Systematic Analysis of the Aberrances and Functional Implications of Ferroptosis in Cancer

Li, Yi; Zhao, Qi; Zuo, Zhixiang; Yuan, Shuqiang; Yu, Kai; Zhang, Qingfeng; Zhang, Xiaolong; Sheng, Hui; Ju, Huai-Qiang; Cheng, Han; Wang, Feng; Xu, Rui‐Hua; Liu, Zexian

doi:10.1016/j.isci.2020.101302

Cited by 165 publications

(171 citation statements)

References 46 publications

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“…In recent years, ferroptosis has gradually become a promising therapeutic method for inducing cancer cell death [ 6 ]. Ferroptosis has been observed associated with tumor prognosis [ 7 ] and a prognostic ferroptosis-related gene signature has been successfully established in hepatocellular carcinoma [ 8 ]. In GC, some genes have been found to play a vital role in regulating ferroptosis.…”

Section: Introductionmentioning

confidence: 99%

Construction and Validation of a Ferroptosis-Related Prognostic Model for Gastric Cancer

Jiang

Yan

Xie

et al. 2021

Journal of Oncology

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Background. Gastric cancer (GC), an extremely aggressive tumor with a very different prognosis, is the third leading cause of cancer-related mortality. We aimed to construct a ferroptosis-related prognostic model that can be distinguished prognostically. Methods. The gene expression and the clinical data of GC patients were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus database (GEO). The ferroptosis-related genes were obtained from the FerrDb. Using the “limma” R package and univariate Cox analysis, ferroptosis-related genes with differential expression and prognostic value were identified in the TCGA cohort. Last absolute shrinkage and selection operator (LASSO) Cox regression was applied to shrink ferroptosis-related predictors and construct a prognostic model. Functional enrichment, ESTIMATE algorithm, and single-sample gene set enrichment analysis (ssGSEA) were applied for exploring the potential mechanism. GC patients from the GEO cohort were used for validation. Results. An 8-gene prognostic model was constructed and stratified GC patients from TCGA and meta-GEO cohort into high-risk groups or low-risk groups. GC patients in high-risk groups have significantly poorer OS compared with those in low-risk groups. The risk score was identified as an independent predictor for OS. Functional analysis revealed that the risk score was mainly associated with the biological function of extracellular matrix (ECM) organization and tumor immunity. Conclusion. In conclusion, the ferroptosis-related model can be utilized for the clinical prognostic prediction in GC.

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Section: Introductionmentioning

confidence: 99%

Construction and Validation of a Ferroptosis-Related Prognostic Model for Gastric Cancer

Jiang

Yan

Xie

et al. 2021

Journal of Oncology

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“…Furthermore, the difference in ferroptosis gene expression between the unsupervised cluster group and the hub gene list showed significant differences (Fig. 5) (Liu et al 2020).…”

Section: Resultsmentioning

confidence: 99%

Identification and verification of the potential effect of therapeutic miRNA-mRNA pairs on ferroptosis in small cell lung cancer by bioinformatics analysis

2021

Preprint

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Owing to the high mortality rate of small cell lung cancer (SCLC), it is essential to determine a novel therapeutic approach for treating patients with SCLC. miRNA is a type of non-coding RNA that plays a role in translational control. By applying this identity, it is applicable for treating patients using miRNA and nanotechnology. Ferroptosis is a newly discovered type of programmed cell death. Accumulated evidence suggests the possibility of using ferroptosis in treating patients with SCLC. Thus, identifying potential therapeutic miRNA-mRNA pairs that have an impact on ferroptosis will be valuable. In the in silico analysis, several Gene Expression Omnibus datasets were analyzed. The results were verified using other data. Here, we report that the miR-30 family and KIF11 pair have a crucial influence on SCLC cells, which may also affect ferroptosis.

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“…Journal of Oncology checked [10,11]. Meanwhile, the association between risk score and survival status, clinical stage, and pathological grade was analyzed.…”

Section: Correlation Analyses Between Risk Model and Tumormentioning

confidence: 99%

Identifying Prognostic Significance of RCL1 and Four-Gene Signature as Novel Potential Biomarkers in HCC Patients

Liu

Zhang

Chen

et al. 2021

Journal of Oncology

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Background. Hepatocellular carcinoma (HCC) is a highly malignant disease, and it is characterized by rapid progression and low five-year survival rate. At present, there are no effective methods for monitoring the treatment and prognosis of HCC. Methods. The transcriptome and gene expression profiles of HCC were obtained from the Cancer Genome Atlas (TCGA) program, International Cancer Genome Consortium (ICGC), and Gene Expression Omnibus (GEO) databases. The random forest method was applied to construct a four-gene prognostic model based on RNA terminal phosphate cyclase like 1 (RCL1) expression. The Kaplan-Meier method was performed to evaluate the prognostic value of RCL1, long noncoding RNAs (AC079061, AL354872, and LINC01093), and four-gene signature (SPP1, MYBL2, TRNP1, and FTCD). We examined the relationship between RCL1 expression and immune cells infiltration, tumor mutation burden (TMB), and microsatellite instability (MSI). Results. The results of multiple databases indicated that the aberrant expression of RCL1 was associated with clinical outcome, immune cells infiltration, TMB, and MSI in HCC patients. Meanwhile, we found that long noncoding RNAs (AC079061, AL354872, and LINC01093) and RCL1 were significantly coexpressed in HCC patients. We also confirmed that the four-gene signature was an independent prognostic factor for HCC patients. Ferroptosis potential index, immune checkpoint molecules, and clinical feature were found to have obvious correlations with risk score. The area under the receiver operating characteristic curve values for the model were 0.7–0.8 in the training set and the validation set, suggesting high robustness of the four-gene signature. We then built a nomogram for facilitating the use in clinical practice. Conclusion. Our study demonstrated that RCL1 and a novel four-gene signature can be used as prognostic biomarkers for predicting clinical outcome in HCC patients; and this model may assist in individualized treatment monitoring of HCC patients in clinical practice.

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Systematic Analysis of the Aberrances and Functional Implications of Ferroptosis in Cancer

Cited by 165 publications

References 46 publications

Construction and Validation of a Ferroptosis-Related Prognostic Model for Gastric Cancer

Construction and Validation of a Ferroptosis-Related Prognostic Model for Gastric Cancer

Identification and verification of the potential effect of therapeutic miRNA-mRNA pairs on ferroptosis in small cell lung cancer by bioinformatics analysis

Identifying Prognostic Significance of RCL1 and Four-Gene Signature as Novel Potential Biomarkers in HCC Patients

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