Identification of a 5-Gene Metabolic Signature for Predicting Prognosis Based on an Integrated Analysis of Tumor Microenvironment in Lung Adenocarcinoma
Joint Authors
Yu, Xiaolin
Zhang, Xiaomei
Zhang, Yanxia
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-06-26
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Lung adenocarcinoma (LUAD) is a common subtype of lung cancer with a depressing survival rate.
The reprogramming of tumor metabolism was identified as a new hallmark of cancer in tumor microenvironment (TME), and we made a comprehensive exploration to reveal the prognostic role of the metabolic-related genes.
Transcriptome profiling data of LUAD were, respectively, downloaded from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database.
Based on the extracted metabolic-related genes, a novel 5-gene metabolic prognostic signature (including GNPNAT1, LPGAT1, TYMS, LDHA, and PTGES) was constructed by univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression.
This signature confirmed its robustness and accuracy by external validation in multiple databases.
It could be an independent risk factor for LUAD, and the nomograms possessed moderately accurate performance with the C-index of 0.755 (95% confidence interval: 0.706–0.804) and 0.691 (95% confidence interval: 0.636–0.746) in training set and testing set.
This signature could reveal the metabolic features according to the results of gene set enrichment analysis (GSEA) and meanwhile monitor the status of TME through ESTIMATE scores and the infiltration levels of immune cells.
In conclusion, this gene signature is a cost-effective tool which could indicate the status of TME to provide more clues in the exploration of new diagnostic and therapeutic strategy.
American Psychological Association (APA)
Yu, Xiaolin& Zhang, Xiaomei& Zhang, Yanxia. 2020. Identification of a 5-Gene Metabolic Signature for Predicting Prognosis Based on an Integrated Analysis of Tumor Microenvironment in Lung Adenocarcinoma. Journal of Oncology،Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1188986
Modern Language Association (MLA)
Yu, Xiaolin…[et al.]. Identification of a 5-Gene Metabolic Signature for Predicting Prognosis Based on an Integrated Analysis of Tumor Microenvironment in Lung Adenocarcinoma. Journal of Oncology No. 2020 (2020), pp.1-12.
https://search.emarefa.net/detail/BIM-1188986
American Medical Association (AMA)
Yu, Xiaolin& Zhang, Xiaomei& Zhang, Yanxia. Identification of a 5-Gene Metabolic Signature for Predicting Prognosis Based on an Integrated Analysis of Tumor Microenvironment in Lung Adenocarcinoma. Journal of Oncology. 2020. Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1188986
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1188986