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. 2020 May;31(5):599-608.
doi: 10.1016/j.annonc.2020.01.065. Epub 2020 Feb 6.

Clinical and molecular correlates of PD-L1 expression in patients with lung adenocarcinomas

A J Schoenfeld  1 , H Rizvi  2 , C Bandlamudi  3 , J L Sauter  4 , W D Travis  4 , N Rekhtman  4 , A J Plodkowski  5 , R Perez-Johnston  5 , P Sawan  5 , A Beras  4 , J V Egger  2 , M Ladanyi  4 , K C Arbour  1 , C M Rudin  6 , G J Riely  1 , B S Taylor  3 , M T A Donoghue  3 , M D Hellmann  7
Affiliations

Clinical and molecular correlates of PD-L1 expression in patients with lung adenocarcinomas

A J Schoenfeld et al. Ann Oncol. 2020 May.

Abstract

Background: Programmed death-ligand 1 (PD-L1) expression is the only FDA-approved biomarker for immune checkpoint inhibitors (ICIs) in patients with lung adenocarcinoma, but sensitivity is modest. Understanding the impact of molecular phenotype, clinical characteristics, and tumor features on PD-L1 expression is largely unknown and may improve prediction of response to ICI.

Patients and methods: We evaluated patients with lung adenocarcinoma for whom PD-L1 testing and targeted next-generation sequencing (using MSK-IMPACT) was performed on the same tissue sample. Clinical and molecular features were compared across PD-L1 subgroups to examine how molecular phenotype associated with tumor PD-L1 expression. In patients treated with anti-PD-(L)1 blockade, we assessed how these interactions impacted efficacy.

Results: A total of 1586 patients with lung adenocarcinoma had paired PD-L1 testing and targeted next-generation sequencing. PD-L1 negativity was more common in primary compared to metastatic samples (P < 0.001). The distribution of PD-L1 expression (lymph nodes enriched for PD-L1 high; bones predominantly PD-L1 negative) and predictiveness of PD-L1 expression on ICI response varied by organ. Mutations in KRAS, TP53, and MET significantly associated with PD-L1 high expression (each P < 0.001, Q < 0.001) and EGFR and STK11 mutations associated with PD-L1 negativity (P < 0.001, Q = 0.01; P = 0.001, Q < 0.001, respectively). WNT pathway alterations also associated with PD-L1 negativity (P = 0.005). EGFR and STK11 mutants abrogated the predictive value of PD-L1 expression on ICI response.

Conclusion: PD-L1 expression and association with ICI response vary across tissue sample sites. Specific molecular features are associated with differential expression of PD-L1 and may impact the predictive capacity of PD-L1 for response to ICIs.

Keywords: NSCLC; PD-1; PD-L1; immunotherapy.

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Conflict of interest statement

Disclosure JLS reports stock ownership in the following companies: Pfizer, Thermo Fischer Scientific, Inc., Merck & Co Inc., and Chemed Corp. KCA has been a compensated consultant for AstraZeneca. MAE is a consultant for AstraZeneca and received support from AstraZeneca, Invivoscribe, and Raindance Technologies. ML has received advisory board compensation from Boehringer Ingelheim, AstraZeneca, Bristol-Myers Squibb, Takeda, and Bayer and research support from Loxo Oncology and Helsinn Healthcare. CML is a consultant for AbbVie, Amgen, Ascentage, AstraZeneca, Bicycle, Celgene, Chugai, Daiichi Sankyo, Genentech/Roche, GI Therapeutics, Loxo, Novartis, PharmaMar, and Seattle Genetics; serves on the scientific advisory boards of Elucida and Harpoon; and reports personal fees from Bristol-Myers Squibb and Ipsen. GJR has research funding for his institution from Pfizer, Novartis, Takeda, and Roche. MDH receives research funding from Bristol-Myers Squibb; is a paid consultant to Merck, Bristol-Myers Squibb, AstraZeneca, Genentech/Roche, Janssen, Nektar, Syndax, Mirati, and Shattuck Labs; receives travel support/honoraria from AstraZeneca and Bristol-Myers Squibb; and a patent has been filed by MSK related to the use of tumor mutation burden to predict response to immunotherapy (PCT/US2015/062208), which has received licensing fees from PGDx. All other authors have declared no conflicts of interest.

Figures

Figure 1.
Figure 1.. PD-L1 expression and ICI response by anatomic site
(A) The distribution of PD-L1 expression (high [≥50], intermediate [1–49%], negative [<1%]) by tissue sampling site. (B) Progression free survival (PFS) in PD-L1 high versus negative cases in which PD-L1 testing was performed in lung (log-rank HR 0.52 [95% CI 0.32–0.71], p<0.001) or distant (log-rank HR 0.56 [95% CI 0.36–0.88], p=0.005) metastasis tissue. (C) Progression free survival (PFS) in PD-L1 high versus negative cases in which PD-L1 testing was performed in lymph node (log-rank HR 0.67 [95% CI 0.37–1.21], p=0.16) or bone (log-rank HR 0.92 [95% CI 0.42–2.01], p=0.83) metastasis tissue.
Figure 2.
Figure 2.. Molecular features of PD-L1 subgroups
(A) Comparison of TMB and PD-L1 expression as continuous variables (above, dots represent individual tumor samples; Spearman rho=0.167, p<0.001) and as categorical variables (below, donut plots characterize proportion of patients who are PD-L1 high [represented in green] within TMB subgroups [TMB low < 8 mt/mb, TMB intermediate ≥ 8 mt/mb and < 20 mt/mb, TMB high ≥ 20 mt/mb]. (B) Comparison of fraction of genome altered (FGA) and PD-L1 expression. Dots represent individual tumor samples. (Spearman rho 0.061, p=0.056) (C) PD-L1 expression by whole genome duplication (WGD) status (PD-L1 high green, PD-L1 intermediate dark blue, PD-L1 negative light blue).
Figure 3.
Figure 3.. Differential PD-L1 expression based on alterations in individual genes and pathways
(A) Frequency of altered individual genes within PD-L1 high vs PD-L1 negative expression subgroups. Genes labeled red were associated with significantly differential PD-L1 expression (q value <0.15). (B) Distribution of PD-L1 expression by commonly altered genes in lung adenocarcinoma. (C) Percentage of tumors harboring an alteration of individual pathways within PD-L1 subgroups (PD-L1 intermediate subgroup not shown).
Figure 4.
Figure 4.. ICI outcomes by PD-L1 expression within mutant genes and altered pathway subgroups
(A) Objective response rate (ORR), PFS, and OS within patients with EGFR mutations. (B) Objective response rate (ORR), PFS, and OS within patients with STK11 mutations. (C) Objective response rate (ORR), PFS, and OS within patients with KRAS mutations. (D) Objective response rate (ORR), PFS, and OS within patients with TP53 mutations. (E) Forest plot of progression-free survival within subgroups of individual altered pathways, comparing outcomes of patients with PD-L1 high vs negative tumors. (F) Forest plot of overall survival within subgroups of individual altered pathways, comparing outcomes of patients with PD-L1 high vs negative tumors.
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