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A Gene Panel for Early Identification of Future Responders to Immune Checkpoint Blockade
Anshuman Panda1, Anil Betigeri2, Shridar Ganesan1,3
1Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, United States.
Abstract:
Immune checkpoint blockade (ICB), therapies that target the PD-1 pathway, CTLA-4 pathway, and other checkpoint pathways, lead to durable responses in many cancer types. Since only a minority of patients respond to ICB, it may be useful to identify the future responders early in the course of treatment. In this study we evaluated a small (15 genes) biologically motivated panel, consisting of genes involved in immune activation and checkpoint pathways, for early identification of future responders to ICB. The panel passed consistency check, pathological and in-silico validations, and was an excellent predictor (area under ROC curve >0.95) of eventual response to ICB, both CTLA-4 and PD-1 blockade, when applied to metastatic melanoma patients undergoing ICB (i.e., "on-treatment") in a publicly available dataset. These results suggest that this small biologically motivated panel may be useful for early identification of future responders to ICB.
Insights
A 15-gene panel accurately predicts response to immune checkpoint blockade (ICB) therapies like PD-1 and CTLA-4 blockade. This tool can identify future responders early in treatment for metastatic melanoma.
Area of Science:
- Immunology
- Oncology
- Genetics
Background:
- Immune checkpoint blockade (ICB) therapies targeting PD-1 and CTLA-4 pathways offer durable responses in various cancers.
- However, only a subset of patients benefit from ICB, necessitating early identification of potential responders.
- Predicting response is crucial for optimizing cancer treatment strategies.
Purpose of the Study:
- To evaluate a small, biologically motivated gene panel for early prediction of ICB response.
- To assess the panel's efficacy in identifying patients who will respond to PD-1 and CTLA-4 blockade.
Main Methods:
- A 15-gene panel, focusing on immune activation and checkpoint pathways, was developed.
- The panel underwent consistency, pathological, and in-silico validation.
- Its predictive performance was tested on a publicly available dataset of metastatic melanoma patients undergoing ICB.
Main Results:
- The 15-gene panel demonstrated high accuracy (AUC >0.95) in predicting ICB response.
- The panel effectively identified responders for both CTLA-4 and PD-1 blockade.
- Validation confirmed the panel's reliability for on-treatment prediction.
Conclusions:
- A small, biologically informed gene panel can reliably predict response to ICB therapies.
- This panel shows potential for early identification of future responders in metastatic melanoma patients.
- The findings suggest clinical utility for this panel in guiding ICB treatment decisions.
