Centro de Química da Madeira, Centro de Ciências Exactas e da Engenharia, Universidade da Madeira, Campus Universitário da Penteada, Funchal, Portugal.
Br J Cancer. 2011 Dec 6;105(12):1894-904. doi: 10.1038/bjc.2011.437. Epub 2011 Nov 15.
Non-invasive diagnostic strategies aimed at identifying biomarkers of cancer are of great interest for early cancer detection. Urine is potentially a rich source of volatile organic metabolites (VOMs) that can be used as potential cancer biomarkers. Our aim was to develop a generally reliable, rapid, sensitive, and robust analytical method for screening large numbers of urine samples, resulting in a broad spectrum of native VOMs, as a tool to evaluate the potential of these metabolites in the early diagnosis of cancer.
To investigate urinary volatile metabolites as potential cancer biomarkers, urine samples from 33 cancer patients (oncological group: 14 leukaemia, 12 colorectal and 7 lymphoma) and 21 healthy (control group, cancer-free) individuals were qualitatively and quantitatively analysed. Dynamic solid-phase microextraction in headspace mode (dHS-SPME) using a carboxen-polydimethylsiloxane (CAR/PDMS) sorbent in combination with GC-qMS-based metabolomics was applied to isolate and identify the volatile metabolites. This method provides a potential non-invasive method for early cancer diagnosis as a first approach. To fulfil this objective, three important dHS-SPME experimental parameters that influence extraction efficiency (fibre coating, extraction time and temperature of sampling) were optimised using a univariate optimisation design. The highest extraction efficiency was obtained when sampling was performed at 50°C for 60 min using samples with high ionic strengths (17% sodium chloride, w v(-1)) and under agitation.
A total of 82 volatile metabolites belonging to distinct chemical classes were identified in the control and oncological groups. Benzene derivatives, terpenoids and phenols were the most common classes for the oncological group, whereas ketones and sulphur compounds were the main classes that were isolated from the urine headspace of healthy subjects. The results demonstrate that compound concentrations were dramatically different between cancer patients and healthy volunteers. The positive rates of 16 patients among the 82 identified were found to be statistically different (P<0.05). A significant increase in the peak area of 2-methyl-3-phenyl-2-propenal, p-cymene, anisole, 4-methyl-phenol and 1,2-dihydro-1,1,6-trimethyl-naphthalene in cancer patients was observed. On average, statistically significant lower abundances of dimethyl disulphide were found in cancer patients.
Gas chromatographic peak areas were submitted to multivariate analysis (principal component analysis and supervised linear discriminant analysis) to visualise clusters within cases and to detect the volatile metabolites that are able to differentiate cancer patients from healthy individuals. Very good discrimination within cancer groups and between cancer and control groups was achieved.
旨在识别癌症生物标志物的非侵入性诊断策略对于早期癌症检测具有重要意义。尿液是挥发性有机代谢物（VOM）的潜在丰富来源，可以用作潜在的癌症生物标志物。我们的目的是开发一种普遍可靠、快速、灵敏和强大的分析方法，用于筛选大量尿液样本，从而产生广泛的天然 VOM 谱，作为评估这些代谢物在癌症早期诊断中的潜力的工具。
为了研究尿液挥发性代谢物作为潜在的癌症生物标志物，对 33 名癌症患者（肿瘤组：14 名白血病、12 名结直肠癌和 7 名淋巴瘤）和 21 名健康（无癌症）个体的尿液样本进行定性和定量分析。采用动态固相微萃取在顶空模式（dHS-SPME）中，使用羧基-聚二甲基硅氧烷（CAR/PDMS）吸附剂与基于 GC-qMS 的代谢组学相结合，用于分离和鉴定挥发性代谢物。该方法为早期癌症诊断提供了一种潜在的非侵入性方法，作为第一步。为了实现这一目标，使用单变量优化设计优化了三个影响提取效率的重要 dHS-SPME 实验参数（纤维涂层、萃取时间和采样温度）。当以 50°C 进行采样 60 分钟、使用具有高离子强度（17%氯化钠，w/v(-1))并搅拌的样品时，获得了最高的提取效率。
在对照组和肿瘤组中鉴定出 82 种属于不同化学类别的挥发性代谢物。苯衍生物、萜类化合物和酚类化合物是肿瘤组中最常见的化合物，而酮类化合物和硫化合物是从健康受试者尿液顶空分离出来的主要化合物。结果表明，癌症患者和健康志愿者之间的化合物浓度差异很大。在 82 种鉴定出的化合物中，16 名患者的阳性率差异有统计学意义（P<0.05）。在癌症患者中观察到 2-甲基-3-苯基-2-丙烯醛、对伞花烃、苯甲醚、4-甲基苯酚和 1,2-二氢-1,1,6-三甲基萘的峰面积显著增加。平均而言，在癌症患者中发现二甲基二硫的丰度明显降低。
气相色谱峰面积经过多元分析（主成分分析和有监督线性判别分析）处理，以观察病例内的聚类并检测能够区分癌症患者和健康个体的挥发性代谢物。在癌症组内和癌症与对照组之间实现了非常好的区分。
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