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Purpose <p>Current lung cancer organoid models often fail to replicate the complex tumor immune microenvironment, reducing their predictive value for immunotherapy and radiotherapy. Therefore, it is crucial to establish an optimized lung cancer organoid model which could recapitulate the tumor immune microenvironment, enabling more accurate evaluation of therapeutic responses.</p> Methods <p>We developed an optimized air-liquid interface (ALI) culture method to generate patient-derived lung cancer organoids (ALI-LUOs) from 19 lung cancer samples. The tumor microenvironment, including immune and stromal components, was characterized using immunofluorescence, flow cytometry, and single-cell RNA sequencing. The organoids were further used to assess responses to αPD-1 therapy and radiotherapy.</p> Results <p>The optimized method significantly improved organoid formation efficiency while preserving immune cell viability for up to 30 days. Immune and fibroblast populations were confirmed by immunofluorescence and flow cytometry. Single-cell RNA sequencing demonstrated that ALI-LUOs accurately replicate the tumor immune landscape. Key tumor immunity pathways such as cGAS-STING could be captured by ALI-LUOs. Importantly, ALI-LUOs modeled clinical responses to immune checkpoint inhibitors and radiotherapy with high fidelity.</p> Conclusions <p>The ALI-LUOs, developed through an optimized culture method, faithfully capture the key characteristics of lung cancer, including its immunosuppressive tumor microenvironment. Our findings highlight this modified ALI-LUOs as a valuable preclinical platform for evaluating antitumor immunity and refining lung cancer treatments.</p>

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Optimized patient-derived lung cancer organoids recapitulating the immune landscape for precision therapy evaluation

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月6日

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  • Huayang Xing,
  • Rui Liu,
  • Yidan Chen,
  • Xueqin Chen,
  • Xianzhi Gao,
  • Chongyang Shen,
  • Shirong Zhang,
  • Yi Tang,
  • Longfeng Wu,
  • Mingliang You,
  • Pinglong Xu,
  • Bing Xia

摘要

Purpose

Current lung cancer organoid models often fail to replicate the complex tumor immune microenvironment, reducing their predictive value for immunotherapy and radiotherapy. Therefore, it is crucial to establish an optimized lung cancer organoid model which could recapitulate the tumor immune microenvironment, enabling more accurate evaluation of therapeutic responses.

Methods

We developed an optimized air-liquid interface (ALI) culture method to generate patient-derived lung cancer organoids (ALI-LUOs) from 19 lung cancer samples. The tumor microenvironment, including immune and stromal components, was characterized using immunofluorescence, flow cytometry, and single-cell RNA sequencing. The organoids were further used to assess responses to αPD-1 therapy and radiotherapy.

Results

The optimized method significantly improved organoid formation efficiency while preserving immune cell viability for up to 30 days. Immune and fibroblast populations were confirmed by immunofluorescence and flow cytometry. Single-cell RNA sequencing demonstrated that ALI-LUOs accurately replicate the tumor immune landscape. Key tumor immunity pathways such as cGAS-STING could be captured by ALI-LUOs. Importantly, ALI-LUOs modeled clinical responses to immune checkpoint inhibitors and radiotherapy with high fidelity.

Conclusions

The ALI-LUOs, developed through an optimized culture method, faithfully capture the key characteristics of lung cancer, including its immunosuppressive tumor microenvironment. Our findings highlight this modified ALI-LUOs as a valuable preclinical platform for evaluating antitumor immunity and refining lung cancer treatments.