Predicting response to checkpoint inhibitors in melanoma beyond PD-L1 and mutational burden

Abstract Background Immune checkpoint inhibitors (ICIs) have changed the clinical management of melanoma. However, not all patients respond, and current biomarkers including PD-L1 and mutational burden show incomplete predictive performance. The clinical validity and utility of complex biomarkers ha...

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Main Authors: Carl Morrison, Sarabjot Pabla, Jeffrey M. Conroy, Mary K. Nesline, Sean T. Glenn, Devin Dressman, Antonios Papanicolau-Sengos, Blake Burgher, Jonathan Andreas, Vincent Giamo, Moachun Qin, Yirong Wang, Felicia L. Lenzo, Angela Omilian, Wiam Bshara, Matthew Zibelman, Pooja Ghatalia, Konstantin Dragnev, Keisuke Shirai, Katherine G. Madden, Laura J. Tafe, Neel Shah, Deepa Kasuganti, Luis de la Cruz-Merino, Isabel Araujo, Yvonne Saenger, Margaret Bogardus, Miguel Villalona-Calero, Zuanel Diaz, Roger Day, Marcia Eisenberg, Steven M. Anderson, Igor Puzanov, Lorenzo Galluzzi, Mark Gardner, Marc S. Ernstoff
Format: Article
Language:English
Published: BMJ Publishing Group 2018-05-01
Series:Journal for ImmunoTherapy of Cancer
Subjects:
Online Access:http://link.springer.com/article/10.1186/s40425-018-0344-8
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author Carl Morrison
Sarabjot Pabla
Jeffrey M. Conroy
Mary K. Nesline
Sean T. Glenn
Devin Dressman
Antonios Papanicolau-Sengos
Blake Burgher
Jonathan Andreas
Vincent Giamo
Moachun Qin
Yirong Wang
Felicia L. Lenzo
Angela Omilian
Wiam Bshara
Matthew Zibelman
Pooja Ghatalia
Konstantin Dragnev
Keisuke Shirai
Katherine G. Madden
Laura J. Tafe
Neel Shah
Deepa Kasuganti
Luis de la Cruz-Merino
Isabel Araujo
Yvonne Saenger
Margaret Bogardus
Miguel Villalona-Calero
Zuanel Diaz
Roger Day
Marcia Eisenberg
Steven M. Anderson
Igor Puzanov
Lorenzo Galluzzi
Mark Gardner
Marc S. Ernstoff
spellingShingle Carl Morrison
Sarabjot Pabla
Jeffrey M. Conroy
Mary K. Nesline
Sean T. Glenn
Devin Dressman
Antonios Papanicolau-Sengos
Blake Burgher
Jonathan Andreas
Vincent Giamo
Moachun Qin
Yirong Wang
Felicia L. Lenzo
Angela Omilian
Wiam Bshara
Matthew Zibelman
Pooja Ghatalia
Konstantin Dragnev
Keisuke Shirai
Katherine G. Madden
Laura J. Tafe
Neel Shah
Deepa Kasuganti
Luis de la Cruz-Merino
Isabel Araujo
Yvonne Saenger
Margaret Bogardus
Miguel Villalona-Calero
Zuanel Diaz
Roger Day
Marcia Eisenberg
Steven M. Anderson
Igor Puzanov
Lorenzo Galluzzi
Mark Gardner
Marc S. Ernstoff
Predicting response to checkpoint inhibitors in melanoma beyond PD-L1 and mutational burden
Journal for ImmunoTherapy of Cancer
Pembrolizumab
Nivolumab
Ipilimumab
Algorithmic analysis
Inflamed
Borderline
author_facet Carl Morrison
Sarabjot Pabla
Jeffrey M. Conroy
Mary K. Nesline
Sean T. Glenn
Devin Dressman
Antonios Papanicolau-Sengos
Blake Burgher
Jonathan Andreas
Vincent Giamo
Moachun Qin
Yirong Wang
Felicia L. Lenzo
Angela Omilian
Wiam Bshara
Matthew Zibelman
Pooja Ghatalia
Konstantin Dragnev
Keisuke Shirai
Katherine G. Madden
Laura J. Tafe
Neel Shah
Deepa Kasuganti
Luis de la Cruz-Merino
Isabel Araujo
Yvonne Saenger
Margaret Bogardus
Miguel Villalona-Calero
Zuanel Diaz
Roger Day
Marcia Eisenberg
Steven M. Anderson
Igor Puzanov
Lorenzo Galluzzi
Mark Gardner
Marc S. Ernstoff
author_sort Carl Morrison
title Predicting response to checkpoint inhibitors in melanoma beyond PD-L1 and mutational burden
title_short Predicting response to checkpoint inhibitors in melanoma beyond PD-L1 and mutational burden
title_full Predicting response to checkpoint inhibitors in melanoma beyond PD-L1 and mutational burden
title_fullStr Predicting response to checkpoint inhibitors in melanoma beyond PD-L1 and mutational burden
title_full_unstemmed Predicting response to checkpoint inhibitors in melanoma beyond PD-L1 and mutational burden
title_sort predicting response to checkpoint inhibitors in melanoma beyond pd-l1 and mutational burden
publisher BMJ Publishing Group
series Journal for ImmunoTherapy of Cancer
issn 2051-1426
publishDate 2018-05-01
description Abstract Background Immune checkpoint inhibitors (ICIs) have changed the clinical management of melanoma. However, not all patients respond, and current biomarkers including PD-L1 and mutational burden show incomplete predictive performance. The clinical validity and utility of complex biomarkers have not been studied in melanoma. Methods Cutaneous metastatic melanoma patients at eight institutions were evaluated for PD-L1 expression, CD8+ T-cell infiltration pattern, mutational burden, and 394 immune transcript expression. PD-L1 IHC and mutational burden were assessed for association with overall survival (OS) in 94 patients treated prior to ICI approval by the FDA (historical-controls), and in 137 patients treated with ICIs. Unsupervised analysis revealed distinct immune-clusters with separate response rates. This comprehensive immune profiling data were then integrated to generate a continuous Response Score (RS) based upon response criteria (RECIST v.1.1). RS was developed using a single institution training cohort (n = 48) and subsequently tested in a separate eight institution validation cohort (n = 29) to mimic a real-world clinical scenario. Results PD-L1 positivity ≥1% correlated with response and OS in ICI-treated patients, but demonstrated limited predictive performance. High mutational burden was associated with response in ICI-treated patients, but not with OS. Comprehensive immune profiling using RS demonstrated higher sensitivity (72.2%) compared to PD-L1 IHC (34.25%) and tumor mutational burden (32.5%), but with similar specificity. Conclusions In this study, the response score derived from comprehensive immune profiling in a limited melanoma cohort showed improved predictive performance as compared to PD-L1 IHC and tumor mutational burden.
topic Pembrolizumab
Nivolumab
Ipilimumab
Algorithmic analysis
Inflamed
Borderline
url http://link.springer.com/article/10.1186/s40425-018-0344-8
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spelling doaj-956c5246c411433fb1a686b13fb6565c2020-11-25T02:20:52ZengBMJ Publishing GroupJournal for ImmunoTherapy of Cancer2051-14262018-05-016111210.1186/s40425-018-0344-8Predicting response to checkpoint inhibitors in melanoma beyond PD-L1 and mutational burdenCarl Morrison0Sarabjot Pabla1Jeffrey M. Conroy2Mary K. Nesline3Sean T. Glenn4Devin Dressman5Antonios Papanicolau-Sengos6Blake Burgher7Jonathan Andreas8Vincent Giamo9Moachun Qin10Yirong Wang11Felicia L. Lenzo12Angela Omilian13Wiam Bshara14Matthew Zibelman15Pooja Ghatalia16Konstantin Dragnev17Keisuke Shirai18Katherine G. Madden19Laura J. Tafe20Neel Shah21Deepa Kasuganti22Luis de la Cruz-Merino23Isabel Araujo24Yvonne Saenger25Margaret Bogardus26Miguel Villalona-Calero27Zuanel Diaz28Roger Day29Marcia Eisenberg30Steven M. Anderson31Igor Puzanov32Lorenzo Galluzzi33Mark Gardner34Marc S. Ernstoff35Center for Personalized Medicine, Roswell Park Comprehensive Cancer CenterOmniSeq Inc.Center for Personalized Medicine, Roswell Park Comprehensive Cancer CenterOmniSeq Inc.Cancer Genetics and Genomics, Roswell Park Comprehensive Cancer CenterOmniSeq Inc.OmniSeq Inc.OmniSeq Inc.OmniSeq Inc.OmniSeq Inc.OmniSeq Inc.OmniSeq Inc.OmniSeq Inc.Department of Pathology, Roswell Park Comprehensive Cancer CenterDepartment of Pathology, Roswell Park Comprehensive Cancer CenterDepartment of Hematology/Oncology, Fox Chase Cancer CenterDepartment of Hematology/Oncology, Fox Chase Cancer CenterDepartment of Hematology and Oncology, Dartmouth HitchcockDepartment of Hematology and Oncology, Dartmouth HitchcockDepartment of Hematology and Oncology, Dartmouth HitchcockDepartment of Hematology and Oncology, Dartmouth HitchcockDepartment of Pathology, Community HospitalDepartment of Pathology, Community HospitalDepartment of Clinical Oncology Development, Hospital Universitario Virgen MacarenaDepartment of Clinical Oncology Development, Hospital Universitario Virgen MacarenaDepartment of Medicine, Columbia UniversityDepartment of Medicine, Columbia UniversityMiami Cancer Institute, Baptist Health South FloridaMiami Cancer Institute, Baptist Health South FloridaDepartment of Biomedical Informatics and Biostatistics, University of PittsburghLaboratory Corporation of America HoldingsLaboratory Corporation of America HoldingsDepartment of Medicine, Roswell Park Comprehensive Cancer CenterDepartment of Radiation Oncology, Weill Cornell Medical CollegeOmniSeq Inc.Department of Medicine, Roswell Park Comprehensive Cancer CenterAbstract Background Immune checkpoint inhibitors (ICIs) have changed the clinical management of melanoma. However, not all patients respond, and current biomarkers including PD-L1 and mutational burden show incomplete predictive performance. The clinical validity and utility of complex biomarkers have not been studied in melanoma. Methods Cutaneous metastatic melanoma patients at eight institutions were evaluated for PD-L1 expression, CD8+ T-cell infiltration pattern, mutational burden, and 394 immune transcript expression. PD-L1 IHC and mutational burden were assessed for association with overall survival (OS) in 94 patients treated prior to ICI approval by the FDA (historical-controls), and in 137 patients treated with ICIs. Unsupervised analysis revealed distinct immune-clusters with separate response rates. This comprehensive immune profiling data were then integrated to generate a continuous Response Score (RS) based upon response criteria (RECIST v.1.1). RS was developed using a single institution training cohort (n = 48) and subsequently tested in a separate eight institution validation cohort (n = 29) to mimic a real-world clinical scenario. Results PD-L1 positivity ≥1% correlated with response and OS in ICI-treated patients, but demonstrated limited predictive performance. High mutational burden was associated with response in ICI-treated patients, but not with OS. Comprehensive immune profiling using RS demonstrated higher sensitivity (72.2%) compared to PD-L1 IHC (34.25%) and tumor mutational burden (32.5%), but with similar specificity. Conclusions In this study, the response score derived from comprehensive immune profiling in a limited melanoma cohort showed improved predictive performance as compared to PD-L1 IHC and tumor mutational burden.http://link.springer.com/article/10.1186/s40425-018-0344-8PembrolizumabNivolumabIpilimumabAlgorithmic analysisInflamedBorderline