Cargando…

Identification of a Novel Oxidative Stress- and Anoikis-Related Prognostic Signature and Its Immune Landscape Analysis in Non-Small Cell Lung Cancer

The objective of this study was to identify a kind of prognostic signature based on oxidative stress- and anoikis-related genes (OARGs) for predicting the prognosis and immune landscape of NSCLC. Initially, We identified 47 differentially expressed OARGs that primarily regulate oxidative stress and...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhao, Hanqing, Huang, Ying, Tong, Guoshun, Wu, Wei, Ren, Yangwu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10671784/
https://www.ncbi.nlm.nih.gov/pubmed/38003378
http://dx.doi.org/10.3390/ijms242216188
_version_ 1785140238824243200
author Zhao, Hanqing
Huang, Ying
Tong, Guoshun
Wu, Wei
Ren, Yangwu
author_facet Zhao, Hanqing
Huang, Ying
Tong, Guoshun
Wu, Wei
Ren, Yangwu
author_sort Zhao, Hanqing
collection PubMed
description The objective of this study was to identify a kind of prognostic signature based on oxidative stress- and anoikis-related genes (OARGs) for predicting the prognosis and immune landscape of NSCLC. Initially, We identified 47 differentially expressed OARGs that primarily regulate oxidative stress and epithelial cell infiltration through the PI3K-Akt pathway. Subsequently, 10 OARGs related to prognosis determined two potential clusters. A cluster was associated with a shorter survival level, lower immune infiltration, higher stemness index and tumor mutation burden. Next, The best risk score model constructed by prognostic OARGs was the Random Survival Forest model, and it included SLC2A1, LDHA and PLAU. The high-risk group was associated with cluster A and poor prognosis, with a higher tumor mutation burden, stemness index and proportion of M0-type macrophages, and a lower immune checkpoint expression level, immune function score and IPS score. The calibration curve and decision-making curve showed that the risk score combined with clinical pathological characteristics could be used to construct a nomogram for guiding the clinical treatment strategies. Finally, We found that all three hub genes were highly expressed in tumor tissues, and LDHA expression was mainly regulated by has-miR-338-3p, has-miR-330-5p and has-miR-34c-5p. Altogether, We constructed an OARG-related prognostic signature to reveal potential relationships between the signature and clinical characteristics, TME, stemness, tumor mutational burden, drug sensitivity and immune landscape in NSCLC patients.
format Online
Article
Text
id pubmed-10671784
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-106717842023-11-10 Identification of a Novel Oxidative Stress- and Anoikis-Related Prognostic Signature and Its Immune Landscape Analysis in Non-Small Cell Lung Cancer Zhao, Hanqing Huang, Ying Tong, Guoshun Wu, Wei Ren, Yangwu Int J Mol Sci Article The objective of this study was to identify a kind of prognostic signature based on oxidative stress- and anoikis-related genes (OARGs) for predicting the prognosis and immune landscape of NSCLC. Initially, We identified 47 differentially expressed OARGs that primarily regulate oxidative stress and epithelial cell infiltration through the PI3K-Akt pathway. Subsequently, 10 OARGs related to prognosis determined two potential clusters. A cluster was associated with a shorter survival level, lower immune infiltration, higher stemness index and tumor mutation burden. Next, The best risk score model constructed by prognostic OARGs was the Random Survival Forest model, and it included SLC2A1, LDHA and PLAU. The high-risk group was associated with cluster A and poor prognosis, with a higher tumor mutation burden, stemness index and proportion of M0-type macrophages, and a lower immune checkpoint expression level, immune function score and IPS score. The calibration curve and decision-making curve showed that the risk score combined with clinical pathological characteristics could be used to construct a nomogram for guiding the clinical treatment strategies. Finally, We found that all three hub genes were highly expressed in tumor tissues, and LDHA expression was mainly regulated by has-miR-338-3p, has-miR-330-5p and has-miR-34c-5p. Altogether, We constructed an OARG-related prognostic signature to reveal potential relationships between the signature and clinical characteristics, TME, stemness, tumor mutational burden, drug sensitivity and immune landscape in NSCLC patients. MDPI 2023-11-10 /pmc/articles/PMC10671784/ /pubmed/38003378 http://dx.doi.org/10.3390/ijms242216188 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhao, Hanqing
Huang, Ying
Tong, Guoshun
Wu, Wei
Ren, Yangwu
Identification of a Novel Oxidative Stress- and Anoikis-Related Prognostic Signature and Its Immune Landscape Analysis in Non-Small Cell Lung Cancer
title Identification of a Novel Oxidative Stress- and Anoikis-Related Prognostic Signature and Its Immune Landscape Analysis in Non-Small Cell Lung Cancer
title_full Identification of a Novel Oxidative Stress- and Anoikis-Related Prognostic Signature and Its Immune Landscape Analysis in Non-Small Cell Lung Cancer
title_fullStr Identification of a Novel Oxidative Stress- and Anoikis-Related Prognostic Signature and Its Immune Landscape Analysis in Non-Small Cell Lung Cancer
title_full_unstemmed Identification of a Novel Oxidative Stress- and Anoikis-Related Prognostic Signature and Its Immune Landscape Analysis in Non-Small Cell Lung Cancer
title_short Identification of a Novel Oxidative Stress- and Anoikis-Related Prognostic Signature and Its Immune Landscape Analysis in Non-Small Cell Lung Cancer
title_sort identification of a novel oxidative stress- and anoikis-related prognostic signature and its immune landscape analysis in non-small cell lung cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10671784/
https://www.ncbi.nlm.nih.gov/pubmed/38003378
http://dx.doi.org/10.3390/ijms242216188
work_keys_str_mv AT zhaohanqing identificationofanoveloxidativestressandanoikisrelatedprognosticsignatureanditsimmunelandscapeanalysisinnonsmallcelllungcancer
AT huangying identificationofanoveloxidativestressandanoikisrelatedprognosticsignatureanditsimmunelandscapeanalysisinnonsmallcelllungcancer
AT tongguoshun identificationofanoveloxidativestressandanoikisrelatedprognosticsignatureanditsimmunelandscapeanalysisinnonsmallcelllungcancer
AT wuwei identificationofanoveloxidativestressandanoikisrelatedprognosticsignatureanditsimmunelandscapeanalysisinnonsmallcelllungcancer
AT renyangwu identificationofanoveloxidativestressandanoikisrelatedprognosticsignatureanditsimmunelandscapeanalysisinnonsmallcelllungcancer