Identification of <scp>FDFT1</scp> as a potential biomarker associated with ferroptosis in <scp>ccRCC</scp>

Huang, Ruizhen; Zhang, Chiyu; Wang, Xing; Zou, Xin; Xiang, Zhengjie; Wang, Zewei; Gui, Bin; Lin, Tao; Hu, Honglin

doi:10.1002/cam4.4716

Cited by 13 publications

(13 citation statements)

References 29 publications

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“…Current studies have shown that these genes are associated with the prognosis of multiple cancers and can be used as independent risk factors for tumors. [30][31][32][33][34][35][36] Consensus clustering with this 10 gene expression signature identi ed three genomic subtypes with similar results to the ferroptosis phenotype cluster. Similarly, using survival analysis, GSVA enrichment analysis, and immune cell in ltrate signature analysis, we demonstrated that overall TME in ltration mediated by multiple FRG types was strongly associated with overall survival in osteosarcoma patients again.…”

Section: Discussionmentioning

confidence: 96%

A novel defined ferroptosis-related gene signature for predicting the prognosis of Osteosarcoma

Pan,

Huang,

Zhu

et al. 2023

Preprint

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Background Osteosarcoma is a malignant tumor that is harmful to adolescents and has a poor prognosis. There is no effective treatment at now. This study aimed to construct a prognosis based on ferroptosis-related genes to provide guidance for the treatment of osteosarcoma. Methods In this study, we identified three ferroptosis-regulating genes that were distinctly expressed in osteosarcoma and normal tissues. Osteosarcoma patients from three datasets were classified using consensus clustering of these three ferroptosis-regulated genes, and gene differences among the three subtypes were analyzed in one step, and these differentially expressed genes were analyzed by univariate regression (DEGs), the ssGSEA method was used to assess the tumor microenvironment (TME), and the principal component analysis algorithm was used to quantitatively construct a predictive model. Finally, we use qRT-PCR to detect gene expression to validate the model. Results We identified three distinct ferroptosis genotypes, and the differences between the three subtypes were used to build a prognostic model, which we termed the "Ferroptosis-Score". The score can predict the prognosis and overall survival time of patients with osteosarcoma. The survival of patients with high scores is higher than that of patients with low scores (P < 0.05). At the same time, it is observed that immune cell infiltration in patients with high scores is significantly higher than that in patients with low scores. Conclusion We constructed a Ferroptosis-Score scoring system, the higher the score, the better the prognosis of the patient. And found that cluster C may activates ferroptosis through autophagy and JAK-STAT signaling pathway, so the patients of cluster C have better prognosis.

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Section: Discussionmentioning

confidence: 96%

A novel defined ferroptosis-related gene signature for predicting the prognosis of Osteosarcoma

Pan,

Huang,

Zhu

et al. 2023

Preprint

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“…FDFT1 encodes a membranelinked enzyme, which constituted the rst speci c enzyme in cholesterol biosynthesis [23]. Recent study showed that increased expression of FDFT1 could potentially enhance ferroptosis through the AKT signaling pathway, but the speci c molecular mechanism remains unclear [24]. Weng et al demonstrated that fasting suppressed aerobic glycolysis as well as CRC cell proliferation through the FDFT1/AKT-mTOR-HIF1α axis and that FDFT1 de ciency was linked to a dismal prognosis in CRC [23].…”

Section: Discussionmentioning

confidence: 99%

Identification of ferroptosis-related prognostic models and FDFT1 as a potential ferroptosis driver in colorectal cancer

Duan

Cao²,

Liu

et al. 2023

Preprint

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Background: Prediction of colorectal cancer (CRC) prognosis is challenging. Ferroptosis constitutes a newly reported kind of cell death, and its association with CRC prognosis remains unexplored. Herein, we aimed to develop ferroptosis-related gene (FRG) signatures to predict overall survival (OS) along with disease-free survival (DFS) in individuals with CRC. Methods: The clinical data and mRNA expression were extracted from the TCGA web data resource. The Lasso algorithm was utilized to construct the OS and DFS prediction signatures. Independent data from GSE38832 were used for verification. Results: Our findings revealed there was a discrepancy in the expression of 85% of FRGs between CRC and healthy tissues. Among them, 11 prognostic genes were identified using UniCox analysis. Predicted risk scores from the two models stratified patients into low- as well as high-risk groups and were demonstrated as independent prognostic factors using MultiCox analysis. The efficacy of the models was verified using ROC curve analysis. Functional enrichment analysis indicated that cancer-linked pathways were abundant in the high-risk group, and that immune status differed between the two risk groups. The CMap web data resource helped in identifying a total of sixteen potential drugs. In addition, FDFT1 was proved to play an anti-tumor role in CRC and may promote ferroptosis by regulating the expression of ISCU. Conclusions: Our FRG-based prognostic models are reliable predictive tools for CRC patients, suggesting that FRGs may be potential targets for CRC therapy.

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“…It can be an effective predictive biomarker in ccRCC, and the nomogram based on KIF23 may help with improved treatment recommendations for ccRCC patients [106]. Other studies reported that FDFT1 and acyl-CoA thioesterases 8 and 11 can be used as new biomarkers for ccRCC [107, 108]. Zhu et al [109] indicated that ZNF419 had the potential to serve as a prognostic and immunological pancancer biomarker, particularly for KIRC, LIHC, LUSC, PRAD, and BLCA.…”

Section: Ferroptosis and Kidney Diseasesmentioning

confidence: 99%

Novel Insight into Ferroptosis in Kidney Diseases

Liu¹,

Liu²,

Zhou³

et al. 2023

Am J Nephrol

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Background: Various kidney diseases such as acute kidney injury, chronic kidney disease, polycystic kidney disease, renal cancer, and kidney stones, are an important part of the global burden, bringing a huge economic burden to people around the world. Ferroptosis is a type of nonapoptotic iron-dependent cell death caused by the excess of iron-dependent lipid peroxides and accompanied by abnormal iron metabolism and oxidative stress. Over the past few decades, several studies have shown that ferroptosis is associated with many types of kidney diseases. Studying the mechanism of ferroptosis and related agonists and inhibitors may provide new ideas and directions for the treatment of various kidney diseases. Summary: In this review, we discuss the differences between ferroptosis and other types of cell death such as apoptosis, necroptosis, pyroptosis, cuprotosis, pathophysiological features of the kidney, and ferroptosis-induced kidney injury. We also provide an overview of the molecular mechanisms involved in ferroptosis and events that lead to ferroptosis. Furthermore, we summarize the possible clinical applications of this mechanism among various kidney diseases. Key Message: The current research suggests that future therapeutic efforts to treat kidney ailments would benefit from a focus on ferroptosis.

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Identification of FDFT1 as a potential biomarker associated with ferroptosis in ccRCC

Cited by 13 publications

References 29 publications

A novel defined ferroptosis-related gene signature for predicting the prognosis of Osteosarcoma

A novel defined ferroptosis-related gene signature for predicting the prognosis of Osteosarcoma

Identification of ferroptosis-related prognostic models and FDFT1 as a potential ferroptosis driver in colorectal cancer

Novel Insight into Ferroptosis in Kidney Diseases

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