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Updated: Nov 6, 2025

Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Categorisation of patients based on immune profiles: a new approach to identifying candidates for response to
Svetlana Bornschlegl1, Michael P Gustafson1,2, Danae A Delivanis3
1Immune Progenitor and Cell Therapy (IMPACT) Division of Experimental Pathology Mayo Clinic Rochester MN USA.
Objectives:
Inhibitors to the checkpoint proteins cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) and programmed cell death protein 1 (PD-1) are becoming widely used in cancer treatment. However, a lack of understanding of the patient response to treatment limits accurate identification of potential responders to immunotherapy.
Methods:
In this study, we assessed the expression of PD-1 and CTLA-4 on 19 leucocyte populations in the peripheral blood of 74 cancer patients. A reference data set for PD-1 and CTLA-4 was established for 40 healthy volunteers to determine the normal expression patterns for these checkpoint proteins.
Results:
Unsupervised hierarchical clustering found four immune profiles shared across the solid tumor types, while chronic lymphocytic leukaemia patients had an immune profile largely unique to them. Furthermore, we measured these leucocyte populations on an additional cohort of 16 cancer patients receiving the PD-1 inhibitor pembrolizumab in order to identify differences between responders and non-responders, as well as compared to healthy volunteers (n = 20). We observed that cancer patients had pre-treatment PD-1 and CTLA-4 expression on their leucocyte populations at different levels compared to healthy volunteers and identified two leucocyte populations positive for CTLA-4 that had not been previously described. We found higher levels of PD-1+ CD3+ CD4- CD8- cells in patients with progressive disease and have identified it as a potential biomarker of response, as well as identifying other significant differences in phenotypes between responders and non-responders.
Conclusion:
These results are suggestive that categorisation of patients based on immune profiles may differentiate responders from non-responders to immunotherapy for solid tumors.
Insights
Identifying immune profiles can help predict patient response to cancer immunotherapy. Researchers found specific leukocyte populations, like PD-1+ CD3+ CD4- CD8- cells, may serve as biomarkers for treatment effectiveness.
Area of Science:
- Immunology
- Oncology
- Biomarker Discovery
Background:
- Immune checkpoint inhibitors targeting cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) and programmed cell death protein 1 (PD-1) are crucial cancer therapies.
- Predicting patient response to immunotherapy remains a challenge due to limited understanding of individual immune variations.
Purpose of the Study:
- To assess PD-1 and CTLA-4 expression on leukocyte populations in cancer patients.
- To establish reference expression patterns in healthy individuals.
- To identify differences in immune profiles between immunotherapy responders and non-responders.
Main Methods:
- Analyzed 19 leukocyte populations in peripheral blood from 74 cancer patients and 40 healthy volunteers.
- Utilized unsupervised hierarchical clustering to identify immune profiles.
- Compared leukocyte populations in patients receiving PD-1 inhibitor pembrolizumab with healthy controls.
Main Results:
- Discovered distinct immune profiles in solid tumor patients and chronic lymphocytic leukemia patients.
- Identified previously undescribed CTLA-4 positive leukocyte populations.
- Found higher levels of PD-1+ CD3+ CD4- CD8- cells in patients with progressive disease, suggesting potential as a response biomarker.
Conclusions:
- Immune profiling may differentiate responders from non-responders to immunotherapy for solid tumors.
- Specific leukocyte phenotypes correlate with treatment response and disease progression.
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