Related Experiment Video
Updated: Dec 9, 2025
Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
A bilateral tumor model identifies transcriptional programs associated with patient response to immune checkpoint
Ivy X Chen1, Kathleen Newcomer2, Kristen E Pauken3,4
1Edwin L. Steele Laboratories, Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114.
Abstract:
Immune checkpoint blockade (ICB) is efficacious in many diverse cancer types, but not all patients respond. It is important to understand the mechanisms driving resistance to these treatments and to identify predictive biomarkers of response to provide best treatment options for all patients. Here we introduce a resection and response-assessment approach for studying the tumor microenvironment before or shortly after treatment initiation to identify predictive biomarkers differentiating responders from nonresponders. Our approach builds on a bilateral tumor implantation technique in a murine metastatic breast cancer model (E0771) coupled with anti-PD-1 therapy. Using our model, we show that tumors from mice responding to ICB therapy had significantly higher CD8+ T cells and fewer Gr1+CD11b+ myeloid-derived suppressor cells (MDSCs) at early time points following therapy initiation. RNA sequencing on the intratumoral CD8+ T cells identified the presence of T cell exhaustion pathways in nonresponding tumors and T cell activation in responding tumors. Strikingly, we showed that our derived response and resistance signatures significantly segregate patients by survival and associate with patient response to ICB. Furthermore, we identified decreased expression of CXCR3 in nonresponding mice and showed that tumors grown in Cxcr3-/- mice had an elevated resistance rate to anti-PD-1 treatment. Our findings suggest that the resection and response tumor model can be used to identify response and resistance biomarkers to ICB therapy and guide the use of combination therapy to further boost the antitumor efficacy of ICB.
Insights
Understanding resistance to immune checkpoint blockade (ICB) is crucial. This study identifies early immune cell changes and molecular signatures in a murine model that predict patient response to ICB therapy, paving the way for improved cancer treatments.
Area of Science:
- Immunology
- Oncology
- Cancer Research
Background:
- Immune checkpoint blockade (ICB) shows efficacy in various cancers, but patient response varies.
- Identifying mechanisms of resistance and predictive biomarkers is essential for optimizing ICB therapy.
- Understanding the tumor microenvironment's role in ICB response is critical.
Purpose of the Study:
- To develop and validate a resection and response-assessment approach for identifying predictive biomarkers of ICB response.
- To investigate the tumor microenvironment changes associated with ICB response and resistance.
- To discover novel biomarkers that segregate patient survival and predict response to ICB.
Main Methods:
- Utilized a bilateral tumor implantation murine metastatic breast cancer model (E0771) with anti-PD-1 therapy.
- Analyzed early time points post-therapy initiation for immune cell populations (CD8+ T cells, MDSCs).
- Performed RNA sequencing on intratumoral CD8+ T cells and assessed CXCR3 expression in a Cxcr3 knockout model.
Main Results:
- Responding tumors showed increased CD8+ T cells and decreased myeloid-derived suppressor cells (MDSCs) early after ICB initiation.
- RNA sequencing revealed T cell exhaustion in nonresponding tumors and T cell activation in responding tumors.
- Derived response/resistance signatures correlated with patient survival and ICB response; decreased CXCR3 expression was linked to resistance.
Conclusions:
- The developed resection and response model effectively identifies biomarkers for ICB therapy response and resistance.
- Early immune cell profiling and molecular signatures can predict patient outcomes.
- Targeting CXCR3 or utilizing combination therapies may enhance ICB efficacy in nonresponding patients.
