TY - JOUR
T1 - Next generation sequencing of PD-L1 for predicting response to immune checkpoint inhibitors
AU - Conroy, Jeffrey M.
AU - Pabla, Sarabjot
AU - Nesline, Mary K.
AU - Glenn, Sean T.
AU - Papanicolau-Sengos, Antonios
AU - Burgher, Blake
AU - Andreas, Jonathan
AU - Giamo, Vincent
AU - Wang, Yirong
AU - Lenzo, Felicia L.
AU - Bshara, Wiam
AU - Khalil, Maya
AU - Dy, Grace K.
AU - Madden, Katherine G.
AU - Shirai, Keisuke
AU - Dragnev, Konstantin
AU - Tafe, Laura J.
AU - Zhu, Jason
AU - Labriola, Matthew
AU - Marin, Daniele
AU - McCall, Shannon J.
AU - Clarke, Jeffrey
AU - George, Daniel J.
AU - Zhang, Tian
AU - Zibelman, Matthew
AU - Ghatalia, Pooja
AU - Araujo-Fernandez, Isabel
AU - De La Cruz-Merino, Luis
AU - Singavi, Arun
AU - George, Ben
AU - MacKinnon, Alexander C.
AU - Thompson, Jonathan
AU - Singh, Rajbir
AU - Jacob, Robin
AU - Kasuganti, Deepa
AU - Shah, Neel
AU - Day, Roger
AU - Galluzzi, Lorenzo
AU - Gardner, Mark
AU - Morrison, Carl
N1 - Publisher Copyright:
© 2019 The Author(s).
PY - 2019/1/24
Y1 - 2019/1/24
N2 - 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.
AB - 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.
KW - Atezolizumab
KW - Avelumab
KW - Biomarker
KW - Durvalumab
KW - Nivolumab
KW - PD-L1
KW - Pembrolizumab
KW - cancer immunotherapy
UR - http://www.scopus.com/inward/record.url?scp=85060525068&partnerID=8YFLogxK
U2 - 10.1186/s40425-018-0489-5
DO - 10.1186/s40425-018-0489-5
M3 - Article
C2 - 30678715
SN - 2051-1426
VL - 7
SP - 18
JO - Journal for ImmunoTherapy of Cancer
JF - Journal for ImmunoTherapy of Cancer
IS - 1
M1 - 18
ER -