Cancer immunotherapy is rapidly evolving, and its success fundamentally depends on the organization and dynamics of the tumor immune microenvironment. In this setting, cell–cell interactions that govern recognition, activation, suppression and antigen discrimination play a central role in shaping antitumor immunity, making their in situ characterization essential for advancing immunotherapeutic strategies. Our research uses chemical tools as the core engine to develop technologies that enable real-time and spatially resolved resolution of immune cell interactions directly within tumors. Through these approaches, we aim to elucidate how immune cells, particularly T cells, recognize antigens and engage in specific interaction events that shape immune outcomes. By integrating interaction mapping with molecular-level analysis, our goal is to monitor the overall T-cell response to antigen engagement and to identify high-quality antigen candidates that may serve as new tumor vaccine leads. Beyond the tumor setting, we also extend these methodologies to other T-cell–centric contexts, including autoimmune diseases, to explore how altered recognition and cellular interactions contribute to immune dysregulation. This direction provides a conceptual foundation for mechanistic insight that can guide the rational development of next-generation immunomodulatory therapies.
1）Tumor microenvironment dissection
Interactions and information transfer between different cells play key roles in numerous life activities including immune response, organ development, and neurotransmission. Currently, most methods to study cellular interactions require known cell types to be involved, making it difficult to discover or study unknown cellular interactions in complex living environments. To address this challenge, we has achieved in situ capture of dynamic interactions between cells with the help of "directed evolution" technology and "proximity labeling" strategy. This technique, named EXCELL (Enzyme-mediated proximal cell labeling), provides a powerful tool for studying cell-cell interactions by displaying the sorting enzyme (mgSrtA) that the authors have evolved in a targeted manner on the surface of the cells to be studied, allowing in situ capture and identification of the cells interacting with them. (JACS, 2019)
To further extend such interaction-capture technologies to primary cells and human samples, we subsequently developed a new generation of photocatalytic proximity-labeling tools based on the small-molecule chromophore DBF (dibromofluorescein), an iridium(III) photocatalyst or enzymes. These systems enable spatiotemporally controlled and quantitatively interpretable labeling of interacting cells within complex biological environments. Using these photocatalytic CCI platforms, we can successfully capture antigen-specific T cells during their interactions with dendritic cells, identify tumor-reactive T cells that genuinely recognize endogenous tumor antigens within the tumor microenvironment and analyze how natural killer cells engage and recognize tumor cells. Together, these advances provide a versatile strategy for resolving immune cell interactions in physiologically and clinically relevant settings. (JACS, 2022; JACS, 2024)
2）Antigen Discovery
T-cell recognition provides a direct window into the antigens that shape immunity in cancer and autoimmune diseases. Building on our current CCI platforms and with the intention to develop next-generation chemical technologies, we aim to use T-cell engagement as the central readout for antigen discovery. First, these approaches allow us to identify the antigens that T cells naturally recognize during immune surveillance or antitumor responses. Second, by quantitatively assessing the quality of these antigens through T-cell functional and interaction signatures, we seek to pinpoint high-quality candidates with the potential to serve as effective cancer vaccine leads. Third, we will extend this strategy to autoimmune settings, where many pathogenic antigens, including those bearing disease-relevant post-translational modifications, remain undefined. Through this integrated framework, our goal is to establish a T-cell–centric route to discovering and prioritizing antigen candidates with translational relevance across disease contexts.
Representative publications：
1. Zhang, Y.; Liu, S.; Guo, F.; Qin, S.; Zhou, N.; Liu, Z.; Fan, X.; Chen P* Bioorthogonal Quinone Methide Decaging Enables Live-Cell Quantification of Tumor-Specific Immune Interactions. J. Am. Chem. Soc. 2024, 146 (22), 15186–15197.
2. Liu, H.; Luo, H.; Xue, Q.; Qin, S.; Qiu, S.; Liu, S.; Lin, J.; Li, J. P.; Chen P*, Antigen-Specific T Cell Detection via Photocatalytic Proximity Cell Labeling (PhoXCELL). J. Am. Chem. Soc. 2022, 144, 5517-5526
3. Ge, Y.; Chen, L.; Liu, S.; Zhao, J.; Zhang, H.; Chen P*., Enzyme-Mediated Intercellular Proximity Labeling for Detecting Cell–Cell Interactions. J. Am. Chem. Soc. 2019, 141 (5), 1833-1837.
4. Wang, R.#, Fang, Y.#, Hu, Y., Liu, Y.*, Chen P.*, Zou, P.* . Bioluminescence-activated proximity labeling for spatial multi-omics. Chem 2025, 11, 102595.
