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

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 b...

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Autores: Morrison, Carl, Pabla, Sarabjot, Conroy, Jeffrey M., Nesline, Mary K., Glenn, Sean T., Dressman, Devin, Cruz Merino, Luis de la, Ernstoff, Marc S.
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2018
País:España
Recursos:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/156114
Acesso em linha:https://hdl.handle.net/11441/156114
https://doi.org/10.1186/s40425-018-0344-8
Access Level:acceso abierto
Palavra-chave:Pembrolizumab
Nivolumab
Ipilimumab
Algorithmic analysis
Inflamed
Borderline
Immune Desert
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repository_id_str
spelling Predicting response to checkpoint inhibitors in melanoma beyond PD-L1 and mutational burdenMorrison, CarlPabla, SarabjotConroy, Jeffrey M.Nesline, Mary K.Glenn, Sean T.Dressman, DevinCruz Merino, Luis de laErnstoff, Marc S.PembrolizumabNivolumabIpilimumabAlgorithmic analysisInflamedBorderlineImmune DesertBackground: 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.BMCMedicinaCTS151: Bioquímica médica2018info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttps://hdl.handle.net/11441/156114https://doi.org/10.1186/s40425-018-0344-8reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésJournal of Immunotherapy of Cancer, 6 (1), 32.https://jitc.bmj.com/content/6/1/32info:eu-repo/semantics/openAccessoai:idus.us.es:11441/1561142026-06-17T12:51:07Z
dc.title.none.fl_str_mv Predicting response to checkpoint inhibitors in melanoma beyond PD-L1 and mutational burden
title Predicting response to checkpoint inhibitors in melanoma beyond PD-L1 and mutational burden
spellingShingle Predicting response to checkpoint inhibitors in melanoma beyond PD-L1 and mutational burden
Morrison, Carl
Pembrolizumab
Nivolumab
Ipilimumab
Algorithmic analysis
Inflamed
Borderline
Immune Desert
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
dc.creator.none.fl_str_mv Morrison, Carl
Pabla, Sarabjot
Conroy, Jeffrey M.
Nesline, Mary K.
Glenn, Sean T.
Dressman, Devin
Cruz Merino, Luis de la
Ernstoff, Marc S.
author Morrison, Carl
author_facet Morrison, Carl
Pabla, Sarabjot
Conroy, Jeffrey M.
Nesline, Mary K.
Glenn, Sean T.
Dressman, Devin
Cruz Merino, Luis de la
Ernstoff, Marc S.
author_role author
author2 Pabla, Sarabjot
Conroy, Jeffrey M.
Nesline, Mary K.
Glenn, Sean T.
Dressman, Devin
Cruz Merino, Luis de la
Ernstoff, Marc S.
author2_role author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Medicina
CTS151: Bioquímica médica
dc.subject.none.fl_str_mv Pembrolizumab
Nivolumab
Ipilimumab
Algorithmic analysis
Inflamed
Borderline
Immune Desert
topic Pembrolizumab
Nivolumab
Ipilimumab
Algorithmic analysis
Inflamed
Borderline
Immune Desert
description 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.
publishDate 2018
dc.date.none.fl_str_mv 2018
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/11441/156114
https://doi.org/10.1186/s40425-018-0344-8
url https://hdl.handle.net/11441/156114
https://doi.org/10.1186/s40425-018-0344-8
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Journal of Immunotherapy of Cancer, 6 (1), 32.
https://jitc.bmj.com/content/6/1/32
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv BMC
publisher.none.fl_str_mv BMC
dc.source.none.fl_str_mv reponame:idUS. Depósito de Investigación de la Universidad de Sevilla
instname:Universidad de Sevilla (US)
instname_str Universidad de Sevilla (US)
reponame_str idUS. Depósito de Investigación de la Universidad de Sevilla
collection idUS. Depósito de Investigación de la Universidad de Sevilla
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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