Quantitative analysis of LC-MS data for peptide and glycan biomarker discovery

描述(由申请人提供)：项目摘要：使用液相色谱-质谱仪(LC-MS)对分析物进行无标记定量正在被公认为是发现生物标记物的一种非常好的策略。然而，这种量化在特定于仪器的软件包中没有得到充分的处理。特别是，LC-MS数据的比对在生物分子的无标记定量和比较中提出了一个重大的挑战。这一挑战加上人类群体中的生物变异性和疾病异质性，限制了基于LC-MS的生物标记物发现研究的最新进展。该项目汇集了生物信息学、生物统计学、生物化学、临床癌症研究、层析和质谱学方面的专家，开发了基于LC-MS的新的分析工具，用于血清和血浆中多糖和多肽的无标记定量和比较。具体地说，一种新的基于概率的混合回归模型和一种新的基于聚类的方法将被研究用于LC-MS数据的比对和患者亚群的识别。来自尖峰研究的LC-MS数据将被用来开发和优化建议的比对方法，并将它们的性能与其他现有解决方案进行比较。优化的算法和统计方法将被应用于识别多肽和多糖候选生物标志物，用于肝细胞癌的早期检测。这将通过使用两种LC-MS技术来评估从肝细胞癌患者和肝硬变对照组收集的血清和血浆样本中多肽和多糖的表达。候选生物标志物将使用同位素稀释质谱分析进行验证。我们提出的基于同一参与者的血清和血浆样本同时进行多肽和葡聚糖图谱研究的建议，是探索发现标志物的综合方法的独特机会。此外，该项目将利用本研究和其他先前研究中确定的标志物来研究可能与肝细胞癌进展相关的关键代谢和信号通路。这将增强我们对疾病进展的理解，以及代谢和信号通路中标志物的功能参与，可用于设计和测试改进的治疗策略。 公共卫生相关性：项目简介该项目将导致开发新的开源分析工具，利用液质联用(LC-MS)技术对血清和血浆中的多肽和多糖进行无标记量化。这些工具的可用将有助于研究界推进基于LC-MS的生物标志物发现研究的前景。建议的工具将被用于寻找和验证肝细胞癌(HCC)的早期诊断生物标记物。在肝硬变患者的高危人群中定义临床适用的生物标志物来检测早期肝细胞癌对疾病管理和患者健康具有潜在的深远影响。这个项目很重要，因为大多数肝细胞癌患者是在晚期确诊的，治疗选择有限。迫切需要确定可用于肝细胞癌早期检测的生物标志物。除了筛选高危人群的早期疾病迹象外，由此产生的生物标记物还可以用于设计和测试改进的治疗策略。

DESCRIPTION (provided by applicant): PROJECT SUMMARY Label-free quantification of analytes using liquid chromatography-mass spectrometry (LC-MS) is gaining recognition as a very good strategy for biomarker discovery. However, such quantification is not addressed adequately in the instrument-specific software packages. In particular, alignment of LC-MS data presents a significant challenge in label-free quantification and comparison of biomolecules. This challenge coupled with biological variability and disease heterogeneity in human populations has restricted recent advances in LC- MS-based biomarker discovery studies. This project brings together experts in bioinformatics, biostatistics, biochemistry, clinical cancer research, chromatography, and mass spectrometry to develop novel analytical tools for LC-MS-based label-free quantification and comparison of glycans and peptides in serum and plasma. Specifically, a novel probabilistic-based mixture regression model and a new clustering-based method will be investigated for alignment of LC-MS data and for identification of patient subgroups. LC-MS data from spike-in studies will be utilized to develop and optimize the proposed alignment methods and to compare their performance with other existing solutions. The optimized algorithms and statistical methods will be applied to identify peptide and glycan candidate biomarkers for early detection of HCC. This will be accomplished by using two LC-MS technologies to evaluate the expression of peptides and glycans in serum and plasma samples collected from HCC patients and cirrhotic controls. The candidate biomarkers will be validated using isotope dilution mass spectrometric assays. Our proposal to perform both peptide and glycan profiling studies based on serum and plasma samples from the same participants is a unique opportunity to explore an integromic approach for marker discovery. Furthermore, this project will capitalize on markers identified in this study and other previous studies to investigate key metabolic and signaling pathways that may be related to the progression of HCC. This will enhance our understanding of the disease progression and the functional involvement of the markers in metabolic and signaling pathways, which could be used to design and test improved treatment strategies. PUBLIC HEALTH RELEVANCE: PROJECT NARRATIVE This project will lead to the development of novel open source analytical tools for label-free quantification of peptides and glycans in serum and plasma using liquid chromatography-mass spectrometry (LC-MS) technologies. The availability of such tools will assist the research community in advancing the promising LC- MS-based biomarker discovery research. The proposed tools will be utilized to find and validate early- diagnosis biomarkers of hepatocellular carcinoma (HCC). Defining clinically applicable biomarkers that detect early-stage HCC in a high-risk population of cirrhotic patients has potentially far-reaching consequences for disease management and patient health. This project is important because most HCC patients are diagnosed at a late stage, where the treatment options are limited. There is a pressing need to identify biomarkers that could be used for early detection of HCC. In addition to screening high-risk populations for early signs of disease, the resulting biomarkers could be used to design and test improved treatment strategies.