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卵巢癌中卵巢、血浆、尿液和毛发之间复杂的代谢相互作用。

Complex metabolic interactions between ovary, plasma, urine, and hair in ovarian cancer.

作者信息

Zhong Xiaocui, Ran Rui, Gao Shanhu, Shi Manlin, Shi Xian, Long Fei, Zhou Yanqiu, Yang Yang, Tang Xianglan, Lin Anping, He Wuyang, Yu Tinghe, Han Ting-Li

机构信息

Department of Obstetrics and Gynaecology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.

State Key Laboratory of Ultrasound Engineering in Medicine Co-Founded by Chongqing and the Ministry of Science and Technology, School of Biomedical Engineering, Chongqing Medical University, Chongqing, China.

出版信息

Front Oncol. 2022 Aug 2;12:916375. doi: 10.3389/fonc.2022.916375. eCollection 2022.

Abstract

Ovarian cancer (OC) is the third most common malignant tumor of women accompanied by alteration of systemic metabolism, yet the underlying interactions between the local OC tissue and other system biofluids remain unclear. In this study, we recruited 17 OC patients, 16 benign ovarian tumor (BOT) patients, and 14 control patients to collect biological samples including ovary plasma, urine, and hair from the same patient. The metabolic features of samples were characterized using a global and targeted metabolic profiling strategy based on Gas chromatography-mass spectrometry (GC-MS). Principal component analysis (PCA) revealed that the metabolites display obvious differences in ovary tissue, plasma, and urine between OC and non-malignant groups but not in hair samples. The metabolic alterations in OC tissue included elevated glycolysis (lactic acid) and TCA cycle intermediates (malic acid, fumaric acid) were related to energy metabolism. Furthermore, the increased levels of glutathione and polyunsaturated fatty acids (linoleic acid) together with decreased levels of saturated fatty acid (palmitic acid) were observed, which might be associated with the anti-oxidative stress capability of cancer. Furthermore, how metabolite profile changes across differential biospecimens were compared in OC patients. Plasma and urine showed a lower concentration of amino acids (alanine, aspartic acid, glutamic acid, proline, leucine, and cysteine) than the malignant ovary. Plasma exhibited the highest concentrations of fatty acids (stearic acid, EPA, and arachidonic acid), while TCA cycle intermediates (succinic acid, citric acid, and malic acid) were most concentrated in the urine. In addition, five plasma metabolites and three urine metabolites showed the best specificity and sensitivity in differentiating the OC group from the control or BOT groups (AUC > 0.90) using machine learning modeling. Overall, this study provided further insight into different specimen metabolic characteristics between OC and non-malignant disease and identified the metabolic fluctuation across ovary and biofluids.

摘要

卵巢癌(OC)是女性第三大常见恶性肿瘤,伴有全身代谢改变,然而局部OC组织与其他系统生物流体之间的潜在相互作用仍不清楚。在本研究中,我们招募了17名OC患者、16名良性卵巢肿瘤(BOT)患者和14名对照患者,收集同一患者的生物样本,包括卵巢组织、血浆、尿液和毛发。使用基于气相色谱 - 质谱(GC - MS)的全局和靶向代谢谱分析策略对样本的代谢特征进行表征。主成分分析(PCA)显示,OC组和非恶性组之间的代谢物在卵巢组织、血浆和尿液中存在明显差异,但在毛发样本中没有。OC组织中的代谢改变包括糖酵解(乳酸)升高和三羧酸循环中间体(苹果酸、富马酸)升高,这与能量代谢有关。此外,还观察到谷胱甘肽和多不饱和脂肪酸(亚油酸)水平升高,同时饱和脂肪酸(棕榈酸)水平降低,这可能与癌症的抗氧化应激能力有关。此外,还比较了OC患者不同生物样本中代谢物谱的变化。血浆和尿液中的氨基酸(丙氨酸、天冬氨酸、谷氨酸、脯氨酸、亮氨酸和半胱氨酸)浓度低于恶性卵巢组织。血浆中脂肪酸(硬脂酸、二十碳五烯酸和花生四烯酸)浓度最高,而三羧酸循环中间体(琥珀酸、柠檬酸和苹果酸)在尿液中浓度最高。此外,使用机器学习模型,五种血浆代谢物和三种尿液代谢物在区分OC组与对照组或BOT组时表现出最佳的特异性和敏感性(AUC>0.90)。总体而言,本研究进一步深入了解了OC与非恶性疾病之间不同样本的代谢特征,并确定了卵巢组织和生物流体之间的代谢波动。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f0c/9379488/2a6a26d3edf4/fonc-12-916375-g001.jpg

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