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Sun H, Zhang L, Wang Z, Gu D, Zhu M, Cai Y, Li L, Tang J, Huang B, Bosco B, Li N, Wu L, Wu W, Li L, Liang Y, Luo L, Liu Q, Zhu Y, Sun J, Shi L, Xia T, Yang C, Xu Q, Han X, Zhang W, Liu J, Meng D, Shao H, Zheng X, Li S, Pan H, Ke J, Jiang W, Zhang X, Han X, Chu J, An H, Ge J, Pan C, Wang X, Li K, Wang Q, Ding Q. Single-cell transcriptome analysis indicates fatty acid metabolism-mediated metastasis and immunosuppression in male breast cancer. Nat Commun 2023; 14:5590. [PMID: 37696831 PMCID: PMC10495415 DOI: 10.1038/s41467-023-41318-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 08/30/2023] [Indexed: 09/13/2023] Open
Abstract
Male breast cancer (MBC) is a rare but aggressive malignancy with cellular and immunological characteristics that remain unclear. Here, we perform transcriptomic analysis for 111,038 single cells from tumor tissues of six MBC and thirteen female breast cancer (FBC) patients. We find that that MBC has significantly lower infiltration of T cells relative to FBC. Metastasis-related programs are more active in cancer cells from MBC. The activated fatty acid metabolism involved with FASN is related to cancer cell metastasis and low immune infiltration of MBC. T cells in MBC show activation of p38 MAPK and lipid oxidation pathways, indicating a dysfunctional state. In contrast, T cells in FBC exhibit higher expression of cytotoxic markers and immune activation pathways mediated by immune-modulatory cytokines. Moreover, we identify the inhibitory interactions between cancer cells and T cells in MBC. Our study provides important information for understanding the tumor immunology and metabolism of MBC.
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Affiliation(s)
- Handong Sun
- Jiangsu Breast Disease Center, The First Affiliated Hospital with Nanjing Medical University, 300 Guangzhou Road, 210029, Nanjing, China
| | - Lishen Zhang
- Department of Bioinformatics, Nanjing Medical University, 101 Longmian Avenue, 211166, Nanjing, China
- Collaborative Innovation Center for Personalized Cancer Medicine, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Nanjing Medical University, 211166, Nanjing, Jiangsu, China
- The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, 210002, Nanjing, China
| | - Zhonglin Wang
- Department of Breast Surgery, The Second People's Hospital of Lianyungang, 41 Hailian East Road, 222006, Lianyungang, China
| | - Danling Gu
- National Health Commission Key Laboratory of Antibody Techniques, Department of Cell Biology, Jiangsu Provincial Key Laboratory of Human Functional Genomics, School of Basic Medical Sciences, Nanjing Medical University, 211166, Nanjing, Jiangsu, China
| | - Mengyan Zhu
- Department of Bioinformatics, Nanjing Medical University, 101 Longmian Avenue, 211166, Nanjing, China
- Collaborative Innovation Center for Personalized Cancer Medicine, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Nanjing Medical University, 211166, Nanjing, Jiangsu, China
- The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, 210002, Nanjing, China
| | - Yun Cai
- Department of Bioinformatics, Nanjing Medical University, 101 Longmian Avenue, 211166, Nanjing, China
- Collaborative Innovation Center for Personalized Cancer Medicine, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Nanjing Medical University, 211166, Nanjing, Jiangsu, China
- The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, 210002, Nanjing, China
| | - Lu Li
- Department of Bioinformatics, Nanjing Medical University, 101 Longmian Avenue, 211166, Nanjing, China
- Collaborative Innovation Center for Personalized Cancer Medicine, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Nanjing Medical University, 211166, Nanjing, Jiangsu, China
- The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, 210002, Nanjing, China
| | - Jiaqi Tang
- Department of Bioinformatics, Nanjing Medical University, 101 Longmian Avenue, 211166, Nanjing, China
- Collaborative Innovation Center for Personalized Cancer Medicine, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Nanjing Medical University, 211166, Nanjing, Jiangsu, China
- The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, 210002, Nanjing, China
| | - Bin Huang
- Department of Bioinformatics, Nanjing Medical University, 101 Longmian Avenue, 211166, Nanjing, China
- Collaborative Innovation Center for Personalized Cancer Medicine, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Nanjing Medical University, 211166, Nanjing, Jiangsu, China
- The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, 210002, Nanjing, China
| | - Bakwatanisa Bosco
- Department of Bioinformatics, Nanjing Medical University, 101 Longmian Avenue, 211166, Nanjing, China
- Collaborative Innovation Center for Personalized Cancer Medicine, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Nanjing Medical University, 211166, Nanjing, Jiangsu, China
- The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, 210002, Nanjing, China
| | - Ning Li
- Department of Bioinformatics, Nanjing Medical University, 101 Longmian Avenue, 211166, Nanjing, China
- Collaborative Innovation Center for Personalized Cancer Medicine, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Nanjing Medical University, 211166, Nanjing, Jiangsu, China
- The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, 210002, Nanjing, China
| | - Lingxiang Wu
- Department of Bioinformatics, Nanjing Medical University, 101 Longmian Avenue, 211166, Nanjing, China
- Collaborative Innovation Center for Personalized Cancer Medicine, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Nanjing Medical University, 211166, Nanjing, Jiangsu, China
- The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, 210002, Nanjing, China
| | - Wei Wu
- Department of Bioinformatics, Nanjing Medical University, 101 Longmian Avenue, 211166, Nanjing, China
- Collaborative Innovation Center for Personalized Cancer Medicine, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Nanjing Medical University, 211166, Nanjing, Jiangsu, China
- The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, 210002, Nanjing, China
| | - Liangyu Li
- Department of Bioinformatics, Nanjing Medical University, 101 Longmian Avenue, 211166, Nanjing, China
- Collaborative Innovation Center for Personalized Cancer Medicine, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Nanjing Medical University, 211166, Nanjing, Jiangsu, China
- The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, 210002, Nanjing, China
| | - Yuan Liang
- Department of Bioinformatics, Nanjing Medical University, 101 Longmian Avenue, 211166, Nanjing, China
- Collaborative Innovation Center for Personalized Cancer Medicine, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Nanjing Medical University, 211166, Nanjing, Jiangsu, China
- The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, 210002, Nanjing, China
| | - Lin Luo
- Department of Bioinformatics, Nanjing Medical University, 101 Longmian Avenue, 211166, Nanjing, China
- Collaborative Innovation Center for Personalized Cancer Medicine, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Nanjing Medical University, 211166, Nanjing, Jiangsu, China
- The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, 210002, Nanjing, China
| | - Quanzhong Liu
- Department of Bioinformatics, Nanjing Medical University, 101 Longmian Avenue, 211166, Nanjing, China
- Collaborative Innovation Center for Personalized Cancer Medicine, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Nanjing Medical University, 211166, Nanjing, Jiangsu, China
- The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, 210002, Nanjing, China
| | - Yanhui Zhu
- Jiangsu Breast Disease Center, The First Affiliated Hospital with Nanjing Medical University, 300 Guangzhou Road, 210029, Nanjing, China
| | - Jie Sun
- Department of Breast Surgery, The First Affiliated Hospital of Soochow University, 188 Shizi Street, 215006, Suzhou, China
| | - Liang Shi
- Jiangsu Breast Disease Center, The First Affiliated Hospital with Nanjing Medical University, 300 Guangzhou Road, 210029, Nanjing, China
| | - Tiansong Xia
- Jiangsu Breast Disease Center, The First Affiliated Hospital with Nanjing Medical University, 300 Guangzhou Road, 210029, Nanjing, China
| | - Chuang Yang
- Jiangsu Breast Disease Center, The First Affiliated Hospital with Nanjing Medical University, 300 Guangzhou Road, 210029, Nanjing, China
| | - Qitong Xu
- Jiangsu Breast Disease Center, The First Affiliated Hospital with Nanjing Medical University, 300 Guangzhou Road, 210029, Nanjing, China
| | - Xue Han
- Department of Pathology, The First Affiliated Hospital with Nanjing Medical University, 300 Guangzhou Road, 210029, Nanjing, China
| | - Weiming Zhang
- Department of Pathology, The First Affiliated Hospital with Nanjing Medical University, 300 Guangzhou Road, 210029, Nanjing, China
| | - Jianxia Liu
- Department of Breast Surgery, The First Affiliated Hospital of Soochow University, 188 Shizi Street, 215006, Suzhou, China
| | - Dong Meng
- Department of Breast Surgery, Affiliated Hospital of Jiangnan University, 1000 Hefeng Road, 214000, Wuxi, China
| | - Hua Shao
- Department of Breast Surgery, The Second People's Hospital of Lianyungang, 41 Hailian East Road, 222006, Lianyungang, China
| | - Xiangxin Zheng
- Department of Breast Surgery, Affiliated Suqian Hospital of Xuzhou Medical University, 138 Huanghe South Road, 223800, Suqian, China
| | - Shuqin Li
- The Affiliated Lianyungang Hospital of Xuzhou Medical University, 6 Zhenhua East Road, 222006, Lianyungang, China
| | - Hua Pan
- Liyang People's Hospital, 70 Jianshe West Road, 213300, Liyang, China
| | - Jing Ke
- The Affiliated Hospital of Nantong University, 20 Xisi Road, 226300, Nantong, China
| | - Wenying Jiang
- Department of Breast Surgery, The Third Affiliated Hospital of Soochow University, 185 Juqian Street, 213000, Changzhou, China
| | - Xiaolan Zhang
- Department of Breast Surgery, The Affiliated Changzhou Second People's Hospital of Nanjing Medical University, 29 Xinglong Lane, 213000, Changzhou, China
| | - Xuedong Han
- Department of Breast and Thyroid Surgery, Huai'an First People's Hospital, Nanjing Medical University, 1 Huanghe West Road, 223300, Huai'an, China
| | - Jian Chu
- Department of General Surgery, the First People's Hospital of Yancheng, 66 Renmin South Road, 224001, Yancheng, China
| | - Hongyin An
- Department of General Surgery, the First People's Hospital of Yancheng, 66 Renmin South Road, 224001, Yancheng, China
| | - Juyan Ge
- Department of Pathology, The Second People's Hospital of Lianyungang, 41 Hailian East Road, 222006, Lianyungang, China
| | - Chi Pan
- Department of Breast Surgery, the Second Affiliated Hospital, Zhejiang University, College of Medicine, 88 Jiefang Road, 310009, Hangzhou, China
| | - Xiuxing Wang
- National Health Commission Key Laboratory of Antibody Techniques, Department of Cell Biology, Jiangsu Provincial Key Laboratory of Human Functional Genomics, School of Basic Medical Sciences, Nanjing Medical University, 211166, Nanjing, Jiangsu, China
- Institute for Brain Tumors, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Personalized Cancer Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
- Department of Medicine, Division of Regenerative Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Kening Li
- Department of Bioinformatics, Nanjing Medical University, 101 Longmian Avenue, 211166, Nanjing, China.
- Collaborative Innovation Center for Personalized Cancer Medicine, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Nanjing Medical University, 211166, Nanjing, Jiangsu, China.
- The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, 210002, Nanjing, China.
| | - Qianghu Wang
- Department of Bioinformatics, Nanjing Medical University, 101 Longmian Avenue, 211166, Nanjing, China.
- Collaborative Innovation Center for Personalized Cancer Medicine, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Nanjing Medical University, 211166, Nanjing, Jiangsu, China.
- The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, 210002, Nanjing, China.
- Biomedical Big Data Center, Nanjing Medical University, 211166, Nanjing, Jiangsu, China.
| | - Qiang Ding
- Jiangsu Breast Disease Center, The First Affiliated Hospital with Nanjing Medical University, 300 Guangzhou Road, 210029, Nanjing, China.
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2
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Kambey PA, Liu WY, Wu J, Bosco B, Nadeem I, Kanwore K, Gao DS. Single-nuclei RNA sequencing uncovers heterogenous transcriptional signatures in Parkinson's disease associated with nuclear receptor-related factor 1 defect. Neural Regen Res 2023; 18:2037-2046. [PMID: 36926730 DOI: 10.4103/1673-5374.366493] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/18/2023] Open
Abstract
Previous studies have found that deficiency in nuclear receptor-related factor 1 (Nurr1), which participates in the development, differentiation, survival, and degeneration of dopaminergic neurons, is associated with Parkinson's disease, but the mechanism of action is perplexing. Here, we first ascertained the repercussion of knocking down Nurr1 by performing liquid chromatography coupled with tandem mass spectrometry. We found that 231 genes were highly expressed in dopaminergic neurons with Nurr1 deficiency, 14 of which were linked to the Parkinson's disease pathway based on Kyoto Encyclopedia of Genes and Genomes analysis. To better understand how Nurr1 deficiency autonomously invokes the decline of dopaminergic neurons and elicits Parkinson's disease symptoms, we performed single-nuclei RNA sequencing in a Nurr1 LV-shRNA mouse model. The results revealed cellular heterogeneity in the substantia nigra and a number of activated genes, the preponderance of which encode components of the major histocompatibility II complex. Cd74, H2-Ab1, H2-Aa, H2-Eb1, Lyz2, Mrc1, Slc6a3, Slc47a1, Ms4a4b, and Ptprc2 were the top 10 differentially expressed genes. Immunofluorescence staining showed that, after Nurr1 knockdown, the number of CD74-immunoreactive cells in mouse brain tissue was markedly increased. In addition, Cd74 expression was increased in a mouse model of Parkinson's disease induced by treatment with 6-hydroxydopamine. Taken together, our results suggest that Nurr1 deficiency results in an increase in Cd74 expression, thereby leading to the destruction of dopaminergic neurons. These findings provide a potential therapeutic target for the treatment of Parkinson's disease.
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Affiliation(s)
- Piniel Alphayo Kambey
- Xuzhou Key Laboratory of Neurobiology, Department of Neurobiology and Anatomy, Xuzhou Medical University, Xuzhou, Jiangsu Province, China; Organization of African Academic Doctors, Nairobi, Kenya
| | - Wen-Ya Liu
- Xuzhou Key Laboratory of Neurobiology, Department of Neurobiology and Anatomy, Xuzhou Medical University, Xuzhou, Jiangsu Province, China
| | - Jiao Wu
- Xuzhou Key Laboratory of Neurobiology, Department of Neurobiology and Anatomy, Xuzhou Medical University, Xuzhou, Jiangsu Province, China
| | - Bakwatanisa Bosco
- Department of Bioinformatics, Nanjing Medical University, Nanjing, Jiangsu Province, China
| | - Iqra Nadeem
- Xuzhou Key Laboratory of Neurobiology, Department of Neurobiology and Anatomy, Xuzhou Medical University, Xuzhou, Jiangsu Province, China
| | - Kouminin Kanwore
- Xuzhou Key Laboratory of Neurobiology, Department of Neurobiology and Anatomy, Xuzhou Medical University, Xuzhou, Jiangsu Province, China
| | - Dian-Shuai Gao
- Xuzhou Key Laboratory of Neurobiology, Department of Neurobiology and Anatomy, Xuzhou Medical University, Xuzhou, Jiangsu Province, China
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3
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Li K, Huang B, Wu M, Zhong A, Li L, Cai Y, Wang Z, Wu L, Zhu M, Li J, Wang Z, Wu W, Li W, Bosco B, Gan Z, Qiao Q, Wu J, Wang Q, Wang S, Xia X. Dynamic changes in anti-SARS-CoV-2 antibodies during SARS-CoV-2 infection and recovery from COVID-19. Nat Commun 2020; 11:6044. [PMID: 33247152 PMCID: PMC7699636 DOI: 10.1038/s41467-020-19943-y] [Citation(s) in RCA: 144] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Accepted: 10/28/2020] [Indexed: 02/06/2023] Open
Abstract
Deciphering the dynamic changes in antibodies against SARS-CoV-2 is essential for understanding the immune response in COVID-19 patients. Here we analyze the laboratory findings of 1,850 patients to describe the dynamic changes of the total antibody, spike protein (S)-, receptor-binding domain (RBD)-, and nucleoprotein (N)-specific immunoglobulin M (IgM) and G (IgG) levels during SARS-CoV-2 infection and recovery. The generation of S-, RBD-, and N-specific IgG occurs one week later in patients with severe/critical COVID-19 compared to patients with mild/moderate disease, while S- and RBD-specific IgG levels are 1.5-fold higher in severe/critical patients during hospitalization. The RBD-specific IgG levels are 4-fold higher in older patients than in younger patients during hospitalization. In addition, the S- and RBD-specific IgG levels are 2-fold higher in the recovered patients who are SARS-CoV-2 RNA negative than those who are RNA positive. Lower S-, RBD-, and N-specific IgG levels are associated with a lower lymphocyte percentage, higher neutrophil percentage, and a longer duration of viral shedding. Patients with low antibody levels on discharge might thereby have a high chance of being tested positive for SARS-CoV-2 RNA after recovery. Our study provides important information for COVID-19 diagnosis, treatment, and vaccine development. Understanding antibody responses to Sars-CoV-2 proteins over time is complicated by many variables. Here the authors survey IgM and IgG antibodies against S protein, RBD and nucleoprotein in a large cohort of infected and recovering severe vs. moderate COVID-19 patients, comparing against clinical parameters and immunological readouts.
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Affiliation(s)
- Kening Li
- The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing, China.,Center for Global Health, School of Public Health, Nanjing Medical University, 211166, Nanjing, Jiangsu, China.,Department of Bioinformatics, Nanjing Medical University, 211166, Nanjing, Jiangsu, China
| | - Bin Huang
- Center for Global Health, School of Public Health, Nanjing Medical University, 211166, Nanjing, Jiangsu, China.,Department of Bioinformatics, Nanjing Medical University, 211166, Nanjing, Jiangsu, China
| | - Min Wu
- Center for Global Health, School of Public Health, Nanjing Medical University, 211166, Nanjing, Jiangsu, China.,Department of Bioinformatics, Nanjing Medical University, 211166, Nanjing, Jiangsu, China
| | - Aifang Zhong
- Medical Technical Support Division, the 904th Hospital, 213003, Changzhou, Jiangsu, China.,Department of Laboratory Medicine & Blood Transfusion, Wuhan Huoshenshan Hospital, 430100, Wuhan, Hubei, China
| | - Lu Li
- Center for Global Health, School of Public Health, Nanjing Medical University, 211166, Nanjing, Jiangsu, China.,Department of Bioinformatics, Nanjing Medical University, 211166, Nanjing, Jiangsu, China
| | - Yun Cai
- Center for Global Health, School of Public Health, Nanjing Medical University, 211166, Nanjing, Jiangsu, China.,Department of Bioinformatics, Nanjing Medical University, 211166, Nanjing, Jiangsu, China
| | - Zhihua Wang
- Department of Laboratory Medicine & Blood Transfusion, Wuhan Huoshenshan Hospital, 430100, Wuhan, Hubei, China.,Department of Laboratory Medicine & Blood Transfusion, the 907th Hospital, 350702, Nanping, Fujian, China
| | - Lingxiang Wu
- Center for Global Health, School of Public Health, Nanjing Medical University, 211166, Nanjing, Jiangsu, China.,Department of Bioinformatics, Nanjing Medical University, 211166, Nanjing, Jiangsu, China
| | - Mengyan Zhu
- Center for Global Health, School of Public Health, Nanjing Medical University, 211166, Nanjing, Jiangsu, China.,Department of Bioinformatics, Nanjing Medical University, 211166, Nanjing, Jiangsu, China
| | - Jie Li
- Center for Global Health, School of Public Health, Nanjing Medical University, 211166, Nanjing, Jiangsu, China.,Department of Bioinformatics, Nanjing Medical University, 211166, Nanjing, Jiangsu, China
| | - Ziyu Wang
- Center for Global Health, School of Public Health, Nanjing Medical University, 211166, Nanjing, Jiangsu, China.,Department of Bioinformatics, Nanjing Medical University, 211166, Nanjing, Jiangsu, China
| | - Wei Wu
- Center for Global Health, School of Public Health, Nanjing Medical University, 211166, Nanjing, Jiangsu, China.,Department of Bioinformatics, Nanjing Medical University, 211166, Nanjing, Jiangsu, China
| | - Wanlin Li
- Center for Global Health, School of Public Health, Nanjing Medical University, 211166, Nanjing, Jiangsu, China.,Department of Bioinformatics, Nanjing Medical University, 211166, Nanjing, Jiangsu, China
| | - Bakwatanisa Bosco
- Center for Global Health, School of Public Health, Nanjing Medical University, 211166, Nanjing, Jiangsu, China.,Department of Bioinformatics, Nanjing Medical University, 211166, Nanjing, Jiangsu, China
| | - Zhenhua Gan
- Department of Medical Administration, Jinling Hospital, Nanjing University School of Medicine, 210002, Nanjing, Jiangsu, China.,Joint Expert Group for COVID-19, Wuhan Huoshenshan Hospital, 430100, Wuhan, Hubei, China
| | - Qinghua Qiao
- Department of Laboratory Medicine & Blood Transfusion, Wuhan Huoshenshan Hospital, 430100, Wuhan, Hubei, China.,Medical and Technical Support Department, Pingdingshan Medical District, the 989th Hospital of Joint Logistic Support Force, 467000, Pingdingshan, Henan, China
| | - Jian Wu
- COVID-19 Research Center, Institute of Laboratory Medicine, Jinling Hospital, Nanjing University School of Medicine, 210002, Nanjing, Jiangsu, China
| | - Qianghu Wang
- The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing, China. .,Center for Global Health, School of Public Health, Nanjing Medical University, 211166, Nanjing, Jiangsu, China. .,Department of Bioinformatics, Nanjing Medical University, 211166, Nanjing, Jiangsu, China. .,Collaborative Innovation Center for Cardiovascular Disease, Nanjing Medical University, 211166, Nanjing, China.
| | - Shukui Wang
- Department of Laboratory Medicine, Nanjing First Hospital, Nanjing Medical University, 210006, Nanjing, Jiangsu, China.
| | - Xinyi Xia
- Department of Laboratory Medicine & Blood Transfusion, Wuhan Huoshenshan Hospital, 430100, Wuhan, Hubei, China. .,Joint Expert Group for COVID-19, Wuhan Huoshenshan Hospital, 430100, Wuhan, Hubei, China. .,COVID-19 Research Center, Institute of Laboratory Medicine, Jinling Hospital, Nanjing University School of Medicine, 210002, Nanjing, Jiangsu, China.
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4
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Rizzotto D, Zaccara S, Dassi E, Galbraith M, Andrysik Z, Bosco B, Rossi A, Quattrone A, Espinosa J, Inga A. PO-077 Identification of DHX30 as an inhibitor of the translation of pro-apoptotic mRNAS after P53 activation by nutlin. ESMO Open 2018. [DOI: 10.1136/esmoopen-2018-eacr25.120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022] Open
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5
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Tang WW, McGee P, Lachin JM, Li DY, Hoogwerf B, Hazen SL, Nathan D, Zinman B, Crofford O, Genuth S, Brown‐Friday J, Crandall J, Engel H, Engel S, Martinez H, Phillips M, Reid M, Shamoon H, Sheindlin J, Gubitosi‐Klug R, Mayer L, Pendegast S, Zegarra H, Miller D, Singerman L, Smith‐Brewer S, Novak M, Quin J, Genuth S, Palmert M, Brown E, McConnell J, Pugsley P, Crawford P, Dahms W, Gregory N, Lackaye M, Kiss S, Chan R, Orlin A, Rubin M, Brillon D, Reppucci V, Lee T, Heinemann M, Chang S, Levy B, Jovanovic L, Richardson M, Bosco B, Dwoskin A, Hanna R, Barron S, Campbell R, Bhan A, Kruger D, Jones J, Edwards P, Bhan A, Carey J, Angus E, Thomas A, Galprin A, McLellan M, Whitehouse F, Bergenstal R, Johnson M, Gunyou K, Thomas L, Laechelt J, Hollander P, Spencer M, Kendall D, Cuddihy R, Callahan P, List S, Gott J, Rude N, Olson B, Franz M, Castle G, Birk R, Nelson J, Freking D, Gill L, Mestrezat W, Etzwiler D, Morgan K, Aiello L, Golden E, Arrigg P, Asuquo V, Beaser R, Bestourous L, Cavallerano J, Cavicchi R, Ganda O, Hamdy O, Kirby R, Murtha T, Schlossman D, Shah S, Sharuk G, Silva P, Silver P, Stockman M, Sun J, Weimann E, Wolpert H, Aiello L, Jacobson A, Rand L, Rosenzwieg J, Nathan D, Larkin M, Christofi M, Folino K, Godine J, Lou P, Stevens C, Anderson E, Bode H, Brink S, Cornish C, Cros D, Delahanty L, eManbey ., Haggan C, Lynch J, McKitrick C, Norman D, Moore D, Ong M, Taylor C, Zimbler D, Crowell S, Fritz S, Hansen K, Gauthier‐Kelly C, Service F, Ziegler G, Barkmeier A, Schmidt L, French B, Woodwick R, Rizza R, Schwenk W, Haymond M, Pach J, Mortenson J, Zimmerman B, Lucas A, Colligan R, Luttrell L, Lopes‐Virella M, Caulder S, Pittman C, Patel N, Lee K, Nutaitis M, Fernandes J, Hermayer K, Kwon S, Blevins A, Parker J, Colwell J, Lee D, Soule J, Lindsey P, Bracey M, Farr A, Elsing S, Thompson T, Selby J, Lyons T, Yacoub‐Wasef S, Szpiech M, Wood D, Mayfield R, Molitch M, Adelman D, Colson S, Jampol L, Lyon A, Gill M, Strugula Z, Kaminski L, Mirza R, Simjanoski E, Ryan D, Johnson C, Wallia A, Ajroud‐Driss S, Astelford P, Leloudes N, Degillio A, Schaefer B, Mudaliar S, Lorenzi G, Goldbaum M, Jones K, Prince M, Swenson M, Grant I, Reed R, Lyon R, Kolterman O, Giotta M, Clark T, Friedenberg G, Sivitz W, Vittetoe B, Kramer J, Bayless M, Zeitler R, Schrott H, Olson N, Snetselaar L, Hoffman R, MacIndoe J, Weingeist T, Fountain C, Miller R, Johnsonbaugh S, Patronas M, Carney M, Mendley S, Salemi P, Liss R, Hebdon M, Counts D, Donner T, Gordon J, Hemady R, Kowarski A, Ostrowski D, Steidl S, Jones B, Herman W, Martin C, Pop‐Busui R, Greene D, Stevens M, Burkhart N, Sandford T, Floyd J, Bantle J, Flaherty N, Terry J, Koozekanani D, Montezuma S, Wimmergren N, Rogness B, Mech M, Strand T, Olson J, McKenzie L, Kwong C, Goetz F, Warhol R, Hainsworth D, Goldstein D, Hitt S, Giangiacomo J, Schade D, Canady J, Burge M, Das A, Avery R, Ketai L, Chapin J, Schluter M, Rich J, Johannes C, Hornbeck D, Schutta M, Bourne P, Brucker A, Braunstein S, Schwartz S, Maschak‐Carey B, Baker L, Orchard T, Cimino L, Songer T, Doft B, Olson S, Becker D, Rubinstein D, Bergren R, Fruit J, Hyre R, Palmer C, Silvers N, Lobes L, Rath PP, Conrad P, Yalamanchi S, Wesche J, Bratkowksi M, Arslanian S, Rinkoff J, Warnicki J, Curtin D, Steinberg D, Vagstad G, Harris R, Steranchak L, Arch J, Kelly K, Ostrosaka P, Guiliani M, Good M, Williams T, Olsen K, Campbell A, Shipe C, Conwit R, Finegold D, Zaucha M, Drash A, Morrison A, Malone J, Bernal M, Pavan P, Grove N, Tanaka E, McMillan D, Vaccaro‐Kish J, Babbione L, Solc H, DeClue T, Dagogo‐Jack S, Wigley C, Ricks H, Kitabchi A, Chaum E, Murphy M, Moser S, Meyer D, Iannacone A, Yoser S, Bryer‐Ash M, Schussler S, Lambeth H, Raskin P, Strowig S, Basco M, Cercone S, Zinman B, Barnie A, Devenyi R, Mandelcorn M, Brent M, Rogers S, Gordon A, Bakshi N, Perkins B, Tuason L, Perdikaris F, Ehrlich R, Daneman D, Perlman K, Ferguson S, Palmer J, Fahlstrom R, de Boer I, Kinyoun J, Van Ottingham L, Catton S, Ginsberg J, McDonald C, Harth J, Driscoll M, Sheidow T, Mahon J, Canny C, Nicolle D, Colby P, Dupre J, Hramiak I, Rodger N, Jenner M, Smith T, Brown W, May M, Lipps Hagan J, Agarwal A, Adkins T, Lorenz R, Feman S, Survant L, White N, Levandoski L, Grand G, Thomas M, Joseph D, Blinder K, Shah G, Burgess D, Boniuk I, Santiago J, Tamborlane W, Gatcomb P, Stoessel K, Ramos P, Fong K, Ossorio P, Ahern J, Gubitosi‐Klug R, Meadema‐Mayer L, Beck C, Farrell K, Genuth S, Quin J, Gaston P, Palmert M, Trail R, Dahms W, Lachin J, Backlund J, Bebu I, Braffett B, Diminick L, Gao X, Hsu W, Klumpp K, Pan H, Trapani V, Cleary P, McGee P, Sun W, Villavicencio S, Anderson K, Dews L, Younes N, Rutledge B, Chan K, Rosenberg D, Petty B, Determan A, Kenny D, Williams C, Cowie C, Siebert C, Steffes M, Arends V, Bucksa J, Nowicki M, Chavers B, O'Leary D, Polak J, Harrington A, Funk L, Crow R, Gloeb B, Thomas S, O'Donnell C, Soliman E, Zhang Z, Li Y, Campbell C, Keasler L, Hensley S, Hu J, Barr M, Taylor T, Prineas R, Feldman E, Albers J, Low P, Sommer C, Nickander K, Speigelberg T, Pfiefer M, Schumer M, Moran M, Farquhar J, Ryan C, Sandstrom D, Williams T, Geckle M, Cupelli E, Thoma F, Burzuk B, Woodfill T, Danis R, Blodi B, Lawrence D, Wabers H, Gangaputra S, Neill S, Burger M, Dingledine J, Gama V, Sussman R, Davis M, Hubbard L, Budoff M, Darabian S, Rezaeian P, Wong N, Fox M, Oudiz R, Kim L, Detrano R, Cruickshanks K, Dalton D, Bainbridge K, Lima J, Bluemke D, Turkbey E, der Geest ., Liu C, Malayeri A, Jain A, Miao C, Chahal H, Jarboe R, Nathan D, Monnier V, Sell D, Strauch C, Hazen S, Pratt A, Tang W, Brunzell J, Purnell J, Natarajan R, Miao F, Zhang L, Chen Z, Paterson A, Boright A, Bull S, Sun L, Scherer S, Lopes‐Virella M, Lyons T, Jenkins A, Klein R, Virella G, Jaffa A, Carter R, Stoner J, Garvey W, Lackland D, Brabham M, McGee D, Zheng D, Mayfield R, Maynard J, Wessells H, Sarma A, Jacobson A, Dunn R, Holt S, Hotaling J, Kim C, Clemens Q, Brown J, McVary K. Oxidative Stress and Cardiovascular Risk in Type 1 Diabetes Mellitus: Insights From the DCCT/EDIC Study. J Am Heart Assoc 2018. [PMCID: PMC6015340 DOI: 10.1161/jaha.117.008368] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background
Hyperglycemia leading to increased oxidative stress is implicated in the increased risk for the development of macrovascular and microvascular complications in patients with type 1 diabetes mellitus.
Methods and Results
A random subcohort of 349 participants was selected from the
DCCT
/
EDIC
(Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications) cohort. This included 320 controls and 29 cardiovascular disease cases that were augmented with 98 additional known cases to yield a case cohort of 447 participants (320 controls, 127 cases). Biosamples from
DCCT
baseline, year 1, and closeout of
DCCT
, and 1 to 2 years post‐
DCCT
(
EDIC
years 1 and 2) were measured for markers of oxidative stress, including plasma myeloperoxidase, paraoxonase activity, urinary F
2α
isoprostanes, and its metabolite, 2,3 dinor‐8
iso
prostaglandin F
2α
. Following adjustment for glycated hemoblobin and weighting the observations inversely proportional to the sampling selection probabilities, higher paraoxonase activity, reflective of antioxidant activity, and 2,3 dinor‐8
iso
prostaglandin F
2α
, an oxidative marker, were significantly associated with lower risk of cardiovascular disease (−4.5% risk for 10% higher paraoxonase,
P
<0.003; −5.3% risk for 10% higher 2,3 dinor‐8
iso
prostaglandin F
2α
,
P
=0.0092). In contrast, the oxidative markers myeloperoxidase and F
2α
isoprostanes were not significantly associated with cardiovascular disease after adjustment for glycated hemoblobin. There were no significant differences between
DCCT
intensive and conventional treatment groups in the change in all biomarkers across time segments.
Conclusions
Heightened antioxidant activity (rather than diminished oxidative stress markers) is associated with lower cardiovascular disease risk in type 1 diabetes mellitus, but these biomarkers did not change over time with intensification of glycemic control.
Clinical Trial Registration
URL
:
https://www.clinicaltrials.gov
. Unique identifiers:
NCT
00360815 and
NCT
00360893.
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Affiliation(s)
- W.H. Wilson Tang
- Department of Cellular and Molecular Medicine, Lerner Research Institute, Cleveland Clinic, Cleveland, OH
- Department of Cardiovascular Medicine, Heart and Vascular Institute, Cleveland Clinic, Cleveland, OH
| | - Paula McGee
- The Biostatistics Center, George Washington University, Rockville, MD
| | - John M. Lachin
- The Biostatistics Center, George Washington University, Rockville, MD
| | - Daniel Y. Li
- Department of Cellular and Molecular Medicine, Lerner Research Institute, Cleveland Clinic, Cleveland, OH
| | | | - Stanley L. Hazen
- Department of Cellular and Molecular Medicine, Lerner Research Institute, Cleveland Clinic, Cleveland, OH
- Department of Cardiovascular Medicine, Heart and Vascular Institute, Cleveland Clinic, Cleveland, OH
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Affiliation(s)
- R S Bockman
- Cornell University Medical College, New York, NY
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Abstract
OBJECTIVE To evaluate whether a brief course of treatment with gallium nitrate can reduce biochemical parameters of accelerated bone turnover in patients with advanced Paget disease. DESIGN Unblinded trial, decreasing dose schedules of gallium nitrate. SETTING University hospital with primary orthopedic and metabolic bone disease specialty. PATIENTS Ten patients with advanced Paget disease who had previously received conventional therapy consisting of calcitonin, etidronate, or mithramycin. INTERVENTIONS Five patients were entered into each of three dose schedules: 2.5 mg/kg body weight per day by continuous intravenous infusion for 7 days; 0.5 mg/kg per day for 14 days by subcutaneous injection; and 0.25 mg/kg per day for 14 days by subcutaneous injection. Several patients were treated with different dose schedules. Patients were followed until relapse. RESULTS Fifteen courses of treatment were administered to ten patients. Reductions in serum alkaline phosphatase and urinary hydroxyproline excretion were observed after treatment with each dose schedule. After treatment with high, intermediate, and low doses, the median maximum decreases in serum alkaline phosphatase activity were 49%, 39%, and 18%, respectively. The median maximum decreases in urinary hydroxyproline excretion were 50%, 52%, and 16%, respectively. The maximum decrease in urinary hydroxyproline excretion occurred within a median of 2 weeks from the start of treatment, whereas the maximum decrease in serum alkaline phosphatase activity occurred substantially later at a median of 6 weeks. All treatment schedules were well tolerated. Response duration was highly variable (range, 6 to 42 weeks). CONCLUSIONS Short-term treatment with gallium nitrate can reduce biochemical parameters of disease activity in patients with advanced Paget disease of bone. Larger trials using low-dose intermittent treatment schedules are required to evaluate the safety and effectiveness of this therapy.
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Affiliation(s)
- R P Warrell
- Hospital for Special Surgery, New York, New York
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Di Matteo L, D'Incecco V, Bosco B, Bosica D, Colangelo G, Consoli G. [Role of lymphapheresis in treatment protocols of rheumatoid arthritis]. Clin Ter 1987; 123:275-9. [PMID: 2972489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
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Swain R, Bapna JS, Das AK, Chandrasekar S, Swaminathan RP, Bosco B, Veliath S, Thombre DP. A study on the neurotoxicity of broxyquinoline and brobenzoxaldine combination in therapeutic doses. Hum Toxicol 1986; 5:35-41. [PMID: 3081428 DOI: 10.1177/096032718600500107] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
The neurotoxicity of a combination of broxyquinoline and brobenzoxaldine (Intestopan Forte, containing 500 mg and 100 mg of the drugs respectively per capsule) was investigated by prospective clinical and electrophysiological studies in patients and volunteer subjects given the drugs in therapeutic doses (two capsules three times a day for 5 days). Of 16 patients with intestinal amoebiasis given the drugs (study A), 13 (81.25%) were cured. Adverse effects were mild and did not affect treatment. No neurological adverse effect was reported. Neurological examinations revealed no abnormality in any patient after treatment. Seven volunteer subjects underwent medical, neurological and ophthalmological examinations, and electrophysiological studies of ulnar and peroneal nerve conduction before and after treatment with the drugs in therapeutic doses (study B). Transient paresthesias were reported by one subject on the fourth day of treatment. No medical, neurological or ophthalmological abnormality was detected in any subject after treatment. There was no significant change in motor nerve conduction velocities. There was a significant (P less than 0.001) increase in the stimulus strength for distal ulnar stimulation and a significant (P less than 0.01) decrease in stimulus duration for proximal and distal ulnar stimulation. No significant changes were seen in the peroneal nerves in these parameters. No qualitative abnormality was seen in the oscilloscopic patterns of nerve conduction after treatment. Literature on the neurotoxicity of the halogenated hydroxyquinolines is reviewed. It is concluded that broxyquinoline and brobenzoxaldine (and probably other halogenated hydroxyquinolines as well) are safe and effective in therapeutic doses; neurotoxicity is unlikely to occur when these drugs are used according to therapeutic recommendations.
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