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Updated: Jun 18, 2026
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A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds
Published on: April 6, 2016
Patient-derived three-dimensional lung tumor models to evaluate response to therapy
Kayla F Goliwas1, Aakash Desai2, Kenneth P Hough3
1Department of Medicine, Division of Pulmonary, Allergy, and Critical Care Medicine, University of Alabama at Birmingham, Birmingham, AL, USA. kfgoliwas@uabmc.edu.
NPJ Precision Oncology
|June 16, 2026
Summary
Researchers developed a novel 3D lung tumor model to study therapy response. This model identified immune cell signatures linked to treatment effectiveness in non-small cell lung cancer.
Area of Science:
- Oncology
- Immunology
- Biotechnology
Background:
- Preclinical models are crucial for understanding tumor biology and therapeutic responses.
- Existing models often fail to accurately replicate the in vivo tumor microenvironment.
- Novel models are needed to better predict patient response to cancer therapies.
Purpose of the Study:
- To develop and characterize a novel ex vivo patient-derived three-dimensional lung tumor model (3D-LTM).
- To evaluate the model's utility in assessing response to immune checkpoint inhibitors (ICI).
- To identify gene signatures and cellular correlates of ICI response in non-small cell lung cancer (NSCLC).
Main Methods:
- Development of a 3D-LTM using patient-derived lung tumors.
- Assessment of heterogeneous response to ICI within the 3D-LTM.
- Application of spatial transcriptomics to analyze cellular composition and gene expression.
- Pathway analysis to identify molecular mechanisms associated with response and non-response.
Main Results:
- The 3D-LTM recapitulated heterogeneous ICI response observed in NSCLC patients.
- Spatial transcriptomics revealed positive correlations between response and CD8+ T cells, CD4+ memory T cells, NK cells, B cells, endothelial cells, and monocytes.
- Macrophages were negatively correlated with response, while chemokine signaling pathways were activated in responders.
- Non-responders showed suppressed antigen presentation and activated T regulatory cell differentiation pathways.
Conclusions:
- The developed 3D-LTM serves as a valuable preclinical tool for studying tumor biology and therapy response.
- The model facilitates the identification of immune cell populations and gene signatures associated with ICI efficacy.
- This model holds potential for rapid therapeutic outcome testing and biomarker development in NSCLC.
