Identifying T-cell clubs by embracing the local harmony between TCR and gene expressions

Yiping Zou (Co-first Author), Jiaqi Luo (Co-first Author), Lingxi Chen, Xueying Wang, Wei Liu, Ruo Han Wang, Shuai Cheng Li*

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Abstract

T cell receptors (TCR) and gene expression provide two complementary and essential aspects in T cell understanding, yet their diversity presents challenges in integrative analysis. We introduce TCRclub, a novel method integrating single-cell RNA sequencing data and single-cell TCR sequencing data using local harmony to identify functionally similar T cell groups, termed ‘clubs’. We applied TCRclub to 298,106 T cells across seven datasets encompassing various diseases. First, TCRclub outperforms the state-of-the-art methods in clustering T cells on a dataset with over 400 verified peptide-major histocompatibility complex categories. Second, TCRclub reveals a transition from activated to exhausted T cells in cholangiocarcinoma patients. Third, TCRclub discovered the pathways that could intervene in response to anti-PD-1 therapy for patients with basal cell carcinoma by analyzing the pre-treatment and post-treatment samples. Furthermore, TCRclub unveiled different T-cell responses and gene patterns at different severity levels in patients with COVID-19. Hence, TCRclub aids in developing more effective immunotherapeutic strategies for cancer and infectious diseases. © The Author(s) 2024.
Original languageEnglish
Pages (from-to)1329-1345
JournalMolecular Systems Biology
Volume20
Issue number12
Online published4 Nov 2024
DOIs
Publication statusPublished - Dec 2024

Research Keywords

  • Integration
  • Local Harmony
  • Single-Cell Analysis
  • T-Cell Clustering

Publisher's Copyright Statement

  • This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

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