Consultoria em Patologia, Botucatu, Brazil.
Mod Pathol. 2012 Nov;25(11):1439-45. doi: 10.1038/modpathol.2012.119. Epub 2012 Jun 29.
Diffuse large B-cell lymphoma can be subclassified into at least two molecular subgroups by gene expression profiling: germinal center B-cell like and activated B-cell like diffuse large B-cell lymphoma. Several immunohistological algorithms have been proposed as surrogates to gene expression profiling at the level of protein expression, but their reliability has been an issue of controversy. Furthermore, the proportion of misclassified cases of germinal center B-cell subgroup by immunohistochemistry, in all reported algorithms, is higher compared with germinal center B-cell cases defined by gene expression profiling. We analyzed 424 cases of nodal diffuse large B-cell lymphoma with the panel of markers included in the three previously described algorithms: Hans, Choi, and Tally. To test whether the sensitivity of detecting germinal center B-cell cases could be improved, the germinal center B-cell marker HGAL/GCET2 was also added to all three algorithms. Our results show that the inclusion of HGAL/GCET2 significantly increased the detection of germinal center B-cell cases in all three algorithms (P<0.001). The proportions of germinal center B-cell cases in the original algorithms were 27%, 34%, and 19% for Hans, Choi, and Tally, respectively. In the modified algorithms, with the inclusion of HGAL/GCET2, the frequencies of germinal center B-cell cases were increased to 38%, 48%, and 35%, respectively. Therefore, HGAL/GCET2 protein expression may function as a marker for germinal center B-cell type diffuse large B-cell lymphoma. Consideration should be given to the inclusion of HGAL/GCET2 analysis in algorithms to better predict the cell of origin. These findings bear further validation, from comparison to gene expression profiles and from clinical/therapeutic data.
弥漫性大 B 细胞淋巴瘤可以通过基因表达谱分析分为至少两个分子亚型:生发中心 B 细胞样和激活 B 细胞样弥漫性大 B 细胞淋巴瘤。已经提出了几种免疫组织化学算法作为蛋白质表达水平的基因表达谱替代物,但它们的可靠性一直存在争议。此外,与基因表达谱定义的生发中心 B 细胞病例相比,所有报道的算法中通过免疫组织化学分类的生发中心 B 细胞亚组的错误分类病例比例更高。我们分析了 424 例淋巴结弥漫性大 B 细胞淋巴瘤,使用包括在三种先前描述的算法中的标记物面板:Hans、Choi 和 Tally。为了测试是否可以提高检测生发中心 B 细胞病例的敏感性,还将生发中心 B 细胞标志物 HGAL/GCET2 添加到所有三种算法中。我们的结果表明,包含 HGAL/GCET2 显著提高了所有三种算法中检测生发中心 B 细胞病例的敏感性(P<0.001)。原始算法中的生发中心 B 细胞病例比例分别为 Hans、Choi 和 Tally 的 27%、34%和 19%。在改良算法中,包含 HGAL/GCET2 后,生发中心 B 细胞病例的频率分别增加到 38%、48%和 35%。因此,HGAL/GCET2 蛋白表达可作为生发中心 B 细胞型弥漫性大 B 细胞淋巴瘤的标志物。应考虑在算法中纳入 HGAL/GCET2 分析,以更好地预测细胞起源。这些发现需要进一步验证,可通过与基因表达谱和临床/治疗数据进行比较来验证。