Evidence map›Paper›PMID 34434660›Full record

ArticlePeerJ2021

Establishment of a ferroptosis-related gene signature for prognosis in lung adenocarcinoma patients.

Jingjing Cai, Chunyan Li, Hongsheng Li, Xiaoxiong Wang, Yongchun Zhou

Abstract read
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Article in PeerJ, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Jingjing Cai *Molecular Diagnostics Center, The Third Affiliated Hospital of Kunming Medical University/Yunnan Cancer Hospital, Kunming, Yunnan, China.
Chunyan Li *Department of Head and Neck Surgery Section II, The Third Affiliated Hospital of Kunming Medical University/Yunnan Cancer Hospital, Kunming, Yunnan, China.
Hongsheng LiMolecular Diagnostics Center, The Third Affiliated Hospital of Kunming Medical University/Yunnan Cancer Hospital, Kunming, Yunnan, China.
Xiaoxiong WangMolecular Diagnostics Center, The Third Affiliated Hospital of Kunming Medical University/Yunnan Cancer Hospital, Kunming, Yunnan, China.
Yongchun ZhouMolecular Diagnostics Center, The Third Affiliated Hospital of Kunming Medical University/Yunnan Cancer Hospital, Kunming, Yunnan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveLung cancer is the most common malignancy worldwide and exhibits both high morbidity and mortality. In recent years, scientists have made substantial breakthroughs in the early diagnosis and treatment of lung adenocarcinoma (LUAD), however, patient prognosis still shows vast individual differences. In this study, bioinformatics methods were used to identify and analyze ferroptosis-related genes to establish an effective signature for predicting prognosis in LUAD patients.

methodsThe gene expression profiles of LUAD patients with complete clinical and follow-up information were downloaded from two public databases, univariate Cox regression and multivariate Cox regression analysis were used to obtain ferroptosis-related genes for constructing the prognos tic risk model, AUC and calibration plot were used to evaluate the predictive accuracy of the FRGS and nomogram.

resultsA total of 74 ferroptosis-related differentially expressed genes (DEGs) were identi fied between LUAD and normal tissues from The Cancer Genome Atlas (TCGA) database. A five-gene panel for prediction of LUAD prognosis was established by multivariate regression and was verified using the GSE68465 cohort from the Gene Expression Omnibus (GEO) database. Patients were divided into two different risk groups according to the median risk score of the five genes. Based on Kaplan-Meier (KM) analysi, the OS rate of the high-risk group was markedly worse than that of the low-risk group. We also found that risk score was an independent prognostic indicator. The receiver operating characteristic ROC curve showed that the proposed model had good prediction ability. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional analyses indicated that risk score was prominently enriched in ferroptosis processes. Moreover, at the score of immune-associated gene sets, significant differences were found between the two risk groups.

conclusionsThis study demonstrated that ferroptosis-related gene signatures can be used as a potential predictor for the prognosis of LUAD, thus providing a novel strategy for individualized treatment in LUAD patients.

Indexed as

FerroptosisGene signatureImmune statusLung adenocarcinomaPrognosis

Identifiers

PMID34434660
PMCPMC8351575

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