Next generation sequencing of PD-L1 for predicting response to immune checkpoint inhibitors

Jeffrey M. Conroy, Sarabjot Pabla, Mary K. Nesline, Sean T. Glenn, Antonios Papanicolau-Sengos, Blake Burgher, Jonathan Andreas, Vincent Giamo, Yirong Wang, Felicia L. Lenzo, Wiam Bshara, Maya Khalil, Grace K. Dy, Katherine G. Madden, Keisuke Shirai, Konstantin Dragnev, Laura J. Tafe, Jason Zhu, Matthew Labriola, Daniele MarinShannon J. McCall, Jeffrey Clarke, Daniel J. George, Tian Zhang, Matthew Zibelman, Pooja Ghatalia, Isabel Araujo-Fernandez, Luis De La Cruz-Merino, Arun Singavi, Ben George, Alexander C. MacKinnon, Jonathan Thompson, Rajbir Singh, Robin Jacob, Deepa Kasuganti, Neel Shah, Roger Day, Lorenzo Galluzzi, Mark Gardner, Carl Morrison

Research output: Contribution to journalArticlepeer-review

43 Scopus citations

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.

Original languageEnglish (US)
Article number18
JournalJournal for ImmunoTherapy of Cancer
Volume7
Issue number1
DOIs
StatePublished - Jan 24 2019
Externally publishedYes

Keywords

  • Atezolizumab
  • Avelumab
  • Biomarker
  • Durvalumab
  • Nivolumab
  • PD-L1
  • Pembrolizumab
  • cancer immunotherapy

ASJC Scopus subject areas

  • Immunology and Allergy
  • Immunology
  • Molecular Medicine
  • Oncology
  • Pharmacology
  • Cancer Research

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