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计算机图像分析显示 C-Myc 可作为鉴别角化棘皮瘤和皮肤鳞状细胞癌的潜在生物标志物。

Computer Image Analysis Reveals C-Myc as a Potential Biomarker for Discriminating between Keratoacanthoma and Cutaneous Squamous Cell Carcinoma.

机构信息

Key Laboratory of Immunodermatology, Ministry of Education, Department of Dermatology, The First Hospital of China Medical University, Shenyang 110001, China.

Key Laboratory of Immunodermatology, National Health Commission of the People's Republic of China, The First Hospital of China Medical University, Shenyang 110001, China.

出版信息

Biomed Res Int. 2022 Aug 23;2022:3168503. doi: 10.1155/2022/3168503. eCollection 2022.

Abstract

The distinction between Keratoacanthoma (KA) and Cutaneous Squamous Cell Carcinoma (cSCC) is critical yet usually challenging to discriminate clinically and histopathologically. One approach to differentiate KA from cSCC is through assessing the immunohistochemical staining patterns of the three indicators, -catenin, C-Myc, and CyclinD1, which are critical molecules that play important roles in the Wnt/-catenin signaling pathway. Ki-67, as a proliferation biomarker for human tumor cells, was also assessed as an additional potential marker for differentiating KA from cSCC. In this report, these four indicators were analyzed in 42 KA and 30 cSCC cases with the use of the computer automated image analysis system. Computer automated image analysis is a time-based and cost-effective method of determining IHC staining in KA and cSCC samples. We found that C-Myc staining was predominantly localized in the nuclei of basal cells within KA patients, whereas cSCC staining was predominantly localized in the nuclei of diffuse cells. This C-Myc staining pattern has a sensitivity of 78.6% and a specificity of 66.7% for identifying KA. Moreover, positive rates of distinct expression patterns of C-Myc and Ki-67 may also serve as a means to clinically distinguish KA from cSCC. Taken together, our results suggest that these markers, in particular C-Myc, may be useful in differentiating KA from cSCC.

摘要

角化棘皮瘤(KA)和皮肤鳞状细胞癌(cSCC)的鉴别具有重要意义,但在临床上和组织病理学上通常难以区分。区分 KA 和 cSCC 的一种方法是通过评估三种指标 - 连环蛋白(-catenin)、C-Myc 和细胞周期蛋白 D1 的免疫组织化学染色模式,这些是在 Wnt/-catenin 信号通路中发挥重要作用的关键分子。Ki-67 作为人类肿瘤细胞的增殖生物标志物,也被评估为区分 KA 和 cSCC 的另一个潜在标志物。在本报告中,使用计算机自动图像分析系统分析了 42 例 KA 和 30 例 cSCC 病例中的这四个指标。计算机自动图像分析是一种基于时间和成本效益的方法,用于确定 KA 和 cSCC 样本中的免疫组织化学染色。我们发现 C-Myc 染色主要定位于 KA 患者基底细胞的核内,而 cSCC 染色主要定位于弥漫细胞的核内。这种 C-Myc 染色模式对识别 KA 的灵敏度为 78.6%,特异性为 66.7%。此外,C-Myc 和 Ki-67 的不同表达模式的阳性率也可作为临床上区分 KA 和 cSCC 的一种手段。总之,我们的结果表明,这些标志物,特别是 C-Myc,可能有助于区分 KA 和 cSCC。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/527c/9427316/0994c3c1c8cd/BMRI2022-3168503.001.jpg

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