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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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2023
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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. |
format | Online Article Text |
id | pubmed-10587271 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
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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