Surface-Enhanced Laser Desorption/Ionization Time-of-flight Mass Spectrometry-mediated Identification of a Biomarker Pattern for Hepatocellular Carcinoma in Taiwanese Patients

利用表面增強雷射脫附游離／飛行時間質譜鑑定台灣病患肝細胞癌的生物標記模式

梁雲(Stephen Wan Leung) ； 孫盟舜(Meng-Shun Sun) ； 何繼忠(Kai-Chung Ho) ； 羅偉菁(Wei-Ching Lo) ； 羅海韻(Hoi-Wan Lo) ； 柯成國(Chen-Guo Ker)

《放射治療與腫瘤學》 19卷3期 (2012/09) Pp. 201-212

https://doi.org/10.6316/TRO/201219(3)201

摘要

目的：早期診斷肝細胞癌是非常重要的，以作為防止其發展成極具破壞性與高好發率的惡性腫瘤。所以，如何在肝細胞癌發展早期便能找出一診斷標記來區別其為良性或惡性是非常有其必要性。此研究中，我們使用SELDI-TOS-MS光譜來分析台灣肝癌族群與非肝癌健康族群血清中之蛋白圖譜。材料及方法：以SELDI晶片系統去偵測台灣人肝癌細胞與非肝癌族群之特定血清內蛋白型態。在最初於台灣阮綜合醫院收集63位受檢者之血清。為了確認潛在有效用的標記，收集另一組63位台灣人血清檢體做為隨機性單盲有效測試。血清測試系統使用Ciphergen ProteinChip®SAX2矩陣系列，並利用ProteinChip Reader Model PBS II系統分析晶片上蛋白質。在晶片計讀後，所有正常及腫瘤血清圖譜都以生物標記型態軟體整理及分析其數據及顯示形態。結果：在搜尋兩組63位檢體作為對照與效力測試，我們找出生物標記圖譜含有四個血清蛋白標記位置在m/z:4091、5637、6840與8567上。此研究建立一個人工網路用做肝細胞癌的高特異性與敏感度之偵測。也就是說能鑑定出的生物標記型態， 可用來區分HCC與非HCC異常族群。並於進一步實驗顯示出，此生物標記型態之靈敏度及特異性可各自達到93.33%及93.93% 所以這檢體可用來分析及發展一區分類性評分系統。結論：這是首次使用SELDl-TOF-MS與簡評分系統去鑑定出一特異性生物標記模式，可有效率及其意義的從非肝癌病人族群中鑑定出肝癌病人。

關鍵字

診斷 ； 蛋白質體學 ； 蛋白質晶片 ； 表面增強雷射脫附游離／飛行時間質譜 ； 肝癌

並列摘要

Purpose: The early detection of hepatocellular carcinoma (HCC) is of tremendous importance to prevent this devastating and frequently reported cancer. Therefore, it is required to identify novel and specific HCC diagnostic marker(s) to distinguish HCC patients from non-HCC patients at the early stage of HCC development. We employed surface enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) to analyze protein profiles in the serum of Taiwanese HCC and healthy, non-HCC subjects.Materials and Methods: The SELDI-Chip-System was used to determine a specific protein pattern in serum samples obtained from Taiwanese HCC and non-HCC subjects. The initial training group consisted of 63 subjects from whom serum was collected at the Yuan's General Hospital (Taiwan). To validate a potential marker pattern, a second group of 63 Taiwanese subjects was enrolled from whom serum samples were also collected, randomized, and used in a blind validation study. Serum was applied to Ciphergen ProteinChip® SAX2 Arrays and proteins bound to the chips were analyzed using the ProteinChip Reader Model PBS II. After reading the chips, all profiles of normal and tumor serum were summarized using the Biomarker pattern software to a master pattern followed by analyses using a clustering method and data mining.Results: By recruiting two groups of 63 subjects for training and validation, we identified a biomarker pattern that contained four serum protein markers with m/z of 4091, 5637, 6840, and 8567. This study allowed setting up an artificial network with high specificity and sensitivity for HCC detection. In other words, the identified biomarker pattern was used to classify serum samples of HCC and non-HCC validation group subjects. During the latter experiment, it appeared that the sensitivity and specificity of the pattern was 93.33% and 93.93%, respectively. The specimens were used to analyze and develop a classification scoring system.Conclusions: For the first time, SELDI-TOF-MS combined with a simple scoring system were employed to identify a specific biomarker pattern that allowed to efficiently and significantly distinguish Taiwanese HCC patients from non-HCC patients.

並列關鍵字

Diagnostics ； Proteomics ； Protein chip ； SELDI-TOF-MS ； Liver cancer