鑑定幽門螺旋桿菌中之生物標記分子及開發胃癌診斷之膜蛋白質晶片

Abstract

幽門螺旋桿菌為人類的病原菌，是一種寄生於人類消化道的革蘭氏陰性菌，並且造成了胃發炎、胃潰瘍、十二指腸潰瘍及胃癌等消化道疾病。有趣的是，臨床統計結果發現受幽門螺旋桿菌感染的病人其得到十二指腸潰瘍或是胃癌是兩條分歧的臨床走向。而之前有一些研究顯示幽門螺旋桿菌的膜蛋白對於菌的致病性及和宿主之間的辨認都扮演了重要的角色，因此我們的研究主要就是希望能從幽門螺旋桿菌的膜蛋白質中找到胃癌相關的生物標記分子，並期望能發展出一個新的平台以應用於臨床上，幫助簡易且快速的診斷出受幽門螺旋桿菌感染的胃癌病患，並能與十二指腸潰瘍病患做區隔。 過去實驗室比較從胃癌及十二指腸潰瘍病人體內分離出來的幽門螺旋桿菌菌株之膜蛋白質體，我們將目標放在於胃癌菌株中表現量高於十二指腸潰瘍菌株的蛋白質，並鑑定到了57個蛋白質。而在我們的實驗中，我們發現了四個膜蛋白具有潛力能做為生物標記分子，這四個膜蛋白為: outer inflammatory protein (OipA), adherence-associated lipoprotein A (AlpA), sialic acid-binding adhesin (SabA)與blood group antigen binding adhesin (BabB)，這四個蛋白都被報導為黏著因子，與幽門螺旋桿菌貼附於胃表皮細胞及胃黏膜相關。我們將這四個膜蛋白基因進行質體建構並且純化出重組蛋白，再利用西方墨點法將重組蛋白與正常人或胃發炎、十二指腸潰瘍及胃癌病人的血清進行反應，結果顯示OipA, AlpA, SabA及BabB這四個膜蛋白在胃癌這組中的免疫反應程度都高於十二指腸潰瘍的組別，且有顯著差異，經過更進一步的統計後發現OipA, SabA與BabB這三個膜蛋白與胃癌病人有高度相關性。此外，我們還將四個膜蛋白合併在一起進行檢測發現到隨著病人辨認到的抗原膜蛋白的個數增加，能區分胃癌與十二指腸潰瘍病人的效果更加顯著，勝算比從只認到一個抗原的0.75 (0.26–2.15)，到認到兩個抗原的3.00 (0.95–9.53)，再到認到三個抗原或是全部抗原都有認到的6.33 (1.29–31.1)。從以上的結果我們認為，我們所選擇的這四個膜蛋白是具潛力的胃癌相關之幽門螺旋桿菌生物標記分子。 接著，我們為了發展出一個能在臨床上快速又方便的診斷方法，我們選擇以蛋白質晶片為基礎並測試了適合膜蛋白點印於晶片上的條件，以製做出胃癌相關之幽門螺旋桿菌膜蛋白質抗原晶片，並且以正常人或十二指腸潰瘍及胃癌的病人血清與膜蛋白晶片進行反應，我們發現到膜蛋白晶片的結果與前一部份以西方墨點法檢測的結果相符合，OipA, SabA及BabB確實能夠將胃癌的病人與十二指腸潰瘍病患及正常人區分開來。未來我們希望能夠利用我們發展的胃癌相關之幽門螺旋桿菌膜蛋白質抗原晶片去偵測病人血清內多種抗體的反應程度，並期望此平台及結合複合型生物標記分子的概念能有效應用於臨床診斷上。

Helicobacter pylori (H. pylori), a human pathogen, is a gram-negative bacterium that colonizes in the host gastroduodenal tract, causing some variant diseases like gastritis, gastric ulcer (GU), duodenal ulcer (DU) and gastric cancer (GC). Interestingly, DU and GC are considered as clinically divergent events. Some previous studies suggested that the outer membrane proteins of H. pylori played important roles in pathogenesis and host recognition. Thus, we aimed to focus on discovering the outer membrane proteins of H. pylori as GC-related biomarkers, and to develop a new platform which is rapid and easy for diagnosis of screening GC patients from DU patients infected by H. pylori. In our previous study, we compared the membrane proteome of two clinical H. pylori strains, one strain from GC patients and the other strain from DU patients. We identified 57 proteins which the expression levels of GC strain were higher than that of DU strain. In this study, we found four membrane proteins as potential biomarkers. The four proteins were outer inflammatory protein (OipA), adherence-associated lipoprotein A (AlpA), sialic acid-binding adhesin (SabA) and blood group antigen binding adhesin (BabB). These candidates were reported to be responsible for the adhesion of H. pylori to the host gastric epithelium and mucosa. We cloned and purified the recombinant membrane proteins. Using immunoblot, the purified proteins were probed with serum samples from gastritis, DU, GC patients and normal controls. The results revealed that OipA, AlpA, SabA and BabB showed significantly higher immuno-reactivity in GC patients than that in DU patients, and OipA, SabA and BabB were strongly related to GC. In addition, we found that the use of multiple antigens improved the discrimination between patients with GC and those with DU as the odds ratios increased from 0.75 (0.26–2.15) for seropositivity for any one antigen alone to 3.00 (0.95–9.53) for two of the four antigens and to 6.33 (1.29–31.1) for three antigens or all four antigens. These results suggested that these adhesion molecules we selected may be potential H. pylori GC-associated biomarkers. Moreover, to develop a faster and more convenient platform for diagnosis, we tested the condition for printing the purified recombinant membrane proteins onto glass slides to create GC-related antigen membrane protein chip and the chip was incubated with serum from DU, GC patients and normal controls. The results were significantly consistent with our results of immunoblot that OipA, SabA and BabB were potential biomarkers for specifically distinguishing GC from DU and healthy controls. In the future, we expect to use GC-related antigen membrane protein chip to detect antibody patterns in sera of patients and the membrane protein chip combined with the idea of multiple biomarkers can be used for diagnostic application.