基于免疫组化和数字图像分析的子宫内膜免疫细胞定量检测平台
Summary
本文开发并验证了数字免疫组化图像分析平台，用于定量分析复发性流产患者在植入窗口期的子宫内膜免疫细胞。
Abstract
为评估复发性流产（RM）患者的子宫内膜免疫微环境，开发并验证了数字免疫组化图像分析平台，用于定量分析黄体中期子宫内膜免疫细胞。所有子宫内膜样本均在月经周期的黄体中期采集。将石蜡包埋的子宫内膜组织切片成4 μm厚的载玻片，进行免疫组化（IHC）染色检测子宫内膜免疫细胞，包括CD56+ uNK细胞、Foxp3+ Tregs、CD163+ M2巨噬细胞、CD1a+ DCs和CD8+ T细胞。使用数字玻片扫描仪对全景玻片进行扫描，并使用商业图像分析系统进行定量分析。子宫内膜免疫细胞的百分比是通过除以总子宫内膜细胞中的免疫细胞数来计算的。使用商用图像分析系统，可以轻松准确地分析传统图像分析难以或不可能分析的子宫内膜免疫细胞的定量评估。该方法可用于定量表征子宫内膜微环境，包括免疫细胞之间的相互作用，以及不同生殖失败患者的异质性。子宫内膜免疫细胞定量评估平台对RM患者的诊断和治疗具有重要的临床意义。
Introduction
复发性流产（RM）是指连续两次或两次以上妊娠的流产，是一种复杂的疾病，近年来引起了临床医生的关注。育龄妇女RM的发病率为1%-5%1。既往研究结果表明，免疫因子与RM 2,3,4,5的发病机制密切相关。维持母胎界面的免疫稳态是胚胎植入和发育所必需的。子宫内膜免疫细胞在维持这种稳态方面发挥多种调节作用，例如促进滋养层侵袭、重塑螺旋动脉和促进胎盘发育 6,7,8,9。
RM 女性的子宫内膜免疫细胞异常既往已有报道。结果显示，高密度子宫自然杀伤细胞 （uNK） 与 RM10、11、12 的发生密切相关。据报道，与活产女性相比，RM女性子宫内膜中的巨噬细胞数量有所增加13。调节性T细胞（Treg）在母体对胚胎的免疫耐受中发挥作用，其水平和功能在RM患者的蜕膜中降低14。细胞毒性 T 细胞 （CTL） 和树突状细胞 （DC） 也在妊娠的免疫调节中发挥作用15,16。因此，对黄体中期局部子宫内膜免疫细胞进行全面的定量分析有助于更好地了解RM的发病机制。目前一些用于子宫内膜免疫细胞定量分析的方法使用流式细胞术，它可以准确地标记具有多种标记物的免疫细胞17,18。然而，流式细胞术的临床应用受到限制，因为它只能在新鲜组织上进行。只有当存在大量多余肿瘤时，获得新鲜组织才可行，这在子宫内膜中很少见。免疫组化可以很好地原位观察组织形态，也可以标记各种免疫细胞，而传统的免疫组化技术无法对免疫细胞进行定量分析。
与常规免疫组化实验相比，子宫内膜免疫细胞的定量免疫组化分析具有重要的临床意义。IHC强度评分通常采用四分制或病理诊断和研究中的强弱排序19,20,21。然而，这种半定量技术是主观的、高度不准确的，并显示出显著的观察者内部和观察者间变异性22。一种可能的解决方案是机器学习的应用，这在数字图像分析中很有价值23,24。通过提供定量测量，这种方法可以更精确地评估子宫组织内的免疫细胞浸润、分布和密度。这种定量信息可以帮助阐明月经周期和各种病理条件下免疫细胞群的动态变化。总体而言，通过免疫组化定量分析子宫内膜中免疫细胞的能力为了解子宫的免疫微环境提供了有价值的见解。
因此，该方案旨在开发和验证一种数字免疫组化图像分析平台，以定量分析RM患者黄体中期的子宫内膜免疫细胞，包括uNK细胞、Tregs、巨噬细胞、DC和细胞毒性T细胞。
Protocol
研究内容和方案已通过深圳市中山泌尿外科医院研究伦理委员会的伦理审查和批准。参与研究的所有女性（20-40 岁）都对样本收集和使用提供了知情同意。 1.病理组织的获取 准备用于组织采集的工具，即测量尺、镊子、包埋盒、包埋纸和纸巾篮。 观察使用移液管的标准方法收集的子宫内膜组织（比绿豆大）的数量是否足够。 用镊子将福尔?…
Representative Results
为了定量评估子宫内膜免疫细胞，减少人为操作失误带来的不稳定性，利用免疫组化自动检测和数字定量评价系统，建立了子宫内膜免疫细胞数字化定量分析平台。建立免疫组化图像分析平台，定量分析复发性流产（RM）患者植入窗口期的子宫内膜免疫细胞。所有子宫内膜组织均在月经周期的黄体中期收集。将石蜡包埋的子宫内膜组织切片成4 μm厚的载玻片，进行IHC染色检测子宫内膜免疫细胞，包…
Discussion
该协议建立了数字免疫组化图像分析平台，以定量分析RM患者的子宫内膜免疫细胞。在这里，检测了六种子宫内膜免疫标志物，以评估RM患者的子宫内膜免疫微环境。
黄体中期的接受性子宫内膜是成功植入和怀孕的关键27,28。因此，评估子宫内膜免疫细胞百分比在估计子宫内膜容受性方面起着重要作用。通过传统的病理学方法进行子…
Divulgazioni
The authors have nothing to disclose.
Acknowledgements
作者感谢所有同意并为这项研究捐赠样本的女性。
Materials
| Automated coverslipper | Sakuraus | DRS-Prisma-P-JCS&Film-JC2 | |
| CD163 | GrowGn Biotechnology | NCL-L-CD163 | |
| CD1a | Gene Tech | GM357129 | |
| CD56 | Gene Tech | GT200529 | |
| CD8 | Novocastra | NCL-L-CD8-4B11 | |
| Dehydrator | Thermo Fisher | Excelsior ES | |
| Digital pathology and | Indica labs | HALO | |
| Foxp3 | YILIFANG biological | 14-477-82 | |
| IHC stainer | Leica | BOND III | |
| Image analysis platform | Indica labs | HALO | |
| Slide Scanner | Olympus life science | VS200 |
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Citazione di questo articolo
Chen, C., Huang, C., Wu, Y., Li, Z., Yu, S., Chen, X., Lian, R., Lin, R., Diao, L., Zeng, Y., Li, Y. Platform for Quantitative Detection of Endometrial Immune Cells Based on Immunohistochemistry and Digital Image Analysis. J. Vis. Exp. (200), e65643, doi:10.3791/65643 (2023).