Identification of a Novel Ferroptosis-Related Gene Prognostic Signature in Bladder Cancer.

bioinformatics analysis bladder cancer ferroptosis gene signature tumor tissue microarray

Journal

Frontiers in oncology
ISSN: 2234-943X
Titre abrégé: Front Oncol
Pays: Switzerland
ID NLM: 101568867

Informations de publication

Date de publication:
2021
Historique:
received: 29 06 2021
accepted: 19 08 2021
entrez: 24 9 2021
pubmed: 25 9 2021
medline: 25 9 2021
Statut: epublish

Résumé

Ferroptosis is a newly found non-apoptotic forms of cell death that plays an important role in tumors. However, the prognostic value of ferroptosis-related genes (FRG) in bladder cancer (BLCA) have not been well examined. FRG data and clinical information were collected from The Cancer Genome Atlas (TCGA). Then, significantly different FRGs were investigated by functional enrichment analyses. The prognostic FRG signature was identified by univariate cox regression and least absolute shrinkage and selection operator (LASSO) analysis, which was validated in TCGA cohort and Gene Expression Omnibus (GEO) cohort. Subsequently, the nomogram integrating risk scores and clinical parameters were established and evaluated. Additionally, Gene Set Enrichment Analyses (GSEA) was performed to explore the potential molecular mechanisms underlying our prognostic FRG signature. Finally, the expression of three key FRGs was verified in clinical specimens. Thirty-two significantly different FRGs were identified from TCGA-BLCA cohort. Enrichment analyses showed that these genes were mainly related to the ferroptosis. Seven genes (TFRC, G6PD, SLC38A1, ZEB1, SCD, SRC, and PRDX6) were then identified to develop a prognostic signature. The Kaplan-Meier analysis confirmed the predictive value of the signature for overall survival (OS) in both TCGA and GEO cohort. A nomogram integrating age and risk scores was established and demonstrated high predictive accuracy, which was validated through calibration curves and receiver operating characteristic (ROC) curve [area under the curve (AUC) = 0.690]. GSEA showed that molecular alteration in the high- or low-risk group was closely associated with ferroptosis. Finally, experimental results confirmed the expression of SCD, SRC, and PRDX6 in BLCA. Herein, we identified a novel FRG prognostic signature that maybe involved in BLCA. It showed high values in predicting OS, and targeting these FRGs may be an alternative for BLCA treatment. Further experimental studies are warranted to uncover the mechanisms that these FRGs mediate BLCA progression.

Sections du résumé

BACKGROUND BACKGROUND
Ferroptosis is a newly found non-apoptotic forms of cell death that plays an important role in tumors. However, the prognostic value of ferroptosis-related genes (FRG) in bladder cancer (BLCA) have not been well examined.
METHODS METHODS
FRG data and clinical information were collected from The Cancer Genome Atlas (TCGA). Then, significantly different FRGs were investigated by functional enrichment analyses. The prognostic FRG signature was identified by univariate cox regression and least absolute shrinkage and selection operator (LASSO) analysis, which was validated in TCGA cohort and Gene Expression Omnibus (GEO) cohort. Subsequently, the nomogram integrating risk scores and clinical parameters were established and evaluated. Additionally, Gene Set Enrichment Analyses (GSEA) was performed to explore the potential molecular mechanisms underlying our prognostic FRG signature. Finally, the expression of three key FRGs was verified in clinical specimens.
RESULTS RESULTS
Thirty-two significantly different FRGs were identified from TCGA-BLCA cohort. Enrichment analyses showed that these genes were mainly related to the ferroptosis. Seven genes (TFRC, G6PD, SLC38A1, ZEB1, SCD, SRC, and PRDX6) were then identified to develop a prognostic signature. The Kaplan-Meier analysis confirmed the predictive value of the signature for overall survival (OS) in both TCGA and GEO cohort. A nomogram integrating age and risk scores was established and demonstrated high predictive accuracy, which was validated through calibration curves and receiver operating characteristic (ROC) curve [area under the curve (AUC) = 0.690]. GSEA showed that molecular alteration in the high- or low-risk group was closely associated with ferroptosis. Finally, experimental results confirmed the expression of SCD, SRC, and PRDX6 in BLCA.
CONCLUSION CONCLUSIONS
Herein, we identified a novel FRG prognostic signature that maybe involved in BLCA. It showed high values in predicting OS, and targeting these FRGs may be an alternative for BLCA treatment. Further experimental studies are warranted to uncover the mechanisms that these FRGs mediate BLCA progression.

Identifiants

pubmed: 34557413
doi: 10.3389/fonc.2021.730716
pmc: PMC8455063
doi:

Types de publication

Journal Article

Langues

eng

Pagination

730716

Informations de copyright

Copyright © 2021 Sun, Yue, You, Wei, Huang, Ling and Hou.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Références

Adv Mater. 2019 Dec;31(51):e1904197
pubmed: 31595562
Cancer Res. 2019 Oct 15;79(20):5355-5366
pubmed: 31270077
Aging (Albany NY). 2021 Apr 4;13(7):10396-10414
pubmed: 33819918
Acta Pharmacol Sin. 2019 Oct;40(10):1334-1342
pubmed: 31036877
Curr Genomics. 2008;9(5):349-60
pubmed: 19517027
Aging (Albany NY). 2020 Jul 20;12(14):14933-14948
pubmed: 32688345
Proc Natl Acad Sci U S A. 2005 Oct 25;102(43):15545-50
pubmed: 16199517
Cancer Cell. 2019 Jun 10;35(6):830-849
pubmed: 31105042
Eur Urol. 2021 Jan;79(1):82-104
pubmed: 32360052
N Engl J Med. 2011 Jan 27;364(4):340-50
pubmed: 21268726
J Cancer. 2020 Feb 10;11(9):2390-2400
pubmed: 32201510
Aging (Albany NY). 2020 Jul 29;12(15):15374-15391
pubmed: 32726752
Biochim Biophys Acta. 2016 Dec;1861(12 Pt A):1865-1880
pubmed: 27639967
Hematol Oncol Clin North Am. 2021 Jun;35(3):633-653
pubmed: 33958155
J Urol. 2020 Mar;203(3):505-511
pubmed: 31609178
J Biol Chem. 2012 Feb 10;287(7):4403-10
pubmed: 22147704
J Cell Biol. 2017 Dec 4;216(12):4287-4297
pubmed: 28972104
J Cell Physiol. 2010 Apr;223(1):14-26
pubmed: 20049846
CA Cancer J Clin. 2021 May;71(3):209-249
pubmed: 33538338
Clin Exp Med. 2021 Aug;21(3):467-477
pubmed: 33674956
Nucleic Acids Res. 2019 Jul 2;47(W1):W556-W560
pubmed: 31114875
Database (Oxford). 2020 Jan 1;2020:
pubmed: 32219413
Cell. 2014 Jan 16;156(1-2):317-331
pubmed: 24439385
Nat Struct Mol Biol. 2015 Jul;22(7):581-5
pubmed: 26098317
Nucleic Acids Res. 2009 Jan;37(1):1-13
pubmed: 19033363
Arch Pathol Lab Med. 2019 Jun;143(6):695-704
pubmed: 30672335
J Cell Mol Med. 2019 Mar;23(3):2064-2076
pubmed: 30592142
Nucleic Acids Res. 2000 Jan 1;28(1):27-30
pubmed: 10592173
Nature. 2015 Apr 2;520(7545):57-62
pubmed: 25799988
Redox Biol. 2021 Jan;38:101807
pubmed: 33271455
World J Urol. 2019 Jan;37(1):31-40
pubmed: 30259123
Redox Biol. 2019 May;23:101107
pubmed: 30692038
Front Mol Biosci. 2021 May 21;8:675651
pubmed: 34095228
Life Sci. 2021 Aug 1;278:119529
pubmed: 33894270
JAMA. 2020 Nov 17;324(19):1980-1991
pubmed: 33201207
Cancer Cell Int. 2021 Feb 18;21(1):124
pubmed: 33602233
Cell. 2012 May 25;149(5):1060-72
pubmed: 22632970

Auteurs

Jiale Sun (J)

Department of Urology, The First Affiliated Hospital of Soochow University, Suzhou, China.

Wenchang Yue (W)

Department of Urology, The First Affiliated Hospital of Soochow University, Suzhou, China.

Jiawei You (J)

Department of Urology, The First Affiliated Hospital of Soochow University, Suzhou, China.

Xuedong Wei (X)

Department of Urology, The First Affiliated Hospital of Soochow University, Suzhou, China.

Yuhua Huang (Y)

Department of Urology, The First Affiliated Hospital of Soochow University, Suzhou, China.

Zhixin Ling (Z)

Department of Urology, The First Affiliated Hospital of Soochow University, Suzhou, China.

Jianquan Hou (J)

Department of Urology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Department of Urology, Dushu Lake Hospital Affiliated to Soochow University, Suzhou, China.

Classifications MeSH