Cargando…
A novel necroptosis-related gene signature for predict prognosis of glioma based on single-cell and bulk RNA sequencing
Background: Glioma is the most fatal neoplasm among the primary intracranial cancers. Necroptosis, a form of programmed cell death, is correlated with tumor progression and immune response. But, the role of necroptosis-related genes (NRGs) in glioma has not been well-uncovered. Methods: Single-cell...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9469195/ https://www.ncbi.nlm.nih.gov/pubmed/36111134 http://dx.doi.org/10.3389/fmolb.2022.984712 |
_version_ | 1784788586951868416 |
---|---|
author | Guo, Kai Duan, Xinxin Zhao, Jiahui Sun, Boyu Liu, Xiaoming Zhao, Zongmao |
author_facet | Guo, Kai Duan, Xinxin Zhao, Jiahui Sun, Boyu Liu, Xiaoming Zhao, Zongmao |
author_sort | Guo, Kai |
collection | PubMed |
description | Background: Glioma is the most fatal neoplasm among the primary intracranial cancers. Necroptosis, a form of programmed cell death, is correlated with tumor progression and immune response. But, the role of necroptosis-related genes (NRGs) in glioma has not been well-uncovered. Methods: Single-cell and bulk RNA sequencing data, obtained from publicly accessed databases, were used to establish a necroptosis-related gene signature for predicting the prognosis of glioma patients. Multiple bioinformatics algorithms were conducted to evaluate the efficacy of the signature. The relative mRNA level of each signature gene was validated by quantitative real-time reverse transcription PCR (qRT-PCR) in glioma cell lines compared to human astrocytes. Results: In this predicted prognosis model, patients with a high risk score showed a shorter overall survival, which was verified in the testing cohorts. The signature risk score was positively related with immune cell infiltration and some immune check points, such as CD276 (B7-H3), CD152 (CTLA-4), CD223 (LAG-3), and CD274 (PD-L1). Single-cell RNA sequencing analysis confirmed that the glioma microenvironment consists of various immune cells with different markers. The eight NRGs of the signature were detected to be expressed in several immune cells. QRT-PCR results verified that all the eight signature genes were differentially expressed between human astrocytes and glioma cells. Conclusion: The eight NRGs correlate with the immune microenvironment of glioma according to our bioinformatics analysis. This necroptosis-related gene signature may evaluate the precise methodology of predicting prognosis of glioma and provide a novel thought in glioma investigation. |
format | Online Article Text |
id | pubmed-9469195 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94691952022-09-14 A novel necroptosis-related gene signature for predict prognosis of glioma based on single-cell and bulk RNA sequencing Guo, Kai Duan, Xinxin Zhao, Jiahui Sun, Boyu Liu, Xiaoming Zhao, Zongmao Front Mol Biosci Molecular Biosciences Background: Glioma is the most fatal neoplasm among the primary intracranial cancers. Necroptosis, a form of programmed cell death, is correlated with tumor progression and immune response. But, the role of necroptosis-related genes (NRGs) in glioma has not been well-uncovered. Methods: Single-cell and bulk RNA sequencing data, obtained from publicly accessed databases, were used to establish a necroptosis-related gene signature for predicting the prognosis of glioma patients. Multiple bioinformatics algorithms were conducted to evaluate the efficacy of the signature. The relative mRNA level of each signature gene was validated by quantitative real-time reverse transcription PCR (qRT-PCR) in glioma cell lines compared to human astrocytes. Results: In this predicted prognosis model, patients with a high risk score showed a shorter overall survival, which was verified in the testing cohorts. The signature risk score was positively related with immune cell infiltration and some immune check points, such as CD276 (B7-H3), CD152 (CTLA-4), CD223 (LAG-3), and CD274 (PD-L1). Single-cell RNA sequencing analysis confirmed that the glioma microenvironment consists of various immune cells with different markers. The eight NRGs of the signature were detected to be expressed in several immune cells. QRT-PCR results verified that all the eight signature genes were differentially expressed between human astrocytes and glioma cells. Conclusion: The eight NRGs correlate with the immune microenvironment of glioma according to our bioinformatics analysis. This necroptosis-related gene signature may evaluate the precise methodology of predicting prognosis of glioma and provide a novel thought in glioma investigation. Frontiers Media S.A. 2022-08-30 /pmc/articles/PMC9469195/ /pubmed/36111134 http://dx.doi.org/10.3389/fmolb.2022.984712 Text en Copyright © 2022 Guo, Duan, Zhao, Sun, Liu and Zhao. 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 | Molecular Biosciences Guo, Kai Duan, Xinxin Zhao, Jiahui Sun, Boyu Liu, Xiaoming Zhao, Zongmao A novel necroptosis-related gene signature for predict prognosis of glioma based on single-cell and bulk RNA sequencing |
title | A novel necroptosis-related gene signature for predict prognosis of glioma based on single-cell and bulk RNA sequencing |
title_full | A novel necroptosis-related gene signature for predict prognosis of glioma based on single-cell and bulk RNA sequencing |
title_fullStr | A novel necroptosis-related gene signature for predict prognosis of glioma based on single-cell and bulk RNA sequencing |
title_full_unstemmed | A novel necroptosis-related gene signature for predict prognosis of glioma based on single-cell and bulk RNA sequencing |
title_short | A novel necroptosis-related gene signature for predict prognosis of glioma based on single-cell and bulk RNA sequencing |
title_sort | novel necroptosis-related gene signature for predict prognosis of glioma based on single-cell and bulk rna sequencing |
topic | Molecular Biosciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9469195/ https://www.ncbi.nlm.nih.gov/pubmed/36111134 http://dx.doi.org/10.3389/fmolb.2022.984712 |
work_keys_str_mv | AT guokai anovelnecroptosisrelatedgenesignatureforpredictprognosisofgliomabasedonsinglecellandbulkrnasequencing AT duanxinxin anovelnecroptosisrelatedgenesignatureforpredictprognosisofgliomabasedonsinglecellandbulkrnasequencing AT zhaojiahui anovelnecroptosisrelatedgenesignatureforpredictprognosisofgliomabasedonsinglecellandbulkrnasequencing AT sunboyu anovelnecroptosisrelatedgenesignatureforpredictprognosisofgliomabasedonsinglecellandbulkrnasequencing AT liuxiaoming anovelnecroptosisrelatedgenesignatureforpredictprognosisofgliomabasedonsinglecellandbulkrnasequencing AT zhaozongmao anovelnecroptosisrelatedgenesignatureforpredictprognosisofgliomabasedonsinglecellandbulkrnasequencing AT guokai novelnecroptosisrelatedgenesignatureforpredictprognosisofgliomabasedonsinglecellandbulkrnasequencing AT duanxinxin novelnecroptosisrelatedgenesignatureforpredictprognosisofgliomabasedonsinglecellandbulkrnasequencing AT zhaojiahui novelnecroptosisrelatedgenesignatureforpredictprognosisofgliomabasedonsinglecellandbulkrnasequencing AT sunboyu novelnecroptosisrelatedgenesignatureforpredictprognosisofgliomabasedonsinglecellandbulkrnasequencing AT liuxiaoming novelnecroptosisrelatedgenesignatureforpredictprognosisofgliomabasedonsinglecellandbulkrnasequencing AT zhaozongmao novelnecroptosisrelatedgenesignatureforpredictprognosisofgliomabasedonsinglecellandbulkrnasequencing |