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Back to simplicity: a four-marker blood cell score to quantify prognostically relevant myeloid cells in melanoma patients

BACKGROUND: Myeloid-derived suppressor cells (MDSC), a cornerstone of cancer-related immunosuppression, influence response to therapy and disease outcomes in melanoma patients. Nevertheless, their quantification is far from being integrated into routine clinical practice mostly because of the comple...

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Autores principales: Huber, Veronica, Di Guardo, Lorenza, Lalli, Luca, Giardiello, Daniele, Cova, Agata, Squarcina, Paola, Frati, Paola, Di Giacomo, Anna Maria, Pilla, Lorenzo, Tazzari, Marcella, Camisaschi, Chiara, Arienti, Flavio, Castelli, Chiara, Rodolfo, Monica, Beretta, Valeria, Di Nicola, Massimo, Maio, Michele, Del Vecchio, Michele, de Braud, Filippo, Mariani, Luigi, Rivoltini, Licia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7887358/
https://www.ncbi.nlm.nih.gov/pubmed/33589521
http://dx.doi.org/10.1136/jitc-2020-001167
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author Huber, Veronica
Di Guardo, Lorenza
Lalli, Luca
Giardiello, Daniele
Cova, Agata
Squarcina, Paola
Frati, Paola
Di Giacomo, Anna Maria
Pilla, Lorenzo
Tazzari, Marcella
Camisaschi, Chiara
Arienti, Flavio
Castelli, Chiara
Rodolfo, Monica
Beretta, Valeria
Di Nicola, Massimo
Maio, Michele
Del Vecchio, Michele
de Braud, Filippo
Mariani, Luigi
Rivoltini, Licia
author_facet Huber, Veronica
Di Guardo, Lorenza
Lalli, Luca
Giardiello, Daniele
Cova, Agata
Squarcina, Paola
Frati, Paola
Di Giacomo, Anna Maria
Pilla, Lorenzo
Tazzari, Marcella
Camisaschi, Chiara
Arienti, Flavio
Castelli, Chiara
Rodolfo, Monica
Beretta, Valeria
Di Nicola, Massimo
Maio, Michele
Del Vecchio, Michele
de Braud, Filippo
Mariani, Luigi
Rivoltini, Licia
author_sort Huber, Veronica
collection PubMed
description BACKGROUND: Myeloid-derived suppressor cells (MDSC), a cornerstone of cancer-related immunosuppression, influence response to therapy and disease outcomes in melanoma patients. Nevertheless, their quantification is far from being integrated into routine clinical practice mostly because of the complex and still evolving phenotypic signatures applied to define the cell subsets. Here, we used a multistep downsizing process to verify whether a core of few markers could be sufficient to capture the prognostic potential of myeloid cells in peripheral blood mononuclear cells (PBMC) of metastatic melanoma patients. METHODS: In baseline frozen PBMC from a total of 143 stage IIIc to IV melanoma patients, we first assessed the relevant or redundant expression of myeloid and MDSC-related markers by flow cytometry (screening set, n=23 patients). Subsequently, we applied the identified panel to the development set samples (n=59 patients undergoing first/second-line therapy) to obtain prognostic variables associated with overall survival (OS) and progression-free survival (PFS) by machine learning adaptive index modeling. Finally, the identified score was confirmed in a validation set (n=61) and compared with standard clinical prognostic factors to assess its additive value in patient prognostication. RESULTS: This selection process led to the identification of what we defined myeloid index score (MIS), which is composed by four cell subsets (CD14(+), CD14(+)HLA-DR(neg), CD14(+)PD-L1(+) and CD15(+) cells), whose frequencies above cut-offs stratified melanoma patients according to progressively worse prognosis. Patients with a MIS=0, showing no over-threshold value of MIS subsets, had the best clinical outcome, with a median survival of >33.6 months, while in patients with MIS 1→3, OS deteriorated from 10.9 to 6.8 and 6.0 months as the MIS increased (p<0.0001, c-index=0.745). MIS clustered patients into risk groups also according to PFS (p<0.0001). The inverse correlation between MIS and survival was confirmed in the validation set, was independent of the type of therapy and was not interfered by clinical prognostic factors. MIS HR was remarkably superior to that of lactate dehydrogenase, tumor burden and neutrophil-to-lymphocyte ratio. CONCLUSION: The MIS >0 identifies melanoma patients with a more aggressive disease, thus acting as a simple blood biomarker that can help tailoring therapeutic choices in real-life oncology.
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spelling pubmed-78873582021-03-03 Back to simplicity: a four-marker blood cell score to quantify prognostically relevant myeloid cells in melanoma patients Huber, Veronica Di Guardo, Lorenza Lalli, Luca Giardiello, Daniele Cova, Agata Squarcina, Paola Frati, Paola Di Giacomo, Anna Maria Pilla, Lorenzo Tazzari, Marcella Camisaschi, Chiara Arienti, Flavio Castelli, Chiara Rodolfo, Monica Beretta, Valeria Di Nicola, Massimo Maio, Michele Del Vecchio, Michele de Braud, Filippo Mariani, Luigi Rivoltini, Licia J Immunother Cancer Immunotherapy Biomarkers BACKGROUND: Myeloid-derived suppressor cells (MDSC), a cornerstone of cancer-related immunosuppression, influence response to therapy and disease outcomes in melanoma patients. Nevertheless, their quantification is far from being integrated into routine clinical practice mostly because of the complex and still evolving phenotypic signatures applied to define the cell subsets. Here, we used a multistep downsizing process to verify whether a core of few markers could be sufficient to capture the prognostic potential of myeloid cells in peripheral blood mononuclear cells (PBMC) of metastatic melanoma patients. METHODS: In baseline frozen PBMC from a total of 143 stage IIIc to IV melanoma patients, we first assessed the relevant or redundant expression of myeloid and MDSC-related markers by flow cytometry (screening set, n=23 patients). Subsequently, we applied the identified panel to the development set samples (n=59 patients undergoing first/second-line therapy) to obtain prognostic variables associated with overall survival (OS) and progression-free survival (PFS) by machine learning adaptive index modeling. Finally, the identified score was confirmed in a validation set (n=61) and compared with standard clinical prognostic factors to assess its additive value in patient prognostication. RESULTS: This selection process led to the identification of what we defined myeloid index score (MIS), which is composed by four cell subsets (CD14(+), CD14(+)HLA-DR(neg), CD14(+)PD-L1(+) and CD15(+) cells), whose frequencies above cut-offs stratified melanoma patients according to progressively worse prognosis. Patients with a MIS=0, showing no over-threshold value of MIS subsets, had the best clinical outcome, with a median survival of >33.6 months, while in patients with MIS 1→3, OS deteriorated from 10.9 to 6.8 and 6.0 months as the MIS increased (p<0.0001, c-index=0.745). MIS clustered patients into risk groups also according to PFS (p<0.0001). The inverse correlation between MIS and survival was confirmed in the validation set, was independent of the type of therapy and was not interfered by clinical prognostic factors. MIS HR was remarkably superior to that of lactate dehydrogenase, tumor burden and neutrophil-to-lymphocyte ratio. CONCLUSION: The MIS >0 identifies melanoma patients with a more aggressive disease, thus acting as a simple blood biomarker that can help tailoring therapeutic choices in real-life oncology. BMJ Publishing Group 2021-02-15 /pmc/articles/PMC7887358/ /pubmed/33589521 http://dx.doi.org/10.1136/jitc-2020-001167 Text en © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/ http://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See http://creativecommons.org/licenses/by-nc/4.0/.
spellingShingle Immunotherapy Biomarkers
Huber, Veronica
Di Guardo, Lorenza
Lalli, Luca
Giardiello, Daniele
Cova, Agata
Squarcina, Paola
Frati, Paola
Di Giacomo, Anna Maria
Pilla, Lorenzo
Tazzari, Marcella
Camisaschi, Chiara
Arienti, Flavio
Castelli, Chiara
Rodolfo, Monica
Beretta, Valeria
Di Nicola, Massimo
Maio, Michele
Del Vecchio, Michele
de Braud, Filippo
Mariani, Luigi
Rivoltini, Licia
Back to simplicity: a four-marker blood cell score to quantify prognostically relevant myeloid cells in melanoma patients
title Back to simplicity: a four-marker blood cell score to quantify prognostically relevant myeloid cells in melanoma patients
title_full Back to simplicity: a four-marker blood cell score to quantify prognostically relevant myeloid cells in melanoma patients
title_fullStr Back to simplicity: a four-marker blood cell score to quantify prognostically relevant myeloid cells in melanoma patients
title_full_unstemmed Back to simplicity: a four-marker blood cell score to quantify prognostically relevant myeloid cells in melanoma patients
title_short Back to simplicity: a four-marker blood cell score to quantify prognostically relevant myeloid cells in melanoma patients
title_sort back to simplicity: a four-marker blood cell score to quantify prognostically relevant myeloid cells in melanoma patients
topic Immunotherapy Biomarkers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7887358/
https://www.ncbi.nlm.nih.gov/pubmed/33589521
http://dx.doi.org/10.1136/jitc-2020-001167
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