Construction of a necroptosis-related lncRNA signature to predict the prognosis and immune microenvironment of head and neck squamous cell carcinoma.
head and neck squamous cell carcinoma
immunotherapy
long non-coding RNA
necroptosis
prognosis
Journal
Journal of clinical laboratory analysis
ISSN: 1098-2825
Titre abrégé: J Clin Lab Anal
Pays: United States
ID NLM: 8801384
Informations de publication
Date de publication:
Jun 2022
Jun 2022
Historique:
revised:
21
04
2022
received:
28
03
2022
accepted:
25
04
2022
pubmed:
7
5
2022
medline:
9
6
2022
entrez:
6
5
2022
Statut:
ppublish
Résumé
Previous studies have determined that necroptosis-related genes are potential biomarkers in head and neck squamous cell carcinoma (HNSCC). Herein, we established a novel risk model based on necroptosis-related lncRNAs (nrlncRNAs) to predict the prognosis of HNSCC patients. Transcriptome and related information were obtained from TCGA database, and an nrlncRNA signature was established based on univariate Cox analysis and least absolute shrinkage and selection operator Cox regression. Kaplan-Meier analysis and time-dependent receiver operating characteristic (ROC) analysis were used to evaluate the model, and a nomogram for survival prediction was established. Gene set enrichment analysis, immune analysis, drug sensitivity analysis, correlation with N6-methylandenosin (m6A), and tumor stemness analysis were performed. Furthermore, the entire set was divided into two clusters for further discussion. A novel signature was established with six nrlncRNAs. The areas under the ROC curves (AUCs) for 1-, 3-, and 5-year overall survival (OS) were 0.699, 0.686, and 0.645, respectively. Patients in low-risk group and cluster 2 had a better prognosis, more immune cell infiltration, higher immune function activity, and higher immune scores; however, patients in high-risk group and cluster 1 were more sensitive to chemotherapy. Moreover, the risk score had negative correlation with m6A-related gene expression and tumor stemness. According to this study, we constructed a novel signature with nrlncRNA pairs to predict the survival of HNSCC patients and guide immunotherapy and chemotherapy. This may possibly promote the development of individualized and precise treatment for HNSCC patients.
Sections du résumé
BACKGROUND
BACKGROUND
Previous studies have determined that necroptosis-related genes are potential biomarkers in head and neck squamous cell carcinoma (HNSCC). Herein, we established a novel risk model based on necroptosis-related lncRNAs (nrlncRNAs) to predict the prognosis of HNSCC patients.
METHODS
METHODS
Transcriptome and related information were obtained from TCGA database, and an nrlncRNA signature was established based on univariate Cox analysis and least absolute shrinkage and selection operator Cox regression. Kaplan-Meier analysis and time-dependent receiver operating characteristic (ROC) analysis were used to evaluate the model, and a nomogram for survival prediction was established. Gene set enrichment analysis, immune analysis, drug sensitivity analysis, correlation with N6-methylandenosin (m6A), and tumor stemness analysis were performed. Furthermore, the entire set was divided into two clusters for further discussion.
RESULTS
RESULTS
A novel signature was established with six nrlncRNAs. The areas under the ROC curves (AUCs) for 1-, 3-, and 5-year overall survival (OS) were 0.699, 0.686, and 0.645, respectively. Patients in low-risk group and cluster 2 had a better prognosis, more immune cell infiltration, higher immune function activity, and higher immune scores; however, patients in high-risk group and cluster 1 were more sensitive to chemotherapy. Moreover, the risk score had negative correlation with m6A-related gene expression and tumor stemness.
CONCLUSION
CONCLUSIONS
According to this study, we constructed a novel signature with nrlncRNA pairs to predict the survival of HNSCC patients and guide immunotherapy and chemotherapy. This may possibly promote the development of individualized and precise treatment for HNSCC patients.
Identifiants
pubmed: 35522142
doi: 10.1002/jcla.24480
pmc: PMC9169178
doi:
Substances chimiques
RNA, Long Noncoding
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e24480Subventions
Organisme : Zhejiang Provincial Medical and Health Science Research Foundation
ID : 2020KY274
Organisme : Zhejiang Provincial Medical and Health Science Research Foundation
ID : 2020RC107
Organisme : Zhejiang Provincial Medical and Health Science Research Foundation
ID : 2022KY1086
Organisme : National Natural Science Foundation of China
ID : 81670920
Organisme : Ningbo Public Science Research Foundation
ID : 2021S170
Organisme : Ningbo Natural Science Foundation
ID : 2018A610363
Informations de copyright
© 2022 The Authors. Journal of Clinical Laboratory Analysis published by Wiley Periodicals LLC.
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