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Identification of comutation in signaling pathways to predict the clinical outcomes of immunotherapy
BACKGROUND: Immune checkpoint blockades (ICBs) have emerged as a promising treatment for cancer. Recently, tumour mutational burden (TMB) and neoantigen load (NAL) have been proposed to be potential biomarkers to predict the efficacy of ICB; however, they were limited by difficulties in defining the...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9783967/ https://www.ncbi.nlm.nih.gov/pubmed/36564823 http://dx.doi.org/10.1186/s12967-022-03836-3 |
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author | Qiu, Jiayue Li, Xiangmei He, Yalan Wang, Qian Li, Ji Wu, Jiashuo Jiang, Ying Han, Junwei |
author_facet | Qiu, Jiayue Li, Xiangmei He, Yalan Wang, Qian Li, Ji Wu, Jiashuo Jiang, Ying Han, Junwei |
author_sort | Qiu, Jiayue |
collection | PubMed |
description | BACKGROUND: Immune checkpoint blockades (ICBs) have emerged as a promising treatment for cancer. Recently, tumour mutational burden (TMB) and neoantigen load (NAL) have been proposed to be potential biomarkers to predict the efficacy of ICB; however, they were limited by difficulties in defining the cut-off values and inconsistent detection platforms. Therefore, it is critical to identify more effective predictive biomarkers for screening patients who will potentially benefit from immunotherapy. In this study, we aimed to identify comutated signaling pathways to predict the clinical outcomes of immunotherapy. METHODS: Here, we comprehensively analysed the signaling pathway mutation status of 9763 samples across 33 different cancer types from The Cancer Genome Atlas (TCGA) by mapping the somatic mutations to the pathways. We then explored the comutated pathways that were associated with increased TMB and NAL by using receiver operating characteristic (ROC) curve analysis and multiple linear regressions. RESULTS: Our results revealed that comutation of the Spliceosome (Sp) pathway and Hedgehog (He) signaling pathway (defined as SpHe-comut(+)) could be used as a predictor of increased TMB and NAL and was associated with increased levels of immune-related signatures. In seven independent immunotherapy cohorts, we validated that SpHe-comut(+) patients exhibited a longer overall survival (OS) or progression-free survival (PFS) and a higher objective response rate (ORR) than SpHe-comut(−) patients. Moreover, a combination of SpHe-comut status with PD-L1 expression further improved the predictive value for ICB therapy. CONCLUSION: Overall, SpHe-comut(+) was demonstrated to be an effective predictor of immunotherapeutic benefit in seven independent immunotherapy cohorts and may serve as a potential and convenient biomarker for the clinical application of ICB therapy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-022-03836-3. |
format | Online Article Text |
id | pubmed-9783967 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-97839672022-12-24 Identification of comutation in signaling pathways to predict the clinical outcomes of immunotherapy Qiu, Jiayue Li, Xiangmei He, Yalan Wang, Qian Li, Ji Wu, Jiashuo Jiang, Ying Han, Junwei J Transl Med Research BACKGROUND: Immune checkpoint blockades (ICBs) have emerged as a promising treatment for cancer. Recently, tumour mutational burden (TMB) and neoantigen load (NAL) have been proposed to be potential biomarkers to predict the efficacy of ICB; however, they were limited by difficulties in defining the cut-off values and inconsistent detection platforms. Therefore, it is critical to identify more effective predictive biomarkers for screening patients who will potentially benefit from immunotherapy. In this study, we aimed to identify comutated signaling pathways to predict the clinical outcomes of immunotherapy. METHODS: Here, we comprehensively analysed the signaling pathway mutation status of 9763 samples across 33 different cancer types from The Cancer Genome Atlas (TCGA) by mapping the somatic mutations to the pathways. We then explored the comutated pathways that were associated with increased TMB and NAL by using receiver operating characteristic (ROC) curve analysis and multiple linear regressions. RESULTS: Our results revealed that comutation of the Spliceosome (Sp) pathway and Hedgehog (He) signaling pathway (defined as SpHe-comut(+)) could be used as a predictor of increased TMB and NAL and was associated with increased levels of immune-related signatures. In seven independent immunotherapy cohorts, we validated that SpHe-comut(+) patients exhibited a longer overall survival (OS) or progression-free survival (PFS) and a higher objective response rate (ORR) than SpHe-comut(−) patients. Moreover, a combination of SpHe-comut status with PD-L1 expression further improved the predictive value for ICB therapy. CONCLUSION: Overall, SpHe-comut(+) was demonstrated to be an effective predictor of immunotherapeutic benefit in seven independent immunotherapy cohorts and may serve as a potential and convenient biomarker for the clinical application of ICB therapy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-022-03836-3. BioMed Central 2022-12-23 /pmc/articles/PMC9783967/ /pubmed/36564823 http://dx.doi.org/10.1186/s12967-022-03836-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Qiu, Jiayue Li, Xiangmei He, Yalan Wang, Qian Li, Ji Wu, Jiashuo Jiang, Ying Han, Junwei Identification of comutation in signaling pathways to predict the clinical outcomes of immunotherapy |
title | Identification of comutation in signaling pathways to predict the clinical outcomes of immunotherapy |
title_full | Identification of comutation in signaling pathways to predict the clinical outcomes of immunotherapy |
title_fullStr | Identification of comutation in signaling pathways to predict the clinical outcomes of immunotherapy |
title_full_unstemmed | Identification of comutation in signaling pathways to predict the clinical outcomes of immunotherapy |
title_short | Identification of comutation in signaling pathways to predict the clinical outcomes of immunotherapy |
title_sort | identification of comutation in signaling pathways to predict the clinical outcomes of immunotherapy |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9783967/ https://www.ncbi.nlm.nih.gov/pubmed/36564823 http://dx.doi.org/10.1186/s12967-022-03836-3 |
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