糖胺聚糖（GAGs）是人体生理、病理变化过程中的关键功能分子，已成为重大疾病标志物研究的热点。研究表明GAGs表达水平及精细结构的变化与乳腺癌的发生发展密切相关，临床样本GAGs组研究有助于发现新型乳腺癌标志物。但是由于GAGs结构复杂，临床样本中痕量GAGs的定量分析及其细微结构表征一直是本领域国内外研究的瓶颈。本课题拟在前期研究基础上，采用定向酶解及荧光标记等手段，结合质谱多反应监测技术，建立并完善准确、高效、超灵敏定量分析临床样本中GAGs的研究体系。运用上述体系，大样本量分析不同分型乳腺癌患者、良性乳腺病患者及健康对照者的血清和组织样本，获得其中GAGs的精细结构信息，构建乳腺癌临床GAGs表达谱库。以此为基础，通过多元统计分析深入探讨血清、组织GAGs表达谱及临床特征间的相关性，以期发现基于GAGs的乳腺癌血清标志物。本研究结果将为乳腺癌的早期诊断和预后监测提供理论依据。

Glycosaminoglycans (GAGs) have emerged as an area of utmost interest for biomarkers discovery due to their biological significance in physiology and pathology. Notably, an evolving body of literature has linked the expression levels and structures of GAGs to the carcinogenesis and development of breast cancer, which necessitates the development of glycosaminoglycanomics from clinical samples as new potential biomarker for breast cancer. However, precise quantification and detailed structural characterization of trace GAGs in clinical samples are currently almost unavailable since GAGs are structurally complex. Therefore, in the current project, a rapid and sensitive method to quantify the GAGs in clinical samples will be developed and improved based on mass spectrum multiple reaction monitoring combined with the preparation processes of selective enzymatic hydrolysis and fluorescence labeling. Grounded on these analytical techniques, the serum and tissue samples in large scale from the patients with breast cancer, benign breast diseases and health volunteers will be further investigated to build the GAGs expression databases. The correlation between GAGs expression levels in serum and tissues and the clinical characteristics will be investigated in detail applying multivariate statistical analysis in order to discover GAGs related tumor serum biomarkers. By implementing this project, we hope to provide a theoretical basis for early diagnosis and prognosis monitoring of breast cancer.