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Spatial proteomic profiling elucidates immune determinants of neoadjuvant chemo-immunotherapy in esophageal squamous cell carcinoma

Oncogene volume 43, pages 2751–2767 (2024)Cite this article

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Abstract

Esophageal squamous cell carcinoma (ESCC) presents significant clinical and therapeutic challenges due to its aggressive nature and generally poor prognosis. We initiated a Phase II clinical trial (ChiCTR1900027160) to assess the efficacy of a pioneering neoadjuvant chemo-immunotherapy regimen comprising programmed death-1 (PD-1) blockade (Toripalimab), nanoparticle albumin-bound paclitaxel (nab-paclitaxel), and the oral fluoropyrimidine derivative S-1, in patients with locally advanced ESCC. This study uniquely integrates clinical outcomes with advanced spatial proteomic profiling using Imaging Mass Cytometry (IMC) to elucidate the dynamics within the tumor microenvironment (TME), focusing on the mechanistic interplay of resistance and response. Sixty patients participated, receiving the combination therapy prior to surgical resection. Our findings demonstrated a major pathological response (MPR) in 62% of patients and a pathological complete response (pCR) in 29%. The IMC analysis provided a detailed regional assessment, revealing that the spatial arrangement of immune cells, particularly CD8+ T cells and B cells within tertiary lymphoid structures (TLS), and S100A9+ inflammatory macrophages in fibrotic regions are predictive of therapeutic outcomes. Employing machine learning approaches, such as support vector machine (SVM) and random forest (RF) analysis, we identified critical spatial features linked to drug resistance and developed predictive models for drug response, achieving an area under the curve (AUC) of 97%. These insights underscore the vital role of integrating spatial proteomics into clinical trials to dissect TME dynamics thoroughly, paving the way for personalized and precise cancer treatment strategies in ESCC. This holistic approach not only enhances our understanding of the mechanistic basis behind drug resistance but also sets a robust foundation for optimizing therapeutic interventions in ESCC.

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Fig. 1: Neoadjuvant chemo-immunotherapy in esophageal squamous cell carcinoma clinical trial.
Fig. 2: Single-cell resolution of the ESCC microenvironment by IMC reveals spatial features related to neoadjuvant therapy response.
Fig. 3: Spatial and functional characteristics of TLS and their milieu in response to chemo-immunotherapy.
Fig. 4: Spatial and functional analysis of TME regions in response to therapy.
Fig. 5: Analysis of cell–cell interactions and their correlation with clinical outcomes.
Fig. 6: Analysis of spatial features for predicting treatment response using machine learning.

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Data availability

The IMC data can be accessed via OMIX/OMIX006370.

Code availability

Please note that the IMC analysis in this study does not involve the original code. To access the original codes used, please refer to the “Methods” section and the respective references provided. If you require any additional information to reanalyze the data presented in this paper, please contact the corresponding author directly.

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Funding

This work was supported by the National Key Research and Development Program of China (grant 2019YFA0803000 to JS), the Excellent Youth Foundation of Zhejiang Scientific (grant R22H1610037 to JS), the National Natural Science Foundation of China (grant 82173078 to JS), the Natural Science Foundation of Zhejiang Province (grant 2022C03037 to JS). Supported by the Henan Provincial Department of Science and Technology, No. 212102310047. Supported by the Henan Provincial Health Commission, No. SBGJ202003005.

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Author notes

  1. These authors contributed equally: Chao Wu, Guoqing Zhang, Lin Wang, Jinlong Hu.

Authors and Affiliations

  1. Department of Medical Oncology, Senior Department of Oncology, Chinese PLA General Hospital, The Fifth Medical Center, Beijing, China

    Chao Wu, Guoqing Zhang, Haitao Tao & Yi Hu

  2. College of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing, China

    Lin Wang & Jianpeng Sheng

  3. Department of Oncology, Henan Provincial People’s Hospital, People’s Hospital of Zhengzhou University, Zhengzhou, China

    Jinlong Hu

  4. Department of Radiation Oncology, Chinese PLA General Hospital, The First Medical Center, Beijing, China

    Zhongjian Ju

  5. The Shapingba Affiliated Hospital, Chongqing University, Chongqing, China

    Qing Li

  6. Chengdu Medical College, Chengdu, China

    Jian Li

  7. Department of Medical Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China

    Wei Zhang

  8. Chinese Institutes for Medical Research, Beijing, China

    Jianpeng Sheng

  9. Department of Thoracic Surgery, Chinese PLA General Hospital, The First Medical Center, Beijing, China

    Xiaobin Hou

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Contributions

CW and GZ conceptualized the study, designed the experiments, and drafted the manuscript. LW conducted data analysis and figure preparation. All three authors contributed equally to this work. ZJ and HT performed the experimental work. QL and JL performed the RF analysis. YH and XH organized the clinical trial and obtained the clinical samples. GZ assisted in coordinating the clinical trials. WZ and JS contributed to proofreading the manuscript and reviewed the manuscript. YH and XH supervised the project. JH helped with the manuscript review. JS secured funding.

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Correspondence to Wei Zhang, Jianpeng Sheng, Xiaobin Hou or Yi Hu.

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41388_2024_3123_MOESM1_ESM.pdf

Correlation between skin rashes and treatment outcomes. Distribution of patients with and without rashes among those exhibiting good (0–1) and poor (2–3) responses.

Distribution of LAMP3-positive DCs across various conditions.

Single-cell RNA-sequencing profile of ESCC TME.

lmaging mass cytometry antibody panel

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Wu, C., Zhang, G., Wang, L. et al. Spatial proteomic profiling elucidates immune determinants of neoadjuvant chemo-immunotherapy in esophageal squamous cell carcinoma. Oncogene 43, 2751–2767 (2024). https://doi.org/10.1038/s41388-024-03123-z

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