusion product. To shed some light on this, clinical outcome was correlated to characteristics of CAR-T infusion products. PATIENTS AND METHODS In this phase II study, patients with B-cell lymphoma (n = 23) or leukemia (n = 1) received one or two infusions of third-generation CD19-directed CAR-Ts (2 × 108/m2). The clinical trial was registered at clinicaltrials.gov: NCT03068416. We investigated the transcriptional profile of individual CD19 CAR-T infusion products using targeted single-cell RNA sequencing and multicolor flow cytometry. RESULTS Two CAR-T infusions were not better than one in the settings used in this study. As for the CAR-T infusion products, we found that effector-like CD8+CAR-Ts with a high polyfunctionality, high cytotoxic and cytokine production profile, and low dysfunctional signature were associated with clinical response. An extended ex vivo expansion time during CAR-T manufacturing negatively influenced the proportion of effector CD8+CAR-Ts in the infusion product. CONCLUSIONS We identified cell-intrinsic characteristics of effector CD8+CAR-Ts correlating with response that could be used as an indicator for clinical outcome. The results in the study also serve as a guide to CAR-T manufacturing practices.
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Affiliation(s)
- Tina Sarén
- Department of Immunology, Genetics and Pathology, Uppsala University, Science for Life Laboratory, Uppsala, Sweden
| | - Mohanraj Ramachandran
- Department of Immunology, Genetics and Pathology, Uppsala University, Science for Life Laboratory, Uppsala, Sweden
| | - Gustav Gammelgård
- Department of Immunology, Genetics and Pathology, Uppsala University, Science for Life Laboratory, Uppsala, Sweden
| | - Tanja Lövgren
- Department of Immunology, Genetics and Pathology, Uppsala University, Science for Life Laboratory, Uppsala, Sweden
| | - Claudio Mirabello
- IFM Bioinformatics, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Linköping University, Linköping, Sweden
| | - Åsa K. Björklund
- Department of Life Sciences, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Chalmers University of Technology, Göteborg, Sweden
| | | | - Jamileh Hashemi
- Department of Immunology, Genetics and Pathology, Uppsala University, Science for Life Laboratory, Uppsala, Sweden
| | - Eva Freyhult
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Håkan Ahlström
- Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
- Antaros Medical AB, Mölndal, Sweden
| | - Rose-Marie Amini
- Department of Immunology, Genetics and Pathology, Uppsala University, Science for Life Laboratory, Uppsala, Sweden
| | - Hans Hagberg
- Department of Immunology, Genetics and Pathology, Uppsala University, Science for Life Laboratory, Uppsala, Sweden
| | - Angelica Loskog
- Department of Immunology, Genetics and Pathology, Uppsala University, Science for Life Laboratory, Uppsala, Sweden
- Lokon Pharma AB, Uppsala, Sweden
| | - Gunilla Enblad
- Department of Immunology, Genetics and Pathology, Uppsala University, Science for Life Laboratory, Uppsala, Sweden
| | - Magnus Essand
- Department of Immunology, Genetics and Pathology, Uppsala University, Science for Life Laboratory, Uppsala, Sweden
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20
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Guyot B, Clément F, Drouet Y, Schmidt X, Lefort S, Delay E, Treilleux I, Foy JP, Jeanpierre S, Thomas E, Kielbassa J, Tonon L, Zhu HH, Saintigny P, Gao WQ, de la Fouchardiere A, Tirode F, Viari A, Blay JY, Maguer-Satta V. An Early Neoplasia Index (ENI10), Based on Molecular Identity of CD10 Cells and Associated Stemness Biomarkers, is a Predictor of Patient Outcome in Many Cancers. CANCER RESEARCH COMMUNICATIONS 2023; 3:1966-1980. [PMID: 37707389 PMCID: PMC10540743 DOI: 10.1158/2767-9764.crc-23-0196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 08/01/2023] [Accepted: 09/08/2023] [Indexed: 09/15/2023]
Abstract
An accurate estimate of patient survival at diagnosis is critical to plan efficient therapeutic options. A simple and multiapplication tool is needed to move forward the precision medicine era. Taking advantage of the broad and high CD10 expression in stem and cancers cells, we evaluated the molecular identity of aggressive cancer cells. We used epithelial primary cells and developed a breast cancer stem cell–based progressive model. The superiority of the early-transformed isolated molecular index was evaluated by large-scale analysis in solid cancers. BMP2-driven cell transformation increases CD10 expression which preserves stemness properties. Our model identified a unique set of 159 genes enriched in G2–M cell-cycle phases and spindle assembly complex. Using samples predisposed to transformation, we confirmed the value of an early neoplasia index associated to CD10 (ENI10) to discriminate premalignant status of a human tissue. Using a stratified Cox model, a large-scale analysis (>10,000 samples, The Cancer Genome Atlas Pan-Cancer) validated a strong risk gradient (HRs reaching HR = 5.15; 95% confidence interval: 4.00–6.64) for high ENI10 levels. Through different databases, Cox regression model analyses highlighted an association between ENI10 and poor progression-free intervals for more than 50% of cancer subtypes tested, and the potential of ENI10 to predict drug efficacy. The ENI10 index constitutes a robust tool to detect pretransformed tissues and identify high-risk patients at diagnosis. Owing to its biological link with refractory cancer stem cells, the ENI10 index constitutes a unique way of identifying effective treatments to improve clinical care. SIGNIFICANCE We identified a molecular signature called ENI10 which, owing to its biological link with stem cell properties, predicts patient outcome and drugs efficiency in breast and several other cancers. ENI10 should allow early and optimized clinical management of a broad number of cancers, regardless of the stage of tumor progression.
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Affiliation(s)
- Boris Guyot
- CNRS UMR5286, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Inserm U1052, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Department of Cancer Initiation and Tumor cell Identity, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Universite Claude Bernard Lyon 1, CRCL, Lyon, France
| | - Flora Clément
- CNRS UMR5286, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Inserm U1052, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Department of Cancer Initiation and Tumor cell Identity, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Universite Claude Bernard Lyon 1, CRCL, Lyon, France
| | | | - Xenia Schmidt
- CNRS UMR5286, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Inserm U1052, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Department of Cancer Initiation and Tumor cell Identity, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Universite Claude Bernard Lyon 1, CRCL, Lyon, France
| | - Sylvain Lefort
- CNRS UMR5286, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Inserm U1052, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Department of Cancer Initiation and Tumor cell Identity, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Universite Claude Bernard Lyon 1, CRCL, Lyon, France
| | - Emmanuel Delay
- CNRS UMR5286, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Inserm U1052, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Department of Cancer Initiation and Tumor cell Identity, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Universite Claude Bernard Lyon 1, CRCL, Lyon, France
- Centre Léon Bérard, Lyon, France
| | | | - Jean-Philippe Foy
- CNRS UMR5286, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Inserm U1052, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Department of Cancer Initiation and Tumor cell Identity, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Department of Tumor Escape Resistance and Immunity, CRCL, Lyon, France
| | - Sandrine Jeanpierre
- CNRS UMR5286, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Inserm U1052, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Department of Cancer Initiation and Tumor cell Identity, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Universite Claude Bernard Lyon 1, CRCL, Lyon, France
- Centre Léon Bérard, Lyon, France
| | - Emilie Thomas
- Bioinformatics Platform, Synergie Lyon Cancer Foundation, Lyon, France
| | - Janice Kielbassa
- Bioinformatics Platform, Synergie Lyon Cancer Foundation, Lyon, France
| | - Laurie Tonon
- Bioinformatics Platform, Synergie Lyon Cancer Foundation, Lyon, France
| | - Helen He Zhu
- State Key Laboratory of Oncogenes and Related Genes, Renji-Med-X Stem Cell Research Center, Shanghai Cancer Institute and Department of Urology, Ren Ji Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, P.R. China
| | - Pierre Saintigny
- CNRS UMR5286, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Inserm U1052, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Department of Cancer Initiation and Tumor cell Identity, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Centre Léon Bérard, Lyon, France
- Department of Tumor Escape Resistance and Immunity, CRCL, Lyon, France
| | - Wei-Qiang Gao
- State Key Laboratory of Oncogenes and Related Genes, Renji-Med-X Stem Cell Research Center, Shanghai Cancer Institute and Department of Urology, Ren Ji Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, P.R. China
- School of Biomedical Engineering and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, P.R. China
| | - Arnaud de la Fouchardiere
- CNRS UMR5286, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Inserm U1052, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Department of Cancer Initiation and Tumor cell Identity, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Centre Léon Bérard, Lyon, France
- Department of Tumor Escape Resistance and Immunity, CRCL, Lyon, France
| | - Franck Tirode
- CNRS UMR5286, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Inserm U1052, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Department of Cancer Initiation and Tumor cell Identity, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Universite Claude Bernard Lyon 1, CRCL, Lyon, France
- Centre Léon Bérard, Lyon, France
| | - Alain Viari
- Bioinformatics Platform, Synergie Lyon Cancer Foundation, Lyon, France
| | - Jean-Yves Blay
- CNRS UMR5286, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Inserm U1052, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Department of Cancer Initiation and Tumor cell Identity, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Centre Léon Bérard, Lyon, France
- Department of Tumor Escape Resistance and Immunity, CRCL, Lyon, France
| | - Véronique Maguer-Satta
- CNRS UMR5286, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Inserm U1052, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Department of Cancer Initiation and Tumor cell Identity, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Universite Claude Bernard Lyon 1, CRCL, Lyon, France
- Centre Léon Bérard, Lyon, France
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21
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Neyton LPA, Patel RK, Sarma A, Willmore A, Haller SC, Kangelaris KN, Eckalbar WL, Erle DJ, Krummel MF, Hendrickson CM, Woodruff PG, Langelier CR, Calfee CS, Fragiadakis GK. Distinct pulmonary and systemic effects of dexamethasone in severe COVID-19. RESEARCH SQUARE 2023:rs.3.rs-3168149. [PMID: 37577607 PMCID: PMC10418533 DOI: 10.21203/rs.3.rs-3168149/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
Dexamethasone is the standard of care for critically ill patients with COVID-19, but the mechanisms by which it decreases mortality and its immunological effects in this setting are not understood. We performed bulk and single-cell RNA sequencing of the lower respiratory tract and blood, and plasma cytokine profiling to study the effect of dexamethasone on systemic and pulmonary immune cells. We find decreased signatures of antigen presentation, T cell recruitment, and viral injury in patients treated with dexamethasone. We identify compartment- and cell- specific differences in the effect of dexamethasone in patients with severe COVID-19 that are reproducible in publicly available datasets. Our results highlight the importance of studying compartmentalized inflammation in critically ill patients.
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Affiliation(s)
- Lucile P A Neyton
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, CA, USA
| | - Ravi K Patel
- UCSF CoLabs, University of California San Francisco, San Francisco, CA, USA
| | - Aartik Sarma
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, CA, USA
| | - Andrew Willmore
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, CA, USA
| | - Sidney C Haller
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, CA, USA
| | | | - Walter L Eckalbar
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, CA, USA
- UCSF CoLabs, University of California San Francisco, San Francisco, CA, USA
| | - David J Erle
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, CA, USA
- UCSF CoLabs, University of California San Francisco, San Francisco, CA, USA
- Department of Medicine, University of California, San Francisco, CA, USA
- Lung Biology Center, University of California, San Francisco, CA, USA
| | - Matthew F Krummel
- Department of Pathology, University of California, San Francisco, CA, USA
| | - Carolyn M Hendrickson
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, CA, USA
| | - Prescott G Woodruff
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, CA, USA
| | - Charles R Langelier
- Chan Zuckerberg Biohub, San Francisco, CA, USA
- Division of Infectious Diseases, University of California, San Francisco, CA, USA
| | - Carolyn S Calfee
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, CA, USA
- Department of Medicine, University of California, San Francisco, CA, USA
- Department of Anesthesia, University of California, San Francisco, CA, USA
| | - Gabriela K Fragiadakis
- UCSF CoLabs, University of California San Francisco, San Francisco, CA, USA
- Division of Rheumatology, University of California, San Francisco, CA, USA
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22
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Gupta P, Herring B, Kumar N, Telange R, Garcia-Buntley SS, Caceres TW, Colantonio S, Williams F, Kurup P, Carter AM, Lin D, Chen H, Rose B, Jaskula-Sztul R, Mukhtar S, Reddy S, Bibb JA. Faulty Metabolism: A Potential Instigator of an Aggressive Phenotype in Cdk5-dependent Medullary Thyroid Carcinoma. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.13.544755. [PMID: 37398342 PMCID: PMC10312670 DOI: 10.1101/2023.06.13.544755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Mechanistic modeling of cancers such as Medullary Thyroid Carcinoma (MTC) to emulate patient-specific phenotypes is challenging. The discovery of potential diagnostic markers and druggable targets in MTC urgently requires clinically relevant animal models. Here we established orthotopic mouse models of MTC driven by aberrantly active Cdk5 using cell-specific promoters. Each of the two models elicits distinct growth differences that recapitulate the less or more aggressive forms of human tumors. The comparative mutational and transcriptomic landscape of tumors revealed significant alterations in mitotic cell cycle processes coupled with the slow-growing tumor phenotype. Conversely, perturbation in metabolic pathways emerged as critical for aggressive tumor growth. Moreover, an overlapping mutational profile was identified between mouse and human tumors. Gene prioritization revealed putative downstream effectors of Cdk5 which may contribute to the slow and aggressive growth in the mouse MTC models. In addition, Cdk5/p25 phosphorylation sites identified as biomarkers for Cdk5-driven neuroendocrine tumors (NETs) were detected in both slow and rapid onset models and were also histologically present in human MTC. Thus, this study directly relates mouse and human MTC models and uncovers vulnerable pathways potentially responsible for differential tumor growth rates. Functional validation of our findings may lead to better prediction of patient-specific personalized combinational therapies.
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Affiliation(s)
- Priyanka Gupta
- Department of Translational Neuroscience, University of Arizona School of Medicine in Phoenix, Phoenix, AZ 85004-2230, USA
| | - Brendon Herring
- Department of Surgery, University of Alabama at Birmingham Heersink School of Medicine, Birmingham, AL 35233, USA
| | - Nilesh Kumar
- Department of Biology, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Rahul Telange
- Department of Hematology, St Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Sandra S. Garcia-Buntley
- Cancer Research Technology Program, Antibody Characterization Lab, Frederick National Laboratory for Cancer Research, Frederick, MD, 21702, USA
| | - Tessa W. Caceres
- Cancer Research Technology Program, Antibody Characterization Lab, Frederick National Laboratory for Cancer Research, Frederick, MD, 21702, USA
| | - Simona Colantonio
- Cancer Research Technology Program, Antibody Characterization Lab, Frederick National Laboratory for Cancer Research, Frederick, MD, 21702, USA
| | - Ford Williams
- Department of Surgery, University of Alabama at Birmingham Heersink School of Medicine, Birmingham, AL 35233, USA
| | - Pradeep Kurup
- Department of Surgery, University of Alabama at Birmingham Heersink School of Medicine, Birmingham, AL 35233, USA
| | - Angela M. Carter
- Department of Surgery, University of Alabama at Birmingham Heersink School of Medicine, Birmingham, AL 35233, USA
| | - Diana Lin
- Department of Pathology, University of Alabama at Birmingham Heersink School of Medicine, Birmingham, AL 35233, USA
| | - Herbert Chen
- Department of Surgery, University of Alabama at Birmingham Heersink School of Medicine, Birmingham, AL 35233, USA
| | - Bart Rose
- Department of Surgery, University of Alabama at Birmingham Heersink School of Medicine, Birmingham, AL 35233, USA
| | - Renata Jaskula-Sztul
- Department of Surgery, University of Alabama at Birmingham Heersink School of Medicine, Birmingham, AL 35233, USA
| | - Shahid Mukhtar
- Department of Biology, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Sushanth Reddy
- Department of Surgery, University of Alabama at Birmingham Heersink School of Medicine, Birmingham, AL 35233, USA
| | - James A. Bibb
- Department of Translational Neuroscience, University of Arizona School of Medicine in Phoenix, Phoenix, AZ 85004-2230, USA
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23
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Nicholas BA, Purohit R, Woods AD, Kannan K, Srinivasa G, Bridge JA, Kim JA, Keller C. BCR-ABL is enriched in S- and G 2-cell cycle phases. Leuk Res 2023; 126:107036. [PMID: 36764024 DOI: 10.1016/j.leukres.2023.107036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 02/03/2023] [Accepted: 02/06/2023] [Indexed: 02/11/2023]
Affiliation(s)
- Bradley A Nicholas
- Children's Cancer Therapy Development Institute, Beaverton, OR 97005 USA
| | - Reshma Purohit
- Children's Cancer Therapy Development Institute, Beaverton, OR 97005 USA
| | - Andrew D Woods
- Children's Cancer Therapy Development Institute, Beaverton, OR 97005 USA
| | | | | | | | - Jin-Ah Kim
- Children's Cancer Therapy Development Institute, Beaverton, OR 97005 USA
| | - Charles Keller
- Children's Cancer Therapy Development Institute, Beaverton, OR 97005 USA.
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24
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Zhang L, Cervantes MD, Pan S, Lindsley J, Dabney A, Kapler GM. Transcriptome analysis of the binucleate ciliate Tetrahymena thermophila with asynchronous nuclear cell cycles. Mol Biol Cell 2023; 34:rs1. [PMID: 36475712 PMCID: PMC9930529 DOI: 10.1091/mbc.e22-08-0326] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Tetrahymena thermophila harbors two functionally and physically distinct nuclei within a shared cytoplasm. During vegetative growth, the "cell cycles" of the diploid micronucleus and polyploid macronucleus are offset. Micronuclear S phase initiates just before cytokinesis and is completed in daughter cells before onset of macronuclear DNA replication. Mitotic micronuclear division occurs mid-cell cycle, while macronuclear amitosis is coupled to cell division. Here we report the first RNA-seq cell cycle analysis of a binucleated ciliated protozoan. RNA was isolated across 1.5 vegetative cell cycles, starting with a macronuclear G1 population synchronized by centrifugal elutriation. Using MetaCycle, 3244 of the 26,000+ predicted genes were shown to be cell cycle regulated. Proteins present in both nuclei exhibit a single mRNA peak that always precedes their macronuclear function. Nucleus-limited genes, including nucleoporins and importins, are expressed before their respective nucleus-specific role. Cyclin D and A/B gene family members exhibit different expression patterns that suggest nucleus-restricted roles. Periodically expressed genes cluster into seven cyclic patterns. Four clusters have known PANTHER gene ontology terms associated with G1/S and G2/M phase. We propose that these clusters encode known and novel factors that coordinate micro- and macronuclear-specific events such as mitosis, amitosis, DNA replication, and cell division.
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Affiliation(s)
- L. Zhang
- Department of Cell Biology and Genetics, Texas A&M University Health Science Center, College Station, TX 77840,Department of Statistics, Texas A&M University, College Station, TX 77843
| | - M. D. Cervantes
- Department of Cell Biology and Genetics, Texas A&M University Health Science Center, College Station, TX 77840
| | - S. Pan
- Department of Cell Biology and Genetics, Texas A&M University Health Science Center, College Station, TX 77840,Department of Statistics, Texas A&M University, College Station, TX 77843
| | - J. Lindsley
- Department of Cell Biology and Genetics, Texas A&M University Health Science Center, College Station, TX 77840
| | - A. Dabney
- Department of Statistics, Texas A&M University, College Station, TX 77843,*Address correspondence to: Geoffrey Kapler (); A. Dabney ()
| | - G. M. Kapler
- Department of Cell Biology and Genetics, Texas A&M University Health Science Center, College Station, TX 77840,*Address correspondence to: Geoffrey Kapler (); A. Dabney ()
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25
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Shang J, Zhang X, Hou G, Qi Y. HMMR potential as a diagnostic and prognostic biomarker of cancer-speculation based on a pan-cancer analysis. Front Surg 2023; 9:998598. [PMID: 36704516 PMCID: PMC9873350 DOI: 10.3389/fsurg.2022.998598] [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: 07/20/2022] [Accepted: 12/21/2022] [Indexed: 01/12/2023] Open
Abstract
Background Although the status of universal upregulation for the Hyaluronan-Mediated Motility Receptor (HMMR) in pan-cancer is still unknown, HMMR is upregulated and associated with poor prognosis for some tumors. Methods Exploring HMMR expression in different tumor types using The Cancer Genome Atlas (TCGA) or other public databases for a pan-cancer analysis, exploring the relationship between HMMR and tumor prognosis, and exploring the role of HMMR in tumor immunity. Results No matter the pairing or unpairing of data, HMMR expression generally increased compared to corresponding normal tissue. Based on a CCLE study, our results indicated that HMMR is widely expressed in various tumor cells. For most tumor types, high HMMR expression was associated with reduced Overall Survival (OS), Return to Functional Status (RFS), and Platinum Free Interval (PFI). ROC curves indicated that HMMR displays high prediction potential for most tumor types. In pan-cancer, HMMR is correlated with some clinical staging, immune cells, and immune checkpoints for some tumors. The GO/KEGG enrichment analysis results for proteins most closely related to HMMR indicate that the most highly enriched pathways are all related to tumor development. Conclusions Our pan-cancer analysis of HMMR suggests that HMMR can be used as a potential diagnostic and prognostic indicator of pan-cancer and that HMMR may be involved in tumor development.
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Affiliation(s)
- Junyi Shang
- Department of Respiratory and Critical Care Medicine; Henan Provincial People's Hospital; People's Hospital of Zhengzhou University, Zhengzhou, China
| | - Xiaoju Zhang
- Department of Respiratory and Critical Care Medicine; Henan Provincial People's Hospital; People's Hospital of Zhengzhou University, Zhengzhou, China
| | - Guangjie Hou
- Department of Thoracic Surgery; Henan Provincial People's Hospital; People's Hospital of Zhengzhou University, Zhengzhou, China
| | - Yong Qi
- Department of Respiratory and Critical Care Medicine; Henan Provincial People's Hospital; People's Hospital of Zhengzhou University, Zhengzhou, China
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26
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Chen L, Su Y, Yin B, Li S, Cheng X, He Y, Jia C. LARP6 Regulates Keloid Fibroblast Proliferation, Invasion, and Ability to Synthesize Collagen. J Invest Dermatol 2022; 142:2395-2405.e7. [PMID: 35176288 DOI: 10.1016/j.jid.2022.01.028] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Revised: 01/13/2022] [Accepted: 01/19/2022] [Indexed: 10/19/2022]
Abstract
Keloid is a skin fibroproliferative disease currently having no uniformly successful treatment. The lesion is composed of actively proliferating and collagen-overproducing fibroblasts. LARP6 is an RNA-binding protein able to regulate collagen synthesis in fibroblasts and to promote proliferation and invasion of tumor cells. To explore LARP6's likely functions in keloid pathogenesis, we performed immunohistochemistry staining on human keloid tissues and discovered markedly upregulated LARP6 expression in lesion fibroblasts compared with that of normal skin and hypertrophic scar tissues. In addition, the keloid tissue‒derived fibroblasts showed constitutive upregulation of LARP6 expression as well as significantly upregulated mRNA and protein expressions of type I collagen and enhanced cell proliferation and invasive behavior in cell culture system. Intriguingly, LARP6 knockdown by targeting with small interfering RNAs significantly inhibited type I collagen expression, proliferation, and invasion capability of keloid tissue‒derived fibroblasts relative to that of normal skin‒ and hypertrophic scar‒derived fibroblasts and control keloid tissue‒derived fibroblasts that were transfected with a scrambled small interfering RNA. In conclusion, the abnormally upregulated expression of LARP6 in fibroblasts may play an important role in the growth and invasive behavior of keloid lesions.
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Affiliation(s)
- Lingxi Chen
- Department of Burns and Plastic Surgery, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Yingjun Su
- Department of Burns and Plastic Surgery, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China; Plastic Surgery Hospital, Xi'an International Medical Center Hospital, Xi'an, China
| | - Bin Yin
- Department of Burns and Plastic Surgery, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Shu Li
- Department of Burns and Plastic Surgery, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Xialin Cheng
- Department of Burns and Plastic Surgery, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Yan He
- Department of Burns and Plastic Surgery, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Chiyu Jia
- Department of Burns and Plastic Surgery, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
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27
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Iida K, Kondo J, Wibisana JN, Inoue M, Okada M. ASURAT: functional annotation-driven unsupervised clustering of single-cell transcriptomes. Bioinformatics 2022; 38:4330-4336. [PMID: 35924984 PMCID: PMC9477531 DOI: 10.1093/bioinformatics/btac541] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 07/04/2022] [Accepted: 08/01/2022] [Indexed: 12/24/2022] Open
Abstract
MOTIVATION Single-cell RNA sequencing (scRNA-seq) analysis reveals heterogeneity and dynamic cell transitions. However, conventional gene-based analyses require intensive manual curation to interpret biological implications of computational results. Hence, a theory for efficiently annotating individual cells remains warranted. RESULTS We present ASURAT, a computational tool for simultaneously performing unsupervised clustering and functional annotation of disease, cell type, biological process and signaling pathway activity for single-cell transcriptomic data, using a correlation graph decomposition for genes in database-derived functional terms. We validated the usability and clustering performance of ASURAT using scRNA-seq datasets for human peripheral blood mononuclear cells, which required fewer manual curations than existing methods. Moreover, we applied ASURAT to scRNA-seq and spatial transcriptome datasets for human small cell lung cancer and pancreatic ductal adenocarcinoma, respectively, identifying previously overlooked subpopulations and differentially expressed genes. ASURAT is a powerful tool for dissecting cell subpopulations and improving biological interpretability of complex and noisy transcriptomic data. AVAILABILITY AND IMPLEMENTATION ASURAT is published on Bioconductor (https://doi.org/10.18129/B9.bioc.ASURAT). The codes for analyzing data in this article are available at Github (https://github.com/keita-iida/ASURATBI) and figshare (https://doi.org/10.6084/m9.figshare.19200254.v4). SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Keita Iida
- To whom correspondence should be addressed.
| | - Jumpei Kondo
- Division of Health Sciences, Osaka University Graduate School of Medicine, Suita, Osaka 565-0871, Japan,Department of Clinical Bio-Resource Research and Development, Graduate School of Medicine Kyoto University, Kyoto 606-8501, Japan
| | | | - Masahiro Inoue
- Department of Clinical Bio-Resource Research and Development, Graduate School of Medicine Kyoto University, Kyoto 606-8501, Japan
| | - Mariko Okada
- Institute for Protein Research, Osaka University, Suita, Osaka 565-0871, Japan,Center for Drug Design and Research, National Institutes of Biomedical Innovation, Health and Nutrition, Ibaraki, Osaka 567-0085, Japan
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28
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Limas JC, Littlejohn AN, House AM, Kedziora KM, Mouery BL, Ma B, Fleifel D, Walens A, Aleman MM, Dominguez D, Cook JG. Quantitative profiling of adaptation to cyclin E overproduction. Life Sci Alliance 2022; 5:e202201378. [PMID: 35173014 PMCID: PMC8860095 DOI: 10.26508/lsa.202201378] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 01/28/2022] [Accepted: 01/31/2022] [Indexed: 01/03/2023] Open
Abstract
Cyclin E/CDK2 drives cell cycle progression from G1 to S phase. Despite the toxicity of cyclin E overproduction in mammalian cells, the cyclin E gene is overexpressed in some cancers. To further understand how cells can tolerate high cyclin E, we characterized non-transformed epithelial cells subjected to chronic cyclin E overproduction. Cells overproducing cyclin E, but not cyclins D or A, briefly experienced truncated G1 phases followed by a transient period of DNA replication origin underlicensing, replication stress, and impaired proliferation. Individual cells displayed substantial intercellular heterogeneity in cell cycle dynamics and CDK activity. Each phenotype improved rapidly despite high cyclin E-associated activity. Transcriptome analysis revealed adapted cells down-regulated a cohort of G1-regulated genes. Withdrawing cyclin E from adapted cells only partially reversed underlicensing indicating that adaptation is at least partly non-genetic. This study provides evidence that mammalian cyclin E/CDK inhibits origin licensing indirectly through premature S phase onset and provides mechanistic insight into the relationship between CDKs and licensing. It serves as an example of oncogene adaptation that may recapitulate molecular changes during tumorigenesis.
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Affiliation(s)
- Juanita C Limas
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Amiee N Littlejohn
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Amy M House
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Katarzyna M Kedziora
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Bioinformatics and Analytics Research Collaborative (BARC), University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Brandon L Mouery
- Curriculum in Genetics and Molecular Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Boyang Ma
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Dalia Fleifel
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Andrea Walens
- Lineberger Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Maria M Aleman
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Daniel Dominguez
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jeanette Gowen Cook
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Curriculum in Genetics and Molecular Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Lineberger Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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29
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Mujal AM, Combes AJ, Rao AA, Binnewies M, Samad B, Tsui J, Boissonnas A, Pollack JL, Argüello RJ, Meng MV, Porten SP, Ruhland MK, Barry KC, Chan V, Krummel MF. Holistic Characterization of Tumor Monocyte-to-Macrophage Differentiation Integrates Distinct Immune Phenotypes in Kidney Cancer. Cancer Immunol Res 2022; 10:403-419. [PMID: 35181780 PMCID: PMC8982148 DOI: 10.1158/2326-6066.cir-21-0588] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 11/20/2021] [Accepted: 02/15/2022] [Indexed: 11/16/2022]
Abstract
The tumor immune microenvironment (TIME) is commonly infiltrated by diverse collections of myeloid cells. Yet, the complexity of myeloid-cell identity and plasticity has challenged efforts to define bona fide populations and determine their connections to T-cell function and their relationship to patient outcome. Here, we have leveraged single-cell RNA-sequencing analysis of several mouse and human tumors and found that monocyte-macrophage diversity is characterized by a combination of conserved lineage states as well as transcriptional programs accessed along the differentiation trajectory. We also found in mouse models that tumor monocyte-to-macrophage progression was profoundly tied to regulatory T cell (Treg) abundance. In human kidney cancer, heterogeneity in macrophage accumulation and myeloid composition corresponded to variance in, not only Treg density, but also the quality of infiltrating CD8+ T cells. In this way, holistic analysis of monocyte-to-macrophage differentiation creates a framework for critically different immune states.
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Affiliation(s)
- Adriana M. Mujal
- Department of Pathology and ImmunoX, University of California, San Francisco, San Francisco, CA 94143, USA
- Present address: Immunology Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
- These authors contributed equally to this work
| | - Alexis J. Combes
- Department of Pathology and ImmunoX, University of California, San Francisco, San Francisco, CA 94143, USA
- UCSF CoLabs, University of California, San Francisco, San Francisco, CA 94143, USA
- UCSF Immunoprofiler Initiative, University of California, San Francisco, San Francisco, CA 94143, USA
- These authors contributed equally to this work
| | - Arjun A. Rao
- UCSF CoLabs, University of California, San Francisco, San Francisco, CA 94143, USA
- UCSF Immunoprofiler Initiative, University of California, San Francisco, San Francisco, CA 94143, USA
- These authors contributed equally to this work
| | - Mikhail Binnewies
- Department of Pathology and ImmunoX, University of California, San Francisco, San Francisco, CA 94143, USA
- These authors contributed equally to this work
| | - Bushra Samad
- Department of Pathology and ImmunoX, University of California, San Francisco, San Francisco, CA 94143, USA
- UCSF CoLabs, University of California, San Francisco, San Francisco, CA 94143, USA
- UCSF Immunoprofiler Initiative, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Jessica Tsui
- Department of Pathology and ImmunoX, University of California, San Francisco, San Francisco, CA 94143, USA
- UCSF CoLabs, University of California, San Francisco, San Francisco, CA 94143, USA
- UCSF Immunoprofiler Initiative, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Alexandre Boissonnas
- Sorbonne Université, INSERM, CNRS, Centre d’Immunologie et des Maladies Infectieuses Cimi-Paris, F-75013, Paris, France
| | - Joshua L. Pollack
- UCSF Immunoprofiler Initiative, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Rafael J. Argüello
- Aix Marseille Univ, CNRS, INSERM, CIML, Centre d’Immunologie de Marseille-Luminy, Marseille, France
| | - Maxwell V. Meng
- Department of Urology, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Sima P. Porten
- Department of Urology, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Megan K. Ruhland
- Department of Pathology and ImmunoX, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Kevin C. Barry
- Department of Pathology and ImmunoX, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Vincent Chan
- Department of Pathology and ImmunoX, University of California, San Francisco, San Francisco, CA 94143, USA
- UCSF CoLabs, University of California, San Francisco, San Francisco, CA 94143, USA
- UCSF Immunoprofiler Initiative, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Matthew F. Krummel
- Department of Pathology and ImmunoX, University of California, San Francisco, San Francisco, CA 94143, USA
- UCSF CoLabs, University of California, San Francisco, San Francisco, CA 94143, USA
- UCSF Immunoprofiler Initiative, University of California, San Francisco, San Francisco, CA 94143, USA
- Lead contact
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30
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Graf M, Interlandi M, Moreno N, Holdhof D, Göbel C, Melcher V, Mertins J, Albert TK, Kastrati D, Alfert A, Holsten T, de Faria F, Meisterernst M, Rossig C, Warmuth-Metz M, Nowak J, Meyer Zu Hörste G, Mayère C, Nef S, Johann P, Frühwald MC, Dugas M, Schüller U, Kerl K. Single-cell transcriptomics identifies potential cells of origin of MYC rhabdoid tumors. Nat Commun 2022; 13:1544. [PMID: 35318328 PMCID: PMC8941154 DOI: 10.1038/s41467-022-29152-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Accepted: 02/26/2022] [Indexed: 11/30/2022] Open
Abstract
Rhabdoid tumors (RT) are rare and highly aggressive pediatric neoplasms. Their epigenetically-driven intertumoral heterogeneity is well described; however, the cellular origin of RT remains an enigma. Here, we establish and characterize different genetically engineered mouse models driven under the control of distinct promoters and being active in early progenitor cell types with diverse embryonic onsets. From all models only Sox2-positive progenitor cells give rise to murine RT. Using single-cell analyses, we identify distinct cells of origin for the SHH and MYC subgroups of RT, rooting in early stages of embryogenesis. Intra- and extracranial MYC tumors harbor common genetic programs and potentially originate from fetal primordial germ cells (PGCs). Using PGC specific Smarcb1 knockout mouse models we validate that MYC RT originate from these progenitor cells. We uncover an epigenetic imbalance in MYC tumors compared to PGCs being sustained by epigenetically-driven subpopulations. Importantly, treatments with the DNA demethylating agent decitabine successfully impair tumor growth in vitro and in vivo. In summary, our work sheds light on the origin of RT and supports the clinical relevance of DNA methyltransferase inhibitors against this disease. Rhabdoid tumors (RT) are aggressive paediatric cancers with yet unknown cells of origin. Here, the authors establish genetically engineered mouse models of RT and, using single-cell RNA-seq and epigenomics, identify potential cells of origin for the SHH and MYC subtypes.
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Affiliation(s)
- Monika Graf
- Department of Pediatric Hematology and Oncology, University Children's Hospital Münster, 48149, Münster, Germany
| | - Marta Interlandi
- Department of Pediatric Hematology and Oncology, University Children's Hospital Münster, 48149, Münster, Germany.,Institute of Medical Informatics, University of Münster, 48149, Münster, Germany
| | - Natalia Moreno
- Department of Pediatric Hematology and Oncology, University Children's Hospital Münster, 48149, Münster, Germany
| | - Dörthe Holdhof
- Department of Pediatric Hematology and Oncology, University Medical Center Hamburg-Eppendorf, 20251, Hamburg, Germany.,Institute of Neuropathology, University Medical Center Hamburg-Eppendorf, 20251, Hamburg, Germany
| | - Carolin Göbel
- Department of Pediatric Hematology and Oncology, University Medical Center Hamburg-Eppendorf, 20251, Hamburg, Germany.,Institute of Neuropathology, University Medical Center Hamburg-Eppendorf, 20251, Hamburg, Germany
| | - Viktoria Melcher
- Department of Pediatric Hematology and Oncology, University Children's Hospital Münster, 48149, Münster, Germany
| | - Julius Mertins
- Department of Neurology, Schlosspark-Klinik, 14059, Berlin, Germany.,Institute of Molecular Tumor Biology, University of Münster, 48149, Münster, Germany
| | - Thomas K Albert
- Department of Pediatric Hematology and Oncology, University Children's Hospital Münster, 48149, Münster, Germany
| | - Dennis Kastrati
- Department of Pediatric Hematology and Oncology, University Children's Hospital Münster, 48149, Münster, Germany
| | - Amelie Alfert
- Department of Pediatric Hematology and Oncology, University Children's Hospital Münster, 48149, Münster, Germany
| | - Till Holsten
- Department of Pediatric Hematology and Oncology, University Medical Center Hamburg-Eppendorf, 20251, Hamburg, Germany.,Institute of Molecular Tumor Biology, University of Münster, 48149, Münster, Germany
| | - Flavia de Faria
- Department of Pediatric Hematology and Oncology, University Children's Hospital Münster, 48149, Münster, Germany.,Department of Pediatric Hematology and Oncology, Children's Hospital of Brasìlia, 70684-831, Brasìlia, Brazil
| | - Michael Meisterernst
- Institute of Molecular Tumor Biology, University of Münster, 48149, Münster, Germany
| | - Claudia Rossig
- Department of Pediatric Hematology and Oncology, University Children's Hospital Münster, 48149, Münster, Germany
| | - Monika Warmuth-Metz
- Neuroradiological Reference Center, University Hospital Würzburg, Würzburg, Germany
| | - Johannes Nowak
- Neuroradiological Reference Center, University Hospital Würzburg, Würzburg, Germany.,SRH Poliklinik Gera GmbH, Radiological Practice Gotha, Gotha, Germany
| | - Gerd Meyer Zu Hörste
- Department of Neurology with Institute of Translational Neurology, University Hospital Münster, 48149, Münster, Germany
| | - Chloe Mayère
- Department of Genetic Medicine and Development, University of Geneva, 1211, Geneva, Switzerland.,iGE3, Institute of Genetics and Genomics of Geneva, University of Geneva, 1211, Geneva, Switzerland
| | - Serge Nef
- Department of Genetic Medicine and Development, University of Geneva, 1211, Geneva, Switzerland.,iGE3, Institute of Genetics and Genomics of Geneva, University of Geneva, 1211, Geneva, Switzerland
| | - Pascal Johann
- Swabian Children's Cancer Center, Paediatric and Adolescent Medicine, University Medical Center Augsburg, 86156, Augsburg, Germany.,Division of Pediatric Neurooncology, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Michael C Frühwald
- Swabian Children's Cancer Center, Paediatric and Adolescent Medicine, University Medical Center Augsburg, 86156, Augsburg, Germany
| | - Martin Dugas
- Institute of Medical Informatics, University of Münster, 48149, Münster, Germany.,Institute of Medical Informatics, Heidelberg University Hospital, Heidelberg, Germany
| | - Ulrich Schüller
- Department of Pediatric Hematology and Oncology, University Medical Center Hamburg-Eppendorf, 20251, Hamburg, Germany.,Institute of Neuropathology, University Medical Center Hamburg-Eppendorf, 20251, Hamburg, Germany.,Research Institute Children's Cancer Center, 20251, Hamburg, Germany
| | - Kornelius Kerl
- Department of Pediatric Hematology and Oncology, University Children's Hospital Münster, 48149, Münster, Germany.
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31
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Zinovyev A, Sadovsky M, Calzone L, Fouché A, Groeneveld CS, Chervov A, Barillot E, Gorban AN. Modeling Progression of Single Cell Populations Through the Cell Cycle as a Sequence of Switches. Front Mol Biosci 2022; 8:793912. [PMID: 35178429 PMCID: PMC8846220 DOI: 10.3389/fmolb.2021.793912] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 12/15/2021] [Indexed: 11/13/2022] Open
Abstract
Cell cycle is a biological process underlying the existence and propagation of life in time and space. It has been an object for mathematical modeling for long, with several alternative mechanistic modeling principles suggested, describing in more or less details the known molecular mechanisms. Recently, cell cycle has been investigated at single cell level in snapshots of unsynchronized cell populations, exploiting the new methods for transcriptomic and proteomic molecular profiling. This raises a need for simplified semi-phenomenological cell cycle models, in order to formalize the processes underlying the cell cycle, at a higher abstracted level. Here we suggest a modeling framework, recapitulating the most important properties of the cell cycle as a limit trajectory of a dynamical process characterized by several internal states with switches between them. In the simplest form, this leads to a limit cycle trajectory, composed by linear segments in logarithmic coordinates describing some extensive (depending on system size) cell properties. We prove a theorem connecting the effective embedding dimensionality of the cell cycle trajectory with the number of its linear segments. We also develop a simplified kinetic model with piecewise-constant kinetic rates describing the dynamics of lumps of genes involved in S-phase and G2/M phases. We show how the developed cell cycle models can be applied to analyze the available single cell datasets and simulate certain properties of the observed cell cycle trajectories. Based on our model, we can predict with good accuracy the cell line doubling time from the length of cell cycle trajectory.
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Affiliation(s)
- Andrei Zinovyev
- Institut Curie, PSL Research University, Paris, France
- INSERM, Paris, France
- MINES ParisTech, PSL Research University, CBIO-Centre for Computational Biology, Paris, France
- *Correspondence: Andrei Zinovyev,
| | - Michail Sadovsky
- Institute of Computational Modeling (RAS), Krasnoyarsk, Russia
- Laboratory of Medical Cybernetics, V.F.Voino-Yasenetsky Krasnoyarsk State Medical University, Krasnoyarsk, Russia
- Federal Research and Clinic Center of FMBA of Russia, Krasnoyarsk, Russia
- Laboratory of Advanced Methods for High-Dimensional Data Analysis, Lobachevsky University, Nizhniy Novgorod, Russia
| | - Laurence Calzone
- Institut Curie, PSL Research University, Paris, France
- INSERM, Paris, France
- MINES ParisTech, PSL Research University, CBIO-Centre for Computational Biology, Paris, France
| | - Aziz Fouché
- Institut Curie, PSL Research University, Paris, France
- INSERM, Paris, France
- MINES ParisTech, PSL Research University, CBIO-Centre for Computational Biology, Paris, France
| | - Clarice S. Groeneveld
- Cartes d’Identité des Tumeurs (CIT) Program, Ligue Nationale Contre le Cancer, Paris, France
- Oncologie Moleculaire, UMR144, Institut Curie, Paris, France
| | - Alexander Chervov
- Institut Curie, PSL Research University, Paris, France
- INSERM, Paris, France
- MINES ParisTech, PSL Research University, CBIO-Centre for Computational Biology, Paris, France
| | - Emmanuel Barillot
- Institut Curie, PSL Research University, Paris, France
- INSERM, Paris, France
- MINES ParisTech, PSL Research University, CBIO-Centre for Computational Biology, Paris, France
| | - Alexander N. Gorban
- Laboratory of Advanced Methods for High-Dimensional Data Analysis, Lobachevsky University, Nizhniy Novgorod, Russia
- Department of Mathematics, University of Leicester, Leicester, United Kingdom
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32
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Guo X. Localized Proteasomal Degradation: From the Nucleus to Cell Periphery. Biomolecules 2022; 12:biom12020229. [PMID: 35204730 PMCID: PMC8961600 DOI: 10.3390/biom12020229] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Revised: 01/25/2022] [Accepted: 01/27/2022] [Indexed: 12/31/2022] Open
Abstract
The proteasome is responsible for selective degradation of most cellular proteins. Abundantly present in the cell, proteasomes not only diffuse in the cytoplasm and the nucleus but also associate with the chromatin, cytoskeleton, various membranes and membraneless organelles/condensates. How and why the proteasome gets to these specific subcellular compartments remains poorly understood, although increasing evidence supports the hypothesis that intracellular localization may have profound impacts on the activity, substrate accessibility and stability/integrity of the proteasome. In this short review, I summarize recent advances on the functions, regulations and targeting mechanisms of proteasomes, especially those localized to the nuclear condensates and membrane structures of the cell, and I discuss the biological significance thereof in mediating compartmentalized protein degradation.
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Affiliation(s)
- Xing Guo
- Life Sciences Institute, Zhejiang University, Hangzhou 310058, China;
- Zhejiang Provincial Key Laboratory for Cancer Molecular Cell Biology, Hangzhou 310058, China
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33
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Monti M, Fiorentino J, Milanetti E, Gosti G, Tartaglia GG. Prediction of Time Series Gene Expression and Structural Analysis of Gene Regulatory Networks Using Recurrent Neural Networks. ENTROPY (BASEL, SWITZERLAND) 2022; 24:141. [PMID: 35205437 PMCID: PMC8871363 DOI: 10.3390/e24020141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 01/14/2022] [Accepted: 01/15/2022] [Indexed: 11/17/2022]
Abstract
Methods for time series prediction and classification of gene regulatory networks (GRNs) from gene expression data have been treated separately so far. The recent emergence of attention-based recurrent neural network (RNN) models boosted the interpretability of RNN parameters, making them appealing for the understanding of gene interactions. In this work, we generated synthetic time series gene expression data from a range of archetypal GRNs and we relied on a dual attention RNN to predict the gene temporal dynamics. We show that the prediction is extremely accurate for GRNs with different architectures. Next, we focused on the attention mechanism of the RNN and, using tools from graph theory, we found that its graph properties allow one to hierarchically distinguish different architectures of the GRN. We show that the GRN responded differently to the addition of noise in the prediction by the RNN and we related the noise response to the analysis of the attention mechanism. In conclusion, this work provides a way to understand and exploit the attention mechanism of RNNs and it paves the way to RNN-based methods for time series prediction and inference of GRNs from gene expression data.
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Affiliation(s)
- Michele Monti
- RNA System Biology Lab, Department of Neuroscience and Brain Technologies, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genoa, Italy
- Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Jonathan Fiorentino
- Center for Life Nano- & Neuro-Science, Istituto Italiano di Tecnologia, Viale Regina Elena 291, 00161 Rome, Italy; (J.F.); (E.M.); (G.G.)
| | - Edoardo Milanetti
- Center for Life Nano- & Neuro-Science, Istituto Italiano di Tecnologia, Viale Regina Elena 291, 00161 Rome, Italy; (J.F.); (E.M.); (G.G.)
- Department of Physics, Sapienza University of Rome, 00185 Rome, Italy
| | - Giorgio Gosti
- Center for Life Nano- & Neuro-Science, Istituto Italiano di Tecnologia, Viale Regina Elena 291, 00161 Rome, Italy; (J.F.); (E.M.); (G.G.)
- Department of Physics, Sapienza University of Rome, 00185 Rome, Italy
| | - Gian Gaetano Tartaglia
- RNA System Biology Lab, Department of Neuroscience and Brain Technologies, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genoa, Italy
- Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Dr. Aiguader 88, 08003 Barcelona, Spain
- Center for Life Nano- & Neuro-Science, Istituto Italiano di Tecnologia, Viale Regina Elena 291, 00161 Rome, Italy; (J.F.); (E.M.); (G.G.)
- Department of Biology and Biotechnology Charles Darwin, Sapienza University of Rome, 00185 Rome, Italy
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34
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Combes AJ, Samad B, Tsui J, Chew NW, Yan P, Reeder GC, Kushnoor D, Shen A, Davidson B, Barczak AJ, Adkisson M, Edwards A, Naser M, Barry KC, Courau T, Hammoudi T, Argüello RJ, Rao AA, Olshen AB, Cai C, Zhan J, Davis KC, Kelley RK, Chapman JS, Atreya CE, Patel A, Daud AI, Ha P, Diaz AA, Kratz JR, Collisson EA, Fragiadakis GK, Erle DJ, Boissonnas A, Asthana S, Chan V, Krummel MF, Fong L, Nelson A, Kumar R, Lee J, Burra A, Hsu J, Hackett C, Tolentino K, Sjarif J, Johnson P, Shao E, Abrau D, Lupin L, Shaw C, Collins Z, Lea T, Corvera C, Nakakura E, Carnevale J, Alvarado M, Loo K, Chen L, Chow M, Grandis J, Ryan W, El-Sayed I, Jablons D, Woodard G, Meng MW, Porten SP, Okada H, Tempero M, Ko A, Kirkwood K, Vandenberg S, Guevarra D, Oropeza E, Cyr C, Glenn P, Bolen J, Morton A, Eckalbar W. Discovering dominant tumor immune archetypes in a pan-cancer census. Cell 2022; 185:184-203.e19. [PMID: 34963056 PMCID: PMC8862608 DOI: 10.1016/j.cell.2021.12.004] [Citation(s) in RCA: 76] [Impact Index Per Article: 25.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 08/25/2021] [Accepted: 12/03/2021] [Indexed: 01/09/2023]
Abstract
Cancers display significant heterogeneity with respect to tissue of origin, driver mutations, and other features of the surrounding tissue. It is likely that individual tumors engage common patterns of the immune system-here "archetypes"-creating prototypical non-destructive tumor immune microenvironments (TMEs) and modulating tumor-targeting. To discover the dominant immune system archetypes, the University of California, San Francisco (UCSF) Immunoprofiler Initiative (IPI) processed 364 individual tumors across 12 cancer types using standardized protocols. Computational clustering of flow cytometry and transcriptomic data obtained from cell sub-compartments uncovered dominant patterns of immune composition across cancers. These archetypes were profound insofar as they also differentiated tumors based upon unique immune and tumor gene-expression patterns. They also partitioned well-established classifications of tumor biology. The IPI resource provides a template for understanding cancer immunity as a collection of dominant patterns of immune organization and provides a rational path forward to learn how to modulate these to improve therapy.
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Affiliation(s)
- Alexis J. Combes
- Department of Pathology, University of California San Francisco, San Francisco, CA 94143, USA,ImmunoX Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF Immunoprofiler Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF CoLabs, University of California San Francisco, San Francisco, CA 94143, USA,Correspondence: and
| | - Bushra Samad
- Department of Pathology, University of California San Francisco, San Francisco, CA 94143, USA,ImmunoX Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF Immunoprofiler Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF CoLabs, University of California San Francisco, San Francisco, CA 94143, USA
| | - Jessica Tsui
- Department of Pathology, University of California San Francisco, San Francisco, CA 94143, USA,ImmunoX Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF Immunoprofiler Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF CoLabs, University of California San Francisco, San Francisco, CA 94143, USA
| | - Nayvin W. Chew
- Department of Pathology, University of California San Francisco, San Francisco, CA 94143, USA,ImmunoX Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF Immunoprofiler Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF CoLabs, University of California San Francisco, San Francisco, CA 94143, USA
| | - Peter Yan
- Department of Pathology, University of California San Francisco, San Francisco, CA 94143, USA,ImmunoX Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF Immunoprofiler Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF CoLabs, University of California San Francisco, San Francisco, CA 94143, USA
| | - Gabriella C. Reeder
- Department of Pathology, University of California San Francisco, San Francisco, CA 94143, USA,ImmunoX Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF Immunoprofiler Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF CoLabs, University of California San Francisco, San Francisco, CA 94143, USA
| | - Divyashree Kushnoor
- Department of Pathology, University of California San Francisco, San Francisco, CA 94143, USA,ImmunoX Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF Immunoprofiler Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF CoLabs, University of California San Francisco, San Francisco, CA 94143, USA
| | - Alan Shen
- Department of Pathology, University of California San Francisco, San Francisco, CA 94143, USA,ImmunoX Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF Immunoprofiler Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF CoLabs, University of California San Francisco, San Francisco, CA 94143, USA
| | - Brittany Davidson
- ImmunoX Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF Immunoprofiler Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF CoLabs, University of California San Francisco, San Francisco, CA 94143, USA
| | - Andrea J. Barczak
- UCSF Immunoprofiler Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF CoLabs, University of California San Francisco, San Francisco, CA 94143, USA
| | - Michael Adkisson
- UCSF Immunoprofiler Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF CoLabs, University of California San Francisco, San Francisco, CA 94143, USA
| | - Austin Edwards
- Department of Pathology, University of California San Francisco, San Francisco, CA 94143, USA,ImmunoX Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF Immunoprofiler Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF CoLabs, University of California San Francisco, San Francisco, CA 94143, USA
| | - Mohammad Naser
- Department of Pathology, University of California San Francisco, San Francisco, CA 94143, USA,ImmunoX Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF Immunoprofiler Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF CoLabs, University of California San Francisco, San Francisco, CA 94143, USA
| | - Kevin C. Barry
- Translational Research Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Tristan Courau
- Department of Pathology, University of California San Francisco, San Francisco, CA 94143, USA,ImmunoX Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF Immunoprofiler Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF CoLabs, University of California San Francisco, San Francisco, CA 94143, USA
| | - Taymour Hammoudi
- Department of Pathology, University of California San Francisco, San Francisco, CA 94143, USA,ImmunoX Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF Immunoprofiler Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF CoLabs, University of California San Francisco, San Francisco, CA 94143, USA
| | - Rafael J Argüello
- Aix Marseille University, CNRS, INSERM, CIML, Centre d’Immunologie de Marseille-Luminy, Marseille, FRANCE
| | - Arjun Arkal Rao
- Department of Pathology, University of California San Francisco, San Francisco, CA 94143, USA,ImmunoX Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF Immunoprofiler Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF CoLabs, University of California San Francisco, San Francisco, CA 94143, USA
| | - Adam B. Olshen
- UCSF Immunoprofiler Initiative, University of California San Francisco, San Francisco, CA 94143, USA,Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA 94143, USA,Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94143, USA
| | | | - Cathy Cai
- Department of Pathology, University of California San Francisco, San Francisco, CA 94143, USA,ImmunoX Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF Immunoprofiler Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF CoLabs, University of California San Francisco, San Francisco, CA 94143, USA
| | - Jenny Zhan
- Department of Pathology, University of California San Francisco, San Francisco, CA 94143, USA,ImmunoX Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF Immunoprofiler Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF CoLabs, University of California San Francisco, San Francisco, CA 94143, USA
| | - Katelyn C. Davis
- Department of Pathology, University of California San Francisco, San Francisco, CA 94143, USA,ImmunoX Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF Immunoprofiler Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF CoLabs, University of California San Francisco, San Francisco, CA 94143, USA
| | - Robin K. Kelley
- Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA 94143, USA
| | - Jocelyn S. Chapman
- UCSF Immunoprofiler Initiative, University of California San Francisco, San Francisco, CA 94143, USA,Departments of Obstetrics, Gynecology, and Reproductive Sciences, Medicine, University of California San Francisco, San Francisco, CA 94143, USA
| | - Chloe E. Atreya
- UCSF Immunoprofiler Initiative, University of California San Francisco, San Francisco, CA 94143, USA,Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA 94143, USA,Department of Medicine, Division of Hematology and Oncology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Amar Patel
- UCSF Immunoprofiler Initiative, University of California San Francisco, San Francisco, CA 94143, USA,Department of Medicine, Division of Hematology and Oncology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Adil I. Daud
- Department of Medicine, Division of Hematology and Oncology, University of California San Francisco, San Francisco, CA 94143, USA,Department of Dermatology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Patrick Ha
- Department of Otolaryngology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Aaron A. Diaz
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA
| | - Johannes R. Kratz
- ImmunoX Initiative, University of California San Francisco, San Francisco, CA 94143, USA,Department of Surgery, University of California San Francisco, San Francisco, CA 94143, USA
| | - Eric A. Collisson
- UCSF Immunoprofiler Initiative, University of California San Francisco, San Francisco, CA 94143, USA,Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA 94143, USA,Department of Medicine, Division of Hematology and Oncology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Gabriela K Fragiadakis
- ImmunoX Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF Immunoprofiler Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF CoLabs, University of California San Francisco, San Francisco, CA 94143, USA,Department of Medicine Division of Rheumatology, University of California San Francisco, San Francisco, CA 94143, USA
| | - David J. Erle
- ImmunoX Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF Immunoprofiler Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF CoLabs, University of California San Francisco, San Francisco, CA 94143, USA,Lung Biology Center, Department of Medicine and the Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA 94143, USA
| | - Alexandre Boissonnas
- Sorbonne Université, INSERM, CNRS, Centre d’Immunologie et des Maladies Infectieuses - CIMI, Paris, France
| | - Saurabh Asthana
- UCSF Immunoprofiler Initiative, University of California San Francisco, San Francisco, CA 94143, USA,Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94143, USA
| | - Vincent Chan
- ImmunoX Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF Immunoprofiler Initiative, University of California San Francisco, San Francisco, CA 94143, USA,Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Matthew F. Krummel
- Department of Pathology, University of California San Francisco, San Francisco, CA 94143, USA,ImmunoX Initiative, University of California San Francisco, San Francisco, CA 94143, USA,UCSF Immunoprofiler Initiative, University of California San Francisco, San Francisco, CA 94143, USA,Correspondence: and
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35
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AKIRIN2 controls the nuclear import of proteasomes in vertebrates. Nature 2021; 599:491-496. [PMID: 34711951 DOI: 10.1038/s41586-021-04035-8] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Accepted: 09/16/2021] [Indexed: 02/08/2023]
Abstract
Protein expression and turnover are controlled through a complex interplay of transcriptional, post-transcriptional and post-translational mechanisms to enable spatial and temporal regulation of cellular processes. To systematically elucidate such gene regulatory networks, we developed a CRISPR screening assay based on time-controlled Cas9 mutagenesis, intracellular immunostaining and fluorescence-activated cell sorting that enables the identification of regulatory factors independent of their effects on cellular fitness. We pioneered this approach by systematically probing the regulation of the transcription factor MYC, a master regulator of cell growth1-3. Our screens uncover a highly conserved protein, AKIRIN2, that is essentially required for nuclear protein degradation. We found that AKIRIN2 forms homodimers that directly bind to fully assembled 20S proteasomes to mediate their nuclear import. During mitosis, proteasomes are excluded from condensing chromatin and re-imported into newly formed daughter nuclei in a highly dynamic, AKIRIN2-dependent process. Cells undergoing mitosis in the absence of AKIRIN2 become devoid of nuclear proteasomes, rapidly causing accumulation of MYC and other nuclear proteins. Collectively, our study reveals a dedicated pathway controlling the nuclear import of proteasomes in vertebrates and establishes a scalable approach to decipher regulators in essential cellular processes.
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36
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Hegre SA, Samdal H, Klima A, Stovner EB, Nørsett KG, Liabakk NB, Olsen LC, Chawla K, Aas PA, Sætrom P. Joint changes in RNA, RNA polymerase II, and promoter activity through the cell cycle identify non-coding RNAs involved in proliferation. Sci Rep 2021; 11:18952. [PMID: 34556693 PMCID: PMC8460802 DOI: 10.1038/s41598-021-97909-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Accepted: 07/26/2021] [Indexed: 11/09/2022] Open
Abstract
Proper regulation of the cell cycle is necessary for normal growth and development of all organisms. Conversely, altered cell cycle regulation often underlies proliferative diseases such as cancer. Long non-coding RNAs (lncRNAs) are recognized as important regulators of gene expression and are often found dysregulated in diseases, including cancers. However, identifying lncRNAs with cell cycle functions is challenging due to their often low and cell-type specific expression. We present a highly effective method that analyses changes in promoter activity, transcription, and RNA levels for identifying genes enriched for cell cycle functions. Specifically, by combining RNA sequencing with ChIP sequencing through the cell cycle of synchronized human keratinocytes, we identified 1009 genes with cell cycle-dependent expression and correlated changes in RNA polymerase II occupancy or promoter activity as measured by histone 3 lysine 4 trimethylation (H3K4me3). These genes were highly enriched for genes with known cell cycle functions and included 57 lncRNAs. We selected four of these lncRNAs-SNHG26, EMSLR, ZFAS1, and EPB41L4A-AS1-for further experimental validation and found that knockdown of each of the four lncRNAs affected cell cycle phase distributions and reduced proliferation in multiple cell lines. These results show that many genes with cell cycle functions have concomitant cell-cycle dependent changes in promoter activity, transcription, and RNA levels and support that our multi-omics method is well suited for identifying lncRNAs involved in the cell cycle.
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Affiliation(s)
- Siv Anita Hegre
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway
| | - Helle Samdal
- Department of Computer Science, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway
| | - Antonin Klima
- Department of Computer Science, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway
| | - Endre B Stovner
- Department of Computer Science, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway.,K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway
| | - Kristin G Nørsett
- Department of Computer Science, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway.,Department of Biomedical Laboratory Science, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway
| | - Nina Beate Liabakk
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway
| | - Lene Christin Olsen
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway.,Bioinformatics Core Facility-BioCore, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway.,The Central Norway Regional Health Authority, St. Olavs Hospital HF, Trondheim, Norway
| | - Konika Chawla
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway.,Bioinformatics Core Facility-BioCore, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway
| | - Per Arne Aas
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway
| | - Pål Sætrom
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway. .,Department of Computer Science, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway. .,K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway. .,Bioinformatics Core Facility-BioCore, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway.
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37
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Lindström NO, Sealfon R, Chen X, Parvez RK, Ransick A, De Sena Brandine G, Guo J, Hill B, Tran T, Kim AD, Zhou J, Tadych A, Watters A, Wong A, Lovero E, Grubbs BH, Thornton ME, McMahon JA, Smith AD, Ruffins SW, Armit C, Troyanskaya OG, McMahon AP. Spatial transcriptional mapping of the human nephrogenic program. Dev Cell 2021; 56:2381-2398.e6. [PMID: 34428401 PMCID: PMC8396064 DOI: 10.1016/j.devcel.2021.07.017] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Revised: 05/06/2021] [Accepted: 07/27/2021] [Indexed: 12/11/2022]
Abstract
Congenital abnormalities of the kidney and urinary tract are among the most common birth defects, affecting 3% of newborns. The human kidney forms around a million nephrons from a pool of nephron progenitors over a 30-week period of development. To establish a framework for human nephrogenesis, we spatially resolved a stereotypical process by which equipotent nephron progenitors generate a nephron anlage, then applied data-driven approaches to construct three-dimensional protein maps on anatomical models of the nephrogenic program. Single-cell RNA sequencing identified progenitor states, which were spatially mapped to the nephron anatomy, enabling the generation of functional gene networks predicting interactions within and between nephron cell types. Network mining identified known developmental disease genes and predicted targets of interest. The spatially resolved nephrogenic program made available through the Human Nephrogenesis Atlas (https://sckidney.flatironinstitute.org/) will facilitate an understanding of kidney development and disease and enhance efforts to generate new kidney structures.
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Affiliation(s)
- Nils O Lindström
- Department of Stem Cell Biology and Regenerative Medicine, Broad-CIRM Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
| | - Rachel Sealfon
- Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY, USA; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Xi Chen
- Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY, USA; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Riana K Parvez
- Department of Stem Cell Biology and Regenerative Medicine, Broad-CIRM Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Andrew Ransick
- Department of Stem Cell Biology and Regenerative Medicine, Broad-CIRM Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Guilherme De Sena Brandine
- Molecular and Computational Biology, Division of Biological Sciences, University of Southern, Los Angeles, CA 90089, USA
| | - Jinjin Guo
- Department of Stem Cell Biology and Regenerative Medicine, Broad-CIRM Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Bill Hill
- MRC Human Genetics Unit, MRC Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Tracy Tran
- Department of Stem Cell Biology and Regenerative Medicine, Broad-CIRM Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Albert D Kim
- Department of Stem Cell Biology and Regenerative Medicine, Broad-CIRM Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jian Zhou
- Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY, USA; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Alicja Tadych
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Aaron Watters
- Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY, USA
| | - Aaron Wong
- Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY, USA
| | - Elizabeth Lovero
- Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY, USA
| | - Brendan H Grubbs
- Maternal Fetal Medicine Division, Department of Obstetrics and Gynecology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Matthew E Thornton
- Maternal Fetal Medicine Division, Department of Obstetrics and Gynecology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jill A McMahon
- Department of Stem Cell Biology and Regenerative Medicine, Broad-CIRM Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Andrew D Smith
- Molecular and Computational Biology, Division of Biological Sciences, University of Southern, Los Angeles, CA 90089, USA
| | - Seth W Ruffins
- Department of Stem Cell Biology and Regenerative Medicine, Broad-CIRM Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Chris Armit
- MRC Human Genetics Unit, MRC Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK; BGI Hong Kong, 26/F, Kings Wing Plaza 2, 1 On Kwan Street, Shek Mun, NT, Hong Kong
| | - Olga G Troyanskaya
- Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY, USA; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA; Department of Computer Science, Princeton University, Princeton, NJ, USA.
| | - Andrew P McMahon
- Department of Stem Cell Biology and Regenerative Medicine, Broad-CIRM Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
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38
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The unique biology of germinal center B cells. Immunity 2021; 54:1652-1664. [PMID: 34380063 DOI: 10.1016/j.immuni.2021.07.015] [Citation(s) in RCA: 104] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 04/08/2021] [Accepted: 07/15/2021] [Indexed: 12/16/2022]
Abstract
Germinal center (GC) B cells are the source of the high-affinity, class-switched antibodies required for protective immunity. The unique biology of GC B cells involves iterative rounds of antibody gene somatic hypermutation coupled to multiple selection and differentiation pathways. Recent advances in areas such as single cell and gene editing technologies have shed new light upon these complex and dynamic processes. We review these findings here and integrate them into the current understanding of GC B cell replication and death, the retention of high-affinity and class-switched B cells in the GC, and differentiation into plasma and memory cell effectors. We also discuss how the biology of GC responses relates to vaccine effectiveness and outline current and future challenges in the field.
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39
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Zonneville J, Wang M, Alruwaili MM, Smith B, Melnick M, Eng KH, Melendy T, Park BH, Iyer R, Fountzilas C, Bakin AV. Selective therapeutic strategy for p53-deficient cancer by targeting dysregulation in DNA repair. Commun Biol 2021; 4:862. [PMID: 34253820 PMCID: PMC8275734 DOI: 10.1038/s42003-021-02370-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Accepted: 06/09/2021] [Indexed: 02/06/2023] Open
Abstract
Breast carcinomas commonly carry mutations in the tumor suppressor p53, although therapeutic efforts to target mutant p53 have previously been unfruitful. Here we report a selective combination therapy strategy for treatment of p53 mutant cancers. Genomic data revealed that p53 mutant cancers exhibit high replication activity and express high levels of the Base-Excision Repair (BER) pathway, whereas experimental testing showed substantial dysregulation in BER. This defect rendered accumulation of DNA damage in p53 mutant cells upon treatment with deoxyuridine analogues. Notably, inhibition of poly (ADP-ribose) polymerase (PARP) greatly enhanced this response, whereas normal cells responded with activation of the p53-p21 axis and cell cycle arrest. Inactivation of either p53 or p21/CDKN1A conferred the p53 mutant phenotype. Preclinical animal studies demonstrated a greater anti-neoplastic efficacy of the drug combination (deoxyuridine analogue and PARP inhibitor) than either drug alone. This work illustrates a selective combination therapy strategy for p53 mutant cancers that will improve survival rates and outcomes for thousands of breast cancer patients.
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Affiliation(s)
- Justin Zonneville
- Department of Cancer Genetics and Genomics, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | - Moyi Wang
- Department of Cancer Genetics and Genomics, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | - Mohammed M Alruwaili
- Department of Cancer Genetics and Genomics, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
- Medical Laboratory Technology Department, Northern Border University, Arar City, Saudi Arabia
| | - Brandon Smith
- Department of Cancer Genetics and Genomics, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | - Megan Melnick
- Department of Cancer Genetics and Genomics, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | - Kevin H Eng
- Department of Cancer Genetics and Genomics, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | - Thomas Melendy
- Department of Microbiology & Immunology and Biochemistry, University at Buffalo, Buffalo, NY, USA
| | - Ben Ho Park
- The Breast Cancer Research Program, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Renuka Iyer
- Department of Medicine, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | - Christos Fountzilas
- Department of Medicine, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | - Andrei V Bakin
- Department of Cancer Genetics and Genomics, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA.
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40
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Moussa M, Măndoiu II. SC1: A Tool for Interactive Web-Based Single-Cell RNA-Seq Data Analysis. J Comput Biol 2021; 28:820-841. [PMID: 34115950 DOI: 10.1089/cmb.2021.0051] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Single-cell RNA-Seq (scRNA-Seq) is critical for studying cellular function and phenotypic heterogeneity as well as the development of tissues and tumors. In this study, we present SC1 a web-based highly interactive scRNA-Seq data analysis tool publicly accessible at https://sc1.engr.uconn.edu. The tool presents an integrated workflow for scRNA-Seq analysis, implements a novel method of selecting informative genes based on term-frequency inverse-document-frequency scores, and provides a broad range of methods for clustering, differential expression analysis, gene enrichment, interactive visualization, and cell cycle analysis. The tool integrates other single-cell omics data modalities such as T-cell receptor (TCR)-Seq and supports several single-cell sequencing technologies. In just a few steps, researchers can generate a comprehensive analysis and gain powerful insights from their scRNA-Seq data.
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Affiliation(s)
- Marmar Moussa
- Carole and Ray Neag Comprehensive Cancer Center, University of Connecticut School of Medicine, Farmington, Connecticut, USA
| | - Ion I Măndoiu
- Computer Science and Engineering Department, University of Connecticut, Storrs, Connecticut, USA
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41
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Wu W, Liu Y, Dai Q, Yan X, Wang Z. G2S3: A gene graph-based imputation method for single-cell RNA sequencing data. PLoS Comput Biol 2021; 17:e1009029. [PMID: 34003861 PMCID: PMC8189489 DOI: 10.1371/journal.pcbi.1009029] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2020] [Revised: 06/09/2021] [Accepted: 04/29/2021] [Indexed: 12/20/2022] Open
Abstract
Single-cell RNA sequencing technology provides an opportunity to study gene expression at single-cell resolution. However, prevalent dropout events result in high data sparsity and noise that may obscure downstream analyses in single-cell transcriptomic studies. We propose a new method, G2S3, that imputes dropouts by borrowing information from adjacent genes in a sparse gene graph learned from gene expression profiles across cells. We applied G2S3 and ten existing imputation methods to eight single-cell transcriptomic datasets and compared their performance. Our results demonstrated that G2S3 has superior overall performance in recovering gene expression, identifying cell subtypes, reconstructing cell trajectories, identifying differentially expressed genes, and recovering gene regulatory and correlation relationships. Moreover, G2S3 is computationally efficient for imputation in large-scale single-cell transcriptomic datasets.
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Affiliation(s)
- Weimiao Wu
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, United States of America
| | - Yunqing Liu
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, United States of America
| | - Qile Dai
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, United States of America
| | - Xiting Yan
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, United States of America
- Section of Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine, New Haven, Connecticut, United States of America
| | - Zuoheng Wang
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, United States of America
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42
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Guiducci G, Stojic L. Long Noncoding RNAs at the Crossroads of Cell Cycle and Genome Integrity. Trends Genet 2021; 37:528-546. [PMID: 33685661 DOI: 10.1016/j.tig.2021.01.006] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 12/28/2020] [Accepted: 01/18/2021] [Indexed: 12/14/2022]
Abstract
The cell cycle is controlled by guardian proteins that coordinate the process of cell growth and cell division. Alterations in these processes lead to genome instability, which has a causal link to many human diseases. Beyond their well-characterized role of influencing protein-coding genes, an increasing body of evidence has revealed that long noncoding RNAs (lncRNAs) actively participate in regulation of the cell cycle and safeguarding of genome integrity. LncRNAs are versatile molecules that act via a wide array of mechanisms. In this review, we discuss how lncRNAs are implicated in control of the cell cycle and maintenance of genome stability and how changes in lncRNA-regulatory networks lead to proliferative diseases such as cancer.
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Affiliation(s)
- Giulia Guiducci
- Barts Cancer Institute, Centre for Cancer Cell and Molecular Biology, John Vane Science Centre, Charterhouse Square, Queen Mary University of London, London EC1M 6BQ, UK
| | - Lovorka Stojic
- Barts Cancer Institute, Centre for Cancer Cell and Molecular Biology, John Vane Science Centre, Charterhouse Square, Queen Mary University of London, London EC1M 6BQ, UK.
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43
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Oh VKS, Li RW. Temporal Dynamic Methods for Bulk RNA-Seq Time Series Data. Genes (Basel) 2021; 12:352. [PMID: 33673721 PMCID: PMC7997275 DOI: 10.3390/genes12030352] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Revised: 02/19/2021] [Accepted: 02/22/2021] [Indexed: 02/06/2023] Open
Abstract
Dynamic studies in time course experimental designs and clinical approaches have been widely used by the biomedical community. These applications are particularly relevant in stimuli-response models under environmental conditions, characterization of gradient biological processes in developmental biology, identification of therapeutic effects in clinical trials, disease progressive models, cell-cycle, and circadian periodicity. Despite their feasibility and popularity, sophisticated dynamic methods that are well validated in large-scale comparative studies, in terms of statistical and computational rigor, are less benchmarked, comparing to their static counterparts. To date, a number of novel methods in bulk RNA-Seq data have been developed for the various time-dependent stimuli, circadian rhythms, cell-lineage in differentiation, and disease progression. Here, we comprehensively review a key set of representative dynamic strategies and discuss current issues associated with the detection of dynamically changing genes. We also provide recommendations for future directions for studying non-periodical, periodical time course data, and meta-dynamic datasets.
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Affiliation(s)
- Vera-Khlara S. Oh
- Animal Genomics and Improvement Laboratory, United States Department of Agriculture, Agricultural Research Service, Beltsville, MD 20705, USA;
- Department of Computer Science and Statistics, College of Natural Sciences, Jeju National University, Jeju City 63243, Korea
| | - Robert W. Li
- Animal Genomics and Improvement Laboratory, United States Department of Agriculture, Agricultural Research Service, Beltsville, MD 20705, USA;
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44
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Mahdessian D, Cesnik AJ, Gnann C, Danielsson F, Stenström L, Arif M, Zhang C, Le T, Johansson F, Schutten R, Bäckström A, Axelsson U, Thul P, Cho NH, Carja O, Uhlén M, Mardinoglu A, Stadler C, Lindskog C, Ayoglu B, Leonetti MD, Pontén F, Sullivan DP, Lundberg E. Spatiotemporal dissection of the cell cycle with single-cell proteogenomics. Nature 2021; 590:649-654. [PMID: 33627808 DOI: 10.1038/s41586-021-03232-9] [Citation(s) in RCA: 97] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2019] [Accepted: 01/12/2021] [Indexed: 01/31/2023]
Abstract
The cell cycle, over which cells grow and divide, is a fundamental process of life. Its dysregulation has devastating consequences, including cancer1-3. The cell cycle is driven by precise regulation of proteins in time and space, which creates variability between individual proliferating cells. To our knowledge, no systematic investigations of such cell-to-cell proteomic variability exist. Here we present a comprehensive, spatiotemporal map of human proteomic heterogeneity by integrating proteomics at subcellular resolution with single-cell transcriptomics and precise temporal measurements of individual cells in the cell cycle. We show that around one-fifth of the human proteome displays cell-to-cell variability, identify hundreds of proteins with previously unknown associations with mitosis and the cell cycle, and provide evidence that several of these proteins have oncogenic functions. Our results show that cell cycle progression explains less than half of all cell-to-cell variability, and that most cycling proteins are regulated post-translationally, rather than by transcriptomic cycling. These proteins are disproportionately phosphorylated by kinases that regulate cell fate, whereas non-cycling proteins that vary between cells are more likely to be modified by kinases that regulate metabolism. This spatially resolved proteomic map of the cell cycle is integrated into the Human Protein Atlas and will serve as a resource for accelerating molecular studies of the human cell cycle and cell proliferation.
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Affiliation(s)
- Diana Mahdessian
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Anthony J Cesnik
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden.,Department of Genetics, Stanford University, Stanford, CA, USA.,Chan Zuckerberg Biohub, San Francisco, San Francisco, CA, USA
| | - Christian Gnann
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden.,Chan Zuckerberg Biohub, San Francisco, San Francisco, CA, USA
| | - Frida Danielsson
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Lovisa Stenström
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Muhammad Arif
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Cheng Zhang
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Trang Le
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Fredric Johansson
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Rutger Schutten
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Anna Bäckström
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Ulrika Axelsson
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Peter Thul
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Nathan H Cho
- Chan Zuckerberg Biohub, San Francisco, San Francisco, CA, USA
| | - Oana Carja
- Department of Genetics, Stanford University, Stanford, CA, USA.,Chan Zuckerberg Biohub, San Francisco, San Francisco, CA, USA.,Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Mathias Uhlén
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Adil Mardinoglu
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden.,Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, London, UK
| | - Charlotte Stadler
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Cecilia Lindskog
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Burcu Ayoglu
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden
| | | | - Fredrik Pontén
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Devin P Sullivan
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Emma Lundberg
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden. .,Department of Genetics, Stanford University, Stanford, CA, USA. .,Chan Zuckerberg Biohub, San Francisco, San Francisco, CA, USA.
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45
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Dual RNA 3'-end processing of H2A.X messenger RNA maintains DNA damage repair throughout the cell cycle. Nat Commun 2021; 12:359. [PMID: 33441544 PMCID: PMC7807067 DOI: 10.1038/s41467-020-20520-6] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Accepted: 12/04/2020] [Indexed: 12/11/2022] Open
Abstract
Phosphorylated H2A.X is a critical chromatin marker of DNA damage repair (DDR) in higher eukaryotes. However, H2A.X gene expression remains relatively uncharacterised. Replication-dependent (RD) histone genes generate poly(A)- mRNA encoding new histones to package DNA during replication. In contrast, replication-independent (RI) histone genes synthesise poly(A)+ mRNA throughout the cell cycle, translated into histone variants that confer specific epigenetic patterns on chromatin. Remarkably H2AFX, encoding H2A.X, is a hybrid histone gene, generating both poly(A)+ and poly(A)- mRNA isoforms. Here we report that the selective removal of either mRNA isoform reveals different effects in different cell types. In some cells, RD H2A.X poly(A)- mRNA generates sufficient histone for deposition onto DDR associated chromatin. In contrast, cells making predominantly poly(A)+ mRNA require this isoform for de novo H2A.X synthesis, required for efficient DDR. This highlights the importance of differential H2A.X mRNA 3’-end processing in the maintenance of effective DDR. H2A.X histone variant gene encodes poly(A)+ and poly(A)- mRNA isoforms which are differentially expressed depending on cell lines. Here the authors show that upon DNA damage, cells expressing more poly(A)+ isoform require this isoform for de novo H2A.X synthesis while cells with more poly(A)- isoform have sufficient H2A.X present in chromatin.
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46
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Schwabe D, Formichetti S, Junker JP, Falcke M, Rajewsky N. The transcriptome dynamics of single cells during the cell cycle. Mol Syst Biol 2020; 16:e9946. [PMID: 33205894 PMCID: PMC7672610 DOI: 10.15252/msb.20209946] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 09/12/2020] [Accepted: 09/22/2020] [Indexed: 11/28/2022] Open
Abstract
The cell cycle is among the most basic phenomena in biology. Despite advances in single-cell analysis, dynamics and topology of the cell cycle in high-dimensional gene expression space remain largely unknown. We developed a linear analysis of transcriptome data which reveals that cells move along a planar circular trajectory in transcriptome space during the cycle. Non-cycling gene expression adds a third dimension causing helical motion on a cylinder. We find in immortalized cell lines that cell cycle transcriptome dynamics occur largely independently from other cellular processes. We offer a simple method ("Revelio") to order unsynchronized cells in time. Precise removal of cell cycle effects from the data becomes a straightforward operation. The shape of the trajectory implies that each gene is upregulated only once during the cycle, and only two dynamic components represented by groups of genes drive transcriptome dynamics. It indicates that the cell cycle has evolved to minimize changes of transcriptional activity and the related regulatory effort. This design principle of the cell cycle may be of relevance to many other cellular differentiation processes.
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Affiliation(s)
- Daniel Schwabe
- Mathematical Cell PhysiologyMax Delbrück Center for Molecular Medicine in the Helmholtz AssociationBerlinGermany
| | - Sara Formichetti
- Systems Biology of Gene Regulatory Elements, Berlin Institute for Medical Systems BiologyMax Delbrück Center for Molecular Medicine in the Helmholtz AssociationBerlinGermany
- Epigenetics and Neurobiology Unit, European Molecular Biology LaboratoryMonterotondoItaly
- Collaboration for Joint PhD Degree between European Molecular Biology Laboratory and Heidelberg University, Faculty of BiosciencesHeidelbergGermany
| | - Jan Philipp Junker
- Quantitative Developmental Biology, Berlin Institute for Medical Systems BiologyMax Delbrück Center for Molecular Medicine in the Helmholtz AssociationBerlinGermany
| | - Martin Falcke
- Mathematical Cell PhysiologyMax Delbrück Center for Molecular Medicine in the Helmholtz AssociationBerlinGermany
- Department of PhysicsHumboldt University BerlinBerlinGermany
| | - Nikolaus Rajewsky
- Systems Biology of Gene Regulatory Elements, Berlin Institute for Medical Systems BiologyMax Delbrück Center for Molecular Medicine in the Helmholtz AssociationBerlinGermany
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47
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Combes AJ, Courau T, Kuhn NF, Hu KH, Ray A, Chen WS, Cleary SJ, Chew NW, Kushnoor D, Reeder GC, Shen A, Tsui J, Hiam-Galvez KJ, Muñoz-Sandoval P, Zhu WS, Lee DS, Sun Y, You R, Magnen M, Rodriguez L, Leligdowicz A, Zamecnik CR, Loudermilk RP, Wilson MR, Ye CJ, Fragiadakis GK, Looney MR, Chan V, Ward A, Carrillo S, Matthay M, Erle DJ, Woodruff PG, Langelier C, Kangelaris K, Hendrickson CM, Calfee C, Rao AA, Krummel MF. Global Absence and Targeting of Protective Immune States in Severe COVID-19. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2020. [PMID: 33140050 DOI: 10.1101/2020.10.28.359935] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
While SARS-CoV-2 infection has pleiotropic and systemic effects in some patients, many others experience milder symptoms. We sought a holistic understanding of the severe/mild distinction in COVID-19 pathology, and its origins. We performed a whole-blood preserving single-cell analysis protocol to integrate contributions from all major cell types including neutrophils, monocytes, platelets, lymphocytes and the contents of serum. Patients with mild COVID-19 disease display a coordinated pattern of interferon-stimulated gene (ISG) expression across every cell population and these cells are systemically absent in patients with severe disease. Severe COVID-19 patients also paradoxically produce very high anti-SARS-CoV-2 antibody titers and have lower viral load as compared to mild disease. Examination of the serum from severe patients demonstrates that they uniquely produce antibodies with multiple patterns of specificity against interferon-stimulated cells and that those antibodies functionally block the production of the mild disease-associated ISG-expressing cells. Overzealous and auto-directed antibody responses pit the immune system against itself in many COVID-19 patients and this defines targets for immunotherapies to allow immune systems to provide viral defense. One Sentence Summary In severe COVID-19 patients, the immune system fails to generate cells that define mild disease; antibodies in their serum actively prevents the successful production of those cells.
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48
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Petasny M, Bentata M, Pawellek A, Baker M, Kay G, Salton M. Splicing to Keep Cycling: The Importance of Pre-mRNA Splicing during the Cell Cycle. Trends Genet 2020; 37:266-278. [PMID: 32950269 DOI: 10.1016/j.tig.2020.08.013] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 08/09/2020] [Accepted: 08/18/2020] [Indexed: 12/16/2022]
Abstract
Pre-mRNA splicing is a fundamental process in mammalian gene expression, and alternative splicing plays an extensive role in generating protein diversity. Because the majority of genes undergo pre-mRNA splicing, most cellular processes depend on proper spliceosome function. We focus on the cell cycle and describe its dependence on pre-mRNA splicing and accurate alternative splicing. We outline the key cell-cycle factors and their known alternative splicing isoforms. We discuss different levels of pre-mRNA splicing regulation such as post-translational modifications and changes in the expression of splicing factors. We describe the effect of chromatin dynamics on pre-mRNA splicing during the cell cycle. In addition, we focus on spliceosome component SF3B1, which is mutated in many types of cancer, and describe the link between SF3B1 and its inhibitors and the cell cycle.
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Affiliation(s)
- Mayra Petasny
- Department of Biochemistry and Molecular Biology, Institute for Medical Research Israel-Canada, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem 91120, Israel
| | - Mercedes Bentata
- Department of Biochemistry and Molecular Biology, Institute for Medical Research Israel-Canada, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem 91120, Israel
| | - Andrea Pawellek
- Centre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dundee, UK
| | - Mai Baker
- Department of Biochemistry and Molecular Biology, Institute for Medical Research Israel-Canada, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem 91120, Israel
| | - Gillian Kay
- Department of Biochemistry and Molecular Biology, Institute for Medical Research Israel-Canada, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem 91120, Israel
| | - Maayan Salton
- Department of Biochemistry and Molecular Biology, Institute for Medical Research Israel-Canada, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem 91120, Israel.
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49
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Biasini A, Smith AAT, Abdulkarim B, Ferreira da Silva M, Tan JY, Marques AC. The Contribution of lincRNAs at the Interface between Cell Cycle Regulation and Cell State Maintenance. iScience 2020; 23:101291. [PMID: 32619701 PMCID: PMC7334372 DOI: 10.1016/j.isci.2020.101291] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Revised: 04/24/2020] [Accepted: 06/15/2020] [Indexed: 12/27/2022] Open
Abstract
Cell cycle progression is controlled by the interplay of established cell cycle regulators. Changes in these regulators' activity underpin differences in cell cycle kinetics between cell types. We investigated whether long intergenic noncoding RNAs (lincRNAs) contribute to embryonic stem cell cycle adaptations. Using single-cell RNA sequencing data for mouse embryonic stem cells (mESCs) staged as G1, S, or G2/M we found differentially expressed lincRNAs are enriched among cell cycle-regulated genes. These lincRNAs (CC-lincRNAs) are co-expressed with genes involved in cell cycle regulation. We tested the impact of two CC-lincRNA candidates and show using CRISPR activation that increasing their expression is associated with deregulated cell cycle progression. Interestingly, CC-lincRNAs are often differentially expressed between G1 and S, their promoters are enriched in pluripotency transcription factor (TF) binding sites, and their transcripts are frequently co-regulated with genes involved in the maintenance of pluripotency, suggesting a contribution of CC-lincRNAs to mESC cell cycle adaptations. Genes differentially expressed between mESC cell cycle stages are enriched in lincRNAs CC-lincRNAs are co-expressed with cell cycle and pluripotency genes CC-lincRNAs are often mESC specific and their promoters enriched in pluripotency TFs Upregulation of two CC-lincRNAs results in deregulated mESC cell cycle progression
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Affiliation(s)
- Adriano Biasini
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | | | - Baroj Abdulkarim
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | | | - Jennifer Yihong Tan
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Ana Claudia Marques
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.
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50
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Pérez-Posada A, Dudin O, Ocaña-Pallarès E, Ruiz-Trillo I, Ondracka A. Cell cycle transcriptomics of Capsaspora provides insights into the evolution of cyclin-CDK machinery. PLoS Genet 2020; 16:e1008584. [PMID: 32176685 PMCID: PMC7098662 DOI: 10.1371/journal.pgen.1008584] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Revised: 03/26/2020] [Accepted: 12/23/2019] [Indexed: 12/19/2022] Open
Abstract
Progression through the cell cycle in eukaryotes is regulated on multiple levels. The main driver of the cell cycle progression is the periodic activity of cyclin-dependent kinase (CDK) complexes. In parallel, transcription during the cell cycle is regulated by a transcriptional program that ensures the just-in-time gene expression. Many core cell cycle regulators are widely conserved in eukaryotes, among them cyclins and CDKs; however, periodic transcriptional programs are divergent between distantly related species. In addition, many otherwise conserved cell cycle regulators have been lost and independently evolved in yeast, a widely used model organism for cell cycle research. For a better understanding of the evolution of the cell cycle regulation in opisthokonts, we investigated the transcriptional program during the cell cycle of the filasterean Capsaspora owczarzaki, a unicellular species closely related to animals. We developed a protocol for cell cycle synchronization in Capsaspora cultures and assessed gene expression over time across the entire cell cycle. We identified a set of 801 periodic genes that grouped into five clusters of expression over time. Comparison with datasets from other eukaryotes revealed that the periodic transcriptional program of Capsaspora is most similar to that of animal cells. We found that orthologues of cyclin A, B and E are expressed at the same cell cycle stages as in human cells and in the same temporal order. However, in contrast to human cells where these cyclins interact with multiple CDKs, Capsaspora cyclins likely interact with a single ancestral CDK1-3. Thus, the Capsaspora cyclin-CDK system could represent an intermediate state in the evolution of animal-like cyclin-CDK regulation. Overall, our results demonstrate that Capsaspora could be a useful unicellular model system for animal cell cycle regulation.
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Affiliation(s)
- Alberto Pérez-Posada
- Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), Barcelona, Catalonia, Spain
| | - Omaya Dudin
- Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), Barcelona, Catalonia, Spain
| | - Eduard Ocaña-Pallarès
- Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), Barcelona, Catalonia, Spain
| | - Iñaki Ruiz-Trillo
- Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), Barcelona, Catalonia, Spain
- Departament de Genètica, Microbiologia i Estadística, Universitat de Barcelona, Barcelona, Catalonia, Spain
- ICREA, Barcelona, Catalonia, Spain
| | - Andrej Ondracka
- Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), Barcelona, Catalonia, Spain
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