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Next generation sequencing of PD-L1 for predicting response to immune checkpoint inhibitors
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...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6346512/ https://www.ncbi.nlm.nih.gov/pubmed/30678715 http://dx.doi.org/10.1186/s40425-018-0489-5 |
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author | 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 |
author_facet | 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 |
author_sort | Conroy, Jeffrey M. |
collection | PubMed |
description | 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s40425-018-0489-5) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6346512 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-63465122019-01-29 Next generation sequencing of PD-L1 for predicting response to immune checkpoint inhibitors 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 J Immunother Cancer Research Article 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s40425-018-0489-5) contains supplementary material, which is available to authorized users. BioMed Central 2019-01-24 /pmc/articles/PMC6346512/ /pubmed/30678715 http://dx.doi.org/10.1186/s40425-018-0489-5 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article 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 Next generation sequencing of PD-L1 for predicting response to immune checkpoint inhibitors |
title | Next generation sequencing of PD-L1 for predicting response to immune checkpoint inhibitors |
title_full | Next generation sequencing of PD-L1 for predicting response to immune checkpoint inhibitors |
title_fullStr | Next generation sequencing of PD-L1 for predicting response to immune checkpoint inhibitors |
title_full_unstemmed | Next generation sequencing of PD-L1 for predicting response to immune checkpoint inhibitors |
title_short | Next generation sequencing of PD-L1 for predicting response to immune checkpoint inhibitors |
title_sort | next generation sequencing of pd-l1 for predicting response to immune checkpoint inhibitors |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6346512/ https://www.ncbi.nlm.nih.gov/pubmed/30678715 http://dx.doi.org/10.1186/s40425-018-0489-5 |
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