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Advances in efficacy prediction and monitoring of neoadjuvant immunotherapy for non-small cell lung cancer

The use of immune checkpoint inhibitors (ICIs) has become mainstream in the treatment of non-small cell lung cancer (NSCLC). The idea of harnessing the immune system to fight cancer is fast developing. Neoadjuvant treatment in NSCLC is undergoing unprecedented change. Chemo-immunotherapy combination...

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Autores principales: Wang, Yunzhen, Huang, Sha, Feng, Xiangwei, Xu, Wangjue, Luo, Raojun, Zhu, Ziyi, Zeng, Qingxin, He, Zhengfu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10229830/
https://www.ncbi.nlm.nih.gov/pubmed/37265800
http://dx.doi.org/10.3389/fonc.2023.1145128
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author Wang, Yunzhen
Huang, Sha
Feng, Xiangwei
Xu, Wangjue
Luo, Raojun
Zhu, Ziyi
Zeng, Qingxin
He, Zhengfu
author_facet Wang, Yunzhen
Huang, Sha
Feng, Xiangwei
Xu, Wangjue
Luo, Raojun
Zhu, Ziyi
Zeng, Qingxin
He, Zhengfu
author_sort Wang, Yunzhen
collection PubMed
description The use of immune checkpoint inhibitors (ICIs) has become mainstream in the treatment of non-small cell lung cancer (NSCLC). The idea of harnessing the immune system to fight cancer is fast developing. Neoadjuvant treatment in NSCLC is undergoing unprecedented change. Chemo-immunotherapy combinations not only seem to achieve population-wide treating coverage irrespective of PD-L1 expression but also enable achieving a pathological complete response (pCR). Despite these recent advancements in neoadjuvant chemo-immunotherapy, not all patients respond favorably to treatment with ICIs plus chemo and may even suffer from severe immune-related adverse effects (irAEs). Similar to selection for target therapy, identifying patients most likely to benefit from chemo-immunotherapy may be valuable. Recently, several prognostic and predictive factors associated with the efficacy of neoadjuvant immunotherapy in NSCLC, such as tumor-intrinsic biomarkers, tumor microenvironment biomarkers, liquid biopsies, microbiota, metabolic profiles, and clinical characteristics, have been described. However, a specific and sensitive biomarker remains to be identified. Recently, the construction of prediction models for ICI therapy using novel tools, such as multi-omics factors, proteomic tests, host immune classifiers, and machine learning algorithms, has gained attention. In this review, we provide a comprehensive overview of the different positive prognostic and predictive factors in treating preoperative patients with ICIs, highlight the recent advances made in the efficacy prediction of neoadjuvant immunotherapy, and provide an outlook for joint predictors.
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spelling pubmed-102298302023-06-01 Advances in efficacy prediction and monitoring of neoadjuvant immunotherapy for non-small cell lung cancer Wang, Yunzhen Huang, Sha Feng, Xiangwei Xu, Wangjue Luo, Raojun Zhu, Ziyi Zeng, Qingxin He, Zhengfu Front Oncol Oncology The use of immune checkpoint inhibitors (ICIs) has become mainstream in the treatment of non-small cell lung cancer (NSCLC). The idea of harnessing the immune system to fight cancer is fast developing. Neoadjuvant treatment in NSCLC is undergoing unprecedented change. Chemo-immunotherapy combinations not only seem to achieve population-wide treating coverage irrespective of PD-L1 expression but also enable achieving a pathological complete response (pCR). Despite these recent advancements in neoadjuvant chemo-immunotherapy, not all patients respond favorably to treatment with ICIs plus chemo and may even suffer from severe immune-related adverse effects (irAEs). Similar to selection for target therapy, identifying patients most likely to benefit from chemo-immunotherapy may be valuable. Recently, several prognostic and predictive factors associated with the efficacy of neoadjuvant immunotherapy in NSCLC, such as tumor-intrinsic biomarkers, tumor microenvironment biomarkers, liquid biopsies, microbiota, metabolic profiles, and clinical characteristics, have been described. However, a specific and sensitive biomarker remains to be identified. Recently, the construction of prediction models for ICI therapy using novel tools, such as multi-omics factors, proteomic tests, host immune classifiers, and machine learning algorithms, has gained attention. In this review, we provide a comprehensive overview of the different positive prognostic and predictive factors in treating preoperative patients with ICIs, highlight the recent advances made in the efficacy prediction of neoadjuvant immunotherapy, and provide an outlook for joint predictors. Frontiers Media S.A. 2023-05-17 /pmc/articles/PMC10229830/ /pubmed/37265800 http://dx.doi.org/10.3389/fonc.2023.1145128 Text en Copyright © 2023 Wang, Huang, Feng, Xu, Luo, Zhu, Zeng and He 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 Oncology
Wang, Yunzhen
Huang, Sha
Feng, Xiangwei
Xu, Wangjue
Luo, Raojun
Zhu, Ziyi
Zeng, Qingxin
He, Zhengfu
Advances in efficacy prediction and monitoring of neoadjuvant immunotherapy for non-small cell lung cancer
title Advances in efficacy prediction and monitoring of neoadjuvant immunotherapy for non-small cell lung cancer
title_full Advances in efficacy prediction and monitoring of neoadjuvant immunotherapy for non-small cell lung cancer
title_fullStr Advances in efficacy prediction and monitoring of neoadjuvant immunotherapy for non-small cell lung cancer
title_full_unstemmed Advances in efficacy prediction and monitoring of neoadjuvant immunotherapy for non-small cell lung cancer
title_short Advances in efficacy prediction and monitoring of neoadjuvant immunotherapy for non-small cell lung cancer
title_sort advances in efficacy prediction and monitoring of neoadjuvant immunotherapy for non-small cell lung cancer
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10229830/
https://www.ncbi.nlm.nih.gov/pubmed/37265800
http://dx.doi.org/10.3389/fonc.2023.1145128
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