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基于超高效液相色谱-高分辨质谱的血清非靶向脂质组学用于发现结直肠高级别腺瘤的潜在生物标志物

Serum Untargeted UHPLC-HRMS-Based Lipidomics to Discover the Potential Biomarker of Colorectal Advanced Adenoma.

作者信息

Zhu Yifan, Wang Lisheng, Nong Yanying, Liang Yunxiao, Huang Zongsheng, Zhu Pingchuan, Zhang Qisong

机构信息

Medical College of Guangxi University, Guangxi University, Nanning, Guangxi, 530004, People's Republic of China.

Department of Gastroenterology, Ruikang Hospital Affiliated to Guangxi University of Chinese Medicine, Nanning, Guangxi, 530011, People's Republic of China.

出版信息

Cancer Manag Res. 2021 Nov 26;13:8865-8878. doi: 10.2147/CMAR.S336322. eCollection 2021.

Abstract

BACKGROUND

As a key precancerous lesion, colorectal advanced adenoma (CAA) is closely related to the occurrence and development of colorectal cancer (CRC). Effective identification of CAA-related biomarkers can prevent CRC morbidity and mortality. Lipids, as an important endogenous substance, have been proved to be involved in the occurrence and development of CRC. Lipidomics is an advanced technique that studies lipid metabolism and biomarkers of diseases. However, there are no lipidomics studies based on large serum samples to explore diagnostic biomarkers for CAA.

METHODS

An integrated serum lipid profile from 50 normal (NR) and 46 CAA subjects was performed using ultra-high performance liquid chromatography tandem high-resolution mass spectrometry (UHPLC-HRMS). Lipidomic data were acquired for negative and positive ionization modes, respectively. Differential lipids were selected by univariate and multivariate statistics analyses. A receiver operator characteristic curve (ROC) analysis was conducted to evaluate the diagnostic performance of differential lipids.

RESULTS

A total of 53 differential lipids were obtained by combining univariate and multivariate statistical analyses ( < 0.05 and VIP > 1). In addition, 12 differential lipids showed good diagnostic performance (AUC > 0.90) for the discrimination of NR and CAA by receiver operating characteristic curve (ROC) analysis. Of them, the performance of PC 44:5 and PC 35:6e presented the outstanding performance (AUC = 1.00, (95% CI, 1.00-1.00)). Moreover, triglyceride (TAG) had the highest proportion (37.74%) as the major dysregulated lipids in the CAA.

CONCLUSION

This is the first study that profiled serum lipidomics and explored lipid biomarkers with good diagnostic ability of CAA to contribute to the early prevention of CRC. Twelve differential lipids that effectively discriminate between NR and CAA serve as the potential diagnostic markers of CAA. An obvious perturbation of TAG metabolism could be involved in the CAA formation.

摘要

背景

作为一种关键的癌前病变,结直肠高级别腺瘤(CAA)与结直肠癌(CRC)的发生发展密切相关。有效识别与CAA相关的生物标志物可预防CRC的发病和死亡。脂质作为一种重要的内源性物质,已被证明参与CRC的发生发展。脂质组学是一项研究脂质代谢和疾病生物标志物的先进技术。然而,尚无基于大样本血清的脂质组学研究来探索CAA的诊断生物标志物。

方法

使用超高效液相色谱串联高分辨率质谱(UHPLC-HRMS)对50名正常(NR)受试者和46名CAA受试者的血清脂质谱进行综合分析。分别在负离子和正离子模式下获取脂质组学数据。通过单变量和多变量统计分析选择差异脂质。进行受试者工作特征曲线(ROC)分析以评估差异脂质的诊断性能。

结果

通过单变量和多变量统计分析相结合,共获得53种差异脂质(<0.05且VIP>1)。此外,通过受试者工作特征曲线(ROC)分析,12种差异脂质对NR和CAA的鉴别显示出良好的诊断性能(AUC>0.90)。其中,PC 44:5和PC 35:6e的性能表现突出(AUC = 1.00,(95%CI,1.00 - 1.00))。此外,甘油三酯(TAG)作为CAA中主要失调的脂质,所占比例最高(37.74%)。

结论

这是第一项对血清脂质组进行分析并探索具有良好CAA诊断能力的脂质生物标志物以促进CRC早期预防的研究。有效区分NR和CAA的12种差异脂质可作为CAA的潜在诊断标志物。TAG代谢的明显紊乱可能参与了CAA的形成。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cefc/8632617/c8edd7113c87/CMAR-13-8865-g0001.jpg

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