Kawaguchi Kathy R, Lu Fang-I, Kaplan Rachel, Liu Yi-Fang, Chadwick Paul, Chen Zhengming, Brogi Edi, Shin Sandra J
Departments of *Pathology and Laboratory Medicine ‡Public Health, Division of Biostatistics and Epidemiology, Weill Cornell Medical College †Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY.
Appl Immunohistochem Mol Morphol. 2014 Apr;22(4):266-74. doi: 10.1097/PAI.0b013e318297cc0b.
Distinguishing metastatic carcinoma of breast origin (MCBO) to lung from primary lung carcinomas (PLC) is a diagnostic quandary with clinical ramifications. Immunostains CK7, CK20, ER, PR, and Mammaglobin as well as pertinent negative stains are utilized but prove insufficient. We set out to identify stains either alone or as a group that would better discern between these 2 entities.
Tissue microarrays of 109 MCBO to lung and 102 PLC were stained with CK7, CK20, ER, PR, AR, Mammaglobin, Napsin A, GATA-3, and TTF-1. An H-score was calculated for each case and stain.
The highest area under the receiver-operating characteristic curves for each stain was seen with GATA-3 (0.817), Napsin A (0.817), and TTF-1 (0.854). When all possible combinations were analyzed, GATA-3 and TTF-1 proved to correctly classify with the highest accuracy (0.934). Combinations of GATA-3 and Napsin A (0.920) and GATA-3, Napsin A, and TTF-1 (0.933) were not significantly different from GATA-3 and TTF-1. The odds ratios for each stain and combination of stains showed that those for GATA-3 and TTF-1 were divergent, signifying that cases with higher H-scores for GATA-3 and TTF-1 were more likely to be classified as MCBO and PLC, respectively.
GATA-3 and TTF-1 can correctly classify a case as either MCBO or PLC in 93.4% of cases. Although highly specific and sensitive for PLC, Napsin A in lieu of TTF-1 or as an additional stain did not improve classification accuracy.
鉴别源自乳腺的肺转移癌（MCBO）与原发性肺癌（PLC）是一个具有临床影响的诊断难题。免疫组化染色使用细胞角蛋白7（CK7）、细胞角蛋白20（CK20）、雌激素受体（ER）、孕激素受体（PR）、乳腺珠蛋白以及相关的阴性染色，但证明并不充分。我们着手确定单独或作为一组能够更好区分这两种实体的染色方法。
用CK7、CK20、ER、PR、雄激素受体（AR）、乳腺珠蛋白、 napsin A、GATA-3和甲状腺转录因子1（TTF-1）对109例MCBO和102例PLC的组织芯片进行染色。计算每个病例和每种染色的H评分。
每种染色在受试者操作特征曲线下的最高面积见于GATA-3（0.817）、napsin A（0.817）和TTF-1（0.854）。当分析所有可能的组合时，GATA-3和TTF-1被证明以最高的准确率（0.934）正确分类。GATA-3和napsin A的组合（0.920）以及GATA-3、napsin A和TTF-1的组合（0.933）与GATA-3和TTF-1没有显著差异。每种染色和染色组合的优势比表明，GATA-3和TTF-1的优势比不同，这表明GATA-3和TTF-1的H评分较高的病例分别更有可能被分类为MCBO和PLC。
GATA-3和TTF-1在93.4%的病例中可以正确地将病例分类为MCBO或PLC。尽管napsin A对PLC具有高度特异性和敏感性，但替代TTF-1或作为额外的染色并未提高分类准确率。
