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Identification and validation of a PD-L1-related signature from mass spectrometry in gastric cancer

BACKGROUND: According to the guidelines, PD-L1 expression is a critical indicator for guiding immunotherapy application. According to certain studies, regardless of PD-L1 expression, immunotherapy could be advantageous for individuals with gastric cancer. Therefore, new scoring systems or biomarkers...

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Autores principales: Chen, Xiancong, Mao, Deli, Li, Dongsheng, Li, Wenchao, Wei, Hongfa, Deng, Cuncan, Chen, Hengxing, Zhang, Changhua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10356661/
https://www.ncbi.nlm.nih.gov/pubmed/36592213
http://dx.doi.org/10.1007/s00432-022-04529-6
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author Chen, Xiancong
Mao, Deli
Li, Dongsheng
Li, Wenchao
Wei, Hongfa
Deng, Cuncan
Chen, Hengxing
Zhang, Changhua
author_facet Chen, Xiancong
Mao, Deli
Li, Dongsheng
Li, Wenchao
Wei, Hongfa
Deng, Cuncan
Chen, Hengxing
Zhang, Changhua
author_sort Chen, Xiancong
collection PubMed
description BACKGROUND: According to the guidelines, PD-L1 expression is a critical indicator for guiding immunotherapy application. According to certain studies, regardless of PD-L1 expression, immunotherapy could be advantageous for individuals with gastric cancer. Therefore, new scoring systems or biomarkers are required to enhance treatment strategies. METHODS: Mass spectrometry and machine learning were used to search for strongly related PD-L1 genes, and the NMF approach was then used to separate gastric cancer patients into two categories. Differentially expressed genes (DEGs) between the two subtypes identified in this investigation were utilized to develop the UBscore predictive model, which was verified by the Gene Expression Omnibus (GEO) database. Coimmunoprecipitation, protein expression, and natural killing (NK) cell coculture experiments were conducted to validate the findings. RESULTS: A total of 123 proteins were identified as PD-L1 interactors that are substantially enriched in the proteasome complex at the mRNA level. Using random forest, 30 UPS genes were discovered in the GSE66229 cohort, and ANAPC7 was experimentally verified as one of 123 PD-L1 interactors. Depending on the expression of PD-L1 and ANAPC7, patients were separated into two subgroups with vastly distinct immune infiltration. Low UBscore was related to increased tumor mutation burden (TMB) and microsatellite instability-high (MSI-H). In addition, chemotherapy medications were more effective in individuals with a low UBscore. Finally, we discovered that ANAPC7 might lead to the incidence of immunological escape when cocultured with NK-92 cells. CONCLUSION: According to our analysis of the PD-L1-related signature in GC, the UBscore played a crucial role in prognosis and had a strong relationship with TMB, MSI, and chemotherapeutic drug sensitivity. This research lays the groundwork for improving GC patient prognosis and treatment response. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00432-022-04529-6.
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spelling pubmed-103566612023-07-21 Identification and validation of a PD-L1-related signature from mass spectrometry in gastric cancer Chen, Xiancong Mao, Deli Li, Dongsheng Li, Wenchao Wei, Hongfa Deng, Cuncan Chen, Hengxing Zhang, Changhua J Cancer Res Clin Oncol Research BACKGROUND: According to the guidelines, PD-L1 expression is a critical indicator for guiding immunotherapy application. According to certain studies, regardless of PD-L1 expression, immunotherapy could be advantageous for individuals with gastric cancer. Therefore, new scoring systems or biomarkers are required to enhance treatment strategies. METHODS: Mass spectrometry and machine learning were used to search for strongly related PD-L1 genes, and the NMF approach was then used to separate gastric cancer patients into two categories. Differentially expressed genes (DEGs) between the two subtypes identified in this investigation were utilized to develop the UBscore predictive model, which was verified by the Gene Expression Omnibus (GEO) database. Coimmunoprecipitation, protein expression, and natural killing (NK) cell coculture experiments were conducted to validate the findings. RESULTS: A total of 123 proteins were identified as PD-L1 interactors that are substantially enriched in the proteasome complex at the mRNA level. Using random forest, 30 UPS genes were discovered in the GSE66229 cohort, and ANAPC7 was experimentally verified as one of 123 PD-L1 interactors. Depending on the expression of PD-L1 and ANAPC7, patients were separated into two subgroups with vastly distinct immune infiltration. Low UBscore was related to increased tumor mutation burden (TMB) and microsatellite instability-high (MSI-H). In addition, chemotherapy medications were more effective in individuals with a low UBscore. Finally, we discovered that ANAPC7 might lead to the incidence of immunological escape when cocultured with NK-92 cells. CONCLUSION: According to our analysis of the PD-L1-related signature in GC, the UBscore played a crucial role in prognosis and had a strong relationship with TMB, MSI, and chemotherapeutic drug sensitivity. This research lays the groundwork for improving GC patient prognosis and treatment response. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00432-022-04529-6. Springer Berlin Heidelberg 2023-01-02 2023 /pmc/articles/PMC10356661/ /pubmed/36592213 http://dx.doi.org/10.1007/s00432-022-04529-6 Text en © The Author(s) 2023 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/) .
spellingShingle Research
Chen, Xiancong
Mao, Deli
Li, Dongsheng
Li, Wenchao
Wei, Hongfa
Deng, Cuncan
Chen, Hengxing
Zhang, Changhua
Identification and validation of a PD-L1-related signature from mass spectrometry in gastric cancer
title Identification and validation of a PD-L1-related signature from mass spectrometry in gastric cancer
title_full Identification and validation of a PD-L1-related signature from mass spectrometry in gastric cancer
title_fullStr Identification and validation of a PD-L1-related signature from mass spectrometry in gastric cancer
title_full_unstemmed Identification and validation of a PD-L1-related signature from mass spectrometry in gastric cancer
title_short Identification and validation of a PD-L1-related signature from mass spectrometry in gastric cancer
title_sort identification and validation of a pd-l1-related signature from mass spectrometry in gastric cancer
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10356661/
https://www.ncbi.nlm.nih.gov/pubmed/36592213
http://dx.doi.org/10.1007/s00432-022-04529-6
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