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Tawengi M, Al-Dali Y, Tawengi A, Benter IF, Akhtar S. Targeting the epidermal growth factor receptor (EGFR/ErbB) for the potential treatment of renal pathologies. Front Pharmacol 2024; 15:1394997. [PMID: 39234105 PMCID: PMC11373609 DOI: 10.3389/fphar.2024.1394997] [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: 03/02/2024] [Accepted: 07/29/2024] [Indexed: 09/06/2024] Open
Abstract
Epidermal growth factor receptor (EGFR), which is referred to as ErbB1/HER1, is the prototype of the EGFR family of receptor tyrosine kinases which also comprises ErbB2 (Neu, HER2), ErbB3 (HER3), and ErbB4 (HER4). EGFR, along with other ErbBs, is expressed in the kidney tubules and is physiologically involved in nephrogenesis and tissue repair, mainly following acute kidney injury. However, its sustained activation is linked to several kidney pathologies, including diabetic nephropathy, hypertensive nephropathy, glomerulonephritis, chronic kidney disease, and renal fibrosis. This review aims to provide a summary of the recent findings regarding the consequences of EGFR activation in several key renal pathologies. We also discuss the potential interplay between EGFR and the reno-protective angiotensin-(1-7) (Ang-(1-7), a heptapeptide member of the renin-angiotensin-aldosterone system that counter-regulates the actions of angiotensin II. Ang-(1-7)-mediated inhibition of EGFR transactivation might represent a potential mechanism of action for its renoprotection. Our review suggests that there is a significant body of evidence supporting the potential inhibition of EGFR/ErbB, and/or administration of Ang-(1-7), as potential novel therapeutic strategies in the treatment of renal pathologies. Thus, EGFR inhibitors such as Gefitinib and Erlinotib that have an acceptable safety profile and have been clinically used in cancer chemotherapy since their FDA approval in the early 2000s, might be considered for repurposing in the treatment of renal pathologies.
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Affiliation(s)
- Mohamed Tawengi
- College of Medicine, QU Health, Qatar University, Doha, Qatar
| | - Yazan Al-Dali
- College of Medicine, QU Health, Qatar University, Doha, Qatar
| | | | - Ibrahim F Benter
- Faculty of Pharmacy, Final International University, Kyrenia, Cyprus
| | - Saghir Akhtar
- College of Medicine, QU Health, Qatar University, Doha, Qatar
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Urie RR, Morris A, Farris D, Hughes E, Xiao C, Chen J, Lombard E, Feng J, Li JZ, Goldstein DR, Shea LD. Biomarkers from subcutaneous engineered tissues predict acute rejection of organ allografts. SCIENCE ADVANCES 2024; 10:eadk6178. [PMID: 38748794 PMCID: PMC11095459 DOI: 10.1126/sciadv.adk6178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 04/10/2024] [Indexed: 05/19/2024]
Abstract
Invasive graft biopsies assess the efficacy of immunosuppression through lagging indicators of transplant rejection. We report on a microporous scaffold implant as a minimally invasive immunological niche to assay rejection before graft injury. Adoptive transfer of T cells into Rag2-/- mice with mismatched allografts induced acute cellular allograft rejection (ACAR), with subsequent validation in wild-type animals. Following murine heart or skin transplantation, scaffold implants accumulate predominantly innate immune cells. The scaffold enables frequent biopsy, and gene expression analyses identified biomarkers of ACAR before clinical signs of graft injury. This gene signature distinguishes ACAR and immunodeficient respiratory infection before injury onset, indicating the specificity of the biomarkers to differentiate ACAR from other inflammatory insult. Overall, this implantable scaffold enables remote evaluation of the early risk of rejection, which could potentially be used to reduce the frequency of routine graft biopsy, reduce toxicities by personalizing immunosuppression, and prolong transplant life.
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Affiliation(s)
- Russell R. Urie
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
| | - Aaron Morris
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
| | - Diana Farris
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA
| | - Elizabeth Hughes
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
| | - Chengchuan Xiao
- Department of Molecular, Cellular, and Developmental Biology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Judy Chen
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA
- Program in Immunology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Elizabeth Lombard
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
| | - Jiane Feng
- Animal Phenotyping Core, University of Michigan, Ann Arbor, MI 48109, USA
| | - Jun Z. Li
- Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Daniel R. Goldstein
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA
- Program in Immunology, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Lonnie D. Shea
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
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Filippone EJ, Gulati R, Farber JL. Noninvasive Assessment of the Alloimmune Response in Kidney Transplantation. Adv Chronic Kidney Dis 2021; 28:548-560. [PMID: 35367023 DOI: 10.1053/j.ackd.2021.08.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Revised: 05/28/2021] [Accepted: 08/26/2021] [Indexed: 11/11/2022]
Abstract
Transplantation remains the optimal mode of kidney replacement therapy, but unfortunately long-term graft survival after 1 year remains suboptimal. The main mechanism of chronic allograft injury is alloimmune, and current clinical monitoring of kidney transplants includes measuring serum creatinine, proteinuria, and immunosuppressive drug levels. The most important biomarker routinely monitored is human leukocyte antigen (HLA) donor-specific antibodies (DSAs) with the frequency based on underlying immunologic risk. HLA-DSA should be measured if there is graft dysfunction, immunosuppression minimization, or nonadherence. Antibody strength is semiquantitatively estimated as mean fluorescence intensity, with titration studies for equivocal cases and for following response to treatment. Determination of in vitro C1q or C3d positivity or HLA-DSA IgG subclass analysis remains of uncertain significance, but we do not recommend these for routine use. Current evidence does not support routine monitoring of non-HLA antibodies except anti-angiotensin II type 1 receptor antibodies when the phenotype is appropriate. The monitoring of both donor-derived cell-free DNA in blood or gene expression profiling of serum and/or urine may detect subclinical rejection, although mainly as a supplement and not as a replacement for biopsy. The optimal frequency and cost-effectiveness of using these noninvasive assays remain to be determined. We review the available literature and make recommendations.
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Shaw BI, Cheng DK, Acharya CR, Ettenger RB, Lyerly HK, Cheng Q, Kirk AD, Chambers ET. An age-independent gene signature for monitoring acute rejection in kidney transplantation. Theranostics 2020; 10:6977-6986. [PMID: 32550916 PMCID: PMC7295062 DOI: 10.7150/thno.42110] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Accepted: 03/20/2020] [Indexed: 12/12/2022] Open
Abstract
Acute rejection (AR) remains a significant problem that negatively impacts long-term renal allograft survival. Numerous therapies are used to prevent AR that differ by center and recipient age. This variability confounds diagnostic methods. Methods: To develop an age-independent gene signature for AR effective across a broad array of immunosuppressive regimens, we compiled kidney transplant biopsy (n=1091) and peripheral blood (n=392) gene expression profiles from 12 independent public datasets. After removing genes differentially expressed in pediatric and adult patients, we compared gene expression profiles from biopsy and peripheral blood samples of patients with AR to those who were stable (STA), using Mann-Whitney U Tests with validation in independent testing datasets. We confirmed this signature in pediatric and adult patients (42 AR and 47 STA) from our institutional biorepository. Results: We identified a novel age-independent gene network that identified AR from both kidney and blood samples. We developed a 90-probe set signature targeting 76 genes that differentiated AR from STA and found an 8 gene subset (DIP2C, ENOSF1, FBXO21, KCTD6, PDXDC1, REXO2, HLA-E, and RAB31) that was associated with AR. Conclusion: We used publicly available datasets to create a gene signature of AR that identified AR irrespective of immunosuppression regimen or recipient age. This study highlights a novel model to screen and validate biomarkers across multiple treatment regimens.
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Affiliation(s)
- Brian I Shaw
- Department of Surgery, Duke University Medical Center, Durham, United States
| | - Daniel K. Cheng
- Department of Pediatrics, Duke University Medical Center, Durham, United States
| | | | - Robert B Ettenger
- Department of Pediatrics, UCLA Mattel Children's Hospital, Los Angeles, United States
| | - Herbert Kim Lyerly
- Department of Surgery, Duke University Medical Center, Durham, United States
| | - Qing Cheng
- Department of Surgery, Duke University Medical Center, Durham, United States
| | - Allan D Kirk
- Department of Surgery, Duke University Medical Center, Durham, United States
- Department of Pediatrics, Duke University Medical Center, Durham, United States
| | - Eileen T Chambers
- Department of Surgery, Duke University Medical Center, Durham, United States
- Department of Pediatrics, Duke University Medical Center, Durham, United States
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Haidar MN, Islam MB, Chowdhury UN, Rahman MR, Huq F, Quinn JMW, Moni MA. Network-based computational approach to identify genetic links between cardiomyopathy and its risk factors. IET Syst Biol 2020; 14:75-84. [PMID: 32196466 PMCID: PMC8687405 DOI: 10.1049/iet-syb.2019.0074] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2019] [Revised: 09/23/2019] [Accepted: 10/21/2019] [Indexed: 12/11/2022] Open
Abstract
Cardiomyopathy (CMP) is a group of myocardial diseases that progressively impair cardiac function. The mechanisms underlying CMP development are poorly understood, but lifestyle factors are clearly implicated as risk factors. This study aimed to identify molecular biomarkers involved in inflammatory CMP development and progression using a systems biology approach. The authors analysed microarray gene expression datasets from CMP and tissues affected by risk factors including smoking, ageing factors, high body fat, clinical depression status, insulin resistance, high dietary red meat intake, chronic alcohol consumption, obesity, high-calorie diet and high-fat diet. The authors identified differentially expressed genes (DEGs) from each dataset and compared those from CMP and risk factor datasets to identify common DEGs. Gene set enrichment analyses identified metabolic and signalling pathways, including MAPK, RAS signalling and cardiomyopathy pathways. Protein-protein interaction (PPI) network analysis identified protein subnetworks and ten hub proteins (CDK2, ATM, CDT1, NCOR2, HIST1H4A, HIST1H4B, HIST1H4C, HIST1H4D, HIST1H4E and HIST1H4L). Five transcription factors (FOXC1, GATA2, FOXL1, YY1, CREB1) and five miRNAs were also identified in CMP. Thus the authors' approach reveals candidate biomarkers that may enhance understanding of mechanisms underlying CMP and their link to risk factors. Such biomarkers may also be useful to develop new therapeutics for CMP.
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Affiliation(s)
- Md Nasim Haidar
- Department of Electrical and Electronic Engineering, University of Rajshahi, Rajshahi 6205, Bangladesh
| | - M Babul Islam
- Department of Electrical and Electronic Engineering, University of Rajshahi, Rajshahi 6205, Bangladesh
| | - Utpala Nanda Chowdhury
- Department of Computer Science and Engineering, University of Rajshahi, Rajshahi 6205, Bangladesh
| | - Md Rezanur Rahman
- Department of Biochemistry and Biotechnology, School of Biomedical Science, Khwaja Yunus Ali University, Sirajgonj 6751, Bangladesh
| | - Fazlul Huq
- School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, NSW 2006, Australia
| | - Julian M W Quinn
- Bone Biology Division, Garvan Institute of Medical Research, Darlinghurst, NSW 2010, Australia
| | - Mohammad Ali Moni
- Bone Biology Division, Garvan Institute of Medical Research, Darlinghurst, NSW 2010, Australia.
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Bioinformatics analyses on the immune status of renal transplant patients, a systemic research of renal transplantation. BMC Med Genomics 2020; 13:24. [PMID: 32046717 PMCID: PMC7014750 DOI: 10.1186/s12920-020-0673-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2019] [Accepted: 01/27/2020] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Kidney transplantation is the most effective treatment for end-stage renal disease. Allograft rejections severely affect survivals of allograft kidneys and recipients. METHODS Using bioinformatics approaches, the present study was designed to investigate immune status in renal transplant recipients. Fifteen datasets from Gene Expression Omnibus (GEO) were collected and analysed. Analysis of gene enrichment and protein-protein interactions were also used. RESULTS There were 40 differentially expressed genes (DEGs) identified in chronic rejection group when compared with stable recipients, which were enriched in allograft rejection module. There were 135 DEGs identified in acute rejection patients, compared with stable recipients, in which most genes were enriched in allograft rejection and immune deficiency. There were 288 DEGs identified in stable recipients when compared to healthy subjects. Most genes were related to chemokine signalling pathway. In integrated comparisons, expressions of MHC molecules and immunoglobulins were increased in both acute and chronic rejection; expressions of LILRB and MAP 4 K1 were increased in acute rejection patients, but not in stable recipients. There were no overlapping DEGs in blood samples of transplant recipients. CONCLUSION By performing bioinformatics analysis on the immune status of kidney transplant patients, the present study reports several DEGs in the renal biopsy of transplant recipients, which are requested to be validated in clinical practice.
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