组合式离子化RRLC-MS/MS方法与~1H NMR技术的肺癌血浆代谢组学分析方法研究
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摘要
本论文重点采用快速高分辨液相色谱系统(RRLC)与MS/MS联用的高通量分析技术,通过考察电喷雾电离(ESI)、大气压化学电离(APCI)和大气压光致电禺(APPI)三种离子化方法获取健康人血浆中小分子代谢物信息的差异,建立了ESI与APPI相结合的组合式离子化RRLC-MS血浆代谢组学分析方法。同时利用RRLC-MS的快速、高灵敏、高选择性和高通量等特点,以及1H NMR技术检测无偏向性、结构鉴定能力强的优势,开展了RRLC-MS/MS与1H NMR技术整合的肺癌血浆代谢组学分析,力求获取更全面的差异代谢物信息,为肺癌的临床疗效评价及预后分析等提供潜在的小分子生物标志物。
本研究通过分析健康志愿者与肺癌患者治疗前血浆代谢组的差异,分别发现66个(由RRLC-MS方法)和12个(利用1H NMR技术)与肺癌诊断相关的可能生物标志物。进一步通过肺癌患者治疗前、治疗后血浆样品的代谢组差异分析,寻找对治疗敏感的可能标志物；同时对上述标志物在健康志愿者组、癌症患者不同疗效组中治疗前、治疗中期、治疗后的变化规律进行了考察与分析。目前,由RRLC-MS方法发现了33个肺癌治疗敏感的可能标志物,并寻找到与疗效评价密切相关的10个可能标志物；另由1H NMR方法发现了10个治疗敏感标志物,其中包括8个与疗效评价密切相关的可能标志物。本研究结果表明“组合式”离子化RRLC-MS方法可以较好地弥补单一离子化质谱技术检测的离子化歧视及离子化效率差异的缺点,可获得更全面的生物标志物信息；此外,结合1H NMR的优势,构成综合性分析技术体系,进一步完善了血浆代谢组学分析方法。
本论文的研究内容主要包括以下三部分：
1.适用于血浆代谢组学的组合式离子化RRLC-MS分析方法研究
采用正负离子电离模式的ESI、APCI和APPI-MS三种离子化RRLC-MS方法,选择健康人血浆,系统考察了不同离子化方法获取代谢物信息的能力,研究结果表明,“组合式”离子化的RRLC-MS/MS方法可获得更为全面的内源性代谢物信息。通过进一步分析三种方法对不同类型代谢物检测灵敏度的差异,发现ESI与APPI结合的组合式离子化方法,可以较好地满足血浆代谢组学研究中全面地获取代谢物信息及高通量分析的要求。
2.组合式离子化RRLC-MS方法在肺癌血浆代谢组学研究中的应用
采用电ESI与APPI二种离子化方式相结合的组合式RRLC-MS方法,结合多变量统计分析,开展了肺癌患者血浆代谢组学研究。通过健康人与肺癌患者治疗前血浆样本的代谢组分析,发现66个与肺癌诊断相关的可能生物标志物,并鉴定出其中27个标志物的结构。然后,通过分析肺癌患者治疗前与治疗后样本组的代谢组差异,筛选出33个对治疗敏感的可能标志物；进一步考察这些代谢物在健康组、治疗前、治疗中期、治疗后的变化规律,最终筛选并鉴定出10个与肿癌治疗及预后密切相关的可能生物标志物,分别是脂酰肉碱carnitine10:0、溶血磷脂酰胆碱sn-1lysoPC (16:1)、sn-2lysoPC (18:2)、sn-1lysoPC(16:0)、谷氨酰胺(glutamine)、硫酸脱氢表雄酮(DHEAs)、硫酸雄甾酮(androsterone sulfate)、油酸(oleic acid)亚油酸(linoleic acid)、葡萄糖(glucose)。本研究结果表明,组合式离子化方法能较好地克服单一离子化质谱技术面临的离子化歧视和离子化效率差异的缺点,在获取不同极性代谢物信息方面不仅存在互补性,而且还可以互相验证共同检测到的生物标志物的可靠性。
3.基于1H NMR技术的肺癌血浆代谢组学研究
在上述研究基础上,采用1H NMR技术,结合多变量统计分析,进一步开展了肺癌血浆代谢组学研究。通过分析健康人与肺癌患者治疗前血浆代谢组的差异,寻找到12个可能的诊断标志物。然后,分析肺癌患者治疗前与治疗后的血浆样本,发现了10个对治疗敏感的代谢物,进一步考察这些代谢物在健康组、治疗前、治疗中期、治疗后的变化规律,筛选出8个与肺癌疗效评价相关的可能生物标志物,分别是柠檬酸(Citrate)、醋酸(Acetate)、葡萄糖(Glucose)、谷氨酰胺(Glutamine)、丙酮酸(Pyruvate)、磷脂胆碱类(Phospholipids choline)、缬氨酸(Valine)、胞嘧啶核苷(Cytidine)
本研究采用RRLC-MS与1H NMR两种不同分析技术开展肺癌血浆代谢组学的研究,共同发现葡萄糖、谷氨酰胺及磷脂胆碱类等3种内源性代谢物与疗效评价密切相关,这进一步验证了上述3种小分子标志物的可靠性；此外,这两种分析技术还分别发现了各自特有的疗效评价标志物。这些结果表明,将LC-MS与NMR两种分析技术联合应用于代谢组学研究中,不仅可以相互验证所发现的生物标志物,同时通过发挥各自技术上的优势,有利于获取更加全面、可靠的可能生物标志物,有望为肺癌的临床疗效评价及预后分析等提供潜在的小分子标志物及其重要依据。
This study mainly addresses the application of rapid resolution liquid chromatography mass spectrometry/tandem mass spectrometry (RRLC-MS/MS) combined with electrospray ionization (ESI), atmospheric pressure chemical ionization (APCI), and atmospheric pressure photoionization (APPI) for investigating the differences of these three ionization methods in acquiring small molecular metabolome of plasma, and integrated RRLC-MS/MS combined with ESI and APCI for plasma metabolomics has been established. Meanwhile, the combination of adavantage of RRLC-MS/MS in fast speed, high sensitivity, high selectivity, high-throughput with the non-deviation detecting and robust identification of NMR has been employed for the identification of lung cancer plasma metabolomics in order to provide biomarkers of small molecule for clinically evaluating therapeutic effects and prognosis analysis of lung cancer.
Through analyzing metabolome differences between healthy and lung cancer plasma,66(detected by LC-MS) and12(detected by1H NMR) potential biomarkers closely related diagnosing lung cancer has been obtained, respectively. In the mean time,33metabolites responded to therapy has been acquired by analyzing the differences among lung cancer plasma samples over the periods of pre and post treatments, and these responded metabolites has further been sifted into potential biomarkers related to evaluating therapeutic effects by observing the dynamic change trends throught the pre, middle, and post treatment periods combined with clinical evaluation of therapeutic effects, and consequently10potential biomarkers related to therapeutic effects'evalution has been achieved. In addition,1H NMR discovered10biomarkers responded to treatments, and8of them are closely related to therapeutic effects. This study proved the integrated ionization methods could better make up the disadvantages of ionization discrimination and efficiency differences encountered by MS with only a single ionization source. Also, the integrated ionization methods combined with1H NMR furtherly consummated the analytical methods for plasma metabolomics.
1. Study on the RRLC-MS methods suited for plasma metabolomics
RRLC-MS in combination with ESI, APCI and APPI in both positive and negative ion modes has been conducted to detedc healthy plasma for investigating the ability of different ionization methods in gaining plasma metaboleme, and the results has proved that integrated ionization RRLC-MS/MS is able to get more global metaboleme information. Further analysis on the applicability of three ionization methods for detecting different types of plasma metabolites indicates that the integration of ESI and APPI without APCI could better satisfy the requirement of metabolomics for obtaining comprehensive metabolites'information and high-throughput detection.
2. The application of integrated ionization RRLC-MS/MS in lung cancer plasma metabolomics
The integrated ESI and APPI with RRLC-MS/MS in combination of multivariate statistical analysis have been implemented in lung cancer plasma metabolomics. Through comparing the differences of plasma motabolime between healthy and cancer patients,66potential biomarkers related to diagnosing lung cancer has been produced, and27metabolited has been identified. Furtherly, differences of plasma metabolome between pre and post treatments of lung cancer patients has been assessed, and33metabolites responded to therapy has been obtained, and danyic change trends of these33metabolites has been analyzed among healthy, pre, middle, and post treatment plasma samples, and10potential biomarkers closely related to lung cancer genesis, development, treatment, and prognosis has been achieved, including carnitine10:0, sn-1lysoPC (16:1), sn-2lysoPC (18:2), sn-1lysoPC(16:0), glutamine, DHEAs, androsterone sulfate, oleic acid, linoleic acid, and glucose. The study results proved that integrated ionization methods could, to some degree, conquer the disadvantage of ionization discrimination and efficiency differences encountered by MS with only a single ionization source. The integrated ionization methods not only provide complementarity for each other in detecting metabolites with different polarity, but also validate the realiability of potential biomarkers discovered by the other side. The study results are very promising to convey the extremely important bases for clinically therapeutic effects evaluation and prognosis.
3.1H NMR-based lung cancer plasma metabolomics
The1H NMR with multivariate statistical analysis has been introduced into lung cancer plasma metabolomics. Through comparing the differences of plasma metabolome between healthy and cancer plasma samples,12potential biomarkers related to diagnosing lung cancer has been achieved, and identified. Furtherly, differences of plasma metabolome between pre and post treatments of lung cancer patients has been evaluated, and10metabolites responded to therapy has been obtained, and danyic change trends of these10metabolites has been analyzed among healthy, pre, middle, and post treatment plasma samples, and8potential biomarkers closely related to lung cancer genesis, development, treatment, and prognosis has been achieved, including citrate, acetate, glucose, glutamine, puruvate, phospholipids choline, valine, cytidine, among which glucose, glutamine, and phospholipids choline linked to therapeutic effects evaluation were simultaneously discovered by1H NMR and LC-MS that validated the detection realiability. At the same time,1H NMR and LC-MS methods offered5and4unique potential biomarkers related to therapy evaluation, respectively, which suggested the combination of two spectrometry technologies could not only validate detection of each others, but also broaden the discovered ranges of potential biomarkers. The above potential biomarkers discovered by integrated LC-MS/MS and1H NMR metabolomics are likely to provide valuable bases for clinically diagnosing, assessing therapy, and prognosis analysis.
本研究通过分析健康志愿者与肺癌患者治疗前血浆代谢组的差异,分别发现66个(由RRLC-MS方法)和12个(利用1H NMR技术)与肺癌诊断相关的可能生物标志物。进一步通过肺癌患者治疗前、治疗后血浆样品的代谢组差异分析,寻找对治疗敏感的可能标志物；同时对上述标志物在健康志愿者组、癌症患者不同疗效组中治疗前、治疗中期、治疗后的变化规律进行了考察与分析。目前,由RRLC-MS方法发现了33个肺癌治疗敏感的可能标志物,并寻找到与疗效评价密切相关的10个可能标志物；另由1H NMR方法发现了10个治疗敏感标志物,其中包括8个与疗效评价密切相关的可能标志物。本研究结果表明“组合式”离子化RRLC-MS方法可以较好地弥补单一离子化质谱技术检测的离子化歧视及离子化效率差异的缺点,可获得更全面的生物标志物信息；此外,结合1H NMR的优势,构成综合性分析技术体系,进一步完善了血浆代谢组学分析方法。
本论文的研究内容主要包括以下三部分：
1.适用于血浆代谢组学的组合式离子化RRLC-MS分析方法研究
采用正负离子电离模式的ESI、APCI和APPI-MS三种离子化RRLC-MS方法,选择健康人血浆,系统考察了不同离子化方法获取代谢物信息的能力,研究结果表明,“组合式”离子化的RRLC-MS/MS方法可获得更为全面的内源性代谢物信息。通过进一步分析三种方法对不同类型代谢物检测灵敏度的差异,发现ESI与APPI结合的组合式离子化方法,可以较好地满足血浆代谢组学研究中全面地获取代谢物信息及高通量分析的要求。
2.组合式离子化RRLC-MS方法在肺癌血浆代谢组学研究中的应用
采用电ESI与APPI二种离子化方式相结合的组合式RRLC-MS方法,结合多变量统计分析,开展了肺癌患者血浆代谢组学研究。通过健康人与肺癌患者治疗前血浆样本的代谢组分析,发现66个与肺癌诊断相关的可能生物标志物,并鉴定出其中27个标志物的结构。然后,通过分析肺癌患者治疗前与治疗后样本组的代谢组差异,筛选出33个对治疗敏感的可能标志物；进一步考察这些代谢物在健康组、治疗前、治疗中期、治疗后的变化规律,最终筛选并鉴定出10个与肿癌治疗及预后密切相关的可能生物标志物,分别是脂酰肉碱carnitine10:0、溶血磷脂酰胆碱sn-1lysoPC (16:1)、sn-2lysoPC (18:2)、sn-1lysoPC(16:0)、谷氨酰胺(glutamine)、硫酸脱氢表雄酮(DHEAs)、硫酸雄甾酮(androsterone sulfate)、油酸(oleic acid)亚油酸(linoleic acid)、葡萄糖(glucose)。本研究结果表明,组合式离子化方法能较好地克服单一离子化质谱技术面临的离子化歧视和离子化效率差异的缺点,在获取不同极性代谢物信息方面不仅存在互补性,而且还可以互相验证共同检测到的生物标志物的可靠性。
3.基于1H NMR技术的肺癌血浆代谢组学研究
在上述研究基础上,采用1H NMR技术,结合多变量统计分析,进一步开展了肺癌血浆代谢组学研究。通过分析健康人与肺癌患者治疗前血浆代谢组的差异,寻找到12个可能的诊断标志物。然后,分析肺癌患者治疗前与治疗后的血浆样本,发现了10个对治疗敏感的代谢物,进一步考察这些代谢物在健康组、治疗前、治疗中期、治疗后的变化规律,筛选出8个与肺癌疗效评价相关的可能生物标志物,分别是柠檬酸(Citrate)、醋酸(Acetate)、葡萄糖(Glucose)、谷氨酰胺(Glutamine)、丙酮酸(Pyruvate)、磷脂胆碱类(Phospholipids choline)、缬氨酸(Valine)、胞嘧啶核苷(Cytidine)
本研究采用RRLC-MS与1H NMR两种不同分析技术开展肺癌血浆代谢组学的研究,共同发现葡萄糖、谷氨酰胺及磷脂胆碱类等3种内源性代谢物与疗效评价密切相关,这进一步验证了上述3种小分子标志物的可靠性；此外,这两种分析技术还分别发现了各自特有的疗效评价标志物。这些结果表明,将LC-MS与NMR两种分析技术联合应用于代谢组学研究中,不仅可以相互验证所发现的生物标志物,同时通过发挥各自技术上的优势,有利于获取更加全面、可靠的可能生物标志物,有望为肺癌的临床疗效评价及预后分析等提供潜在的小分子标志物及其重要依据。
This study mainly addresses the application of rapid resolution liquid chromatography mass spectrometry/tandem mass spectrometry (RRLC-MS/MS) combined with electrospray ionization (ESI), atmospheric pressure chemical ionization (APCI), and atmospheric pressure photoionization (APPI) for investigating the differences of these three ionization methods in acquiring small molecular metabolome of plasma, and integrated RRLC-MS/MS combined with ESI and APCI for plasma metabolomics has been established. Meanwhile, the combination of adavantage of RRLC-MS/MS in fast speed, high sensitivity, high selectivity, high-throughput with the non-deviation detecting and robust identification of NMR has been employed for the identification of lung cancer plasma metabolomics in order to provide biomarkers of small molecule for clinically evaluating therapeutic effects and prognosis analysis of lung cancer.
Through analyzing metabolome differences between healthy and lung cancer plasma,66(detected by LC-MS) and12(detected by1H NMR) potential biomarkers closely related diagnosing lung cancer has been obtained, respectively. In the mean time,33metabolites responded to therapy has been acquired by analyzing the differences among lung cancer plasma samples over the periods of pre and post treatments, and these responded metabolites has further been sifted into potential biomarkers related to evaluating therapeutic effects by observing the dynamic change trends throught the pre, middle, and post treatment periods combined with clinical evaluation of therapeutic effects, and consequently10potential biomarkers related to therapeutic effects'evalution has been achieved. In addition,1H NMR discovered10biomarkers responded to treatments, and8of them are closely related to therapeutic effects. This study proved the integrated ionization methods could better make up the disadvantages of ionization discrimination and efficiency differences encountered by MS with only a single ionization source. Also, the integrated ionization methods combined with1H NMR furtherly consummated the analytical methods for plasma metabolomics.
1. Study on the RRLC-MS methods suited for plasma metabolomics
RRLC-MS in combination with ESI, APCI and APPI in both positive and negative ion modes has been conducted to detedc healthy plasma for investigating the ability of different ionization methods in gaining plasma metaboleme, and the results has proved that integrated ionization RRLC-MS/MS is able to get more global metaboleme information. Further analysis on the applicability of three ionization methods for detecting different types of plasma metabolites indicates that the integration of ESI and APPI without APCI could better satisfy the requirement of metabolomics for obtaining comprehensive metabolites'information and high-throughput detection.
2. The application of integrated ionization RRLC-MS/MS in lung cancer plasma metabolomics
The integrated ESI and APPI with RRLC-MS/MS in combination of multivariate statistical analysis have been implemented in lung cancer plasma metabolomics. Through comparing the differences of plasma motabolime between healthy and cancer patients,66potential biomarkers related to diagnosing lung cancer has been produced, and27metabolited has been identified. Furtherly, differences of plasma metabolome between pre and post treatments of lung cancer patients has been assessed, and33metabolites responded to therapy has been obtained, and danyic change trends of these33metabolites has been analyzed among healthy, pre, middle, and post treatment plasma samples, and10potential biomarkers closely related to lung cancer genesis, development, treatment, and prognosis has been achieved, including carnitine10:0, sn-1lysoPC (16:1), sn-2lysoPC (18:2), sn-1lysoPC(16:0), glutamine, DHEAs, androsterone sulfate, oleic acid, linoleic acid, and glucose. The study results proved that integrated ionization methods could, to some degree, conquer the disadvantage of ionization discrimination and efficiency differences encountered by MS with only a single ionization source. The integrated ionization methods not only provide complementarity for each other in detecting metabolites with different polarity, but also validate the realiability of potential biomarkers discovered by the other side. The study results are very promising to convey the extremely important bases for clinically therapeutic effects evaluation and prognosis.
3.1H NMR-based lung cancer plasma metabolomics
The1H NMR with multivariate statistical analysis has been introduced into lung cancer plasma metabolomics. Through comparing the differences of plasma metabolome between healthy and cancer plasma samples,12potential biomarkers related to diagnosing lung cancer has been achieved, and identified. Furtherly, differences of plasma metabolome between pre and post treatments of lung cancer patients has been evaluated, and10metabolites responded to therapy has been obtained, and danyic change trends of these10metabolites has been analyzed among healthy, pre, middle, and post treatment plasma samples, and8potential biomarkers closely related to lung cancer genesis, development, treatment, and prognosis has been achieved, including citrate, acetate, glucose, glutamine, puruvate, phospholipids choline, valine, cytidine, among which glucose, glutamine, and phospholipids choline linked to therapeutic effects evaluation were simultaneously discovered by1H NMR and LC-MS that validated the detection realiability. At the same time,1H NMR and LC-MS methods offered5and4unique potential biomarkers related to therapy evaluation, respectively, which suggested the combination of two spectrometry technologies could not only validate detection of each others, but also broaden the discovered ranges of potential biomarkers. The above potential biomarkers discovered by integrated LC-MS/MS and1H NMR metabolomics are likely to provide valuable bases for clinically diagnosing, assessing therapy, and prognosis analysis.
引文
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