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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
PubMed

Insights

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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