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Profiling of immune features to predict immunotherapy efficacy
Youqiong Ye1,2, Yongchang Zhang3, Nong Yang3
1Shanghai Institute of Immunology, Department of Immunology and Microbiology, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
Innovation (Cambridge (Mass.))
|January 3, 2022
Summary
Predicting immunotherapy success is crucial. A new immune activation score, based on early changes in patient plasma, accurately forecasts response to immune checkpoint blockade therapy.
Area of Science:
- Immunology
- Cancer Research
- Biomarker Discovery
Background:
- Immune checkpoint blockade (ICB) therapies offer significant benefits in cancer treatment.
- Low response rates necessitate understanding immune feature interactions for improved efficacy.
- Identifying reliable biomarkers for predicting ICB response is critical.
Purpose of the Study:
- To investigate the correlations among immune checkpoints and immune cell populations.
- To identify predictive biomarkers for ICB therapy response.
- To develop a noninvasive method for early prediction of immunotherapy efficacy.
Main Methods:
- Analysis of immune features and their correlations in cancer patients.
- Monitoring dynamic alterations in plasma interleukins after initiating immunotherapy.
- Development and validation of an immune activation score (ISΔ) using early on-treatment plasma samples.
Main Results:
- Positive correlations were observed between immune checkpoints and immune cell populations.
- Patients responding to ICB showed increased immune stimulatory and inhibitory features.
- The developed immune activation score (ISΔ) accurately predicted immunotherapy efficacy as early as 4-6 weeks.
Conclusions:
- Immune microenvironment activation serves as a potential biomarker for ICB response.
- Dynamic profiling of plasma interleukins offers a noninvasive, cost-effective, and time-efficient predictive approach.
- The immune activation score (ISΔ) shows promise for personalized immunotherapy strategies.
