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Orthotopic Implantation of Patient-Derived Cancer Cells in Mice Recapitulates Advanced Colorectal Cancer
Published on: February 10, 2023
Patient-derived colorectal microtumors predict response to anti-PD-1 therapy
Duy T Nguyen1, Matthew A Schaller2, Krista P Terracina3
1Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL, United States.
Abstract:
Immune checkpoint inhibitors have made remarkable impacts in treating various cancers, including colorectal cancer (CRC). However, CRC still remains a leading cause of cancer-related deaths. While microsatellite instability (MSI) CRC has shown positive responses to anti-PD-1 therapy, this subgroup represents a minority of all CRC patients. Extensive research has focused on identifying predictive biomarkers to understand treatment response in CRC. Interestingly, a growing number of clinical cases have reported favorable outcomes from a subtype of supposedly non-responder microsatellite stable (MSS) CRC, characterized by DNA polymerase ϵ (POLE) proofreading domain mutations with high tumor mutational burden (TMB). This subtype has shown a notable response, either partial or complete, to pembrolizumab as salvage treatment, often following significant disease progression. To improve efficiency, cost-effectiveness, and clinical outcomes, there is an essential need for a testing platform capable of promptly identifying evidence of anti-PD-1 response to inform treatment strategies. Here, we established a novel 3D ex vivo immunotherapy model using patient-derived tumor microexplants (or microtumors <1 mm) co-cultured with autologous peripheral blood mononuclear cells (PBMCs) from treatment-naïve CRC patients. We demonstrate that long-term ex vivo treatment with pembrolizumab induced a heterogeneous but appreciable interferon-gamma (IFN-γ) secretion, accompanied by infiltrating PBMCs. Intriguingly, a case study involving an MSS CRC phenotype harboring POLE mutation and associated ultrahigh TMB demonstrated a response to PD-1 blockade, potentially from the intratumoral immune cell population. Ultimately, this novel model could serve as a valuable tool in complementing clinical diagnostics and guiding personalized treatment plans for CRC patients, particularly those with specific phenotypes and mutational profiles.
Insights
A new 3D ex vivo model using colorectal cancer (CRC) microtumors and patient immune cells shows promise for predicting response to anti-PD-1 therapy, especially in rare POLE-mutated MSS CRC cases.
Area of Science:
- Oncology
- Immunotherapy
- Cancer Research
Background:
- Colorectal cancer (CRC) remains a significant cause of cancer mortality.
- While anti-PD-1 therapy benefits microsatellite instability (MSI) CRC, most patients are microsatellite stable (MSS).
- A subset of MSS CRC with POLE mutations and high tumor mutational burden (TMB) shows unexpected responses to immunotherapy.
Purpose of the Study:
- To develop a novel 3D ex vivo immunotherapy model for predicting anti-PD-1 response in CRC.
- To investigate the potential of this model in identifying responders among MSS CRC patients with specific mutations.
- To guide personalized treatment strategies for CRC based on predictive biomarkers.
Main Methods:
- Established a 3D ex vivo co-culture system with patient-derived CRC microtumors and autologous peripheral blood mononuclear cells (PBMCs).
- Treated microtumors ex vivo with pembrolizumab (anti-PD-1 therapy).
- Assessed interferon-gamma (IFN-γ) secretion and T-cell infiltration as indicators of immune response.
Main Results:
- The 3D ex vivo model demonstrated heterogeneous but appreciable IFN-γ secretion and T-cell infiltration upon pembrolizumab treatment.
- A case study highlighted a POLE-mutated, ultrahigh TMB MSS CRC phenotype responding to PD-1 blockade.
- The model showed potential in reflecting treatment response in specific CRC subtypes.
Conclusions:
- The novel 3D ex vivo model can predict anti-PD-1 therapy response in CRC.
- This model may identify MSS CRC patients with POLE mutations and high TMB as potential responders.
- The model serves as a valuable tool for personalized treatment planning in CRC.
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