Abstract：
OBJECTIVE: Large-cell neuroendocrine carcinoma (LCNEC) and small-cell carcinoma (SCLC) of lung encompass high-grade neuroendocrine tumour category and share several fundamental features. As both tumours may respond to different treatment modalities and show unique molecular alterations distinction between the two is clinically relevant, but can be challenging due to sampling and fixation issues and shared morphological features.
METHODS: Surgically resected primary SCLC (n = 129) and LCNEC (n = 27) were immunohistochemically stained with Rb1, cyclin D1 and p16 using tissue microarray (TMA), and expression patterns of the proteins were compared between the two to identify the discriminatory pattern.
RESULTS: All markers had high diagnostic accuracy; Rb1 was the highest followed by p16 and cyclin D1. The majority of SCLC had the pattern Rb1-/p16+/cyclin D1- and more than half of LCNEC had Rb1+/p16-/cyclin D1+. Overall, the expression pattern Rb1- and cyclin D1- was strongly associated with the diagnosis of SCLC, while the pattern Rb1+ and/or cyclin D1+ was strongly associated with LCNEC. The use of this simplified expression pattern leads to a diagnostic accuracy of 97.3%. p16 did not add to further discrimination. The heterogeneity in Rb1, cyclin D1 and p16 expression was insignificant in SCLCs compared with LCNECs.
CONCLUSIONS: Use of Rb1, cyclin D1 and p16 immunohistochemistry can distinguish the two with high accuracy. Notably, the Rb1-/cyclin D1- pattern in given tumour sample would confirm the diagnosis of SCLC. Our results could be extrapolated and applied to routine diagnostic samples such as biopsies and cytology samples.
METHODS: Surgically resected primary SCLC (n = 129) and LCNEC (n = 27) were immunohistochemically stained with Rb1, cyclin D1 and p16 using tissue microarray (TMA), and expression patterns of the proteins were compared between the two to identify the discriminatory pattern.
RESULTS: All markers had high diagnostic accuracy; Rb1 was the highest followed by p16 and cyclin D1. The majority of SCLC had the pattern Rb1-/p16+/cyclin D1- and more than half of LCNEC had Rb1+/p16-/cyclin D1+. Overall, the expression pattern Rb1- and cyclin D1- was strongly associated with the diagnosis of SCLC, while the pattern Rb1+ and/or cyclin D1+ was strongly associated with LCNEC. The use of this simplified expression pattern leads to a diagnostic accuracy of 97.3%. p16 did not add to further discrimination. The heterogeneity in Rb1, cyclin D1 and p16 expression was insignificant in SCLCs compared with LCNECs.
CONCLUSIONS: Use of Rb1, cyclin D1 and p16 immunohistochemistry can distinguish the two with high accuracy. Notably, the Rb1-/cyclin D1- pattern in given tumour sample would confirm the diagnosis of SCLC. Our results could be extrapolated and applied to routine diagnostic samples such as biopsies and cytology samples.
摘要：
目的：肺的大细胞神经内分泌癌（LCNEC）和小细胞癌（SCLC）涵盖了高级神经内分泌肿瘤类别，并具有多个基本特征。由于两种肿瘤可能对不同的治疗方式有反应，并显示出独特的分子改变，两者之间的区别是临床相关的，但由于采样和固定问题以及共同的形态特征，可能具有挑战性。
方法：手术切除的原发性SCLC（n=129）和LCNEC（n=27）使用组织微阵列（TMA）用Rb1，细胞周期蛋白D1和p16进行免疫组织化学染色，和蛋白质的表达模式进行了比较，以确定区分模式。
结果：所有标记物的诊断准确性都很高；Rb1最高，其次是p16和cyclinD1。大多数SCLC的模式为Rb1-/p16+/细胞周期蛋白D1-，一半以上的LCNEC的模式为Rb1+/p16-/细胞周期蛋白D1+。总的来说,表达模式Rb1-和细胞周期蛋白D1-与SCLC的诊断密切相关，而Rb1+和/或细胞周期蛋白D1+模式与LCNEC密切相关。使用这种简化的表达模式导致97.3%的诊断准确度。p16没有增加进一步的歧视。与LCNEC相比，SCLC中Rb1，cyclinD1和p16表达的异质性不明显。
结论：使用Rb1，cyclinD1和p16免疫组织化学可以高度区分两者。值得注意的是,给定肿瘤样本中的Rb1-/细胞周期蛋白D1-模式将证实SCLC的诊断。我们的结果可以外推并应用于常规诊断样品，例如活检和细胞学样品。
方法：手术切除的原发性SCLC（n=129）和LCNEC（n=27）使用组织微阵列（TMA）用Rb1，细胞周期蛋白D1和p16进行免疫组织化学染色，和蛋白质的表达模式进行了比较，以确定区分模式。
结果：所有标记物的诊断准确性都很高；Rb1最高，其次是p16和cyclinD1。大多数SCLC的模式为Rb1-/p16+/细胞周期蛋白D1-，一半以上的LCNEC的模式为Rb1+/p16-/细胞周期蛋白D1+。总的来说,表达模式Rb1-和细胞周期蛋白D1-与SCLC的诊断密切相关，而Rb1+和/或细胞周期蛋白D1+模式与LCNEC密切相关。使用这种简化的表达模式导致97.3%的诊断准确度。p16没有增加进一步的歧视。与LCNEC相比，SCLC中Rb1，cyclinD1和p16表达的异质性不明显。
结论：使用Rb1，cyclinD1和p16免疫组织化学可以高度区分两者。值得注意的是,给定肿瘤样本中的Rb1-/细胞周期蛋白D1-模式将证实SCLC的诊断。我们的结果可以外推并应用于常规诊断样品，例如活检和细胞学样品。
