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An immune risk score predicts progression-free survival of melanoma patients in South China receiving anti-PD-1 inhibitor therapy—a retrospective cohort study examining 66 circulating immune cell subsets
INTRODUCTION: Immune checkpoint blockade inhibitor (ICI) therapy offers significant survival benefits for malignant melanoma. However, some patients were observed to be in disease progression after the first few treatment cycles. As such, it is urgent to find convenient and accessible indicators tha...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9768215/ https://www.ncbi.nlm.nih.gov/pubmed/36569825 http://dx.doi.org/10.3389/fimmu.2022.1012673 |
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author | Chi, Peidong Jiang, Hang Li, Dandan Li, Jingjing Wen, Xizhi Ding, Qiyue Chen, Linbin Zhang, Xiaoshi Huang, Junqi Ding, Ya |
author_facet | Chi, Peidong Jiang, Hang Li, Dandan Li, Jingjing Wen, Xizhi Ding, Qiyue Chen, Linbin Zhang, Xiaoshi Huang, Junqi Ding, Ya |
author_sort | Chi, Peidong |
collection | PubMed |
description | INTRODUCTION: Immune checkpoint blockade inhibitor (ICI) therapy offers significant survival benefits for malignant melanoma. However, some patients were observed to be in disease progression after the first few treatment cycles. As such, it is urgent to find convenient and accessible indicators that assess whether patients can benefit from ICI therapy. METHODS: In the training cohort, flow cytometry was used to determine the absolute values of 66 immune cell subsets in the peripheral blood of melanoma patients (n=29) before treatment with anti-PD-1 inhibitors. The least absolute shrinkage and selection operator (LASSO) Cox regression model was followed for the efficacy of each subset in predicting progression-free survival. Then we validated the performance of the selected model in validation cohorts (n=20), and developed a nomogram for clinical use. RESULTS: A prognostic immune risk score composed of CD1c(+) dendritic cells and three subsets of T cells (CD8(+)CD28(+), CD3(+)TCRab(+)HLA-DR(+), CD3(+)TCRgd(+)HLA-DR(+)) with a higher prognostic power than individual features (AUC = 0.825). Using this model, patients in the training cohort were divided into high- and low-risk groups with significant differences in mean progression-free survival (3.6 vs. 12.3 months), including disease control rate (41.2% vs. 91.7%), and objective response rate (17.6% vs. 41.6%). Integrating four-immune cell-subset based classifiers and three clinicopathologic risk factors can help to predict which patients might benefit from anti-PD-1 antibody inhibitors and remind potential non-responders to pursue effective treatment options in a timely way. CONCLUSIONS: The prognostic immune risk score including the innate immune and adaptive immune cell populations could provide an accurate prediction efficacy in malignant melanoma patients with ICI therapy. |
format | Online Article Text |
id | pubmed-9768215 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-97682152022-12-22 An immune risk score predicts progression-free survival of melanoma patients in South China receiving anti-PD-1 inhibitor therapy—a retrospective cohort study examining 66 circulating immune cell subsets Chi, Peidong Jiang, Hang Li, Dandan Li, Jingjing Wen, Xizhi Ding, Qiyue Chen, Linbin Zhang, Xiaoshi Huang, Junqi Ding, Ya Front Immunol Immunology INTRODUCTION: Immune checkpoint blockade inhibitor (ICI) therapy offers significant survival benefits for malignant melanoma. However, some patients were observed to be in disease progression after the first few treatment cycles. As such, it is urgent to find convenient and accessible indicators that assess whether patients can benefit from ICI therapy. METHODS: In the training cohort, flow cytometry was used to determine the absolute values of 66 immune cell subsets in the peripheral blood of melanoma patients (n=29) before treatment with anti-PD-1 inhibitors. The least absolute shrinkage and selection operator (LASSO) Cox regression model was followed for the efficacy of each subset in predicting progression-free survival. Then we validated the performance of the selected model in validation cohorts (n=20), and developed a nomogram for clinical use. RESULTS: A prognostic immune risk score composed of CD1c(+) dendritic cells and three subsets of T cells (CD8(+)CD28(+), CD3(+)TCRab(+)HLA-DR(+), CD3(+)TCRgd(+)HLA-DR(+)) with a higher prognostic power than individual features (AUC = 0.825). Using this model, patients in the training cohort were divided into high- and low-risk groups with significant differences in mean progression-free survival (3.6 vs. 12.3 months), including disease control rate (41.2% vs. 91.7%), and objective response rate (17.6% vs. 41.6%). Integrating four-immune cell-subset based classifiers and three clinicopathologic risk factors can help to predict which patients might benefit from anti-PD-1 antibody inhibitors and remind potential non-responders to pursue effective treatment options in a timely way. CONCLUSIONS: The prognostic immune risk score including the innate immune and adaptive immune cell populations could provide an accurate prediction efficacy in malignant melanoma patients with ICI therapy. Frontiers Media S.A. 2022-12-07 /pmc/articles/PMC9768215/ /pubmed/36569825 http://dx.doi.org/10.3389/fimmu.2022.1012673 Text en Copyright © 2022 Chi, Jiang, Li, Li, Wen, Ding, Chen, Zhang, Huang and Ding https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Immunology Chi, Peidong Jiang, Hang Li, Dandan Li, Jingjing Wen, Xizhi Ding, Qiyue Chen, Linbin Zhang, Xiaoshi Huang, Junqi Ding, Ya An immune risk score predicts progression-free survival of melanoma patients in South China receiving anti-PD-1 inhibitor therapy—a retrospective cohort study examining 66 circulating immune cell subsets |
title | An immune risk score predicts progression-free survival of melanoma patients in South China receiving anti-PD-1 inhibitor therapy—a retrospective cohort study examining 66 circulating immune cell subsets |
title_full | An immune risk score predicts progression-free survival of melanoma patients in South China receiving anti-PD-1 inhibitor therapy—a retrospective cohort study examining 66 circulating immune cell subsets |
title_fullStr | An immune risk score predicts progression-free survival of melanoma patients in South China receiving anti-PD-1 inhibitor therapy—a retrospective cohort study examining 66 circulating immune cell subsets |
title_full_unstemmed | An immune risk score predicts progression-free survival of melanoma patients in South China receiving anti-PD-1 inhibitor therapy—a retrospective cohort study examining 66 circulating immune cell subsets |
title_short | An immune risk score predicts progression-free survival of melanoma patients in South China receiving anti-PD-1 inhibitor therapy—a retrospective cohort study examining 66 circulating immune cell subsets |
title_sort | immune risk score predicts progression-free survival of melanoma patients in south china receiving anti-pd-1 inhibitor therapy—a retrospective cohort study examining 66 circulating immune cell subsets |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9768215/ https://www.ncbi.nlm.nih.gov/pubmed/36569825 http://dx.doi.org/10.3389/fimmu.2022.1012673 |
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