開發定量質譜分析技術應用於血清蛋白質標誌分子轉譯後修飾之分析

蛋白質在細胞內負責執行各種生物功能、代謝和調節生化反應。然而，即時的反應動力學、蛋白質功能和結構的調控卻是由特定的轉譯後修飾所決定。越來越多的實驗證據顯示，蛋白質轉譯後修飾的改變與疾病或癌症具有高度關聯性，並可能是潛在的癌症生物標記分子。由於質譜儀器的長足進步和實驗策略的改善，近期以新穎質譜分析發法為基礎的技術進展，促進了蛋白質轉譯後修飾與疾病進程，例如癌症，之間相關性的研究。本篇論文的主要目標為發展各種結合質譜技術和樣本製備方法的分析平台，作為分析疾病相關蛋白質的特定轉譯後修飾變化與癌症之間的關聯性。在第二章，我們設計了一個分析平台結合奈米探針親和質譜法與生物統計分類法，評估血清澱粉蛋白A (serum amyloid A, SAA) 的蛋白質變體所組成的表達條形碼作為胃癌偵測的可行性。此研究策略揭示了癌症血清中血清澱粉蛋白A變體的高複雜度，也證明由蛋白質變體所組成的條形碼可作為癌症相關性的生物標記。在第三章中，我們建立了一個多重反應監測定量法，針對alpha1-酸性醣蛋白(alpha 1-acid glycoprotein, AGP)上特定醣基化位點的醣型結構在正常人與肝癌病患族群中的變化進行分析。實驗結果顯示，五個醣基化位點上各有不同的醣基化型式，而且特定的醣基化位點上有末端與核心岩藻醣基修飾增加的情況。在第四章中，我們應用18O穩定同位素標記技術對肝臟疾病患者的-胎兒蛋白(alpha-fetoprotein, AFP)的醣基化比例進行評估。藉由此策略，我們預期能夠藉由評估不同alpha-胎兒蛋白的醣型表現量，進而提高辨別肝炎患者與肝癌患者的診斷能力。在未來，甚至能更進一步對於感染不同病毒的患者進行區分。到目前為止，我們已經證實這些新開發的質譜分析平台可被用於偵測與定量癌症相關的蛋白質轉譯後修飾，而這些蛋白質轉譯後修飾的改變都是潛在的生物標記分子。此外，本論文的成果不僅僅有助於改善現今用於轉譯後修飾分析和生物標記分子的研究策略，同時也可作為闡明疾病基本致病機制的研究工具。

關鍵字

轉譯後修飾；生物標記分子；血清澱粉蛋白A ； alpha1-酸性醣蛋白； alpha-胎兒蛋白

並列摘要

Proteins execute biological functions and underpin metabolic and regulation processes in living cells. However, the real-time dynamics and regulation of protein function and structure plasticity are defined by specific PTMs. Increasing evidences show that the altered PTMs of proteins are highly relevant to disease and cancer and can be a source of potential cancer biomarker. Taking advantages of improvements in mass spectrometry instrumentation and experimental procedure designs, the recent advances in new mass spectrometry-based analytical methodologies enable the study of correlation between distinct protein PTMs and disease progression such as cancer. The overarching aim of this work is to develop mass spectrometry-based platforms coupled with different sample preparation methodologies, with the goal of analyzing cancer-specific PTMs of disease-related proteins. In Chapter 2, we designed an integrated platform combining nanoprobe-based affinity mass spectrometry with statistical classification to evaluate the alteration of serum amyloid A (SAA) variants profiling as an expression bar code for gastric cancer detection. This approach of protein profiling revealed the heterogeneous SAA variants in cancer, which also demonstrated the protein variant bar code as a cancer-related signature. In Chapter 3, a reliable MRM-based quantitative method to compare and elucidate the site-specific alpha 1-acid glycoprotein (AGP) glycoforms was developed and applied to discriminate between healthy individuals and liver cancer patients. The results showed markedly diverse glyco-profiles for each of the five N-glycosylation sites and increased glycoforms of sLeX and core fucosylation at specific sites between hepatocellular carcinoma (HCC) and non-cancer groups. In Chapter 4, an 18O stable-isotope labeling technique to evaluate the glycosylation occupancy (glycosylation/nonglycosylation ratio) of alpha-fetoprotein (AFP) obtained from patients with liver diseases was introduced. Through this proposed method, it is expected that the expression level of different AGP glycoforms can provide higher diagnostic power to distinguish patients with cirrhosis from those with liver cancer. In the future, it is also hoped that this information can be employed to differentiate between those patients with different virus infections. So far, it has been demonstrated that these newly developed MS platforms can be utilized to determine and quantify the characteristic alteration of protein PTMs related to cancer development, which can be potential biomarker candidates. Furthermore, the results of this work could not only help improve the existing methodologies for PTMs discovery and biomarker development, but also as tools to elucidate the underlying mechanisms in disease pathogenesis.

並列關鍵字

PTMs ； biomarker ； serum amyloid A ； alpha 1-acid glycoprotein ； alpha-fetoprotein

參考文獻

Chapter1 Reference

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