Ferroptosis‐based molecular prognostic model for adrenocortical carcinoma based on least absolute shrinkage and selection operator regression

Cc, Lin; Hu, Ruofei; Sun, Fangfang; Liang, Weiwei

doi:10.1002/jcla.24465

Cited by 7 publications

(5 citation statements)

References 44 publications

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Section: Discussionmentioning

confidence: 92%

“…However, STMN1 has been reported to as an important ferrGene in coronary artery disease, 45 soft tissue sarcoma, 46 adrenocortical carcinoma. 47 Similarly, the research of Wang et al 48 exhibited that STMN1 was a ferrGene that correlated to the poor survival of HCC. Moreover, STMN1 was identified as a prognostically relevant methylation-driven ferrGene in HCC, with diminished methylation level of STMN1 found in HCC tissues.…”

Section: Discussionmentioning

confidence: 95%

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CENPA-driven STMN1 Transcription Inhibits Ferroptosis in Hepatocellular Carcinoma

Liang¹,

Luo²,

Wang³

et al. 2023

J Clin Transl Hepatol

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Background and Aims The growing knowledge of ferroptosis has suggested the regulatory role of ferroptosis in hepatocellular carcinoma (HCC), but the pertinent molecular mechanisms remain unclear. Herein, this study investigated the mechanistic basis of ferroptosis-related genes (ferrGenes) in the growth of HCC. Methods Differentially expressed human ferrGenes and tumor-related transcription factors (TFs) were obtained from the The Cancer Genome Atlas (TCGA) dataset and the GTEx dataset. Spearman method-based correlation analysis were conducted to construct TF-ferrGene coexpression regulatory network. Key genes associated with prognosis were singled out with Lasso regression and multivariate Cox analysis to construct the prognostic risk model. Then the accuracy and independent prognostic ability of the model were evaluated. Expression of CENPA and STMN1 was determined in clinical HCC tissues and HCC cells, and their binding was analyzed with dual-luciferase and chromatin immunoprecipitation (ChIP) assays. Furthermore, ectopic expression and knockdown assays were performed in HCC cells to assess the effect of CENPA and STMN1 on ferroptosis and malignant phenotypes. Results The prognostic risk model constructed based on the eight TF-ferrGene regulatory network-related genes accurately predicted the prognosis of HCC patients. It was strongly related to the clinical characteristics of HCC patients. Moreover, CENPA/STMN1 might be a key TF-ferrGene regulatory network in ferroptosis of HCC. CENPA and STMN1 were overexpressed in HCC tissues and cells. Additionally, CENPA facilitated STMN1 transcription by binding to STMN1 promoter, thus facilitating the malignant phenotypes and suppressing the ferroptosis of HCC cells. Conclusions Taken together, CENPA curbs the ferroptosis of HCC cells by upregulating STMN1 transcription, thereby promoting HCC growth.

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Section: Discussionmentioning

confidence: 92%

Section: Discussionmentioning

confidence: 95%

CENPA-driven STMN1 Transcription Inhibits Ferroptosis in Hepatocellular Carcinoma

Liang¹,

Luo²,

Wang³

et al. 2023

J Clin Transl Hepatol

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“…The K-M and ROC curves suggested that the model had good predictive value. Nomograms have been well developed as a prognostic assessment tool and have been proven to be more accurate than conventional staging systems in several cancers ( 30 ). We constructed a nomogram in combination with clinical factors.…”

Section: Discussionmentioning

confidence: 99%

A signature of four ferroptosis-related genes in laryngeal squamous cell carcinoma

Zhao,

Chen,

Qiao

et al. 2024

Transl Cancer Res

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Background Laryngeal squamous cell carcinoma (LSCC) prognosis has not improved significantly in the past few decades, and more effective treatments are needed to be explored. Ferroptosis is a newly discovered kind of regulated cell death in recent years, which is related to tumor immunity and can used to treat tumors. Therefore, the prognostic value of ferroptosis-related genes in laryngeal cancer needs further clarification. Methods In this study, the mRNA expression profile data of LSCC were downloaded from the public database. After identifying ferroptosis-related differentially expressed genes (FDGs), we explored the role of these genes through functional enrichment analysis. FDGs with prognostic significance were identified by univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses. By calculating the risk score, we constructed a prognostic model. Kaplan-Meier (K-M) analysis, the receiver operating characteristic (ROC) curves, and the nomogram were utilized to investigate this model. Public databases and quantitative real-time polymerase chain reaction (qRT-PCR) were performed to verify the expression of model genes. Results The model consisting of four FDGs was acknowledged to be a self-determining predictor of prognosis. The K-M survival curves and the ROC curves confirmed the model’s predictive ability. The C index (0.805) indicates that the nomogram has a good predictive ability. In vitro studies have confirmed the differential expression of the four FDGs. Conclusions We identified a novel ferroptosis-related gene signature for predicting prognosis in LSCC.

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“…We used the least absolute shrinkage and selection operator (LASSO) algorithm based on the R software "glmnet" package and the support vector machine -recursive feature elimination (SVM-RFE) based on the "e1071" package to further screen for characteristic FRGs biomarkers associated with IS [21,22]. The biomarkers obtained by both methods were intersected to get the characteristic FRGs and visualized by R software.…”

Section: Screen Characteristic Frgs For Ismentioning

confidence: 99%

Identification of five characteristic ferroptosis-related genes as novel biomarkers for ischemic stroke using bioinformatic and machine learning strategies

Feng¹,

Huang²,

Lin³

et al. 2023

Preprint

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Ferroptosis is crucial in neuronal cell death, associated with various neurological disorders. However, the role of ferroptosis-related genes (FRGs) in ischaemic stroke (IS) has yet to be well elucidated. We downloaded IS-related gene information and FRGs from the Gene Expression Omnibus (GEO) and Ferritin databases (FerrDb). 22 IS-related DE-FRGs were obtained. Functional enrichment analysis showed that these genes involve multiple regulatory pathways related to IS pathogenesis, including redox, amino acid metabolism, and cell cycle. Subsequently, DUOX2, MDM2, EGFR, MAP3K14, and TRIM46 were identified as core marker genes among the 22 DE-FRGs by lasso and SVM-RFE algorithms. The construction of the nomogram using the five marker genes had excellent diagnostic value. In addition, CIBERSORT analysis showed that changes in the immune microenvironment of IS patients might be associated with TRIM46, MDM2, and DUOX2. In addition, a total of 66 drugs targeting two characteristic FRGs were obtained. The ceRNA networks revealed complex regulatory relationships based on characteristic FRGs. These findings provide new insights into the diagnosis and treatment of IS.

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Ferroptosis‐based molecular prognostic model for adrenocortical carcinoma based on least absolute shrinkage and selection operator regression

Cited by 7 publications

References 44 publications

CENPA-driven STMN1 Transcription Inhibits Ferroptosis in Hepatocellular Carcinoma

CENPA-driven STMN1 Transcription Inhibits Ferroptosis in Hepatocellular Carcinoma

A signature of four ferroptosis-related genes in laryngeal squamous cell carcinoma

Identification of five characteristic ferroptosis-related genes as novel biomarkers for ischemic stroke using bioinformatic and machine learning strategies

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