Roblick U J, Bader F G, Lenander C, Hellman U, Zimmermann K, Becker S, Ost A, Alaiya A, Bruch H-P, Keller R, Mirow L, Franzén B, Ried T, Auer G, Habermann J K
Laboratory for Surgical Research, Department of Surgery, University Hospital of Schleswig-Holstein, Campus Lübeck, Ratzeburgerallee 160, 23538 Lübeck, Germany.
Int J Colorectal Dis. 2008 May;23(5):483-91. doi: 10.1007/s00384-008-0448-6. Epub 2008 Feb 22.
Despite improved techniques, the determination of tumor origin in poorly differentiated adenocarcinomas still remains a challenge for the pathologist. Here we report the use of protein profiling combined with principal component analysis to improve diagnostic decision-making in tumor samples, in which standard pathologic investigations cannot present reliable results.
A poorly differentiated adenocarcinoma of unknown origin located in the pelvis, infiltrating the sigmoid colon as well as the ovary, served as a model to evaluate our proteomic approach. Firstly, we characterized the protein expression profiles from eight advanced colon and seven ovarian adenocarcinomas using two-dimensional gel electrophoresis (2-DE). Qualitative and quantitative patterns were recorded and compared to the tumor of unknown origin. Based on these protein profiles, match sets from the different tumors were created. Finally, a multivariate principal component analysis was applied to the entire 2-DE data to disclose differences in protein patterns between the different tumors.
Over 89% of the unknown tumor sample spots could be matched with the colon standard gel, whereas only 63% of the spots could be matched with the ovarian standard. In addition, principal component analysis impressively displayed the clustering of the unknown case within the colon cancer samples, whereas this case did not cluster at all within the group of ovarian adenocarcinomas.
These results show that 2-DE protein expression profiling combined with principal component analysis is a sensitive method for diagnosing undifferentiated adenocarcinomas of unknown origin. The described approach can contribute greatly to diagnostic decision-making and, with further technical improvements and a higher throughput, become a powerful tool in the armentarium of the pathologist.
尽管技术有所进步，但对于病理学家而言，确定低分化腺癌的肿瘤起源仍是一项挑战。在此，我们报告使用蛋白质谱分析结合主成分分析来改善肿瘤样本的诊断决策，在这些样本中，标准病理检查无法给出可靠结果。
一例位于盆腔、起源不明的低分化腺癌，浸润乙状结肠及卵巢，作为评估我们蛋白质组学方法的模型。首先，我们使用二维凝胶电泳（2-DE）对8例晚期结肠癌和7例卵巢腺癌的蛋白质表达谱进行了表征。记录定性和定量模式，并与起源不明的肿瘤进行比较。基于这些蛋白质谱，创建了不同肿瘤的匹配集。最后，对整个二维电泳数据应用多变量主成分分析，以揭示不同肿瘤之间蛋白质模式的差异。
超过89%的未知肿瘤样本点可与结肠癌标准凝胶匹配，而只有63%的点可与卵巢标准凝胶匹配。此外，主成分分析令人印象深刻地显示了未知病例在结肠癌样本中的聚类情况，而该病例在卵巢腺癌组中根本没有聚类。
这些结果表明，二维凝胶电泳蛋白质表达谱分析结合主成分分析是诊断起源不明的未分化腺癌的一种敏感方法。所描述的方法可极大地有助于诊断决策，并且随着技术的进一步改进和更高的通量，成为病理学家武器库中的有力工具。
