PD-L1 expression and tumor mutational burden are independent biomarkers in most cancers
Mark Yarchoan, Lee A. Albacker, Alexander C. Hopkins, Meagan Montesion, Karthikeyan Murugesan, Teena T. Vithayathil, Neeha Zaidi, Nilofer S. Azad, Daniel A. Laheru, Garrett M. Frampton, Elizabeth M. Jaffee
Mark Yarchoan, Lee A. Albacker, Alexander C. Hopkins, Meagan Montesion, Karthikeyan Murugesan, Teena T. Vithayathil, Neeha Zaidi, Nilofer S. Azad, Daniel A. Laheru, Garrett M. Frampton, Elizabeth M. Jaffee
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Clinical Research and Public Health Genetics Immunology

PD-L1 expression and tumor mutational burden are independent biomarkers in most cancers

Abstract

BACKGROUND. PD-L1 expression and tumor mutational burden (TMB) have emerged as important biomarkers of response to immune checkpoint inhibitor (ICI) therapy. These biomarkers have each succeeded and failed in predicting responders for different cancer types. We sought to describe the PD-L1 expression landscape across the spectrum of ICI-responsive human cancers, and to determine the relationship between PD-L1 expression, TMB, and response rates to ICIs. METHODS. We assessed 9887 clinical samples for PD-L1 expression and TMB. RESULTS. PD-L1 expression and TMB are not significantly correlated within most cancer subtypes, and they show only a marginal association at the tumor sample level (Pearson’s correlation 0.084). Across distinct tumor types, PD-L1 expression and TMB have nonoverlapping effects on the response rate to PD-1/PD-L1 inhibitors and can broadly be used to categorize the immunologic subtypes of cancer. CONCLUSION. Our results indicate that PD-L1 expression and TMB may each inform the use of ICIs, point to different mechanisms by which PD-L1 expression regulates ICI responsiveness, and identify new opportunities for therapeutic development. FUNDING. Funding was provided by Foundation Medicine Inc., the Johns Hopkins Bloomberg–Kimmel Institute for Cancer Immunotherapy, the Viragh Foundation, the National Cancer Institute Specialized Program of Research Excellence (SPORE) in Gastrointestinal Cancers (P50 CA062924), the NIH Center Core Grant (P30 CA006973), the Norman & Ruth Rales Foundation, and the Conquer Cancer Foundation.

Authors

Mark Yarchoan, Lee A. Albacker, Alexander C. Hopkins, Meagan Montesion, Karthikeyan Murugesan, Teena T. Vithayathil, Neeha Zaidi, Nilofer S. Azad, Daniel A. Laheru, Garrett M. Frampton, Elizabeth M. Jaffee

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Figure 5

TMB and PD-L1 expression broadly categorize the immunologic subtypes of cancer.

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TMB and PD-L1 expression broadly categorize the immunologic subtypes of ...
(A) There is a positive relationship between the PD-L1 expression positivity rate and the ORR for anti–PD-1 or anti–PD-L1 therapy for the 29 tumor types or subtypes for which data regarding the ORR are available. For each tumor type, we pooled the response data from the largest published studies that evaluated the ORR (see Methods). (B) There is also a positive relationship between the TMB and the ORR for anti–PD-1 or anti–PD-L1 therapy. (C) An unbiased regression tree algorithm recursively identifies that hypermutated tumor types with TMB ≥ 10 have the best predicted ORR (38%) regardless of PD-L1 positivity. Response rates for cancer types with fewer than 10 mutations/Mb, however, are progressively higher as PD-L1 positivity rates increase. The algorithm identified <7%, 7%–13%, 13%–33%, and >33% of tumors staining positive for PD-L1 as the 4 PD-L1 thresholds that would most informatively split the data. Table 1 details the major tumor types that belong to each of these categories. (D) The unbiased regression tree supports a model of anti–PD-1 therapy in which hypermutated tumor types as well as inflamed tumor types with high PD-L1 expression are likely to respond to anti–PD-1 or anti–PD-L1 therapy, whereas nonhypermutated tumor types with low PD-L1 expression are unlikely to respond. MMRd, mismatch repair–deficient; H&N, head and neck carcinoma; UM, uveal melanoma.