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Computational recognition of LncRNA signatures in tumor-associated neutrophils could have implications for immunotherapy and prognostic outcome of non-small cell lung cancer

Cancer immune function and tumor microenvironment are governed by long noncoding RNAs (lncRNAs). Nevertheless, it has yet to be established whether lncRNAs play a role in tumor-associated neutrophils (TANs). Here, a computing framework based on machine learning was used to identify neutrophil-specif...

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Autores principales: Tang, Zhuoran, Wang, Qi, Chen, Peixin, Guo, Haoyue, Shi, Jinpeng, Pan, Yingying, Li, Chunyu, Zhou, Caicun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9649922/
https://www.ncbi.nlm.nih.gov/pubmed/36386809
http://dx.doi.org/10.3389/fgene.2022.1002699
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author Tang, Zhuoran
Wang, Qi
Chen, Peixin
Guo, Haoyue
Shi, Jinpeng
Pan, Yingying
Li, Chunyu
Zhou, Caicun
author_facet Tang, Zhuoran
Wang, Qi
Chen, Peixin
Guo, Haoyue
Shi, Jinpeng
Pan, Yingying
Li, Chunyu
Zhou, Caicun
author_sort Tang, Zhuoran
collection PubMed
description Cancer immune function and tumor microenvironment are governed by long noncoding RNAs (lncRNAs). Nevertheless, it has yet to be established whether lncRNAs play a role in tumor-associated neutrophils (TANs). Here, a computing framework based on machine learning was used to identify neutrophil-specific lncRNA with prognostic significance in squamous cell carcinoma and lung adenocarcinoma using univariate Cox regression to comprehensively analyze immune, lncRNA, and clinical characteristics. The risk score was determined using LASSO Cox regression analysis. Meanwhile, we named this risk score as “TANlncSig.” TANlncSig was able to distinguish between better and worse survival outcomes in various patient datasets independently of other clinical variables. Functional assessment of TANlncSig showed it is a marker of myeloid cell infiltration into tumor infiltration and myeloid cells directly or indirectly inhibit the anti-tumor immune response by secreting cytokines, expressing immunosuppressive receptors, and altering metabolic processes. Our findings highlighted the value of TANlncSig in TME as a marker of immune cell infiltration and showed the values of lncRNAs as indicators of immunotherapy.
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spelling pubmed-96499222022-11-15 Computational recognition of LncRNA signatures in tumor-associated neutrophils could have implications for immunotherapy and prognostic outcome of non-small cell lung cancer Tang, Zhuoran Wang, Qi Chen, Peixin Guo, Haoyue Shi, Jinpeng Pan, Yingying Li, Chunyu Zhou, Caicun Front Genet Genetics Cancer immune function and tumor microenvironment are governed by long noncoding RNAs (lncRNAs). Nevertheless, it has yet to be established whether lncRNAs play a role in tumor-associated neutrophils (TANs). Here, a computing framework based on machine learning was used to identify neutrophil-specific lncRNA with prognostic significance in squamous cell carcinoma and lung adenocarcinoma using univariate Cox regression to comprehensively analyze immune, lncRNA, and clinical characteristics. The risk score was determined using LASSO Cox regression analysis. Meanwhile, we named this risk score as “TANlncSig.” TANlncSig was able to distinguish between better and worse survival outcomes in various patient datasets independently of other clinical variables. Functional assessment of TANlncSig showed it is a marker of myeloid cell infiltration into tumor infiltration and myeloid cells directly or indirectly inhibit the anti-tumor immune response by secreting cytokines, expressing immunosuppressive receptors, and altering metabolic processes. Our findings highlighted the value of TANlncSig in TME as a marker of immune cell infiltration and showed the values of lncRNAs as indicators of immunotherapy. Frontiers Media S.A. 2022-10-28 /pmc/articles/PMC9649922/ /pubmed/36386809 http://dx.doi.org/10.3389/fgene.2022.1002699 Text en Copyright © 2022 Tang, Wang, Chen, Guo, Shi, Pan, Li and Zhou. 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 Genetics
Tang, Zhuoran
Wang, Qi
Chen, Peixin
Guo, Haoyue
Shi, Jinpeng
Pan, Yingying
Li, Chunyu
Zhou, Caicun
Computational recognition of LncRNA signatures in tumor-associated neutrophils could have implications for immunotherapy and prognostic outcome of non-small cell lung cancer
title Computational recognition of LncRNA signatures in tumor-associated neutrophils could have implications for immunotherapy and prognostic outcome of non-small cell lung cancer
title_full Computational recognition of LncRNA signatures in tumor-associated neutrophils could have implications for immunotherapy and prognostic outcome of non-small cell lung cancer
title_fullStr Computational recognition of LncRNA signatures in tumor-associated neutrophils could have implications for immunotherapy and prognostic outcome of non-small cell lung cancer
title_full_unstemmed Computational recognition of LncRNA signatures in tumor-associated neutrophils could have implications for immunotherapy and prognostic outcome of non-small cell lung cancer
title_short Computational recognition of LncRNA signatures in tumor-associated neutrophils could have implications for immunotherapy and prognostic outcome of non-small cell lung cancer
title_sort computational recognition of lncrna signatures in tumor-associated neutrophils could have implications for immunotherapy and prognostic outcome of non-small cell lung cancer
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9649922/
https://www.ncbi.nlm.nih.gov/pubmed/36386809
http://dx.doi.org/10.3389/fgene.2022.1002699
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