On July 8, 2024, the research group led by Prof.Zemin Zhang from the Biomedical Pioneering Innovation Center (BIOPIC) at Peking University, in collaboration with the group led by Prof.AiwenWu from the Peking University Cancer Hospital, published a research paper entitled "Spatiotemporal single-cell analysis decodes cellular dynamics underlying different responses to immunotherapy in Colorectal Cancer" in Cancer Cell. This study dynamically tracked the spatiotemporal changes in the localtumor tissue and peripheral system of colorectal cancer (CRC) patients undergoing immunotherapy. By systematically identifying "cellular programs", the study revealed the synergistic evolution of various cell types in the tumor microenvironment (TME) during immunotherapy and further elucidated the critical role of the peripheral immune system in the efficacy of immunotherapy. A correlation between the baseline activation state of peripheral CD8+ T cells and patient outcomeswas established, offering new perspectives for understanding differential responses to immunotherapy.

　　In recent years, immune checkpoint blockade (ICB) has achieved remarkable success in cancer treatment, which could elicit an anti-tumor response centered on T cells1,2, accompanied by the remodeling of the TME3,4 and changes in systemic immunity5,6. In CRC,however, only a subset of patients could benefit from ICB, and the underlying cellular and molecular mechanisms remain elusive. A deeper understanding of the local and systemic dynamics is essential for propellingcurrent treatment strategies forward.

　　The research team conducted temporaltracking of 22 CRC patients undergoing neoadjuvant PD-1 blockade therapy, collecting a total of 169 samples spanning peripheral blood, tumors, and adjacent normal tissues. Using single-cell RNA sequencing (scRNA-seq) and single-cell TCR sequencing (scTCR-seq), the studyestablishedthe dynamic immune landscape of colorectal cancer under immunotherapy (Figure 1).

　　Figure 1. Study design

　　By dissecting the dynamic patterns of TME cells during treatment, the study identified three co-evolving cell programs closely related to treatment response: the TLS-like program, the tumor-enriched program, and the tissue-reconstruction program (Figure 2). Both responder groups showed enhanced TLS-associated signals during treatment. Additionally, the complete responders exhibited increased signals related to the tissue-reconstruction program, suggesting a trend towards normalized tissue structure. In contrast, partial responders displayed progressively stronger tumor-enriched signals, reflecting anti-tumor immune activation induced by ICB.

　　Notably, this study highlighted the prominent role of exhausted T cells in the cellular programs and identified the tumor-specific CD8+ T cell population (Ttr-like cells) via TCR tracking. Patients with higher baseline abundances of these cells generally exhibited better clinical outcomes. Further characterization of this population revealed that, after treatment, complete responders showed a decrease in terminally exhausted subpopulations (Text) and an accumulation of precursor-like subpopulations (Texp), whereas partial responders still showed a significant abundance of Text (Figure 2), indicating differential effects of PD-1 blockade on the exhaustion process of Ttr-like cells in different responders.

　　Moreover, this study focused on the involvement of peripheral circulation during the therapy process. TheTCR sharing analysis identified potentially recently recruited subpopulations (blood-associated Ttr-like cells) within the Ttr-like population. These cells were not fully exhausted and exhibited significant abundance differences between the two responder groups (Figure 2), suggesting their potential role in the anti-tumor response within the TME and their importance in immunotherapy.

　　Considering the close association between systemic immunity and the TME under immunotherapy, the differential expression analysis was conducted between the blood-enriched Ttr-like subpopulations and other circulatingCD8+ T cells. This analysisrevealed a set of MHC II-related signatures in circulating CD8+ T cells that could effectively predict therapeutic responses at baseline (Figure 2), providing new molecular markers for predicting the efficacy of PD-1 blockade.

　　Figure 2.Major findings

　　In summary, this study provided a high-resolution depiction of the cellular and molecular dynamics acrossdifferent response groups during neoadjuvant immunotherapy. The findings enhance the current understanding of TME and systemic immunity in CRC patients undergoing PD-1 blockade therapy, providing valuable data resources for subsequent research and offering new insights for optimizing treatment strategies.

　　Ph.D. candidateYuqingChen, Dr. DongfangWang, and Dr. Yingjie Li are co-first authors of this paper. Prof. ZeminZhang, Prof.Aiwen Wu, and Dr. Dongfang Wang are co-corresponding authors. The research was supported by the National Key Research and Development Program, the National Natural Science Foundation, the Beijing Municipal Science and Technology Commission, and the Beijing Hospital Clinical Medicine Development Administration.

　　Reference:

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　　Philip, M., and Schietinger, A. (2022). CD8+ T cell differentiation and dysfunction in cancer. Nature Reviews Immunology 22, 209–223.

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　　Cohen, M., Giladi, A., Barboy, O., Hamon, P., Li, B., Zada, M., Gurevich-Shapiro, A., Beccaria, C.G., David, E., Maier, B.B., et al. (2022). The interaction of CD4+ helper T cells with dendritic cells shapes the tumor microenvironment and immune checkpoint blockade response. Nature Cancer 3, 303–317.

　　Hiam-Galvez, K.J., Allen, B.M., and Spitzer, M.H. (2021). Systemic immunity in cancer. Nat Rev Cancer 21, 345–359.

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