High-throughput screening of functional neo-antigens and their specific TCRs via the Jurkat reporter system combined with droplet microfluidics
Summary T-cell receptor (TCR)-engineered T cells can precisely recognize a broad repertoire of targets derived from both intracellular and surface proteins of tumor cells. TCR-T adoptive cell therapy has shown safety and promising efficacy in solid tumor immunotherapy. However, antigen-specific functional TCR screening is time-consuming and expensive, which limits its application clinically. Here, we developed a novel integrated antigen-TCR screening platform based on droplet microfluidics technology, enabling high-throughput peptide-major histocompatibility complex (pMHC) library-to-TCR library screening with high sensitivity and low background signal. We introduced DNA barcoding technology to label peptide antigen candidate-loaded antigen-presenting cells (APCs) and Jurkat reporter cells to check the specificity of pMHC-TCR candidates. Coupled with the next-generation sequencing pipeline, interpretation of the DNA barcodes and the gene expression level of the Jurkat T-cell activation pathway provided a clear peptide-MHC-TCR recognition relationship. Our proof-of-principle study demonstrates that the platform could achieve unbiased pMHC-TCR library-on-library screening, which is expected to be used in the cross-reactivity and off-target testing of candidate pMHC-TCR libraries in clinical applications..
Medienart: |
Preprint |
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Erscheinungsjahr: |
2023 |
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Erschienen: |
2023 |
Enthalten in: |
bioRxiv.org - (2023) vom: 23. Feb. Zur Gesamtaufnahme - year:2023 |
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Sprache: |
Englisch |
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Beteiligte Personen: |
Li, Yijian [VerfasserIn] |
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Links: |
Volltext [kostenfrei] |
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Themen: |
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doi: |
10.1101/2023.02.20.529171 |
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funding: |
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Förderinstitution / Projekttitel: |
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PPN (Katalog-ID): |
XBI038751933 |
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520 | |a Summary T-cell receptor (TCR)-engineered T cells can precisely recognize a broad repertoire of targets derived from both intracellular and surface proteins of tumor cells. TCR-T adoptive cell therapy has shown safety and promising efficacy in solid tumor immunotherapy. However, antigen-specific functional TCR screening is time-consuming and expensive, which limits its application clinically. Here, we developed a novel integrated antigen-TCR screening platform based on droplet microfluidics technology, enabling high-throughput peptide-major histocompatibility complex (pMHC) library-to-TCR library screening with high sensitivity and low background signal. We introduced DNA barcoding technology to label peptide antigen candidate-loaded antigen-presenting cells (APCs) and Jurkat reporter cells to check the specificity of pMHC-TCR candidates. Coupled with the next-generation sequencing pipeline, interpretation of the DNA barcodes and the gene expression level of the Jurkat T-cell activation pathway provided a clear peptide-MHC-TCR recognition relationship. Our proof-of-principle study demonstrates that the platform could achieve unbiased pMHC-TCR library-on-library screening, which is expected to be used in the cross-reactivity and off-target testing of candidate pMHC-TCR libraries in clinical applications. | ||
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700 | 1 | |a Qi, Jingyu |4 aut | |
700 | 1 | |a Liu, Yang |4 aut | |
700 | 1 | |a Zheng, Yuyu |4 aut | |
700 | 1 | |a Zhu, Haibin |4 aut | |
700 | 1 | |a Zang, Yupeng |4 aut | |
700 | 1 | |a Guan, Xiangyu |4 aut | |
700 | 1 | |a Xie, Sichong |4 aut | |
700 | 1 | |a Zhao, Hongyan |4 aut | |
700 | 1 | |a Fu, Yunyun |4 aut | |
700 | 1 | |a Xiang, Haitao |4 aut | |
700 | 1 | |a Zhang, Weicong |4 aut | |
700 | 1 | |a Chen, Huanyi |4 aut | |
700 | 1 | |a Liu, Huan |4 aut | |
700 | 1 | |a Zhao, Yuntong |4 aut | |
700 | 1 | |a Feng, Yu |4 aut | |
700 | 1 | |a Bu, Fanyu |4 aut | |
700 | 1 | |a Liang, Yanling |4 aut | |
700 | 1 | |a Li, Yang |4 aut | |
700 | 1 | |a Xu, Qumiao |4 aut | |
700 | 1 | |a He, Ying |4 aut | |
700 | 1 | |a Sun, Li |4 aut | |
700 | 1 | |a Liu, Longqi |4 aut | |
700 | 1 | |a Gu, Ying |4 aut | |
700 | 1 | |a Xu, Xun |4 aut | |
700 | 1 | |a Hou, Yong |0 (orcid)0000-0001-7822-0570 |4 aut | |
700 | 1 | |a Dong, Xuan |4 aut | |
700 | 1 | |a Liu, Ya |4 aut | |
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