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Updated: Jul 16, 2026
Immunophenotyping of Orthotopic Homograft (Syngeneic) of Murine Primary KPC Pancreatic Ductal Adenocarcinoma by Flow Cytometry
Published on: October 9, 2018
Intra-Tumor Heterogeneity of Pancreatic Ductal Adenocarcinoma (PDAC)-Microenvironmental Interaction and Precision
Boyeon Kim1,2, Jee-Hyung Lee3,4,5
1Division of Medical Oncology, Department of Internal Medicine, Korea University College of Medicine, Seoul 02841, Republic of Korea.
Abstract:
Pancreatic ductal adenocarcinoma (PDAC) remains among the most therapeutically intractable malignancies, with a 5-year survival rate of approximately 10% and near-universal resistance to immune checkpoint inhibitor (ICI) therapy. This refractoriness arises from the convergence of pronounced intratumoral heterogeneity (ITH) and a profoundly immunosuppressive tumor microenvironment (TME), which together configure PDAC as a prototypical immune-excluded tumor. Beyond low tumor mutational burden, PDAC exhibits layered genetic, epigenetic, transcriptional, and metabolic heterogeneity that enables rapid adaptation and immune evasion under selective pressure, while dense desmoplastic stroma, cancer-associated fibroblasts (CAFs), and immunosuppressive immune populations collectively impose formidable physical and immunologic barriers to antitumor immunity. In this review, we synthesize multi-omics, spatial transcriptomic, and immunologic evidence to elucidate how ITH and the TME dynamically interact to reinforce immune resistance. We examine reciprocal crosstalk mechanisms-including immune-driven clonal selection, interclonal cooperation, metabolic niche specialization, and metabolic-epigenetic coupling-and discuss emerging platforms such as single-cell spatial omics, patient-derived organoid immune co-culture systems, and longitudinal circulating tumor DNA monitoring that enable high-resolution mapping of ITH-TME dynamics. Finally, we evaluate ITH-TME-guided combination therapeutic strategies targeting oncogenic drivers, stromal architecture, myeloid suppression, and metabolic checkpoints, and propose a prioritized framework for near-term and speculative clinical translation in PDAC.
Insights
Pancreatic cancer (PDAC) is hard to treat due to tumor diversity and a suppressive microenvironment, causing resistance to therapies. Understanding these interactions is key to developing new treatments for pancreatic cancer.
Area of Science:
- Oncology
- Immunology
- Genetics
Background:
- Pancreatic ductal adenocarcinoma (PDAC) is a lethal cancer with poor survival and resistance to immune checkpoint inhibitors (ICIs).
- This resistance is driven by intratumoral heterogeneity (ITH) and an immunosuppressive tumor microenvironment (TME), creating an immune-excluded phenotype.
- PDAC's complexity includes genetic, epigenetic, transcriptional, and metabolic heterogeneity, alongside dense stroma, cancer-associated fibroblasts (CAFs), and immunosuppressive immune cells, forming barriers to immunity.
Purpose of the Study:
- To review the dynamic interplay between ITH and TME in PDAC and its role in immune resistance.
- To examine mechanisms of reciprocal crosstalk, including immune-driven selection, interclonal cooperation, and metabolic-epigenetic coupling.
- To discuss emerging technologies for mapping ITH-TME dynamics and evaluate ITH-TME-guided therapeutic strategies.
Main Methods:
- Synthesis of multi-omics, spatial transcriptomic, and immunologic data.
- Examination of reciprocal crosstalk mechanisms between ITH and TME.
- Evaluation of emerging platforms like single-cell spatial omics and patient-derived organoid co-cultures.
Main Results:
- ITH and TME synergistically create physical and immunological barriers, reinforcing immune resistance in PDAC.
- Specific crosstalk mechanisms like immune-driven clonal selection and metabolic niche specialization contribute to immune evasion.
- Advanced technologies offer high-resolution mapping of ITH-TME dynamics.
Conclusions:
- Understanding ITH-TME interactions is crucial for overcoming therapeutic resistance in PDAC.
- ITH-TME-guided combination therapies targeting drivers, stroma, myeloid cells, and metabolic pathways show promise.
- A framework for clinical translation of these strategies is proposed.
