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Background <p>Tumor heterogeneity and the complexity of the tumor microenvironment (TME) drive therapeutic resistance in lung cancer, highlighting the critical need for experimental models that faithfully recapitulate tumor–stroma–immune interactions.</p> Methods <p>We developed patient-specific lung cancer tumoroid (LCT) models by integrating lung cancer organoids (LCOs), cancer-associated fibroblasts (CAFs) and immune cells isolated from single tumor tissue sources using a modular, transwell-based culture platform. The model supports cryopreservation and reproducible reconstruction of cellular components. Multimodal assessments, including histological characterization, dose-response pharmacologic profiling, immune profiling, and transcriptomic analyses, were performed across diverse co-culture configurations to evaluate patient-specific TME features and treatment-associated responses.</p> Results <p>The LCT models successfully recapitulated key structural and cellular features of native TMEs, demonstrating high reproducibility across patient samples. Functional analyses revealed tumor-intrinsic heterogeneity in responses to chemotherapy and chemo-immunotherapy. CAF integration altered therapeutic responses and was associated with reduced immune activation and cytotoxic efficacy in selected models, suggesting stromal contributions to treatment resistance. Transcriptomic analyses showed that reconstructed TMEs preserved patient-specific stromal and immune programs associated with therapeutic responsiveness, including transcriptional features linked to clinical outcomes in independent immunotherapy-treated cohorts.</p> Conclusions <p>This patient-specific LCT model provides a scalable and translationally relevant approach for the ex vivo reconstruction of native TMEs, facilitating the functional interrogation of tumor–stroma–immune interactions. By capturing heterogeneous stromal responses, this platform offers a valuable tool for investigating therapeutic resistance and supports the further development of precision immune-oncology and patient-tailored therapeutic strategies in lung cancer.</p>

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Patient-specific lung cancer tumoroids recapitulate the tumor microenvironments for functional evaluation of therapeutic responses and immune-stromal interactions

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月18日

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  • Yoo Ri Ko,
  • Chae Won Park,
  • Jihye Kim,
  • Da Jung Jung,
  • Sung Min Kim,
  • Hye Seon Park,
  • Bokyung Ahn,
  • Hee Sang Hwang,
  • Chang Ohk Sung,
  • Se Jin Jang

摘要

Background

Tumor heterogeneity and the complexity of the tumor microenvironment (TME) drive therapeutic resistance in lung cancer, highlighting the critical need for experimental models that faithfully recapitulate tumor–stroma–immune interactions.

Methods

We developed patient-specific lung cancer tumoroid (LCT) models by integrating lung cancer organoids (LCOs), cancer-associated fibroblasts (CAFs) and immune cells isolated from single tumor tissue sources using a modular, transwell-based culture platform. The model supports cryopreservation and reproducible reconstruction of cellular components. Multimodal assessments, including histological characterization, dose-response pharmacologic profiling, immune profiling, and transcriptomic analyses, were performed across diverse co-culture configurations to evaluate patient-specific TME features and treatment-associated responses.

Results

The LCT models successfully recapitulated key structural and cellular features of native TMEs, demonstrating high reproducibility across patient samples. Functional analyses revealed tumor-intrinsic heterogeneity in responses to chemotherapy and chemo-immunotherapy. CAF integration altered therapeutic responses and was associated with reduced immune activation and cytotoxic efficacy in selected models, suggesting stromal contributions to treatment resistance. Transcriptomic analyses showed that reconstructed TMEs preserved patient-specific stromal and immune programs associated with therapeutic responsiveness, including transcriptional features linked to clinical outcomes in independent immunotherapy-treated cohorts.

Conclusions

This patient-specific LCT model provides a scalable and translationally relevant approach for the ex vivo reconstruction of native TMEs, facilitating the functional interrogation of tumor–stroma–immune interactions. By capturing heterogeneous stromal responses, this platform offers a valuable tool for investigating therapeutic resistance and supports the further development of precision immune-oncology and patient-tailored therapeutic strategies in lung cancer.