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Next Generation Sequencing of PD-L1 for Predicting Response to Immune Checkpoint Inhibitors

Abstract

Background: PD-L1 immunohistochemistry (IHC) has been traditionally used for predicting clinical responses to immune checkpoint inhibitors (ICIs). However, there are at least 4 different assays and antibodies used for PD-L1 IHC, each developed with a different ICI. We set to test if next generation RNA sequencing (RNA-seq) is a robust method to determine PD-L1 mRNA expression levels and furthermore, efficacy of predicting response to ICIs as compared to routinely used, standardized IHC procedures.

Methods: A total of 209 cancer patients treated on-label by FDA-approved ICIs, with evaluable responses were assessed for PD-L1 expression by RNA-seq and IHC, based on tumor proportion score (TPS) and immune cell staining (ICS). A subset of serially diluted cases was evaluated for RNA-seq assay performance across a broad range of PD-L1 expression levels.

Results: Assessment of PD-L1 mRNA levels by RNA-seq demonstrated robust linearity across high and low expression ranges. PD-L1 mRNA levels assessed by RNA-seq and IHC (TPS and ICS) were highly correlated (p < 2e-16). Sub-analyses showed sustained correlation when IHC results were classified as high or low by clinically accepted cut-offs (p < 0.01), and results did not differ by tumor type or anti-PD-L1 antibody used. Overall, a combined positive PD-L1 result (≥1% IHC TPS and high PD-L1 expression by RNA-Seq) was associated with a 2-to-5-fold higher overall response rate (ORR) compared to a double negative result. Standard assessments of sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) showed that a PD-L1 positive assessment for melanoma samples by RNA-seq had the lowest sensitivity (25%) but the highest PPV (72.7%). Among the three tumor types analyzed in this study, the only non-overlapping confidence interval for predicting response was for "RNA-seq low vs high" in melanoma.

Conclusions: Measurement of PD-L1 mRNA expression by RNA-seq is comparable to PD-L1 expression by IHC both analytically and clinically in predicting ICI response. RNA-seq has the added advantages of being amenable to standardization and avoidance of interpretation bias. PD-L1 by RNA-seq needs to be validated in future prospective ICI clinical studies across multiple histologies.

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References
1.
Blomquist T, Crawford E, Lovett J, Yeo J, Stanoszek L, Levin A . Targeted RNA-sequencing with competitive multiplex-PCR amplicon libraries. PLoS One. 2013; 8(11):e79120. PMC: 3827295. DOI: 10.1371/journal.pone.0079120. View

2.
Daud A, Wolchok J, Robert C, Hwu W, Weber J, Ribas A . Programmed Death-Ligand 1 Expression and Response to the Anti-Programmed Death 1 Antibody Pembrolizumab in Melanoma. J Clin Oncol. 2016; 34(34):4102-4109. PMC: 5562434. DOI: 10.1200/JCO.2016.67.2477. View

3.
Herbst R, Soria J, Kowanetz M, Fine G, Hamid O, Gordon M . Predictive correlates of response to the anti-PD-L1 antibody MPDL3280A in cancer patients. Nature. 2014; 515(7528):563-7. PMC: 4836193. DOI: 10.1038/nature14011. View

4.
Garon E, Rizvi N, Hui R, Leighl N, Balmanoukian A, Eder J . Pembrolizumab for the treatment of non-small-cell lung cancer. N Engl J Med. 2015; 372(21):2018-28. DOI: 10.1056/NEJMoa1501824. View

5.
Baehner F . The analytical validation of the Oncotype DX Recurrence Score assay. Ecancermedicalscience. 2016; 10:675. PMC: 5045300. DOI: 10.3332/ecancer.2016.675. View