Comprehensive metabolomic profiling of osteosarcoma based on UHPLC-HRMS.
Comprehensive metabolomic profiling of osteosarcoma based on UHPLC-HRMS.
复制标题
DOI:
10.1007/s11306-020-01745-4
复制
发表时间:
2020-11-18
期刊:
影响因子:
--
通讯作者:
Xie X
中科院分区:
文献类型:
--
作者:
Lv D;Zou Y;Zeng Z;Yao H;Ding S;Bian Y;Wen L;Xie X
Osteosarcoma (OS) is the most common primary malignant bone tumor in children and adolescents. An increasing number of studies have demonstrated that tumor proliferation and metastasis are closely related to complex metabolic reprogramming. However, there are limited data to provide a comprehensive metabolic picture of osteosarcoma. Our study aims to identify aberrant metabolic pathways and seek potential adjuvant biomarkers for osteosarcoma. Serum samples were collected from 65 osteosarcoma patients and 30 healthy controls. Nontargeted metabolomic profiling was performed by liquid chromatography-mass spectrometry (LC-MS) based on univariate and multivariate statistical analyses. The OPLS-DA model analysis identified clear separations among groups. We identified a set of differential metabolites such as higher serum levels of adenosine-5-monophosphate, inosine-5-monophosphate and guanosine monophosphate in primary OS patients compared to healthy controls, and higher serum levels of 5-aminopentanamide, 13(S)-HpOTrE (FA 18:3 + 2O) and methionine sulfoxide in lung metastatic OS patients compared to primary OS patients, revealing aberrant metabolic features during the proliferation and metastasis of osteosarcoma. We found a group of metabolites especially lactic acid and glutamic acid, with AUC values of 0.97 and 0.98, which could serve as potential adjuvant diagnostic biomarkers for primary osteosarcoma, and a panel of 2 metabolites, 5-aminopentanamide and 13(S)-HpOTrE (FA 18:3 + 2O), with an AUC value of 0.92, that had good monitoring ability for lung metastases. Our study provides new insight into the aberrant metabolic features of osteosarcoma. The potential biomarkers identified here may have translational significance. The online version of this article (doi:10.1007/s11306-020-01745-4) contains supplementary material, which is available to authorized users.
登录
查看更多内容
影响因子:
3.7
作者:
Liao S;Ruiz Y;Gulzar H;Yelskaya Z;Ait Taouit L;Houssou M;Jaikaran T;Schvarts Y;Kozlitina K;Basu-Roy U;Mansukhani A;Mahajan SS
通讯作者:
Mahajan SS
影响因子:
4.7
作者:
Seyfried TN;Flores RE;Poff AM;D'Agostino DP
通讯作者:
D'Agostino DP
影响因子:
64.5
作者:
Jang C;Chen L;Rabinowitz JD
通讯作者:
Rabinowitz JD
影响因子:
9.2
作者:
Willard SS;Koochekpour S
通讯作者:
Koochekpour S
影响因子:
29
作者:
Yoo, Hee Chan;Park, Seung Joon;Han, Jung Min
通讯作者:
Han, Jung Min