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

Journal for ImmunoTherapy of Cancer

Deepa Kasuganti¹  Neel Shah¹  Konstantin Dragnev²  Laura J. Tafe²  Katherine G. Madden²  Keisuke Shirai²  Lorenzo Galluzzi³  Jason Zhu⁴  Shannon J. McCall⁴  Matthew Labriola⁴  Jeffrey Clarke⁴  Daniel J. George⁴  Tian Zhang⁴  Daniele Marin⁴  Matthew Zibelman⁵  Pooja Ghatalia⁵  Isabel Araujo-Fernandez⁶  Luis de la Cruz-Merino⁶  Arun Singavi⁷  Ben George⁷  Alexander C. MacKinnon⁷  Jonathan Thompson⁷  Rajbir Singh⁸  Robin Jacob⁸  Sarabjot Pabla⁹  Blake Burgher⁹  Carl Morrison⁹  Mary K. Nesline⁹  Yirong Wang⁹  Vincent Giamo⁹  Sean T. Glenn⁹  Felicia L. Lenzo⁹  Mark Gardner⁹  Antonios Papanicolau-Sengos⁹  Jonathan Andreas⁹  Jeffrey M. Conroy⁹  Grace K. Dy^1,10  Wiam Bshara^1,10  Maya Khalil^1,10  Roger Day^1,11 

[1] Community Hospital;Dartmouth-Hitchcock Medical Center;Department of Radiation Oncology, Weill Cornell Medical College;Duke University Medical Center;Fox Chase Cancer Center;Hospital Universitario Virgen Macarena;Medical College of Wisconsin;Meharry Medical College;OmniSeq, Inc.;Roswell Park Comprehensive Cancer Center;University of Pittsburgh;

关键词: Atezolizumab;    Avelumab;    cancer immunotherapy;    Durvalumab;    Nivolumab;    Pembrolizumab;   

DOI  :  10.1186/s40425-018-0489-5

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

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