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Key Predictors of Response Rates to PD-1/PD-L1 Inhibitor Therapy Across Cancer Types


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In a study reported in JAMA Oncology, Lee and Ruppin found that CD8-positive T-cell abundance, tumor mutational burden, and high PD1 gene expression were the strongest predictors of response to anti–programmed cell death protein 1/programmed cell death ligand 1 (PD-1/PD-L1) treatment across cancer types.

Study Details

The analysis included use of whole-exome and RNA sequencing data of 7,187 patients from the Cancer Genome Atlas, as well as objective response rate data on 21 cancer types obtained from a collection of clinical trials of PD-1/PD-L1 inhibitor therapy published by Yarchoan et al in The New England Journal of Medicine. A total of 36 variables representing tumor neoantigens, tumor microenvironment and inflammation, and checkpoint inhibitor targets were analyzed.

"The findings suggest that the three key variables can explain most of the observed cross-cancer response variability, but their relative explanatory roles may vary in specific cancer types.”
— Lee and Ruppin

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Findings

Among the 36 variables evaluated, the 3 most predictive of response to PD-1/PD-L1 inhibitor therapy across cancer types represented each of the three categories of variables considered; they were, in order of predictive ability:

  • Estimated CD8-positive T-cell abundance (Spearman R = 0.72, P < 2.3 × 10-4 )
  • Tumor mutational burden (R = 0.68, P < 6.2 × 10-4)
  • Fraction of tumor samples with high PD1 gene expression (R = 0.68, P < 6.9 × 10-4).

In analysis combining the three variables, the combination was highly correlated with treatment response (R = 0.90, P < 4.1 × 10-8), accounting for more than 80% of objective response rate variability across tumor types.

The investigators concluded, “That we know of, this is the first systematic evaluation of the different variables associated with anti–PD-1/PD-L1 therapy response across different tumor types. The findings suggest that the three key variables can explain most of the observed cross-cancer response variability, but their relative explanatory roles may vary in specific cancer types.”

Joo Sang Lee, PhD, of Samsung Medical Center, Sungkyunkwan University School of Medicine, Suwon, Republic of Korea, and Eytan Ruppin, MD, PhD, of the National Cancer Institute, are the corresponding authors for the JAMA Oncology article.

Disclosure: The study was supported by the Intramural Research Program of the Center for Cancer Research, National Cancer Institute, National Institutes of Health. For full disclosures of the study authors, visit jamanetwork.com.

The content in this post has not been reviewed by the American Society of Clinical Oncology, Inc. (ASCO®) and does not necessarily reflect the ideas and opinions of ASCO®.
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