Cargando…

A multiparametric approach to improve the prediction of response to immunotherapy in patients with metastatic NSCLC

BACKGROUND: It is still unclear how to combine biomarkers to identify patients who will truly benefit from anti-PD-1 agents in NSCLC. This study investigates exosomal mRNA expression of PD-L1 and IFN-γ, PD-L1 polymorphisms, tumor mutational load (TML) in circulating cell-free DNA (cfDNA) and radiomi...

Descripción completa

Detalles Bibliográficos
Autores principales: Del Re, Marzia, Cucchiara, Federico, Rofi, Eleonora, Fontanelli, Lorenzo, Petrini, Iacopo, Gri, Nicole, Pasquini, Giulia, Rizzo, Mimma, Gabelloni, Michela, Belluomini, Lorenzo, Crucitta, Stefania, Ciampi, Raffaele, Frassoldati, Antonio, Neri, Emanuele, Porta, Camillo, Danesi, Romano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8139911/
https://www.ncbi.nlm.nih.gov/pubmed/33315149
http://dx.doi.org/10.1007/s00262-020-02810-6
_version_ 1783696086345449472
author Del Re, Marzia
Cucchiara, Federico
Rofi, Eleonora
Fontanelli, Lorenzo
Petrini, Iacopo
Gri, Nicole
Pasquini, Giulia
Rizzo, Mimma
Gabelloni, Michela
Belluomini, Lorenzo
Crucitta, Stefania
Ciampi, Raffaele
Frassoldati, Antonio
Neri, Emanuele
Porta, Camillo
Danesi, Romano
author_facet Del Re, Marzia
Cucchiara, Federico
Rofi, Eleonora
Fontanelli, Lorenzo
Petrini, Iacopo
Gri, Nicole
Pasquini, Giulia
Rizzo, Mimma
Gabelloni, Michela
Belluomini, Lorenzo
Crucitta, Stefania
Ciampi, Raffaele
Frassoldati, Antonio
Neri, Emanuele
Porta, Camillo
Danesi, Romano
author_sort Del Re, Marzia
collection PubMed
description BACKGROUND: It is still unclear how to combine biomarkers to identify patients who will truly benefit from anti-PD-1 agents in NSCLC. This study investigates exosomal mRNA expression of PD-L1 and IFN-γ, PD-L1 polymorphisms, tumor mutational load (TML) in circulating cell-free DNA (cfDNA) and radiomic features as possible predictive markers of response to nivolumab and pembrolizumab in metastatic NSCLC patients. METHODS: Patients were enrolled and blood (12 ml) was collected at baseline before receiving anti-PD-1 therapy. Exosome-derived mRNA and cfDNA were extracted to analyse PD-L1 and IFN-γ expression and tumor mutational load (TML) by digital droplet PCR (ddPCR) and next-generation sequencing (NGS), respectively. The PD-L1 single nucleotide polymorphisms (SNPs) c.-14-368 T > C and c.*395G > C, were analysed on genomic DNA by Real-Time PCR. A radiomic analysis was performed on the QUIBIM Precision(®) V3.0 platform. RESULTS: Thirty-eight patients were enrolled. High baseline IFN-γ was independently associated with shorter median PFS (5.6 months vs. not reached p = 0.0057), and levels of PD-L1 showed an increase at 3 months vs. baseline in patients who progressed (p = 0.01). PD-L1 baseline levels showed significant direct and inverse relationships with radiomic features. Radiomic features also inversely correlated with PD-L1 expression in tumor tissue. In subjects receiving nivolumab, median PFS was shorter in carriers of c.*395GG vs. c.*395GC/CC genotype (2.3 months vs. not reached, p = 0.041). Lastly, responders had higher non-synonymous mutations and more links between co-occurring genetic somatic mutations and ARID1A alterations as well. CONCLUSIONS: A combined multiparametric approach may provide a better understanding of the molecular determinants of response to immunotherapy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00262-020-02810-6.
format Online
Article
Text
id pubmed-8139911
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Springer Berlin Heidelberg
record_format MEDLINE/PubMed
spelling pubmed-81399112021-06-03 A multiparametric approach to improve the prediction of response to immunotherapy in patients with metastatic NSCLC Del Re, Marzia Cucchiara, Federico Rofi, Eleonora Fontanelli, Lorenzo Petrini, Iacopo Gri, Nicole Pasquini, Giulia Rizzo, Mimma Gabelloni, Michela Belluomini, Lorenzo Crucitta, Stefania Ciampi, Raffaele Frassoldati, Antonio Neri, Emanuele Porta, Camillo Danesi, Romano Cancer Immunol Immunother Original Article BACKGROUND: It is still unclear how to combine biomarkers to identify patients who will truly benefit from anti-PD-1 agents in NSCLC. This study investigates exosomal mRNA expression of PD-L1 and IFN-γ, PD-L1 polymorphisms, tumor mutational load (TML) in circulating cell-free DNA (cfDNA) and radiomic features as possible predictive markers of response to nivolumab and pembrolizumab in metastatic NSCLC patients. METHODS: Patients were enrolled and blood (12 ml) was collected at baseline before receiving anti-PD-1 therapy. Exosome-derived mRNA and cfDNA were extracted to analyse PD-L1 and IFN-γ expression and tumor mutational load (TML) by digital droplet PCR (ddPCR) and next-generation sequencing (NGS), respectively. The PD-L1 single nucleotide polymorphisms (SNPs) c.-14-368 T > C and c.*395G > C, were analysed on genomic DNA by Real-Time PCR. A radiomic analysis was performed on the QUIBIM Precision(®) V3.0 platform. RESULTS: Thirty-eight patients were enrolled. High baseline IFN-γ was independently associated with shorter median PFS (5.6 months vs. not reached p = 0.0057), and levels of PD-L1 showed an increase at 3 months vs. baseline in patients who progressed (p = 0.01). PD-L1 baseline levels showed significant direct and inverse relationships with radiomic features. Radiomic features also inversely correlated with PD-L1 expression in tumor tissue. In subjects receiving nivolumab, median PFS was shorter in carriers of c.*395GG vs. c.*395GC/CC genotype (2.3 months vs. not reached, p = 0.041). Lastly, responders had higher non-synonymous mutations and more links between co-occurring genetic somatic mutations and ARID1A alterations as well. CONCLUSIONS: A combined multiparametric approach may provide a better understanding of the molecular determinants of response to immunotherapy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00262-020-02810-6. Springer Berlin Heidelberg 2020-12-14 2021 /pmc/articles/PMC8139911/ /pubmed/33315149 http://dx.doi.org/10.1007/s00262-020-02810-6 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Article
Del Re, Marzia
Cucchiara, Federico
Rofi, Eleonora
Fontanelli, Lorenzo
Petrini, Iacopo
Gri, Nicole
Pasquini, Giulia
Rizzo, Mimma
Gabelloni, Michela
Belluomini, Lorenzo
Crucitta, Stefania
Ciampi, Raffaele
Frassoldati, Antonio
Neri, Emanuele
Porta, Camillo
Danesi, Romano
A multiparametric approach to improve the prediction of response to immunotherapy in patients with metastatic NSCLC
title A multiparametric approach to improve the prediction of response to immunotherapy in patients with metastatic NSCLC
title_full A multiparametric approach to improve the prediction of response to immunotherapy in patients with metastatic NSCLC
title_fullStr A multiparametric approach to improve the prediction of response to immunotherapy in patients with metastatic NSCLC
title_full_unstemmed A multiparametric approach to improve the prediction of response to immunotherapy in patients with metastatic NSCLC
title_short A multiparametric approach to improve the prediction of response to immunotherapy in patients with metastatic NSCLC
title_sort multiparametric approach to improve the prediction of response to immunotherapy in patients with metastatic nsclc
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8139911/
https://www.ncbi.nlm.nih.gov/pubmed/33315149
http://dx.doi.org/10.1007/s00262-020-02810-6
work_keys_str_mv AT delremarzia amultiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT cucchiarafederico amultiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT rofieleonora amultiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT fontanellilorenzo amultiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT petriniiacopo amultiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT grinicole amultiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT pasquinigiulia amultiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT rizzomimma amultiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT gabellonimichela amultiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT belluominilorenzo amultiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT crucittastefania amultiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT ciampiraffaele amultiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT frassoldatiantonio amultiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT neriemanuele amultiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT portacamillo amultiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT danesiromano amultiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT delremarzia multiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT cucchiarafederico multiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT rofieleonora multiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT fontanellilorenzo multiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT petriniiacopo multiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT grinicole multiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT pasquinigiulia multiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT rizzomimma multiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT gabellonimichela multiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT belluominilorenzo multiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT crucittastefania multiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT ciampiraffaele multiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT frassoldatiantonio multiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT neriemanuele multiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT portacamillo multiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc
AT danesiromano multiparametricapproachtoimprovethepredictionofresponsetoimmunotherapyinpatientswithmetastaticnsclc