Nurul Azmir Amir Hashim, Sharaniza Ab-Rahim, Wan Zurinah Wan Ngah, Sheila Nathan, Nurul Syakima Ab Mutalib, Ismail Sagap, A Rahman A Jamal, Musalmah Mazlan
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The samples were deproteinized with acetonitrile and untargeted metabolomics profile determined using liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOFMS, Agilent USA). The data were analysed using Mass Profiler Professional (Agilent, USA) software. The panel of biomarkers determined were then used to identify CRC from a new set of 20 matched samples. <i><b>Results:</b></i> Eleven differential metabolites were identified whose levels were significantly different between CRC patients compared to normal controls. Based on the analysis of the area under the curve, 7 of these metabolites showed high sensitivity and specificity as biomarkers. The use of the 11 metabolites on a new set of samples was able to differentiate CRC from normal samples with 80% accuracy. These metabolites were hypoxanthine, acetylcarnitine, xanthine, uric acid, tyrosine, methionine, lysoPC, lysoPE, citric acid, 5-oxoproline, and pipercolic acid. 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引用次数: 15
摘要
血清代谢组学方法已被用于鉴定能够准确和特异性诊断结直肠癌(CRC)的代谢物生物标志物。然而,在不同的研究中发现的生物标志物不同,这表明需要进行更多的研究来了解遗传和环境因素的影响。因此,本研究旨在确定马来西亚结直肠癌患者的生物标志物和受影响的代谢途径。方法:采集50例健康对照和50例结直肠癌患者血清。样品用乙腈脱蛋白,用液相色谱-四极杆飞行时间质谱(LC-QTOFMS, Agilent USA)测定非靶向代谢组学特征。使用Mass Profiler Professional (Agilent, USA)软件分析数据。然后将确定的生物标志物面板用于从一组新的20个匹配样本中识别CRC。结果:鉴定出11种差异代谢物,其水平在结直肠癌患者与正常对照组之间存在显著差异。根据曲线下面积分析,其中7种代谢物作为生物标志物具有较高的敏感性和特异性。在一组新样本上使用11种代谢物能够以80%的准确率区分CRC和正常样本。这些代谢物是次黄嘌呤、乙酰肉碱、黄嘌呤、尿酸、酪氨酸、蛋氨酸、溶血opc、溶血ope、柠檬酸、5-氧脯氨酸和胡椒酸。数据还显示,CRC中最受干扰的途径是嘌呤、儿茶酚胺和氨基酸代谢。结论:血清代谢组学分析可用于识别CRC的特异性生物标志物,并进一步了解其病理生理机制。
Global metabolomics profiling of colorectal cancer in Malaysian patients.
Introduction: The serum metabolomics approach has been used to identify metabolite biomarkers that can diagnose colorectal cancer (CRC) accurately and specifically. However, the biomarkers identified differ between studies suggesting that more studies need to be performed to understand the influence of genetic and environmental factors. Therefore, this study aimed to identify biomarkers and affected metabolic pathways in Malaysian CRC patients. Methods: Serum from 50 healthy controls and 50 CRC patients were collected at UKM Medical Centre. The samples were deproteinized with acetonitrile and untargeted metabolomics profile determined using liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOFMS, Agilent USA). The data were analysed using Mass Profiler Professional (Agilent, USA) software. The panel of biomarkers determined were then used to identify CRC from a new set of 20 matched samples. Results: Eleven differential metabolites were identified whose levels were significantly different between CRC patients compared to normal controls. Based on the analysis of the area under the curve, 7 of these metabolites showed high sensitivity and specificity as biomarkers. The use of the 11 metabolites on a new set of samples was able to differentiate CRC from normal samples with 80% accuracy. These metabolites were hypoxanthine, acetylcarnitine, xanthine, uric acid, tyrosine, methionine, lysoPC, lysoPE, citric acid, 5-oxoproline, and pipercolic acid. The data also showed that the most perturbed pathways in CRC were purine, catecholamine, and amino acid metabolisms. Conclusion: Serum metabolomics profiling can be used to identify distinguishing biomarkers for CRC as well as to further our knowledge of its pathophysiological mechanisms.
BioimpactsPharmacology, Toxicology and Pharmaceutics-Pharmaceutical Science
CiteScore
4.80
自引率
7.70%
发文量
36
审稿时长
5 weeks
期刊介绍:
BioImpacts (BI) is a peer-reviewed multidisciplinary international journal, covering original research articles, reviews, commentaries, hypotheses, methodologies, and visions/reflections dealing with all aspects of biological and biomedical researches at molecular, cellular, functional and translational dimensions.