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Systematic transcriptome profiling of pyroptosis related signature for predicting prognosis and immune landscape in lower grade glioma

BACKGROUND: Pyroptosis is a programmed cell death mediated by the gasdermin superfamily, accompanied by inflammatory and immune responses. Exogenously activated pyroptosis is still not well characterized in the tumor microenvironment. Furthermore, whether pyroptosis-related genes (PRGs) in lower-gra...

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Autores principales: Yu, Huihan, Gong, Meiting, Qi, Jian, Zhao, Chenggang, Niu, Wanxiang, Sun, Suling, Li, Shuyang, Hong, Bo, Qian, Junchao, Wang, Hongzhi, Chen, Xueran, Fang, Zhiyou
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9375370/
https://www.ncbi.nlm.nih.gov/pubmed/35964070
http://dx.doi.org/10.1186/s12885-022-09982-7
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author Yu, Huihan
Gong, Meiting
Qi, Jian
Zhao, Chenggang
Niu, Wanxiang
Sun, Suling
Li, Shuyang
Hong, Bo
Qian, Junchao
Wang, Hongzhi
Chen, Xueran
Fang, Zhiyou
author_facet Yu, Huihan
Gong, Meiting
Qi, Jian
Zhao, Chenggang
Niu, Wanxiang
Sun, Suling
Li, Shuyang
Hong, Bo
Qian, Junchao
Wang, Hongzhi
Chen, Xueran
Fang, Zhiyou
author_sort Yu, Huihan
collection PubMed
description BACKGROUND: Pyroptosis is a programmed cell death mediated by the gasdermin superfamily, accompanied by inflammatory and immune responses. Exogenously activated pyroptosis is still not well characterized in the tumor microenvironment. Furthermore, whether pyroptosis-related genes (PRGs) in lower-grade glioma (LGG) may be used as a biomarker remains unknown. METHODS: The RNA-Sequencing and clinical data of LGG patients were downloaded from publicly available databases. Bioinformatics approaches were used to analyze the relationship between PRGs and LGG patients’ prognosis, clinicopathological features, and immune status. The NMF algorithm was used to differentiate phenotypes, the LASSO regression model was used to construct prognostic signature, and GSEA was used to analyze biological functions and pathways. The expression of the signature genes was verified using qRT-PCR. In addition, the L1000FWD and CMap tools were utilized to screen potential therapeutic drugs or small molecule compounds and validate their effects in glioma cell lines using CCK-8 and colony formation assays. RESULTS: Based on PRGs, we defined two phenotypes with different prognoses. Stepwise regression analysis was carried out to identify the 3 signature genes to construct a pyroptosis-related signature. After that, samples from the training and test cohorts were incorporated into the signature and divided by the median RiskScore value (namely, Risk-H and Risk-L). The signature shows excellent predictive LGG prognostic power in the training and validation cohorts. The prognostic signature accurately stratifies patients according to prognostic differences and has predictive value for immune cell infiltration and immune checkpoint expression. Finally, the inhibitory effect of the small molecule inhibitor fedratinib on the viability and proliferation of various glioma cells was verified using cell biology-related experiments. CONCLUSION: This study developed and validated a novel pyroptosis-related signature, which may assist instruct clinicians to predict the prognosis and immunological status of LGG patients more precisely. Fedratinib was found to be a small molecule inhibitor that significantly inhibits glioma cell viability and proliferation, which provides a new therapeutic strategy for gliomas. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-09982-7.
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spelling pubmed-93753702022-08-14 Systematic transcriptome profiling of pyroptosis related signature for predicting prognosis and immune landscape in lower grade glioma Yu, Huihan Gong, Meiting Qi, Jian Zhao, Chenggang Niu, Wanxiang Sun, Suling Li, Shuyang Hong, Bo Qian, Junchao Wang, Hongzhi Chen, Xueran Fang, Zhiyou BMC Cancer Research BACKGROUND: Pyroptosis is a programmed cell death mediated by the gasdermin superfamily, accompanied by inflammatory and immune responses. Exogenously activated pyroptosis is still not well characterized in the tumor microenvironment. Furthermore, whether pyroptosis-related genes (PRGs) in lower-grade glioma (LGG) may be used as a biomarker remains unknown. METHODS: The RNA-Sequencing and clinical data of LGG patients were downloaded from publicly available databases. Bioinformatics approaches were used to analyze the relationship between PRGs and LGG patients’ prognosis, clinicopathological features, and immune status. The NMF algorithm was used to differentiate phenotypes, the LASSO regression model was used to construct prognostic signature, and GSEA was used to analyze biological functions and pathways. The expression of the signature genes was verified using qRT-PCR. In addition, the L1000FWD and CMap tools were utilized to screen potential therapeutic drugs or small molecule compounds and validate their effects in glioma cell lines using CCK-8 and colony formation assays. RESULTS: Based on PRGs, we defined two phenotypes with different prognoses. Stepwise regression analysis was carried out to identify the 3 signature genes to construct a pyroptosis-related signature. After that, samples from the training and test cohorts were incorporated into the signature and divided by the median RiskScore value (namely, Risk-H and Risk-L). The signature shows excellent predictive LGG prognostic power in the training and validation cohorts. The prognostic signature accurately stratifies patients according to prognostic differences and has predictive value for immune cell infiltration and immune checkpoint expression. Finally, the inhibitory effect of the small molecule inhibitor fedratinib on the viability and proliferation of various glioma cells was verified using cell biology-related experiments. CONCLUSION: This study developed and validated a novel pyroptosis-related signature, which may assist instruct clinicians to predict the prognosis and immunological status of LGG patients more precisely. Fedratinib was found to be a small molecule inhibitor that significantly inhibits glioma cell viability and proliferation, which provides a new therapeutic strategy for gliomas. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-09982-7. BioMed Central 2022-08-13 /pmc/articles/PMC9375370/ /pubmed/35964070 http://dx.doi.org/10.1186/s12885-022-09982-7 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
Yu, Huihan
Gong, Meiting
Qi, Jian
Zhao, Chenggang
Niu, Wanxiang
Sun, Suling
Li, Shuyang
Hong, Bo
Qian, Junchao
Wang, Hongzhi
Chen, Xueran
Fang, Zhiyou
Systematic transcriptome profiling of pyroptosis related signature for predicting prognosis and immune landscape in lower grade glioma
title Systematic transcriptome profiling of pyroptosis related signature for predicting prognosis and immune landscape in lower grade glioma
title_full Systematic transcriptome profiling of pyroptosis related signature for predicting prognosis and immune landscape in lower grade glioma
title_fullStr Systematic transcriptome profiling of pyroptosis related signature for predicting prognosis and immune landscape in lower grade glioma
title_full_unstemmed Systematic transcriptome profiling of pyroptosis related signature for predicting prognosis and immune landscape in lower grade glioma
title_short Systematic transcriptome profiling of pyroptosis related signature for predicting prognosis and immune landscape in lower grade glioma
title_sort systematic transcriptome profiling of pyroptosis related signature for predicting prognosis and immune landscape in lower grade glioma
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9375370/
https://www.ncbi.nlm.nih.gov/pubmed/35964070
http://dx.doi.org/10.1186/s12885-022-09982-7
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