以奈米探針親和質譜法定量分析生物標記蛋白質變化與其醣基化修飾

Abstract

近年來，生物標記分子被廣泛應用於臨床疾病診斷、術後追蹤及輔助治療方式的選擇等等，然而，因缺乏可信分析方法、方法開發的高成本與高難度大大降低了驗證大量候選的生物標記分子的可能性，進而阻礙了這類分子於臨床使用上的發展。本篇論文中，我們建立一個新的定量分析方法並探討其後轉譯修飾的變異程度，藉由此一方法於非侵入性樣本尋找與驗證蛋白質生物標記分子。首先，我們設計界面劑包覆的單分散磁性奈米探針來提升其測量的靈敏度(MNP@IGEPAL)，並以固化定向抗體提升其專一性與免疫活性。我們發現，MNP@IGEPAL於溶劑中分散性與萃取效率皆優於傳統共沉澱法合成之磁性奈米探針(MNPcp)。 接著，我們將MNP@IGEPAL的萃取方法串聯多重反應監測質譜術(MRM-MS)，同時定量血清中低豐度的生物標記分子：甲種胎兒蛋白(AFP)與高爾基體膜蛋白1(GOLM1)，此一方法提供高靈敏度、優化的分析品質(平均準確度與精密度皆於15%以內)與寬動態範圍的分析條件。此外，我們基於此方法分析定量肝病病患血清中的生物標記分子，結果顯示，甲種胎兒蛋白與高爾基體膜蛋白1對肝癌具有相似的診斷準確度，更重要的是，近七成低濃度甲種胎兒蛋白(<20 ng/mL)病患中，高爾基體膜蛋白1的量增加，因此我們認為這兩個蛋白質於疾病診斷上有互補性。除了檢測蛋白質濃度外，我們希望藉由蛋白質上的後轉譯修飾輔助疾病的診斷，因此，我們設計了一鍋化雙功能奈米探針搭配質譜分析技術，以期同時定量蛋白質與定性其後轉譯修飾的分布。藉由分析AFP與血紅素結合蛋白 (Hp) 證實我們能以少量樣品於短時間內完成高靈敏度的蛋白質定量並鑑定其醣型分布。個人化分析肝癌病患除提供其標的蛋白的生物特徵外，更於甲種胎兒蛋白中鑑定了59個醣型，其中12種醣型是於此一蛋白中首次被辨認。最終，我們期許此一方法的建立能促進疾病診斷便利性，並應用於其他癌症與疾病的大規模生物標記分子的篩選、定量與後轉譯修飾的分布。

Disease biomarker development is plagued by lack of acceptable analytical methods, difficulty and cost for method development, overwhelming need for validation on a large population and the poor performance of biomarkers under development. In this dissertation, we introduce alternative methods for protein biomarker discovery and validation that encompasses quantification and post-translational modification (PTM) profiling in non-invasive specimens. We first designed surfactant-coated monodisperse magnetic nanoprobes to improve detection sensitivity (MNP@IGEPAL). Following oriented antibody immobilization for increased specificity and immuno-activity, the MNP@IGEPAL were found to be superior in solvent dispersibility and enrichment efficiency compared to nanoprobes obtained by conventional co-precipitation method (MNPCP). We then coupled the MNP@IGEPAL-based enrichment to multiple reaction monitoring mass spectrometry (MRM-MS) for multiplexed quantification of alpha-fetoprotein (AFP) and golgi membrane protein 1 (GOLM1), which are low-abundant biomarkers in human serum. The method was found to be sensitive, have good analytical merits (average precision and accuracy of 15%) and wide dynamic range. This method was applied to qualify the biomarkers in serum of liver disease patients, where we found that AFP and GOLM1 had similar diagnostic accuracy for hepatocellular carcinoma (HCC), although AFP has a higher false negative rate (sensitivity = 22%). More importantly, we found complementarity between AFP and GOLM1, where GOLM1 was found to be elevated in 69% of patients with low AFP concentration (<20 ng/mL). To supplement disease diagnoses based on protein concentration, we designed a one-pot dual nanoprobe-based mass spectrometry method to simultaneously quantify the protein and profile its post-translational modification (PTM). Using AFP and another clinically-relevant protein, haptoglobin (Hp), we were able to quantify the protein and profile its glycoforms with superior speed and sensitivity and minimal amount of sample. In addition to obtaining individual biosignatures of AFP in HCC patients, we were able to identify a total of 59 glycoforms, 12 of which were identified on AFP for the first time. Ultimately, we were able to develop methods that can improve disease diagnosis, which can be applied to other cancers and diseases for large-scale biomarker triaging, qualification and PTM profiling.