Ferroptosis‐related gene signature as a prognostic marker for lower‐grade gliomas

Zheng, Yi; Ji, Qiang; Xie, Lei; Wang, Can; Yu, Chunna; Wang, Yali; Jiang, Jing; Chen, Feng; Li, Wenbin

doi:10.1111/jcmm.16368

Cited by 31 publications

(29 citation statements)

References 46 publications

(84 reference statements)

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“…For example, Zhu et al demonstrated the utility of a 4-FRGs model in predicting the prognosis of esophageal adenocarcinoma (38). Zheng et al developed a 12-FRGs model to better predict the prognosis of patients with lower-grade gliomas (39). Jiang and his colleagues constructed an eight-gene ferroptosis-related prognostic model to predict the prognosis of gastric cancer patients (40).…”

Section: Discussionmentioning

confidence: 99%

A New Prognostic Risk Signature of Eight Ferroptosis-Related Genes in the Clear Cell Renal Cell Carcinoma

et al. 2021

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Clear cell renal cell carcinoma (ccRCC) is the most common renal cell carcinoma and has poor prognosis in the locally advanced stage. Ferroptosis, a relatively new type of cell death, has gained significant attention in recent years. This study aimed to explore the prognostic value of ferroptosis-related genes (FRGs) in ccRCC. In this study, 50 differentially expressed FRGs between ccRCC and adjacent normal kidney tissues were identified, 26 of them correlated with overall survival (OS) (P <0.05). Eight optimal FRGs were selected by Lasso regression and multivariate Cox regression analysis, and used to construct a new prognostic risk signature to predict the prognosis of ccRCC patients. In addition, the signature passed the validation of prognostic survival analyses by a significant margin, and the risk score was identified as an independent prognostic marker via Cox regression analyses. Further studies indicated that the signature was significantly correlated with immune cell infiltration. Moreover, the levels of eight FRGs were examined in ccRCC. Collectively, the 8-FRG prognostic risk signature helps the clinicians predict the prognosis and OS of the patients, and standardize prognostic assessments.

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Section: Discussionmentioning

confidence: 99%

A New Prognostic Risk Signature of Eight Ferroptosis-Related Genes in the Clear Cell Renal Cell Carcinoma

et al. 2021

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“…By integrating different independent prognostic factors, the nomogram can predict the possibility of an event outcome, such as the possibility of death or disease recurrence [ 17 ]. Several ferroptosis-related gene nomograms for predicting prognosis have been established for various types of cancer [ 18 , 19 ]. Zheng et al [ 18 ] developed a 12-FRG signature to predict the OS of patients with lower-grade gliomas, which showed a favorable predictive capacity.…”

Section: Discussionmentioning

confidence: 99%

“…Several ferroptosis-related gene nomograms for predicting prognosis have been established for various types of cancer [ 18 , 19 ]. Zheng et al [ 18 ] developed a 12-FRG signature to predict the OS of patients with lower-grade gliomas, which showed a favorable predictive capacity. Based on the signature and clinicopathological features, they established a nomogram for predicting 1-, 3-, and 5-year OS.…”

Section: Discussionmentioning

confidence: 99%

Identification and validation of a novel ferroptosis-related gene model for predicting the prognosis of gastric cancer patients

Liu

et al. 2021

PLoS ONE

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Background Ferroptosis is a novel form of regulated cell death that plays a critical role in tumorigenesis. The purpose of this study was to establish a ferroptosis-associated gene (FRG) signature and assess its clinical outcome in gastric cancer (GC). Methods Differentially expressed FRGs were identified using gene expression profiles from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. Univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses were performed to construct a prognostic signature. The model was validated using an independent GEO dataset, and a genomic-clinicopathologic nomogram integrating risk scores and clinicopathological features was established. Results An 8-FRG signature was constructed to calculate the risk score and classify GC patients into two risk groups (high- and low-risk) according to the median value of the risk score. The signature showed a robust predictive capacity in the stratification analysis. A high-risk score was associated with advanced clinicopathological features and an unfavorable prognosis. The predictive accuracy of the signature was confirmed using an independent GSE84437 dataset. Patients in the two groups showed different enrichment of immune cells and immune-related pathways. Finally, we established a genomic-clinicopathologic nomogram (based on risk score, age, and tumor stage) to predict the overall survival (OS) of GC patients. Conclusions The novel FRG signature may be a reliable tool for assisting clinicians in predicting the OS of GC patients and may facilitate personalized treatment.

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“…To date, the establishment of cancer prognostic models has been a mainstream of tumor research. For instance, Zheng et al (2021) identified 12 prognostic feature genes associated with ferroptosis in low level glioma. Jiang et al (2019) analyzed the glycolysis gene expression profiles of hepatocellular carcinoma and acquired a prognostic model based on metabolism-associated feature genes.…”

Section: Discussionmentioning

confidence: 99%

Investigation of Prognostic Markers of Lung Adenocarcinoma Based on Tumor Metabolism-Related Genes

Zhang

Cheng³

2021

Front. Genet.

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Lung adenocarcinoma (LUAD) is a prevalent cancer killer. Investigation on potential prognostic markers of LUAD is crucial for a patient’s postoperative planning. LUAD-associated datasets were acquired from Gene Expression Omnibus (GEO) as well as The Cancer Genome Atlas (TCGA). LUAD metabolism-associated differentially expressed genes were obtained, combining tumor metabolism-associated genes. COX regression analyses were conducted to build a five-gene prognostic model. Samples were divided into high- and low-risk groups by the established model. Survival analysis displayed favorable prognosis in the low-risk group in the training set. Favorable predictive performance of the model was discovered as hinted by receiver’s operative curve (ROC). Survival analysis and ROC analysis in the validation set held an agreement. Gene Set Enrichment Analysis (GSEA), tumor mutation bearing (TMB), and immune infiltration differential analysis were performed. The two groups displayed differences in glycolysis gluconeogenesis, P53 signaling pathway, etc. The high-risk group showed higher TP53 mutation frequency as well as TMB. The low-risk group displayed higher immune activity along with immune score. Altogether, this study casts light on further development of novel prognostic markers for LUAD.

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Ferroptosis‐related gene signature as a prognostic marker for lower‐grade gliomas

Cited by 31 publications

References 46 publications

A New Prognostic Risk Signature of Eight Ferroptosis-Related Genes in the Clear Cell Renal Cell Carcinoma

A New Prognostic Risk Signature of Eight Ferroptosis-Related Genes in the Clear Cell Renal Cell Carcinoma

Identification and validation of a novel ferroptosis-related gene model for predicting the prognosis of gastric cancer patients

Investigation of Prognostic Markers of Lung Adenocarcinoma Based on Tumor Metabolism-Related Genes

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