Abstract
Non-small cell lung cancer (NSCLC) remains a leading cause of cancer-related mortality. Despite various therapeutic options, treatment resistance is common, underscoring the need for effective combination therapies and reliable pre-clinical models for patient-specific evaluation. Here, we describe strategies for reconstituting tumor immune microenvironment (TIME) components within patient-derived tumor organoid (PDTO) cultures. We established a tumor processing pipeline that enables concurrent expansion of tumor-infiltrating lymphocytes (TILs) and PDTO generation from the same resection. We optimized scalable assays to assess IFN-γ secretion and T cell cytotoxicity with immune checkpoint inhibitors (alone or in combination) and targeted inhibitors, capturing inter-patient heterogeneity and intra-patient variations between TILs and peripheral blood mononuclear cells (PBMCs). Additionally, we developed methods for differentiating PDTO-specific tumor-associated macrophages (TAMs) and established PDTO-TAM co-culture systems to evaluate TAM effects on PDTO growth and chemotherapy sensitivity. All approaches are scalable to high-throughput levels, highlighting the value of TIME-PDTO co-cultures for therapeutic modeling and precision medicine.
| Original language | English (US) |
|---|---|
| Article number | 101339 |
| Pages (from-to) | 101339 |
| Journal | Cell Reports Methods |
| Volume | 6 |
| Issue number | 6 |
| DOIs | |
| State | Published - Jun 15 2026 |
Keywords
- CP: cancer biology
- CP: immunology
- T cells
- co-cultures
- immunotherapy
- tumor microenviroment
- tumor organoids
- tumor-infiltrating lymphocytes
- Carcinoma, Non-Small-Cell Lung/immunology
- Lung Neoplasms/immunology
- Humans
- Coculture Techniques
- Tumor-Associated Macrophages/immunology
- Lymphocytes, Tumor-Infiltrating/immunology
- Tumor Microenvironment/immunology
- Organoids/immunology
ASJC Scopus subject areas
- Biotechnology
- Biochemistry
- Biochemistry, Genetics and Molecular Biology (miscellaneous)
- Genetics
- Radiology Nuclear Medicine and imaging
- Computer Science Applications
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