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Yang Y, Sheng YH, Carreira P, Wang T, Zhao H, Wang R. Genome-wide assessment of shared genetic landscape of idiopathic pulmonary fibrosis and its comorbidities. Hum Genet 2024:10.1007/s00439-024-02696-9. [PMID: 39103522 DOI: 10.1007/s00439-024-02696-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Accepted: 07/27/2024] [Indexed: 08/07/2024]
Abstract
Idiopathic pulmonary fibrosis (IPF) is a progressive interstitial lung disease accompanied by both local and systemic comorbidities. Genetic factors play a role in the development of IPF and certain associated comorbidities. Nevertheless, it is uncertain whether there are shared genetic factors underlying IPF and these comorbidities. To bridge this knowledge gap, we conducted a systematic investigation into the shared genetic architecture between IPF and ten prevalent heritable comorbidities (i.e., body mass index [BMI], coronary artery disease [CAD], chronic obstructive pulmonary disease [COPD], gastroesophageal reflux disease, lung cancer, major depressive disorder [MDD], obstructive sleep apnoea, pulmonary hypertension [PH], stroke, and type 2 diabetes), by utilizing large-scale summary data from their respective genome-wide association studies and multi-omics studies. We revealed significant (false discovery rate [FDR] < 0.05) and moderate genetic correlations between IPF and seven comorbidities, excluding lung cancer, MDD and PH. Evidence suggested a partially putative causal effect of IPF on CAD. Notably, we observed FDR-significant genetic enrichments in lung for the cross-trait between IPF and CAD and in liver for the cross-trait between IPF and COPD. Additionally, we identified 65 FDR-significant genes over-represented in 20 biological pathways related to the etiology of IPF, BMI, and COPD, including inflammation-related mucin gene clusters. Several of these genes were associated with clinically relevant drugs for the treatment of IPF, CAD, and/or COPD. Our results underscore the pervasive shared genetic basis between IPF and its common comorbidities and hold future implications for early diagnosis of IPF-related comorbidities, drug repurposing, and the development of novel therapies for IPF.
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Affiliation(s)
- Yuanhao Yang
- Mater Research Institute, The University of Queensland, Woolloongabba, QLD, Australia.
| | - Yong H Sheng
- Mater Research Institute, The University of Queensland, Woolloongabba, QLD, Australia
- Cancer Program, QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
| | - Patricia Carreira
- Immunology and Infectious Disease Division, John Curtin School of Medical Research, Australian National University, Acton, ACT, Australia
| | - Tong Wang
- Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Huiying Zhao
- Department of Medical Research Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Ran Wang
- Mater Research Institute, The University of Queensland, Woolloongabba, QLD, Australia.
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Kleymenova A, Zemskaya A, Kochetkov S, Kozlov M. In-Cell Testing of Zinc-Dependent Histone Deacetylase Inhibitors in the Presence of Class-Selective Fluorogenic Substrates: Potential and Limitations of the Method. Biomedicines 2024; 12:1203. [PMID: 38927410 PMCID: PMC11200365 DOI: 10.3390/biomedicines12061203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Revised: 05/23/2024] [Accepted: 05/25/2024] [Indexed: 06/28/2024] Open
Abstract
The development of anticancer drugs based on zinc-dependent histone deacetylase inhibitors (HDACi) has acquired great practical significance over the past decade. The most important HDACi characteristics are selectivity and strength of inhibition since they determine the mechanisms of therapeutic action. For in-cell testing of the selectivity of de novo-synthesized HDACi, Western blot analysis of the level of acetylation of bona fide protein substrates of HDACs of each class is usually used. However, the high labor intensity of this method prevents its widespread use in inhibitor screening. We developed an in-cell high-throughput screening method based on the use of three subtype-selective fluorogenic substrates of the general structure Boc-Lys(Acyl)-AMC, which in many cases makes it possible to determine the selectivity of HDACi at the class level. However, we found that the additional inhibitory activity of HDACi against metallo-β-lactamase domain-containing protein 2 (MBLAC2) leads to testing errors.
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Affiliation(s)
| | | | | | - Maxim Kozlov
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia; (A.K.); (A.Z.); (S.K.)
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Wang X, Xiong Z, Hong W, Liao X, Yang G, Jiang Z, Jing L, Huang S, Fu Z, Zhu F. Identification of cuproptosis-related gene clusters and immune cell infiltration in major burns based on machine learning models and experimental validation. Front Immunol 2024; 15:1335675. [PMID: 38410514 PMCID: PMC10894925 DOI: 10.3389/fimmu.2024.1335675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 01/23/2024] [Indexed: 02/28/2024] Open
Abstract
Introduction Burns are a global public health problem. Major burns can stimulate the body to enter a stress state, thereby increasing the risk of infection and adversely affecting the patient's prognosis. Recently, it has been discovered that cuproptosis, a form of cell death, is associated with various diseases. Our research aims to explore the molecular clusters associated with cuproptosis in major burns and construct predictive models. Methods We analyzed the expression and immune infiltration characteristics of cuproptosis-related factors in major burn based on the GSE37069 dataset. Using 553 samples from major burn patients, we explored the molecular clusters based on cuproptosis-related genes and their associated immune cell infiltrates. The WGCNA was utilized to identify cluster-specific genes. Subsequently, the performance of different machine learning models was compared to select the optimal model. The effectiveness of the predictive model was validated using Nomogram, calibration curves, decision curves, and an external dataset. Finally, five core genes related to cuproptosis and major burn have been was validated using RT-qPCR. Results In both major burn and normal samples, we determined the cuproptosis-related genes associated with major burns through WGCNA analysis. Through immune infiltrate profiling analysis, we found significant immune differences between different clusters. When K=2, the clustering number is the most stable. GSVA analysis shows that specific genes in cluster 2 are closely associated with various functions. After identifying the cross-core genes, machine learning models indicate that generalized linear models have better accuracy. Ultimately, a generalized linear model for five highly correlated genes was constructed, and validation with an external dataset showed an AUC of 0.982. The accuracy of the model was further verified through calibration curves, decision curves, and modal graphs. Further analysis of clinical relevance revealed that these correlated genes were closely related to time of injury. Conclusion This study has revealed the intricate relationship between cuproptosis and major burns. Research has identified 15 cuproptosis-related genes that are associated with major burn. Through a machine learning model, five core genes related to cuproptosis and major burn have been selected and validated.
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Affiliation(s)
- Xin Wang
- Medical Center of Burn Plastic and Wound Repair, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Zhenfang Xiong
- Medical Center of Burn Plastic and Wound Repair, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Wangbing Hong
- Medical Center of Burn Plastic and Wound Repair, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Xincheng Liao
- Medical Center of Burn Plastic and Wound Repair, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Guangping Yang
- Medical Center of Burn Plastic and Wound Repair, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Zhengying Jiang
- Medical Center of Burn Plastic and Wound Repair, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Lanxin Jing
- Medical Center of Burn Plastic and Wound Repair, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Shengyu Huang
- Medical Center of Burn Plastic and Wound Repair, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Zhonghua Fu
- Medical Center of Burn Plastic and Wound Repair, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Feng Zhu
- Department of Critical Care Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China
- Department of Burns, The First Affiliated Hospital, Naval Medical University, Shanghai, China
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4
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Lechner S, Malgapo MIP, Grätz C, Steimbach RR, Baron A, Rüther P, Nadal S, Stumpf C, Loos C, Ku X, Prokofeva P, Lautenbacher L, Heimburg T, Würf V, Meng C, Wilhelm M, Sippl W, Kleigrewe K, Pauling JK, Kramer K, Miller AK, Pfaffl MW, Linder ME, Kuster B, Médard G. Target deconvolution of HDAC pharmacopoeia reveals MBLAC2 as common off-target. Nat Chem Biol 2022; 18:812-820. [PMID: 35484434 PMCID: PMC9339481 DOI: 10.1038/s41589-022-01015-5] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Accepted: 03/15/2022] [Indexed: 01/22/2023]
Abstract
Histone deacetylase (HDAC) targeting drugs have entered the pharmacopoeia in the 2000s. However, some enigmatic phenotypes suggest off-target engagement. Here, we developed a quantitative chemical proteomics assay using immobilized HDAC inhibitors and mass spectrometry that we deployed to establish the target landscape of 53 drugs. The assay covers 9 of the 11 human zinc-dependent HDACs, questions the reported selectivity of some widely-used molecules, notably for HDAC6, and delineates how the composition of HDAC complexes influences drug potency. Unexpectedly, metallo-beta-lactamase domain-containing protein 2 (MBLAC2) featured as a frequent off-target of hydroxamate drugs. This poorly characterized palmitoyl-CoA hydrolase is inhibited by 24 HDAC inhibitors at low nM potency. MBLAC2 enzymatic inhibition and knock down led to the accumulation of extracellular vesicles. Given the importance of extracellular vesicle biology in neurological diseases and cancer, this HDAC-independent drug effect may qualify MBLAC2 as a target for drug discovery.
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Affiliation(s)
- Severin Lechner
- Chair of Proteomics and Bioanalytics, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Martin Ian P Malgapo
- Department of Molecular Medicine, College of Veterinary Medicine, Cornell University, Ithaca, New York, USA
| | - Christian Grätz
- Animal Physiology and Immunology, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Raphael R Steimbach
- Cancer Drug Development, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
| | - Agnes Baron
- Chair of Proteomics and Bioanalytics, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Patrick Rüther
- Chair of Proteomics and Bioanalytics, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Simon Nadal
- Chair of Proteomics and Bioanalytics, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Carmen Stumpf
- Chair of Proteomics and Bioanalytics, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Christina Loos
- Chair of Proteomics and Bioanalytics, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Xin Ku
- Chair of Proteomics and Bioanalytics, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Polina Prokofeva
- Chair of Proteomics and Bioanalytics, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Ludwig Lautenbacher
- Computational Mass Spectrometry, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Tino Heimburg
- Institute of Pharmacy, Martin Luther University of Halle-Wittenberg, Halle (Saale), Germany
| | - Vivian Würf
- LipiTUM, Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Chen Meng
- Bavarian Center for Biomolecular Mass Spectrometry (BayBioMS), Technical University of Munich, Freising, Germany
| | - Mathias Wilhelm
- Computational Mass Spectrometry, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Wolfgang Sippl
- Institute of Pharmacy, Martin Luther University of Halle-Wittenberg, Halle (Saale), Germany
| | - Karin Kleigrewe
- Bavarian Center for Biomolecular Mass Spectrometry (BayBioMS), Technical University of Munich, Freising, Germany
| | - Josch K Pauling
- LipiTUM, Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Karl Kramer
- Chair of Proteomics and Bioanalytics, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Aubry K Miller
- Cancer Drug Development, German Cancer Research Center (DKFZ), Heidelberg, Germany.,German Cancer Consortium (DKTK), Heidelberg, Germany
| | - Michael W Pfaffl
- Animal Physiology and Immunology, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Maurine E Linder
- Department of Molecular Medicine, College of Veterinary Medicine, Cornell University, Ithaca, New York, USA
| | - Bernhard Kuster
- Chair of Proteomics and Bioanalytics, TUM School of Life Sciences, Technical University of Munich, Freising, Germany.,Bavarian Center for Biomolecular Mass Spectrometry (BayBioMS), Technical University of Munich, Freising, Germany
| | - Guillaume Médard
- Chair of Proteomics and Bioanalytics, TUM School of Life Sciences, Technical University of Munich, Freising, Germany.
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