Pan-tumor genomic biomarkers for PD-1 checkpoint blockade-based immunotherapy
Razvan Cristescu1, Robin Mogg2, Mark Ayers2
1Merck & Co., Kenilworth, NJ 07033, USA. razvan_cristescu@merck.com.
Science (New York, N.Y.)
|October 13, 2018
Summary
Tumor mutational burden (TMB) and T cell-inflamed gene expression profile (GEP) predict response to PD-1 immunotherapy like pembrolizumab. These distinct biomarkers identify patients likely to benefit from immunotherapy, aiding clinical trial design.
Area of Science:
- Immunotherapy
- Oncology
- Genomics
Background:
- Programmed cell death protein-1 (PD-1) and programmed cell death ligand-1 (PD-L1) checkpoint blockade immunotherapy offers durable antitumor effects.
- However, not all cancer patients respond to this treatment.
Purpose of the Study:
- To evaluate the predictive utility of tumor mutational burden (TMB) and T cell-inflamed gene expression profile (GEP) for pembrolizumab response.
- To investigate the correlation between TMB and GEP in identifying responders and nonresponders.
Main Methods:
- Analysis of >300 patient samples across 22 tumor types from four KEYNOTE clinical trials.
- Evaluation of The Cancer Genome Atlas (TCGA) database for biomarker correlation.
- Joint stratification analysis to identify biomarker-defined resistance patterns.
Main Results:
- TMB and T cell-inflamed GEP jointly predicted response to PD-1 antibody pembrolizumab.
- Both TMB and GEP were independently predictive of response.
- TMB and GEP showed low correlation, indicating they capture distinct biological features.
Conclusions:
- TMB and GEP are valuable biomarkers for identifying patients who will respond to PD-1 blockade immunotherapy.
- These biomarkers can inform clinical trial design for selecting appropriate immunotherapy regimens (monotherapy or combination).
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