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Chao BT, McInnis MC, Sage AT, Yeung JC, Cypel M, Liu M, Wang B, Keshavjee S. A radiographic score for human donor lungs on ex vivo lung perfusion predicts transplant outcomes. J Heart Lung Transplant 2024; 43:797-805. [PMID: 38211838 DOI: 10.1016/j.healun.2024.01.004] [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] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 01/02/2024] [Accepted: 01/05/2024] [Indexed: 01/13/2024] Open
Abstract
BACKGROUND Ex vivo lung perfusion (EVLP) is an advanced platform for isolated lung assessment and treatment. Radiographs acquired during EVLP provide a unique opportunity to assess lung injury. The purpose of our study was to define and evaluate EVLP radiographic findings and their association with lung transplant outcomes. METHODS We retrospectively evaluated 113 EVLP cases from 2020-21. Radiographs were scored by a thoracic radiologist blinded to outcome. Six lung regions were scored for 5 radiographic features (consolidation, infiltrates, atelectasis, nodules, and interstitial lines) on a scale of 0 to 3 to derive a score. Spearman's correlation was used to correlate radiographic scores to biomarkers of lung injury. Machine learning models were developed using radiographic features and EVLP functional data. Predictive performance was assessed using the area under the curve. RESULTS Consolidation and infiltrates were the most frequent findings at 1 hour EVLP (radiographic lung score 2.6 (3.3) and 4.6 (4.3)). Consolidation (r = -0.536 and -0.608, p < 0.0001) and infiltrates (r = -0.492 and -0.616, p < 0.0001) were inversely correlated with oxygenation (∆pO2) at 1 hour and 3 hours of EVLP. First-hour consolidation and infiltrate lung scores predicted transplant suitability with an area under the curve of 87% and 88%, respectively. Prediction of transplant outcomes using a machine learning model yielded an area under the curve of 80% in the validation set. CONCLUSIONS EVLP radiographs provide valuable insight into donor lungs being assessed for transplantation. Consolidation and infiltrates were the most common abnormalities observed in EVLP lungs, and radiographic lung scores predicted the suitability of donor lungs for transplant.
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Affiliation(s)
- Bonnie T Chao
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario, Canada; Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada
| | - Micheal C McInnis
- University Medical Imaging Toronto, Toronto General Hospital, University Health Network, Toronto, ON, Canada; Department of Medical Imaging, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Andrew T Sage
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario, Canada; Department of Surgery, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Jonathan C Yeung
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario, Canada
| | - Marcelo Cypel
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario, Canada; Department of Surgery, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Mingyao Liu
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario, Canada; Department of Surgery, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Bo Wang
- Vector Institute, University of Toronto, Toronto, Ontario, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
| | - Shaf Keshavjee
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario, Canada; Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada; Department of Surgery, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.
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Chao BT, Sage AT, Yeung JC, Bai X, Ma J, Martinu T, Liu M, Cypel M, Van Raemdonck D, Ceulemans LJ, Neyrinck A, Verleden S, Keshavjee S. Identification of regional variation in gene expression and inflammatory proteins in donor lung tissue and ex vivo lung perfusate. J Thorac Cardiovasc Surg 2023; 166:1520-1528.e3. [PMID: 37482240 DOI: 10.1016/j.jtcvs.2023.07.013] [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] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 06/08/2023] [Accepted: 07/12/2023] [Indexed: 07/25/2023]
Abstract
OBJECTIVE Diagnosing lung injury is a challenge in lung transplantation. It has been unclear if a single biopsy specimen is truly representative of the entire organ. Our objective was to investigate lung inflammatory biomarkers using human lung tissue biopsies and ex vivo lung perfusion perfusate. METHODS Eight human donor lungs declined for transplantation were air inflated, flash frozen, and partitioned from apex to base. Biopsies were then sampled throughout the lung. Perfusate was sampled from 4 lung lobes in 8 additional donor lungs subjected to ex vivo lung perfusion. The levels of interleukin-6, interleukin-8, interleukin-10, and interleukin-1β were measured using quantitative reverse transcription polymerase chain reaction from lung biopsies and enzyme-linked immunosorbent assay from ex vivo lung perfusion perfusate. RESULTS The median intra-biopsy equal-variance P value was .50 for messenger RNA biomarkers in tissue biopsies. The median intra-biopsy coefficient of variance was 18%. In donors with no apparent focal injuries, the biopsies in each donor showed no difference in various lung slices, with a coefficient of variance of 20%. The exception was biopsies from the lingula and injured focal areas that demonstrated larger differences. Cytokines in ex vivo lung perfusion perfusate showed minimal variation among different lobes (coefficient of variance = 4.9%). CONCLUSIONS Cytokine gene expression in lung biopsies was consistent, and the biopsy analysis reflects the whole lung, except when specimens were collected from the lingula or an area of focal injury. Ex vivo lung perfusion perfusate also provides a representative measurement of lung inflammation from the draining lobe. These results will reassure clinicians that a lung biopsy or an ex vivo lung perfusion perfusate sample can be used to inform donor lung selection.
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Affiliation(s)
- Bonnie T Chao
- Toronto Lung Transplant Program and Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario, Canada; Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada
| | - Andrew T Sage
- Toronto Lung Transplant Program and Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario, Canada; Ajmera Transplant Centre, University Health Network, University of Toronto, Toronto, Ontario, Canada; Department of Surgery, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Jonathan C Yeung
- Toronto Lung Transplant Program and Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario, Canada; Ajmera Transplant Centre, University Health Network, University of Toronto, Toronto, Ontario, Canada; Department of Surgery, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Xiaohui Bai
- Toronto Lung Transplant Program and Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario, Canada
| | - Jin Ma
- Biostatistics Research Unit, University Health Network, Toronto, Ontario, Canada
| | - Tereza Martinu
- Toronto Lung Transplant Program and Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario, Canada; Ajmera Transplant Centre, University Health Network, University of Toronto, Toronto, Ontario, Canada; Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Department of Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Mingyao Liu
- Toronto Lung Transplant Program and Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario, Canada; Ajmera Transplant Centre, University Health Network, University of Toronto, Toronto, Ontario, Canada; Department of Surgery, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Marcelo Cypel
- Toronto Lung Transplant Program and Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario, Canada; Ajmera Transplant Centre, University Health Network, University of Toronto, Toronto, Ontario, Canada; Department of Surgery, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Dirk Van Raemdonck
- BREATHE, Department of CHROMETA, KU Leuven, Leuven, Belgium; Department of Thoracic Surgery, University Hospitals Leuven, Leuven, Belgium
| | - Laurens J Ceulemans
- BREATHE, Department of CHROMETA, KU Leuven, Leuven, Belgium; Department of Thoracic Surgery, University Hospitals Leuven, Leuven, Belgium
| | - Arne Neyrinck
- Department of Cardiovascular Sciences, KU Leuven, Leuven, Belgium; Department of Anesthesiology, University Hospitals Leuven, Leuven, Belgium
| | - Stijn Verleden
- BREATHE, Department of CHROMETA, KU Leuven, Leuven, Belgium; Department of ASTARC, University of Antwerp, Antwerp, Belgium
| | - Shaf Keshavjee
- Toronto Lung Transplant Program and Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario, Canada; Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada; Ajmera Transplant Centre, University Health Network, University of Toronto, Toronto, Ontario, Canada; Department of Surgery, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.
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Sage AT, Donahoe LL, Shamandy AA, Mousavi SH, Chao BT, Zhou X, Valero J, Balachandran S, Ali A, Martinu T, Tomlinson G, Del Sorbo L, Yeung JC, Liu M, Cypel M, Wang B, Keshavjee S. A machine-learning approach to human ex vivo lung perfusion predicts transplantation outcomes and promotes organ utilization. Nat Commun 2023; 14:4810. [PMID: 37558674 PMCID: PMC10412608 DOI: 10.1038/s41467-023-40468-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [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: 09/28/2022] [Accepted: 07/26/2023] [Indexed: 08/11/2023] Open
Abstract
Ex vivo lung perfusion (EVLP) is a data-intensive platform used for the assessment of isolated lungs outside the body for transplantation; however, the integration of artificial intelligence to rapidly interpret the large constellation of clinical data generated during ex vivo assessment remains an unmet need. We developed a machine-learning model, termed InsighTx, to predict post-transplant outcomes using n = 725 EVLP cases. InsighTx model AUROC (area under the receiver operating characteristic curve) was 79 ± 3%, 75 ± 4%, and 85 ± 3% in training and independent test datasets, respectively. Excellent performance was observed in predicting unsuitable lungs for transplantation (AUROC: 90 ± 4%) and transplants with good outcomes (AUROC: 80 ± 4%). In a retrospective and blinded implementation study by EVLP specialists at our institution, InsighTx increased the likelihood of transplanting suitable donor lungs [odds ratio=13; 95% CI:4-45] and decreased the likelihood of transplanting unsuitable donor lungs [odds ratio=0.4; 95%CI:0.16-0.98]. Herein, we provide strong rationale for the adoption of machine-learning algorithms to optimize EVLP assessments and show that InsighTx could potentially lead to a safe increase in transplantation rates.
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Affiliation(s)
- Andrew T Sage
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
- Toronto Lung Transplant Program, Ajmera Transplant Centre, University Health Network, Toronto, ON, Canada
- Department of Surgery, University of Toronto, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Laura L Donahoe
- Toronto Lung Transplant Program, Ajmera Transplant Centre, University Health Network, Toronto, ON, Canada
- Department of Surgery, University of Toronto, Toronto, ON, Canada
| | - Alaa A Shamandy
- Department of Computer Science, University of Toronto, Toronto, ON, Canada
- Peter Munk Cardiac Centre, University Health Network, Toronto, ON, Canada
| | - S Hossein Mousavi
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
- Toronto Lung Transplant Program, Ajmera Transplant Centre, University Health Network, Toronto, ON, Canada
| | - Bonnie T Chao
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
- Toronto Lung Transplant Program, Ajmera Transplant Centre, University Health Network, Toronto, ON, Canada
| | - Xuanzi Zhou
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
- Toronto Lung Transplant Program, Ajmera Transplant Centre, University Health Network, Toronto, ON, Canada
| | - Jerome Valero
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
- Toronto Lung Transplant Program, Ajmera Transplant Centre, University Health Network, Toronto, ON, Canada
| | - Sharaniyaa Balachandran
- Toronto Lung Transplant Program, Ajmera Transplant Centre, University Health Network, Toronto, ON, Canada
| | - Aadil Ali
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
- Toronto Lung Transplant Program, Ajmera Transplant Centre, University Health Network, Toronto, ON, Canada
| | - Tereza Martinu
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
- Toronto Lung Transplant Program, Ajmera Transplant Centre, University Health Network, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - George Tomlinson
- Department of Medicine, University Health Network, Toronto, ON, Canada
| | - Lorenzo Del Sorbo
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
- Interdepartmental Division of Critical Care Medicine, Medical and Surgical Intensive Care Unit, University Health Network, Toronto, ON, Canada
| | - Jonathan C Yeung
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
- Toronto Lung Transplant Program, Ajmera Transplant Centre, University Health Network, Toronto, ON, Canada
- Department of Surgery, University of Toronto, Toronto, ON, Canada
| | - Mingyao Liu
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
- Toronto Lung Transplant Program, Ajmera Transplant Centre, University Health Network, Toronto, ON, Canada
- Department of Surgery, University of Toronto, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Marcelo Cypel
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
- Toronto Lung Transplant Program, Ajmera Transplant Centre, University Health Network, Toronto, ON, Canada
- Department of Surgery, University of Toronto, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Bo Wang
- Department of Computer Science, University of Toronto, Toronto, ON, Canada.
- Peter Munk Cardiac Centre, University Health Network, Toronto, ON, Canada.
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada.
- Vector Institute, Toronto, ON, Canada.
| | - Shaf Keshavjee
- Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada.
- Toronto Lung Transplant Program, Ajmera Transplant Centre, University Health Network, Toronto, ON, Canada.
- Department of Surgery, University of Toronto, Toronto, ON, Canada.
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada.
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4
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Husain S, Sage AT, Del Sorbo L, Cypel M, Martinu T, Juvet SC, Mariscal A, Wright J, Chao BT, Shamandy AA, Mousavi SH, Ma J, Wang B, Valero J, Liu M, Landes M, Balachandran S, Hudson K, Ngai M, Capuano M, Gelardi M, Lupia E, Marinowic DR, Friedrich FO, Schmitz CRR, Dos Santos LSM, Barbe-Tuana FM, Jones MH, Kain KC, Mazzulli T, Sabbah S, Keshavjee S. A biomarker assay to risk-stratify patients with symptoms of respiratory tract infection. Eur Respir J 2022; 60:2200459. [PMID: 36104292 PMCID: PMC9753477 DOI: 10.1183/13993003.00459-2022] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Accepted: 07/25/2022] [Indexed: 11/05/2022]
Abstract
BACKGROUND Patients who present to an emergency department (ED) with respiratory symptoms are often conservatively triaged in favour of hospitalisation. We sought to determine if an inflammatory biomarker panel that identifies the host response better predicts hospitalisation in order to improve the precision of clinical decision making in the ED. METHODS From April 2020 to March 2021, plasma samples of 641 patients with symptoms of respiratory illness were collected from EDs in an international multicentre study: Canada (n=310), Italy (n=131) and Brazil (n=200). Patients were followed prospectively for 28 days. Subgroup analysis was conducted on confirmed coronavirus disease 2019 (COVID-19) patients (n=245). An inflammatory profile was determined using a rapid, 50-min, biomarker panel (RALI-Dx (Rapid Acute Lung Injury Diagnostic)), which measures interleukin (IL)-6, IL-8, IL-10, soluble tumour necrosis factor receptor 1 (sTNFR1) and soluble triggering receptor expressed on myeloid cells 1 (sTREM1). RESULTS RALI-Dx biomarkers were significantly elevated in patients who required hospitalisation across all three sites. A machine learning algorithm that was applied to predict hospitalisation using RALI-Dx biomarkers had a mean±sd area under the receiver operating characteristic curve of 76±6% (Canada), 84±4% (Italy) and 86±3% (Brazil). Model performance was 82±3% for COVID-19 patients and 87±7% for patients with a confirmed pneumonia diagnosis. CONCLUSIONS The rapid diagnostic biomarker panel accurately identified the need for inpatient care in patients presenting with respiratory symptoms, including COVID-19. The RALI-Dx test is broadly and easily applicable across many jurisdictions, and represents an important diagnostic adjunct to advance ED decision-making protocols.
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Affiliation(s)
- Shahid Husain
- Division of Infectious Diseases, Toronto General Hospital, University Health Network, University of Toronto, Toronto, ON, Canada
- Toronto Lung Transplant Program and Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, University of Toronto, Toronto, ON, Canada
- Ajmera Transplant Centre, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Andrew T Sage
- Toronto Lung Transplant Program and Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, University of Toronto, Toronto, ON, Canada
- Ajmera Transplant Centre, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Lorenzo Del Sorbo
- Toronto Lung Transplant Program and Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, University of Toronto, Toronto, ON, Canada
- Ajmera Transplant Centre, University Health Network, University of Toronto, Toronto, ON, Canada
- Interdepartmental Division of Critical Care Medicine, Medical and Surgical Intensive Care Unit, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Marcelo Cypel
- Toronto Lung Transplant Program and Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, University of Toronto, Toronto, ON, Canada
- Ajmera Transplant Centre, University Health Network, University of Toronto, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Division of Thoracic Surgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
| | - Tereza Martinu
- Toronto Lung Transplant Program and Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, University of Toronto, Toronto, ON, Canada
- Ajmera Transplant Centre, University Health Network, University of Toronto, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Division of Respirology, Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Stephen C Juvet
- Toronto Lung Transplant Program and Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, University of Toronto, Toronto, ON, Canada
- Ajmera Transplant Centre, University Health Network, University of Toronto, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Division of Respirology, Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Andrea Mariscal
- Toronto Lung Transplant Program and Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, University of Toronto, Toronto, ON, Canada
- Ajmera Transplant Centre, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Julie Wright
- Tropical Disease Unit, Department of Medicine, University of Toronto, Sandra Rotman Centre for Global Health, University Health Network, Toronto General Hospital, Toronto, ON, Canada
| | - Bonnie T Chao
- Toronto Lung Transplant Program and Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Alaa A Shamandy
- Department of Computer Science, University of Toronto, Toronto, ON, Canada
- Peter Munk Cardiac Centre, University Health Network, Toronto, ON, Canada
| | - S Hossein Mousavi
- Toronto Lung Transplant Program and Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Jin Ma
- Biostatistics Research Unit, University Health Network, Toronto, ON, Canada
| | - Bo Wang
- Department of Computer Science, University of Toronto, Toronto, ON, Canada
- Peter Munk Cardiac Centre, University Health Network, Toronto, ON, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
- Vector Institute, Toronto, ON, Canada
| | - Jerome Valero
- Toronto Lung Transplant Program and Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, University of Toronto, Toronto, ON, Canada
- Ajmera Transplant Centre, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Mingyao Liu
- Toronto Lung Transplant Program and Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, University of Toronto, Toronto, ON, Canada
- Ajmera Transplant Centre, University Health Network, University of Toronto, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Megan Landes
- Department of Emergency Medicine, University Health Network, Toronto, ON, Canada
- Division of Emergency Medicine, Department of Family and Community Medicine, University of Toronto, Toronto, ON, Canada
| | - Sharaniyaa Balachandran
- Toronto Lung Transplant Program and Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, University of Toronto, Toronto, ON, Canada
- Ajmera Transplant Centre, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Kimberley Hudson
- Toronto Lung Transplant Program and Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, University of Toronto, Toronto, ON, Canada
- Ajmera Transplant Centre, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Michelle Ngai
- Tropical Disease Unit, Department of Medicine, University of Toronto, Sandra Rotman Centre for Global Health, University Health Network, Toronto General Hospital, Toronto, ON, Canada
| | - Marialessia Capuano
- Division of Emergency Medicine and High Dependency Unit, Cittá della Salute e della Scienza di Torino Hospital-Molinette Site, Department of Medical Sciences, University of Turin, Turin, Italy
| | - Maria Gelardi
- Division of Emergency Medicine and High Dependency Unit, Cittá della Salute e della Scienza di Torino Hospital-Molinette Site, Department of Medical Sciences, University of Turin, Turin, Italy
| | - Enrico Lupia
- Division of Emergency Medicine and High Dependency Unit, Cittá della Salute e della Scienza di Torino Hospital-Molinette Site, Department of Medical Sciences, University of Turin, Turin, Italy
| | - Daniel R Marinowic
- School of Medicine, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
| | - Frederico O Friedrich
- School of Medicine, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
| | - Carine R R Schmitz
- Biochemistry, Federal University of Rio Grande do Sul, Porto Alegre, Brazil
| | - Leticya S M Dos Santos
- School of Health, Sciences and Life, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
| | - Florencia M Barbe-Tuana
- School of Health, Sciences and Life, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
| | - Marcus H Jones
- School of Medicine, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
| | - Kevin C Kain
- Tropical Disease Unit, Department of Medicine, University of Toronto, Sandra Rotman Centre for Global Health, University Health Network, Toronto General Hospital, Toronto, ON, Canada
| | - Tony Mazzulli
- Department of Microbiology, Mount Sinai Hospital, Toronto, ON, Canada
| | - Sam Sabbah
- Department of Emergency Medicine, University Health Network, Toronto, ON, Canada
- Division of Emergency Medicine, Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Shaf Keshavjee
- Toronto Lung Transplant Program and Latner Thoracic Research Laboratories, Toronto General Hospital Research Institute, University Health Network, University of Toronto, Toronto, ON, Canada
- Ajmera Transplant Centre, University Health Network, University of Toronto, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Division of Thoracic Surgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
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Nykänen AI, Mariscal A, Duong A, Estrada C, Ali A, Hough O, Sage A, Chao BT, Chen M, Gokhale H, Shan H, Bai X, Zehong G, Yeung J, Waddell T, Martinu T, Juvet S, Cypel M, Liu M, Davies JE, Keshavjee S. Engineered mesenchymal stromal cell therapy during human lung ex vivo lung perfusion is compromised by acidic lung microenvironment. Mol Ther Methods Clin Dev 2021; 23:184-197. [PMID: 34703841 PMCID: PMC8516994 DOI: 10.1016/j.omtm.2021.05.018] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Accepted: 05/07/2021] [Indexed: 11/29/2022]
Abstract
Ex vivo lung perfusion (EVLP) is an excellent platform to apply novel therapeutics, such as gene and cell therapies, before lung transplantation. We investigated the concept of human donor lung engineering during EVLP by combining gene and cell therapies. Premodified cryopreserved mesenchymal stromal cells with augmented anti-inflammatory interleukin-10 production (MSCIL-10) were administered during EVLP to human lungs that had various degrees of underlying lung injury. Cryopreserved MSCIL-10 had excellent viability, and they immediately and efficiently elevated perfusate and lung tissue IL-10 levels during EVLP. However, MSCIL-10 function was compromised by the poor metabolic conditions present in the most damaged lungs. Similarly, exposing cultured MSCIL-10 to poor metabolic, and especially acidic, conditions decreased their IL-10 production. In conclusion, we found that "off-the-shelf" MSCIL-10 therapy of human lungs during EVLP is safe and feasible, and results in rapid IL-10 elevation, and that the acidic target-tissue microenvironment may compromise the efficacy of cell-based therapies.
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Affiliation(s)
- Antti I Nykänen
- Latner Thoracic Surgery Research Laboratories, Toronto General Hospital Research Institute, University Health Network and University of Toronto, 101 College Street, Toronto, ON M5G 1L7, Canada
| | - Andrea Mariscal
- Latner Thoracic Surgery Research Laboratories, Toronto General Hospital Research Institute, University Health Network and University of Toronto, 101 College Street, Toronto, ON M5G 1L7, Canada
| | - Allen Duong
- Latner Thoracic Surgery Research Laboratories, Toronto General Hospital Research Institute, University Health Network and University of Toronto, 101 College Street, Toronto, ON M5G 1L7, Canada
| | - Catalina Estrada
- Tissue Regeneration Therapeutics, 790 Bay Street, Toronto, ON M5G 1N8, Canada
| | - Aadil Ali
- Latner Thoracic Surgery Research Laboratories, Toronto General Hospital Research Institute, University Health Network and University of Toronto, 101 College Street, Toronto, ON M5G 1L7, Canada
| | - Olivia Hough
- Latner Thoracic Surgery Research Laboratories, Toronto General Hospital Research Institute, University Health Network and University of Toronto, 101 College Street, Toronto, ON M5G 1L7, Canada
| | - Andrew Sage
- Latner Thoracic Surgery Research Laboratories, Toronto General Hospital Research Institute, University Health Network and University of Toronto, 101 College Street, Toronto, ON M5G 1L7, Canada
| | - Bonnie T Chao
- Latner Thoracic Surgery Research Laboratories, Toronto General Hospital Research Institute, University Health Network and University of Toronto, 101 College Street, Toronto, ON M5G 1L7, Canada
| | - Manyin Chen
- Latner Thoracic Surgery Research Laboratories, Toronto General Hospital Research Institute, University Health Network and University of Toronto, 101 College Street, Toronto, ON M5G 1L7, Canada
| | - Hemant Gokhale
- Latner Thoracic Surgery Research Laboratories, Toronto General Hospital Research Institute, University Health Network and University of Toronto, 101 College Street, Toronto, ON M5G 1L7, Canada
| | - Hongchao Shan
- Latner Thoracic Surgery Research Laboratories, Toronto General Hospital Research Institute, University Health Network and University of Toronto, 101 College Street, Toronto, ON M5G 1L7, Canada
| | - Xiaohui Bai
- Latner Thoracic Surgery Research Laboratories, Toronto General Hospital Research Institute, University Health Network and University of Toronto, 101 College Street, Toronto, ON M5G 1L7, Canada
| | - Guan Zehong
- Latner Thoracic Surgery Research Laboratories, Toronto General Hospital Research Institute, University Health Network and University of Toronto, 101 College Street, Toronto, ON M5G 1L7, Canada
| | - Jonathan Yeung
- Latner Thoracic Surgery Research Laboratories, Toronto General Hospital Research Institute, University Health Network and University of Toronto, 101 College Street, Toronto, ON M5G 1L7, Canada
| | - Tom Waddell
- Latner Thoracic Surgery Research Laboratories, Toronto General Hospital Research Institute, University Health Network and University of Toronto, 101 College Street, Toronto, ON M5G 1L7, Canada
| | - Tereza Martinu
- Latner Thoracic Surgery Research Laboratories, Toronto General Hospital Research Institute, University Health Network and University of Toronto, 101 College Street, Toronto, ON M5G 1L7, Canada
| | - Stephen Juvet
- Latner Thoracic Surgery Research Laboratories, Toronto General Hospital Research Institute, University Health Network and University of Toronto, 101 College Street, Toronto, ON M5G 1L7, Canada
| | - Marcelo Cypel
- Latner Thoracic Surgery Research Laboratories, Toronto General Hospital Research Institute, University Health Network and University of Toronto, 101 College Street, Toronto, ON M5G 1L7, Canada
| | - Mingyao Liu
- Latner Thoracic Surgery Research Laboratories, Toronto General Hospital Research Institute, University Health Network and University of Toronto, 101 College Street, Toronto, ON M5G 1L7, Canada
| | - John E Davies
- Institute of Biomedical Engineering, University of Toronto, 164 College St, Toronto, ON M5S 3G9, Canada
| | - Shaf Keshavjee
- Latner Thoracic Surgery Research Laboratories, Toronto General Hospital Research Institute, University Health Network and University of Toronto, 101 College Street, Toronto, ON M5G 1L7, Canada
- Institute of Biomedical Engineering, University of Toronto, 164 College St, Toronto, ON M5S 3G9, Canada
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Chen XN, Chao BT, Li XJ. [Circadian rhythm of urinary hydroxyproline: creatinine ratio in schoolchildren]. Hua Xi Yi Ke Da Xue Xue Bao 1986; 17:228-31. [PMID: 3557429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
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