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Screening biomarkers for predicting the efficacy of immunotherapy in patients with PD-L1 overexpression

PURPOSE: Immunotherapy plays an important role in non-small cell lung cancer (NSCLC); in particular, immune checkpoint inhibitors (ICIs) therapy has good therapeutic effects in PD-L1-positive patients. This study aims to screen NSCLC patients with PD-L1-positive expression and select effective bioma...

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Autores principales: Zhu, Xiaodan, Yu, Bo, Shen, Yanli, Zhao, Yan, Fu, Xiyujing, Zhu, Yunji, Gu, Guomin, Liu, Chunling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10587271/
https://www.ncbi.nlm.nih.gov/pubmed/37468609
http://dx.doi.org/10.1007/s00432-023-05160-9
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author Zhu, Xiaodan
Yu, Bo
Shen, Yanli
Zhao, Yan
Fu, Xiyujing
Zhu, Yunji
Gu, Guomin
Liu, Chunling
author_facet Zhu, Xiaodan
Yu, Bo
Shen, Yanli
Zhao, Yan
Fu, Xiyujing
Zhu, Yunji
Gu, Guomin
Liu, Chunling
author_sort Zhu, Xiaodan
collection PubMed
description PURPOSE: Immunotherapy plays an important role in non-small cell lung cancer (NSCLC); in particular, immune checkpoint inhibitors (ICIs) therapy has good therapeutic effects in PD-L1-positive patients. This study aims to screen NSCLC patients with PD-L1-positive expression and select effective biomarkers for ICI immunotherapy. METHODS: Collected tumor samples from the Affiliated Cancer Hospital of Xinjiang Medical University and 117 patients with stage III–IV NSCLC were included in the study. All patients were on first- or second-line therapy and not on targeted therapy. Based on the molecular profiles and clinical features, we screened biomarkers for predicting the efficacy of immunotherapy in patients with PD-L1 overexpression. RESULTS: 117 NSCLC patients receiving ICIs immunotherapy were enrolled. First, we found that immunotherapy was more effective in patients with positive PD-L1 expression. Second, we found that ROS1 gene mutations, KRAS gene mutations, tumor stage, and the endocrine system diseases history are independent prognostic factors for PD-L1 positive patients. Then we combined independent risk factors and constructed a new Nomogram to predict the therapeutic efficacy of ICIs immunotherapy in PD-L1 positive patients. The Nomogram integrates these factors into a prediction model, and the predicted C-statistic of 3 months, 6 months and 12 months are 0.85, 0.84 and 0.85, which represents the high predictive accuracy of the model. CONCLUSIONS: We have established a model that can predict the efficacy of ICIs immunotherapy in PD-L1 positive patients. The model consists of ROS1 gene mutations, KRAS gene mutations, tumor staging, and endocrine system disease history, and has good predictive ability. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00432-023-05160-9.
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spelling pubmed-105872712023-10-21 Screening biomarkers for predicting the efficacy of immunotherapy in patients with PD-L1 overexpression Zhu, Xiaodan Yu, Bo Shen, Yanli Zhao, Yan Fu, Xiyujing Zhu, Yunji Gu, Guomin Liu, Chunling J Cancer Res Clin Oncol Research PURPOSE: Immunotherapy plays an important role in non-small cell lung cancer (NSCLC); in particular, immune checkpoint inhibitors (ICIs) therapy has good therapeutic effects in PD-L1-positive patients. This study aims to screen NSCLC patients with PD-L1-positive expression and select effective biomarkers for ICI immunotherapy. METHODS: Collected tumor samples from the Affiliated Cancer Hospital of Xinjiang Medical University and 117 patients with stage III–IV NSCLC were included in the study. All patients were on first- or second-line therapy and not on targeted therapy. Based on the molecular profiles and clinical features, we screened biomarkers for predicting the efficacy of immunotherapy in patients with PD-L1 overexpression. RESULTS: 117 NSCLC patients receiving ICIs immunotherapy were enrolled. First, we found that immunotherapy was more effective in patients with positive PD-L1 expression. Second, we found that ROS1 gene mutations, KRAS gene mutations, tumor stage, and the endocrine system diseases history are independent prognostic factors for PD-L1 positive patients. Then we combined independent risk factors and constructed a new Nomogram to predict the therapeutic efficacy of ICIs immunotherapy in PD-L1 positive patients. The Nomogram integrates these factors into a prediction model, and the predicted C-statistic of 3 months, 6 months and 12 months are 0.85, 0.84 and 0.85, which represents the high predictive accuracy of the model. CONCLUSIONS: We have established a model that can predict the efficacy of ICIs immunotherapy in PD-L1 positive patients. The model consists of ROS1 gene mutations, KRAS gene mutations, tumor staging, and endocrine system disease history, and has good predictive ability. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00432-023-05160-9. Springer Berlin Heidelberg 2023-07-19 2023 /pmc/articles/PMC10587271/ /pubmed/37468609 http://dx.doi.org/10.1007/s00432-023-05160-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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 Research
Zhu, Xiaodan
Yu, Bo
Shen, Yanli
Zhao, Yan
Fu, Xiyujing
Zhu, Yunji
Gu, Guomin
Liu, Chunling
Screening biomarkers for predicting the efficacy of immunotherapy in patients with PD-L1 overexpression
title Screening biomarkers for predicting the efficacy of immunotherapy in patients with PD-L1 overexpression
title_full Screening biomarkers for predicting the efficacy of immunotherapy in patients with PD-L1 overexpression
title_fullStr Screening biomarkers for predicting the efficacy of immunotherapy in patients with PD-L1 overexpression
title_full_unstemmed Screening biomarkers for predicting the efficacy of immunotherapy in patients with PD-L1 overexpression
title_short Screening biomarkers for predicting the efficacy of immunotherapy in patients with PD-L1 overexpression
title_sort screening biomarkers for predicting the efficacy of immunotherapy in patients with pd-l1 overexpression
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10587271/
https://www.ncbi.nlm.nih.gov/pubmed/37468609
http://dx.doi.org/10.1007/s00432-023-05160-9
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