Department of Pathology, Women's and Perinatal Pathology Division, Brigham and Women's Hospital, Boston, MA, USA.
Mod Pathol. 2014 Apr;27(4):569-79. doi: 10.1038/modpathol.2013.123. Epub 2013 Sep 27.
When classifying cellular uterine mesenchymal neoplasms, histological distinction of endometrial stromal from smooth muscle neoplasms can be difficult. The only widely established marker of endometrial stromal differentiation, CD10, has marginal specificity. We took a bioinformatics approach to identify more specific markers of endometrial stromal differentiation by searching the Human Protein Atlas, a public database of protein expression profiles. After screening the database using different methods, interferon-induced transmembrane protein 1 (IFITM1) was selected for further analysis. Immunohistochemistry for IFITM1 was performed using tissue sections from the selected cases of proliferative endometrium (22), secretory endometrium (6), inactive endometrium (19), adenomyosis (10), conventional leiomyoma (11), cellular leiomyoma (16), endometrial stromal nodule (2), low-grade endometrial stromal sarcoma (16), high-grade endometrial stromal sarcoma (2) and undifferentiated uterine sarcoma (2). Stained slides were scored in terms of intensity and distribution. Normal endometrial samples uniformly showed diffuse and strong IFITM1 staining. Endometrial stromal neoplasms, particularly low-grade endometrial stromal sarcoma, showed higher IFITM1 expression compared with smooth muscle neoplasms (P<0.0001). IFITM1 immunohistochemistry has high sensitivity and specificity, particularly in the distinction between low-grade endometrial stromal sarcoma and leiomyoma (81.2 and 86.7%, respectively). Our results indicate that IFITM1 is a sensitive and specific marker of endometrial stromal differentiation across the spectrum from proliferative endometrium to metastatic stromal sarcoma. IFITM1 is a potential valuable addition to immunohistochemical panels used in the diagnosis of cellular mesenchymal uterine tumors. Further studies with larger number of cases are necessary to corroborate this impression and determine the utility of IFITM1 in routine practice. This study is a clear example of how bioinformatics, particularly tools for mining genomic and proteomic databases, can enhance and accelerate biomarker development in diagnostic pathology.
在对子宫间质肿瘤进行分类时，子宫内膜基质与平滑肌肿瘤的组织学区分可能较为困难。唯一广泛确立的子宫内膜基质分化标志物 CD10，其特异性有限。我们采用生物信息学方法，通过搜索人类蛋白质图谱（一种公共蛋白质表达谱数据库）来寻找更特异的子宫内膜基质分化标志物。使用不同方法筛选数据库后，选择干扰素诱导跨膜蛋白 1（IFITM1）进行进一步分析。使用所选病例的组织切片进行 IFITM1 免疫组化检测，包括增生期子宫内膜（22 例）、分泌期子宫内膜（6 例）、静止期子宫内膜（19 例）、子宫腺肌病（10 例）、普通平滑肌瘤（11 例）、富于细胞性平滑肌瘤（16 例）、子宫内膜间质结节（2 例）、低级别子宫内膜间质肉瘤（16 例）、高级别子宫内膜间质肉瘤（2 例）和未分化子宫肉瘤（2 例）。根据染色强度和分布对染色切片进行评分。正常子宫内膜样本均显示弥漫性和强 IFITM1 染色。与平滑肌肿瘤相比，子宫内膜间质肿瘤，特别是低级别子宫内膜间质肉瘤，显示出更高的 IFITM1 表达（P<0.0001）。IFITM1 免疫组化具有较高的敏感性和特异性，特别是在低级别子宫内膜间质肉瘤和平滑肌瘤的鉴别诊断中（分别为 81.2%和 86.7%）。我们的结果表明，IFITM1 是一种从增生期子宫内膜到转移性间质肉瘤的广谱子宫内膜基质分化的敏感和特异标志物。IFITM1 是用于诊断富于细胞性子宫间叶肿瘤的免疫组化组合的潜在有价值的补充标志物。需要更多病例的进一步研究来证实这一印象，并确定 IFITM1 在常规实践中的效用。本研究清楚地说明了生物信息学，特别是挖掘基因组和蛋白质组数据库的工具，如何增强和加速诊断病理学中的生物标志物开发。
