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A novel survival model based on a Ferroptosis-related gene signature for predicting overall survival in bladder cancer
by
Ye, Fangdie
, Hu, Yun
, Liang, Yingchun
, Jiang, Haowen
, Xu, Chenyang
, Hu, Jimeng
, Zou, Lujia
in
Apoptosis
/ Biomedical and Life Sciences
/ Biomedicine
/ Bladder cancer
/ Cancer
/ Cancer Research
/ Cancer therapies
/ Cell death
/ Diagnosis
/ Ferroptosis
/ Gene expression
/ Gene set enrichment analysis
/ Gene signature
/ Genetic aspects
/ Genomes
/ Glucosephosphate dehydrogenase
/ Health aspects
/ Health Promotion and Disease Prevention
/ Medical prognosis
/ Medicine/Public Health
/ Oncology
/ Ovarian cancer
/ Patients
/ Principal components analysis
/ Prognosis
/ Prognostic model
/ Regression analysis
/ Risk groups
/ Surgical Oncology
/ The Cancer genome atlas (TCGA)
/ Tumors
2021
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A novel survival model based on a Ferroptosis-related gene signature for predicting overall survival in bladder cancer
by
Ye, Fangdie
, Hu, Yun
, Liang, Yingchun
, Jiang, Haowen
, Xu, Chenyang
, Hu, Jimeng
, Zou, Lujia
in
Apoptosis
/ Biomedical and Life Sciences
/ Biomedicine
/ Bladder cancer
/ Cancer
/ Cancer Research
/ Cancer therapies
/ Cell death
/ Diagnosis
/ Ferroptosis
/ Gene expression
/ Gene set enrichment analysis
/ Gene signature
/ Genetic aspects
/ Genomes
/ Glucosephosphate dehydrogenase
/ Health aspects
/ Health Promotion and Disease Prevention
/ Medical prognosis
/ Medicine/Public Health
/ Oncology
/ Ovarian cancer
/ Patients
/ Principal components analysis
/ Prognosis
/ Prognostic model
/ Regression analysis
/ Risk groups
/ Surgical Oncology
/ The Cancer genome atlas (TCGA)
/ Tumors
2021
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A novel survival model based on a Ferroptosis-related gene signature for predicting overall survival in bladder cancer
by
Ye, Fangdie
, Hu, Yun
, Liang, Yingchun
, Jiang, Haowen
, Xu, Chenyang
, Hu, Jimeng
, Zou, Lujia
in
Apoptosis
/ Biomedical and Life Sciences
/ Biomedicine
/ Bladder cancer
/ Cancer
/ Cancer Research
/ Cancer therapies
/ Cell death
/ Diagnosis
/ Ferroptosis
/ Gene expression
/ Gene set enrichment analysis
/ Gene signature
/ Genetic aspects
/ Genomes
/ Glucosephosphate dehydrogenase
/ Health aspects
/ Health Promotion and Disease Prevention
/ Medical prognosis
/ Medicine/Public Health
/ Oncology
/ Ovarian cancer
/ Patients
/ Principal components analysis
/ Prognosis
/ Prognostic model
/ Regression analysis
/ Risk groups
/ Surgical Oncology
/ The Cancer genome atlas (TCGA)
/ Tumors
2021
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A novel survival model based on a Ferroptosis-related gene signature for predicting overall survival in bladder cancer
Journal Article
A novel survival model based on a Ferroptosis-related gene signature for predicting overall survival in bladder cancer
2021
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Overview
Background
The effective treatment and prognosis prediction of bladder cancer (BLCA) remains a medical problem. Ferroptosis is an iron-dependent form of programmed cell death. Ferroptosis is closely related to tumour occurrence and progression, but the prognostic value of ferroptosis-related genes (FRGs) in BLCA remains to be further clarified. In this study, we identified an FRG signature with potential prognostic value for patients with BLCA.
Methods
The corresponding clinical data and mRNA expression profiles of BLCA patients were downloaded from The Cancer Genome Atlas (TCGA). Univariate Cox regression was used to extract FRGs related to survival time, and a Cox regression model was used to construct a multigene signature. Both principal component analysis (PCA) and single-sample gene set enrichment analysis (ssGSEA) were performed for functional annotation.
Results
Clinical traits were combined with FRGs, and 15 prognosis-related FRGs were identified by Cox regression. High expression of CISD1, GCLM, CRYAB, SLC7A11, TFRC, ACACA, ZEB1, SQLE, FADS2, ABCC1, G6PD and PGD was related to poor survival in BLCA patients. Multivariate Cox regression was used to construct a prognostic model with 7 FRGs that divided patients into two risk groups. Compared with that in the low-risk group, the overall survival (OS) of patients in the high-risk group was significantly lower (
P
< 0.001). In multivariate regression analysis, the risk score was shown to be an independent predictor of OS (HR = 1.772,
P
< 0.01). Receiver operating characteristic (ROC) curve analysis verified the predictive ability of the model. In addition, the two risk groups displayed different immune statuses in ssGSEA and different distributed patterns in PCA.
Conclusion
Our research suggests that a new gene model related to ferroptosis can be applied for the prognosis prediction of BLCA. Targeting FRGs may be a treatment option for BLCA.
Publisher
BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
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