Cargando…
Characterization of ferroptosis signature to evaluate the predict prognosis and immunotherapy in glioblastoma
Background: Glioblastoma (GBM) is the most common type of brain cancer with poor survival outcomes and unsatisfactory response to current therapeutic strategies. Recent studies have demonstrated that ferroptosis-related genes (FRGs) are linked with the occurrence and development of GBM and may becom...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8312442/ https://www.ncbi.nlm.nih.gov/pubmed/34244461 http://dx.doi.org/10.18632/aging.203257 |
_version_ | 1783729148930293760 |
---|---|
author | Zhu, Xiaopeng Zhou, Yuxiang Ou, Yangqian Cheng, Zebo Han, Deqing Chu, Zhou Pan, Sian |
author_facet | Zhu, Xiaopeng Zhou, Yuxiang Ou, Yangqian Cheng, Zebo Han, Deqing Chu, Zhou Pan, Sian |
author_sort | Zhu, Xiaopeng |
collection | PubMed |
description | Background: Glioblastoma (GBM) is the most common type of brain cancer with poor survival outcomes and unsatisfactory response to current therapeutic strategies. Recent studies have demonstrated that ferroptosis-related genes (FRGs) are linked with the occurrence and development of GBM and may become promising biological indicators in GBM therapy. Methods: We systematically assessed the relationship between FRGs expression profiles and prognosis in glioma patients based on the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) datasets to establish a risk score model according to the gene signature of multiple survival-associated DEGs. Further, the differences between the tumor microenvironment score, immune cell infiltration, immune checkpoint expression levels, and drug sensitivity in the high- and low-risk group are analyzed through a variety of algorithms in R software. Results: GBM patients were divided into two subgroups (high- and low-risk) according to the established risk score model. Patients in the high-risk group showed significantly reduced overall survival compared with those in the low-risk group. Also, we found that the high-risk group showed higher ImmuneScore and StromalScore, while different subgroups have significant differences in immune cell infiltration, immune checkpoint expression levels, and drug sensitivity. In summary, we developed and validated an FRGs risk model, which served as an independent prognostic indicator for GBM. Besides, the two subgroups divided by the model have significant differences, which provides novel insights for further studies as well as the personalized treatment of patients. |
format | Online Article Text |
id | pubmed-8312442 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Impact Journals |
record_format | MEDLINE/PubMed |
spelling | pubmed-83124422021-07-27 Characterization of ferroptosis signature to evaluate the predict prognosis and immunotherapy in glioblastoma Zhu, Xiaopeng Zhou, Yuxiang Ou, Yangqian Cheng, Zebo Han, Deqing Chu, Zhou Pan, Sian Aging (Albany NY) Research Paper Background: Glioblastoma (GBM) is the most common type of brain cancer with poor survival outcomes and unsatisfactory response to current therapeutic strategies. Recent studies have demonstrated that ferroptosis-related genes (FRGs) are linked with the occurrence and development of GBM and may become promising biological indicators in GBM therapy. Methods: We systematically assessed the relationship between FRGs expression profiles and prognosis in glioma patients based on the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) datasets to establish a risk score model according to the gene signature of multiple survival-associated DEGs. Further, the differences between the tumor microenvironment score, immune cell infiltration, immune checkpoint expression levels, and drug sensitivity in the high- and low-risk group are analyzed through a variety of algorithms in R software. Results: GBM patients were divided into two subgroups (high- and low-risk) according to the established risk score model. Patients in the high-risk group showed significantly reduced overall survival compared with those in the low-risk group. Also, we found that the high-risk group showed higher ImmuneScore and StromalScore, while different subgroups have significant differences in immune cell infiltration, immune checkpoint expression levels, and drug sensitivity. In summary, we developed and validated an FRGs risk model, which served as an independent prognostic indicator for GBM. Besides, the two subgroups divided by the model have significant differences, which provides novel insights for further studies as well as the personalized treatment of patients. Impact Journals 2021-07-09 /pmc/articles/PMC8312442/ /pubmed/34244461 http://dx.doi.org/10.18632/aging.203257 Text en Copyright: © 2021 Zhu et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Zhu, Xiaopeng Zhou, Yuxiang Ou, Yangqian Cheng, Zebo Han, Deqing Chu, Zhou Pan, Sian Characterization of ferroptosis signature to evaluate the predict prognosis and immunotherapy in glioblastoma |
title | Characterization of ferroptosis signature to evaluate the predict prognosis and immunotherapy in glioblastoma |
title_full | Characterization of ferroptosis signature to evaluate the predict prognosis and immunotherapy in glioblastoma |
title_fullStr | Characterization of ferroptosis signature to evaluate the predict prognosis and immunotherapy in glioblastoma |
title_full_unstemmed | Characterization of ferroptosis signature to evaluate the predict prognosis and immunotherapy in glioblastoma |
title_short | Characterization of ferroptosis signature to evaluate the predict prognosis and immunotherapy in glioblastoma |
title_sort | characterization of ferroptosis signature to evaluate the predict prognosis and immunotherapy in glioblastoma |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8312442/ https://www.ncbi.nlm.nih.gov/pubmed/34244461 http://dx.doi.org/10.18632/aging.203257 |
work_keys_str_mv | AT zhuxiaopeng characterizationofferroptosissignaturetoevaluatethepredictprognosisandimmunotherapyinglioblastoma AT zhouyuxiang characterizationofferroptosissignaturetoevaluatethepredictprognosisandimmunotherapyinglioblastoma AT ouyangqian characterizationofferroptosissignaturetoevaluatethepredictprognosisandimmunotherapyinglioblastoma AT chengzebo characterizationofferroptosissignaturetoevaluatethepredictprognosisandimmunotherapyinglioblastoma AT handeqing characterizationofferroptosissignaturetoevaluatethepredictprognosisandimmunotherapyinglioblastoma AT chuzhou characterizationofferroptosissignaturetoevaluatethepredictprognosisandimmunotherapyinglioblastoma AT pansian characterizationofferroptosissignaturetoevaluatethepredictprognosisandimmunotherapyinglioblastoma |