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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...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2020
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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 |
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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 |
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