REVIEW article
Front. Immunol.
Sec. Systems Immunology
Volume 16 - 2025 | doi: 10.3389/fimmu.2025.1564248
This article is part of the Research TopicMulti-omics Assessment for the Discovery of Promising Novel Molecules in the Treatment of Transplant Organ InjuryView all 5 articles
Advanced Omics Approaches in Liver Transplant Settings: Current Applications and Future Prospectives
Provisionally accepted
- 1School of Medicine, Zhejiang Chinese Medical University, Hangzhou, China, Hangzhou, Jiangsu Province, China
- 2Key Laboratory of Artificial Organs and Computational Medicine in Zhejiang Province, Shulan International Medical College, Zhejiang Shuren University, Hangzhou, China
- 3Zhejiang Shuren University, Hangzhou, China
- 4Shulan Hangzhou Hospital, Hangzhou, Zhejiang Province, China
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Single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST), as advanced omics technologies, have addressed critical challenges in liver transplantation (LT), the most effective treatment for end-stage liver disease. This review aims to summarize the applications and future directions of scRNA-seq and ST in the context of LT. We highlight their role in uncovering immune cell heterogeneity and related injury mechanisms post-transplantation. From a clinician's perspective, we also outline potential future developments in the application of advanced omics in LT. Specifically, we focus on key immune cells involved in LT, with an emphasis on posttransplant immune responses and ischemia-reperfusion injury (IRI), as revealed by scRNA-seq and ST. Furthermore, we underscore the importance of multi-omics approaches and dynamic omics analyses in clinical LT research. With ongoing technological advancements, the integration of cutting-edge omics technologies and artificial intelligence (AI) holds great promise for advancing precision medicine in LT. Emphasis should be placed on the value of single-cell and spatial omics technologies in improving precision therapy and clinical management for LT patients.
Keywords: Liver Transplantation, single-cell sequencing, Spatial transcriptomics, Cell heterogeneity, Precision medicine AI, artificial intelligence, APCs, antigen-presenting cells, ACR, acute cellular rejection, AMR, acute antibody-mediated rejection
Received: 21 Jan 2025; Accepted: 23 May 2025.
Copyright: © 2025 Wang, Zhou, Yu, Liu and Zheng. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Zhengtao Liu, Zhejiang Shuren University, Hangzhou, China
Shusen Zheng, Shulan Hangzhou Hospital, Hangzhou, Zhejiang Province, China
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