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Kwon J, Zhang J, Mok B, Allsup S, Kim C, Toretsky J, Han C. USP13 drives lung squamous cell carcinoma by switching lung club cell lineage plasticity. Mol Cancer 2023; 22:204. [PMID: 38093367 PMCID: PMC10717271 DOI: 10.1186/s12943-023-01892-x] [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: 08/18/2023] [Accepted: 10/27/2023] [Indexed: 12/17/2023] Open
Abstract
Lung squamous cell carcinoma (LUSC) is associated with high mortality and limited targeted therapies. USP13 is one of the most amplified genes in LUSC, yet its role in lung cancer is largely unknown. Here, we established a novel mouse model of LUSC by overexpressing USP13 on KrasG12D/+; Trp53flox/flox background (KPU). KPU-driven lung squamous tumors faithfully recapitulate key pathohistological, molecular features, and cellular pathways of human LUSC. We found that USP13 altered lineage-determining factors such as NKX2-1 and SOX2 in club cells of the airway and reinforced the fate of club cells to squamous carcinoma development. We showed a strong molecular association between USP13 and c-MYC, leading to the upregulation of squamous programs in murine and human lung cancer cells. Collectively, our data demonstrate that USP13 is a molecular driver of lineage plasticity in club cells and provide mechanistic insight that may have potential implications for the treatment of LUSC.
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Affiliation(s)
- Juntae Kwon
- Department of Oncology, Georgetown University School of Medicine, Washington D.C, USA
| | - Jinmin Zhang
- Department of Biochemistry and Molecular & Cellular Biology, Georgetown University School of Medicine, Washington D.C, USA
| | - Boram Mok
- Department of Oncology, Georgetown University School of Medicine, Washington D.C, USA
| | - Samuel Allsup
- Department of Biochemistry and Molecular & Cellular Biology, Georgetown University School of Medicine, Washington D.C, USA
| | - Chul Kim
- Division of Hematology and Oncology, Georgetown University School of Medicine, Washington D.C, USA
- MedStar Georgetown University Hospital, Washington D.C, USA
- Lombardi Comprehensive Cancer Center, Washington D.C, USA
| | - Jeffrey Toretsky
- Department of Oncology, Georgetown University School of Medicine, Washington D.C, USA
- Lombardi Comprehensive Cancer Center, Washington D.C, USA
- Departments of Pediatrics, Washington D.C, USA
| | - Cecil Han
- Department of Oncology, Georgetown University School of Medicine, Washington D.C, USA.
- Lombardi Comprehensive Cancer Center, Washington D.C, USA.
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Liu W, Yang H, Zhi F, Feng Y, Luo H, Zhu Y, Lei Y. Macrophage migration inhibitory factor may contribute to the occurrence of multiple primary lung adenocarcinomas. Clin Transl Med 2023; 13:e1368. [PMID: 37784249 PMCID: PMC10545892 DOI: 10.1002/ctm2.1368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 08/07/2023] [Indexed: 10/04/2023] Open
Abstract
BACKGROUND This study aimed to identify the key genes involved in the development of multiple primary lung cancers. METHODS Differential expression analysis was performed, followed by comparing the infiltration levels of 22 immune cell types between multiple and single primary lung adenocarcinomas. Marker genes for epithelial cells with different proportions between the two types of lung adenocarcinomas were identified. The common genes between the marker genes and differentially expressed genes were identified. Finally, the effects of the key genes were tested on the in vitro proliferation, migration and morphology. RESULTS The infiltration levels of helper follicular T cells, resting NK cells, activated NK cells, M2 macrophages and resting mast cells were higher in the patients with multiple than in those with single primary lung adenocarcinomas. A total of 1553 differentially expressed genes and 4414 marker genes of epithelial cells were identified. Logistic regression analysis was performed on the 164 resulting genes. The macrophage migration inhibitory factor expression was positively associated with the occurrence of multiple primary lung adenocarcinomas. Moreover, its signalling pathway was the key pathway among the epithelial cells and multiple and single primary lung adenocarcinoma cells, and it was upregulated in lung adenocarcinoma cells. It also increased the expression of lung cancer markers, including NES and CA125, induced morphological changes in alveolar epithelial type II cells, and promoted their proliferation, migration and invasion. CONCLUSIONS Multiple and single primary lung adenocarcinomas have different tumour immune microenvironments, and migration inhibitory factor may be a key factor in the occurrence of multiple primary lung adenocarcinomas.
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Affiliation(s)
- Wei Liu
- Department of Thoracic SurgeryThe First Affiliated HospitalSun Yat‐sen UniversityGuangzhouGuangdongChina
| | - Hao‐Shuai Yang
- Department of Thoracic SurgeryChina‐Japan Friendship HospitalBeijingChina
| | - Fei‐Hang Zhi
- Department of Thoracic SurgeryThe First Affiliated HospitalSun Yat‐sen UniversityGuangzhouGuangdongChina
| | - Yan‐Fen Feng
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer MedicineSun Yat‐sen University Cancer CenterGuangzhouGuangdongChina
- Department of PathologySun Yat‐sen University Cancer CenterGuangzhouGuangdongChina
| | - Hong‐He Luo
- Department of Thoracic SurgeryThe First Affiliated HospitalSun Yat‐sen UniversityGuangzhouGuangdongChina
| | - Ying Zhu
- Department of RadiologyThe First Affiliated HospitalSun Yat‐sen UniversityGuangzhouGuangdongChina
| | - Yi‐Yan Lei
- Department of Thoracic SurgeryThe First Affiliated HospitalSun Yat‐sen UniversityGuangzhouGuangdongChina
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3
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Siegl D, Kruchem M, Jansky S, Eichler E, Thies D, Hartwig U, Schuppan D, Bockamp E. A PCR protocol to establish standards for routine mycoplasma testing that by design detects over ninety percent of all known mycoplasma species. iScience 2023; 26:106724. [PMID: 37216121 PMCID: PMC10192841 DOI: 10.1016/j.isci.2023.106724] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 02/07/2023] [Accepted: 04/19/2023] [Indexed: 05/24/2023] Open
Abstract
Mycoplasma infection leads to false and non-reproducible scientific data and poses a risk to human health. Despite strict guidelines calling for regular mycoplasma screening, there is no universal and widely established standard procedure. Here, we describe a reliable and cost-effective PCR method that establishes a universal protocol for mycoplasma testing. The applied strategy utilizes ultra-conserved eukaryotic and mycoplasma sequence primers covering by design 92% of all species in the six orders of the class Mollicutes within the phylum Mycoplasmatota and is applicable to mammalian and many non-mammalian cell types. This method can stratify mycoplasma screening and is suitable as a common standard for routine mycoplasma testing.
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Affiliation(s)
- Dominik Siegl
- Institute of Translational Immunology (TIM), University Medical Center of the Johannes Gutenberg-University, Mainz 55131, Germany
| | - Marie Kruchem
- Institute of Translational Immunology (TIM), University Medical Center of the Johannes Gutenberg-University, Mainz 55131, Germany
| | - Sandrine Jansky
- Institute of Translational Immunology (TIM), University Medical Center of the Johannes Gutenberg-University, Mainz 55131, Germany
| | - Emma Eichler
- Institute of Translational Immunology (TIM), University Medical Center of the Johannes Gutenberg-University, Mainz 55131, Germany
| | - Dorothe Thies
- Institute of Translational Immunology (TIM), University Medical Center of the Johannes Gutenberg-University, Mainz 55131, Germany
| | - Udo Hartwig
- Department of Medicine III Hematology & Medical Oncology, University Medical Center of the Johannes Gutenberg-University, Mainz 55131, Germany
- Research Center for Immunotherapy, University Medical Center of the Johannes Gutenberg-University, Mainz 55131, Germany
| | - Detlef Schuppan
- Institute of Translational Immunology (TIM), University Medical Center of the Johannes Gutenberg-University, Mainz 55131, Germany
- ImmuneNTech GmbH, Wendelsheim 55234, Germany
- Division of Gastroenterology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA
- Research Center for Immunotherapy, University Medical Center of the Johannes Gutenberg-University, Mainz 55131, Germany
| | - Ernesto Bockamp
- Institute of Translational Immunology (TIM), University Medical Center of the Johannes Gutenberg-University, Mainz 55131, Germany
- ImmuneNTech GmbH, Wendelsheim 55234, Germany
- Research Center for Immunotherapy, University Medical Center of the Johannes Gutenberg-University, Mainz 55131, Germany
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4
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Keyl P, Bischoff P, Dernbach G, Bockmayr M, Fritz R, Horst D, Blüthgen N, Montavon G, Müller KR, Klauschen F. Single-cell gene regulatory network prediction by explainable AI. Nucleic Acids Res 2023; 51:e20. [PMID: 36629274 PMCID: PMC9976884 DOI: 10.1093/nar/gkac1212] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 11/16/2022] [Accepted: 12/06/2022] [Indexed: 01/12/2023] Open
Abstract
The molecular heterogeneity of cancer cells contributes to the often partial response to targeted therapies and relapse of disease due to the escape of resistant cell populations. While single-cell sequencing has started to improve our understanding of this heterogeneity, it offers a mostly descriptive view on cellular types and states. To obtain more functional insights, we propose scGeneRAI, an explainable deep learning approach that uses layer-wise relevance propagation (LRP) to infer gene regulatory networks from static single-cell RNA sequencing data for individual cells. We benchmark our method with synthetic data and apply it to single-cell RNA sequencing data of a cohort of human lung cancers. From the predicted single-cell networks our approach reveals characteristic network patterns for tumor cells and normal epithelial cells and identifies subnetworks that are observed only in (subgroups of) tumor cells of certain patients. While current state-of-the-art methods are limited by their ability to only predict average networks for cell populations, our approach facilitates the reconstruction of networks down to the level of single cells which can be utilized to characterize the heterogeneity of gene regulation within and across tumors.
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Affiliation(s)
- Philipp Keyl
- Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Berlin, Charitéplatz 1, 10117 Berlin, Germany
| | - Philip Bischoff
- Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Berlin, Charitéplatz 1, 10117 Berlin, Germany.,Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Anna-Louisa-Karsch-Straße 2, 10178 Berlin, Germany.,German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Berlin partner site, Germany
| | - Gabriel Dernbach
- Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Berlin, Charitéplatz 1, 10117 Berlin, Germany.,BIFOLD - Berlin Institute for the Foundations of Learning and Data, Berlin, Germany
| | - Michael Bockmayr
- Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Berlin, Charitéplatz 1, 10117 Berlin, Germany.,Department of Pediatric Hematology and Oncolog, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246 Hamburg, Germany.,Mildred Scheel Cancer Career Center HaTriCS4, University Medical Center Hamburg-Eppendorf Martinistr. 52, 20246 Hamburg, Germany
| | - Rebecca Fritz
- Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Berlin, Charitéplatz 1, 10117 Berlin, Germany
| | - David Horst
- Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Berlin, Charitéplatz 1, 10117 Berlin, Germany.,German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Berlin partner site, Germany
| | - Nils Blüthgen
- Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Berlin, Charitéplatz 1, 10117 Berlin, Germany.,Institut für Biologie, Humboldt University, Free University of Berlin, Unter den Linden 6, 10099 Berlin, Germany
| | - Grégoire Montavon
- BIFOLD - Berlin Institute for the Foundations of Learning and Data, Berlin, Germany.,Machine Learning Group, Technical University of Berlin, Marchstr. 23, 10587 Berlin, Germany
| | - Klaus-Robert Müller
- BIFOLD - Berlin Institute for the Foundations of Learning and Data, Berlin, Germany.,Machine Learning Group, Technical University of Berlin, Marchstr. 23, 10587 Berlin, Germany.,Department of Artificial Intelligence, Korea University, Seoul 136-713, South Korea.,Max-Planck-Institute for Informatics, Stuhlsatzenhausweg 4, 66123 Saarbrücken, Germany
| | - Frederick Klauschen
- Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Berlin, Charitéplatz 1, 10117 Berlin, Germany.,German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Berlin partner site, Germany.,BIFOLD - Berlin Institute for the Foundations of Learning and Data, Berlin, Germany.,Institute of Pathology, Ludwig-Maximilians-University Munich, Thalkirchner Str. 36, 80337 München, Germany.,German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Munich partner site, Germany
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Chen Y, Toth R, Chocarro S, Weichenhan D, Hey J, Lutsik P, Sawall S, Stathopoulos GT, Plass C, Sotillo R. Club cells employ regeneration mechanisms during lung tumorigenesis. Nat Commun 2022; 13:4557. [PMID: 35931677 PMCID: PMC9356049 DOI: 10.1038/s41467-022-32052-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2021] [Accepted: 07/12/2022] [Indexed: 11/09/2022] Open
Abstract
The high plasticity of lung epithelial cells, has for many years, confounded the correct identification of the cell-of-origin of lung adenocarcinoma (LUAD), one of the deadliest malignancies worldwide. Here, we employ lineage-tracing mouse models to investigate the cell of origin of Eml4-Alk LUAD, and show that Club and Alveolar type 2 (AT2) cells give rise to tumours. We focus on Club cell originated tumours and find that Club cells experience an epigenetic switch by which they lose their lineage fidelity and gain an AT2-like phenotype after oncogenic transformation. Single-cell transcriptomic analyses identified two trajectories of Club cell evolution which are similar to the ones used during lung regeneration, suggesting that lung epithelial cells leverage on their plasticity and intrinsic regeneration mechanisms to give rise to a tumour. Together, this study highlights the role of Club cells in LUAD initiation, identifies the mechanism of Club cell lineage infidelity, confirms the presence of these features in human tumours, and unveils key mechanisms conferring LUAD heterogeneity.
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Affiliation(s)
- Yuanyuan Chen
- Division of Molecular Thoracic Oncology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
| | - Reka Toth
- Division of Molecular Thoracic Oncology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany.,Division of Cancer Epigenomics, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany.,Bioinformatics Platform, Luxembourg Institute of Health, Strassen, Luxembourg
| | - Sara Chocarro
- Division of Molecular Thoracic Oncology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany.,Ruprecht Karl University of Heidelberg, Heidelberg, Germany
| | - Dieter Weichenhan
- Division of Cancer Epigenomics, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
| | - Joschka Hey
- Division of Cancer Epigenomics, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany.,Ruprecht Karl University of Heidelberg, Heidelberg, Germany
| | - Pavlo Lutsik
- Division of Cancer Epigenomics, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
| | - Stefan Sawall
- X-Ray Imaging and CT, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
| | - Georgios T Stathopoulos
- Comprehensive Pneumology Center (CPC) and Institute for Lung Biology and Disease (iLBD), Helmholtz Center Munich-German Research Center for Environmental Health (HMGU), Max-Lebsche-Platz 31, 81377, Munich, Bavaria, Germany.,German Center for Lung Research (DZL), Heidelberg, Germany
| | - Christoph Plass
- Division of Cancer Epigenomics, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany.,German Center for Lung Research (DZL), Heidelberg, Germany.,Translational Lung Research Center Heidelberg (TRLC), Heidelberg, Germany.,German Consortium for Translational Cancer Research (DKTK), 69120, Heidelberg, Germany
| | - Rocio Sotillo
- Division of Molecular Thoracic Oncology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany. .,German Center for Lung Research (DZL), Heidelberg, Germany. .,Translational Lung Research Center Heidelberg (TRLC), Heidelberg, Germany. .,German Consortium for Translational Cancer Research (DKTK), 69120, Heidelberg, Germany.
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