GC-MS based metabolite fingerprinting of serous ovarian carcinoma and benign ovarian tumor

IF 1.1 4区 化学 Q4 PHYSICS, ATOMIC, MOLECULAR & CHEMICAL European Journal of Mass Spectrometry Pub Date : 2022-04-01 DOI:10.1177/14690667221098520
E. Eroglu, U. Kucukgoz Gulec, M. Vardar, S. Paydaş
{"title":"GC-MS based metabolite fingerprinting of serous ovarian carcinoma and benign ovarian tumor","authors":"E. Eroglu, U. Kucukgoz Gulec, M. Vardar, S. Paydaş","doi":"10.1177/14690667221098520","DOIUrl":null,"url":null,"abstract":"The aim of this study is to identify urinary metabolomic profile of benign and malign ovarian tumors patients. Samples were analyzed using gas chromatography-mass spectrometry (GC-MS) and metabolomic tools to define biomarkers that cause differentiation between groups. 7 metabolites were found to be different in patients with ovarian cancer (OC) and benign tumors (BT). R2Y and Q2 values were found to be 0.670 and 0.459, respectively. L-tyrosine, glycine, stearic acid, turanose and L-threonine metabolites were defined as prominent biomarkers. The sensitivity of the model was calculated as 90.72% and the specificity as 82.09%. In the pathway analysis, glutathione metabolism, aminoacyl-tRNA biosynthesis, glycine serine and threonine metabolic pathway, primary bile acid biosynthesis pathways were found to be important. According to the t-test, 29 metabolites were found to be significant in urine samples of OC patients and healthy controls (HC). R2Y and Q2 values were found to be 0.8170 and 0.749, respectively. These results showed that the model has high compatibility and predictive power. Benzoic acid, L-threonine, L-pyroglutamic acid, creatinine and 3,4-dihydroxyphenylacetic acid metabolites were determined as prominent biomarkers. The sensitivity of the model was calculated as 93.81% and the specificity as 98.59%. Glycine serine and threonine metabolic pathway, glutathione metabolism and aminoacyl-tRNA biosynthesis pathways were determined important in OC patients and HC. The R2Y, Q2, sensitivity and specificity values in the urine samples of BT patients and HC were found to be 0.869, 0.794, 91.75, 97.01% and 97.18%, respectively. L-threonine, L-pyroglutamic acid, benzoic acid, creatinine and pentadecanol metabolites were determined as prominent biomarkers. Valine, leucine and isoleucine biosynthesis and aminoacyl-tRNA biosynthesis were significant. In this study, thanks to the untargeted metabolomic approach and chemometric methods, every group was differentiated from the others and prominent biomarkers were determined.","PeriodicalId":12007,"journal":{"name":"European Journal of Mass Spectrometry","volume":null,"pages":null},"PeriodicalIF":1.1000,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Mass Spectrometry","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1177/14690667221098520","RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"PHYSICS, ATOMIC, MOLECULAR & CHEMICAL","Score":null,"Total":0}
引用次数: 1

Abstract

The aim of this study is to identify urinary metabolomic profile of benign and malign ovarian tumors patients. Samples were analyzed using gas chromatography-mass spectrometry (GC-MS) and metabolomic tools to define biomarkers that cause differentiation between groups. 7 metabolites were found to be different in patients with ovarian cancer (OC) and benign tumors (BT). R2Y and Q2 values were found to be 0.670 and 0.459, respectively. L-tyrosine, glycine, stearic acid, turanose and L-threonine metabolites were defined as prominent biomarkers. The sensitivity of the model was calculated as 90.72% and the specificity as 82.09%. In the pathway analysis, glutathione metabolism, aminoacyl-tRNA biosynthesis, glycine serine and threonine metabolic pathway, primary bile acid biosynthesis pathways were found to be important. According to the t-test, 29 metabolites were found to be significant in urine samples of OC patients and healthy controls (HC). R2Y and Q2 values were found to be 0.8170 and 0.749, respectively. These results showed that the model has high compatibility and predictive power. Benzoic acid, L-threonine, L-pyroglutamic acid, creatinine and 3,4-dihydroxyphenylacetic acid metabolites were determined as prominent biomarkers. The sensitivity of the model was calculated as 93.81% and the specificity as 98.59%. Glycine serine and threonine metabolic pathway, glutathione metabolism and aminoacyl-tRNA biosynthesis pathways were determined important in OC patients and HC. The R2Y, Q2, sensitivity and specificity values in the urine samples of BT patients and HC were found to be 0.869, 0.794, 91.75, 97.01% and 97.18%, respectively. L-threonine, L-pyroglutamic acid, benzoic acid, creatinine and pentadecanol metabolites were determined as prominent biomarkers. Valine, leucine and isoleucine biosynthesis and aminoacyl-tRNA biosynthesis were significant. In this study, thanks to the untargeted metabolomic approach and chemometric methods, every group was differentiated from the others and prominent biomarkers were determined.
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
基于GC-MS的浆液性卵巢癌和卵巢良性肿瘤代谢物指纹图谱
本研究的目的是确定良性和恶性卵巢肿瘤患者的尿液代谢组学特征。使用气相色谱-质谱(GC-MS)和代谢组学工具对样品进行分析,以确定导致组间差异的生物标志物。发现卵巢癌症(OC)和良性肿瘤(BT)患者的7种代谢产物存在差异。R2Y和Q2的值分别为0.670和0.459。L-酪氨酸、甘氨酸、硬脂酸、turanase和L-苏氨酸代谢产物被定义为显著的生物标志物。该模型的敏感性为90.72%,特异性为82.09%。在途径分析中,谷胱甘肽代谢、氨酰基tRNA生物合成、甘氨酸-丝氨酸和苏氨酸代谢途径、初级胆汁酸生物合成途径是重要的。根据t检验,在OC患者和健康对照(HC)的尿液样本中发现29种代谢产物具有显著性。R2Y和Q2的值分别为0.8170和0.749。这些结果表明,该模型具有很高的兼容性和预测能力。苯甲酸、L-苏氨酸、L-焦谷氨酸、肌酸酐和3,4-二羟基苯乙酸代谢产物被确定为显著的生物标志物。该模型的敏感性为93.81%,特异性为98.59%。甘氨酸-丝氨酸和苏氨酸代谢途径、谷胱甘肽代谢和氨酰基-tRNA生物合成途径在OC患者和HC中具有重要意义。BT患者和HC的R2Y、Q2、敏感性和特异性分别为0.869、0.794、91.75、97.01%和97.18%。L-苏氨酸、L-焦谷氨酸、苯甲酸、肌酸酐和十五醇代谢产物被确定为显著的生物标志物。缬氨酸、亮氨酸和异亮氨酸的生物合成以及氨酰基tRNA的生物合成显著。在这项研究中,由于采用了非靶向代谢组学方法和化学计量方法,每个组都与其他组进行了区分,并确定了突出的生物标志物。
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
CiteScore
2.40
自引率
7.70%
发文量
16
审稿时长
>12 weeks
期刊介绍: JMS - European Journal of Mass Spectrometry, is a peer-reviewed journal, devoted to the publication of innovative research in mass spectrometry. Articles in the journal come from proteomics, metabolomics, petroleomics and other areas developing under the umbrella of the “omic revolution”.
期刊最新文献
Clustering of biphenyl oxamide ions by chiral recognition. Analysis of dimer and trimer complexes of the non-amyloidogenic rat islet amyloid polypeptide 21-37 by electrospray ionization-tandem mass spectrometry. Exploring the versatility of mass spectrometry: Applications across diverse scientific disciplines. Bioanalytical method development and validation of docetaxel and carvacrol in mice plasma using LC-QqQ-MS/MS. Ion crystal size and structure in Paul traps.
×
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