Related Experiment Video
Updated: Feb 3, 2026
06:51
Manufacturing Chimeric Antigen Receptor CAR T Cells for Adoptive Immunotherapy
Published on: December 17, 2019
16.0K
Summary
Tumor mutational burden and T cell-inflamed gene expression profile can predict response to pembrolizumab. Combining these biomarkers offers the best clinical utility for predicting patient outcomes.
Area of Science:
- Oncology
- Immunotherapy
- Biomarker Discovery
Background:
- Pembrolizumab is an immune checkpoint inhibitor used in cancer therapy.
- Predicting patient response to immunotherapy is crucial for effective treatment.
- Biomarkers can help identify patients most likely to benefit from pembrolizumab.
Discussion:
- Tumor mutational burden (TMB) and T cell-inflamed gene expression profile (GEP) were analyzed as predictive biomarkers.
- The largest dataset of its kind was used for this analysis.
- Both TMB and T cell-inflamed GEP independently predict response to pembrolizumab.
Key Insights:
- Independently, TMB and T cell-inflamed GEP predict patient response to pembrolizumab.
- Joint consideration of both biomarkers provides the greatest clinical utility.
- Combined biomarker analysis identifies patterns of underlying, targetable biology.
Outlook:
- This combined biomarker approach can optimize patient selection for pembrolizumab therapy.
- Further research may elucidate specific targetable pathways identified by the combined biomarkers.
- Enhanced prediction of immunotherapy response can improve patient outcomes and treatment strategies.
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