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Biology

Platform for Quantitative Detection of Endometrial Immune Cells Based on Immunohistochemistry and Digital Image Analysis

Published: October 13, 2023 doi: 10.3791/65643
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1, 1,2, 1, 1, 1, 1, 1, 1, 1,2, 1,2, 1,2
1Shenzhen Key Laboratory of Reproductive Immunology for Peri-implantation, Shenzhen Zhongshan Institute for Reproduction and Genetics, Fertility Center, Shenzhen Zhongshan Urology Hospital, 2Shenzhen Jinxin Medical Technology Innovation Center, Co., Ltd.

Summary

Here, a digital immunohistochemistry image analysis platform was developed and validated to quantitatively analyze the endometrial immune cells of patients with recurrent miscarriages in the window of implantation.

Abstract

To evaluate the endometrial immune microenvironment of patients with recurrent miscarriage (RM), a digital immunohistochemistry image analysis platform was developed and validated to quantitatively analyze endometrial immune cells during the mid-luteal phase. All endometrium samples were collected during the mid-luteal phase of the menstrual cycle. Paraffin-embedded endometrial tissues were sectioned into 4 µm thick slides, and immunohistochemistry (IHC)staining was carried out for detecting endometrial immune cells, including CD56+ uNK cells, Foxp3+ Tregs, CD163+ M2 macrophages, CD1a+ DCs, and CD8+ T cells. The panoramic slides were scanned using a digital slide scanner and a commercial image analysis system was used for quantitative analysis. The percentage of endometrial immune cells was calculated by dividing the number of immune cells in the total endometrial cells. Using the commercial image analysis system, quantitative evaluation of endometrial immune cells, which are difficult or impossible to analyze with conventional image analysis, could be easily, and accurately analyzed. This methodology can be applied to quantitatively characterize the endometrium microenvironment, including interaction between immune cells, and its heterogeneity for different reproductive failure patients. The platform for quantitative evaluation of endometrial immune cells may be of important clinical significance for the diagnosis and treatment of RM patients.

Introduction

Recurrent miscarriage (RM) is the loss of two or more consecutive pregnancies and is a complex disease drawing attention from clinicians in recent years.The incidence rate of RM in women of childbearing age is 1%-5% 1. Results of previous studies show that immune factors are closely associated with the pathogenesis of RM2,3,4,5. Maintaining immune homeostasis at the maternal-fetal interface is required for embryo implantation and development. Endometrial immune cells perform several regulatory roles to maintain this homeostasis, such as promoting trophoblast invasion, remodeling spiral arteries, and contributing to placenta development6,7,8,9.

Aberrant endometrial immune cells in women with RM have previously been reported. Results show a close association between the high density of uterine natural killer cells (uNKs) and the occurrence of RM10,11,12. An increased number of macrophages has been reported in the endometrium of women with RM, compared with those who had a live birth13. Regulatory T cells (Treg) play a role in maternal immune tolerance toward the embryo, and their level and function are decreased in the decidua of RM patients14. Cytotoxicity T cells (CTL) and dendritic cells (DCs) also play a role in the immune regulation of pregnancy15,16. Therefore, a comprehensive quantitative analysis of local endometrial immune cells during the mid-luteal phase could help to better understand the pathogenesis of RM. Some current methods for quantitative analysis of endometrial immune cells use flow cytometry which can accurately label immune cells with multiple markers17,18. However, clinical application of flow cytometry is limited because it can only be performed on fresh tissue. Obtaining fresh tissue is only feasible when a large volume of excess tumor is available, a rare occurrence for endometrium. Immunohistochemistry can observe tissue morphology well in situ and can also label various immune cells, while traditional immunohistochemical techniques cannot perform quantitative analysis of immune cells.

Compared to conventional immunohistochemistry experiments, quantitative immunohistochemical analysis of immune cells in the endometrium has important clinical significance. IHC intensity scoring is usually ranked on a four-point scale or strong and weak in pathological diagnostics and research19,20,21. However, this semi-quantitative technique is subjective, highly inaccurate, and demonstrates significant intra-observer and inter-observer variability22. One possible solution is the application of machine learning, which is valuable indigital image analysis23,24. By providing quantitative measurements, this approach enables a more precise assessment of immune cell infiltration, distribution, and density within the uterine tissue. This quantitative information can help to elucidate the dynamic changes in immune cell populations during the menstrual cycle and in various pathological conditions. Overall, the ability to quantitatively analyze immune cells in the endometrium through immunohistochemistry offers valuable insights into the immune microenvironment of the uterus.

Therefore, the protocol aimed to developed and validated a digital immunohistochemistry image analysis platform to quantitatively analyze endometrial immune cells including uNK cells, Tregs, macrophages, DCs and cytotoxic T cells during the mid-luteal phase in RM patients.

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Protocol

The research content and protocol has been ethically reviewed and approved by the research ethics committee of Shenzhen Zhongshan Urology Hospital. All women (20- 40 years old) involved in the study provided informed consent for sample collection and usage.

1. Acquisition of pathological tissue

  1. Prepare the tools for tissue harvesting namely, measuring ruler, tweezer, embedding cassette, embedding paper, and tissue basket.
  2. Observe whether the amount of endometrial tissue (bigger than a mung bean), collected using a standard approach with a pipelle catheter, is sufficient.
  3. Transfer the endometrial tissue from formalin onto the embedding paper with tweezer and measure the endometrial tissue dimensions with a ruler.
  4. Wrap the endometrial tissue with embedding paper and place in an embedding cassette.
  5. Place the embedding cassette into the tissue basket for dehydration.

2. Tissue dehydration

  1. Put the tissue basket into the reaction chamber of the dehydrator (see Table of Materials) and start the procedure for routine tissue dehydration: formalin for 100 min; formalin for 100 min; 75% alcohol for 60 min; 85% alcohol for 60 min; 95% alcohol for 60 min; 100% alcohol for 60 min; 100% alcohol for 60 min; 100% alcohol for 60 min; xylene for 35 min; xylene for 20 min; xylene for 20 min; wax for 80 min; wax for 80 min; wax for 80 min. The process takes about 15 h.
  2. At the end of the tissue dehydration procedure, open the reaction chamber of the dehydrator, remove the tissue basket.

3. Tissue embedding

  1. Take out a suitable embedding mold according to the size of the specimen, and fill with paraffin wax at 70 ° C.
  2. Quickly place the tissue into the mold and carefully adjust so that the tissue is located in the center of the mold.
  3. Move the mold smoothly to the cooling plate and gently press the tissue while the paraffin at the bottom sets.
  4. Put embedding cassette on top of the mold and top up with more wax.
  5. Place the mold on the cooling plate, and when the paraffin is completely solidified, remove the block with its attached cassette away from the mold.

4. Tissue sections

  1. Insert the block on the sample clip of the microtome, place the blade in the holder, adjust the angle between the plane of block and the blade, adjust the thickness of the section to 4 µm, turn the hand wheel, and start the slicing.
  2. Expose the appropriate tissue surface by cutting a few thin sections from the block. Take the continuous and complete sections out with the brush.
  3. When enough sections are cut, stop turning the hand wheel, remove the unqualified sections at the front end with tweezers, and float the sections on the surface of 42 °C water in the water bath with tweezers and brush.
  4. After the sections are fully flattened out, pick the sections on anti-detachment slides and transfer to a slide warmer at 65 °C to bake for 60 min.
  5. When the baking is finished, take the glass slides out from the slide warmer.

5. Immunohistochemical staining

  1. Dilute the primary antibody into a working solution with antibody diluent. See Table 1 for details.
  2. Put the diluted antibody solution into a special reagent bottle and the detection kit into the reagent compartment of an automatic IHC staining instrument (see Table of Materials).
  3. Place the slides on a slide holder, covered with a special covertile, and insert them into the experimental reaction compartment of the instrument.
  4. After the instrument automatically recognizes the reagent and experimental information on the slide, click the Start button to start the immunohistochemical staining. The experiment lasts for about 3 h.

6. Dehydration and sealing of the slide

  1. After immunohistochemical staining, take out the slide holder, take off the special covertile, put the stained slide into the slide holder, and wash off the remaining dye on the slide with clean water.
  2. Transfer the slide holder to an automated coverslipper (see Table of Materials), select and run the dehydration and sealing procedure.
  3. Take out the slides after dehydration and sealing.

7. Scanning slide

  1. Put the slides on the slide rack of the panoramic pathological image scanner (see Table of Materials) and place it in the instrument slide scanning compartment for panoramic pathological image scanning. The scanning takes 2 min. See Figure 1.

8. Analysis of images

  1. Import image
    1. Open the pathological image analysis software (see Table of Materials) and create a new folder. Import immunohistochemical images to be analyzed.
  2. Build a tissue classifier
    1. Mark several tissues and blank annotation to train and establish a classifier for identifying the tissue and blank area, respectively.
    2. Use real-time tuning to observe the recognition capacity of the software in real time during mark annotation. If the recognition is not timely, remark annotation and train again until the tissue recognition is accurate.
  3. Build analysis algorithm
    1. Select the standard algorithm in the software according to the type of experiment: multiplex IHC.
    2. Set the color parameters of cell recognition by selecting typical negative and positive pixel.
      On this basis, set the parameters of nucleus, cytoplasm, and cell membrane, and observe the cell recognition situation in real time until the most suitable parameters for the image have found.
    3. Set the positive cell recognition threshold and observe the recognition situation in real time until the appropriate threshold is adjusted.
    4. Select the tissue classifier in the algorithm, and check the tissue part in the tissue classifier, so as to identify cells on the basis of tissues. At this point, the establishment of an analysis algorithm is completed.
  4. Run image analysis
    1. Select the analysis area. Use the established algorithm to analyze images.
  5. After the software analysis has finished analyzing, manually check whether the image recognition is accurate, including tissue recognition, negative and positive cell recognition.
  6. If the image recognition is not accurate, adjust the algorithm and parameter threshold again, and rerun image analysis until success. Export the results of the analysis. See Figure 1.
  7. Other immune cells can also be analyzed according to the above steps (see Figure 1). Set different analysis parameters according to the actual expression of different endometrial immune markers (CD56+uNK cells, Foxp3+Tregs, CD68+ macrophages, CD163+M2 macrophages, CD1a+DCs and CD8+T cells25,26).
  8. Through the calculation of the software, obtain the proportion of endometrial immune cells (see Table 2). Use this to evaluate the levels of various immune cells in the endometrium of patients with recurrent miscarriage.

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Representative Results

In order to evaluate endometrial immune cells quantitatively and reduce the instability caused by man-made operational mistakes, we established a digital quantitative analysis platform for endometrial immune cells by using automatic immunohistochemical detection and digital quantitative evaluation system. Immunohistochemistry image analysis platform was established to quantitatively analyze endometrial immune cells of patients with recurrent miscarriage (RM) in the window of implantation. All endometrium tissues were collected during the mid-luteal phase of the menstrual cycle. Paraffin-embedded endometrial tissues were sectioned into 4 µm thick slides, and IHC staining was carried out for detecting endometrial immune cells, including CD56+uNK cells, Foxp3+Tregs, CD163+M2 macrophages, CD1a+ DCs, and CD8+ T cells. The panoramic slides were scanned using the digital slide scanner, and quantitative analysis was performed using a digital image analysis system. For calculating the percentage of endometrial immune cells, divide the number of immune cells by the total number of endometrial cells. (Figure 1 and Figure 2). The proportion of different endometrial immune cells in women with RM (N=30) is shown in Table 2.

Figure 1
Figure 1: Schematic workflow for the analysis of mid-luteal endometrial immune cells. Collection of samples was done during the mid-luteal phase of the menstrual cycle, at 7-9 days after theluteinizing hormone (LH) surge. Fixation was done in 10% neutral buffered formalin for 4-6 h at room temperature, and then embedded in paraffin wax. IHC staining was performed for detection of immune cells in the endometrium during the mid-luteal phase, including CD56+uNK cells, Foxp3+Tregs, CD68+ macrophages, CD163+M2 macrophages, CD1a+DCs and CD8+T cells25,26. Tissues were scanned using a commercial scanner and quantitative analysis was performed using the immunohistochemistry image analysis system. Please click here to view a larger version of this figure.

Figure 2
Figure 2: Immunostaining of endometrial cells for identification of positive immune cells. Immunostaining of CD56+uNK cells, Foxp3+Tregs, CD68+ macrophages, CD163+M2 macrophages, CD1a+DCs and CD8+T cells in endometrium from RM patients. Brown represents positive immune cells and blue represents the nucleus. Please click here to view a larger version of this figure.

Primary antibody Clone Dilution
CD56 123C3 1/800
Foxp3 236A/E7 1/100
CD163 10D6 1/1200
CD1a 10 1/200
CD8 4B11 1/300

Table 1: Primary antibodies used during immunohistochemical staining. The table shows the clone and dilution of the primary antibodies.

Immune markers Median (%) Minimum (%) Maximum (%) Mean (%) 5th percentile (%) 95th percentile (%)
CD56 4.83 1.8 16.76 6.03 2.04 13.63
Foxp3 0.05 0.02 0.12 0.06 0.02 0.11
CD68 0.78 0.37 3.62 0.99 0.44 2.67
CD163 0.84 0.35 2.38 0.93 0.38 2.13
CD1a 0.04 0.01 0.11 0.05 0.01 0.1
CD8 1.69 0.76 4.1 1.85 0.81 3.72

Table 2: Percentage of various endometrial immune cells in women with RM. The percentage of CD56+uNK cells, Foxp3+Tregs, CD68+ macrophages, CD163+M2 macrophages, CD1a+DCs and CD8+T cells in RM patients was calculated by immunohistochemistry image analysis platform.

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Discussion

This protocol established a digital immunohistochemistry image analysis platform to quantitatively analyze endometrial immune cells of RM patients. Here, six endometrial immune markers were detected to evaluate the endometrial immune microenvironment in RM patients.

A receptive endometrium during the mid-luteal phase is key for successful implantation and pregnancy27,28. Therefore, evaluation of percent endometrial immune cells plays an important role in estimating endometrial receptivity. Endometrial immune cells analysis, by conventional pathologic methods, is predictive so it does not help in clinical application. At present, there is no standardized method for the measurement of immune cell percentage which poses a barrier to understanding the role of these cells in pregnancy. Conventional IHC analysis is based on selected visual fields and manual counting. Precise tissue segmentation and localization of immune cells cannot be evaluated with conventional IHC because manual analysis is subjective leading to observer bias29.

Compared to analysis of the distribution of immune cells in the selected field, panoramic analysis of tissues is more accurate for analyzing the distribution of endometrial immune cells. Digital pathology approaches that utilize machine-based learning algorithms have been tested in multiple tumors to evaluate large tissue areas and complex cell phenotypes30,31. In the present study, a commercial system was introduced for obtaining a panoramic image of endometrium samples. The percentage of endometrial immune cells was subsequently determined using an automated quantitative analysis based on the immunohistochemistry image analysis system.

The immunohistochemistry image analysis system used here is an image analysis platform specialized for pathological tissues, which enables tissue segmentation by using artificial intelligence. Many studies using various modules with this system have been reported32,33,34. The system was used to quantify various histopathological changes and findings that were difficult to analyze using conventional image processing software. For example, the number of CD56+NK cells account for about 5% of the total cells in the endometrium during the mid-luteal phase. Traditional immunohistochemical analysis is difficult to accurately calculate the number of CD56+ NK cells, and it may take at least 30 min to calculate the total number of positive cells on the whole section, but it takes 2-3 min with the system used here. Therefore, using the immunohistochemistry image analysis system used here, endometrial immune cells could be easily, and accurately analyzed. Quantification of pathological findings by image analysis can contribute to improving objectivity, precision, and persuasiveness of endometrial immune environment evaluation.

However, there is a limitation of the described method. Endometrium consists of various immunocytes that have an association with pregnancy outcome. Therefore, defining only one or two immune markers might be insufficient. Hence, multiparametric approaches are needed to comprehensively assess immune profiling of cells.

In summary, it can be concluded that this protocol has successfully applied digital image analysis in endometrial sections during mid-luteal phase of RM patients for the quantification of immune cells and panoramic analysis was conducted in the present study to determine the distribution of endometrial CD56+ uNKs, Foxp3+Tregs, CD68+ macrophages, CD163+ M2 macrophages, CD1a+ iDCs and CD8+T cells during the mid-luteal phase. More evidence is required to support the association between endometrial immune cells with pregnancy outcomes of patients with RM and future studies will focus on this. This was the first study that investigated endometrial immune environment in RM patients using digital pathology.

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Disclosures

The authors have nothing to disclose.

Acknowledgments

The authors are grateful to all women who consented and donated samples for this study.

Materials

Name Company Catalog Number Comments
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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Tags

Endometrial Immune Cells Immunohistochemistry Digital Image Analysis Recurrent Miscarriage Mid-luteal Phase Endometrial Tissues CD56+ UNK Cells Foxp3+ Tregs CD163+ M2 Macrophages CD1a+ DCs CD8+ T Cells Quantitative Analysis Commercial Image Analysis System Reproductive Failure Patients
Platform for Quantitative Detection of Endometrial Immune Cells Based on Immunohistochemistry and Digital Image Analysis
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Cite this Article

Chen, C., Huang, C., Wu, Y., Li, Z., … More

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).

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