Department of Pathology, BC Cancer Agency, Vancouver, British Columbia, Canada.
Am J Surg Pathol. 2010 Dec;34(12):1805-11. doi: 10.1097/PAS.0b013e3181f7dae3.
The histologic subtype of non-small cell lung carcinoma is important in selecting appropriate chemotherapy for patients with advanced disease. As many of these patients are not operative candidates, they are treated medically after biopsy for diagnosis. Inherent limitations of small biopsy samples can make distinguishing poorly differentiated lung adenocarcinoma (ADC) from squamous cell carcinoma (SCC) difficult. The value of histochemical and immunohistochemical markers to help separate poorly differentiated ADC from SCC in resection specimens is well established; however, the optimal use of markers in small tissue samples has only recently been examined and the correlation of marker expression in small tissue samples with histologic subtype determined on resection specimens has not been well documented. We address this issue by examining the expression of 9 markers (p63, TTF1, CK5/6, CK7, 34βE12, Napsin A, mucicarmine, NTRK1, and NTRK2) on 200 cases of ADC and 225 cases of SCC in tissue microarray format to mimic small tissue specimens. The single best marker to separate ADC from SCC is p63 (for SCC: sensitivity 84%, specificity 85%). Logistic regression analysis identifies p63, TTF1, CK5/6, CK7, Napsin A, and mucicarmine as the optimal panel to separate ADC from SCC. Reduction of the panel to p63, TTF1, CK5/6, and CK7 is marginally less effective but may be the best compromise when tissue is limited. We present an algorithm for the stepwise application of p63, TTF1, CK5/6, CK7, Napsin A, and mucicarmine in situations in which separation of ADC from SCC in small specimens cannot be accomplished by morphology alone.
非小细胞肺癌的组织学亚型对于选择晚期疾病患者的合适化疗方案非常重要。由于这些患者中的许多都不是手术候选人,因此在活检后进行诊断时会进行医学治疗。小活检样本固有的局限性使得区分低分化肺腺癌(ADC)和鳞状细胞癌(SCC)变得困难。组织化学和免疫组织化学标志物有助于区分切除标本中低分化 ADC 和 SCC 的价值已得到充分确立;然而,最近才研究了小组织样本中标志物的最佳使用方法,并且小组织样本中标志物表达与切除标本上组织学亚型的相关性尚未得到很好的记录。我们通过在组织微阵列格式下检查 200 例 ADC 和 225 例 SCC 中 9 种标志物(p63、TTF1、CK5/6、CK7、34βE12、Napsin A、粘蛋白、NTRK1 和 NTRK2)的表达来解决这个问题,以模拟小组织样本。单独用于区分 ADC 和 SCC 的最佳标志物是 p63(用于 SCC:敏感性 84%,特异性 85%)。逻辑回归分析确定 p63、TTF1、CK5/6、CK7、Napsin A 和粘蛋白是区分 ADC 和 SCC 的最佳组合。将面板减少到 p63、TTF1、CK5/6 和 CK7 的效果略差,但当组织有限时,可能是最佳折衷方案。我们提出了一种逐步应用 p63、TTF1、CK5/6、CK7、Napsin A 和粘蛋白的算法,用于在仅凭形态学无法区分小标本中的 ADC 和 SCC 的情况下。