Tumor immune microenvironment reconstitution in patient-derived organoids enables therapy modeling for NSCLC

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Authors: Enrique Podaza, Jared Capuano, Hui–Hsuan Kuo, Majd Al Assaad, Geoffrey Markowitz, M. Victoria Revuelta, John Nguyen, Adriana Irizarry, Hiranmayi Ravichandran, Sarah Ackermann, Troy Kane, Jyothi Manohar
+14 more Alyssa Duren-Lubanski, Michael Sigouros, Jenna Moyer, Bhavneet Bhinder, Pooja Chandra, Murtaza S. Malbari, Karsten Boehnke, Juan Miguel Mosquera, Vivek Mittal, Andrea Sboner, Hamza Gokozan, Nasser Altorki, Olivier Elemento, M. Laura Martin
Cited by: 1
References: 58

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.

Fields of Study & Subjects

Cancer Cells and Metastasis Cancer Immunotherapy and Biomarkers Radiopharmaceutical Chemistry and Applications

Publication details

Journal / source
Cell Reports Methods
Publisher
Elsevier BV
Volume
6
Issue
6
Pages
101339–101339
Publication date
14 May 2026
Language
EN