Next generation sequencing of PD-L1 for predicting response to immune checkpoint inhibitors. Issue 1 (24th January 2019)

• Record Type: Journal Article
• Authors: Conroy, Jeffrey M.; Pabla, Sarabjot; Nesline, Mary K.; Glenn, Sean T.; Papanicolau-Sengos, Antonios; Burgher, Blake; Andreas, Jonathan; Giamo, Vincent; Wang, Yirong; Lenzo, Felicia L.; Bshara, Wiam; Khalil, Maya; Dy, Grace K.; Madden, Katherine G.; Shirai, Keisuke; Dragnev, Konstantin; Tafe, Laura J.; Zhu, Jason; Labriola, Matthew; Marin, Daniele; McCall, Shannon J.; Clarke, Jeffrey; George, Daniel J.; Zhang, Tian; Zibelman, Matthew; Ghatalia, Pooja; Araujo-Fernandez, Isabel; de la Cruz-Merino, Luis; Singavi, Arun; George, Ben; MacKinnon, Alexander C.; Thompson, Jonathan; Singh, Rajbir; Jacob, Robin; Kasuganti, Deepa; Shah, Neel; Day, Roger; Galluzzi, Lorenzo; Gardner, Mark; Morrison, Carl;
• Is Part Of: Journal for immunotherapy of cancer. Volume 7:Issue 1(2019)
• Publication Date: 2019-01-24
• Subjects: Atezolizumab -- Avelumab -- cancer immunotherapy -- Durvalumab -- Nivolumab -- Pembrolizumab -- PD-L1 -- Biomarker; Cancer -- Immunotherapy -- Periodicals; Cancer -- Immunological aspects -- Periodicals; Tumors -- Immunological aspects -- Periodicals; Immunotherapy -- Periodicals; 616.99406105
• DOI: 10.1186/s40425-018-0489-5
• Languages: English
• ISSNs: 2051-1426

Abstract

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.