Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

Emerging approaches and technologies in transplantation: the potential game changers

Abstract

Newly emerging technologies are rapidly changing conventional approaches to organ transplantation. In the modern era, the key challenges to transplantation include (1) how to best individualize and possibly eliminate the need for life-long immunosuppression and (2) how to expand the donor pool suitable for human transplantation. This article aims to provide readers with an updated review of three new technologies that address these challenges. First, single-cell RNA sequencing technology is rapidly evolving and has recently been employed in settings related to transplantation. The new sequencing data indicate an unprecedented cellular heterogeneity within organ transplants, as well as exciting new molecular signatures involved in alloimmune responses. Second, sophisticated nanotechnology platforms provide a means of therapeutically delivering immune modulating reagents to promote transplant tolerance. Tolerogenic nanoparticles with regulatory molecules and donor antigens are capable of targeting host immune responses with tremendous precision, which, in some cases, results in donor-specific tolerance. Third, CRISPR/Cas9 gene editing technology has the potential to precisely remove immunogenic molecules while inserting desirable regulatory molecules. This technology is particularly useful in generating genetically modified pigs for xenotransplantation to solve the issue of the shortage of human organs. Collectively, these new technologies are positioning the transplant community for major breakthroughs that will significantly advance transplant medicine.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Wu, H., Kirita, Y., Donnelly, E. L. & Humphreys, B. D. Advantages of single-nucleus over single-cell RNA sequencing of adult kidney: Rare cell types and novel cell states revealed in fibrosis. J. Am. Soc. Nephrol. 30, 23–32 (2019).

    Article  PubMed  CAS  Google Scholar 

  2. Naeimi Kararoudi, M. et al. Clustered regularly interspaced short palindromic repeats/Cas9 gene editing technique in xenotransplantation. Front. Immunol. 9, 1711 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  3. Tasciotti, E. et al. The emerging role of nanotechnology in cell and organ transplantation. Transplantation 100, 1629–1638 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Wang, J. & Song, Y. Single cell sequencing: a distinct new field. Clin. Transl. Med. 6, 10 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Kitchens, W. H. & Adams, A. B. Nonhuman primate models of transplant tolerance: closer to the holy grail. Curr. Opin. Organ Transplant. 21, 59–65 (2016).

    Article  CAS  PubMed  Google Scholar 

  6. Xie, J., Lee, S. & Chen, X. Nanoparticle-based theranostic agents. Adv. Drug Deliv. Rev. 62, 1064–1079 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Chopra, B. & Sureshkumar, K. K. Changing organ allocation policy for kidney transplantation in the United States. World J. Transplant. 5, 38–43 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  8. Meier, R. P. H. et al. Xenotransplantation: back to the future? Transpl. Int. 31, 465–477 (2018).

    Article  PubMed  Google Scholar 

  9. Altschuler, S. J. & Wu, L. F. Cellular heterogeneity: do differences make a difference? Cell 141, 559–563 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Wu, H. & Humphreys, B. D. The promise of single-cell RNA sequencing for kidney disease investigation. Kidney Int. 92, 1334–1342 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Villani, A. C., et al. Single-cell RNA-seq reveals new types of human blood dendritic cells, monocytes, and progenitors. Science. 2017; 356. https://doi.org/10.1126/science.aah4573.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  12. Shalek, A. K. et al. Single-cell RNA-seq reveals dynamic paracrine control of cellular variation. Nature 510, 363–369 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Chu, L. F. et al. Single-cell RNA-seq reveals novel regulators of human embryonic stem cell differentiation to definitive endoderm. Genome Biol. 17, 173 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  14. Lambrechts, D. et al. Phenotype molding of stromal cells in the lung tumor microenvironment. Nat. Med. 24, 1277–1289 (2018).

    Article  CAS  PubMed  Google Scholar 

  15. Lee, M. C. et al. Single-cell analyses of transcriptional heterogeneity during drug tolerance transition in cancer cells by RNA sequencing. Proc. Natl Acad. Sci. USA 111, E4726–E4735 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Sun, Z. et al. Single-cell RNA sequencing reveals gene expression signatures of breast cancer-associated endothelial cells. Oncotarget 9, 10945–10961 (2018).

    Article  PubMed  Google Scholar 

  17. Zhao, T. et al. Single-cell RNA-seq reveals dynamic early embryonic-like programs during chemical reprogramming. Cell Stem Cell 23, 31–45.e7 (2018).

    Article  CAS  PubMed  Google Scholar 

  18. Tang, F. et al. mRNA-Seq whole-transcriptome analysis of a single cell. Nat. Methods 6, 377–382 (2009).

    Article  CAS  PubMed  Google Scholar 

  19. Tung, P. Y. et al. Batch effects and the effective design of single-cell gene expression studies. Sci. Rep. 7, 39921 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Wang, Y. & Navin, N. E. Advances and applications of single-cell sequencing technologies. Mol. Cell 58, 598–609 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Islam, S. et al. Characterization of the single-cell transcriptional landscape by highly multiplex RNA-seq. Genome Res. 21, 1160–1167 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Klein, A. M. et al. Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell 161, 1187–1201 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Macosko, E. Z. et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161, 1202–1214 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Islam, S. et al. Quantitative single-cell RNA-seq with unique molecular identifiers. Nat. Methods 11, 163–166 (2014).

    Article  CAS  PubMed  Google Scholar 

  25. Pierson, E. & Yau, C. ZIFA: Dimensionality reduction for zero-inflated single-cell gene expression analysis. Genome Biol. 16, 241 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  26. Wang, Y. J. et al. Single-cell transcriptomics of the human endocrine pancreas. Diabetes 65, 3028–3038 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Xu, C. & Su, Z. Identification of cell types from single-cell transcriptomes using a novel clustering method. Bioinformatics 31, 1974–1980 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Bendall, S. C. et al. Single-cell trajectory detection uncovers progression and regulatory coordination in human B cell development. Cell 157, 714–725 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Setty, M. et al. Wishbone identifies bifurcating developmental trajectories from single-cell data. Nat. Biotechnol. 34, 637–645 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Trapnell, C. et al. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nat. Biotechnol. 32, 381–386 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Park, J. et al. Single-cell transcriptomics of the mouse kidney reveals potential cellular targets of kidney disease. Science 360, 758–763 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Wu, H. et al. Single-cell transcriptomics of a human kidney allograft biopsy specimen defines a diverse inflammatory response. J. Am. Soc. Nephrol. 29, 2069–2080 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Gladka, M. M. et al. Single-cell sequencing of the healthy and diseased heart reveals cytoskeleton-associated protein 4 as a new modulator of fibroblasts activation. Circulation 138, 166–180 (2018).

    Article  CAS  PubMed  Google Scholar 

  34. Dick, S. A. et al. Self-renewing resident cardiac macrophages limit adverse remodeling following myocardial infarction. Nat. Immunol. 20, 29–39 (2019).

    Article  CAS  PubMed  Google Scholar 

  35. Deng, Q., Ramskold, D., Reinius, B. & Sandberg, R. Single-cell RNA-seq reveals dynamic, random monoallelic gene expression in mammalian cells. Science 343, 193–196 (2014).

    Article  CAS  PubMed  Google Scholar 

  36. Miyamoto, D. T. et al. RNA-Seq of single prostate CTCs implicates noncanonical Wnt signaling in antiandrogen resistance. Science 349, 1351–1356 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Ross, I. L., Browne, C. M. & Hume, D. A. Transcription of individual genes in eukaryotic cells occurs randomly and infrequently. Immunol. Cell Biol. 72, 177–185 (1994).

    Article  CAS  PubMed  Google Scholar 

  38. Svensson, V. et al. Power analysis of single-cell RNA-sequencing experiments. Nat. Methods 14, 381–387 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Soares, S., Sousa, J., Pais, A. & Vitorino, C. Nanomedicine: Principles, properties, and regulatory issues. Front. Chem. 6, 360 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  40. Pober, J. S. & Tellides, G. Participation of blood vessel cells in human adaptive immune responses. Trends Immunol. 33, 49–57 (2012).

    Article  CAS  PubMed  Google Scholar 

  41. Piotti, G., Palmisano, A., Maggiore, U. & Buzio, C. Vascular endothelium as a target of immune response in renal transplant rejection. Front. Immunol. 5, 505 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. van Buul, J. D. et al. ICAM-1 clustering on endothelial cells recruits VCAM-1. J. Biomed. Biotechnol. 2010, 120328 (2010).

    PubMed  PubMed Central  Google Scholar 

  43. Tietjen, G. T., Bracaglia, L. G., Saltzman, W. M. & Pober, J. S. Focus on fundamentals: Achieving effective nanoparticle targeting. Trends Mol. Med. 24, 598–606 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Glotz, D., Lucchiari, N., Pegaz-Fiornet, B. & Suberbielle-Boissel, C. Endothelial cells as targets of allograft rejection. Transplantation 82, S19–S21 (2006).

    Article  PubMed  Google Scholar 

  45. Al-Lamki, R. S., Bradley, J. R. & Pober, J. S. Endothelial cells in allograft rejection. Transplantation 86, 1340–1348 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Muro, S. et al. Endothelial targeting of high-affinity multivalent polymer nanocarriers directed to intercellular adhesion molecule 1. J. Pharmacol. Exp. Ther. 317, 1161–1169 (2006).

    Article  CAS  PubMed  Google Scholar 

  47. Cui, J. et al. Ex vivo pretreatment of human vessels with siRNA nanoparticles provides protein silencing in endothelial cells. Nat. Commun. 8, 191 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  48. Tietjen, G. T. et al. Nanoparticle targeting to the endothelium during normothermic machine perfusion of human kidneys. Sci. Transl. Med. 9 (2017). https://doi.org/10.1126/scitranslmed.aam6764.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  49. Zhu, P. et al. Organ preservation with targeted rapamycin nanoparticles: a pre-treatment strategy preventing chronic rejection in vivo. RSC Adv. 8, 25909–25919 (2018).

    Article  CAS  PubMed  Google Scholar 

  50. Schroeder, R. A., Marroquin, C. E. & Kuo, P. C. Tolerance and the “Holy Grail” of transplantation. J. Surg. Res. 111, 109–119 (2003).

    Article  CAS  PubMed  Google Scholar 

  51. Kishimoto, T. K. & Maldonado, R. A. Nanoparticles for the induction of antigen-specific immunological tolerance. Front. Immunol. 9, 230 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  52. Steinman, R. M. & Hemmi, H. Dendritic cells: translating innate to adaptive immunity. Curr. Top. Microbiol. Immunol. 311, 17–58 (2006).

    CAS  PubMed  Google Scholar 

  53. Zhang, A. H., Rossi, R. J., Yoon, J., Wang, H. & Scott, D. W. Tolerogenic nanoparticles to induce immunologic tolerance: Prevention and reversal of FVIII inhibitor formation. Cell. Immunol. 301, 74–81 (2016).

    Article  CAS  PubMed  Google Scholar 

  54. Pang, L., Macauley, M. S., Arlian, B. M., Nycholat, C. M. & Paulson, J. C. Encapsulating an immunosuppressant enhances tolerance induction by siglec-engaging tolerogenic liposomes. Chembiochem 18, 1226–1233 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Stead, S. O. et al. Murine and non-human primate dendritic cell targeting nanoparticles for in vivo generation of regulatory T-cells. ACS Nano 12, 6637–6647 (2018).

    Article  CAS  PubMed  Google Scholar 

  56. Bryant, J. et al. Nanoparticle delivery of donor antigens for transplant tolerance in allogeneic islet transplantation. Biomaterials 35, 8887–8894 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Shahzad, K. A. et al. On-target and direct modulation of alloreactive T cells by a nanoparticle carrying MHC alloantigen, regulatory molecules and CD47 in a murine model of alloskin transplantation. Drug Deliv. 25, 703–715 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Leventhal, J. et al. Chimerism and tolerance without GVHD or engraftment syndrome in HLA-mismatched combined kidney and hematopoietic stem cell transplantation. Sci. Transl. Med. 4, 124ra28 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  59. Scandling, J. D. et al. Tolerance and chimerism after renal and hematopoietic-cell transplantation. N. Engl. J. Med. 358, 362–368 (2008).

    Article  CAS  PubMed  Google Scholar 

  60. Kawai, T. et al. HLA-mismatched renal transplantation without maintenance immunosuppression. N. Engl. J. Med. 358, 353–361 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Hlavaty, K. A. et al. Tolerance induction using nanoparticles bearing HY peptides in bone marrow transplantation. Biomaterials 76, 1–10 (2016).

    Article  CAS  PubMed  Google Scholar 

  62. Braza, M. S. et al. Inhibiting inflammation with myeloid cell-specific nanobiologics promotes organ transplant acceptance. Immunity 49, 819–28.e6 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Dangi, A., Yu, S. & Luo, X. Apoptotic cell-based therapies for promoting transplantation tolerance. Curr. Opin. Organ Transplant. 23, 552–558 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  64. Jinek, M. et al. A programmable dual-RNA-guided DNA endonuclease in adaptive bacterial immunity. Science 337, 816–821 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Lander, N., Chiurillo, M. A. & Docampo, R. Genome editing by CRISPR/Cas9: A game change in the genetic manipulation of protists. J. Eukaryot. Microbiol. 63, 679–690 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Doudna, J. A. & Charpentier, E. Genome editing. The new frontier of genome engineering with CRISPR-Cas9. Science 346, 1258096 (2014).

    Article  CAS  PubMed  Google Scholar 

  67. Cowan, P. J. & Tector, A. J. The resurgence of xenotransplantation. Am. J. Transplant. 17, 2531–2536 (2017).

    Article  CAS  PubMed  Google Scholar 

  68. Denner, J. Paving the path toward porcine organs for transplantation. N. Engl. J. Med. 377, 1891–1893 (2017).

    Article  PubMed  Google Scholar 

  69. Fung, R. K. & Kerridge, I. H. Gene editing advance re-ignites debate on the merits and risks of animal to human transplantation. Intern. Med. J. 46, 1017–1022 (2016).

    Article  CAS  PubMed  Google Scholar 

  70. Niu, D. et al. Inactivation of porcine endogenous retrovirus in pigs using CRISPR-Cas9. Science 357, 1303–1307 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Salomon, D. R. A CRISPR way to block PERVs--engineering organs for transplantation. N. Engl. J. Med. 374, 1089–1091 (2016).

    Article  CAS  PubMed  Google Scholar 

  72. Shrock, E. & Guell, M. CRISPR in animals and animal models. Prog. Mol. Biol. Transl. Sci. 152, 95–114 (2017).

    Article  PubMed  CAS  Google Scholar 

  73. Wiedenheft, B., Sternberg, S. H. & Doudna, J. A. RNA-guided genetic silencing systems in bacteria and archaea. Nature 482, 331–338 (2012).

    Article  CAS  PubMed  Google Scholar 

  74. Lau, R. W., Wang, B. & Ricardo, S. D. Gene editing of stem cells for kidney disease modelling and therapeutic intervention. Nephrology 23, 981–990 (2018).

    Article  PubMed  Google Scholar 

  75. Cruz, N. M. & Freedman, B. S. CRISPR gene editing in the kidney. Am. J. Kidney Dis. 71, 874–883 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Cong, L. et al. Multiplex genome engineering using CRISPR/Cas systems. Science 339, 819–823 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Guo, T. et al. Harnessing accurate non-homologous end joining for efficient precise deletion in CRISPR/Cas9-mediated genome editing. Genome Biol. 19, 170 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  78. Estrada, J. L. et al. Evaluation of human and non-human primate antibody binding to pig cells lacking GGTA1/CMAH/beta4GalNT2 genes. Xenotransplantation 22, 194–202 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  79. Petersen, B. et al. Efficient production of biallelic GGTA1 knockout pigs by cytoplasmic microinjection of CRISPR/Cas9 into zygotes. Xenotransplantation 23, 338–346 (2016).

    Article  PubMed  Google Scholar 

  80. Fischer, K., Kind, A. & Schnieke, A. Assembling multiple xenoprotective transgenes in pigs. Xenotransplantation 25, e12431 (2018).

    Article  PubMed  Google Scholar 

  81. Lambrigts, D., Sachs, D. H. & Cooper, D. K. Discordant organ xenotransplantation in primates: world experience and current status. Transplantation 66, 547–561 (1998).

    Article  CAS  PubMed  Google Scholar 

  82. Fischer, K. et al. Efficient production of multi-modified pigs for xenotransplantation by ‘combineering’, gene stacking and gene editing. Sci. Rep. 6, 29081 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Byrne, G. W., McGregor, C. G. A. & Breimer, M. E. Recent investigations into pig antigen and anti-pig antibody expression. Int. J. Surg. 23, 223–228 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  84. Sato, M. et al. The combinational use of CRISPR/Cas9-based gene editing and targeted toxin technology enables efficient biallelic knockout of the alpha-1,3-galactosyltransferase gene in porcine embryonic fibroblasts. Xenotransplantation 21, 291–300 (2014).

    Article  PubMed  Google Scholar 

  85. Gao, H. et al. Production of alpha1,3-galactosyltransferase and cytidine monophosphate-N-acetylneuraminic acid hydroxylase gene double-deficient pigs by CRISPR/Cas9 and handmade cloning. J. Rreprod. Dev. 63, 17–26 (2017).

    Article  CAS  Google Scholar 

  86. Zhang, R. et al. Reducing immunoreactivity of porcine bioprosthetic heart valves by genetically-deleting three major glycan antigens, GGTA1/beta4GalNT2/CMAH. Acta Biomater. 72, 196–205 (2018).

    Article  CAS  PubMed  Google Scholar 

  87. Adams, A. B. et al. Xenoantigen deletion and chemical immunosuppression can prolong renal xenograft survival. Ann. Surg. 268, 564–573 (2018).

    Article  PubMed  Google Scholar 

  88. Reyes, L. M. et al. Creating class I MHC-null pigs using guide RNA and the Cas9 endonuclease. J. Immunol. 193, 5751–5757 (2014).

    Article  CAS  PubMed  Google Scholar 

  89. Kemter, E., Denner, J. & Wolf, E. Will genetic engineering carry xenotransplantation of pig islets to the clinic? Curr. Diab. Rep. 18, 103 (2018).

    Article  PubMed  CAS  Google Scholar 

  90. Martens, G. R. et al. Humoral reactivity of renal transplant-waitlisted patients to cells from GGTA1/CMAH/B4GalNT2, and SLA class I knockout pigs. Transplantation 101, e86–e92 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Hara, H. et al. Human dominant-negative class II transactivator transgenic pigs—effect on the human anti-pig T-cell immune response and immune status. Immunology 140, 39–46 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Zhang, W. et al. Generation of complement protein C3 deficient pigs by CRISPR/Cas9-mediated gene targeting. Sci. Rep. 7, 5009 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  93. Iwase, H. et al. Immunological and physiological observations in baboons with life-supporting genetically engineered pig kidney grafts. Xenotransplantation. 24 (2017). https://doi.org/10.1111/xen.12293.

    Article  Google Scholar 

  94. Mohiuddin, M. M. et al. Chimeric 2C10R4 anti-CD40 antibody therapy is critical for long-term survival of GTKO.hCD46.hTBM pig-to-primate cardiac xenograft. Nat. Commun. 7, 11138 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Denner, J. How active are porcine endogenous retroviruses (PERVs)? Viruses 8 (2016). https://doi.org/10.3390/v8080215.

    Article  PubMed Central  CAS  Google Scholar 

  96. Ross, M. J. & Coates, P. T. Using CRISPR to inactivate endogenous retroviruses in pigs: an important step toward safe xenotransplantation? Kidney Int. 93, 4–6 (2018).

    Article  CAS  PubMed  Google Scholar 

  97. Patience, C., Takeuchi, Y. & Weiss, R. A. Infection of human cells by an endogenous retrovirus of pigs. Nat. Med. 3, 282–286 (1997).

    Article  CAS  PubMed  Google Scholar 

  98. Yang, L. et al. Genome-wide inactivation of porcine endogenous retroviruses (PERVs). Science 350, 1101–1104 (2015).

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

This work was supported by grants from the National Institutes of Health (R01 EB009910) (A.D. and X.L.) and the Chinese Scholarship Council (S.Y.).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xunrong Luo.

Ethics declarations

Competing interests

The authors declare no competing interests.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dangi, A., Yu, S. & Luo, X. Emerging approaches and technologies in transplantation: the potential game changers. Cell Mol Immunol 16, 334–342 (2019). https://doi.org/10.1038/s41423-019-0207-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41423-019-0207-3

Keywords

This article is cited by

Search

Quick links