Markers of adenocarcinoma characteristic of the site of origin: Development of a diagnostic algorithm
Markers of adenocarcinoma characteristic of the site of origin: Development of a diagnostic algorithm
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DOI：
10.1158/1078-0432.ccr-04-2236
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发表时间：
2005-05-15
影响因子：
11.5
通讯作者：
Olien, KA
中科院分区：
文献类型：
--
作者：
Dennis, JL;Hvidsten, TR;Olien, KA
目的：未知来源的转移性腺癌患者是一个常见的临床问题。对主要部位的知识对于他们的管理很重要，但是从组织学上讲，这种肿瘤似乎相似。需要更好的诊断标记，以使转移分配到病理样本上的起源部位。实验设计：使用组织微阵列和免疫组织化学进行了27个候选标记的表达分析。在第一轮（训练）回合中，我们从七个主要部位（乳房，结肠，肺，卵巢，胰腺，前列腺和胃）研究了352个原发性腺癌。在Microsoft访问和Rosetta系统中分析了数据，并用于制定分类方案。在第二轮（验证）回合中，我们研究了100个主要的腺癌和30个成对转移。倒流：在第一轮中，我们在七个主要主要位点中的每个主要地点中的每个候选者中生成了所有27个候选标记。数据分析导致一个简化的诊断面板和决策树，仅包含10个标记：CA125，CDX2，细胞角蛋白7和20，雌激素受体，囊性疾病蛋白15，溶菌酶，间皮素，前列腺特异性抗原和甲状腺转录因子1。将面板和树应用于原始数据，提供了88％的正确分类。然后在第二个独立的，一组原发性和转移性肿瘤中测试了10个标记和诊断算法，并再次对88％进行了分类。结论：这种分类方案应在转移性腺癌患者中对原发性活检材料进行更好的预测。起源未知，导致管理和治疗的改善。
Purpose: Patients with metastatic adenocarcinoma of unknown origin are a common clinical problem. Knowledge of the primary site is important for their management, but histologically, such tumors appear similar. Better diagnostic markers are needed to enable the assignment of metastases to likely sites of origin on pathologic samples.Experimental Design: Expression profiling of 27 candidate markers was done using tissue microarrays and immunohistochemistry. In the first (training) round, we studied 352 primary adenocarcinomas, from seven main sites (breast, colon, lung, ovary, pancreas, prostate and stomach) and their differential diagnoses. Data were analyzed in Microsoft Access and the Rosetta system, and used to develop a classification scheme. In the second (validation) round, we studied 100 primary adenocarcinomas and 30 paired metastases.Results: In the first round, we generated expression profiles for all 27 candidate markers in each of the seven main primary sites. Data analysis led to a simplified diagnostic panel and decision tree containing 10 markers only: CA125, CDX2, cytokeratins 7 and 20, estrogen receptor, gross cystic disease fluid protein 15, lysozyme, mesothelin, prostate-specific antigen, and thyroid transcription factor 1. Applying the panel and tree to the original data provided correct classification in 88%. The 10 markers and diagnostic algorithm were then tested in a second, independent, set of primary and metastatic tumors and again 88% were correctly classified.Conclusions: This classification scheme should enable better prediction on biopsy material of the primary site in patients with metastatic adenocarcinoma of unknown origin, leading to improved management and therapy.