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Chen C, Kang D, Chen Z, Shi P, Li Y, Qian S. DLD is a potential therapeutic target for COVID-19 infection in diffuse large B-cell lymphoma patients. Apoptosis 2024; 29:1696-1708. [PMID: 38581529 PMCID: PMC11416400 DOI: 10.1007/s10495-024-01959-0] [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] [Accepted: 03/10/2024] [Indexed: 04/08/2024]
Abstract
Since the discovery of copper induces cell death(cuprotosis) in 2022, it has been one of the biggest research hotspots. cuprotosis related genes (CRGs) has been demonstrated to be a potential therapeutic target for cancer, however, the molecular mechanism of CRGs in coronavirus disease 2019 (COVID-19) infected in DLBCL patients has not been reported yet. Therefore, our research objective is first to elucidate the mechanism and role of CRGs in COVID-19. Secondly, we conducted univariate and multivariate analysis and machine learning to screen for CRGs with common expression differences in COVID-19 and DLBCL. Finally, the functional role and immune mechanism of genes in DLBCL were confirmed through cell experiments and immune analysis. The research results show that CRGs play an important role in the occurrence and development of COVID-19. Univariate analysis and machine learning confirm that dihydrolipoamide dehydrogenase (DLD) is the common key gene of COVID-19 and DLBCL. Inhibiting the expression of DLD can significantly inhibit the cycle progression and promote cell apoptosis of DLBCL cells and can target positive regulation of Lysine-specific demethylase 1 (LSD1, also known as KDM1A) to inhibit the proliferation of DLBCL cells and promote cell apoptosis. The immune analysis results show that high-expression of DLD may reduce T cell-mediated anti-tumor immunity by regulating immune infiltration of CD8 + T cells and positively regulating immune checkpoints LAG3 and CD276. Reducing the expression of DLD can effectively enhance T cell-mediated anti-tumor immunity, thereby clearing cancer cells and preventing cancer growth. In conclusion, DLD may be a potential therapeutic target for COVID-19 infection in DLBCL patients. Our research provides a theoretical basis for improving the clinical treatment of COVID-19 infection in DLBCL.
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MESH Headings
- Humans
- Lymphoma, Large B-Cell, Diffuse/genetics
- Lymphoma, Large B-Cell, Diffuse/virology
- Lymphoma, Large B-Cell, Diffuse/immunology
- Lymphoma, Large B-Cell, Diffuse/drug therapy
- COVID-19/immunology
- COVID-19/genetics
- COVID-19/virology
- Apoptosis
- SARS-CoV-2
- Cell Line, Tumor
- Gene Expression Regulation, Neoplastic
- Machine Learning
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Affiliation(s)
- Can Chen
- Department of Hematology, Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, China
- School of Medicine, Zhejiang University, Hangzhou, China
| | - Dandan Kang
- School of Medicine, Zhejiang University, Hangzhou, China
| | - Zhenzhen Chen
- Department of Hematology, Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, China
| | - Pengfei Shi
- Department of Hematology, Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, China
| | - Yun Li
- Team of neonatal & infant development, health and nutrition, NDHN. School of Biology and Pharmaceutical Engineering, Wuhan Polytechnic University, Wuhan, China.
- Kindstar Global Precision Medicine Institute, Wuhan, China.
| | - Shenxian Qian
- Department of Hematology, Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, China.
- School of Medicine, Zhejiang University, Hangzhou, China.
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Li Z, Li L, Yue M, Peng Q, Pu X, Zhou Y. Tracing Immunological Interaction in Trimethylamine N-Oxide Hydrogel-Derived Zwitterionic Microenvironment During Promoted Diabetic Wound Regeneration. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2402738. [PMID: 38885961 DOI: 10.1002/adma.202402738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Revised: 05/30/2024] [Indexed: 06/20/2024]
Abstract
The diabetic wound healing is challenging due to the sabotaged delicate balance of immune regulation via an undetermined pathophysiological mechanism, so it is crucial to decipher multicellular signatures underlying diabetic wound healing and seek therapeutic strategies. Here, this work develops a strategy using novel trimethylamine N-oxide (TMAO)-derived zwitterionic hydrogel to promote diabetic wound healing, and explore the multi-cellular ecosystem around zwitterionic hydrogel, mapping out an overview of different cells in the zwitterionic microenvironment by single-cell RNA sequencing. The diverse cellular heterogeneity is revealed, highlighting the critical role of macrophage and neutrophils in managing diabetic wound healing. It is found that polyzwitterionic hydrogel can upregulate Ccl3+ macrophages and downregulate S100a9+ neutrophils and facilitate their interactions compared with polyanionic and polycationic hydrogels, validating the underlying effect of zwitterionic microenvironment on the activation of adaptive immune system. Moreover, zwitterionic hydrogel inhibits the formation of neutrophil extracellular traps (NETs) and promotes angiogenesis, thus improving diabetic wound healing. These findings expand the horizons of the sophisticated orchestration of immune systems in zwitterion-directed diabetic wound repair and uncover new strategies of novel immunoregulatory biomaterials.
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Affiliation(s)
- Zheng Li
- Department of Prosthodontics, Peking University School and Hospital of Stomatology, Beijing, 100081, China
- National Center for Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & Beijing Key Laboratory of Digital Stomatology & NHC Key Laboratory of Digital Stomatology, 22 Zhongguancun South Avenue, Haidian District, Beijing, 100081, P. R. China
| | - Longwei Li
- CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-Nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 101400, China
- School of Nanoscience and Engineering, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Muxin Yue
- Department of Prosthodontics, Peking University School and Hospital of Stomatology, Beijing, 100081, China
- National Center for Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & Beijing Key Laboratory of Digital Stomatology & NHC Key Laboratory of Digital Stomatology, 22 Zhongguancun South Avenue, Haidian District, Beijing, 100081, P. R. China
- Institute of Medical Technology, Peking University Health Science Center, 38 Xueyuan Road, Haidian District, Beijing, 100191, P. R. China
| | - Qingyu Peng
- School of Mechanical and Material Engineering, North China University of Technology, Beijing, 100144, P. R. China
| | - Xiong Pu
- CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-Nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 101400, China
- School of Nanoscience and Engineering, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yongsheng Zhou
- Department of Prosthodontics, Peking University School and Hospital of Stomatology, Beijing, 100081, China
- National Center for Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & Beijing Key Laboratory of Digital Stomatology & NHC Key Laboratory of Digital Stomatology, 22 Zhongguancun South Avenue, Haidian District, Beijing, 100081, P. R. China
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Gao G, Liu R, Wu D, Gao D, Lv Y, Xu X, Fu B, Lin Z, Wang T, He A, Bai J. Risk score constructed with neutrophil extracellular traps-related genes predicts prognosis and immune microenvironment in multiple myeloma. Front Oncol 2024; 14:1365460. [PMID: 38919521 PMCID: PMC11196624 DOI: 10.3389/fonc.2024.1365460] [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: 01/04/2024] [Accepted: 05/28/2024] [Indexed: 06/27/2024] Open
Abstract
Background Multiple myeloma (MM) exhibits considerable heterogeneity in treatment responses and survival rates, even when standardized care is administered. Ongoing efforts are focused on developing prognostic models to predict these outcomes more accurately. Recently, neutrophil extracellular traps (NETs) have emerged as a potential factor in MM progression, sparking investigation into their role in prognostication. Methods In this study, a multi-gene risk scoring model was constructed using the intersection of NTEs and differentially expressed genes (DEGs), applying the least absolute shrinkage and selection operator (LASSO) Cox regression model. A nomogram was established, and the prognostic model's effectiveness was determined via Kaplan-Meier survival analysis, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA). The ESTIMATE algorithm and immune-related single-sample gene set enrichment analysis (ssGSEA) were employed to evaluate the level of immune infiltration. The sensitivity of chemotherapy drugs was assessed using the Genomics of Drug Sensitivity in Cancer (GDSC) database. Ultimately, the presence of the detected genes was confirmed through quantitative real-time polymerase chain reaction (qRT-PCR) analysis in MM cell specimens. Results 64 NETs-DEGs were yielded, and through univariate Cox regression and LASSO regression analysis, we constructed a risk score composed of six genes: CTSG, HSPE1, LDHA, MPO, PINK1, and VCAM1. MM patients in three independent datasets were classified into high- and low-risk groups according to the risk score. The overall survival (OS) of patients in the high-risk group was significantly reduced compared to the low-risk group. Furthermore, the risk score was an independent predictive factor for OS. In addition, interactions between the risk score, immune score, and immune cell infiltration were investigated. Further analysis indicated that patients in the high-risk group were more sensitive to a variety of chemotherapy and targeted drugs, including bortezomib. Moreover, the six genes provided insights into the progression of plasma cell disorders. Conclusion This study offers novel insights into the roles of NETs in prognostic prediction, immune status, and drug sensitivity in MM, serving as a valuable supplement and enhancement to existing grading systems.
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Affiliation(s)
- Gongzhizi Gao
- Department of Hematology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Rui Liu
- Department of Hematology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Dong Wu
- Department of Hematology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Dandan Gao
- Department of Hematology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Yang Lv
- Department of Hematology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Xuezhu Xu
- Department of Hematology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Bingjie Fu
- Department of Hematology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Zujie Lin
- Department of Hematology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Ting Wang
- Department of Hematology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Aili He
- Department of Hematology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
- National-Local Joint Engineering Research Center of Biodiagnostics & Biotherapy, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
- Xi’an Key Laboratory of hematological diseases, Xi’an, China
| | - Ju Bai
- Department of Hematology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
- Xi’an Key Laboratory of hematological diseases, Xi’an, China
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Wang J, Wang H, Ding Y, Jiao X, Zhu J, Zhai Z. NET-related gene signature for predicting AML prognosis. Sci Rep 2024; 14:9115. [PMID: 38643300 PMCID: PMC11032381 DOI: 10.1038/s41598-024-59464-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Accepted: 04/11/2024] [Indexed: 04/22/2024] Open
Abstract
Acute Myeloid Leukemia (AML) is a malignant blood cancer with a high mortality rate. Neutrophil extracellular traps (NETs) influence various tumor outcomes. However, NET-related genes (NRGs) in AML had not yet received much attention. This study focuses on the role of NRGs in AML and their interaction with the immunological microenvironment. The gene expression and clinical data of patients with AML were downloaded from the TCGA-LAML and GEO cohorts. We identified 148 NRGs through the published article. Univariate Cox regression was used to analyze the association of NRGs with overall survival (OS). The least absolute shrinkage and selection operator were utilized to assess the predictive efficacy of NRGs. Kaplan-Meier plots visualized survival estimates. ROC curves assessed the prognostic value of NRG-based features. A nomogram, integrating clinical information and prognostic scores of patients, was constructed using multivariate logistic regression and Cox proportional hazards regression models. Twenty-seven NRGs were found to significantly impact patient OS. Six NRGs-CFTR, ENO1, PARVB, DDIT4, MPO, LDLR-were notable for their strong predictive ability regarding patient survival. The ROC values for 1-, 3-, and 5-year survival rates were 0.794, 0.781, and 0.911, respectively. In the training set (TCGA-LAML), patients in the high NRG risk group showed a poorer prognosis (p < 0.001), which was validated in two external datasets (GSE71014 and GSE106291). The 6-NRG signature and corresponding nomograms exhibit superior predictive accuracy, offering insights for pre-immune response evaluation and guiding future immuno-oncology treatments and drug selection for AML patients.
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Affiliation(s)
- Jiajia Wang
- Department of Hematology, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, Anhui, China
- Center of Hematology Research, Anhui Medical University, Hefei, 230601, Anhui, China
- Department of Hematology, Tongling People's Hospital, Tongling, 244000, Anhui, China
| | - Huiping Wang
- Department of Hematology, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, Anhui, China
- Center of Hematology Research, Anhui Medical University, Hefei, 230601, Anhui, China
| | - Yangyang Ding
- Department of Hematology, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, Anhui, China
- Center of Hematology Research, Anhui Medical University, Hefei, 230601, Anhui, China
| | - Xunyi Jiao
- Department of Hematology, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, Anhui, China
- Center of Hematology Research, Anhui Medical University, Hefei, 230601, Anhui, China
| | - Jinli Zhu
- Department of Hematology, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, Anhui, China
- Center of Hematology Research, Anhui Medical University, Hefei, 230601, Anhui, China
| | - Zhimin Zhai
- Department of Hematology, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, Anhui, China.
- Center of Hematology Research, Anhui Medical University, Hefei, 230601, Anhui, China.
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Jelicic J, Larsen TS, Andjelic B, Juul-Jensen K, Bukumiric Z. Should we use nomograms for risk predictions in diffuse large B cell lymphoma patients? A systematic review. Crit Rev Oncol Hematol 2024; 196:104293. [PMID: 38346460 DOI: 10.1016/j.critrevonc.2024.104293] [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: 02/17/2023] [Revised: 01/24/2024] [Accepted: 02/07/2024] [Indexed: 02/24/2024] Open
Abstract
Models based on risk stratification are increasingly reported for Diffuse large B cell lymphoma (DLBCL). Due to a rising interest in nomograms for cancer patients, we aimed to review and critically appraise prognostic models based on nomograms in DLBCL patients. A literature search in PubMed/Embase identified 59 articles that proposed prognostic models for DLBCL by combining parameters of interest (e.g., clinical, laboratory, immunohistochemical, and genetic) between January 2000 and 2024. Of them, 40 studies proposed different gene expression signatures and incorporated them into nomogram-based prognostic models. Although most studies assessed discrimination and calibration when developing the model, many lacked external validation. Current nomogram-based models for DLBCL are mainly developed from publicly available databases, lack external validation, and have no applicability in clinical practice. However, they may be helpful in individual patient counseling, although careful considerations should be made regarding model development due to possible limitations when choosing nomograms for prognostication.
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Affiliation(s)
- Jelena Jelicic
- Department of Hematology, Sygehus Lillebaelt, Vejle, Denmark; Department of Hematology, Odense University Hospital, Odense, Denmark.
| | - Thomas Stauffer Larsen
- Department of Hematology, Odense University Hospital, Odense, Denmark; Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Bosko Andjelic
- Department of Haematology, Blackpool Victoria Hospital, Lancashire Haematology Centre, Blackpool, United Kingdom
| | - Karen Juul-Jensen
- Department of Hematology, Odense University Hospital, Odense, Denmark
| | - Zoran Bukumiric
- Department of Statistics, Faculty of Medicine, University of Belgrade, Serbia
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Chen C, Li T, Li Y, Chen Z, Shi P, Li Y, Qian S. GPX4 is a potential diagnostic and therapeutic biomarker associated with diffuse large B lymphoma cell proliferation and B cell immune infiltration. Heliyon 2024; 10:e24857. [PMID: 38333875 PMCID: PMC10850411 DOI: 10.1016/j.heliyon.2024.e24857] [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: 06/29/2023] [Revised: 01/08/2024] [Accepted: 01/16/2024] [Indexed: 02/10/2024] Open
Abstract
At present, GPX4's role in the occurrence and development of diffuse large B lymphoma (DLBCL) is rarely reported. This study's purpose is to explore GPX4's significance in the diagnosis, treatment, and pathological mechanisms of DLBCL. The TIMER 2.0, GEPIA, and GEO databases were used to analyze GPX4's expression levels in DLBCL tissue, peripheral blood, and single cells, and evaluate its potential performance as a therapeutic and diagnostic marker. Cell experiments validate GPX4's role in DLBCL cells. And revealed the potential mechanism of GPX4's action from three aspects: immunity, pathogenic gene expression, and protein interaction. The results indicate that GPX4 can be used as a biomarker for treatment and diagnosis (FC > 1.5, P < 0.05, AUC>0.8, KM-P value < 0.05). In single cell data, GPX4 also showed high expression in immune cells. Besides, cell experiments have confirmed that GPX4's high expression can inhibit DLBCL cells' proliferation. Meanwhile, we found a negative correlation between GPX4 and the 16 core DLBCL's pathogenic genes, and a significant negative correlation with immune B cell infiltration. In summary, GPX4 can serve as a potential therapeutic and diagnostic marker for DLBCL. GPX4's high expression can lead to a good prognosis in DLBCL patients, which may be related to its inhibition of cancer cell proliferation, high expression of key pathogenic genes, and infiltration of immune B cells.
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Affiliation(s)
- Can Chen
- Department of Hematology, Affiliated Hangzhou First People's Hospital, West Lake University, School of Medicine, Hangzhou, China
| | - TongYu Li
- Department of Hematology, Ningbo First Hospital, Ningbo, China
| | - Yiwei Li
- Department of Hematology, Affiliated Hangzhou First People's Hospital, West Lake University, School of Medicine, Hangzhou, China
| | - Zhenzhen Chen
- Department of Hematology, Affiliated Hangzhou First People's Hospital, West Lake University, School of Medicine, Hangzhou, China
| | - Pengfei Shi
- Department of Hematology, Affiliated Hangzhou First People's Hospital, West Lake University, School of Medicine, Hangzhou, China
| | - Yun Li
- Team of Neonatal & Infant Development, Health and Nutrition, NDHN, School of Biology and Pharmaceutical Engineering, Wuhan Polytechnic University, Wuhan, China
- Kindstar Global Precision Medicine Institute, Wuhan, China
- Department of Scientific Research Project, Wuhan Kindstar Medical Laboratory Co., Ltd., Wuhan, China
| | - Shenxian Qian
- Department of Hematology, Affiliated Hangzhou First People's Hospital, West Lake University, School of Medicine, Hangzhou, China
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