Ferroptosis-related biomarkers for adamantinomatous craniopharyngioma treatment: conclusions from machine learning techniques.

IF 3.9 2区 医学 Q2 ENDOCRINOLOGY & METABOLISM Frontiers in Endocrinology Pub Date : 2024-11-13 eCollection Date: 2024-01-01 DOI:10.3389/fendo.2024.1362278
Ying Feng, Zhen Zhang, Jiahao Tang, Yan Chen, Dan Hu, Xinwei Huang, Fangping Li
{"title":"Ferroptosis-related biomarkers for adamantinomatous craniopharyngioma treatment: conclusions from machine learning techniques.","authors":"Ying Feng, Zhen Zhang, Jiahao Tang, Yan Chen, Dan Hu, Xinwei Huang, Fangping Li","doi":"10.3389/fendo.2024.1362278","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Adamantinomatous craniopharyngioma (ACP) is difficult to cure completely and prone to recurrence after surgery. Ferroptosis as an iron-dependent programmed cell death, may be a critical process in ACP. The study aimed to screen diagnostic markers related to ferroptosis in ACP to improve diagnostic accuracy.</p><p><strong>Methods: </strong>Gene expression profiles of ACP were obtained from the gene expression omnibus (GEO) database. Limma package was used to analyze the differently expressed genes (DEGs). The intersection of DEGs and ferroptosis-related factors was obtained as differently expressed ferroptosis-related genes (DEFRGs). Enrichment analysis was processed, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), disease ontology (DO), gene set enrichment analysis (GSEA), and Gene Set Variation Analysis (GSVA) analysis. Machine learning algorithms were undertaken for screening diagnostic markers associated with ferroptosis in ACP. The levels of DEFRGs were verified in ACP patients. A nomogram was drawn to predict the relationship between key DEFRG expression and risk of disease. The disease groups were then clustered by consensus clustering analysis.</p><p><strong>Results: </strong>DEGs were screened between ACP and normal samples. Ferroptosis-related factors were obtained from the FerrDb V2 and GeneCard databases. The correlation between DEFRGs and ferroptosis markers was also confirmed. A total of 6 overlapped DEFRGs were obtained. Based on the results of the nomogram, CASP8, KRT16, KRT19, and TP63 were the protective factors of the risk of disease, while GOT1 and TFAP2C were the risk factors. According to screened DEFRGs, the consensus clustering matrix was differentiated, and the number of clusters was stable. CASP8, KRT16, KRT19, and TP63, were upregulated in ACP patients, while GOT1 was downregulated. CASP8, KRT16, KRT19, TP63, CASP8, and GOT1 affect multiple ferroptosis marker genes. The combination of these genes might be the biomarker for ACP diagnosis via participating ferroptosis process.</p><p><strong>Discussion: </strong>Ferroptosis-related genes, including CASP8, KRT16, KRT19, TP63, and GOT1 were the potential markers for ACP, which lays the theoretical foundation for ACP diagnosis.</p>","PeriodicalId":12447,"journal":{"name":"Frontiers in Endocrinology","volume":"15 ","pages":"1362278"},"PeriodicalIF":3.9000,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11598535/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Endocrinology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3389/fendo.2024.1362278","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
引用次数: 0

Abstract

Introduction: Adamantinomatous craniopharyngioma (ACP) is difficult to cure completely and prone to recurrence after surgery. Ferroptosis as an iron-dependent programmed cell death, may be a critical process in ACP. The study aimed to screen diagnostic markers related to ferroptosis in ACP to improve diagnostic accuracy.

Methods: Gene expression profiles of ACP were obtained from the gene expression omnibus (GEO) database. Limma package was used to analyze the differently expressed genes (DEGs). The intersection of DEGs and ferroptosis-related factors was obtained as differently expressed ferroptosis-related genes (DEFRGs). Enrichment analysis was processed, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), disease ontology (DO), gene set enrichment analysis (GSEA), and Gene Set Variation Analysis (GSVA) analysis. Machine learning algorithms were undertaken for screening diagnostic markers associated with ferroptosis in ACP. The levels of DEFRGs were verified in ACP patients. A nomogram was drawn to predict the relationship between key DEFRG expression and risk of disease. The disease groups were then clustered by consensus clustering analysis.

Results: DEGs were screened between ACP and normal samples. Ferroptosis-related factors were obtained from the FerrDb V2 and GeneCard databases. The correlation between DEFRGs and ferroptosis markers was also confirmed. A total of 6 overlapped DEFRGs were obtained. Based on the results of the nomogram, CASP8, KRT16, KRT19, and TP63 were the protective factors of the risk of disease, while GOT1 and TFAP2C were the risk factors. According to screened DEFRGs, the consensus clustering matrix was differentiated, and the number of clusters was stable. CASP8, KRT16, KRT19, and TP63, were upregulated in ACP patients, while GOT1 was downregulated. CASP8, KRT16, KRT19, TP63, CASP8, and GOT1 affect multiple ferroptosis marker genes. The combination of these genes might be the biomarker for ACP diagnosis via participating ferroptosis process.

Discussion: Ferroptosis-related genes, including CASP8, KRT16, KRT19, TP63, and GOT1 were the potential markers for ACP, which lays the theoretical foundation for ACP diagnosis.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
治疗金刚瘤性颅咽管瘤的铁突变相关生物标志物:机器学习技术的结论。
导言:金刚瘤性颅咽管瘤(ACP)难以彻底治愈,术后容易复发。铁突变作为一种铁依赖性程序性细胞死亡,可能是ACP的一个关键过程。该研究旨在筛选ACP中与铁突变相关的诊断标记物,以提高诊断的准确性:方法:从基因表达总库(GEO)数据库中获取 ACP 的基因表达谱。方法:从基因表达总库(GEO)数据库中获取 ACP 的基因表达谱,使用 Limma 软件包分析差异表达基因(DEGs)。将 DEGs 与铁蛋白沉积相关因子的交叉点作为不同表达的铁蛋白沉积相关基因(DEFRGs)。富集分析包括基因本体(GO)、京都基因和基因组百科全书(KEGG)、疾病本体(DO)、基因组富集分析(GSEA)和基因组变异分析(GSVA)。采用机器学习算法筛选了与 ACP 中铁细胞减少症相关的诊断标记物。对 ACP 患者的 DEFRGs 水平进行了验证。通过绘制提名图来预测关键 DEFRG 表达与疾病风险之间的关系。然后通过共识聚类分析对疾病组进行聚类:结果:筛查了 ACP 与正常样本之间的 DEGs。从 FerrDb V2 和 GeneCard 数据库中获得了铁蛋白沉积相关因子。DEFRGs 与铁突变标志物之间的相关性也得到了证实。共获得了 6 个重叠的 DEFRGs。根据提名图的结果,CASP8、KRT16、KRT19 和 TP63 是疾病风险的保护因素,而 GOT1 和 TFAP2C 则是风险因素。根据筛选出的 DEFRGs,共识聚类矩阵得到了分化,且聚类数量稳定。CASP8、KRT16、KRT19和TP63在ACP患者中上调,而GOT1下调。CASP8、KRT16、KRT19、TP63、CASP8和GOT1影响多个铁变态标记基因。这些基因的组合可能是通过参与铁突变过程诊断 ACP 的生物标志物:讨论:CASP8、KRT16、KRT19、TP63和GOT1等铁突变相关基因是ACP的潜在标记基因,这为ACP的诊断奠定了理论基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Frontiers in Endocrinology
Frontiers in Endocrinology Medicine-Endocrinology, Diabetes and Metabolism
CiteScore
5.70
自引率
9.60%
发文量
3023
审稿时长
14 weeks
期刊介绍: Frontiers in Endocrinology is a field journal of the "Frontiers in" journal series. In today’s world, endocrinology is becoming increasingly important as it underlies many of the challenges societies face - from obesity and diabetes to reproduction, population control and aging. Endocrinology covers a broad field from basic molecular and cellular communication through to clinical care and some of the most crucial public health issues. The journal, thus, welcomes outstanding contributions in any domain of endocrinology. Frontiers in Endocrinology publishes articles on the most outstanding discoveries across a wide research spectrum of Endocrinology. The mission of Frontiers in Endocrinology is to bring all relevant Endocrinology areas together on a single platform.
期刊最新文献
Glucagon-like peptide-1 receptor agonists and the risk of erectile dysfunction: a drug target Mendelian randomization study. Mitochondria: the epigenetic regulators of ovarian aging and longevity. Relationship between liver and cardiometabolic health in type 1 diabetes. Editorial: Insights in obesity: 2023. Editorial: Pulmonary fibrosis and endocrine factors.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1