Dan Liu1†Jingjing Zhao2†Ling Li3†Jie Wang4
Chao Wang4Yudong Wu4Yucun Huang1*
Dongming Xing4,5*
Wujun Chen4*- 1Guangdong Provincial People’s Hospital, Zhuhai Hospital (Jinwan Central Hospital of Zhuhai), Zhuhai, Guangdong, China
- 2Sleep Medicine Center, Huai’an No.3 People’s Hospital, Huaian Second Clinical College of Xuzhou Medical University, Huaian, China
- 3Department of Pharmacy, The Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, Guangdong, China
- 4The Affiliated Hospital of Qingdao University, Qingdao University, Qingdao Cancer Institute, Qingdao, Shandong, China
- 5School of Life Sciences, Tsinghua University, Beijing, China
CD73, an important metabolic and immune escape-promoting gene, catalyzes the hydrolysis of adenosine monophosphate (AMP) to adenosine (ADO). AMP has anti-inflammatory and vascular relaxant properties, while ADO has a strong immunosuppressive effect, suggesting that CD73 has pro-inflammatory and immune escape effects. However, CD73 also decreased proinflammatory reaction, suggesting that CD73 has a positive side to the body. Indeed, CD73 plays a protective role in diabetes, while with age, CD73 changes from anti-atherosclerosis to pro-atherosclerosis. The upregulation of CD73 with agents, including AGT-5, Aire-overexpressing DCs, Aspirin, BAFFR-Fc, CD4+ peptide, ICAs, IL-2 therapies, SAgAs, sCD73, stem cells, RAD51 inhibitor, TLR9 inhibitor, and VD, decreased diabetes and atherosclerosis development. However, the downregulation of CD73 with agents, including benzothiadiazine derivatives and CD73 siRNA, reduced atherosclerosis. Notably, many CD73 agents were investigated in clinical trials. However, no agents were used to treat diabetes and atherosclerosis. Most agents were CD73 inhibitors. Only FP-1201, a CD73 agonist, was investigated in clinical trials but its further development was discontinued. In addition, many lncRNAs, circRNAs, and genes are located at the same chromosomal location as CD73. In particular, circNT5E promoted CD73 expression. circNT5E may be a promising target for agent development. This mini-review focuses on the current state of knowledge of CD73 in diabetes, atherosclerosis, and its potential role in agent development.
1 Introduction
CD73 [also named ecto-5’-nucleotidase (5NTE), a cell surface-bound nucleotidase, is an important metabolic and immune escape-promoting gene. CD73 catalyzes the hydrolysis of adenosine monophosphate (AMP) to adenosine (ADO). AMP has anti-inflammatory and vascular relaxant properties, while ADO has a strong immunosuppressive effect by adenosine A2A receptor (A2AR) and A2BR, suggesting that CD73 promotes tumor cells to achieve immune escape (1–3). However, CD73 also has a positive side to the body. CD73 decreased proinflammatory reaction by promoting M2 macrophage phenotype (anti-inflammatory), enhancing endothelial barrier function, and inhibiting leukocyte trafficking (4). CD73 is a mesenchymal stem cell (MSC) and Breg-specific marker (5–8). CD73 is associated with a variety of diseases, including atherosclerosis, cancer, cirrhotic cardiomyopathy, diabetes, graft-versus-host disease (GVHD), periodontitis, rheumatoid arthritis, and systemic lupus erythematosus (SLE) (1–3, 9–12). Especially in cancer, the role and mechanism of CD73 have been reviewed and studied by multiple laboratories (1–3). However, few reviews exist on the agent development of CD73 and its role in diabetes and atherosclerosis. The main aims of this mini-review are to describe the current state of knowledge of CD73 in diabetes, atherosclerosis, and its potential role in agent development.
2 The role and mechanism of CD73 in diabetes and atherosclerosis
2.1 Diabetes
CD73 was increased in the kidneys of diabetic mice. The absence of CD73 was positively associated with the severity of diabetic nephropathy, suggesting that CD73 is a potential biomarker of diabetic nephropathy (13). B lymphocytes promote the development of type 1 diabetes mellitus (T1DM) by promoting the expansion of pathogenic T cells. Anti-CD20, a B lymphocyte-targeted therapy, promoted B lymphocyte depletion. However, they failed to halt β cell demise. Suppressing RAD51 with CRISPR/cas9 and inhibitors (such as 4,4’-diisothiocyanatostilbene-2, 2’-disulfonic acid) decreases the diabetes process by reducing diabetogenic T cell responses via expanding CD73+ B lymphocytes that exert regulatory activity in T1DM-susceptible nonobese diabetic (NOD) mice (14). Soluble BAFF receptor (BAFFR)-Fc (BAFFR-Fc), a fusion protein that fuses with the extracellular part of BAFFR to the Fc domain of mouse IgG1, was developed by MedImmune. BAFFR-Fc decreases T1DM procession by expanding CD73+ B lymphocytes and reduces side effects of anti-CD20 (15), suggesting that CD73 plays a key role in reducing side effects of B lymphocyte-targeted therapies. Indeed, many studies have shown that CD73 plays a protective role in diabetes. For example, AGT-5 (oral compound), a new class of fluorescent aryl hydrocarbon receptor (AHR) ligands (FluoAHRL), suppressed the severity of streptozotocin (STZ)-induced T1DM by enhancing AHR and CD73 expression in mice (16). Vitamin D3 (VD, 25-(OH)D3) reduced diabetes mellitus (DM)-related cognitive dysfunction by enhancing CD39 and CD73 expression in streptozotocin-induced T1DM rats (17). Autoimmune regulator (Aire)-overexpressing dendritic cells (DCs) delayed T1DM processing by reducing CD4+ IFN-γ+ T cells level and enhancing CD73, lymphocyte activation Gene-3 (LAG-3), and folic acid receptor 4 (FR4) expression and CD4+ T cells apoptosis in splenocytes in STZ-T1DM mouse (18). The islet-like cell aggregates (ICAs) decreased diabetes procession by expressing CD73 in STZ-induced diabetic mice (19). Interleukin-2 (IL-2) therapies with anti-IL-2 antibodies decrease the T1DM process by enhancing CD25, CD39, and CD73 expression in regulatory T cells (Treg cells) in NOD mice (20). Liposomes encapsulating the CD4+ peptide [BDC2.5mim, has a high affinity for islet autoantigen chromogranin a (ChgA)] and 1α,25-dihydroxy vitamin D3 (calcitriol) suppressed diabetes progression by activating ChgA-specific forkhead box P3 (Foxp3)+ and Foxp3- programmed cell death 1 (PD1)+ CD73+ inducible T cell costimulator (ICOS, also named CD278)+ IL-10+ peripheral regulatory T cells (21), suggesting that CD4+ peptide combination with calcitriol decreased diabetes progression by enhancing CD73+ expression. Soluble CD73 (sCD73) decreased diabetic nephropathy (13). Soluble antigen arrays (SAgAs) were able to bind more effectively to antigen-specific T cells, such as CD73, IL-10, PD-1, and killer cell lectin-like receptor G1 (KLRG1), alleviating disease progression in non-obese diabetic mouse models of T1DM (22). Toll-like receptor 9 (TLR9) deficiency and inhibitor decreases diabetes development by reducing proinflammatory cytokines and promoting anti-inflammatory cytokine release via enhancing CD73 expression in T cells in NOD mice. The increase in CD73-expressing immune cells is specific for TLR9 deficiency (23), suggesting that CD73 plays a key role in TLR9 inhibitors in reducing diabetes development. In summary, CD73 may be a promising target for treating diabetes. Overexpressing CD73 with agents, such as AGT-5, Aire-overexpressing DCs, BAFFR-Fc, CD4+ peptide, ICAs, IL-2 therapies, SAgAs, sCD73, RAD51 inhibitor, TLR9 inhibitor, and VD decreases diabetes development (Figure 1A). However, the role of CD73 knockdown (such as siRNA) and knockout in diabetes is unclear.
Figure 1. The role of CD73 agents in diabetes and atherosclerosis and the lncRNAs and genes at the same chromosomal location as CD73. (A) Diabetes, (B) atherosclerosis, (C) This information was modified from gene (NIH).
Many studies have shown that MSC transplantation, such as adipose tissue-derived MSCs, bone MSCs (BMSCs), human gingiva MSCs (GMSCs), pancreatic MSCs, human islet-MSCs (HI-MSCs), human umbilical cord MSCs (HUMSCs), Islet MSCs, pigment epithelial-derived factor (PEDF) gene-modified HUMSCs (PEDF-HUMSCs), umbilical cord (UC) MSCs (UC-MSCs), Wharton’s jelly-derived MSCs (WJMSCs) suppressed diabetes development (13, 16, 17, 22, 24–36). Human urine-derived stem cells (hUSCs) and their exosomes (hUSC-Exos) also suppressed diabetes development (37–39). Cow-derived placental stem cells (CPSCs) and periosteum-derived progenitor cells (PDPCs) promoted insulin secretion by differentiating into islet-producing cells (IPCs) (40, 41), suggesting that CPSCs and PDPCs have the potential to treat diabetes by differentiating IPCs. CD73 is expressed in hUSCs, hUSC-Exos, CPSCs, and PDPCs. As mentioned earlier, CD73 is a marker of MSCs. However, the role and mechanism of CD73 in MSCs, hUSCs, and USC-Exos in suppressing diabetes is unclear. Notably, MSCs, hUSCs, and USC-Exos can hydrolyze inflammatory extracellular ATP to anti-inflammatory adenosine via expressing CD73 and CD39 (42). In addition, GMSCs require CD39/CD73 signals to inhibit T1DM (43). GMSCs delayed the onset of diabetes by downregulating IL-17 and IFN-γ levels in CD4+ and CD8+ T cells in spleens, pancreatic lymph nodes (pLN), and other lymph nodes via expressing CD39 and CD73 (43). Thus, CD73 plays an anti-inflammatory role and immunoregulatory function in MSCs for treating diseases.
2.2 Atherosclerosis
Serum CD73 activity is upregulated in patients with atherosclerotic burden (44). Deficiency CD73 in patients exhibited extensive medial arterial calcification (MAC) which is an atherosclerosis risk, suggesting that CD73 may be a biomarker of MAC and atherosclerosis (45–47). Many studies have shown that CD37 is an enemy of atherosclerosis. For example, deficiency CD73 caused arterial calcification in patients, suggesting that overexpression CD73 suppressed arterial calcification (45–47). In ECs, CD73 suppressed inflammation and thrombosis and enhanced endothelial permeability by activating the adenosine/P1 receptor signaling pathway, (48). ECs CD73 can reduce leukocyte adhesion to the endothelium. Deletion of ECs connexin40 (Cx40) increases atherosclerosis by increasing CD73-dependent leukocyte adhesion via reducing CD73 expression (49), suggesting that ECs CD73 is an antiatherosclerotic factor. Aspirin reduces atherosclerotic plaque and immuno-inflammation by rebalancing Treg/Th17 cells via enhancing CD73 expression in ApoE-/- mice (50). However, CD37 is a friend of atherosclerosis. Suppressing CD73 with siRNA decreased atherosclerosis and plaque formation by reducing migration, proliferation, and foam cell transformation of vascular smooth muscle cells (VSMCs) via reducing CyclinD1 expression and serum lipid levels in ApoE-/- mice (51). However, the mechanism of CD73 on serum lipid levels is unclear. Inhibition of CD73 can reduce the increase of heart rate caused by hypoxia (52). Benzothiadiazine derivatives, the CD73 inhibitors, were investigated for treating atherosclerosis and ischemia-reperfusion injury (53). These results suggest that CD73 is double-sided in atherosclerosis. ECs CD73 is an antiatherosclerotic factor, while VSMCs CD73 is a proatherosclerotic factor. In fact, whether CD73 is a friend or foe in atherosclerosis may be age-related (Figure 1B). In early atherosclerosis, CD73 knockout promoted plaque area in apoE-/- mice at 12 weeks of age. However, the pattern shifts with age. CD73 knockout did not plaque area in apoE-/- mice at 20 weeks of age. In apoE-/- mice at 32 weeks and 52 weeks of age, CD73 knockout decreased plaque area by reducing lipolysis (54). ADO suppresses lipolysis, suggesting that CD73 promoted plaque accumulation by suppressing lipid catabolism via catalyzing the conversion of AMP to ADO with aging (54). Thus, with the increase of age, CD73 gradually changed from inhibiting atherosclerosis to promoting atherosclerosis.
3 The agent development in preclinical and clinical trials by targeting CD73
3.1 Targeting CD73
Given the important role of CD73 in diabetes mellitus and atherosclerosis, we searched for agents that target CD73 with AdisInsight, Bing, Chinadrugtrials, ClinicalTrials, Glgoo, ICTRP, Pharmacodia, Pharnexcloud, Pubmed, Yaozh, and Zhihuiya. Indeed, many agnets were developed in preclinical and clinical trials by targeting CD73 (Table 1), including A000830 (also named A-001190, A-001202, A-001421, AB-421) (55, 56), Adeno-associated viral type 5 (AAV5)-CD39/CD73 (57), ABSK051 (58–60), AG-2170 (61), AK131 (also named AK123) (62), ATN-037 (also named ATG-037, CB-708) (63–65), AP401 (67–69), APB-A2 (also named Anti-CD73 IgG4) (66), APCP (70), BB-1709 (71), BC010 (72), BP-1200 (73, 74), BPI-472372 (75, 76), BR101 (also named Ansipastobart) (77), BsAb CD73xEGFR (78), BMS-986179 (79), CBO421 (also named CBO-212, CD-421) (80–83), CC-5 (84), CD39/CD73 bifunctional fusion protein (85), CD39/CD73 transgenic exosomes and recombinant fusion protein (86, 87), CD73/PD-1 targeting DFC (88, 89), CD73 inhibitor (BioArdis) (90), CD73 inhibitor (Arcus Bios) (91), CD73 ASO (92), CHS-7304 (93), Compound 12f (94), Dalutrafusp alfa (also named AEGN-1423, GS-1423) (95), DN-018 (also named DN-019, DN-020, DN-052, DN-A1) (96), Dresbuxelimab (also named ak-119) (97), FP-1201 (also named ATC code L03AB07, Avonex, BG9418, Rebif, FP-1201-lyo, MR11A8, Traumakine) (98–101), 68GA-DOTA-dPNE, GB-7002 (also named GB-7002-01, GB-7002-04) (102), GI-108 (103, 104), HB-0039 (105), HB0045 (106), HB0046 (107), HB-0052 (106), HBM1007 (108), HLX23 (109), IBI325 (110), INCA-00186 (also named INCA-0186) (111), IOA-237 (112), IPH5301 (113), JAB-X1800 (also named CD73-STING iADC) (114, 115), JAB-BX102 (116), LY-3475070 (84), mAb19 (117), Mupadolimab (also named CPI-006, CPX-006) (118–121), Oleclumab (also named MEDI9447) (122–124), OP-5558 (125), OP-5244 (126, 152), OPN-CD73 (also named OPN-9627) (127), ORIC-533 (also named OP-5244, OR-558) (128–130), PBF2828 (131), PM-1015 (132), PSB-12379 (133), PSB-18332 (134, 135), PSB-19416 (134, 135), PT199 (136), Quemliclustat (also named AB680, A-0002396) (137–139, 152–155), S095024 (also named Sym024) (140), SHR170008 (141), siRNA-CD73 (70), SRF-373 (also named NZV930) (142), TRB-010 (143), Uliledlimab (also named TJD5, TJ004309, I-Mab Biopharma) (144–146), VE-3771 (147), VE-5953 (147), X-6350 (148), ZM514 (149), ZM552 (150), ZM553 (150), ZM557 (150), and ZS-1001 (151). However, no agents have been approved for sale. Notably, most of these agents are used to treat cancer. Whether CD73 as a target for treating atherosclerosis and diabetes is worth developing remains to be investigated. Notably, CD73 may be a delivery target for atherosclerotic plaques. As mentioned earlier, CD73 is a specific marker of MSC. Many studies have shown that umbilical cord (UC) MSC transplantation suppressed atherosclerosis development. However, MSCs have limited homing ability to atherosclerotic plaque sites. Integrin beta 3 (ITGB3)-modified MSCs successfully retained CD73 expression and enhanced the plaque-homing ability of MSCs, suggesting that ITGB3 is a good material for MSCs to deliver to plaques (7). CD73 combination with ITGB3 may be worth developing as the delivery target for atherosclerotic plaques.
Table 1. Agents that target CD73 in preclinical and clinical trials.
3.2 Targeting CD73 antisense RNA
According to the gene (NIH), CD73 was encoded by NT5E. There are multiple long noncoding antisense RNAs (lncRNAs) and genes in the same region of NT5E. The same position of NT5E in human includes lncRNAs and genes in the same direction (inlcuding LOC121132697, LOC127406705, LOC127406706, LOC127406707, LOC127406708, LOC127406709, LOC129661796, LOC129996774, LOC129996775, LOC129996776, LOC129996777, and LOC129996778) and those in the opposite direction (including DUTP5, SNX14, SYNCRIP, and TPT1P6) (Figure 1C). The NT5E in house mouse in the same direction includes LOC131376145, LOC131376146, LOC132440797, LOC132440798, LOC132440799, and Gm10163, while the opposite direction includes miR12205, SNX14, SYNCRIP, and Gm5066. The norway rat in the same direction includes Gabarapl3 and LOC134480214, while the opposite direction includes Rps15-ps11, SNX14, and SYNCRIP. Notably, the DNA region of NT5E in humans contains both LOC129996774 and LOC129996775. The same position of NT5E in human, house mouse, and norway rat includes SNX14 and SYNCRIP. Targeting LOC129996774, LOC129996775 SNX14, and SYNCRIP may be a novel agent development strategy by regulating CD73 expression and immune homeostasis. However, the role of LOC129996774, LOC129996775, SNX14, and SYNCRIP on CD73 is unclear. In addition, the DNA region of NT5E in house mouse and norway rat did not contain LOC129996774 and LOC129996775. Notably, lncRNA NT5E (lncNT5E) was located on human chromosome 6q14.3. LncNT5E promotes pancreatic cancer (PC) development and may be a poor prognosis biomarker of PC (156). CircNT5E (also named hsa_circ_0077232), a novel circRNA derived from NT5E, promoted the development of multiple tumors, including bladder cancer (157), glioblastoma (GBM) (158), and non-small cell lung cancer (NSCLC) (159). CircNT5E promoted NT5E expression in U87 and U251 cells (158). Targeting CD73 with lncNT5E and circNT5E, specifically, circNT5E, may be a novel strategy for agent development. However, the role of lncRNA NT5E on NT5E is unclear. CircNT5E did not change NT5E expression in A549 cells (159). Research on lncNT5E and circNT5E is also scarce, with only four references in PubMed. More research is needed to confirm the feasibility of lncNT5E and circNT5E development.
4 Summary
Serum CD73 is a potential biomarker of diabetes and atherosclerosis. However, the selection of biomarkers should consider disease status, predisease status, or prognosis and should be more sensitive, specific, and easier to detect than existing markers. The upregulation of CD73 with agents, including AGT-5, Aire-overexpressing DCs, Aspirin, BAFFR-Fc, CD4+ peptide, ICAs, IL-2 therapies, SAgAs, sCD73, stem cells, RAD51 inhibitor, TLR9 inhibitor, and VD, decreased the development of diabetes and atherosclerosis in preclinical trials. However, the downregulation of CD73 with agents, including benzothiadiazine derivatives and CD73 siRNA, decreased atherosclerosis. ECs CD73 is an antiatherosclerotic factor, while VSMCs CD73 is a proatherosclerotic factor, suggesting that the role of CD73 in atherosclerosis may depend on its localization. However, CD73 may change from anti-atherosclerosis to pro-atherosclerosis with age. More studies were needed to confirm the role of CD73 in atherosclerosis. In addition, CD73 has a cardioprotective function in heart failure (HF) and myocardial infarction (MI). CD73 has a protective effect on the liver and kidney during ischemia-reperfusion injury (IR/I). The function of CD73 in multiple organ systems and cell types is reviewed by Minor et al. (160). Notably, many agents, including ABSK051, AK131, ATN-037, AP401, APB-A2, BB-1709, BPI-472372, BR101, BMS-986179, CBO421, Dalutrafusp alfa, Dresbuxelimab, FP-1201, 68GA-DOTA-dPNE, GI-108, HB0045, HB0046, HB-0052, HBM1007, HLX23, IBI325, INCA-00186, IPH5301, JAB-BX100, JAB-BX102, LY-3475070, Mupadolimab, Oleclumab, ORIC-533, PM-1015, PT199, Quemliclustat, S095024, SRF-373, and Uliledlimab, was investigated in clinical trials. However, most of these agents were CD73 inhibitors and were used to treat acute lung injury (ALI), acute respiratory distress syndrome (ARDS), cancer, and COVID-19. Only FP-1201 was a CD73 agonist and was investigated in phase 1/2/3 clinical trials. However, the further development of FP-201 was discontinued. CD39/CD73 BFP and recombinant fusion protein CD39/CD73 transgenic exosomes, the CD73 agonist were investigated for the treatment of inflammatory disease. However, more studies are needed to confirm whether clinical trials are warranted. Whether CD73 agonists are worth developing remains to be seen. In addition, many lncRNAs, circRNAs, and genes are located at the same chromosomal location as CD73. In particular, circNT5E promoted CD73 expression. circNT5E may be a promising target for agent development. However, circRNAs usually have many target genes, so how to reduce off-target effects also needs more research.
In summary, CD73 is a potential biomarker of diabetes and atherosclerosis. Targeting CD73 could improve the success rate of drug development. As research continues and technology advances, we believe that new agents will be developed to combat diseases.
Author contributions
DL: Conceptualization, Data curation, Formal analysis, Writing – original draft. JZ: Data curation, Formal analysis, Investigation, Writing – original draft, Funding acquisition. LL: Conceptualization, Investigation, Project administration, Writing – original draft. JW: Conceptualization, Formal analysis, Writing – original draft. CW: Conceptualization, Data curation, Formal analysis, Writing – original draft. YW: Conceptualization, Data curation, Formal analysis, Validation, Writing – original draft. YH: Data curation, Formal analysis, Project administration, Writing – review & editing. DX: Conceptualization, Data curation, Project administration, Writing – review & editing. WC: Funding acquisition, Project administration, Writing – review & editing.
Funding
The author(s) declare financial support was received for the research, authorship, and/or publication of this article. The authors are grateful for the financial support from the Qingdao Major Scientific and Technological Project for Distinguished Scholars (20170103), the Laoshan Major Scientific and Technological Project for Distinguished Scholars (20181030), and Huai’an natural science research program (HAB202216).
Acknowledgments
We thank the laboratory of Professor Dongming Xing for generously supplying reagents, providing technical assistance, stimulating discussions. We thank Mantao Xu (College of Information Technology, Shanghai Jian Qiao University Co Ltd, No.1111 Hucheng Ring Rd, China (Shanghai) Pilot Free Trade Zone Lin-Gang Special Area, 201315 Shanghai, China) for contributing to grammar editing.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declare that no Generative AI was used in the creation of this manuscript.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Abbreviations
A2AR, Adenosine A2A receptor; AAV5, Adeno-associated viral type 5; ADO, Adenosine; AHR, Aryl hydrocarbon receptor; Aire, Autoimmune regulator; ALI, Acute lung injury; AMP, Adenosine monophosphate; ATP, Adenosine triphosphate; ARDS, Acute respiratory distress syndrome; BAFFR, BAFF receptor; calcitriol, 1α,25-dihydroxy vitamin D3; ChgA, Chromogranin a; CPSCs, Cow-derived placental stem cells; Cx40, Connexin40; DCs, Dendritic cells; DM, Diabetes mellitus; FluoAHRL, Fluorescent AHR ligands; Foxp3, Forkhead box P3; FR4, Folic acid receptor 4; GBM, Glioblastoma; GVHD, Graft-versus-host disease; HF, Heart failure; hUSCs, Human urine-derived stem cells; ICAs, Islet-like cell aggregates; IL-2, Interleukin-2; IPCs, Islet-producing cells; IRI, Ischemia-reperfusion injury; KLRG1, Killer cell lectin-like receptor G1; LAG-3, Lymphocyte activation Gene-3; MAC, Medial arterial calcification; MI, Myocardial infarction; MSC, Mesenchymal stem cell; 5NTE, Ecto-5’-nucleotidase; NOD, Nonobese diabetic; NSCLC, Non-small cell lung cancer; PDPCs, Periosteum-derived progenitor cells; PEDF, Pigment epithelial-derived factor; SAgAs, Soluble antigen arrays; sCD73, Soluble CD73; SLE, Systemic lupus erythematosus; STZ, Streptozotocin; T1DM, Type 1 diabetes mellitus; TLR9, Toll-like receptor 9; VD, Vitamin D3; VSMCs, Vascular smooth muscle cells.
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Keywords: CD73, circNT5E, diabetes, atherosclerosis, agent development
Citation: Liu D, Zhao J, Li L, Wang J, Wang C, Wu Y, Huang Y, Xing D and Chen W (2024) CD73: agent development potential and its application in diabetes and atherosclerosis. Front. Immunol. 15:1515875. doi: 10.3389/fimmu.2024.1515875
Received: 23 October 2024; Accepted: 25 November 2024;
Published: 12 December 2024.
Edited by:
Vinay Kumar, The Pennsylvania State University, United StatesReviewed by:
Hina Sultana, University of North Carolina System, United StatesShwetank, University of Pennsylvania, United States
Anuradha Tyagi, Institute of Nuclear Medicine & Allied Sciences (DRDO), India
Copyright © 2024 Liu, Zhao, Li, Wang, Wang, Wu, Huang, Xing and Chen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Dongming Xing, eGRtX3RzaW5naHVhQDE2My5jb20=; Yucun Huang, aHljdW5AMTI2LmNvbQ==; Wujun Chen, Y3dqd3h0NTk1MUAxNjMuY29t
†These authors have contributed equally to this work