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Comprehensive Analysis of the Expression and Clinical Significance of a Ferroptosis-Related Genome in Ovarian Serous Cystadenocarcinoma: A Study Based on TCGA Data

Hua Yang*

Department of Gynecology, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, 519000, China

* Corresponding Author: Hua Yang. Email: email

(This article belongs to the Special Issue: Ferroptosis in the Occurrence and Treatment of Cancer)

Oncologie 2022, 24(4), 835-863. https://doi.org/10.32604/oncologie.2022.026447

Abstract

Background: Epithelial ovarian cancer (EOC) is the deadliest malignancy among the gynecologic tumors, and ovarian serous cystadenocarcinoma (OV) is the dominant histological type. Ferroptosis is a novel iron-dependent, programmed form of cell death, and agents that trigger ferroptosis may constitute potential anti-cancer therapies. Materials and Methods: We herein extracted the genes that participate in the process of ferroptosis from the online FerrDb database to create a ferroptosis-related genome (FRG), and then comprehensively analyzed the relationship between the mRNA expression of each gene and the clinicopathologic features of The Cancer Genome Atlas (TCGA)-OV cohort. Results: We found that most of the FRG genes were differently expressed between OV and normal ovarian tissue and were significantly related to the prognosis of OV. In addition, gene ontology (GO) analysis revealed that the candidate genes of the FRG were primarily associated with responses to nutrient levels, oxidative stress, oxygen levels, and neuronal death. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated that candidate genes of the FRG were primarily associated with ferroptosis, hepatitis B, mitophagy, prostate cancer, and bladder cancer. The protein–protein interaction (PPI) network exhibited 132 nodes, 565 edges, an average node degree of 9.94, and an average local clustering coefficient of 0.539, indicating that the proteins were closely interrelated with one another and constitute a biological cluster. A comprehensive analysis of the top 5 genes involved in promoting and preventing ferroptosis revealed that these genes were differently expressed between OV and normal ovarian tissue, were significantly related to the prognosis of OV, reflected excellent diagnostic value, and were significantly correlated with immune cell infiltration in the tumor microenvironment (TME), polarization of macrophages, and with immune checkpoints. The protein levels of top 5 genes involved in promoting ferroptosis were differentially expressed between OV and normal ovarian tissue, and the top 5 genes involved in preventing ferroptosis were constitutively expressed in most of the normal tissues and tumors. Conclusions: We herein ascertained that the majority of the FRG was differentially expressed between OV and normal ovarian tissue, that the genes were significantly related to prognosis, and that the dysregulation of ferroptosis appeared to influence the development and progression of OV. The FRG showed an excellent diagnostic value for OV, and we postulate that it is significantly correlated with immune cell infiltration and immune checkpoints in the TME. We posit that targeting ferroptosis might comprise a novel anti-cancer therapy in OV.

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APA Style
Yang, H. (2022). Comprehensive analysis of the expression and clinical significance of a ferroptosis-related genome in ovarian serous cystadenocarcinoma: A study based on TCGA data. Oncologie, 24(4), 835-863. https://doi.org/10.32604/oncologie.2022.026447
Vancouver Style
Yang H. Comprehensive analysis of the expression and clinical significance of a ferroptosis-related genome in ovarian serous cystadenocarcinoma: A study based on TCGA data. Oncologie . 2022;24(4):835-863 https://doi.org/10.32604/oncologie.2022.026447
IEEE Style
H. Yang, “Comprehensive Analysis of the Expression and Clinical Significance of a Ferroptosis-Related Genome in Ovarian Serous Cystadenocarcinoma: A Study Based on TCGA Data,” Oncologie , vol. 24, no. 4, pp. 835-863, 2022. https://doi.org/10.32604/oncologie.2022.026447



cc Copyright © 2022 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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