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Boutanquoi PM, Pommerolle L, Dondaine L, Tanguy J, Bellaye PS, Biziorek L, Gautier-Isola M, Mari B, Masnikov D, Rocchi P, Finetti P, Korczak P, Vialet B, Barthelemy P, Garrido C, Bonniaud P, Burgy O, Goirand F. An antisense oligonucleotide targeting the heat-shock protein HSPB5 as an innovative therapeutic approach in pulmonary fibrosis. Br J Pharmacol 2025; 182:2713-2729. [PMID: 40033950 DOI: 10.1111/bph.17470] [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: 12/21/2023] [Revised: 12/11/2024] [Accepted: 12/31/2024] [Indexed: 03/05/2025] Open
Abstract
BACKGROUND AND PURPOSE Idiopathic pulmonary fibrosis (IPF) is a fatal disease characterized by fibroblast activation and abnormal accumulation of extracellular matrix in the lungs. We previously demonstrated the importance of the heat shock protein αB-crystallin (HSPB5) in TGF-β1 profibrotic signalling, which suggests that HSPB5 could be a new therapeutic target for the treatment of IPF. The purpose of this study was thus to develop antisense oligonucleotides targeting HSPB5 and to study their effects on the development of experimental pulmonary fibrosis. EXPERIMENTAL APPROACH Specific antisense oligonucleotides (ASO) were designed and screened in vitro, based on their ability to inhibit human and murine HSPB5 expression. The selected ASO22 was characterized in vitro in human fibroblast CCD-19Lu cells and A549 epithelial pulmonary cells, as well as in vivo using a mouse model of bleomycin-induced pulmonary fibrosis. KEY RESULTS ASO22 was selected for its capacity to inhibit TGF-β1-induced expression of HSPB5 and additional key markers of fibrosis such as plasminogen activator inhibitor-1, collagen, fibronectin and α-smooth muscle actin in fibroblastic human CCD-19Lu cells as well as plasminogen activator inhibitor-1 and α-smooth muscle actin in pulmonary epithelial A549 cells. Intra-tracheal or intravenous administration of ASO22 in bleomycin-induced pulmonary fibrotic mice decreased HSPB5 expression and reduced fibrosis, as demonstrated by decreased pulmonary remodelling, collagen accumulation and Acta2 and Col1a1 expression. CONCLUSION AND IMPLICATIONS Our results suggest that an antisense oligonucleotide strategy targeting HSPB5 could be of interest for the treatment of IPF.
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Affiliation(s)
- Pierre-Marie Boutanquoi
- INSERM U1231, Center for Translational and Molecular Medicine, Labex LIPSTIC and Label of Excellence From La Ligue Nationale Contre le Cancer, Dijon, France
- UFR des Sciences de Santé, Université Bourgogne Europe, Dijon, France
| | - Lenny Pommerolle
- INSERM U1231, Center for Translational and Molecular Medicine, Labex LIPSTIC and Label of Excellence From La Ligue Nationale Contre le Cancer, Dijon, France
- UFR des Sciences de Santé, Université Bourgogne Europe, Dijon, France
| | - Lucile Dondaine
- INSERM U1231, Center for Translational and Molecular Medicine, Labex LIPSTIC and Label of Excellence From La Ligue Nationale Contre le Cancer, Dijon, France
- Centre de Référence Constitutif des Maladies Pulmonaires Rares de l'Adultes de Dijon, réseau OrphaLung, Filière RespiFil, Centre Hospitalier Universitaire, Dijon, France
| | - Julie Tanguy
- INSERM U1231, Center for Translational and Molecular Medicine, Labex LIPSTIC and Label of Excellence From La Ligue Nationale Contre le Cancer, Dijon, France
- UFR des Sciences de Santé, Université Bourgogne Europe, Dijon, France
| | - Pierre-Simon Bellaye
- INSERM U1231, Center for Translational and Molecular Medicine, Labex LIPSTIC and Label of Excellence From La Ligue Nationale Contre le Cancer, Dijon, France
- Centre de Référence Constitutif des Maladies Pulmonaires Rares de l'Adultes de Dijon, réseau OrphaLung, Filière RespiFil, Centre Hospitalier Universitaire, Dijon, France
- Centre Georges-François Leclerc, Service de médecine nucléaire, Plateforme d'imagerie et de radiothérapie précliniques, Dijon, France
| | - Léo Biziorek
- INSERM U1231, Center for Translational and Molecular Medicine, Labex LIPSTIC and Label of Excellence From La Ligue Nationale Contre le Cancer, Dijon, France
- UFR des Sciences de Santé, Université Bourgogne Europe, Dijon, France
- Centre de Référence Constitutif des Maladies Pulmonaires Rares de l'Adultes de Dijon, réseau OrphaLung, Filière RespiFil, Centre Hospitalier Universitaire, Dijon, France
| | | | - Bernard Mari
- Université Côte d'Azur - CNRS UMR7275 - Inserm U1323, Sophia Antipolis, France
| | - Denis Masnikov
- INSERM U1231, Center for Translational and Molecular Medicine, Labex LIPSTIC and Label of Excellence From La Ligue Nationale Contre le Cancer, Dijon, France
- UFR des Sciences de Santé, Université Bourgogne Europe, Dijon, France
| | - Palma Rocchi
- Aix Marseille Univ, CNRS, CINAM, ERL INSERM U1326, CERIMED, Marseille, France
| | - Pascal Finetti
- Département d'Oncologie Prédictive, Centre de Recherche en Cancérologie de Marseille, Institut Paoli-Calmettes, CRCM, Inserm UMR1068, CNRS UMR7258, Aix-Marseille University, Marseille, France
| | - Patricia Korczak
- ARNA Laboratory, INSERM U1212, CNRS UMR 5320, University of Bordeaux, Bordeaux, France
| | - Brune Vialet
- ARNA Laboratory, INSERM U1212, CNRS UMR 5320, University of Bordeaux, Bordeaux, France
| | - Philippe Barthelemy
- ARNA Laboratory, INSERM U1212, CNRS UMR 5320, University of Bordeaux, Bordeaux, France
| | - Carmen Garrido
- INSERM U1231, Center for Translational and Molecular Medicine, Labex LIPSTIC and Label of Excellence From La Ligue Nationale Contre le Cancer, Dijon, France
- UFR des Sciences de Santé, Université Bourgogne Europe, Dijon, France
- Cancer Centre George-François Leclerc, Dijon, France
| | - Philippe Bonniaud
- INSERM U1231, Center for Translational and Molecular Medicine, Labex LIPSTIC and Label of Excellence From La Ligue Nationale Contre le Cancer, Dijon, France
- UFR des Sciences de Santé, Université Bourgogne Europe, Dijon, France
- Centre de Référence Constitutif des Maladies Pulmonaires Rares de l'Adultes de Dijon, réseau OrphaLung, Filière RespiFil, Centre Hospitalier Universitaire, Dijon, France
- Institut Universitaire du Poumon Dijon-Bourgogne, Centre Hospitalier Universitaire, Dijon, France
| | - Olivier Burgy
- INSERM U1231, Center for Translational and Molecular Medicine, Labex LIPSTIC and Label of Excellence From La Ligue Nationale Contre le Cancer, Dijon, France
- UFR des Sciences de Santé, Université Bourgogne Europe, Dijon, France
- Centre de Référence Constitutif des Maladies Pulmonaires Rares de l'Adultes de Dijon, réseau OrphaLung, Filière RespiFil, Centre Hospitalier Universitaire, Dijon, France
| | - Françoise Goirand
- INSERM U1231, Center for Translational and Molecular Medicine, Labex LIPSTIC and Label of Excellence From La Ligue Nationale Contre le Cancer, Dijon, France
- UFR des Sciences de Santé, Université Bourgogne Europe, Dijon, France
- Centre de Référence Constitutif des Maladies Pulmonaires Rares de l'Adultes de Dijon, réseau OrphaLung, Filière RespiFil, Centre Hospitalier Universitaire, Dijon, France
- Laboratoire de Pharmacologie et Toxicologie, Centre Hospitalier Universitaire Dijon-Bourgogne, Dijon, France
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2
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Seasock MJ, Shafiquzzaman M, Ruiz-Echartea ME, Kanchi RS, Tran BT, Simon LM, Meyer MD, Erice PA, Lotlikar SL, Wenlock SC, Ochsner SA, Enright A, Carisey AF, Romero F, Rosas IO, King KY, McKenna NJ, Coarfa C, Rodriguez A. Let-7 restrains an epigenetic circuit in AT2 cells to prevent fibrogenic intermediates in pulmonary fibrosis. Nat Commun 2025; 16:4353. [PMID: 40348760 PMCID: PMC12065893 DOI: 10.1038/s41467-025-59641-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2024] [Accepted: 04/30/2025] [Indexed: 05/14/2025] Open
Abstract
MicroRNA-mediated post-transcriptional regulation of lung alveolar type 2 (AT2) and AT1 cell differentiation remains understudied. Here, we demonstrate that the let-7 miRNA family plays a homeostatic role in AT2 quiescence by preventing the uncontrolled accumulation of AT2 transitional cells and promoting AT1 differentiation. Using mouse and organoid models, we show that genetic ablation of let-7a1/let-7f1/let-7d cluster (let-7afd) in AT2 cells prevents AT1 differentiation and leads to KRT8 transitional cell accumulation in progressive pulmonary fibrosis. Integration of AGO2-eCLIP with RNA-sequencing identified direct let-7 targets within an oncogene feed-forward regulatory network, including BACH1/EZH2/MYC, which drives an aberrant fibrotic cascade. Additional CUT&RUN-sequencing analyses revealed that let-7afd loss disrupts histone acetylation and methylation, driving epigenetic reprogramming and altered gene transcription in profibrotic AT2 cells. This study identifies let-7 as a central hub linking unchecked oncogenic signaling to impaired AT2 cell plasticity and fibrogenesis.
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Grants
- HL140398 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- R35 HL155672 NHLBI NIH HHS
- S10 RR024574 NCRR NIH HHS
- HL155672 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- F31 HL164287 NHLBI NIH HHS
- R01 HL140398 NHLBI NIH HHS
- HL167814 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- T32 GM136554 NIGMS NIH HHS
- HL164287 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- R01 HL167814 NHLBI NIH HHS
- P42 ES027725 NIEHS NIH HHS
- GM136554 U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS)
- P30 ES030285 NIEHS NIH HHS
- P30 CA125123 NCI NIH HHS
- U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS)
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Affiliation(s)
- Matthew J Seasock
- Immunology & Microbiology Graduate Program, Baylor College of Medicine, Houston, TX, USA
- Department of Medicine, Section of Immunology, Allergy & Rheumatology, Baylor College of Medicine, Houston, TX, USA
| | - Md Shafiquzzaman
- Department of Medicine, Section of Immunology, Allergy & Rheumatology, Baylor College of Medicine, Houston, TX, USA
| | - Maria E Ruiz-Echartea
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, USA
| | - Rupa S Kanchi
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, USA
- Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, USA
| | - Brandon T Tran
- Cancer & Cell Biology Graduate Program, Baylor College of Medicine, Houston, TX, USA
- Department of Pediatrics, Division of Infectious Diseases, Texas Children's Hospital, Baylor College of Medicine, Houston, TX, USA
| | - Lukas M Simon
- Verna & Marrs McLean Department of Biochemistry and Molecular Pharmacology, Baylor College of Medicine, Houston, TX, USA
| | - Matthew D Meyer
- Shared Equipment Authority, Rice University, Houston, TX, USA
| | - Phillip A Erice
- Immunology & Microbiology Graduate Program, Baylor College of Medicine, Houston, TX, USA
- Department of Medicine, Section of Immunology, Allergy & Rheumatology, Baylor College of Medicine, Houston, TX, USA
| | - Shivani L Lotlikar
- Department of Medicine, Section of Immunology, Allergy & Rheumatology, Baylor College of Medicine, Houston, TX, USA
| | | | - Scott A Ochsner
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, USA
| | - Anton Enright
- Department of Pathology, University of Cambridge, Cambridge, United Kingdom
| | - Alex F Carisey
- William T. Shearer Center for Immunobiology, Texas Children's Hospital, Houston, TX, USA
- Department of Cell and Molecular Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Freddy Romero
- Department of Medicine, Section of Pulmonary, Critical Care and Sleep Medicine, Baylor College of Medicine, Houston, TX, USA
- Vertex Pharmaceuticals, 3215 Merryfield Row, San Diego, CA, USA
| | - Ivan O Rosas
- Department of Medicine, Section of Pulmonary, Critical Care and Sleep Medicine, Baylor College of Medicine, Houston, TX, USA
| | - Katherine Y King
- Department of Pediatrics, Division of Infectious Diseases, Texas Children's Hospital, Baylor College of Medicine, Houston, TX, USA
| | - Neil J McKenna
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, USA
| | - Cristian Coarfa
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, USA
- Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, USA
| | - Antony Rodriguez
- Department of Medicine, Section of Immunology, Allergy & Rheumatology, Baylor College of Medicine, Houston, TX, USA.
- Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, USA.
- Center for Translational Research on Inflammatory Diseases, Michael E. Debakey VA Medical Center, Baylor College of Medicine, Houston, TX, USA.
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3
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Yi E, Li H, Liu Y, Li Q, Xie C, Sun R, Wu F, Deng Z, Zhou K, Wang H, Ran X, Zhou Y, Ran P. An integrated machine learning model of transcriptomic genes in multi-center chronic obstructive pulmonary disease reveals the causal role of TIMP4 in airway epithelial cell. Respir Res 2025; 26:158. [PMID: 40269868 PMCID: PMC12020095 DOI: 10.1186/s12931-025-03238-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2024] [Accepted: 04/15/2025] [Indexed: 04/25/2025] Open
Abstract
BACKGROUND Chronic obstructive pulmonary disease (COPD) is a heterogeneous syndrome, resulting in inconsistent findings across studies. Identifying a core set of genes consistently involved in COPD pathogenesis, independent of patient variability, is essential. METHODS We integrated lung tissue sequencing data from patients with COPD across two centers. We used weighted gene co-expression network analysis and machine learning to identify 13 potential pathogenic genes common to both centers. Additionally, a gene-based model was constructed to distinguish COPD at the molecular level and validated in independent cohorts. Gene expression in specific cell types was analyzed, and Mendelian randomization was used to confirm associations between candidate genes and lung function/COPD. Preliminary in vitro functional validation was performed on prioritized core candidate genes. RESULTS Tissue inhibitor of metalloproteinase 4 (TIMP4) was identified as a key pathogenic gene and validated in COPD cohorts. Further analysis using single-cell sequencing from mice and patients with COPD revealed that TIMP4 is involved in ciliated cells. In primary human airway epithelial cells cultured at the air-liquid interface, TIMP4 overexpression reduced ciliated cell numbers. CONCLUSIONS We developed a 13-gene model for distinguishing COPD at the molecular level and identified TIMP4 as a potential hub pathogenic gene. This finding provides insights into shared disease mechanisms and positions TIMP4 as a promising therapeutic target for further investigation.
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Affiliation(s)
- Erkang Yi
- Guangzhou National Laboratory, No.9 Xing Dao Huan Bei Road, Guangzhou International BioIsland, Guangzhou, 510005, Guangdong, China
| | - Haiqing Li
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, No.195 Dong Feng Xi Road, Guangzhou, 510182, Guangdong, China
| | - Yu Liu
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, No.195 Dong Feng Xi Road, Guangzhou, 510182, Guangdong, China
| | - Qingyang Li
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, No.195 Dong Feng Xi Road, Guangzhou, 510182, Guangdong, China
| | - Chengshu Xie
- Guangzhou National Laboratory, No.9 Xing Dao Huan Bei Road, Guangzhou International BioIsland, Guangzhou, 510005, Guangdong, China
| | - Ruining Sun
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, No.195 Dong Feng Xi Road, Guangzhou, 510182, Guangdong, China
| | - Fan Wu
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, No.195 Dong Feng Xi Road, Guangzhou, 510182, Guangdong, China
| | - Zhishan Deng
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, No.195 Dong Feng Xi Road, Guangzhou, 510182, Guangdong, China
| | - Kunning Zhou
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, No.195 Dong Feng Xi Road, Guangzhou, 510182, Guangdong, China
| | - Hairong Wang
- Guangzhou National Laboratory, No.9 Xing Dao Huan Bei Road, Guangzhou International BioIsland, Guangzhou, 510005, Guangdong, China
| | - Xinru Ran
- GMU-GIBH Joint School of Life Sciences, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Yumin Zhou
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, No.195 Dong Feng Xi Road, Guangzhou, 510182, Guangdong, China.
- Guangzhou National Laboratory, No.9 Xing Dao Huan Bei Road, Guangzhou International BioIsland, Guangzhou, 510005, Guangdong, China.
| | - Pixin Ran
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, No.195 Dong Feng Xi Road, Guangzhou, 510182, Guangdong, China.
- Guangzhou National Laboratory, No.9 Xing Dao Huan Bei Road, Guangzhou International BioIsland, Guangzhou, 510005, Guangdong, China.
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Shao S, Cao S, Chen Y, Zhang Z, Zhaohui T. Immunological Features and Potential Biomarkers of Systemic Sclerosis-Associated Interstitial Lung Disease and Idiopathic Pulmonary Fibrosis. THE CLINICAL RESPIRATORY JOURNAL 2025; 19:e70072. [PMID: 40165483 PMCID: PMC11959098 DOI: 10.1111/crj.70072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/09/2024] [Revised: 03/01/2025] [Accepted: 03/17/2025] [Indexed: 04/02/2025]
Abstract
BACKGROUND This study aims to summarize the similarities and differences in immune cell characteristics, and potential therapeutic targets between systemic sclerosis-associated interstitial lung disease (SSc-ILD) and idiopathic pulmonary fibrosis (IPF). METHODS This study included SSc-ILD and SSc-nonILD patients who were admitted to Beijing Chaoyang Hospital between April 4th, 2013, to June 30th, 2023. Publicly available datasets, including peripheral blood monocular cell (pbmc) single-cell data, SSc, SSc-ILD pbmc transcriptome data, and SSc-ILD, IPF lung tissue transcriptome data were analyzed. Statistical analyses were conducted using the SPSS and R software, employing standard statistical methods and bioinformatics packages such as Seurat, DESeq2, enrichR, and CellChat. RESULTS The results revealed that the CD4+/CD8+ T cell ratio of pbmc in SSc-ILD patients was significantly higher than in SSc-nonILD patients. In IPF patients, an elevated CD4+/CD8+ T cell ratio was also observed in progressive group, and Treg and mature CD4+ T cells might cause this change. JAK-STAT pathway and the cytokine-cytokine receptor interaction pathway were activated in peripheral blood T cells of IPF patients. The CD30, CD40, and FLT3 signaling pathways were found to play crucial roles in T cell interactions with other immune cells among IPF patients. SPA17 as a commonly upregulated gene among SSc, SSc-ILD, and IPF pbmc and lung, with its expression correlating positively with disease severity and lung function progression. CONCLUSION CD4+/CD8+ T cell ratio might associate with ILD initiation and progression; Treg cells and mature CD4+ T cells play key roles of it. SPA17 might serve as a pan-ILD marker and associated with lung function progression.
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Affiliation(s)
- Shuai Shao
- Department of Respiratory and Critical Care Medicine, Beijing Institute of Respiratory Medicine, Beijing Chao‐Yang HospitalCapital Medical UniversityBeijingChina
| | - Siyu Cao
- Department of Respiratory and Critical Care Medicine, Beijing Institute of Respiratory Medicine, Beijing Chao‐Yang HospitalCapital Medical UniversityBeijingChina
| | - Yusha Chen
- Department of Respiratory and Critical Care Medicine, Beijing Institute of Respiratory Medicine, Beijing Chao‐Yang HospitalCapital Medical UniversityBeijingChina
| | - Zhijin Zhang
- Department of Respiratory and Critical Care Medicine, Beijing Institute of Respiratory Medicine, Beijing Chao‐Yang HospitalCapital Medical UniversityBeijingChina
| | - Tong Zhaohui
- Department of Respiratory and Critical Care Medicine, Beijing Institute of Respiratory Medicine, Beijing Chao‐Yang HospitalCapital Medical UniversityBeijingChina
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5
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Seasock MJ, Shafiquzzaman M, Ruiz-Echartea ME, Kanchi RS, Tran BT, Simon LM, Meyer MD, Erice PA, Lotlikar SL, Wenlock SC, Ochsner SA, Enright A, Carisey AF, Romero F, Rosas IO, King KY, McKenna NJ, Coarfa C, Rodriguez A. Let-7 restrains an oncogenic circuit in AT2 cells to prevent fibrogenic cell intermediates in pulmonary fibrosis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2024.05.22.595205. [PMID: 38826218 PMCID: PMC11142151 DOI: 10.1101/2024.05.22.595205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Analysis of lung alveolar type 2 (AT2) progenitor stem cells has highlighted fundamental mechanisms that direct their differentiation into alveolar type 1 cells (AT1s) in lung repair and disease. However, microRNA (miRNA) mediated post-transcriptional mechanisms which govern this nexus remain understudied. We show here that the let-7 miRNA family serves a homeostatic role in governance of AT2 quiescence, specifically by preventing the uncontrolled accumulation of AT2 transitional cells and by promoting AT1 differentiation. Using mice and organoid models, we demonstrate genetic ablation of let-7a1/let-7f1/let-7d cluster (let-7afd) in AT2 cells prevents AT1 differentiation and results in accumulation of AT2 transitional cells in progressive pulmonary fibrosis. Integration of AGO2-eCLIP with RNA-sequencing from AT2 cells uncovered the induction of direct targets of let-7 in an oncogene feed-forward regulatory network including BACH1/EZH2/MYC which drives an aberrant fibrotic cascade. Additional analyses using CUT&RUN-sequencing revealed an epigenetic role of let-7 in induction of chromatin histone acetylation and methylation and maladaptive AT2 cell reprogramming. This study identifies let-7 as a key gatekeeper of post-transcriptional and epigenetic chromatin signals to prevent AT2-driven pulmonary fibrosis.
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Affiliation(s)
- Matthew J Seasock
- Immunology & Microbiology Graduate Program, Baylor College of Medicine, Houston, TX, 77030
- Department of Medicine, Section of Immunology, Allergy & Rheumatology, Baylor College of Medicine Houston TX, 77030
| | - Md Shafiquzzaman
- Department of Medicine, Section of Immunology, Allergy & Rheumatology, Baylor College of Medicine Houston TX, 77030
| | - Maria E Ruiz-Echartea
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, 77030
| | - Rupa S Kanchi
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, 77030
- Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine Houston, TX, 77030
| | - Brandon T Tran
- Graduate Program of Cancer Biology and Cell Biology, Baylor College of Medicine, Houston, TX, 77030
- Department of Pediatrics, Division of Infectious Diseases, Texas Children's Hospital, Baylor College of Medicine, Houston, TX, 77030
| | - Lukas M Simon
- Therapeutic Innovation Center, Baylor College of Medicine, Houston, TX, 77030
| | - Matthew D Meyer
- Shared Equipment Authority, Rice University, Houston, TX 77005
| | - Phillip A Erice
- Immunology & Microbiology Graduate Program, Baylor College of Medicine, Houston, TX, 77030
- Department of Medicine, Section of Immunology, Allergy & Rheumatology, Baylor College of Medicine Houston TX, 77030
| | - Shivani L Lotlikar
- Department of Medicine, Section of Immunology, Allergy & Rheumatology, Baylor College of Medicine Houston TX, 77030
| | | | - Scott A Ochsner
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, 77030
| | - Anton Enright
- Department of Pathology, University of Cambridge, Cambridge, CB2 1TN, UK
| | - Alex F Carisey
- William T. Shearer Center for Immunobiology, Texas Children's Hospital, Houston, TX, 77030
- Current Address: Department of Cell and Molecular Biology, St. Jude Children's Research Hospital, Memphis, TN
| | - Freddy Romero
- Department of Medicine, Section of Pulmonary and Critical Care, Baylor College of Medicine. Houston, TX, 77030
- Current Address: Vertex Pharmaceuticals, 3215 Merryfield Row, San Diego, CA, 92121
| | - Ivan O Rosas
- Department of Medicine, Section of Pulmonary and Critical Care, Baylor College of Medicine. Houston, TX, 77030
| | - Katherine Y King
- Department of Pediatrics, Division of Infectious Diseases, Texas Children's Hospital, Baylor College of Medicine, Houston, TX, 77030
| | - Neil J McKenna
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, 77030
| | - Cristian Coarfa
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, 77030
- Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine Houston, TX, 77030
| | - Antony Rodriguez
- Department of Medicine, Section of Immunology, Allergy & Rheumatology, Baylor College of Medicine Houston TX, 77030
- Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine Houston, TX, 77030
- Center for Translational Research on Inflammatory Diseases, Michael E. Debakey, Baylor College of Medicine, Houston, TX, 77030
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6
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Zong W, Li D, Seney ML, Mcclung CA, Tseng GC. Model-based multifacet clustering with high-dimensional omics applications. Biostatistics 2024; 26:kxae020. [PMID: 39002144 PMCID: PMC11823124 DOI: 10.1093/biostatistics/kxae020] [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: 06/01/2023] [Revised: 05/08/2024] [Accepted: 06/02/2024] [Indexed: 07/15/2024] Open
Abstract
High-dimensional omics data often contain intricate and multifaceted information, resulting in the coexistence of multiple plausible sample partitions based on different subsets of selected features. Conventional clustering methods typically yield only one clustering solution, limiting their capacity to fully capture all facets of cluster structures in high-dimensional data. To address this challenge, we propose a model-based multifacet clustering (MFClust) method based on a mixture of Gaussian mixture models, where the former mixture achieves facet assignment for gene features and the latter mixture determines cluster assignment of samples. We demonstrate superior facet and cluster assignment accuracy of MFClust through simulation studies. The proposed method is applied to three transcriptomic applications from postmortem brain and lung disease studies. The result captures multifacet clustering structures associated with critical clinical variables and provides intriguing biological insights for further hypothesis generation and discovery.
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Affiliation(s)
- Wei Zong
- Department of Biostatistics, University of Pittsburgh, 130 De Soto St, Pittsburgh, PA 15261, United States
| | - Danyang Li
- Translational Neuroscience Program, Department of Psychiatry, Center for Neuroscience, University of Pittsburgh, 3811 O’Hara Street, PA 15213, United States
| | - Marianne L Seney
- Translational Neuroscience Program, Department of Psychiatry, Center for Neuroscience, University of Pittsburgh, 3811 O’Hara Street, PA 15213, United States
| | - Colleen A Mcclung
- Translational Neuroscience Program, Department of Psychiatry, Center for Neuroscience, University of Pittsburgh, 3811 O’Hara Street, PA 15213, United States
| | - George C Tseng
- Department of Biostatistics, University of Pittsburgh, 130 De Soto St, Pittsburgh, PA 15261, United States
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7
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Bhargava M, Crouser ED. Application of laboratory models for sarcoidosis research. J Autoimmun 2024; 149:103184. [PMID: 38443221 DOI: 10.1016/j.jaut.2024.103184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 02/12/2024] [Accepted: 02/15/2024] [Indexed: 03/07/2024]
Abstract
This manuscript will review the implications and applications of sarcoidosis models towards advancing our understanding of sarcoidosis disease mechanisms, identification of biomarkers, and preclinical testing of novel therapies. Emerging disease models and innovative research tools will also be considered.
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Affiliation(s)
- Maneesh Bhargava
- University of Minnesota Medical Center, Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, 420 Delaware Street SE, MMC 276. Minneapolis, MN 55455, USA
| | - Elliott D Crouser
- Ohio State University Wexner Medicine Center, Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, 241 W. 11th Street, Suite 5000, Columbus, OH 43201, USA.
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8
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Jin H, Park SY, Lee JE, Park H, Jeong M, Lee H, Cho J, Lee YS. GTSE1-driven ZEB1 stabilization promotes pulmonary fibrosis through the epithelial-to-mesenchymal transition. Mol Ther 2024; 32:4138-4157. [PMID: 39342428 PMCID: PMC11573610 DOI: 10.1016/j.ymthe.2024.09.029] [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: 04/14/2024] [Revised: 08/06/2024] [Accepted: 09/25/2024] [Indexed: 10/01/2024] Open
Abstract
G2 and S phase-expressed protein 1 (GTSE1) has been implicated in the development of pulmonary fibrosis (PF); however, its biological function, molecular mechanism, and potential clinical implications remain unknown. Here, we explored the genomic data of patients with idiopathic PF (IPF) and found that GTSE1 expression is elevated in their lung tissues, but rarely expressed in normal lung tissues. Thus, we explored the biological role and downstream events of GTSE1 using IPF patient tissues and PF mouse models. The comprehensive bioinformatics analyses suggested that the increase of GTSE1 in IPF is linked to the enhanced gene signature for the epithelial-to-mesenchymal transition (EMT), leading us to investigate the potential interaction between GTSE1 and EMT transcription factors. GTSE1 preferentially binds to the less stable form of zinc-finger E-box-binding homeobox 1 (ZEB1), the unphosphorylated form at Ser585, inhibiting ZEB1 degradation. Consistently, the ZEB1 protein level in IPF patient and PF mouse tissues correlates with the GTSE1 protein level and the amount of collagen accumulation, representing fibrosis severity. Collectively, our findings highlight the GTSE1-ZEB1 axis as a novel driver of the pathological EMT characteristic during PF development and progression, supporting further investigation into GTSE1-targeting approaches for PF treatment.
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Affiliation(s)
- Hee Jin
- Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 120-750, Republic of Korea
| | - So-Yeon Park
- Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 120-750, Republic of Korea; Center for Genome Engineering, Institute for Basic Science, Daejeon 34126, Republic of Korea
| | - Ji Eun Lee
- Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 120-750, Republic of Korea
| | - Hangyeol Park
- Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 120-750, Republic of Korea
| | - Michaela Jeong
- Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 120-750, Republic of Korea
| | - Hyukjin Lee
- Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 120-750, Republic of Korea
| | - Jaeho Cho
- Department of Radiation Oncology, Yonsei University Health System, Seoul 120-749, Republic of Korea
| | - Yun-Sil Lee
- Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 120-750, Republic of Korea.
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9
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Manuilova I, Bossenz J, Weise AB, Boehm D, Strantz C, Unberath P, Reimer N, Metzger P, Pauli T, Werle SD, Schulze S, Hiemer S, Ustjanzew A, Kestler HA, Busch H, Brors B, Christoph J. Identifications of Similarity Metrics for Patients With Cancer: Protocol for a Scoping Review. JMIR Res Protoc 2024; 13:e58705. [PMID: 39230952 PMCID: PMC11411229 DOI: 10.2196/58705] [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: 04/11/2024] [Revised: 06/19/2024] [Accepted: 07/16/2024] [Indexed: 09/05/2024] Open
Abstract
BACKGROUND Understanding the similarities of patients with cancer is essential to advancing personalized medicine, improving patient outcomes, and developing more effective and individualized treatments. It enables researchers to discover important patterns, biomarkers, and treatment strategies that can have a significant impact on cancer research and oncology. In addition, the identification of previously successfully treated patients supports oncologists in making treatment decisions for a new patient who is clinically or molecularly similar to the previous patient. OBJECTIVE The planned review aims to systematically summarize, map, and describe existing evidence to understand how patient similarity is defined and used in cancer research and clinical care. METHODS To systematically identify relevant studies and to ensure reproducibility and transparency of the review process, a comprehensive literature search will be conducted in several bibliographic databases, including Web of Science, PubMed, LIVIVIVO, and MEDLINE, covering the period from 1998 to February 2024. After the initial duplicate deletion phase, a study selection phase will be applied using Rayyan, which consists of 3 distinct steps: title and abstract screening, disagreement resolution, and full-text screening. To ensure the integrity and quality of the selection process, each of these steps is preceded by a pilot testing phase. This methodological process will culminate in the presentation of the final research results in a structured form according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) flowchart. The protocol has been registered in the Journal of Medical Internet Research. RESULTS This protocol outlines the methodologies used in conducting the scoping review. A search of the specified electronic databases and after removing duplicates resulted in 1183 unique records. As of March 2024, the review process has moved to the full-text evaluation phase. At this stage, data extraction will be conducted using a pretested chart template. CONCLUSIONS The scoping review protocol, centered on these main concepts, aims to systematically map the available evidence on patient similarity among patients with cancer. By defining the types of data sources, approaches, and methods used in the field, and aligning these with the research questions, the review will provide a foundation for future research and clinical application in personalized cancer care. This protocol will guide the literature search, data extraction, and synthesis of findings to achieve the review's objectives. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) DERR1-10.2196/58705.
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Affiliation(s)
- Iryna Manuilova
- Junior Research Group (Bio-) Medical Data Science, Faculty of Medicine, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
- Data Integration Centre, University Hospital Halle (Saale), Halle (Saale), Germany
| | - Jan Bossenz
- Junior Research Group (Bio-) Medical Data Science, Faculty of Medicine, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
| | - Annemarie Bianka Weise
- Junior Research Group (Bio-) Medical Data Science, Faculty of Medicine, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
| | - Dominik Boehm
- Medical Center for Information and Communication Technology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- Bavarian Cancer Research Center (Bayerisches Zentrum für Krebsforschung), Erlangen, Germany
| | - Cosima Strantz
- Medical Informatics, Institute for Medical Informatics, Biometrics and Epidemiology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Philipp Unberath
- Medical Center for Information and Communication Technology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- SRH Fürth University of Applied Sciences, Fürth, Germany
| | - Niklas Reimer
- Medical Systems Biology Group, Lübeck Institute of Experimental Dermatology, University of Lübeck, Lübeck, Germany
- University Cancer Center Schleswig-Holstein, University Hospital Schleswig-Holstein, Lübeck, Germany
- Medical Data Integration Center, University Hospital Schleswig-Holstein, Lübeck, Germany
| | - Patrick Metzger
- Institute of Medical Bioinformatics and Systems Medicine, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Clinical Trial Office, German Cancer Research Center (DKFZ) Heidelberg, Heidelberg, Germany
| | - Thomas Pauli
- Institute of Medical Bioinformatics and Systems Medicine, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Silke D Werle
- Institute of Medical Systems Biology, Ulm University, Ulm, Germany
| | - Susann Schulze
- Krukenberg Cancer Center Halle (Saale), Halle (Saale), Germany
| | - Sonja Hiemer
- Krukenberg Cancer Center Halle (Saale), Halle (Saale), Germany
| | - Arsenij Ustjanzew
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Hans A Kestler
- Institute of Medical Systems Biology, Ulm University, Ulm, Germany
| | - Hauke Busch
- Medical Systems Biology Group, Lübeck Institute of Experimental Dermatology, University of Lübeck, Lübeck, Germany
- University Cancer Center Schleswig-Holstein, University Hospital Schleswig-Holstein, Lübeck, Germany
| | - Benedikt Brors
- Division of Applied Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg, Germany
- German Cancer Consortium, Heidelberg, Germany
- National Center for Tumor Diseases (NCT), Heidelberg, Germany
- Medical Faculty Heidelberg and Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
| | - Jan Christoph
- Junior Research Group (Bio-) Medical Data Science, Faculty of Medicine, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
- Data Integration Centre, University Hospital Halle (Saale), Halle (Saale), Germany
- Medical Informatics, Institute for Medical Informatics, Biometrics and Epidemiology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
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Saha E, Ben Guebila M, Fanfani V, Fischer J, Shutta KH, Mandros P, DeMeo DL, Quackenbush J, Lopes-Ramos CM. Gene regulatory networks reveal sex difference in lung adenocarcinoma. Biol Sex Differ 2024; 15:62. [PMID: 39107837 PMCID: PMC11302009 DOI: 10.1186/s13293-024-00634-y] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Accepted: 07/04/2024] [Indexed: 08/10/2024] Open
Abstract
BACKGROUND Lung adenocarcinoma (LUAD) has been observed to have significant sex differences in incidence, prognosis, and response to therapy. However, the molecular mechanisms responsible for these disparities have not been investigated extensively. METHODS Sample-specific gene regulatory network methods were used to analyze RNA sequencing data from non-cancerous human lung samples from The Genotype Tissue Expression Project (GTEx) and lung adenocarcinoma primary tumor samples from The Cancer Genome Atlas (TCGA); results were validated on independent data. RESULTS We found that genes associated with key biological pathways including cell proliferation, immune response and drug metabolism are differentially regulated between males and females in both healthy lung tissue and tumor, and that these regulatory differences are further perturbed by tobacco smoking. We also discovered significant sex bias in transcription factor targeting patterns of clinically actionable oncogenes and tumor suppressor genes, including AKT2 and KRAS. Using differentially regulated genes between healthy and tumor samples in conjunction with a drug repurposing tool, we identified several small-molecule drugs that might have sex-biased efficacy as cancer therapeutics and further validated this observation using an independent cell line database. CONCLUSIONS These findings underscore the importance of including sex as a biological variable and considering gene regulatory processes in developing strategies for disease prevention and management.
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Affiliation(s)
- Enakshi Saha
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Marouen Ben Guebila
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Viola Fanfani
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Jonas Fischer
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Katherine H Shutta
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, 02115, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | - Panagiotis Mandros
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Dawn L DeMeo
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA
| | - John Quackenbush
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, 02115, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, 02115, USA
| | - Camila M Lopes-Ramos
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, 02115, USA.
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA.
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA.
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11
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Li Q, Liu Y, Wang X, Xie C, Mei X, Cao W, Guan W, Lin X, Xie X, Zhou C, Yi E. The influence of CLEC5A on early macrophage-mediated inflammation in COPD progression. Cell Mol Life Sci 2024; 81:330. [PMID: 39097839 PMCID: PMC11335254 DOI: 10.1007/s00018-024-05375-0] [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: 05/25/2024] [Revised: 07/11/2024] [Accepted: 07/18/2024] [Indexed: 08/05/2024]
Abstract
Chronic obstructive pulmonary disease (COPD) is a complex syndrome with poorly understood mechanisms driving its early progression (GOLD stages 1-2). Elucidating the genetic factors that influence early-stage COPD, particularly those related to airway inflammation and remodeling, is crucial. This study analyzed lung tissue sequencing data from patients with early-stage COPD (GSE47460) and smoke-exposed mice. We employed Weighted Gene Co-Expression Network Analysis (WGCNA) and machine learning to identify potentially pathogenic genes. Further analyses included single-cell sequencing from both mice and COPD patients to pinpoint gene expression in specific cell types. Cell-cell communication and pseudotemporal analyses were conducted, with findings validated in smoke-exposed mice. Additionally, Mendelian randomization (MR) was used to confirm the association between candidate genes and lung function/COPD. Finally, functional validation was performed in vitro using cell cultures. Machine learning analysis of 30 differentially expressed genes identified 8 key genes, with CLEC5A emerging as a potential pathogenic factor in early-stage COPD. Bioinformatics analyses suggested a role for CLEC5A in macrophage-mediated inflammation during COPD. Two-sample Mendelian randomization linked CLEC5A single nucleotide polymorphisms (SNPs) with Forced Expiratory Volume in One Second (FEV1), FEV1/Forced Vital Capacity (FVC) and early/later on COPD. In vitro, the knockdown of CLEC5A led to a reduction in inflammatory markers within macrophages. Our study identifies CLEC5A as a critical gene in early-stage COPD, contributing to its pathogenesis through pro-inflammatory mechanisms. This discovery offers valuable insights for developing early diagnosis and treatment strategies for COPD and highlights CLEC5A as a promising target for further investigation.
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Affiliation(s)
- Qingyang Li
- State Key Laboratory of Respiratory Diseases, National Clinical Research Center for Respiratory Diseases, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, 195 Dongfeng Xi Road, Guangzhou, 510182, Guangdong, China
| | - Yu Liu
- State Key Laboratory of Respiratory Diseases, National Clinical Research Center for Respiratory Diseases, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, 195 Dongfeng Xi Road, Guangzhou, 510182, Guangdong, China
| | - Xiaoyu Wang
- State Key Laboratory of Respiratory Diseases, National Clinical Research Center for Respiratory Diseases, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, 195 Dongfeng Xi Road, Guangzhou, 510182, Guangdong, China
| | - Chengshu Xie
- Guangzhou National Laboratory, Guangzhou International BioIsland, No.9 XingDaoHuanBei Road, Guangzhou, 510005, Guangdong, China
| | - Xinyue Mei
- State Key Laboratory of Respiratory Diseases, National Clinical Research Center for Respiratory Diseases, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, 195 Dongfeng Xi Road, Guangzhou, 510182, Guangdong, China
| | - Weitao Cao
- Department of Pulmonary and Critical Care Medicine, Guangzhou First People's Hospital, South China University of Technology Guangzhou, Guangzhou, 510180, Guangdong, China
| | - Wenhui Guan
- State Key Laboratory of Respiratory Diseases, National Clinical Research Center for Respiratory Diseases, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, 195 Dongfeng Xi Road, Guangzhou, 510182, Guangdong, China
| | - Xinqing Lin
- State Key Laboratory of Respiratory Diseases, National Clinical Research Center for Respiratory Diseases, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, 195 Dongfeng Xi Road, Guangzhou, 510182, Guangdong, China
| | - Xiaohong Xie
- State Key Laboratory of Respiratory Diseases, National Clinical Research Center for Respiratory Diseases, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, 195 Dongfeng Xi Road, Guangzhou, 510182, Guangdong, China
| | - Chengzhi Zhou
- State Key Laboratory of Respiratory Diseases, National Clinical Research Center for Respiratory Diseases, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, 195 Dongfeng Xi Road, Guangzhou, 510182, Guangdong, China.
| | - Erkang Yi
- State Key Laboratory of Respiratory Diseases, National Clinical Research Center for Respiratory Diseases, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, 195 Dongfeng Xi Road, Guangzhou, 510182, Guangdong, China.
- Guangzhou National Laboratory, Guangzhou International BioIsland, No.9 XingDaoHuanBei Road, Guangzhou, 510005, Guangdong, China.
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12
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Saha E, Guebila MB, Fanfani V, Shutta KH, DeMeo DL, Quackenbush J, Lopes-Ramos CM. Aging-associated Alterations in the Gene Regulatory Network Landscape Associate with Risk, Prognosis and Response to Therapy in Lung Adenocarcinoma. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.02.601689. [PMID: 39005266 PMCID: PMC11244978 DOI: 10.1101/2024.07.02.601689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Aging is the primary risk factor for many individual cancer types, including lung adenocarcinoma (LUAD). To understand how aging-related alterations in the regulation of key cellular processes might affect LUAD risk and survival outcomes, we built individual (person)-specific gene regulatory networks integrating gene expression, transcription factor protein-protein interaction, and sequence motif data, using PANDA/LIONESS algorithms, for both non-cancerous lung tissue samples from the Genotype Tissue Expression (GTEx) project and LUAD samples from The Cancer Genome Atlas (TCGA). In GTEx, we found that pathways involved in cell proliferation and immune response are increasingly targeted by regulatory transcription factors with age; these aging-associated alterations are accelerated by tobacco smoking and resemble oncogenic shifts in the regulatory landscape observed in LUAD and suggests that dysregulation of aging pathways might be associated with an increased risk of LUAD. Comparing normal adjacent samples from individuals with LUAD with healthy lung tissue samples from those without LUAD, we found that aging-associated genes show greater aging-biased targeting patterns in younger individuals with LUAD compared to their healthy counterparts of similar age, a pattern suggestive of age acceleration. This implies that an accelerated aging process may be responsible for tumor incidence in younger individuals. Using drug repurposing tool CLUEreg, we found small molecule drugs with potential geroprotective effects that may alter the accelerating aging profiles we found. We also observed that, in contrast to chronological age, a network-informed aging signature was associated with survival and response to chemotherapy in LUAD.
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Affiliation(s)
- Enakshi Saha
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
| | - Marouen Ben Guebila
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
| | - Viola Fanfani
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
| | - Katherine H Shutta
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA 02115
| | - Dawn L DeMeo
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA 02115
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - John Quackenbush
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA 02115
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02115, USA
| | - Camila M Lopes-Ramos
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA 02115
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
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Rakkar K, Thakker D, Portelli MA, Hall I, Schlüter H, Sayers I. Transcriptomics using lung resection material to advance our understanding of COPD and idiopathic pulmonary fibrosis pathogenesis. ERJ Open Res 2024; 10:00061-2024. [PMID: 39104962 PMCID: PMC11299008 DOI: 10.1183/23120541.00061-2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Accepted: 04/11/2024] [Indexed: 08/07/2024] Open
Abstract
Genes involved in cell death, inflammation and viral infection are common to both COPD and IPF. A link to rheumatic disease is unique to COPD, and IPF-specific analyses showed increases in gene expression of keratins, collagens, mucins and MMPs. https://bit.ly/3JoW73H.
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Affiliation(s)
- Kamini Rakkar
- Centre for Respiratory Research, NIHR Nottingham Biomedical Research Centre, School of Medicine, Biodiscovery Institute, University of Nottingham, Nottingham, UK
| | - Dhruma Thakker
- Centre for Respiratory Research, NIHR Nottingham Biomedical Research Centre, School of Medicine, Biodiscovery Institute, University of Nottingham, Nottingham, UK
| | - Michael A. Portelli
- Centre for Respiratory Research, NIHR Nottingham Biomedical Research Centre, School of Medicine, Biodiscovery Institute, University of Nottingham, Nottingham, UK
| | - Ian Hall
- Centre for Respiratory Research, NIHR Nottingham Biomedical Research Centre, School of Medicine, Biodiscovery Institute, University of Nottingham, Nottingham, UK
| | - Holger Schlüter
- Immunology and Respiratory Department, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany
| | - Ian Sayers
- Centre for Respiratory Research, NIHR Nottingham Biomedical Research Centre, School of Medicine, Biodiscovery Institute, University of Nottingham, Nottingham, UK
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Rodrigues Pereira RP, Mazzali Pessoa Martins AM, Mendes de Carvalho IT, Kel de Souza LD, Francao P, Gomes CM, Bernardes RDP, Meyer KF, Fonseca EMGOD, Machado MG, Tanaka C. Clinical phenotyping of children with nocturnal enuresis: A key classification to improve the approach. J Pediatr Urol 2024; 20:384.e1-384.e9. [PMID: 38508980 DOI: 10.1016/j.jpurol.2024.01.019] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 12/01/2023] [Accepted: 01/19/2024] [Indexed: 03/22/2024]
Abstract
INTRODUCTION The literature shows that nocturnal enuresis is not an isolated phenomenon of urinary loss during sleep, but encompasses a set of systemic clinical manifestations that significantly influence children's quality of life and development. However, the understanding of the clinical and physiological relationship of these systemic manifestations remains a clinical challenge. The recognition of these manifestations and their subsequent categorisation, may provide better insights into integrated clinical manifestations, facilitating the understanding of pathophysiological mechanisms, and promote increased assertiveness in the assessment and the selection of appropriate therapies. OBJECTIVE The aim of this study is to develop a phenotyping model for children with nocturnal enuresis based on evidence. METHODS This study presents a clinical phenotyping model for children with nocturnal enuresis based on an analytical and methodological review of the literature, about nocturnal enuresis and its associated clinical manifestations. There was a bibliometric analysis carried out to better analyse outcomes. After reading and analysing the literature, the clinical manifestations were categorised into domains and submitted to the validation of an expert committee with extensive experience in their specific area of expertise. A visual representation of the categorised model was developed to make the phenotyping concept easily understandable to all professionals. RESULTS The clinical manifestations related to nocturnal enuresis have been categorised according to frequency and relation found in the literature and validation by an expert committee and the development of the phenotyping model for children with nocturnal enuresis was completed. CONCLUSION The present study developed an evidence-based phenotyping model for children with nocturnal enuresis.
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Affiliation(s)
- Rita Pavione Rodrigues Pereira
- Departamento de Fisioterapia, Fonoaudiologia e Terapia Ocupacional da Faculdade de Medicina da Universidade de São Paulo, Sao Paulo, SP, Brazil; LIM 54 - Laboratório de Investigação em Fisioterapia, Hospital das Clínicas da Faculdade de Medicina da Universidade De São Paulo, Sao Paulo, SP, Brazil.
| | - Aline Mari Mazzali Pessoa Martins
- Departamento de Fisioterapia, Fonoaudiologia e Terapia Ocupacional da Faculdade de Medicina da Universidade de São Paulo, Sao Paulo, SP, Brazil; LIM 54 - Laboratório de Investigação em Fisioterapia, Hospital das Clínicas da Faculdade de Medicina da Universidade De São Paulo, Sao Paulo, SP, Brazil.
| | - Isabela Teixeira Mendes de Carvalho
- Departamento de Fisioterapia, Fonoaudiologia e Terapia Ocupacional da Faculdade de Medicina da Universidade de São Paulo, Sao Paulo, SP, Brazil; LIM 54 - Laboratório de Investigação em Fisioterapia, Hospital das Clínicas da Faculdade de Medicina da Universidade De São Paulo, Sao Paulo, SP, Brazil.
| | - Luana Daniele Kel de Souza
- Departamento de Fisioterapia, Fonoaudiologia e Terapia Ocupacional da Faculdade de Medicina da Universidade de São Paulo, Sao Paulo, SP, Brazil; LIM 54 - Laboratório de Investigação em Fisioterapia, Hospital das Clínicas da Faculdade de Medicina da Universidade De São Paulo, Sao Paulo, SP, Brazil.
| | - Patricia Francao
- Departamento de Fisioterapia, Fonoaudiologia e Terapia Ocupacional da Faculdade de Medicina da Universidade de São Paulo, Sao Paulo, SP, Brazil; LIM 54 - Laboratório de Investigação em Fisioterapia, Hospital das Clínicas da Faculdade de Medicina da Universidade De São Paulo, Sao Paulo, SP, Brazil.
| | - Cristiano Mendes Gomes
- Divisão de Urologia do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, Sao Paulo, SP, Brazil.
| | | | | | - Eliane Maria Garcez Oliveira da Fonseca
- Departamento de Pediatria, Núcleo de Disfunção Miccional, Faculdade de Ciências Médicas da Universidade Estadual do Rio de Janeiro, Rio de Janeiro, Brazil; Departamento de Pediatria da Escola de Medicina Souza Marques, Rio de Janeiro, Brazil.
| | - Marcos Giannetti Machado
- Divisão de Urologia do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, Sao Paulo, SP, Brazil.
| | - Clarice Tanaka
- Departamento de Fisioterapia, Fonoaudiologia e Terapia Ocupacional da Faculdade de Medicina da Universidade de São Paulo, Sao Paulo, SP, Brazil; LIM 54 - Laboratório de Investigação em Fisioterapia, Hospital das Clínicas da Faculdade de Medicina da Universidade De São Paulo, Sao Paulo, SP, Brazil.
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Zheng Z, Peng F, Zhou Y. Biomarkers in idiopathic pulmonary fibrosis: Current insight and future direction. CHINESE MEDICAL JOURNAL PULMONARY AND CRITICAL CARE MEDICINE 2024; 2:72-79. [PMID: 38962100 PMCID: PMC11221783 DOI: 10.1016/j.pccm.2024.04.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 07/05/2024]
Abstract
Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive interstitial lung disease with a dismal prognosis. Early diagnosis, accurate prognosis, and personalized therapeutic interventions are essential for improving patient outcomes. Biomarkers, as measurable indicators of biological processes or disease states, hold significant promise in IPF management. In recent years, there has been a growing interest in identifying and validating biomarkers for IPF, encompassing various molecular, imaging, and clinical approaches. This review provides an in-depth examination of the current landscape of IPF biomarker research, highlighting their potential applications in disease diagnosis, prognosis, and treatment response. Additionally, the challenges and future perspectives of biomarker integration into clinical practice for precision medicine in IPF are discussed.
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Affiliation(s)
- Zhen Zheng
- Section of Pulmonary Diseases, Critical Care and Environmental Medicine, School of Medicine, Tulane University, New Orleans, LA 70112, USA
| | - Fei Peng
- Section of Pulmonary Diseases, Critical Care and Environmental Medicine, School of Medicine, Tulane University, New Orleans, LA 70112, USA
| | - Yong Zhou
- Section of Pulmonary Diseases, Critical Care and Environmental Medicine, School of Medicine, Tulane University, New Orleans, LA 70112, USA
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16
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Sakamachi Y, Wiley E, Solis A, Johnson CG, Meng X, Hussain S, Lipinski JH, O'Dwyer DN, Randall T, Malphurs J, Papas B, Wu BG, Li Y, Kugler M, Mehta S, Trempus CS, Thomas SY, Li JL, Zhou L, Karmaus PW, Fessler MB, McGrath JA, Gibson K, Kass DJ, Gleiberman A, Walts A, Invernizzi R, Molyneaux PL, Yang IV, Zhang Y, Kaminski N, Segal LN, Schwartz DA, Gudkov AV, Garantziotis S. Toll-Like-Receptor 5 protects against pulmonary fibrosis by reducing lung dysbiosis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.30.591719. [PMID: 39605370 PMCID: PMC11601505 DOI: 10.1101/2024.04.30.591719] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2024]
Abstract
Idiopathic pulmonary fibrosis (IPF) is a devastating pulmonary disease with no curative treatment other than lung transplantation. IPF results from maladaptive responses to lung epithelial injury, but the underlying mechanisms remain unclear. Here, we show that deficiency in the innate immune receptor, toll-like receptor 5 (TLR5), is associated with IPF in humans and with increased susceptibility to epithelial injury and experimental fibrosis in mice, while activation of lung epithelial TLR5 through a synthetic flagellin analogue protects from experimental fibrosis. Mechanistically, epithelial TLR5 activation induces antimicrobial gene expression and ameliorates dysbiosis after lung injury. In contrast, TLR5 deficiency in mice and IPF patients is associated with lung dysbiosis. Elimination of the microbiome in mice through antibiotics abolishes the protective effect of TLR5 and reconstitution of the microbiome rescues the observed phenotype. In aggregate, TLR5 deficiency is associated with IPF and dysbiosis in humans and in the murine model of pulmonary fibrosis. Furthermore, TLR5 protects against pulmonary fibrosis in mice and this protection is mediated by effects on the microbiome. One-sentence summary Deficiency in the innate immune receptor TLR5 is a risk factor for pulmonary fibrosis, because TLR5 prevents microbial dysbiosis after lung injury.
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17
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Xu F, Tong Y, Yang W, Cai Y, Yu M, Liu L, Meng Q. Identifying a survival-associated cell type based on multi-level transcriptome analysis in idiopathic pulmonary fibrosis. Respir Res 2024; 25:126. [PMID: 38491375 PMCID: PMC10941445 DOI: 10.1186/s12931-024-02738-w] [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: 11/24/2023] [Accepted: 02/19/2024] [Indexed: 03/18/2024] Open
Abstract
BACKGROUND Idiopathic pulmonary fibrosis (IPF) is a progressive disease with a five-year survival rate of less than 40%. There is significant variability in survival time among IPF patients, but the underlying mechanisms for this are not clear yet. METHODS AND RESULTS We collected single-cell RNA sequence data of 13,223 epithelial cells taken from 32 IPF patients and bulk RNA sequence data from 456 IPF patients in GEO. Based on unsupervised clustering analysis at the single-cell level and deconvolution algorithm at bulk RNA sequence data, we discovered a special alveolar type 2 cell subtype characterized by high expression of CCL20 (referred to as ATII-CCL20), and found that IPF patients with a higher proportion of ATII-CCL20 had worse prognoses. Furthermore, we uncovered the upregulation of immune cell infiltration and metabolic functions in IPF patients with a higher proportion of ATII-CCL20. Finally, the comprehensive decision tree and nomogram were constructed to optimize the risk stratification of IPF patients and provide a reference for accurate prognosis evaluation. CONCLUSIONS Our study by integrating single-cell and bulk RNA sequence data from IPF patients identified a special subtype of ATII cells, ATII-CCL20, which was found to be a risk cell subtype associated with poor prognosis in IPF patients. More importantly, the ATII-CCL20 cell subtype was linked with metabolic functions and immune infiltration.
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Affiliation(s)
- Fei Xu
- Department of Pharmacogenomics, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China
| | - Yun Tong
- Department of Pharmacogenomics, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China
| | - Wenjun Yang
- Department of Pharmacogenomics, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China
| | - Yiyang Cai
- Department of Pharmacogenomics, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China
| | - Meini Yu
- Department of Pharmacogenomics, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China
| | - Lei Liu
- Department of Pharmacogenomics, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
| | - Qingkang Meng
- Department of Pharmacogenomics, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
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18
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Wang W, Ren W, Zhu L, Hu Y, Ye C. Identification of genes and key pathways underlying the pathophysiological association between sarcopenia and chronic obstructive pulmonary disease. Exp Gerontol 2024; 187:112373. [PMID: 38320732 DOI: 10.1016/j.exger.2024.112373] [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: 12/26/2023] [Revised: 01/26/2024] [Accepted: 01/30/2024] [Indexed: 02/09/2024]
Abstract
PURPOSE Chronic obstructive pulmonary disease (COPD) patients are likely to develop sarcopenia, while the exact mechanism underlying the association between sarcopenia and COPD is still not clear. This cohort study aims to explore the genes, signaling pathways, and transcription factors (TFs) that are related to the molecular pathogenesis of sarcopenia and COPD. METHODS According to the strict inclusion criteria, two gene sets (GSE8479 for sarcopenia and GSE76925 for COPD) were obtained from the Gene Expression Omnibus (GEO) platform. Overlapping differentially expressed genes (DEGs) in sarcopenia and COPD were detected, and comprehensive bioinformatics analysis was conducted, including functional annotation, enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), construction of a protein-protein interaction (PPI) network, co-expression analysis, identification and validation of hub genes, and TFs prediction and verification. RESULTS In total, 118 downregulated and 92 upregulated common DEGs were detected. Functional analysis revealed that potential pathogenesis involves oxidoreductase activity and ferroptosis. Thirty hub genes were detected, and ATP metabolic process and oxidative phosphorylation were identified to be closely related to the hub genes. Validation analysis revealed that SAA1, C3, and ACSS2 were significantly upregulated, whereas ATF4, PPARGC1A, and MCTS1 were markedly downregulated in both sarcopenia and COPD. In addition, six TFs (NFKB1, RELA, IRF7, SP1, MYC, and JUN) were identified to regulate the expression of these genes, and SAA1 was found to be coregulated by NFKB1 and RELA. CONCLUSION This study uncovers potential common mechanisms of COPD complicated by sarcopenia. The hub gene SAA1 and the NF-κB signaling pathway could be involved, and oxidative phosphorylation and ferroptosis might be important contributors to this comorbidity.
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Affiliation(s)
- Weixi Wang
- Department of Geriatrics, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Weiying Ren
- Department of Geriatrics, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Lin Zhu
- Department of Geriatrics, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yu Hu
- Department of Geriatrics, Zhongshan Hospital, Fudan University, Shanghai, China.
| | - Cong Ye
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University, Shanghai, China.
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19
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Bahudhanapati H, Tan J, Apel RM, Seeliger B, Schupp J, Li X, Sullivan DI, Sembrat J, Rojas M, Tabib T, Valenzi E, Lafyatis R, Mitash N, Hernandez Pineda R, Jawale C, Peroumal D, Biswas P, Tedrow J, Adams T, Kaminski N, Wuyts WA, McDyer JF, Gibson KF, Alder JK, Königshoff M, Zhang Y, Nouraie M, Prasse A, Kass DJ. Increased expression of CXCL6 in secretory cells drives fibroblast collagen synthesis and is associated with increased mortality in idiopathic pulmonary fibrosis. Eur Respir J 2024; 63:2300088. [PMID: 37918852 DOI: 10.1183/13993003.00088-2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Accepted: 10/09/2023] [Indexed: 11/04/2023]
Abstract
RATIONALE Recent data suggest that the localisation of airway epithelial cells in the distal lung in idiopathic pulmonary fibrosis (IPF) may drive pathology. We set out to discover whether chemokines expressed in these ectopic airway epithelial cells may contribute to the pathogenesis of IPF. METHODS We analysed whole lung and single-cell transcriptomic data obtained from patients with IPF. In addition, we measured chemokine levels in blood, bronchoalveolar lavage (BAL) of IPF patients and air-liquid interface cultures. We employed ex vivo donor and IPF lung fibroblasts and an animal model of pulmonary fibrosis to test the effects of chemokine signalling on fibroblast function. RESULTS By analysis of whole-lung transcriptomics, protein and BAL, we discovered that CXCL6 (a member of the interleukin-8 family) was increased in patients with IPF. Elevated CXCL6 levels in the BAL of two cohorts of patients with IPF were associated with poor survival (hazard ratio of death or progression 1.89, 95% CI 1.16-3.08; n=179, p=0.01). By immunostaining and single-cell RNA sequencing, CXCL6 was detected in secretory cells. Administration of mCXCL5 (LIX, murine CXCL6 homologue) to mice increased collagen synthesis with and without bleomycin. CXCL6 increased collagen I levels in donor and IPF fibroblasts 4.4-fold and 1.7-fold, respectively. Both silencing of and chemical inhibition of CXCR1/2 blocked the effects of CXCL6 on collagen, while overexpression of CXCR2 increased collagen I levels 4.5-fold in IPF fibroblasts. CONCLUSIONS CXCL6 is expressed in ectopic airway epithelial cells. Elevated levels of CXCL6 are associated with IPF mortality. CXCL6-driven collagen synthesis represents a functional consequence of ectopic localisation of airway epithelial cells in IPF.
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Affiliation(s)
- Harinath Bahudhanapati
- Dorothy P. and Richard P. Simmons Center for Interstitial Lung Disease, Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
- Denotes equal contribution
| | - Jiangning Tan
- Dorothy P. and Richard P. Simmons Center for Interstitial Lung Disease, Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
- Denotes equal contribution
| | - Rosa Marie Apel
- Fraunhofer ITEM, Hannover, Germany
- DZL BREATH, Hannover, Germany
| | - Benjamin Seeliger
- Department of Respiratory Medicine, Hannover Medical School, Hannover, Germany
- German Centre for Lung Research (DZL), Biomedical Research in End-stage and Obstructive Lung Disease Hannover, Hannover, Germany
| | - Jonas Schupp
- Department of Respiratory Medicine, Hannover Medical School, Hannover, Germany
- German Centre for Lung Research (DZL), Biomedical Research in End-stage and Obstructive Lung Disease Hannover, Hannover, Germany
| | - Xiaoyun Li
- Dorothy P. and Richard P. Simmons Center for Interstitial Lung Disease, Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Daniel I Sullivan
- Dorothy P. and Richard P. Simmons Center for Interstitial Lung Disease, Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - John Sembrat
- Dorothy P. and Richard P. Simmons Center for Interstitial Lung Disease, Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Mauricio Rojas
- Pulmonary, Critical Care and Sleep Medicine, College of Medicine, Ohio State University, Columbus, OH, USA
| | - Tracy Tabib
- Division of Rheumatology and Clinical Immunology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Eleanor Valenzi
- Dorothy P. and Richard P. Simmons Center for Interstitial Lung Disease, Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Robert Lafyatis
- Division of Rheumatology and Clinical Immunology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Nilay Mitash
- Dorothy P. and Richard P. Simmons Center for Interstitial Lung Disease, Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Ricardo Hernandez Pineda
- Dorothy P. and Richard P. Simmons Center for Interstitial Lung Disease, Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Chetan Jawale
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Partha Biswas
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - John Tedrow
- Norman Regional Health System, Norman, OK, USA
| | - Taylor Adams
- Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Naftali Kaminski
- Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Wim A Wuyts
- Unit for Interstitial Lung Diseases, Department of Respiratory Diseases, University Hospitals Leuven, Leuven, Belgium
- Department of Chronic Diseases, Metabolism, and Ageing, KU Leuven, Leuven, Belgium
| | - John F McDyer
- Starzl Transplantation Institute, University of Pittsburgh, Pittsburgh, PA, USA
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Kevin F Gibson
- Dorothy P. and Richard P. Simmons Center for Interstitial Lung Disease, Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Jonathan K Alder
- Dorothy P. and Richard P. Simmons Center for Interstitial Lung Disease, Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Melanie Königshoff
- Dorothy P. and Richard P. Simmons Center for Interstitial Lung Disease, Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Yingze Zhang
- Dorothy P. and Richard P. Simmons Center for Interstitial Lung Disease, Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Mehdi Nouraie
- Dorothy P. and Richard P. Simmons Center for Interstitial Lung Disease, Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Antje Prasse
- Fraunhofer ITEM, Hannover, Germany
- DZL BREATH, Hannover, Germany
- Department of Respiratory Medicine, Hannover Medical School, Hannover, Germany
- German Centre for Lung Research (DZL), Biomedical Research in End-stage and Obstructive Lung Disease Hannover, Hannover, Germany
- Denotes equal contribution
| | - Daniel J Kass
- Dorothy P. and Richard P. Simmons Center for Interstitial Lung Disease, Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
- Denotes equal contribution
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20
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Karampitsakos T, Galaris A, Chrysikos S, Papaioannou O, Vamvakaris I, Barbayianni I, Kanellopoulou P, Grammenoudi S, Anagnostopoulos N, Stratakos G, Katsaras M, Sampsonas F, Dimakou K, Manali ED, Papiris S, Tourki B, Juan-Guardela BM, Bakakos P, Bouros D, Herazo-Maya JD, Aidinis V, Tzouvelekis A. Expression of PD-1/PD-L1 axis in mediastinal lymph nodes and lung tissue of human and experimental lung fibrosis indicates a potential therapeutic target for idiopathic pulmonary fibrosis. Respir Res 2023; 24:279. [PMID: 37964265 PMCID: PMC10648728 DOI: 10.1186/s12931-023-02551-x] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 10/02/2023] [Indexed: 11/16/2023] Open
Abstract
BACKGROUND Mediastinal lymph node enlargement is prevalent in patients with idiopathic pulmonary fibrosis (IPF). Studies investigating whether this phenomenon reflects specific immunologic activation are lacking. METHODS Programmed cell death-1 (PD-1)/ programmed cell death ligand-1 (PD-L1) expression in mediastinal lymph nodes and lung tissues was analyzed. PD-1, PD-L1 mRNA expression was measured in tracheobronchial lymph nodes of mice following bleomycin-induced injury on day 14. Finally, the effect of the PD-1 inhibitor, pembrolizumab, in bleomycin-induced pulmonary fibrosis was investigated. RESULTS We analyzed mediastinal lymph nodes of thirty-three patients (n = 33, IPF: n = 14, lung cancer: n = 10, concomitant IPF and lung cancer: n = 9) and lung tissues of two hundred nineteen patients (n = 219, IPF: 123, controls: 96). PD-1 expression was increased, while PD-L1 expression was decreased, in mediastinal lymph nodes of patients with IPF compared to lung cancer and in IPF lungs compared to control lungs. Tracheobronchial lymph nodes isolated on day 14 from bleomycin-treated mice exhibited increased size and higher PD-1, PD-L1 mRNA levels compared to saline-treated animals. Pembrolizumab blunted bleomycin-induced lung fibrosis, as indicated by reduction in Ashcroft score and improvement in respiratory mechanics. CONCLUSIONS Mediastinal lymph nodes of patients with IPF exhibit differential expression profiles than those of patients with lung cancer indicating distinct immune-mediated pathways regulating fibrogenesis and carcinogenesis. PD-1 expression in mediastinal lymph nodes is in line with lung tissue expression. Lower doses of pembrolizumab might exert antifibrotic effects. Clinical trials aiming to endotype patients based on mediastinal lymph node profiling and accordingly implement targeted therapies such as PD-1 inhibitors are greatly anticipated.
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Affiliation(s)
- Theodoros Karampitsakos
- Department of Respiratory Medicine, University Hospital of Patras, Rio, Greece
- Ubben Center and Laboratory for Pulmonary Fibrosis Research, Morsani College of Medicine, University of South Florida, 33620, Tampa, FL, USA
| | - Apostolos Galaris
- Institute of Bio- Innovation, Biomedical Sciences Research Center Alexander Fleming, Athens, Greece
| | - Serafeim Chrysikos
- 5th Department of Pneumonology, Hospital for Thoracic Diseases, "SOTIRIA", Athens, Greece
| | - Ourania Papaioannou
- Department of Respiratory Medicine, University Hospital of Patras, Rio, Greece
| | - Ioannis Vamvakaris
- Department of Pathology, Hospital for Thoracic Diseases, "SOTIRIA", Athens, Greece
| | - Ilianna Barbayianni
- Institute of Bio- Innovation, Biomedical Sciences Research Center Alexander Fleming, Athens, Greece
| | - Paraskevi Kanellopoulou
- Institute of Bio- Innovation, Biomedical Sciences Research Center Alexander Fleming, Athens, Greece
| | - Sofia Grammenoudi
- Institute of Bio- Innovation, Biomedical Sciences Research Center Alexander Fleming, Athens, Greece
| | - Nektarios Anagnostopoulos
- First Academic Department of Pneumonology, "SOTIRIA", Medical School, Hospital for Thoracic Diseases, National and Kapodistrian University of Athens, Athens, Greece
| | - Grigoris Stratakos
- First Academic Department of Pneumonology, "SOTIRIA", Medical School, Hospital for Thoracic Diseases, National and Kapodistrian University of Athens, Athens, Greece
| | - Matthaios Katsaras
- Department of Respiratory Medicine, University Hospital of Patras, Rio, Greece
| | - Fotios Sampsonas
- Department of Respiratory Medicine, University Hospital of Patras, Rio, Greece
| | - Katerina Dimakou
- 5th Department of Pneumonology, Hospital for Thoracic Diseases, "SOTIRIA", Athens, Greece
| | - Effrosyni D Manali
- 2nd Pulmonary Medicine Department, Athens Medical School, "ATTIKON" University Hospital, National and Kapodistrian University of Athens, Athens, Greece
| | - Spyridon Papiris
- 2nd Pulmonary Medicine Department, Athens Medical School, "ATTIKON" University Hospital, National and Kapodistrian University of Athens, Athens, Greece
| | - Bochra Tourki
- Ubben Center and Laboratory for Pulmonary Fibrosis Research, Morsani College of Medicine, University of South Florida, 33620, Tampa, FL, USA
| | - Brenda M Juan-Guardela
- Ubben Center and Laboratory for Pulmonary Fibrosis Research, Morsani College of Medicine, University of South Florida, 33620, Tampa, FL, USA
| | - Petros Bakakos
- First Academic Department of Pneumonology, "SOTIRIA", Medical School, Hospital for Thoracic Diseases, National and Kapodistrian University of Athens, Athens, Greece
| | - Demosthenes Bouros
- First Academic Department of Pneumonology, "SOTIRIA", Medical School, Hospital for Thoracic Diseases, National and Kapodistrian University of Athens, Athens, Greece
| | - Jose D Herazo-Maya
- Ubben Center and Laboratory for Pulmonary Fibrosis Research, Morsani College of Medicine, University of South Florida, 33620, Tampa, FL, USA
| | - Vassilis Aidinis
- Institute of Bio- Innovation, Biomedical Sciences Research Center Alexander Fleming, Athens, Greece
| | - Argyris Tzouvelekis
- Department of Respiratory Medicine, University Hospital of Patras, Rio, Greece.
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21
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He J, Wang B, Chen M, Song L, Li H. Machine learning-based metabolism-related genes signature, single-cell RNA sequencing, and experimental validation in hypersensitivity pneumonitis. Medicine (Baltimore) 2023; 102:e34940. [PMID: 37800807 PMCID: PMC10553120 DOI: 10.1097/md.0000000000034940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 08/04/2023] [Indexed: 10/07/2023] Open
Abstract
Metabolism is involved in the pathogenesis of hypersensitivity pneumonitis. To identify diagnostic feature biomarkers based on metabolism-related genes (MRGs) and determine the correlation between MRGs and M2 macrophages in patients with hypersensitivity pneumonitis (HP). We retrieved the gene expression matrix from the Gene Expression Omnibus database. The differentially expressed MRGs (DE-MRGs) between healthy control (HC) and patients with HP were identified using the "DESeq2" R package. The "clusterProfiler" R package was used to perform "Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses" on DE-MRGs. We used machine learning algorithms for screening diagnostic feature biomarkers for HP. The "receiver operating characteristic curve" was used to evaluate diagnostic feature biomarkers' discriminating ability. Next, we used the "Cell-type Identification by Estimating Relative Subsets of RNA Transcripts" algorithm to determine the infiltration status of 22 types of immune cells in the HC and HP groups. Single-cell sequencing and qRT-PCR were used to validate the diagnostic feature biomarkers. Furthermore, the status of macrophage polarization in the peripheral blood of patients with HP was determined using flow cytometry. Finally, the correlation between the proportion of M2 macrophages in peripheral blood and the diagnostic biomarker expression profile in HP patients was determined using Spearman analysis. We identified a total of 311 DE-MRGs. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis showed that DE-MRGs were primarily enriched in processes like steroid hormone biosynthesis, drug metabolism, retinol metabolism, etc. Finally, we identified NPR3, GPX3, and SULF1 as diagnostic feature biomarkers for HP using machine learning algorithms. The bioinformatic results were validated using the experimental results. The CIERSORT algorithm and flow cytometry showed a significant difference in the proportion of M2 macrophages in the HC and HP groups. The expression of SULF1 was positively correlated with the proportion of M2-type macrophages. In addition, a positive correlation was observed between SULF1 expression and M2 macrophage proportion. Finally, we identified NPR3, GPX3, and SULF1 as diagnostic feature biomarkers for HP. Further, a correlation between SULF1 and M2 macrophages was observed, providing a novel perspective for treating patients with HP and future studies.
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Affiliation(s)
- Jie He
- Clinical Medical College of Chengdu Medical College, Chengdu, China
- Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Chengdu Medical College, Chengdu, China
- Key Laboratory of Geriatric Respiratory Diseases of Sichuan Higher Education Institutes, Chengdu, China
| | - Bo Wang
- Clinical Medical College of Chengdu Medical College, Chengdu, China
- Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Chengdu Medical College, Chengdu, China
- Key Laboratory of Geriatric Respiratory Diseases of Sichuan Higher Education Institutes, Chengdu, China
| | - Meifeng Chen
- Clinical Medical College of Chengdu Medical College, Chengdu, China
- Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Chengdu Medical College, Chengdu, China
- Key Laboratory of Geriatric Respiratory Diseases of Sichuan Higher Education Institutes, Chengdu, China
| | - Lingmeng Song
- Clinical Medical College of Chengdu Medical College, Chengdu, China
- Medical Department, The First Affiliated Hospital of Chengdu Medical College, Chengdu, China
| | - Hezhi Li
- Clinical Medical College of Chengdu Medical College, Chengdu, China
- Department of Anesthesiology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, China
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22
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Saha E, Guebila MB, Fanfani V, Fischer J, Shutta KH, Mandros P, DeMeo DL, Quackenbush J, Lopes-Ramos CM. Gene regulatory Networks Reveal Sex Difference in Lung Adenocarcinoma. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.22.559001. [PMID: 37790409 PMCID: PMC10543009 DOI: 10.1101/2023.09.22.559001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
Lung adenocarcinoma (LUAD) has been observed to have significant sex differences in incidence, prognosis, and response to therapy. However, the molecular mechanisms responsible for these disparities have not been investigated extensively. Sample-specific gene regulatory network methods were used to analyze RNA sequencing data from non-cancerous human lung samples from The Genotype Tissue Expression Project (GTEx) and lung adenocarcinoma primary tumor samples from The Cancer Genome Atlas (TCGA); results were validated on independent data. We observe that genes associated with key biological pathways including cell proliferation, immune response and drug metabolism are differentially regulated between males and females in both healthy lung tissue, as well as in tumor, and that these regulatory differences are further perturbed by tobacco smoking. We also uncovered significant sex bias in transcription factor targeting patterns of clinically actionable oncogenes and tumor suppressor genes, including AKT2 and KRAS. Using differentially regulated genes between healthy and tumor samples in conjunction with a drug repurposing tool, we identified several small-molecule drugs that might have sex-biased efficacy as cancer therapeutics and further validated this observation using an independent cell line database. These findings underscore the importance of including sex as a biological variable and considering gene regulatory processes in developing strategies for disease prevention and management.
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Affiliation(s)
- Enakshi Saha
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
| | - Marouen Ben Guebila
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
| | - Viola Fanfani
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
| | - Jonas Fischer
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
| | - Katherine H Shutta
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA 02115
| | - Panagiotis Mandros
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
| | - Dawn L DeMeo
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA 02115
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - John Quackenbush
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA 02115
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02115, USA
| | - Camila M Lopes-Ramos
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA 02115
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
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23
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Chen Y, Wang Y, Li Z, Jing J, Jiang D, Yuan X, Li F. Exploration of the Mechanism of Shengxian Decoction Against Chronic Obstructive Pulmonary Disease Based on Network Pharmacology and Experimental Verification. Assay Drug Dev Technol 2023; 21:258-272. [PMID: 37682969 DOI: 10.1089/adt.2023.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/10/2023] Open
Abstract
Shengxian decoction (SXT) is clinically used in chronic obstructive pulmonary disease (COPD) treatment. This study aimed to explore the mechanism and target genes of SXT acting on COPD. Differentially expressed genes (DEGs) between COPD and controls were identified and then performed enrichment analysis. The effective active compounds and corresponding target genes were obtained from the traditional Chinese medicine systems pharmacology database. We also compiled COPD related genes from the GeneCards database. Through the protein-protein interaction (PPI) network and least absolute shrinkage and selection operator (LASSO) regression was performed to identify key genes. Molecular docking was used for docking of key genes and compounds. The expression of key genes was detected by quantitative real-time PCR in COPD patients and bronchial epithelial cells stimulated with cigarette stroke extract (CSE). We identified 1,458 intersected DEGs from GSE47460 and GSE57148 datasets. Compared with intersected DEGs, we obtained 33 SXT target COPD-related genes. PI3K-Akt signaling pathway, MAPK signaling pathway, and focal adhesion were enriched by these 33 genes, as well as intersected DEGs. According to LASSO regression, there were 12 genes considered as signature genes. Then we constructed active compounds and corresponding six target genes. Finally, HIF1A and IL1B were selected as key genes by combining PPI network. HIF1A and IL1B were all upregulated expression in COPD and CSE stimulated cells and recovered in SXT treated CSE stimulated cells. This study provides a scientific basis for the identification of active compounds and target genes of SXT in the treatment of COPD.
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Affiliation(s)
- Yifei Chen
- Basic Teaching and Research Office of Traditional Chinese Medicine, College of Traditional Chinese Medicine, Xinjiang Medical University, Shuimogou, Urumqi, China
| | - Yiming Wang
- Department of Acupuncture, Traditional Chinese Medicine Hospital Affiliated to Xinjiang Medical University, Shaybagh, Urumqi, China
| | - Zheng Li
- Department of Respiration, Traditional Chinese Medicine Hospital Affiliated to Xinjiang Medical University, Shaybagh, Urumqi, China
- Department of Respiration, National Clinical Research Base of Traditional Chinese Medicine in Xinjiang, Shaybagh, Urumqi, China
| | - Jing Jing
- Department of Respiration, Traditional Chinese Medicine Hospital Affiliated to Xinjiang Medical University, Shaybagh, Urumqi, China
- Department of Respiration, National Clinical Research Base of Traditional Chinese Medicine in Xinjiang, Shaybagh, Urumqi, China
| | - De Jiang
- Basic Teaching and Research Office of Traditional Chinese Medicine, College of Traditional Chinese Medicine, Xinjiang Medical University, Shuimogou, Urumqi, China
| | - Xiaoxia Yuan
- Basic Teaching and Research Office of Traditional Chinese Medicine, College of Traditional Chinese Medicine, Xinjiang Medical University, Shuimogou, Urumqi, China
| | - Fengsen Li
- Department of Respiration, Traditional Chinese Medicine Hospital Affiliated to Xinjiang Medical University, Shaybagh, Urumqi, China
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24
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Zhang YH, Cho MH, Morrow JD, Castaldi PJ, Hersh CP, Midha MK, Hoopmann MR, Lutz SM, Moritz RL, Silverman EK. Integrating Genetics, Transcriptomics, and Proteomics in Lung Tissue to Investigate Chronic Obstructive Pulmonary Disease. Am J Respir Cell Mol Biol 2023; 68:651-663. [PMID: 36780661 PMCID: PMC10257075 DOI: 10.1165/rcmb.2022-0302oc] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Accepted: 02/13/2023] [Indexed: 02/15/2023] Open
Abstract
The integration of transcriptomic and proteomic data from lung tissue with chronic obstructive pulmonary disease (COPD)-associated genetic variants could provide insight into the biological mechanisms of COPD. Here, we assessed associations between lung transcriptomics and proteomics with COPD in 98 subjects from the Lung Tissue Research Consortium. Low correlations between transcriptomics and proteomics were generally observed, but higher correlations were found for COPD-associated proteins. We integrated COPD risk SNPs or SNPs near COPD-associated proteins with lung transcripts and proteins to identify regulatory cis-quantitative trait loci (QTLs). Significant expression QTLs (eQTLs) and protein QTLs (pQTLs) were found regulating multiple COPD-associated biomarkers. We investigated mediated associations from significant pQTLs through transcripts to protein levels of COPD-associated proteins. We also attempted to identify colocalized effects between COPD genome-wide association studies and eQTL and pQTL signals. Evidence was found for colocalization between COPD genome-wide association study signals and a pQTL for RHOB and an eQTL for DSP. We applied weighted gene co-expression network analysis to find consensus COPD-associated network modules. Two network modules generated by consensus weighted gene co-expression network analysis were associated with COPD with a false discovery rate lower than 0.05. One network module is related to the catenin complex, and the other module is related to plasma membrane components. In summary, multiple cis-acting determinants of transcripts and proteins associated with COPD were identified. Colocalization analysis, mediation analysis, and correlation-based network analysis of multiple omics data may identify key genes and proteins that work together to influence COPD pathogenesis.
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Affiliation(s)
- Yu-Hang Zhang
- Channing Division of Network Medicine, Harvard Medical School, and
| | - Michael H. Cho
- Channing Division of Network Medicine, Harvard Medical School, and
- Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Boston, Massachusetts; and
| | | | | | - Craig P. Hersh
- Channing Division of Network Medicine, Harvard Medical School, and
- Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Boston, Massachusetts; and
| | | | | | - Sharon M. Lutz
- Channing Division of Network Medicine, Harvard Medical School, and
- Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Boston, Massachusetts; and
| | | | - Edwin K. Silverman
- Channing Division of Network Medicine, Harvard Medical School, and
- Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Boston, Massachusetts; and
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25
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Ruan P, Todd JL, Zhao H, Liu Y, Vinisko R, Soellner JF, Schmid R, Kaner RJ, Luckhardt TR, Neely ML, Noth I, Porteous M, Raj R, Safdar Z, Strek ME, Hesslinger C, Palmer SM, Leonard TB, Salisbury ML. Integrative multi-omics analysis reveals novel idiopathic pulmonary fibrosis endotypes associated with disease progression. Respir Res 2023; 24:141. [PMID: 37344825 PMCID: PMC10283254 DOI: 10.1186/s12931-023-02435-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Accepted: 04/26/2023] [Indexed: 06/23/2023] Open
Abstract
BACKGROUND Idiopathic pulmonary fibrosis (IPF) is characterized by the accumulation of extracellular matrix in the pulmonary interstitium and progressive functional decline. We hypothesized that integration of multi-omics data would identify clinically meaningful molecular endotypes of IPF. METHODS The IPF-PRO Registry is a prospective registry of patients with IPF. Proteomic and transcriptomic (including total RNA [toRNA] and microRNA [miRNA]) analyses were performed using blood collected at enrollment. Molecular data were integrated using Similarity Network Fusion, followed by unsupervised spectral clustering to identify molecular subtypes. Cox proportional hazards models tested the relationship between these subtypes and progression-free and transplant-free survival. The molecular subtypes were compared to risk groups based on a previously described 52-gene (toRNA expression) signature. Biological characteristics of the molecular subtypes were evaluated via linear regression differential expression and canonical pathways (Ingenuity Pathway Analysis [IPA]) over-representation analyses. RESULTS Among 232 subjects, two molecular subtypes were identified. Subtype 1 (n = 105, 45.3%) and Subtype 2 (n = 127, 54.7%) had similar distributions of age (70.1 +/- 8.1 vs. 69.3 +/- 7.6 years; p = 0.31) and sex (79.1% vs. 70.1% males, p = 0.16). Subtype 1 had more severe disease based on composite physiologic index (CPI) (55.8 vs. 51.2; p = 0.002). After adjusting for CPI and antifibrotic treatment at enrollment, subtype 1 experienced shorter progression-free survival (HR 1.79, 95% CI 1.28,2.56; p = 0.0008) and similar transplant-free survival (HR 1.30, 95% CI 0.87,1.96; p = 0.20) as subtype 2. There was little agreement in the distribution of subjects to the molecular subtypes and the risk groups based on 52-gene signature (kappa = 0.04, 95% CI= -0.08, 0.17), and the 52-gene signature risk groups were associated with differences in transplant-free but not progression-free survival. Based on heatmaps and differential expression analyses, proteins and miRNAs (but not toRNA) contributed to classification of subjects to the molecular subtypes. The IPA showed enrichment in pulmonary fibrosis-relevant pathways, including mTOR, VEGF, PDGF, and B-cell receptor signaling. CONCLUSIONS Integration of transcriptomic and proteomic data from blood enabled identification of clinically meaningful molecular endotypes of IPF. If validated, these endotypes could facilitate identification of individuals likely to experience disease progression and enrichment of clinical trials. TRIAL REGISTRATION NCT01915511.
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Affiliation(s)
- Peifeng Ruan
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
| | - Jamie L Todd
- Duke Clinical Research Institute, Durham, NC, USA
- Duke University Medical Center, Durham, NC, USA
| | - Hongyu Zhao
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
| | - Yi Liu
- Boehringer Ingelheim Pharmaceuticals, Inc, Ridgefield, CT, USA
| | - Richard Vinisko
- Boehringer Ingelheim Pharmaceuticals, Inc, Ridgefield, CT, USA
| | | | - Ramona Schmid
- Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany
| | | | - Tracy R Luckhardt
- Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Megan L Neely
- Duke Clinical Research Institute, Durham, NC, USA
- Duke University Medical Center, Durham, NC, USA
| | - Imre Noth
- Division of Pulmonary and Critical Care Medicine, University of Virginia, Charlottesville, VA, USA
| | - Mary Porteous
- Hospital of the University of Pennsylvania, Philadelphia, PA, USA
| | - Rishi Raj
- Stanford University School of Medicine, Stanford, CA, USA
| | | | - Mary E Strek
- Section of Pulmonary and Critical Care Medicine, University of Chicago, Chicago, IL, USA
| | | | - Scott M Palmer
- Duke Clinical Research Institute, Durham, NC, USA
- Duke University Medical Center, Durham, NC, USA
| | | | - Margaret L Salisbury
- Department of Medicine, Vanderbilt University Medical Center, 1211 Medical Center Drive, 37232, Nashville, TN, USA.
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26
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Hobbs BD, Morrow JD, Wang XW, Liu YY, DeMeo DL, Hersh CP, Celli BR, Bueno R, Criner GJ, Silverman EK, Cho MH. Identifying chronic obstructive pulmonary disease from integrative omics and clustering in lung tissue. BMC Pulm Med 2023; 23:115. [PMID: 37041558 PMCID: PMC10091624 DOI: 10.1186/s12890-023-02389-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 03/15/2023] [Indexed: 04/13/2023] Open
Abstract
BACKGROUND Chronic obstructive pulmonary disease (COPD) is a highly morbid and heterogenous disease. While COPD is defined by spirometry, many COPD characteristics are seen in cigarette smokers with normal spirometry. The extent to which COPD and COPD heterogeneity is captured in omics of lung tissue is not known. METHODS We clustered gene expression and methylation data in 78 lung tissue samples from former smokers with normal lung function or severe COPD. We applied two integrative omics clustering methods: (1) Similarity Network Fusion (SNF) and (2) Entropy-Based Consensus Clustering (ECC). RESULTS SNF clusters were not significantly different by the percentage of COPD cases (48.8% vs. 68.6%, p = 0.13), though were different according to median forced expiratory volume in one second (FEV1) % predicted (82 vs. 31, p = 0.017). In contrast, the ECC clusters showed stronger evidence of separation by COPD case status (48.2% vs. 81.8%, p = 0.013) and similar stratification by median FEV1% predicted (82 vs. 30.5, p = 0.0059). ECC clusters using both gene expression and methylation were identical to the ECC clustering solution generated using methylation data alone. Both methods selected clusters with differentially expressed transcripts enriched for interleukin signaling and immunoregulatory interactions between lymphoid and non-lymphoid cells. CONCLUSIONS Unsupervised clustering analysis from integrated gene expression and methylation data in lung tissue resulted in clusters with modest concordance with COPD, though were enriched in pathways potentially contributing to COPD-related pathology and heterogeneity.
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Affiliation(s)
- Brian D Hobbs
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Ave, Rm 460, Boston, MA, 02115, USA.
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Jarrett D Morrow
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Ave, Rm 460, Boston, MA, 02115, USA
| | - Xu-Wen Wang
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Ave, Rm 460, Boston, MA, 02115, USA
| | - Yang-Yu Liu
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Ave, Rm 460, Boston, MA, 02115, USA
| | - Dawn L DeMeo
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Ave, Rm 460, Boston, MA, 02115, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Craig P Hersh
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Ave, Rm 460, Boston, MA, 02115, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Bartolome R Celli
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Raphael Bueno
- Division of Thoracic Surgery, Brigham and Women's Hospital, Boston, MA, USA
| | - Gerard J Criner
- Division of Pulmonary and Critical Care Medicine, Temple University School of Medicine, Philadelphia, PA, USA
| | - Edwin K Silverman
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Ave, Rm 460, Boston, MA, 02115, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Michael H Cho
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Ave, Rm 460, Boston, MA, 02115, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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27
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Yi E, Cao W, Zhang J, Lin B, Wang Z, Wang X, Bai G, Mei X, Xie C, Jin J, Liu X, Li H, Wu F, Lin Z, Sun R, Li B, Zhou Y, Ran P. Genetic screening of MMP1 as a potential pathogenic gene in chronic obstructive pulmonary disease. Life Sci 2023; 313:121214. [PMID: 36442527 DOI: 10.1016/j.lfs.2022.121214] [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: 09/15/2022] [Revised: 11/16/2022] [Accepted: 11/17/2022] [Indexed: 11/27/2022]
Abstract
BACKGROUND Chronic obstructive pulmonary disease (COPD) is a complex and heterogeneous syndrome. Airway inflammation and remodeling are the two key processes involved in COPD pathogenesis. However, the key pathogenic genes driving COPD development have not been revealed. This study aims to identify and validate hub gene(s) underlying COPD development through bioinformatics analysis and experimental validation. METHODS Three lung tissue sequencing datasets of the COPD (including GSE38974, GSE103174, and GSE106986) were analyzed. Further, differentially expressed genes (DEGs) were used to compare patients with COPD with non-COPD individuals, and the Robust Rank Aggregation (RRA) analysis was also performed. Results revealed a series of potential pathogenic genes of COPD. DEGs were subjected to KEGG, GO, and GSEA analyses. The scRNA dataset of human lung tissues (Human Lung Cell Atlas), and human primary airway epithelial cells (GSE134147) were used to identify the cell subtype localization. The qRT-PCR assay was performed in the human lung tissues, COPD mice model, and primary bronchial epithelial cells at the air-liquid interface (ALI) under cigarette smoke extract (CSE) stimulation to verify the expression of the hub genes. LASSO and GLM analysis with the hub genes were performed to identify the most critical gene. RNA-seq was performed after knocking down the critical gene using siRNA in HBECs at ALI. The potential role of the critical gene was confirmed through qRT-PCR, Western blot, and Immunofluorescence (IF) assays. RESULTS A total of 98 genes were significantly and differently expressed in 3 GEO datasets. The KEGG and GO analyses showed that most of these genes are responsible for inflammation, immunity, and cell proliferation. The core gene set including 15 genes was screened out and consequently, the MMP1 was the most likely responsible for the progression of COPD. Moreover, we confirmed that MMP1 is significantly related to inflammatory effects and cilia function in human bronchial epithelial cells cultured at the air-liquid interface (ALI). CONCLUSION In summary, we confirmed that inflammation and cell proliferation are potentially critical processes in COPD occurrence and development. A total of 15 potential hub genes were identified among which MMP1 was the most likely gene responsible for the development of COPD. Therefore, MMP1 is a potential molecular target of COPD therapy.
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Affiliation(s)
- Erkang Yi
- State Key Laboratory of Respiratory Diseases, National Clinical Research Center for Respiratory Diseases, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Weitao Cao
- State Key Laboratory of Respiratory Diseases, National Clinical Research Center for Respiratory Diseases, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Jiahuan Zhang
- State Key Laboratory of Respiratory Diseases, National Clinical Research Center for Respiratory Diseases, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Biting Lin
- GMU-GIBH Joint School of Life Sciences, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Zihui Wang
- State Key Laboratory of Respiratory Diseases, National Clinical Research Center for Respiratory Diseases, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Xiaoyu Wang
- State Key Laboratory of Respiratory Diseases, National Clinical Research Center for Respiratory Diseases, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Ge Bai
- State Key Laboratory of Respiratory Diseases, National Clinical Research Center for Respiratory Diseases, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Xinyue Mei
- State Key Laboratory of Respiratory Diseases, National Clinical Research Center for Respiratory Diseases, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - ChengShu Xie
- GMU-GIBH Joint School of Life Sciences, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Jing Jin
- State Key Laboratory of Respiratory Diseases, National Clinical Research Center for Respiratory Diseases, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Xinyuan Liu
- State Key Laboratory of Respiratory Diseases, National Clinical Research Center for Respiratory Diseases, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Haiqing Li
- State Key Laboratory of Respiratory Diseases, National Clinical Research Center for Respiratory Diseases, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Fan Wu
- State Key Laboratory of Respiratory Diseases, National Clinical Research Center for Respiratory Diseases, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Zhiwei Lin
- GMU-GIBH Joint School of Life Sciences, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Ruiting Sun
- State Key Laboratory of Respiratory Diseases, National Clinical Research Center for Respiratory Diseases, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Bing Li
- GMU-GIBH Joint School of Life Sciences, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Yumin Zhou
- State Key Laboratory of Respiratory Diseases, National Clinical Research Center for Respiratory Diseases, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Pixin Ran
- State Key Laboratory of Respiratory Diseases, National Clinical Research Center for Respiratory Diseases, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China; Guangzhou Laboratory, Bioland, Guangzhou, China.
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28
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Zhang J, Zhang Y, Wang Z, Zhao J, Li Z, Wang K, Tian L, Yao B, Wu Q, Wang T, Wang J. Genes related to N6-methyladenosine in the diagnosis and prognosis of idiopathic pulmonary fibrosis. Front Genet 2023; 13:1102422. [PMID: 36685949 PMCID: PMC9846232 DOI: 10.3389/fgene.2022.1102422] [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: 11/18/2022] [Accepted: 12/12/2022] [Indexed: 01/05/2023] Open
Abstract
Introduction: Idiopathic pulmonary fibrosis (IPF) is a chronic progressive pulmonary fibrotic disease with unknown etiology and poor outcomes. It severely affects the quality of life. In this study, we comprehensively analyzed the expression of N6-methyladenosine (m6A) RNA methylation regulators using gene expression data from various tissue sources in IPF patients and healthy volunteers. Methods: The gene expression matrix and clinical characteristics of IPF patients were retrieved from the Gene Expression Omnibus database. A random forest model was used to construct diagnosis signature m6A regulators. Regression analysis and correlation analysis were used to identify prognosis m6A regulators. Consensus cluster analysis was used to construct different m6A prognosis risk groups, then functional enrichment, immune infiltration and drug sensitivity analysis were performed. Result: Five candidate m6A genes from lung tissue were used to predict the incidence, and the incidence was validated using datasets from bronchoalveolar lavage fluid (BALF) and peripheral blood mononuclear cells. Subsequently, the BALF dataset containing outcomes data was used for the prognosis analysis of m6A regulators. METTL14, G3BP2, and ZC3H13 were independent protective factors. Using correlation analysis with lung function in the lung tissue-derived dataset, METTL14 was a protective factor in IPF. Based on METTL14 and G3BP2, a consensus cluster analysis was applied to distinguish the prognostic m6A regulation patterns. The low-risk group's prognosis was significantly better than the high-risk group. Biological processes regulated by various risk groups included fibrogenesis and cell adhesion. Analysis of immune cell infiltration showed upregulation of neutrophils in the m6A high-risk group. Subsequently, five m6A high-risk group sensitive drugs and one m6A low-risk group sensitive drug were identified. Discussion: These findings suggest that m6A regulators are involved in the diagnosis and prognosis of IPF, and m6A patterns are a method to identify IPF outcomes.
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Affiliation(s)
- Jingcheng Zhang
- Northeast Asia Research Institute of Traditional Chinese Medicine, Changchun University of Chinese Medicine, Changchun, China
| | - Ying Zhang
- Department of Respiratory, The Affiliated Hospital to Changchun University of Chinese Medicine, Changchun, China
| | - Ziyuan Wang
- College of Traditional Chinese Medicine, Changchun University of Chinese Medicine, Changchun, China
| | - Jiachao Zhao
- College of Integrated Traditional Chinese and Western Medicine, Changchun University of Chinese Medicine, Changchun, China
| | - Zhenyu Li
- College of Traditional Chinese Medicine, Changchun University of Chinese Medicine, Changchun, China
| | - Keju Wang
- College of Traditional Chinese Medicine, Changchun University of Chinese Medicine, Changchun, China
| | - Lin Tian
- Department of Respiratory, The Affiliated Hospital to Changchun University of Chinese Medicine, Changchun, China
| | - Baojin Yao
- Northeast Asia Research Institute of Traditional Chinese Medicine, Changchun University of Chinese Medicine, Changchun, China
| | - Qibiao Wu
- State Key Laboratory of Quality Research in Chinese Medicines, Faculty of Chinese Medicine, Macau University of Science and Technology, Macau, China,Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangdong University of Technology, Guangzhou, China,Zhuhai MUST Science and Technology Research Institute, Zhuhai, China,*Correspondence: Qibiao Wu, ; Tan Wang, ; Jing Wang,
| | - Tan Wang
- Department of Respiratory, The Affiliated Hospital to Changchun University of Chinese Medicine, Changchun, China,*Correspondence: Qibiao Wu, ; Tan Wang, ; Jing Wang,
| | - Jing Wang
- Northeast Asia Research Institute of Traditional Chinese Medicine, Changchun University of Chinese Medicine, Changchun, China,Department of Respiratory, The Affiliated Hospital to Changchun University of Chinese Medicine, Changchun, China,*Correspondence: Qibiao Wu, ; Tan Wang, ; Jing Wang,
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29
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He J, Zhang J, Ren X. Krebs von den lungen-6 as a clinical marker for hypersensitivity pneumonitis: A meta-analysis and bioinformatics analysis. Front Immunol 2022; 13:1041098. [PMID: 36532009 PMCID: PMC9748086 DOI: 10.3389/fimmu.2022.1041098] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2022] [Accepted: 11/14/2022] [Indexed: 12/05/2022] Open
Abstract
Aim Hypersensitivity pneumonitis (HP), also referred to as exogenous allergic alveolitis, is one of the most common interstitial lung diseases (ILDs). A potential immune biomarker, Krebs von den lgen-6 (KL-6) characterizes the progression and severity of HP. The meta-analysis in this study was conducted to elucidate the variations in the concentrations of KL-6 in different types of HP. Methods A systematic search of various databases such as EMBASE, Pubmed, CNKI, VIP, Web of Science, and WanFang was carried out to find relevant published articles between January 1980 and August 2022 that explored the relationship between KL-6 and allergic pneumonia. Standardized mean difference (SMD) and 95% confidence interval (CI) were used as effect sizes for comparison among different groups. The GSE47460 and GSE150910 datasets were downloaded to extract and validate the differences in KL-6 mRNA expression between HP lung tissue and healthy controls. Furthermore, the single-cell sequencing dataset GSE135893 was downloaded to extract KL-6 mRNA expression in type II alveolar epithelial cells to validate the differences between HP and healthy controls. Two researchers evaluated the quality of the included studies by employing Newcastle-Ottawa Scale. All the qualified studies were subjected to statistical analyses carried out utilizing RevMan 5.2, Stata 11.0, and R software 4.1.3. Results Twenty studies aligned perfectly with the inclusion criteria of the meta. The concentrations of KL-6 were substantially higher in the blood of HP patients as compared to the control group. Subgroup analyses were carried out in accordance with the allergen source and the results revealed that patients with different allergens had higher blood KL-6 concentrations than healthy controls. Additionally, different subgroups of subjects were created for meta-analysis as per the fibrosis status, race, measurement method, and sample type. The concentration of KL-6 in blood was much higher in all HP subgroups than in healthy control groups. Moreover, the bioinformatics analysis revealed that KL-6 mRNA expression was higher in HP lung tissue and type II alveolar epithelial cells as compared to healthy controls. Conclusion The present meta-analysis and bioinformatics analysis suggested that the concentration levels of KL-6 varied between HP patients and healthy individuals, and the KL-6 concentrations may be higher in the blood samples of HP patients. Systematic review registration https://www.crd.york.ac.uk/prospero/, CRD42022355334.
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Affiliation(s)
- Jie He
- Clinical Medical College of Chengdu Medical College. Chengdu, Sichuan, China,Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, China,*Correspondence: Jie He,
| | - Jiangliu Zhang
- Clinical Medical College of Chengdu Medical College. Chengdu, Sichuan, China,Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, China
| | - Xinyi Ren
- Clinical Medical College of Chengdu Medical College. Chengdu, Sichuan, China,Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, China
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30
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Zhang L, Tang C, Zhang M, Tong X, Xie Y, Yan R, Wang X, Zhang X, Liu D, Li S. Single cell meta-analysis of EndMT and EMT state in COVID-19. Front Immunol 2022; 13:976512. [PMID: 36248845 PMCID: PMC9558222 DOI: 10.3389/fimmu.2022.976512] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Accepted: 08/24/2022] [Indexed: 11/13/2022] Open
Abstract
COVID-19 prognoses suggests that a proportion of patients develop fibrosis, but there is no evidence to indicate whether patients have progression of mesenchymal transition (MT) in the lungs. The role of MT during the COVID-19 pandemic remains poorly understood. Using single-cell RNA sequencing, we profiled the transcriptomes of cells from the lungs of healthy individuals (n = 45), COVID-19 patients (n = 58), and idiopathic pulmonary fibrosis (IPF) patients (n = 64) human lungs to map the entire MT change. This analysis enabled us to map all high-resolution matrix-producing cells and identify distinct subpopulations of endothelial cells (ECs) and epithelial cells as the primary cellular sources of MT clusters during COVID-19. For the first time, we have identied early and late subgroups of endothelial mesenchymal transition (EndMT) and epithelial-mesenchymal transition (EMT) using analysis of public databases for single-cell sequencing. We assessed epithelial subgroups by age, smoking status, and gender, and the data suggest that the proportional changes in EMT in COVID-19 are statistically significant. Further enumeration of early and late EMT suggests a correlation between invasive genes and COVID-19. Finally, EndMT is upregulated in COVID-19 patients and enriched for more inflammatory cytokines. Further, by classifying EndMT as early or late stages, we found that early EndMT was positively correlated with entry factors but this was not true for late EndMT. Exploring the MT state of may help to mitigate the fibrosis impact of SARS-CoV-2 infection.
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Affiliation(s)
- Lanlan Zhang
- Division of Pulmonary Diseases, State Key Laboratory of Biotherapy, And Department of Respiratory and Critical Care Medicine, West China Hospital of Sichuan University, Chengdu, China
- *Correspondence: Dan Liu, ; Lanlan Zhang, ; Xin Zhang,
| | - Chuang Tang
- Department of Gastroenterology, West China (Airport) Hospital, Sichuan University, Chengdu, China
| | - Min Zhang
- Oncology Bussiness Department, Novogene Co., Ltd, Beijing, China
| | - Xia Tong
- Department of Gastroenterology, West China (Airport) Hospital, Sichuan University, Chengdu, China
- Department of Gastroenterology, West China Hospital of Sichuan University, Chengdu, China
| | - Yingying Xie
- Department of Nephrology, Seventh Affiliated Hospital Sun Yat-sen University, Shenzhen, China
| | | | - Xiangjun Wang
- First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Xin Zhang
- Department of Gastroenterology, West China (Airport) Hospital, Sichuan University, Chengdu, China
- Department of Gastroenterology, West China Hospital of Sichuan University, Chengdu, China
- *Correspondence: Dan Liu, ; Lanlan Zhang, ; Xin Zhang,
| | - Dan Liu
- Division of Pulmonary Diseases, State Key Laboratory of Biotherapy, And Department of Respiratory and Critical Care Medicine, West China Hospital of Sichuan University, Chengdu, China
- *Correspondence: Dan Liu, ; Lanlan Zhang, ; Xin Zhang,
| | - Shasha Li
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States
- Harvard Medical School, Boston, MA, United States
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31
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Tebani A, Bekri S. [The promise of omics in the precision medicine era]. Rev Med Interne 2022; 43:649-660. [PMID: 36041909 DOI: 10.1016/j.revmed.2022.07.009] [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: 06/10/2022] [Accepted: 07/12/2022] [Indexed: 10/15/2022]
Abstract
The rise of omics technologies that simultaneously measure thousands of molecules in a complex biological sample represents the core of systems biology. These technologies have profoundly impacted biomarkers and therapeutic targets discovery in the precision medicine era. Systems biology aims to perform a systematic probing of complex interactions in biological systems. Powered by high-throughput omics technologies and high-performance computing, systems biology provides relevant, resolving, and multi-scale overviews from cells to populations. Precision medicine takes advantage of these conceptual and technological developments and is based on two main pillars: the generation of multimodal data and their subsequent modeling. High-throughput omics technologies enable the comprehensive and holistic extraction of biological information, while computational capabilities enable multidimensional modeling and, as a result, offer an intuitive and intelligible visualization. Despite their promise, translating these technologies into clinically actionable tools has been slow. In this contribution, we present the most recent multi-omics data generation and analysis strategies and their clinical deployment in the post-genomic era. Furthermore, medical application challenges of omics-based biomarkers are discussed.
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Affiliation(s)
- A Tebani
- UNIROUEN, Inserm U1245, Department of Metabolic Biochemistry, Normandie University, CHU Rouen, 76000 Rouen, France.
| | - S Bekri
- UNIROUEN, Inserm U1245, Department of Metabolic Biochemistry, Normandie University, CHU Rouen, 76000 Rouen, France
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Mostafaei S, Borna H, Emamvirdizadeh A, Arabfard M, Ahmadi A, Salimian J, Salesi M, Azimzadeh Jamalkandi S. Causal Path of COPD Progression-Associated Genes in Different Biological Samples. COPD 2022; 19:290-299. [PMID: 35696265 DOI: 10.1080/15412555.2022.2081541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Chronic obstructive pulmonary disease (COPD) is a progressive inflammatory disease with pulmonary and extra-pulmonary complications. Due to the disease's systemic nature, many investigations investigated the genetic alterations in various biological samples. We aimed to infer causal genes in COPD's pathogenesis in different biological samples using elastic-net logistic regression and the Structural Equation Model. Samples of small airway epithelial cells, bronchoalveolar lavage macrophages, lung tissue biopsy, sputum, and blood samples were selected (135, 70, 235, 143, and 226 samples, respectively). Elastic-net Logistic Regression analysis was implemented to identify the most important genes involved in COPD progression. Thirty-three candidate genes were identified as essential factors in the pathogenesis of COPD and regulation of lung function. Recognized candidate genes in small airway epithelial (SAE) cells have the highest area under the ROC curve (AUC = 97%, SD = 3.9%). Our analysis indicates that macrophages and epithelial cells are more influential in COPD progression at the transcriptome level.
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Affiliation(s)
- Shayan Mostafaei
- Chemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran.,Department of Biostatistics, Faculty of Health, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Hojat Borna
- Chemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran.,Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran
| | - Alireza Emamvirdizadeh
- Department of Molecular Genetics, Faculty of Bio Sciences, Tehran North Branch, Islamic Azad University, Tehran, Iran
| | - Masoud Arabfard
- Chemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Ali Ahmadi
- Molecular Biology Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Jafar Salimian
- Chemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Mahmood Salesi
- Chemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Sadegh Azimzadeh Jamalkandi
- Chemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
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Preisendörfer S, Ishikawa Y, Hennen E, Winklmeier S, Schupp JC, Knüppel L, Fernandez IE, Binzenhöfer L, Flatley A, Juan-Guardela BM, Ruppert C, Guenther A, Frankenberger M, Hatz RA, Kneidinger N, Behr J, Feederle R, Schepers A, Hilgendorff A, Kaminski N, Meinl E, Bächinger HP, Eickelberg O, Staab-Weijnitz CA. FK506-Binding Protein 11 Is a Novel Plasma Cell-Specific Antibody Folding Catalyst with Increased Expression in Idiopathic Pulmonary Fibrosis. Cells 2022; 11:1341. [PMID: 35456020 PMCID: PMC9027113 DOI: 10.3390/cells11081341] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 04/08/2022] [Accepted: 04/12/2022] [Indexed: 02/01/2023] Open
Abstract
Antibodies are central effectors of the adaptive immune response, widespread used therapeutics, but also potentially disease-causing biomolecules. Antibody folding catalysts in the plasma cell are incompletely defined. Idiopathic pulmonary fibrosis (IPF) is a fatal chronic lung disease with increasingly recognized autoimmune features. We found elevated expression of FK506-binding protein 11 (FKBP11) in IPF lungs where FKBP11 specifically localized to antibody-producing plasma cells. Suggesting a general role in plasma cells, plasma cell-specific FKBP11 expression was equally observed in lymphatic tissues, and in vitro B cell to plasma cell differentiation was accompanied by induction of FKBP11 expression. Recombinant human FKBP11 was able to refold IgG antibody in vitro and inhibited by FK506, strongly supporting a function as antibody peptidyl-prolyl cis-trans isomerase. Induction of ER stress in cell lines demonstrated induction of FKBP11 in the context of the unfolded protein response in an X-box-binding protein 1 (XBP1)-dependent manner. While deficiency of FKBP11 increased susceptibility to ER stress-mediated cell death in an alveolar epithelial cell line, FKBP11 knockdown in an antibody-producing hybridoma cell line neither induced cell death nor decreased expression or secretion of IgG antibody. Similarly, antibody secretion by the same hybridoma cell line was not affected by knockdown of the established antibody peptidyl-prolyl isomerase cyclophilin B. The results are consistent with FKBP11 as a novel XBP1-regulated antibody peptidyl-prolyl cis-trans isomerase and indicate significant redundancy in the ER-resident folding machinery of antibody-producing hybridoma cells.
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Affiliation(s)
- Stefan Preisendörfer
- Institute of Lung Health and Immunity and Comprehensive Pneumology Center with the CPC-M bioArchive, Member of the German Center of Lung Research (DZL), Helmholtz-Zentrum München, 81377 Munich, Germany; (S.P.); (E.H.); (L.K.); (I.E.F.); (L.B.); (M.F.); (A.H.); (O.E.)
| | - Yoshihiro Ishikawa
- Department of Biochemistry and Molecular Biology, Oregon Health & Science University, Portland, OR 97239, USA; (Y.I.); (H.P.B.)
| | - Elisabeth Hennen
- Institute of Lung Health and Immunity and Comprehensive Pneumology Center with the CPC-M bioArchive, Member of the German Center of Lung Research (DZL), Helmholtz-Zentrum München, 81377 Munich, Germany; (S.P.); (E.H.); (L.K.); (I.E.F.); (L.B.); (M.F.); (A.H.); (O.E.)
| | - Stephan Winklmeier
- Institute of Clinical Neuroimmunology, Biomedical Center and LMU Klinikum, Ludwig-Maximilians-Universität München, 81377 Munich, Germany; (S.W.); (E.M.)
| | - Jonas C. Schupp
- Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine, New Haven, CT 06520, USA; (J.C.S.); (B.M.J.-G.); (N.K.)
- Department of Respiratory Medicine, Hannover Medical School, Biomedical Research in End-Stage and Obstructive Lung Disease Hannover, Member of the German Center for Lung Research (DZL), 30625 Hannover, Germany
| | - Larissa Knüppel
- Institute of Lung Health and Immunity and Comprehensive Pneumology Center with the CPC-M bioArchive, Member of the German Center of Lung Research (DZL), Helmholtz-Zentrum München, 81377 Munich, Germany; (S.P.); (E.H.); (L.K.); (I.E.F.); (L.B.); (M.F.); (A.H.); (O.E.)
| | - Isis E. Fernandez
- Institute of Lung Health and Immunity and Comprehensive Pneumology Center with the CPC-M bioArchive, Member of the German Center of Lung Research (DZL), Helmholtz-Zentrum München, 81377 Munich, Germany; (S.P.); (E.H.); (L.K.); (I.E.F.); (L.B.); (M.F.); (A.H.); (O.E.)
- Department of Medicine V, LMU Klinikum, Ludwig-Maximilians-Universität München, Member of the German Center of Lung Research (DZL), 81377 Munich, Germany; (N.K.); (J.B.)
| | - Leonhard Binzenhöfer
- Institute of Lung Health and Immunity and Comprehensive Pneumology Center with the CPC-M bioArchive, Member of the German Center of Lung Research (DZL), Helmholtz-Zentrum München, 81377 Munich, Germany; (S.P.); (E.H.); (L.K.); (I.E.F.); (L.B.); (M.F.); (A.H.); (O.E.)
| | - Andrew Flatley
- Monoclonal Antibody Core Facility, Institute for Diabetes and Obesity, Helmholtz-Zentrum München, 85764 Neuherberg, Germany; (A.F.); (R.F.); (A.S.)
| | - Brenda M. Juan-Guardela
- Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine, New Haven, CT 06520, USA; (J.C.S.); (B.M.J.-G.); (N.K.)
| | - Clemens Ruppert
- Department of Internal Medicine, Medizinische Klinik II, Member of the German Center of Lung Research (DZL), 35392 Giessen, Germany; (C.R.); (A.G.)
| | - Andreas Guenther
- Department of Internal Medicine, Medizinische Klinik II, Member of the German Center of Lung Research (DZL), 35392 Giessen, Germany; (C.R.); (A.G.)
| | - Marion Frankenberger
- Institute of Lung Health and Immunity and Comprehensive Pneumology Center with the CPC-M bioArchive, Member of the German Center of Lung Research (DZL), Helmholtz-Zentrum München, 81377 Munich, Germany; (S.P.); (E.H.); (L.K.); (I.E.F.); (L.B.); (M.F.); (A.H.); (O.E.)
| | - Rudolf A. Hatz
- Thoraxchirurgisches Zentrum, Klinik für Allgemeine-, Viszeral-, Transplantations-, Gefäß- und Thoraxchirurgie, LMU Klinikum, Ludwig-Maximilians-Universität München, 81377 Munich, Germany;
- Asklepios Fachkliniken München-Gauting, 82131 Gauting, Germany
| | - Nikolaus Kneidinger
- Department of Medicine V, LMU Klinikum, Ludwig-Maximilians-Universität München, Member of the German Center of Lung Research (DZL), 81377 Munich, Germany; (N.K.); (J.B.)
| | - Jürgen Behr
- Department of Medicine V, LMU Klinikum, Ludwig-Maximilians-Universität München, Member of the German Center of Lung Research (DZL), 81377 Munich, Germany; (N.K.); (J.B.)
| | - Regina Feederle
- Monoclonal Antibody Core Facility, Institute for Diabetes and Obesity, Helmholtz-Zentrum München, 85764 Neuherberg, Germany; (A.F.); (R.F.); (A.S.)
| | - Aloys Schepers
- Monoclonal Antibody Core Facility, Institute for Diabetes and Obesity, Helmholtz-Zentrum München, 85764 Neuherberg, Germany; (A.F.); (R.F.); (A.S.)
| | - Anne Hilgendorff
- Institute of Lung Health and Immunity and Comprehensive Pneumology Center with the CPC-M bioArchive, Member of the German Center of Lung Research (DZL), Helmholtz-Zentrum München, 81377 Munich, Germany; (S.P.); (E.H.); (L.K.); (I.E.F.); (L.B.); (M.F.); (A.H.); (O.E.)
| | - Naftali Kaminski
- Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine, New Haven, CT 06520, USA; (J.C.S.); (B.M.J.-G.); (N.K.)
| | - Edgar Meinl
- Institute of Clinical Neuroimmunology, Biomedical Center and LMU Klinikum, Ludwig-Maximilians-Universität München, 81377 Munich, Germany; (S.W.); (E.M.)
| | - Hans Peter Bächinger
- Department of Biochemistry and Molecular Biology, Oregon Health & Science University, Portland, OR 97239, USA; (Y.I.); (H.P.B.)
| | - Oliver Eickelberg
- Institute of Lung Health and Immunity and Comprehensive Pneumology Center with the CPC-M bioArchive, Member of the German Center of Lung Research (DZL), Helmholtz-Zentrum München, 81377 Munich, Germany; (S.P.); (E.H.); (L.K.); (I.E.F.); (L.B.); (M.F.); (A.H.); (O.E.)
| | - Claudia A. Staab-Weijnitz
- Institute of Lung Health and Immunity and Comprehensive Pneumology Center with the CPC-M bioArchive, Member of the German Center of Lung Research (DZL), Helmholtz-Zentrum München, 81377 Munich, Germany; (S.P.); (E.H.); (L.K.); (I.E.F.); (L.B.); (M.F.); (A.H.); (O.E.)
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Vahabi N, Michailidis G. Unsupervised Multi-Omics Data Integration Methods: A Comprehensive Review. Front Genet 2022; 13:854752. [PMID: 35391796 PMCID: PMC8981526 DOI: 10.3389/fgene.2022.854752] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Accepted: 02/28/2022] [Indexed: 12/26/2022] Open
Abstract
Through the developments of Omics technologies and dissemination of large-scale datasets, such as those from The Cancer Genome Atlas, Alzheimer’s Disease Neuroimaging Initiative, and Genotype-Tissue Expression, it is becoming increasingly possible to study complex biological processes and disease mechanisms more holistically. However, to obtain a comprehensive view of these complex systems, it is crucial to integrate data across various Omics modalities, and also leverage external knowledge available in biological databases. This review aims to provide an overview of multi-Omics data integration methods with different statistical approaches, focusing on unsupervised learning tasks, including disease onset prediction, biomarker discovery, disease subtyping, module discovery, and network/pathway analysis. We also briefly review feature selection methods, multi-Omics data sets, and resources/tools that constitute critical components for carrying out the integration.
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Affiliation(s)
- Nasim Vahabi
- Informatics Institute, University of Florida, Gainesville, FL, United States
| | - George Michailidis
- Informatics Institute, University of Florida, Gainesville, FL, United States
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35
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Kim J, Yoon Y, Park HJ, Kim YH. Comparative Study of Classification Algorithms for Various DNA Microarray Data. Genes (Basel) 2022; 13:494. [PMID: 35328048 PMCID: PMC8951024 DOI: 10.3390/genes13030494] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 03/07/2022] [Indexed: 12/19/2022] Open
Abstract
Microarrays are applications of electrical engineering and technology in biology that allow simultaneous measurement of expression of numerous genes, and they can be used to analyze specific diseases. This study undertakes classification analyses of various microarrays to compare the performances of classification algorithms over different data traits. The datasets were classified into test and control groups based on five utilized machine learning methods, including MultiLayer Perceptron (MLP), Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), and k-Nearest Neighbors (KNN), and the resulting accuracies were compared. k-fold cross-validation was used in evaluating the performance and the result was analyzed by comparing the performances of the five machine learning methods. Through the experiments, it was observed that the two tree-based methods, DT and RF, showed similar trends in results and the remaining three methods, MLP, SVM, and DT, showed similar trends. DT and RF generally showed worse performance than other methods except for one dataset. This suggests that, for the effective classification of microarray data, selecting a classification algorithm that is suitable for data traits is crucial to ensure optimum performance.
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Affiliation(s)
- Jingeun Kim
- Department of IT Convergence Engineering, Gachon University, Seongnam-daero 1342, Seongnam-si 13120, Korea;
| | - Yourim Yoon
- Department of Computer Engineering, College of Information Technology, Gachon University, Seongnam-daero 1342, Sujeong-gu, Seongnam-si 13120, Korea
| | - Hye-Jin Park
- Department of Food Science and Biotechnology, College of BioNano Technology, Gachon University, Seongnam-daero 1342, Sujeong-gu, Seongnam-si 13120, Korea;
| | - Yong-Hyuk Kim
- School of Software, Kwangwoon University, 20 Kwangwoon-ro, Nowon-gu, Seoul 01897, Korea;
- Department of Cell and Regenerative Biology, School of Medicine and Public Health, University of Wisconsin-Madison, 1111 Highland Ave, Madison, WI 53705, USA
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36
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Lin J, Xue Y, Su W, Zhang Z, Wei Q, Huang T. Identification of Dysregulated Mechanisms and Candidate Gene Markers in Chronic Obstructive Pulmonary Disease. Int J Chron Obstruct Pulmon Dis 2022; 17:475-487. [PMID: 35281477 PMCID: PMC8904782 DOI: 10.2147/copd.s349694] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Accepted: 02/27/2022] [Indexed: 11/23/2022] Open
Abstract
Purpose This study aimed to identify candidate gene markers that may facilitate chronic obstructive pulmonary disease (COPD) diagnosis and treatment. Methods The GSE47460 and GSE151052 datasets were analyzed to identify differentially expressed mRNAs (DEmRs) between COPD patients and controls. DEmRs that were differentially expressed in the same direction in both datasets were analyzed for functional enrichment and for coexpression. Genes from the largest three modules were tested for their ability to diagnose COPD based on the area under the receiver operating characteristic curve (AUC). Genes with AUC > 0.7 in both datasets were used to perform regression based on the "least absolute shrinkage and selection operator" in order to identify feature genes. We also identified differentially expressed miRNAs (DEmiRs) between COPD patients and controls using the GSE38974 dataset, then constructed a regulatory network. We also examined associations between feature genes and immune cell infiltration in COPD, and we identified methylation markers of COPD using the GSE63704 dataset. Results A total of 1350 genes differentially regulated in the same direction in the GSE47460 and GSE151052 datasets were found. The genes were significantly enriched in immune-related biological functions. Of 186 modules identified using MEGENA, the largest were C1_ 6, C1_ 3, and C1_ 2. Of the 22 candidate genes screened based on AUC, 11 feature genes emerged from analysis of a subset of GSE47460 data, which we validated using another subset of GSE47460 data as well as the independent GSE151052 dataset. Feature genes correlated significantly with infiltration by immune cells. The feature genes GPC4 and RS1 were predicted to be regulated by miR-374a-3p. We identified 117 candidate methylation markers of COPD, including PRRG4. Conclusion The feature genes we identified may be potential diagnostic markers and therapeutic targets in COPD. These findings provide new leads for exploring disease mechanisms and targeted treatments.
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Affiliation(s)
- Jie Lin
- Department of Respiratory and Critical Care, The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, 530022, People’s Republic of China,Department of Respiratory and Critical Care, The First People’s Hospital of Nanning, Nanning, Guangxi, 530022, People’s Republic of China
| | - Yanlong Xue
- Department of Respiratory and Critical Care, The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, 530022, People’s Republic of China,Department of Respiratory and Critical Care, The First People’s Hospital of Nanning, Nanning, Guangxi, 530022, People’s Republic of China
| | - Wenyan Su
- Department of Respiratory and Critical Care, The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, 530022, People’s Republic of China,Department of Respiratory and Critical Care, The First People’s Hospital of Nanning, Nanning, Guangxi, 530022, People’s Republic of China
| | - Zan Zhang
- Department of Respiratory and Critical Care, The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, 530022, People’s Republic of China,Department of Respiratory and Critical Care, The First People’s Hospital of Nanning, Nanning, Guangxi, 530022, People’s Republic of China
| | - Qiu Wei
- Department of Respiratory and Critical Care, The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, 530022, People’s Republic of China,Department of Respiratory and Critical Care, The First People’s Hospital of Nanning, Nanning, Guangxi, 530022, People’s Republic of China,Correspondence: Qiu Wei; Tianxia Huang, Department of Respiratory and Critical Care, The Fifth Affiliated Hospital of Guangxi Medical University, 89 Qixing Road, Nanning, Guangxi, 530022, People’s Republic of China, Tel +86 7712636163, Fax +86 7712617892, Email ;
| | - Tianxia Huang
- Department of Respiratory and Critical Care, The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, 530022, People’s Republic of China,Department of Respiratory and Critical Care, The First People’s Hospital of Nanning, Nanning, Guangxi, 530022, People’s Republic of China
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37
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Sauler M, McDonough JE, Adams TS, Kothapalli N, Barnthaler T, Werder RB, Schupp JC, Nouws J, Robertson MJ, Coarfa C, Yang T, Chioccioli M, Omote N, Cosme C, Poli S, Ayaub EA, Chu SG, Jensen KH, Gomez JL, Britto CJ, Raredon MSB, Niklason LE, Wilson AA, Timshel PN, Kaminski N, Rosas IO. Characterization of the COPD alveolar niche using single-cell RNA sequencing. Nat Commun 2022; 13:494. [PMID: 35078977 PMCID: PMC8789871 DOI: 10.1038/s41467-022-28062-9] [Citation(s) in RCA: 121] [Impact Index Per Article: 40.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Accepted: 12/14/2021] [Indexed: 12/16/2022] Open
Abstract
Chronic obstructive pulmonary disease (COPD) is a leading cause of death worldwide, however our understanding of cell specific mechanisms underlying COPD pathobiology remains incomplete. Here, we analyze single-cell RNA sequencing profiles of explanted lung tissue from subjects with advanced COPD or control lungs, and we validate findings using single-cell RNA sequencing of lungs from mice exposed to 10 months of cigarette smoke, RNA sequencing of isolated human alveolar epithelial cells, functional in vitro models, and in situ hybridization and immunostaining of human lung tissue samples. We identify a subpopulation of alveolar epithelial type II cells with transcriptional evidence for aberrant cellular metabolism and reduced cellular stress tolerance in COPD. Using transcriptomic network analyses, we predict capillary endothelial cells are inflamed in COPD, particularly through increased CXCL-motif chemokine signaling. Finally, we detect a high-metallothionein expressing macrophage subpopulation enriched in advanced COPD. Collectively, these findings highlight cell-specific mechanisms involved in the pathobiology of advanced COPD.
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Affiliation(s)
- Maor Sauler
- Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine, New Haven, CT, USA.
| | - John E McDonough
- Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine, New Haven, CT, USA.
| | - Taylor S Adams
- Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Neeharika Kothapalli
- Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Thomas Barnthaler
- Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine, New Haven, CT, USA
- Division of Pharmacology, Otto Loewi Research Center, Medical University of Graz, Graz, Austria
| | - Rhiannon B Werder
- Center for Regenerative Medicine of Boston University and Boston Medical Center, Boston, MA, 02118, USA
- The Pulmonary Center and Department of Medicine, Boston University School of Medicine, Boston, MA, 02118, USA
- QIMR Berghofer Medical Research Institute, Herston, QLD, 4006, Australia
| | - Jonas C Schupp
- Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine, New Haven, CT, USA
- Department of Respiratory Medicine, Hannover Medical School and Biomedical Research in End-stage and Obstructive Lung Disease Hannover, German Lung Research Center (DZL), Hannover, Germany
| | - Jessica Nouws
- Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Matthew J Robertson
- Pulmonary, Critical Care and Sleep Medicine, Baylor College of Medicine, Houston, TX, USA
| | - Cristian Coarfa
- Pulmonary, Critical Care and Sleep Medicine, Baylor College of Medicine, Houston, TX, USA
| | - Tao Yang
- Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine, New Haven, CT, USA
- Department of Thoracic and Cardiovascular Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Maurizio Chioccioli
- Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Norihito Omote
- Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Carlos Cosme
- Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Sergio Poli
- Department of Internal Medicine, Mount Sinai Medical Center, Miami, FL, USA
| | - Ehab A Ayaub
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Sarah G Chu
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Jose L Gomez
- Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Clemente J Britto
- Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Micha Sam B Raredon
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
- Medical Scientist Training Program, Yale School of Medicine, New Haven, CT, USA
| | - Laura E Niklason
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Andrew A Wilson
- Center for Regenerative Medicine of Boston University and Boston Medical Center, Boston, MA, 02118, USA
- The Pulmonary Center and Department of Medicine, Boston University School of Medicine, Boston, MA, 02118, USA
| | | | - Naftali Kaminski
- Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Ivan O Rosas
- Pulmonary, Critical Care and Sleep Medicine, Baylor College of Medicine, Houston, TX, USA
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38
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Ma C, Wu M, Ma S. Analysis of cancer omics data: a selective review of statistical techniques. Brief Bioinform 2022; 23:6510158. [PMID: 35039832 DOI: 10.1093/bib/bbab585] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 12/19/2021] [Accepted: 12/20/2021] [Indexed: 11/13/2022] Open
Abstract
Cancer is an omics disease. The development in high-throughput profiling has fundamentally changed cancer research and clinical practice. Compared with clinical, demographic and environmental data, the analysis of omics data-which has higher dimensionality, weaker signals and more complex distributional properties-is much more challenging. Developments in the literature are often 'scattered', with individual studies focused on one or a few closely related methods. The goal of this review is to assist cancer researchers with limited statistical expertise in establishing the 'overall framework' of cancer omics data analysis. To facilitate understanding, we mainly focus on intuition, concepts and key steps, and refer readers to the original publications for mathematical details. This review broadly covers unsupervised and supervised analysis, as well as individual-gene-based, gene-set-based and gene-network-based analysis. We also briefly discuss 'special topics' including interaction analysis, multi-datasets analysis and multi-omics analysis.
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Affiliation(s)
- Chenjin Ma
- College of Statistics and Data Science, Faculty of Science, Beijing University of Technology, Beijing, China
| | - Mengyun Wu
- School of Statistics and Management, Shanghai University of Finance and Economics, Shanghai, China
| | - Shuangge Ma
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
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Vukmirovic M, Yan X, Gibson KF, Gulati M, Schupp JC, DeIuliis G, Adams TS, Hu B, Mihaljinec A, Woolard TN, Lynn H, Emeagwali N, Herzog EL, Chen ES, Morris A, Leader JK, Zhang Y, Garcia JGN, Maier LA, Collman RG, Drake WP, Becich MJ, Hochheiser H, Wisniewski SR, Benos PV, Moller DR, Prasse A, Koth LL, Kaminski N. Transcriptomics of bronchoalveolar lavage cells identifies new molecular endotypes of sarcoidosis. Eur Respir J 2021; 58:2002950. [PMID: 34083402 PMCID: PMC9759791 DOI: 10.1183/13993003.02950-2020] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Accepted: 04/20/2021] [Indexed: 11/05/2022]
Abstract
BACKGROUND Sarcoidosis is a multisystem granulomatous disease of unknown origin with a variable and often unpredictable course and pattern of organ involvement. In this study we sought to identify specific bronchoalveolar lavage (BAL) cell gene expression patterns indicative of distinct disease phenotypic traits. METHODS RNA sequencing by Ion Torrent Proton was performed on BAL cells obtained from 215 well-characterised patients with pulmonary sarcoidosis enrolled in the multicentre Genomic Research in Alpha-1 Antitrypsin Deficiency and Sarcoidosis (GRADS) study. Weighted gene co-expression network analysis and nonparametric statistics were used to analyse genome-wide BAL transcriptome. Validation of results was performed using a microarray expression dataset of an independent sarcoidosis cohort (Freiburg, Germany; n=50). RESULTS Our supervised analysis found associations between distinct transcriptional programmes and major pulmonary phenotypic manifestations of sarcoidosis including T-helper type 1 (Th1) and Th17 pathways associated with hilar lymphadenopathy, transforming growth factor-β1 (TGFB1) and mechanistic target of rapamycin (MTOR) signalling with parenchymal involvement, and interleukin (IL)-7 and IL-2 with airway involvement. Our unsupervised analysis revealed gene modules that uncovered four potential sarcoidosis endotypes including hilar lymphadenopathy with increased acute T-cell immune response; extraocular organ involvement with PI3K activation pathways; chronic and multiorgan disease with increased immune response pathways; and multiorgan involvement, with increased IL-1 and IL-18 immune and inflammatory responses. We validated the occurrence of these endotypes using gene expression, pulmonary function tests and cell differentials from Freiburg. CONCLUSION Taken together, our results identify BAL gene expression programmes that characterise major pulmonary sarcoidosis phenotypes and suggest the presence of distinct disease molecular endotypes.
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Affiliation(s)
- Milica Vukmirovic
- Section of Pulmonary, Critical Care and Sleep Medicine, Dept of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA
- Dept of Medicine, Division of Respirology, McMaster University, Hamilton, ON, Canada
- Equally contributing authors
| | - Xiting Yan
- Section of Pulmonary, Critical Care and Sleep Medicine, Dept of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA
- Dept of Biostatistics, Yale School of Public Health, New Haven, CT, USA
- Equally contributing authors
| | - Kevin F Gibson
- Dept of Medicine, University of Pittsburgh, School of Medicine, Pittsburgh, PA, US
| | - Mridu Gulati
- Section of Pulmonary, Critical Care and Sleep Medicine, Dept of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Jonas C Schupp
- Section of Pulmonary, Critical Care and Sleep Medicine, Dept of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Giuseppe DeIuliis
- Section of Pulmonary, Critical Care and Sleep Medicine, Dept of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Taylor S Adams
- Section of Pulmonary, Critical Care and Sleep Medicine, Dept of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Buqu Hu
- Section of Pulmonary, Critical Care and Sleep Medicine, Dept of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Antun Mihaljinec
- Section of Pulmonary, Critical Care and Sleep Medicine, Dept of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Tony N Woolard
- Section of Pulmonary, Critical Care and Sleep Medicine, Dept of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Heather Lynn
- Section of Pulmonary, Critical Care and Sleep Medicine, Dept of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA
- University of Arizona Health Sciences, Tucson, AZ, USA
| | - Nkiruka Emeagwali
- Section of Pulmonary, Critical Care and Sleep Medicine, Dept of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Erica L Herzog
- Section of Pulmonary, Critical Care and Sleep Medicine, Dept of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA
| | | | - Alison Morris
- Dept of Medicine, University of Pittsburgh, School of Medicine, Pittsburgh, PA, US
| | - Joseph K Leader
- Dept of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Yingze Zhang
- Dept of Medicine, University of Pittsburgh, School of Medicine, Pittsburgh, PA, US
| | | | | | | | | | - Michael J Becich
- Dept of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Harry Hochheiser
- Dept of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Steven R Wisniewski
- Dept of Medicine, University of Pittsburgh, School of Medicine, Pittsburgh, PA, US
| | - Panayiotis V Benos
- Dept of Computational and Systems Biology and Department of Computer Science, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Antje Prasse
- Hannover Medical School (MHH), Hannover, Germany
- Fraunhofer ITEM, Hannover, Germany
| | - Laura L Koth
- University of California San Francisco, San Francisco, CA, USA
| | - Naftali Kaminski
- Section of Pulmonary, Critical Care and Sleep Medicine, Dept of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA
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Fanidis D, Moulos P, Aidinis V. Fibromine is a multi-omics database and mining tool for target discovery in pulmonary fibrosis. Sci Rep 2021; 11:21712. [PMID: 34741074 PMCID: PMC8571330 DOI: 10.1038/s41598-021-01069-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 10/21/2021] [Indexed: 11/22/2022] Open
Abstract
Idiopathic pulmonary fibrosis is a lethal lung fibroproliferative disease with limited therapeutic options. Differential expression profiling of affected sites has been instrumental for involved pathogenetic mechanisms dissection and therapeutic targets discovery. However, there have been limited efforts to comparatively analyse/mine the numerous related publicly available datasets, to fully exploit their potential on the validation/creation of novel research hypotheses. In this context and towards that goal, we present Fibromine, an integrated database and exploration environment comprising of consistently re-analysed, manually curated transcriptomic and proteomic pulmonary fibrosis datasets covering a wide range of experimental designs in both patients and animal models. Fibromine can be accessed via an R Shiny application (http://www.fibromine.com/Fibromine) which offers dynamic data exploration and real-time integration functionalities. Moreover, we introduce a novel benchmarking system based on transcriptomic datasets underlying characteristics, resulting to dataset accreditation aiming to aid the user on dataset selection. Cell specificity of gene expression can be visualised and/or explored in several scRNA-seq datasets, in an effort to link legacy data with this cutting-edge methodology and paving the way to their integration. Several use case examples are presented, that, importantly, can be reproduced on-the-fly by a non-specialist user, the primary target and potential user of this endeavour.
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Affiliation(s)
- Dionysios Fanidis
- Institute for Bioinnovation, Biomedical Sciences Research Center ″Alexander Fleming″, 16672, Athens, Greece
| | - Panagiotis Moulos
- Institute for Fundamental Biomedical Research, Biomedical Sciences Research Center ″Alexander Fleming″, 16672, Athens, Greece.
| | - Vassilis Aidinis
- Institute for Bioinnovation, Biomedical Sciences Research Center ″Alexander Fleming″, 16672, Athens, Greece.
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41
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Fließer E, Birnhuber A, Marsh LM, Gschwandtner E, Klepetko W, Olschewski H, Kwapiszewska G. Dysbalance of ACE2 levels - a possible cause for severe COVID-19 outcome in COPD. J Pathol Clin Res 2021; 7:446-458. [PMID: 33978304 PMCID: PMC8239572 DOI: 10.1002/cjp2.224] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 03/22/2021] [Accepted: 04/21/2021] [Indexed: 12/23/2022]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a serious threat to healthcare systems worldwide. Binding of the virus to angiotensin-converting enzyme 2 (ACE2) is an important step in the infection mechanism. However, it is unknown if ACE2 expression in patients with chronic lung diseases (CLDs), such as chronic obstructive pulmonary disease (COPD), idiopathic pulmonary arterial hypertension (IPAH), or pulmonary fibrosis (PF), is changed as compared to controls. We used lung samples from patients with COPD (n = 28), IPAH (n = 10), and PF (n = 10) as well as healthy control donor (n = 10) tissue samples to investigate the expression of ACE2 and related cofactors that might influence the course of SARS-CoV-2 infection. Expression levels of the ACE2 receptor, the putative receptor CD147/BSG, and the viral entry cofactors TMPRSS2 (transmembrane serine protease 2), EZR, and FURIN were determined by quantitative PCR and in open-access RNA sequencing datasets. Immunohistochemical and single-cell RNA sequencing (scRNAseq) analyses were used for localization and coexpression, respectively. Soluble ACE2 (sACE2) plasma levels were analyzed by enzyme-linked immunosorbent assay. In COPD as compared to donor, IPAH, and PF lung tissue, gene expression of ACE2, TMPRSS2, and EZR was significantly elevated, but circulating sACE2 levels were significantly reduced in COPD and PF plasma compared to healthy control and IPAH plasma samples. Lung tissue expressions of FURIN and CD147/BSG were downregulated in COPD. None of these changes were associated with changes in pulmonary hemodynamics. Histological analysis revealed coexpression of ACE2, TMPRSS2, and Ezrin in bronchial regions and epithelial cells. This was confirmed by scRNAseq analysis. There were no significant expression changes of the analyzed molecules in the lung tissue of IPAH and idiopathic PF as compared to control. In conclusion, we reveal increased ACE2 and TMPRSS2 expression in lung tissue with a concomitant decrease of protective sACE2 in COPD patients. These changes represent the possible risk factors for an increased susceptibility of COPD patients to SARS-CoV-2 infection.
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Affiliation(s)
| | - Anna Birnhuber
- Ludwig Boltzmann Institute for Lung Vascular ResearchGrazAustria
| | - Leigh M Marsh
- Ludwig Boltzmann Institute for Lung Vascular ResearchGrazAustria
| | - Elisabeth Gschwandtner
- Division of Thoracic Surgery, Department of SurgeryMedical University of ViennaViennaAustria
| | - Walter Klepetko
- Division of Thoracic Surgery, Department of SurgeryMedical University of ViennaViennaAustria
| | | | - Grazyna Kwapiszewska
- Ludwig Boltzmann Institute for Lung Vascular ResearchGrazAustria
- Otto Loewi Research CenterMedical University of GrazGrazAustria
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Gong M, Liu P, Sciurba FC, Stojanov P, Tao D, Tseng GC, Zhang K, Batmanghelich K. Unpaired data empowers association tests. Bioinformatics 2021; 37:785-792. [PMID: 33070196 PMCID: PMC8098021 DOI: 10.1093/bioinformatics/btaa886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Revised: 09/07/2020] [Accepted: 10/05/2020] [Indexed: 11/25/2022] Open
Abstract
Motivation There is growing interest in the biomedical research community to incorporate retrospective data, available in healthcare systems, to shed light on associations between different biomarkers. Understanding the association between various types of biomedical data, such as genetic, blood biomarkers, imaging, etc. can provide a holistic understanding of human diseases. To formally test a hypothesized association between two types of data in Electronic Health Records (EHRs), one requires a substantial sample size with both data modalities to achieve a reasonable power. Current association test methods only allow using data from individuals who have both data modalities. Hence, researchers cannot take advantage of much larger EHR samples that includes individuals with at least one of the data types, which limits the power of the association test. Results We present a new method called the Semi-paired Association Test (SAT) that makes use of both paired and unpaired data. In contrast to classical approaches, incorporating unpaired data allows SAT to produce better control of false discovery and to improve the power of the association test. We study the properties of the new test theoretically and empirically, through a series of simulations and by applying our method on real studies in the context of Chronic Obstructive Pulmonary Disease. We are able to identify an association between the high-dimensional characterization of Computed Tomography chest images and several blood biomarkers as well as the expression of dozens of genes involved in the immune system. Availability and implementation Code is available on https://github.com/batmanlab/Semi-paired-Association-Test. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Mingming Gong
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA 15206, USA.,Department of Philosophy, Carnegie Mellon University, Pittsburgh, PA 15213, USA.,School of Mathematics and Statistics, The University of Melbourne, Melbourne, VIC 3010, Australia
| | - Peng Liu
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA 15206, USA
| | - Frank C Sciurba
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA 15206, USA
| | - Petar Stojanov
- Department of Philosophy, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Dacheng Tao
- Australia School of Computer Science, The University of Sydney, Sydney, NSW 2006, Australia
| | - George C Tseng
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA 15206, USA
| | - Kun Zhang
- Department of Philosophy, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Kayhan Batmanghelich
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA 15206, USA
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Watson NF, Fernandez CR. Artificial intelligence and sleep: Advancing sleep medicine. Sleep Med Rev 2021; 59:101512. [PMID: 34166990 DOI: 10.1016/j.smrv.2021.101512] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 05/20/2021] [Accepted: 05/21/2021] [Indexed: 02/07/2023]
Abstract
Artificial intelligence (AI) allows analysis of "big data" combining clinical, environmental and laboratory based objective measures to allow a deeper understanding of sleep and sleep disorders. This development has the potential to transform sleep medicine in coming years to the betterment of patient care and our collective understanding of human sleep. This review addresses the current state of the field starting with a broad definition of the various components and analytic methods deployed in AI. We review examples of AI use in screening, endotyping, diagnosing, and treating sleep disorders and place this in the context of precision/personalized sleep medicine. We explore the opportunities for AI to both facilitate and extend providers' clinical impact and present ethical considerations regarding AI derived prognostic information. We cover early adopting specialties of AI in the clinical realm, such as radiology and pathology, to provide a road map for the challenges sleep medicine is likely to face when deploying this technology. Finally, we discuss pitfalls to ensure clinical AI implementation proceeds in the safest and most effective manner possible.
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Affiliation(s)
- Nathaniel F Watson
- Department of Neurology, University of Washington (UW) School of Medicine, USA; UW Medicine Sleep Center, USA.
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44
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Wu M, Yi H, Ma S. Vertical integration methods for gene expression data analysis. Brief Bioinform 2021; 22:bbaa169. [PMID: 32793970 PMCID: PMC8138889 DOI: 10.1093/bib/bbaa169] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 06/18/2020] [Accepted: 07/04/2020] [Indexed: 12/12/2022] Open
Abstract
Gene expression data have played an essential role in many biomedical studies. When the number of genes is large and sample size is limited, there is a 'lack of information' problem, leading to low-quality findings. To tackle this problem, both horizontal and vertical data integrations have been developed, where vertical integration methods collectively analyze data on gene expressions as well as their regulators (such as mutations, DNA methylation and miRNAs). In this article, we conduct a selective review of vertical data integration methods for gene expression data. The reviewed methods cover both marginal and joint analysis and supervised and unsupervised analysis. The main goal is to provide a sketch of the vertical data integration paradigm without digging into too many technical details. We also briefly discuss potential pitfalls, directions for future developments and application notes.
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Affiliation(s)
- Mengyun Wu
- School of Statistics and Management, Shanghai University of Finance and Economics
| | - Huangdi Yi
- Department of Biostatistics at Yale University
| | - Shuangge Ma
- Department of Biostatistics at Yale University
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45
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Lung gene expression and single cell analyses reveal two subsets of idiopathic pulmonary fibrosis (IPF) patients associated with different pathogenic mechanisms. PLoS One 2021; 16:e0248889. [PMID: 33755690 PMCID: PMC7987152 DOI: 10.1371/journal.pone.0248889] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Accepted: 03/07/2021] [Indexed: 12/13/2022] Open
Abstract
Idiopathic pulmonary fibrosis is a progressive and debilitating lung disease with large unmet medical need and few treatment options. We describe an analysis connecting single cell gene expression with bulk gene expression-based subsetting of patient cohorts to identify IPF patient subsets with different underlying pathogenesis and cellular changes. We reproduced earlier findings indicating the existence of two major subsets in IPF and showed that these subsets display different alterations in cellular composition of the lung. We developed classifiers based on the cellular changes in disease to distinguish subsets. Specifically, we showed that one subset of IPF patients had significant increases in gene signature scores for myeloid cells versus a second subset that had significantly increased gene signature scores for ciliated epithelial cells, suggesting a differential pathogenesis among IPF subsets. Ligand-receptor analyses suggested there was a monocyte-macrophage chemoattractant axis (including potentially CCL2-CCR2 and CCL17-CCR4) among the myeloid-enriched IPF subset and a ciliated epithelium-derived chemokine axis (e.g. CCL15) among the ciliated epithelium-enriched IPF subset. We also found that these IPF subsets had differential expression of pirfenidone-responsive genes suggesting that our findings may provide an approach to identify patients with differential responses to pirfenidone and other drugs. We believe this work is an important step towards targeted therapies and biomarkers of response.
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46
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Nouws J, Wan F, Finnemore E, Roque W, Kim SJ, Bazan I, Li CX, Skold CM, Dai Q, Yan X, Chioccioli M, Neumeister V, Britto CJ, Sweasy J, Bindra R, Wheelock ÅM, Gomez JL, Kaminski N, Lee PJ, Sauler M. MicroRNA miR-24-3p reduces DNA damage responses, apoptosis, and susceptibility to chronic obstructive pulmonary disease. JCI Insight 2021; 6:134218. [PMID: 33290275 PMCID: PMC7934877 DOI: 10.1172/jci.insight.134218] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Accepted: 12/02/2020] [Indexed: 12/27/2022] Open
Abstract
The pathogenesis of chronic obstructive pulmonary disease (COPD) involves aberrant responses to cellular stress caused by chronic cigarette smoke (CS) exposure. However, not all smokers develop COPD and the critical mechanisms that regulate cellular stress responses to increase COPD susceptibility are not understood. Because microRNAs are well-known regulators of cellular stress responses, we evaluated microRNA expression arrays performed on distal parenchymal lung tissue samples from 172 subjects with and without COPD. We identified miR-24-3p as the microRNA that best correlated with radiographic emphysema and validated this finding in multiple cohorts. In a CS exposure mouse model, inhibition of miR-24-3p increased susceptibility to apoptosis, including alveolar type II epithelial cell apoptosis, and emphysema severity. In lung epithelial cells, miR-24-3p suppressed apoptosis through the BH3-only protein BIM and suppressed homology-directed DNA repair and the DNA repair protein BRCA1. Finally, we found BIM and BRCA1 were increased in COPD lung tissue, and BIM and BRCA1 expression inversely correlated with miR-24-3p. We concluded that miR-24-3p, a regulator of the cellular response to DNA damage, is decreased in COPD, and decreased miR-24-3p increases susceptibility to emphysema through increased BIM and apoptosis.
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Affiliation(s)
- Jessica Nouws
- Section of Pulmonary, Critical Care, and Sleep Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Feng Wan
- Section of Pulmonary, Critical Care, and Sleep Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA.,Department of Anatomy, Beijing University of Chinese Medicine, Beijing, China
| | - Eric Finnemore
- Section of Pulmonary, Critical Care, and Sleep Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Willy Roque
- Department of Internal Medicine, Rutgers New Jersey Medical School, Newark, New Jersey, USA
| | - So-Jin Kim
- Section of Pulmonary, Critical Care, and Sleep Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Isabel Bazan
- Section of Pulmonary, Critical Care, and Sleep Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Chuan-Xing Li
- Division of Respiratory Medicine and Allergy, Department of Medicine, and Center for Molecular Medicine, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
| | - C Magnus Skold
- Division of Respiratory Medicine and Allergy, Department of Medicine, and Center for Molecular Medicine, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
| | - Qile Dai
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, USA
| | - Xiting Yan
- Section of Pulmonary, Critical Care, and Sleep Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA.,Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, USA
| | - Maurizio Chioccioli
- Section of Pulmonary, Critical Care, and Sleep Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Veronique Neumeister
- Department of Pathology, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Clemente J Britto
- Section of Pulmonary, Critical Care, and Sleep Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Joann Sweasy
- Department of Radiation Oncology, University of Arizona College of Medicine, Tucson, Arizona, USA.,Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Ranjit Bindra
- Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Åsa M Wheelock
- Division of Respiratory Medicine and Allergy, Department of Medicine, and Center for Molecular Medicine, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
| | - Jose L Gomez
- Section of Pulmonary, Critical Care, and Sleep Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Naftali Kaminski
- Section of Pulmonary, Critical Care, and Sleep Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Patty J Lee
- Section of Pulmonary, Critical Care, and Sleep Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA.,Section of Pulmonary, Allergy, and Critical Care Medicine, Department of Internal Medicine, Duke University School of Medicine, Durham, North Carolina, USA
| | - Maor Sauler
- Section of Pulmonary, Critical Care, and Sleep Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
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López-Agudelo VA, Gómez-Ríos D, Ramirez-Malule H. Clavulanic Acid Production by Streptomyces clavuligerus: Insights from Systems Biology, Strain Engineering, and Downstream Processing. Antibiotics (Basel) 2021; 10:84. [PMID: 33477401 PMCID: PMC7830376 DOI: 10.3390/antibiotics10010084] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 01/11/2021] [Accepted: 01/12/2021] [Indexed: 12/16/2022] Open
Abstract
Clavulanic acid (CA) is an irreversible β-lactamase enzyme inhibitor with a weak antibacterial activity produced by Streptomyces clavuligerus (S. clavuligerus). CA is typically co-formulated with broad-spectrum β‑lactam antibiotics such as amoxicillin, conferring them high potential to treat diseases caused by bacteria that possess β‑lactam resistance. The clinical importance of CA and the complexity of the production process motivate improvements from an interdisciplinary standpoint by integrating metabolic engineering strategies and knowledge on metabolic and regulatory events through systems biology and multi-omics approaches. In the large-scale bioprocessing, optimization of culture conditions, bioreactor design, agitation regime, as well as advances in CA separation and purification are required to improve the cost structure associated to CA production. This review presents the recent insights in CA production by S. clavuligerus, emphasizing on systems biology approaches, strain engineering, and downstream processing.
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Affiliation(s)
| | - David Gómez-Ríos
- Grupo de Investigación en Simulación, Diseño, Control y Optimización de Procesos (SIDCOP), Departamento de Ingeniería Química, Universidad de Antioquia UdeA, Calle 70 No. 52-21, Medellín 050010, Colombia;
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Walentek P. Xenopus epidermal and endodermal epithelia as models for mucociliary epithelial evolution, disease, and metaplasia. Genesis 2021; 59:e23406. [PMID: 33400364 DOI: 10.1002/dvg.23406] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 12/21/2020] [Accepted: 12/22/2020] [Indexed: 11/08/2022]
Abstract
The Xenopus embryonic epidermis is a powerful model to study mucociliary biology, development, and disease. Particularly, the Xenopus system is being used to elucidate signaling pathways, transcription factor functions, and morphogenetic mechanisms regulating cell fate specification, differentiation and cell function. Thereby, Xenopus research has provided significant insights into potential underlying molecular mechanisms for ciliopathies and chronic airway diseases. Recent studies have also established the embryonic epidermis as a model for mucociliary epithelial remodeling, multiciliated cell trans-differentiation, cilia loss, and mucus secretion. Additionally, the tadpole foregut epithelium is lined by a mucociliary epithelium, which shows remarkable features resembling mammalian airway epithelia, including its endodermal origin and a variable cell type composition along the proximal-distal axis. This review aims to summarize the advantages of the Xenopus epidermis for mucociliary epithelial biology and disease modeling. Furthermore, the potential of the foregut epithelium as novel mucociliary model system is being highlighted. Additional perspectives are presented on how to expand the range of diseases that can be modeled in the frog system, including proton pump inhibitor-associated pneumonia as well as metaplasia in epithelial cells of the airway and the gastroesophageal region.
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Affiliation(s)
- Peter Walentek
- Renal Division, Department of Medicine, University Hospital Freiburg, Freiburg University Faculty of Medicine, Freiburg, Germany.,CIBSS - Centre for Integrative Biological Signalling Studies, University of Freiburg, Freiburg, Germany
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Abstract
In recent biomedical studies, multidimensional profiling, which collects proteomics as well as other types of omics data on the same subjects, is getting increasingly popular. Proteomics, transcriptomics, genomics, epigenomics, and other types of data contain overlapping as well as independent information, which suggests the possibility of integrating multiple types of data to generate more reliable findings/models with better classification/prediction performance. In this chapter, a selective review is conducted on recent data integration techniques for both unsupervised and supervised analysis. The main objective is to provide the "big picture" of data integration that involves proteomics data and discuss the "intuition" beneath the recently developed approaches without invoking too many mathematical details. Potential pitfalls and possible directions for future developments are also discussed.
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Affiliation(s)
- Mengyun Wu
- School of Statistics and Management, Shanghai University of Finance and Economics, Shanghai, China
| | - Yu Jiang
- School of Public Health, University of Memphis, Memphis, TN, USA
| | - Shuangge Ma
- Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, CT, USA.
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Zhu K, Xu A, Xia W, Li P, Han R, Wang E, Zhou S, Wang R. Integrated analysis of the molecular mechanisms in idiopathic pulmonary fibrosis. Int J Med Sci 2021; 18:3412-3424. [PMID: 34522168 PMCID: PMC8436110 DOI: 10.7150/ijms.61309] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 06/30/2021] [Indexed: 12/29/2022] Open
Abstract
Rationale: Idiopathic pulmonary fibrosis (IPF) is one of the most aggressive forms of idiopathic interstitial pneumonia. Some miRNAs may be associated with IPF and may affect the occurrence and development of IPF in various pathways. Many miRNAs and genes that may be involved in the development of IPF have been discovered using chip and high throughput technologies. Methods: We analyzed one miRNA and four mRNA databases. We identified hub genes and pathways related to IPF using GO, KEGG enrichment analysis, gene set variation analysis (GSVA), PPI network construction, and hub gene analysis. A comprehensive analysis of differentially expressed miRNAs (DEMs), predicted miRNA target genes, and differentially expressed genes (DEGs) led to the creation of a miRNA-mRNA regulatory network in IPF. Results: We found 203 DEGs and 165 DEMs that were associated with IPF. The findings of enrichment analyses showed that these DEGs were mainly involved in antimicrobial humoral response, antimicrobial humoral immune response mediated by antimicrobial peptide, extracellular matrix organization, cell killing, and organ or tissue specific immune response. The VEGFA, CDH5, and WNT3A genes overlapped between hub genes and the miRNA-mRNA regulatory network. The miRNAs including miR-199b-5p, miR-140-5p, miR-199a-5p, miR-125A-5p, and miR-107 that we predicted would regulate the VEGFA, CDH5, and WNT3A genes, which were also associated with IPF or other fibrosis-related diseases. GSVA indicated that metabolic processes of UTP and IMP, immune response, regulation of Th2 cell cytokine production, and positive regulation of NK cell-mediated immunity are associated with the pathogenesis and treatment of IPF. These pathways also interact with VEGFA, CDH5, and WNT3A. Conclusion: These findings provide a new research direction for the diagnosis and treatment of IPF.
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Affiliation(s)
- Ke Zhu
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Aiqun Xu
- Department of General Medicine, Hefei Second People's Hospital, Hefei 230001, China
| | - Wanli Xia
- Department of Thoracic Surgery, the first affiliated hospital of Anhui medical university, Hefei 230022, China
| | - Pulin Li
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Rui Han
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Enze Wang
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Sijing Zhou
- Hefei Third Clinical College of Anhui Medical University, Hefei 230022, China.,Hefei Prevention and Treatment Center for Occupational Diseases, Hefei 230022, China
| | - Ran Wang
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
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