{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,14]],"date-time":"2026-09-14T19:22:14Z","timestamp":1789413734037,"version":"build-2803163510"},"reference-count":217,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2022,12,16]],"date-time":"2022-12-16T00:00:00Z","timestamp":1671148800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Med."],"abstract":"<jats:p>The development of systems biology represents an immense breakthrough in our ability to perform translational research and deliver personalized and precision medicine. A multidisciplinary approach in combination with use of novel techniques allows for the extraction and analysis of vast quantities of data even from the volume and source limited samples that can be obtained from human subjects. Continued advances in microfluidics, scalability and affordability of sequencing technologies, and development of data analysis tools have made the application of a multi-omics, or systems, approach more accessible for use outside of specialized centers. The study of alloimmune and protective immune responses after solid organ transplant offers innumerable opportunities for a multi-omics approach, however, transplant immunology labs are only just beginning to adopt the systems methodology. In this review, we focus on advances in biological techniques and how they are improving our understanding of the immune system and its interactions, highlighting potential applications in transplant immunology. First, we describe the techniques that are available, with emphasis on major advances that allow for increased scalability. Then, we review initial applications in the field of transplantation with a focus on topics that are nearing clinical integration. Finally, we examine major barriers to adapting these methods and discuss potential future developments.<\/jats:p>","DOI":"10.3389\/fmed.2022.1070385","type":"journal-article","created":{"date-parts":[[2022,12,16]],"date-time":"2022-12-16T04:53:50Z","timestamp":1671166430000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":8,"title":["Progress in kidney transplantation: The role for systems immunology"],"prefix":"10.3389","volume":"9","author":[{"given":"Aileen C.","family":"Johnson","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juliete A. F.","family":"Silva","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Steven C.","family":"Kim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christian P.","family":"Larsen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2022,12,16]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"2824","DOI":"10.1111\/ajt.16463","article-title":"Long-term kidney transplant graft survival-Making progress when most needed.","volume":"21","author":"Poggio","year":"2021","journal-title":"Am J Transplant."},{"key":"B2","doi-asserted-by":"publisher","first-page":"1723","DOI":"10.2215\/CJN.15590920","article-title":"Chronic Allograft Injury.","volume":"16","author":"Langewisch","year":"2021","journal-title":"Clin J Am Soc Nephrol CJASN."},{"key":"B3","doi-asserted-by":"publisher","first-page":"1158","DOI":"10.1111\/ajt.14590","article-title":"Late graft failure after kidney transplantation as the consequence of late versus early events.","volume":"18","author":"Gaston","year":"2018","journal-title":"Am J Transplant."},{"key":"B4","doi-asserted-by":"publisher","first-page":"e46","DOI":"10.1097\/TP.0000000000003012","article-title":"The causes of kidney allograft failure: More than alloimmunity. a viewpoint article.","volume":"104","author":"Van Loon","year":"2020","journal-title":"Transplantation."},{"key":"B5","doi-asserted-by":"publisher","first-page":"3401","DOI":"10.1016\/j.transproceed.2008.08.130","article-title":"Long-term efficacy of induction therapy with anti-interleukin-2 receptor antibodies or thymoglobulin compared with no induction therapy in renal transplantation.","volume":"40","author":"Taber","year":"2008","journal-title":"Transplant Proc."},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.1002\/14651858.CD004759.pub2","article-title":"Polyclonal and monoclonal antibodies for induction therapy in kidney transplant recipients.","volume":"1","author":"Hill","year":"2017","journal-title":"Cochrane Database Syst Rev."},{"key":"B7","doi-asserted-by":"publisher","DOI":"10.1016\/j.semnephrol.2016.05.010","article-title":"Introduction: Kidney Transplantation and Viral Infection.","volume":"36","author":"Brennan","year":"2016","journal-title":"Semin Nephrol."},{"key":"B8","doi-asserted-by":"publisher","DOI":"10.1172\/JCI151178","article-title":"Interpreting and addressing suboptimal immune responses after COVID-19 vaccination in solid-organ transplant recipients.","volume":"131","author":"Stock","year":"2021","journal-title":"J Clin Invest."},{"key":"B9","doi-asserted-by":"publisher","DOI":"10.1016\/j.trre.2020.100588","article-title":"COVID-19 in solid organ transplant recipients: A systematic review and meta-analysis of current literature.","volume":"35","author":"Raja","year":"2021","journal-title":"Transplant Rev."},{"key":"B10","doi-asserted-by":"publisher","first-page":"1576","DOI":"10.1111\/ajt.16351","article-title":"COVID-19 outcomes in patients waitlisted for kidney transplantation and kidney transplant recipients.","volume":"21","author":"Craig-Schapiro","year":"2020","journal-title":"Am J Transplant."},{"key":"B11","doi-asserted-by":"publisher","first-page":"417","DOI":"10.1053\/j.ajkd.2019.06.014","article-title":"Practical guide to vaccination in all stages of CKD, including patients treated by dialysis or kidney transplantation.","volume":"75","author":"Krueger","year":"2020","journal-title":"Am J Kidney Dis."},{"key":"B12","doi-asserted-by":"publisher","first-page":"208","DOI":"10.1111\/ajt.16132","article-title":"CMV high-risk status and posttransplant outcomes in kidney transplant recipients treated with belatacept.","volume":"21","author":"Karadkhele","year":"2021","journal-title":"Am J Transplant."},{"key":"B13","doi-asserted-by":"publisher","first-page":"379","DOI":"10.1007\/s00018-019-03410-z","article-title":"Systems biology: current status and challenges.","volume":"77","author":"Zupanic","year":"2020","journal-title":"Cell Mol Life Sci."},{"key":"B14","article-title":"The Tabula Sapiens: A multiple-organ, single-cell transcriptomic atlas of humans.","volume":"376","author":"Jones","year":"2022","journal-title":"Science."},{"key":"B15","doi-asserted-by":"publisher","first-page":"725","DOI":"10.1038\/ni.3768","article-title":"Systems immunology: just getting started.","volume":"18","author":"Davis","year":"2017","journal-title":"Nat Immunol."},{"key":"B16","doi-asserted-by":"publisher","DOI":"10.5041\/RMMJ.10112","article-title":"Systems Biology and P4 Medicine: Past, present, and future.","volume":"4","author":"Hood","year":"2013","journal-title":"Rambam Maimonides Med J."},{"key":"B17","doi-asserted-by":"publisher","first-page":"968","DOI":"10.1016\/j.cell.2020.09.016","article-title":"The immunology of multisystem inflammatory syndrome in children with COVID-19.","volume":"183","author":"Consiglio","year":"2020","journal-title":"Cell."},{"key":"B18","doi-asserted-by":"publisher","first-page":"2238","DOI":"10.1016\/j.celrep.2017.08.021","article-title":"Mass cytometry and topological data analysis reveal immune parameters associated with complications after allogeneic stem cell transplantation.","volume":"20","author":"Lakshmikanth","year":"2017","journal-title":"Cell Rep."},{"key":"B19","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2017.00717","article-title":"Combining flow and mass cytometry in the search for biomarkers in chronic graft-versus-host disease.","volume":"8","author":"Stikvoort","year":"2017","journal-title":"Front Immunol."},{"key":"B20","doi-asserted-by":"publisher","first-page":"6813","DOI":"10.1021\/ac901049w","article-title":"Mass cytometry: technique for real time single cell multitarget immunoassay based on inductively coupled plasma time-of-flight mass spectrometry.","volume":"81","author":"Bandura","year":"2009","journal-title":"Anal Chem."},{"key":"B21","doi-asserted-by":"publisher","first-page":"1514","DOI":"10.1111\/febs.14693","article-title":"The biology of the cell \u2013 insights from mass cytometry.","volume":"286","author":"Brodin","year":"2019","journal-title":"FEBS J."},{"key":"B22","doi-asserted-by":"crossref","first-page":"86.35","DOI":"10.4049\/jimmunol.204.Supp.86.35","article-title":"Evaluation of oligonucleotide conjugated antibodies as reporter molecules in single-cell assays.","author":"Takahashi","year":"2020","journal-title":"J Immunol."},{"key":"B23","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/978-1-4939-8546-3_1","article-title":"The past, present, and future of HLA typing in transplantation.","volume":"1802","author":"Edgerly","year":"2018","journal-title":"Methods Mol Biol."},{"key":"B24","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1016\/j.humimm.2006.10.003","article-title":"HLAMatchmaker: A Molecularly Based Algorithm for Histocompatibility Determination. V. Eplet Matching for HLA-DR, HLA-DQ, and HLA-DP.","volume":"68","author":"Duquesnoy","year":"2007","journal-title":"Hum Immunol."},{"key":"B25","doi-asserted-by":"publisher","first-page":"353","DOI":"10.1016\/S0198-8859(02)00381-6","article-title":"HLAMatchmaker: a molecularly based algorithm for histocompatibility determination. II. Verification of the algorithm and determination of the relative immunogenicity of amino acid triplet-defined epitopes.","volume":"63","author":"Duquesnoy","year":"2002","journal-title":"Hum Immunol."},{"key":"B26","doi-asserted-by":"publisher","first-page":"2139","DOI":"10.1111\/ajt.13707","article-title":"Alloantibody responses after renal transplant failure can be better predicted by donor-recipient HLA amino acid sequence and physicochemical disparities than conventional HLA matching.","volume":"16","author":"Kosmoliaptsis","year":"2016","journal-title":"Am J Transplant."},{"key":"B27","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2020.580752","article-title":"Low Hydrophobic Mismatch Scores Calculated for HLA-A\/B\/DR\/DQ Loci Improve Kidney Allograft Survival.","volume":"11","author":"Bekbolsynov","year":"2020","journal-title":"Front Immunol."},{"key":"B28","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1111\/tan.13883","article-title":"HLA-EMMA: A user-friendly tool to analyse HLA class I and class II compatibility on the amino acid level.","volume":"96","author":"Kramer","year":"2020","journal-title":"Hla."},{"key":"B29","doi-asserted-by":"publisher","first-page":"1338","DOI":"10.1097\/TP.0000000000002117","article-title":"Comparison of HLA molecular mismatch methods to determine HLA immunogenicity.","volume":"102","author":"Wiebe","year":"2018","journal-title":"Transplantation."},{"key":"B30","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2018.00321","article-title":"PIRCHE-II is related to graft failure after kidney transplantation.","volume":"9","author":"Geneugelijk","year":"2018","journal-title":"Front Immunol."},{"key":"B31","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.2113476118","article-title":"Cell-free DNA profiling informs all major complications of hematopoietic cell transplantation.","volume":"119","author":"Cheng","year":"2022","journal-title":"Proc Natl Acad Sci USA."},{"key":"B32","doi-asserted-by":"publisher","first-page":"793","DOI":"10.1016\/j.kint.2021.11.034","article-title":"Clinical outcomes from the Assessing Donor-derived cell-free DNA Monitoring Insights of kidney Allografts with Longitudinal surveillance (ADMIRAL) study.","volume":"101","author":"Bu","year":"2022","journal-title":"Kidney Int."},{"key":"B33","doi-asserted-by":"publisher","first-page":"1178","DOI":"10.1016\/j.cell.2013.10.034","article-title":"Temporal response of the human virome to immunosuppression and antiviral therapy.","volume":"155","author":"De Vlaminck","year":"2013","journal-title":"Cell."},{"key":"B34","doi-asserted-by":"publisher","first-page":"18738","DOI":"10.1073\/pnas.1906320116","article-title":"A cell-free DNA metagenomic sequencing assay that integrates the host injury response to infection.","volume":"116","author":"Cheng","year":"2019","journal-title":"Proc Natl Acad Sci USA."},{"key":"B35","doi-asserted-by":"publisher","first-page":"689","DOI":"10.1038\/s41586-022-04410-z","article-title":"Early prediction of preeclampsia in pregnancy with cell-free RNA| .","volume":"602","author":"Moufarrej","year":"2022","journal-title":"Nature."},{"key":"B36","doi-asserted-by":"publisher","first-page":"855","DOI":"10.1101\/2021.05.05.441859","article-title":"Cell types of origin of the cell-free transcriptome.","volume":"40","author":"Vorperian","year":"2022","journal-title":"Nat Biotechnol."},{"key":"B37","doi-asserted-by":"publisher","first-page":"275","DOI":"10.1146\/annurev-immunol-030409-101253","article-title":"On the composition of the preimmune repertoire of T cells specific for Peptide-major histocompatibility complex ligands.","volume":"28","author":"Jenkins","year":"2010","journal-title":"Annu Rev Immunol."},{"key":"B38","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1111\/imr.12654","article-title":"TCR repertoire evolution during maintenance of CMV-specific T-cell populations.","volume":"283","author":"Schober","year":"2018","journal-title":"Immunol Rev."},{"key":"B39","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1002\/cpim.14","article-title":"MHC-Peptide Tetramers to Visualize Antigen-Specific T Cells.","volume":"115","author":"Altman","year":"2016","journal-title":"Curr Protoc Immunol."},{"key":"B40","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1006457","article-title":"Systematically benchmarking peptide-MHC binding predictors: From synthetic to naturally processed epitopes.","volume":"14","author":"Zhao","year":"2018","journal-title":"PLoS Comput Biol."},{"key":"B41","doi-asserted-by":"publisher","first-page":"D1057","DOI":"10.1093\/nar\/gkz874","article-title":"VDJdb in 2019: database extension, new analysis infrastructure and a T-cell receptor motif compendium.","volume":"48","author":"Bagaev","year":"2020","journal-title":"Nucleic Acids Res."},{"key":"B42","doi-asserted-by":"publisher","first-page":"1194","DOI":"10.1038\/s41587-020-0505-4","article-title":"Analyzing the Mycobacterium tuberculosis immune response by T-cell receptor clustering with GLIPH2 and genome-wide antigen screening.","volume":"38","author":"Huang","year":"2020","journal-title":"Nat Biotechnol."},{"key":"B43","doi-asserted-by":"publisher","first-page":"888","DOI":"10.4049\/jimmunol.1800186","article-title":"A diverse lipid antigen-specific TCR repertoire is clonally expanded during active tuberculosis.","volume":"201","author":"DeWitt","year":"2018","journal-title":"J Immunol."},{"key":"B44","doi-asserted-by":"publisher","DOI":"10.1186\/s12859-019-2864-8","article-title":"Balancing sensitivity and specificity in distinguishing TCR groups by CDR sequence similarity.","volume":"20","author":"Thakkar","year":"2019","journal-title":"BMC Bioinform."},{"key":"B45","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2018.01638","article-title":"Single Cell T Cell receptor sequencing: Techniques and future challenges.","volume":"9","author":"De Simone","year":"2018","journal-title":"Front Immunol."},{"key":"B46","doi-asserted-by":"publisher","first-page":"713","DOI":"10.1016\/j.tibtech.2017.05.004","article-title":"Microfluidics as a strategic player to decipher single-cell omics?","volume":"35","author":"Caen","year":"2017","journal-title":"Trends Biotechnol."},{"key":"B47","doi-asserted-by":"publisher","first-page":"1706","DOI":"10.1039\/C8LC01239C","article-title":"Droplet-based single cell RNAseq tools: a practical guide.","volume":"19","author":"Salomon","year":"2019","journal-title":"Lab Chip."},{"key":"B48","doi-asserted-by":"publisher","first-page":"130","DOI":"10.1016\/j.molcel.2018.10.020","article-title":"Comparative analysis of droplet-based ultra-high-throughput single-cell RNA-Seq systems.","volume":"73","author":"Zhang","year":"2019","journal-title":"Mol Cell."},{"key":"B49","doi-asserted-by":"publisher","first-page":"865","DOI":"10.1038\/nmeth.4380","article-title":"Large-scale simultaneous measurement of epitopes and transcriptomes in single cells.","volume":"14","author":"Stoeckius","year":"2017","journal-title":"Nat Methods."},{"key":"B50","doi-asserted-by":"publisher","first-page":"2712","DOI":"10.1111\/j.1600-6143.2007.02005.x","article-title":"Microarray analysis of rejection in human kidney transplants using pathogenesis-based transcript sets.","volume":"7","author":"Mueller","year":"2007","journal-title":"Am J Transplant."},{"key":"B51","doi-asserted-by":"publisher","first-page":"2215","DOI":"10.1111\/j.1600-6143.2010.03267.x","article-title":"The molecular phenotype of kidney transplants.","volume":"10","author":"Halloran","year":"2010","journal-title":"Am J Transplant."},{"key":"B52","doi-asserted-by":"publisher","first-page":"2223","DOI":"10.1111\/j.1600-6143.2010.03268.x","article-title":"An integrated view of molecular changes, histopathology and outcomes in kidney transplants.","volume":"10","author":"Halloran","year":"2010","journal-title":"Am J Transplant."},{"key":"B53","doi-asserted-by":"publisher","first-page":"534","DOI":"10.1038\/nrneph.2016.85","article-title":"Molecular assessment of disease states in kidney transplant biopsy samples.","volume":"12","author":"Halloran","year":"2016","journal-title":"Nat Rev Nephrol."},{"key":"B54","doi-asserted-by":"publisher","first-page":"258","DOI":"10.1038\/ki.2013.300","article-title":"Antibody-mediated rejection, T cell-mediated rejection, and the injury-repair response: new insights from the Genome Canada studies of kidney transplant biopsies.","volume":"85","author":"Halloran","year":"2014","journal-title":"Kidney Int."},{"key":"B55","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1097\/MOT.0b013e3283352a50","article-title":"Endothelial transcripts uncover a previously unknown phenotype: C4d-negative antibody-mediated rejection.","volume":"15","author":"Sis","year":"2010","journal-title":"Curr Opin Organ Transplant."},{"key":"B56","doi-asserted-by":"publisher","first-page":"1711","DOI":"10.1681\/ASN.2014060588","article-title":"Disappearance of T Cell-Mediated Rejection Despite Continued Antibody-Mediated Rejection in Late Kidney Transplant Recipients.","volume":"26","author":"Halloran","year":"2015","journal-title":"J Am Soc Nephrol JASN."},{"key":"B57","doi-asserted-by":"publisher","first-page":"1475","DOI":"10.1111\/j.1600-6143.2004.00526.x","article-title":"Kidney transplant rejection and tissue injury by gene profiling of biopsies and peripheral blood lymphocytes.","volume":"4","author":"Flechner","year":"2004","journal-title":"Am J Transplant."},{"key":"B58","doi-asserted-by":"publisher","first-page":"645","DOI":"10.1111\/ajt.12079","article-title":"Molecular diagnosis of T cell-mediated rejection in human kidney transplant biopsies.","volume":"13","author":"Reeve","year":"2013","journal-title":"Am J Transplant."},{"key":"B59","article-title":"Analysis of RNA Transcripts by the Molecular Microscope Diagnostic System (MMDx) Can Direct Management after Indication Kidney Transplant Biopsy.","volume":"5","author":"Lawrence","year":"2020","journal-title":"Kidney Dis."},{"key":"B60","doi-asserted-by":"publisher","DOI":"10.1001\/jamanetworkopen.2020.35048","article-title":"Molecular diversity of clinically stable human kidney allografts.","volume":"4","author":"Rychkov","year":"2021","journal-title":"JAMA Netw Open."},{"key":"B61","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pmed.1001759","article-title":"The kSORT assay to detect renal transplant patients at high risk for acute rejection: results of the multicenter AART study.","volume":"11","author":"Roedder","year":"2014","journal-title":"PLoS Med."},{"key":"B62","doi-asserted-by":"publisher","first-page":"740","DOI":"10.1111\/ajt.16179","article-title":"Diagnostic performance of kSORT, a blood-based mRNA assay for noninvasive detection of rejection after kidney transplantation: A retrospective multicenter cohort study.","volume":"21","author":"Van Loon","year":"2021","journal-title":"Am J Transplant."},{"key":"B63","doi-asserted-by":"publisher","first-page":"280","DOI":"10.1007\/s10875-012-9777-x","article-title":"Combination of IL-1 receptor antagonist, IL-20 and CD40 ligand for the prediction of acute cellular renal allograft rejection.","volume":"33","author":"Xu","year":"2013","journal-title":"J Clin Immunol."},{"key":"B64","doi-asserted-by":"publisher","first-page":"917","DOI":"10.1007\/s12551-020-00713-5","article-title":"Understanding and using AlloSure donor derived cell-free DNA.","volume":"12","author":"Seeto","year":"2020","journal-title":"Biophys Rev."},{"key":"B65","author":"Wojciechowski","year":"2021","journal-title":"Use of Donor Derived-cell Free DNA (AlloSure) to Facilitate Belatacept Monotherapy in Kidney Transplant Patients"},{"key":"B66","doi-asserted-by":"publisher","first-page":"1565","DOI":"10.1097\/01.TP.0000058230.91518.2F","article-title":"Serine proteinase inhibitor-9, an endogenous blocker of granzyme B\/perforin lytic pathway, is hyperexpressed during acute rejection of renal allografts.","volume":"75","author":"Muthukumar","year":"2003","journal-title":"Transplantation."},{"key":"B67","doi-asserted-by":"publisher","first-page":"2342","DOI":"10.1056\/NEJMoa051907","article-title":"Messenger RNA for FOXP3 in the urine of renal-allograft recipients.","volume":"353","author":"Muthukumar","year":"2005","journal-title":"N Engl J Med."},{"key":"B68","first-page":"1543","article-title":"Analysis of urine cytology by flow cytometry in renal transplantation.","volume":"24","author":"Lee","year":"1992","journal-title":"Transplant Proc."},{"key":"B69","doi-asserted-by":"publisher","first-page":"1866","DOI":"10.1097\/01.TP.0000131157.19937.3F","article-title":"Enhanced granulysin mRNA expression in urinary sediment in early and delayed acute renal allograft rejection.","volume":"77","author":"Kotsch","year":"2004","journal-title":"Transplantation."},{"key":"B70","doi-asserted-by":"publisher","first-page":"2390","DOI":"10.1111\/j.1523-1755.2004.00663.x","article-title":"Noninvasive detection of renal allograft inflammation by measurements of mRNA for IP-10 and CXCR3 in urine.","volume":"65","author":"Tatapudi","year":"2004","journal-title":"Kidney Int."},{"key":"B71","doi-asserted-by":"publisher","first-page":"1661","DOI":"10.1111\/j.1600-6143.2007.01795.x","article-title":"High expression of Tim-3 mRNA in urinary cells from kidney transplant recipients with acute rejection.","volume":"7","author":"Renesto","year":"2007","journal-title":"Am J Transplant."},{"key":"B72","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1056\/NEJMoa1215555","article-title":"Urinary-cell mRNA profile and acute cellular rejection in kidney allografts.","volume":"369","author":"Suthanthiran","year":"2013","journal-title":"N Engl J Med."},{"key":"B73","doi-asserted-by":"publisher","first-page":"1586","DOI":"10.1681\/ASN.2013080900","article-title":"Urinary cell mRNA profiles and differential diagnosis of acute kidney graft dysfunction.","volume":"25","author":"Matignon","year":"2014","journal-title":"J Am Soc Nephrol JASN."},{"key":"B74","doi-asserted-by":"publisher","first-page":"2228","DOI":"10.1111\/j.1600-6143.2011.03680.x","article-title":"Urinary chemokines CXCL9 and CXCL10 are noninvasive markers of renal allograft rejection and BK viral infection.","volume":"11","author":"Jackson","year":"2011","journal-title":"Am J Transplant."},{"key":"B75","doi-asserted-by":"publisher","first-page":"1814","DOI":"10.1097\/TP.0b013e3181a66b3e","article-title":"Noninvasive detection of acute and chronic injuries in human renal transplant by elevation of multiple cytokines\/chemokines in urine.","volume":"87","author":"Hu","year":"2009","journal-title":"Transplantation."},{"key":"B76","doi-asserted-by":"publisher","first-page":"1347","DOI":"10.1111\/j.1600-6143.2009.02645.x","article-title":"Urinary CXCL9 and CXCL10 levels correlate with the extent of subclinical tubulitis.","volume":"9","author":"Schaub","year":"2009","journal-title":"Am J Transplant."},{"key":"B77","doi-asserted-by":"publisher","first-page":"1811","DOI":"10.1111\/j.1600-6143.2012.03999.x","article-title":"Detection of clinical and subclinical tubulo-interstitial inflammation by the urinary CXCL10 chemokine in a real-life setting.","volume":"12","author":"Hirt-Minkowski","year":"2012","journal-title":"Am J Transplant."},{"key":"B78","doi-asserted-by":"publisher","first-page":"3114","DOI":"10.1681\/ASN.2014121234","article-title":"Adverse outcomes of tacrolimus withdrawal in immune\u2013quiescent kidney transplant recipients.","volume":"26","author":"Hricik","year":"2015","journal-title":"J Am Soc Nephrol."},{"key":"B79","doi-asserted-by":"publisher","first-page":"311","DOI":"10.1002\/prca.201000109","article-title":"Elevated expression levels of ANXA11, integrins \u03b23 and \u03b13, and TNF-\u03b1 contribute to a candidate proteomic signature in urine for kidney allograft rejection.","volume":"5","author":"Srivastava","year":"2011","journal-title":"Proteomics Clin Appl."},{"key":"B80","doi-asserted-by":"publisher","first-page":"1244","DOI":"10.1016\/j.kint.2015.12.049","article-title":"Mining the human urine proteome for monitoring renal transplant injury.","volume":"89","author":"Sigdel","year":"2016","journal-title":"Kidney Int."},{"key":"B81","doi-asserted-by":"publisher","DOI":"10.3390\/jcm9082341","article-title":"Targeted urine metabolomics for monitoring renal allograft injury and immunosuppression in pediatric patients.","volume":"9","author":"Sigdel","year":"2020","journal-title":"J Clin Med."},{"key":"B82","doi-asserted-by":"publisher","first-page":"621","DOI":"10.1074\/mcp.M113.030577","article-title":"The identification of novel potential injury mechanisms and candidate biomarkers in renal allograft rejection by quantitative proteomics.","volume":"13","author":"Sigdel","year":"2014","journal-title":"Mol Cell Proteom MCP."},{"key":"B83","doi-asserted-by":"publisher","DOI":"10.3389\/fmed.2019.00213","article-title":"Assessment of 19 genes and validation of crm gene panel for quantitative transcriptional analysis of molecular rejection and inflammation in archival kidney transplant biopsies.","volume":"6","author":"Sigdel","year":"2019","journal-title":"Front Med."},{"key":"B84","doi-asserted-by":"publisher","first-page":"646","DOI":"10.1681\/ASN.2009080876","article-title":"Integrative urinary peptidomics in renal transplantation identifies biomarkers for acute rejection.","volume":"21","author":"Ling","year":"2010","journal-title":"J Am Soc Nephrol JASN."},{"key":"B85","doi-asserted-by":"publisher","DOI":"10.1126\/scitranslmed.aba2501","article-title":"A urine score for noninvasive accurate diagnosis and prediction of kidney transplant rejection.","volume":"12","author":"Yang","year":"2020","journal-title":"Sci Transl Med."},{"key":"B86","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1111\/tri.13363","article-title":"Urinary proteomics to diagnose chronic active antibody-mediated rejection in pediatric kidney transplantation - a pilot study.","volume":"32","author":"Kanzelmeyer","year":"2019","journal-title":"Transpl Int."},{"key":"B87","doi-asserted-by":"publisher","first-page":"1448","DOI":"10.1016\/j.ekir.2020.06.018","article-title":"Urinary protein biomarker panel for the diagnosis of antibody-mediated rejection in kidney transplant recipients.","volume":"5","author":"Mertens","year":"2020","journal-title":"Kidney Int Rep."},{"key":"B88","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1159\/000030378","article-title":"Flow-Cytometric measurement of cellular changes in urine: A simple and rapid method for perioperatively monitoring patients after kidney transplantation.","volume":"62","author":"Yu","year":"1999","journal-title":"Urol Int."},{"key":"B89","doi-asserted-by":"publisher","first-page":"S8","DOI":"10.1111\/tri.1992.5.s1.8","article-title":"Flow cytometry evaluation of urinary sediment in renal transplantation.","author":"Nanni-Costa","year":"1992","journal-title":"Transpl Int."},{"key":"B90","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1016\/j.trim.2006.03.014","article-title":"Noninvasive immune monitoring assessed by flow cytometry and real time RT-PCR in urine of renal transplantation recipients.","volume":"16","author":"Galante","year":"2006","journal-title":"Transpl Immunol."},{"key":"B91","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-57524-7","article-title":"Kidney transplant monitoring by urinary flow cytometry: Biomarker combination of T cells, renal tubular epithelial cells, and podocalyxin-positive cells detects rejection.","volume":"10","author":"Goerlich","year":"2020","journal-title":"Sci Rep."},{"key":"B92","doi-asserted-by":"publisher","DOI":"10.1155\/2015\/782798","article-title":"Human urine proteomics: Analytical techniques and clinical applications in renal diseases.","volume":"2015","author":"Kalantari","year":"2015","journal-title":"Int J Proteomics."},{"key":"B93","doi-asserted-by":"publisher","DOI":"10.1016\/j.trre.2021.100649","article-title":"The clinical value of donor-derived cell-free DNA measurements in kidney transplantation.","volume":"35","author":"Garg","year":"2021","journal-title":"Transplant Rev."},{"key":"B94","doi-asserted-by":"publisher","DOI":"10.3390\/jcm8010019","article-title":"Optimizing detection of kidney transplant injury by assessment of donor-derived cell-free DNA via massively multiplex PCR.","volume":"8","author":"Sigdel","year":"2018","journal-title":"J Clin Med."},{"key":"B95","doi-asserted-by":"publisher","first-page":"2221","DOI":"10.1681\/ASN.2016091034","article-title":"Cell-Free DNA and active rejection in kidney allografts.","volume":"28","author":"Bloom","year":"2017","journal-title":"J Am Soc Nephrol."},{"key":"B96","doi-asserted-by":"publisher","DOI":"10.1097\/TXD.0000000000001027","article-title":"Donor-derived Cell-free DNA combined with histology improves prediction of estimated glomerular filtration rate over time in kidney transplant recipients compared with histology alone.","volume":"6","author":"Huang","year":"2020","journal-title":"Transplant Direct."},{"key":"B97","doi-asserted-by":"publisher","DOI":"10.1097\/TP.0000000000004267","article-title":"An assessment of the value of donor-derived cell-free DNA surveillance in patients with preserved kidney allograft function.","author":"Huang","year":"2022","journal-title":"Transplantation."},{"key":"B98","doi-asserted-by":"publisher","DOI":"10.1111\/ctr.14785","article-title":"Levels of donor-derived cell-free DNA and chemokines in BK polyomavirus-associated nephropathy.","author":"Mayer","year":"2022","journal-title":"Clin Transplant."},{"key":"B99","doi-asserted-by":"publisher","first-page":"65","DOI":"10.5414\/CN110760","article-title":"Protocol-based donor-derived cell-free DNA surveillance in kidney transplant recipients: A single-center experience.","volume":"98","author":"Nissaisorakarn","year":"2022","journal-title":"Clin Nephrol."},{"key":"B100","doi-asserted-by":"publisher","first-page":"2388","DOI":"10.1016\/j.transproceed.2018.02.183","article-title":"Class II HLA Eplet Mismatch Is a risk factor for de novo donor-specific antibody development and antibody-mediated rejection in kidney transplantation recipients.","volume":"50","author":"Kishikawa","year":"2018","journal-title":"Transplant Proc."},{"key":"B101","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1016\/j.humimm.2020.12.009","article-title":"Eplet mismatch scores and de novo donor-specific antibody development in simultaneous pancreas-kidney transplantation.","volume":"82","author":"Ladowski","year":"2021","journal-title":"Hum Immunol."},{"key":"B102","doi-asserted-by":"publisher","first-page":"778","DOI":"10.1016\/j.kint.2019.10.028","article-title":"Epitopes as characterized by antibody-verified eplet mismatches determine risk of kidney transplant loss.","volume":"97","author":"Sapir-Pichhadze","year":"2020","journal-title":"Kidney Int."},{"key":"B103","doi-asserted-by":"publisher","first-page":"2193","DOI":"10.1681\/ASN.2020010019","article-title":"Eplet mismatch load and de novo occurrence of donor-specific Anti-HLA antibodies, rejection, and graft failure after kidney transplantation: An observational cohort study.","volume":"31","author":"Senev","year":"2020","journal-title":"J Am Soc Nephrol JASN."},{"key":"B104","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1111\/iji.12519","article-title":"HLA class II eplet mismatch load improves prediction of dnDSA development after living donor kidney transplantation.","volume":"48","author":"Tafulo","year":"2021","journal-title":"Int J Immunogenet."},{"key":"B105","doi-asserted-by":"publisher","first-page":"3353","DOI":"10.1681\/ASN.2017030287","article-title":"Class II Eplet mismatch modulates tacrolimus trough levels required to prevent donor-specific antibody development.","volume":"28","author":"Wiebe","year":"2017","journal-title":"J Am Soc Nephrol JASN."},{"key":"B106","doi-asserted-by":"publisher","first-page":"322","DOI":"10.1111\/ajt.16290","article-title":"Adequate tacrolimus exposure modulates the impact of HLA class II molecular mismatch: a validation study in an American cohort.","volume":"21","author":"Davis","year":"2021","journal-title":"Am J Transplant."},{"key":"B107","doi-asserted-by":"publisher","DOI":"10.3390\/ijms23137357","article-title":"Combined Analysis of HLA Class II eplet mismatch and tacrolimus levels for the prediction of de novo donor specific antibody development in kidney transplant recipients.","volume":"23","author":"Lee","year":"2022","journal-title":"Int J Mol Sci."},{"key":"B108","doi-asserted-by":"publisher","first-page":"264","DOI":"10.1016\/j.humimm.2022.01.002","article-title":"Genome Canada precision medicine strategy for structured national implementation of epitope matching in renal transplantation.","volume":"83","author":"Sherwood","year":"2022","journal-title":"Hum Immunol."},{"key":"B109","doi-asserted-by":"publisher","first-page":"931","DOI":"10.1111\/petr.12815","article-title":"Application of an epitope-based allocation system in pediatric kidney transplantation.","volume":"20","author":"Kausman","year":"2016","journal-title":"Pediatr Transplant."},{"key":"B110","doi-asserted-by":"publisher","first-page":"1567","DOI":"10.1016\/j.ekir.2021.03.877","article-title":"On path to informing hierarchy of eplet mismatches as determinants of kidney transplant loss.","volume":"6","author":"Mohammadhassanzadeh","year":"2021","journal-title":"Kidney Int Rep."},{"key":"B111","doi-asserted-by":"publisher","DOI":"10.1111\/ctr.12924","article-title":"De novo DQ donor-specific antibodies are associated with worse outcomes compared to non-DQ de novo donor-specific antibodies following heart transplantation.","volume":"31","author":"Cole","year":"2017","journal-title":"Clin Transplant."},{"key":"B112","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1111\/tan.14110","article-title":"Development of an immunogenicity score for HLA-DQ eplets: A conceptual study.","volume":"97","author":"Schawalder","year":"2021","journal-title":"HLA."},{"key":"B113","doi-asserted-by":"publisher","first-page":"589","DOI":"10.1111\/tan.14054","article-title":"Toward defining the immunogenicity of HLA epitopes: Impact of HLA class I eplets on antibody formation during pregnancy.","volume":"96","author":"H\u00f6nger","year":"2020","journal-title":"HLA."},{"key":"B114","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2018.02010","article-title":"HLA-Epitope matching or eplet risk stratification: The devil is in the details.","volume":"9","author":"Tambur","year":"2018","journal-title":"Front Immunol."},{"key":"B115","doi-asserted-by":"publisher","first-page":"336","DOI":"10.3390\/transplantology2030033","article-title":"Epitope-Level matching\u2014a review of the novel concept of eplets in transplant histocompatibility.","volume":"2","author":"Renaldo","year":"2021","journal-title":"Transplantology."},{"key":"B116","doi-asserted-by":"publisher","first-page":"314","DOI":"10.1016\/j.kint.2017.08.008","article-title":"Novel aspects of epitope matching and practical application in kidney transplantation.","volume":"93","author":"Lim","year":"2018","journal-title":"Kidney Int."},{"key":"B117","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1007\/s00251-019-01140-x","article-title":"PIRCHE-II: an algorithm to predict indirectly recognizable HLA epitopes in solid organ transplantation.","volume":"72","author":"Geneugelijk","year":"2020","journal-title":"Immunogenetics."},{"key":"B118","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2021.631246","article-title":"Can PIRCHE-II Matching Outmatch Traditional HLA Matching?","volume":"12","author":"Unterrainer","year":"2021","journal-title":"Front Immunol."},{"key":"B119","author":"Zhang","year":"2021","journal-title":"hlaR: Streamlined HLA Eplet Analysis."},{"key":"B120","author":"Zhang","year":"2021","journal-title":"hlaR: Tools for HLA Data."},{"key":"B121","doi-asserted-by":"publisher","first-page":"248","DOI":"10.1016\/j.humimm.2022.01.007","article-title":"hlaR: A rapid and reproducible tool to identify eplet mismatches between transplant donors and recipients.","volume":"83","author":"Johnson","year":"2022","journal-title":"Hum Immunol."},{"key":"B122","doi-asserted-by":"publisher","first-page":"344","DOI":"10.1111\/ajt.16070","article-title":"Substituting imputation of HLA antigens for high-resolution HLA typing: Evaluation of a multiethnic population and implications for clinical decision making in transplantation.","volume":"21","author":"Engen","year":"2021","journal-title":"Am J Transplant."},{"key":"B123","doi-asserted-by":"publisher","first-page":"20339","DOI":"10.1073\/pnas.1911281116","article-title":"Predicting kidney transplant outcomes with partial knowledge of HLA mismatch.","volume":"116","author":"Manski","year":"2019","journal-title":"Proc Natl Acad Sci USA."},{"key":"B124","doi-asserted-by":"publisher","DOI":"10.1016\/j.prp.2020.153040","article-title":"The future of pathology is digital.","volume":"216","author":"Pallua","year":"2020","journal-title":"Pathol - Res Pract."},{"key":"B125","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41592-020-01042-x","article-title":"Method of the Year 2020: spatially resolved transcriptomics.","volume":"18","year":"2021","journal-title":"Nat Methods."},{"key":"B126","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1038\/s41592-020-01033-y","article-title":"Method of the Year: spatially resolved transcriptomics.","volume":"18","author":"Marx","year":"2021","journal-title":"Nat Methods."},{"key":"B127","doi-asserted-by":"publisher","first-page":"1192","DOI":"10.1016\/j.healun.2017.05.029","article-title":"Building a tissue-based molecular diagnostic system in heart transplant rejection: The heart Molecular Microscope Diagnostic (MMDx) System.","volume":"36","author":"Halloran","year":"2017","journal-title":"J Heart Lung Transplant."},{"key":"B128","doi-asserted-by":"publisher","first-page":"1341","DOI":"10.1111\/ajt.15752","article-title":"Discrepancy analysis comparing molecular and histology diagnoses in kidney transplant biopsies.","volume":"20","author":"Madill-Thomsen","year":"2020","journal-title":"Am J Transplant."},{"key":"B129","doi-asserted-by":"publisher","first-page":"2305","DOI":"10.1111\/ajt.16059","article-title":"Banff 2019 meeting report: molecular diagnostics in solid organ transplantation\u2013consensus for the banff human organ transplant (B-HOT) gene panel and open source multicenter validation.","volume":"20","author":"Mengel","year":"2020","journal-title":"Am J Transplant."},{"key":"B130","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2021.664244","article-title":"Immune Monitoring for Advanced Cell Therapy Trials in Transplantation: Which Assays and When?","volume":"12","author":"Stark","year":"2021","journal-title":"Front Immunol."},{"key":"B131","doi-asserted-by":"publisher","DOI":"10.1111\/apha.13848","article-title":"Single cell- and spatial \u2018Omics revolutionize physiology.","volume":"235","author":"Conrad","year":"2022","journal-title":"Acta Physiol."},{"key":"B132","doi-asserted-by":"publisher","first-page":"1190","DOI":"10.1038\/s41587-022-01233-1","article-title":"Spatial charting of single-cell transcriptomes in tissues.","volume":"40","author":"Wei","year":"2022","journal-title":"Nat Biotechnol."},{"key":"B133","doi-asserted-by":"publisher","first-page":"997","DOI":"10.1038\/s41592-021-01203-6","article-title":"Spatial omics and multiplexed imaging to explore cancer biology.","volume":"18","author":"Lewis","year":"2021","journal-title":"Nat Methods."},{"key":"B134","doi-asserted-by":"publisher","DOI":"10.1002\/ctm2.696","article-title":"Spatial omics: Navigating to the golden era of cancer research.","volume":"12","author":"Wu","year":"2022","journal-title":"Clin Transl Med."},{"key":"B135","doi-asserted-by":"publisher","DOI":"10.1016\/j.mcpro.2021.100186","article-title":"Subcellular transcriptomics and proteomics: A comparative methods review.","volume":"21","author":"Christopher","year":"2022","journal-title":"Mol Cell Proteom."},{"key":"B136","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1016\/j.kint.2021.09.004","article-title":"The spatially resolved transcriptional profile of acute T cell\u2013mediated rejection in a kidney allograft.","volume":"101","author":"Salem","year":"2022","journal-title":"Kidney Int."},{"key":"B137","doi-asserted-by":"publisher","DOI":"10.1002\/hep.32666","article-title":"Next-generation pathology detection of T cell\u2013antigen-presenting cell immune synapses in human liver allografts.","author":"Wood-Trageser","year":"2022","journal-title":"Hepatology."},{"key":"B138","doi-asserted-by":"publisher","first-page":"659","DOI":"10.1038\/ng.3822","article-title":"Immunosequencing identifies signatures of cytomegalovirus exposure history and HLA-mediated effects on the T cell repertoire.","volume":"49","author":"Emerson","year":"2017","journal-title":"Nat Genet."},{"key":"B139","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-018-02832-w","article-title":"High-throughput immune repertoire analysis with IGoR.","volume":"9","author":"Marcou","year":"2018","journal-title":"Nat Commun."},{"key":"B140","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1038\/cr.2012.1","article-title":"Determinants of public T cell responses.","volume":"22","author":"Li","year":"2012","journal-title":"Cell Res."},{"key":"B141","doi-asserted-by":"publisher","DOI":"10.7554\/eLife.68605","article-title":"TCR meta-clonotypes for biomarker discovery with tcrdist3 enabled identification of public, HLA-restricted clusters of SARS-CoV-2 TCRs.","volume":"10","author":"Mayer-Blackwell","year":"2021","journal-title":"eLife."},{"key":"B142","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2022.851868","article-title":"Public T-Cell Receptors (TCRs) revisited by analysis of the magnitude of identical and highly-similar TCRs in Virus-Specific T-Cell Repertoires of Healthy Individuals.","volume":"13","author":"Huisman","year":"2022","journal-title":"Front Immunol."},{"key":"B143","doi-asserted-by":"publisher","DOI":"10.1101\/2021.07.30.21261353","article-title":"Immunosequencing of the T-Cell Receptor repertoire reveals signatures specific for identification and characterization of early lyme disease.","author":"Greissl","year":"2022","journal-title":"medRxiv"},{"key":"B144","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2021.620386","article-title":"CMV Status Drives Distinct Trajectories of CD4+ T Cell Differentiation.","volume":"12","author":"Zhang","year":"2021","journal-title":"Front Immunol."},{"key":"B145","doi-asserted-by":"publisher","DOI":"10.1101\/2021.01.06.21249345","article-title":"Clinical Validation of a Novel T-cell Receptor Sequencing Assay for Identification of Recent or Prior SARS-CoV-2 Infection.","volume":"6","author":"Dalai","year":"2022","journal-title":"Clin Infect Dis."},{"key":"B146","doi-asserted-by":"publisher","DOI":"10.1172\/jci.insight.150070","article-title":"T cell receptor sequencing identifies prior SARS-CoV-2 infection and correlates with neutralizing antibodies and disease severity.","volume":"7","author":"Elyanow","year":"2022","journal-title":"JCI Insight."},{"key":"B147","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2022.880190","article-title":"Differences in SARS-CoV-2 Vaccine Response Dynamics Between Class-I- and Class-II-Specific T-Cell Receptors in Inflammatory Bowel Disease.","volume":"13","author":"Xu","year":"2022","journal-title":"Front Immunol."},{"key":"B148","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics12051222","article-title":"Utility of Bulk T-Cell Receptor Repertoire Sequencing Analysis in Understanding Immune Responses to COVID-19.","volume":"12","author":"Kockelbergh","year":"2022","journal-title":"Diagn Basel Switz."},{"key":"B149","doi-asserted-by":"publisher","DOI":"10.1016\/j.simpa.2021.100142","article-title":"Integrated analysis toolset for defining and tracking alloreactive T-cell clones after human solid organ and hematopoietic stem cell transplantation.","volume":"10","author":"Obradovic","year":"2021","journal-title":"Softw Impacts."},{"key":"B150","doi-asserted-by":"publisher","first-page":"538","DOI":"10.1111\/ajt.15592","article-title":"Deletion of donor-reactive T cell clones after human liver transplant.","volume":"20","author":"Savage","year":"2020","journal-title":"Am J Transplant."},{"key":"B151","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2021.791725","article-title":"Chimerism-Based tolerance to kidney allografts in humans: Novel insights and future perspectives.","volume":"12","author":"Podest\u00e0","year":"2021","journal-title":"Front Immunol."},{"key":"B152","doi-asserted-by":"publisher","DOI":"10.1172\/jci.insight.121256","article-title":"Quantifying size and diversity of the human T cell alloresponse.","volume":"3","author":"DeWolf","year":"2018","journal-title":"JCI Insight."},{"key":"B153","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2021.750005","article-title":"Prospective tracking of donor-reactive T-Cell clones in the circulation and rejecting human kidney allografts.","volume":"12","author":"Aschauer","year":"2021","journal-title":"Front Immunol."},{"key":"B154","doi-asserted-by":"publisher","DOI":"10.1172\/JCI146771","article-title":"The self-peptide repertoire plays a critical role in transplant tolerance induction.","volume":"131","author":"Son","year":"2021","journal-title":"J Clin Invest."},{"key":"B155","doi-asserted-by":"publisher","DOI":"10.1136\/jitc-2020-002071","article-title":"HLA Ligand Atlas: a benign reference of HLA-presented peptides to improve T-cell-based cancer immunotherapy.","volume":"9","author":"Marcu","year":"2021","journal-title":"J Immunother Cancer."},{"key":"B156","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0136417","article-title":"Comprehensive analysis of the naturally processed peptide repertoire: Differences between HLA-A and B in the Immunopeptidome.","volume":"10","author":"Schellens","year":"2015","journal-title":"PLoS One."},{"key":"B157","doi-asserted-by":"publisher","first-page":"864","DOI":"10.1182\/blood.2020009266","article-title":"The immunopeptidome guides permissive HLA mismatch.","volume":"137","author":"Walz","year":"2021","journal-title":"Blood."},{"key":"B158","doi-asserted-by":"publisher","first-page":"W449","DOI":"10.1093\/nar\/gkaa379","article-title":"NetMHCpan-4.1 and NetMHCIIpan-4.0: improved predictions of MHC antigen presentation by concurrent motif deconvolution and integration of MS MHC eluted ligand data.","volume":"48","author":"Reynisson","year":"2020","journal-title":"Nucleic Acids Res."},{"key":"B159","doi-asserted-by":"publisher","first-page":"1362","DOI":"10.1182\/blood-2004-07-2602","article-title":"Cross-recognition of human alloantigen by cytomegalovirus glycoprotein-specific CD4+ cytotoxic T lymphocytes: implications for graft-versus-host disease.","volume":"105","author":"Elkington","year":"2005","journal-title":"Blood."},{"key":"B160","doi-asserted-by":"publisher","first-page":"3844","DOI":"10.1182\/blood.V99.10.3844","article-title":"Herpes simplex virus type 2-specific CD8 cytotoxic T lymphocyte cross-reactivity against prevalent HLA class I alleles.","volume":"99","author":"Koelle","year":"2002","journal-title":"Blood."},{"key":"B161","doi-asserted-by":"publisher","first-page":"2033","DOI":"10.1111\/ajt.14279","article-title":"Allo-HLA Cross-Reactivities of Cytomegalovirus-, Influenza-, and Varicella Zoster Virus-Specific Memory T Cells Are Shared by Different Healthy Individuals.","volume":"17","author":"van den Heuvel","year":"2017","journal-title":"Am J Transplant."},{"key":"B162","doi-asserted-by":"publisher","first-page":"1155","DOI":"10.1084\/jem.179.4.1155","article-title":"An alloresponse in humans is dominated by cytotoxic T lymphocytes (CTL) cross-reactive with a single Epstein-Barr virus CTL epitope: implications for graft-versus-host disease.","volume":"179","author":"Burrows","year":"1994","journal-title":"J Exp Med."},{"key":"B163","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0012120","article-title":"Cross-Reactivity of Herpesvirus-Specific CD8 T Cell Lines Toward Allogeneic Class I MHC Molecules.","volume":"5","author":"Morice","year":"2010","journal-title":"PLoS One."},{"key":"B164","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1111\/iji.12563","article-title":"Human leukocyte antigen epitope mismatch loads and the development of de novo donor-specific antibodies in cardiothoracic organ transplantation.","volume":"49","author":"Bedford","year":"2022","journal-title":"Int J Immunogenet."},{"key":"B165","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2022.788818","article-title":"High PIRCHE scores may allow risk stratification of borderline rejection in kidney transplant recipients.","volume":"13","author":"Lezoeva","year":"2022","journal-title":"Front Immunol."},{"key":"B166","doi-asserted-by":"publisher","DOI":"10.1111\/ctr.14755","article-title":"Formation of donor-specific antibodies depends on the epitope load of mismatched HLAs in lung transplant recipients: A retrospective single-center study.","author":"Lobashevsky","year":"2022","journal-title":"Clin Transplant."},{"key":"B167","doi-asserted-by":"publisher","first-page":"1592","DOI":"10.1002\/lt.26238","article-title":"Molecular mismatch predicts T cell-mediated rejection and de novo donor-specific antibody formation after living donor liver transplantation.","volume":"27","author":"Ono","year":"2021","journal-title":"Liver Transplant."},{"key":"B168","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2021.621138","article-title":"Clinical significance of shared T cell epitope analysis in early de novo donor-specific Anti-HLA antibody production after kidney transplantation and comparison with shared B cell Epitope Analysis.","volume":"12","author":"Tomosugi","year":"2021","journal-title":"Front Immunol."},{"key":"B169","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1007\/978-1-0716-0327-7_12","article-title":"The SysteMHC Atlas: A Computational pipeline, a website, and a data repository for immunopeptidomic analyses.","volume":"2120","author":"Shao","year":"2020","journal-title":"Methods Mol Biol."},{"key":"B170","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41586-022-04916-6","article-title":"Immune tolerance of food is mediated by layers of CD4+ T cell dysfunction.","volume":"6","author":"Hong","year":"2022","journal-title":"Nature."},{"key":"B171","doi-asserted-by":"publisher","DOI":"10.1126\/sciadv.abm7950","article-title":"In vivo mRNA delivery to virus-specific T cells by light-induced ligand exchange of MHC class I antigen-presenting nanoparticles.","volume":"8","author":"Su","year":"2022","journal-title":"Sci Adv."},{"key":"B172","doi-asserted-by":"publisher","first-page":"393","DOI":"10.1093\/bib\/bbz170","article-title":"Deep learning-based clustering approaches for bioinformatics.","volume":"22","author":"Karim","year":"2021","journal-title":"Brief Bioinform."},{"key":"B173","first-page":"2579","article-title":"Visualizing Data using t-SNE.","volume":"9","author":"van der Maaten","year":"2008","journal-title":"J Mach Learn Res."},{"key":"B174","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1802.03426","article-title":"UMAP: Uniform manifold approximation and projection for dimension reduction.","author":"McInnes","year":"2020","journal-title":"arXiv"},{"key":"B175","doi-asserted-by":"publisher","DOI":"10.3389\/fgene.2019.00995","article-title":"Microbiome multi-omics network analysis: statistical considerations, limitations, and opportunities.","volume":"10","author":"Jiang","year":"2019","journal-title":"Front Genet."},{"key":"B176","doi-asserted-by":"publisher","DOI":"10.1186\/s12711-016-0205-1","article-title":"Using biological networks to integrate, visualize and analyze genomics data.","volume":"48","author":"Charitou","year":"2016","journal-title":"Genet Sel Evol GSE."},{"key":"B177","doi-asserted-by":"publisher","DOI":"10.1093\/acprof:oso\/9780199206650.001.0001","author":"Newman","year":"2010","journal-title":"Networks: An Introduction."},{"key":"B178","doi-asserted-by":"publisher","first-page":"D1228","DOI":"10.1093\/nar\/gks1147","article-title":"InnateDB: systems biology of innate immunity and beyond\u2014recent updates and continuing curation.","volume":"41","author":"Breuer","year":"2013","journal-title":"Nucleic Acids Res."},{"key":"B179","doi-asserted-by":"publisher","first-page":"2498","DOI":"10.1101\/gr.1239303","article-title":"Cytoscape: a software environment for integrated models of biomolecular interaction networks.","volume":"13","author":"Shannon","year":"2003","journal-title":"Genome Res."},{"key":"B180","doi-asserted-by":"publisher","first-page":"8685","DOI":"10.1073\/pnas.0701361104","article-title":"The human disease network.","volume":"104","author":"Goh","year":"2007","journal-title":"Proc Natl Acad Sci."},{"key":"B181","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-020-14766-3","article-title":"Trajectory-based differential expression analysis for single-cell sequencing data.","volume":"11","author":"Van den Berge","year":"2020","journal-title":"Nat Commun."},{"key":"B182","doi-asserted-by":"publisher","first-page":"E6097","DOI":"10.1073\/pnas.1705065114","article-title":"Continuous immunotypes describe human immune variation and predict diverse responses.","volume":"114","author":"Kaczorowski","year":"2017","journal-title":"Proc Natl Acad Sci USA."},{"key":"B183","author":"Nazarov","year":"2022","journal-title":"Immunarch: Bioinformatics Analysis of T-Cell and B-Cell Immune Repertoires."},{"key":"B184","doi-asserted-by":"publisher","first-page":"2846","DOI":"10.1093\/bioinformatics\/bty203","article-title":"B-cell receptor reconstruction from single-cell RNA-seq with VDJPuzzle.","volume":"34","author":"Rizzetto","year":"2018","journal-title":"Bioinforma Oxf Engl."},{"key":"B185","doi-asserted-by":"publisher","DOI":"10.1186\/s12896-017-0379-9","article-title":"Overview of methodologies for T-cell receptor repertoire analysis.","volume":"17","author":"Rosati","year":"2017","journal-title":"BMC Biotechnol."},{"key":"B186","doi-asserted-by":"publisher","first-page":"2000","DOI":"10.1016\/j.csbj.2020.07.008","article-title":"Methods for sequence and structural analysis of B and T cell receptor repertoires.","volume":"18","author":"Teraguchi","year":"2020","journal-title":"Comput Struct Biotechnol J."},{"key":"B187","author":"Ellis","year":"2022","journal-title":"Flowcore: flowCore: Basic structures for flow cytometry data."},{"key":"B188","author":"Hammill","year":"2022","journal-title":"Interactive Analysis of Cytometry Data."},{"key":"B189","doi-asserted-by":"publisher","first-page":"636","DOI":"10.1002\/cyto.a.22625","article-title":"FlowSOM: Using self-organizing maps for visualization and interpretation of cytometry data.","volume":"87","author":"Van Gassen","year":"2015","journal-title":"Cytom Part J Int Soc Anal Cytol."},{"key":"B190","doi-asserted-by":"publisher","first-page":"449","DOI":"10.1038\/nri.2016.56","article-title":"Computational flow cytometry: helping to make sense of high-dimensional immunology data.","volume":"16","author":"Saeys","year":"2016","journal-title":"Nat Rev Immunol."},{"key":"B191","author":"Butler","year":"2022","journal-title":"Seurat: Tools for Single Cell Genomics."},{"key":"B192","doi-asserted-by":"publisher","first-page":"1179","DOI":"10.1093\/bioinformatics\/btw777","article-title":"Scater: pre-processing, quality control, normalization and visualization of single-cell RNA-seq data in R.","volume":"33","author":"McCarthy","year":"2017","journal-title":"Bioinformatics."},{"key":"B193","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41596-020-00409-w","article-title":"Tutorial: guidelines for the computational analysis of single-cell RNA sequencing data.","volume":"16","author":"Andrews","year":"2021","journal-title":"Nat Protoc."},{"key":"B194","doi-asserted-by":"publisher","DOI":"10.15252\/msb.20188746","article-title":"Current best practices in single-cell RNA-seq analysis: a tutorial.","volume":"15","author":"Luecken","year":"2019","journal-title":"Mol Syst Biol."},{"key":"B195","doi-asserted-by":"publisher","first-page":"824","DOI":"10.1101\/gr.213959.116","article-title":"metaSPAdes: a new versatile metagenomic assembler.","volume":"27","author":"Nurk","year":"2017","journal-title":"Genome Res."},{"key":"B196","doi-asserted-by":"publisher","DOI":"10.1186\/s13059-019-1891-0","article-title":"Improved metagenomic analysis with Kraken 2.","volume":"20","author":"Wood","year":"2019","journal-title":"Genome Biol."},{"key":"B197","year":"2022","journal-title":"Viral-ngs: genomic analysis pipelines for viral sequencing."},{"key":"B198","doi-asserted-by":"publisher","first-page":"833","DOI":"10.1038\/nbt.3935","article-title":"Shotgun metagenomics, from sampling to analysis.","volume":"35","author":"Quince","year":"2017","journal-title":"Nat Biotechnol."},{"key":"B199","doi-asserted-by":"publisher","DOI":"10.1016\/j.trre.2020.100533","article-title":"Critical evaluation of a possible role of HLA epitope matching in kidney transplantation.","volume":"34","author":"Kumru Sahin","year":"2020","journal-title":"Transplant Rev."},{"key":"B200","doi-asserted-by":"publisher","DOI":"10.1186\/s12864-018-4772-0","article-title":"Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics.","volume":"19","author":"Street","year":"2018","journal-title":"BMC Genomics."},{"key":"B201","doi-asserted-by":"crossref","DOI":"10.1126\/sciimmunol.aal2192","article-title":"Single-cell RNA-seq and computational analysis using temporal mixture modelling resolves Th1\/Tfh fate bifurcation in malaria.","volume":"2","author":"L\u00f6nnberg","year":"2017","journal-title":"Sci Immunol."},{"key":"B202","doi-asserted-by":"publisher","first-page":"547","DOI":"10.1038\/s41587-019-0071-9","article-title":"A comparison of single-cell trajectory inference methods.","volume":"37","author":"Saelens","year":"2019","journal-title":"Nat Biotechnol."},{"key":"B203","doi-asserted-by":"publisher","first-page":"W214","DOI":"10.1093\/nar\/gkq537","article-title":"The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function.","volume":"38","author":"Warde-Farley","year":"2010","journal-title":"Nucleic Acids Res."},{"key":"B204","doi-asserted-by":"publisher","first-page":"333","DOI":"10.1038\/nmeth.2810","article-title":"Similarity network fusion for aggregating data types on a genomic scale.","volume":"11","author":"Wang","year":"2014","journal-title":"Nat Methods."},{"key":"B205","year":"2022","journal-title":"Igraph: Network Analysis and Visualization."},{"key":"B206","author":"Mo","year":"2022","journal-title":"iClusterPlus: Integrative clustering of multi-type genomic data."},{"key":"B207","doi-asserted-by":"publisher","first-page":"i237","DOI":"10.1093\/bioinformatics\/btq182","article-title":"Inference of patient-specific pathway activities from multi-dimensional cancer genomics data using PARADIGM.","volume":"26","author":"Vaske","year":"2010","journal-title":"Bioinformatics."},{"key":"B208","doi-asserted-by":"publisher","DOI":"10.15252\/msb.20178124","article-title":"Multi-Omics Factor Analysis\u2014a framework for unsupervised integration of multi-omics data sets.","volume":"14","author":"Argelaguet","year":"2018","journal-title":"Mol Syst Biol."},{"key":"B209","doi-asserted-by":"publisher","DOI":"10.1038\/s41540-019-0099-y","article-title":"iOmicsPASS: network-based integration of multiomics data for predictive subnetwork discovery.","volume":"5","author":"Koh","year":"2019","journal-title":"NPJ Syst Biol Appl."},{"key":"B210","doi-asserted-by":"publisher","DOI":"10.3389\/fgene.2021.620453","article-title":"STATegra: Multi-Omics data integration \u2013 a conceptual scheme with a bioinformatics pipeline.","volume":"12","author":"Planell","year":"2021","journal-title":"Front Genet."},{"key":"B211","doi-asserted-by":"publisher","DOI":"10.1101\/122432","article-title":"xMWAS: an R package for data-driven integration and differential network analysis.","author":"Uppal","year":"","journal-title":"bioRxiv"},{"key":"B212","doi-asserted-by":"publisher","DOI":"10.1177\/1177932219899051","article-title":"Multi-omics data integration, interpretation, and its application.","volume":"14","author":"Subramanian","year":"2020","journal-title":"Bioinforma Biol Insights."},{"key":"B213","doi-asserted-by":"publisher","DOI":"10.1186\/s13059-015-0844-5","article-title":"MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data.","volume":"16","author":"Finak","year":"2015","journal-title":"Genome Biol."},{"key":"B214","author":"Smyth","year":"2022","journal-title":"Limma: Linear Models for Microarray Data."},{"key":"B215","author":"Love","year":"2022","journal-title":"DESeq2: Differential gene expression analysis based on the negative binomial distribution."},{"key":"B216","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0190152","article-title":"RNA-Seq differential expression analysis: An extended review and a software tool.","volume":"12","author":"Costa-Silva","year":"2017","journal-title":"PLoS One."},{"key":"B217","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2019.02159","article-title":"Framework for annotation of antigen specificities in high-throughput T-Cell repertoire sequencing studies.","volume":"10","author":"Pogorelyy","year":"2019","journal-title":"Front Immunol."}],"container-title":["Frontiers in Medicine"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fmed.2022.1070385\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,3,18]],"date-time":"2023-03-18T04:54:44Z","timestamp":1679115284000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fmed.2022.1070385\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,16]]},"references-count":217,"alternative-id":["10.3389\/fmed.2022.1070385"],"URL":"https:\/\/doi.org\/10.3389\/fmed.2022.1070385","relation":{},"ISSN":["2296-858X"],"issn-type":[{"value":"2296-858X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,12,16]]},"article-number":"1070385"}}