High-Content Screening Assay for the Identification of Antibody-Dependent Cellular Cytotoxicity Modifying Compounds

Summary

This protocol presents an automated, image-based high-throughput technique to identify compounds modulating natural killer cell-mediated breast cancer cell killing in the presence of a therapeutic anti-HER-2 antibody.

Abstract

Immunotherapy with antigen-specific antibodies or immune checkpoint inhibitors has revolutionized the therapy of breast cancer. Breast cancer cells expressing the epidermal growth factor receptor HER2 can be targeted by the anti-HER-2 antibody trastuzumab. Antibody-dependent cellular cytotoxicity (ADCC) is an important mechanism implicated in the antitumor action of HER-2. Trastuzumab bound to cancer cells can be recognized by the Fc receptors of ADCC effector cells (e.g., natural killer (NK) cells, macrophages, and granulocytes), triggering the cytotoxic activity of these immune cells leading to cancer cell death. We set out to develop an image-based assay for the quantification of ADCC to identify novel ADCC modulator compounds by high-content screening. In the assay, HER2 overexpressing JIMT-1 breast cancer cells are co-cultured with NK-92 cells in the presence of trastuzumab, and target cell death is quantified by automated microscopy and quantitative image analysis. Target cells are distinguished from effector cells based on their EGFP fluorescence. We show how compound libraries can be tested in the assay to identify ADCC modulator drugs. For this purpose, a compound library test plate was set up using randomly selected fine chemicals off the lab shelf. Three microtubule destabilizing compounds (colchicine, vincristine, podophyllotoxin) expected to interfere with NK cell migration and degranulation were also included in the test library. The test screen identified all three positive control compounds as hits proving the suitability of the method to identify ADCC-modifying drugs in a chemical library. With this assay, compound library screens can be performed to identify ADCC-enhancing compounds that could be used as adjuvant therapeutic agents for the treatment of patients receiving anticancer immunotherapies. In addition, the method can also be used to identify any undesirable ADCC-inhibiting side effects of therapeutic drugs taken by cancer patients for different indications.

Introduction

Immunotherapy with anticancer antibodies, immune checkpoint inhibitors, or chimeric antigen receptor-expressing T (CAR-T) cells represents a powerful approach to cancer treatment^1,2,3. Trastuzumab is a humanized monoclonal anti-HER-2 (human epidermal growth factor receptor 2) antibody used for treating HER-2 positive early stage or metastatic breast cancer, as well as HER-2 positive metastatic gastric cancer^4,5,6. It primarily acts by inhibiting the proliferation stimulating effect of the epidermal growth factor⁴. It has been reported, however, that trastuzumab efficiently triggers cancer cell death even if the cancer cells have lost their responsiveness to HER-2 stimulation⁷. This paradoxical effect of the antibody is due to antibody-dependent cell-mediated cytotoxicity (ADCC)⁷. ADCC can be mediated by natural killer (NK) cells, granulocytes, and macrophages collectively known as the effector cells of ADCC^8,9. If an antibody, such as trastuzumab, binds to tumor cells, then these effector cells use their Fc receptors to bind the constant (Fc) region of the antibody. The antibody bridges the tumor cells and the Fc receptor-bearing effector cells, triggering the release of their cytotoxic mediators¹⁰. Natural killer cells release the cytotoxic cargo of their granules containing perforin to generate pores in the target cell membrane and granzyme (triggering cell death signaling pathways) into the immune synapse leading to apoptosis of the cancer cells (see Figure 1).

Figure 1: Effector and target cell interactions in ADCC. The cell surface Fcγ receptor of the effector NK cell recognizes the Fc region of the anti-HER2 trastuzumab antibody specific for the HER2 molecule expressed on the surface of the tumor cell. Thus, the so-called immunological synapse is established between the two cells, inducing the directed exocytosis of cytotoxic granules of the effector cell. The released perforin and granzyme molecules eventually result in apoptosis of the target cell. Please click here to view a larger version of this figure.

Several assays have previously been developed to quantify cytotoxicity, including ADCC. The gold standard is the radioactive chromium release method, where the target cells are labeled with radioactive ⁵¹Cr isotope, and ADCC is quantified by measuring radioactivity from the supernatant of lysed target cells¹¹. Because of the obvious problems due to the strictly regulated handling, storage, and disposal of radioactive pharmacons and wastes, this method has become increasingly non-popular among life scientists. In addition, it is not amenable to high-throughput applications either. Measuring the activity of enzymes (e.g., lactate-dehydrogenase) released from the killed target cells can provide a non-radioactive alternative to the ⁵¹Cr assay¹². These assays, however, fail to distinguish between target and effector cell deaths. Electric Cell-substrate Impedance Sensing (ECIS) proved suitable for the quantification of ADCC¹³, but the ECIS equipment is not available in most laboratories, and the technique is not compatible with high-throughput applications/screening. Fluorescently labeled cells represent a popular alternative in many cell biology assays and are often used in flow cytometry or plate reader-based applications^14,15,16. However, these assays often contain washing steps or are otherwise incompatible with high-throughput applications (e.g., flow cytometry-based techniques). Some popular cytotoxicity assays, which in theory should be suitable for ADCC quantification, fail to reliably determine ADCC efficiency¹³. Recently, with the spreading of fluorescent confocal microscopy, image-based, high-content assays are becoming increasingly popular in various areas of life sciences¹⁷. On the one hand, cell imaging equipment are now rather ubiquitous, while, on the other hand, virtually endless morphological parameters can be gathered from the acquired images. Therefore, we set out to develop a high-content screening compatible ADCC assay and to demonstrate its suitability for compound library screening.

Here, we present an image-based ADCC assay and demonstrate how this assay can be used for High-Content Screening (HCS) to identify ADCC modulating compounds. The model is based on JIMT-1 breast carcinoma target cells, CD16.176V.NK-92 effector cells and the humanized monoclonal anti-HER2 antibody trastuzumab. With this method, it is possible to identify drugs that can enhance the tumor-killing action of NK cells or to gain insight into the mechanism of NK cell-mediated ADCC by identifying small molecules interfering with ADCC. We suggest that life scientists aiming to quantify cell-mediated cytotoxicity with special regard to ADCC may benefit from using this assay either for the discovery science or drug development. This assay may be an alternative if a laboratory has access to and some experience in fluorescent imaging and quantitative image analysis.

Protocol

NOTE: Key steps of the assay workflow are presented in Figure 2.

Figure 2: Workflow of the ADCC screen. JIMT-1-EGFP target cells seeded into 96 well HCS plates are treated with drugs of the compound library. In turn, unstained NK (effector) cells and trastuzumab are added, and the plate is imaged at 0 timepoint and after 3 h of incubation. ADCC evaluation is based on the change in the number of viable (surface adherent) target cells. Please click here to view a larger version of this figure.

1. Coating of the HCS plate

1. Coat the 96 well high-content screening (HSC) plates with 50 µL/well JIMT-1 medium (DMEM/F-12 medium supplemented with 20% fetal bovine serum (FBS), 0.3 U/mL insulin (100 IU/mL, Humulin R, and 1% penicillin-streptomycin).
2. Place the plate into a CO₂ incubator for 1 h.
   ​NOTE: Coating is crucial for attaching JIMT-1 cells to the glass surface of the plate.

2. Seeding of JIMT-1 Enhanced Green Fluorescent Protein (EGFP) cells

NOTE: EGFP-expressing JIMT-1 cells were generated in our previous work¹⁸, and the cells were cultured in T25 tissue culture flasks in JIMT-1 media (see composition in step 1.1).

1. Wash the cells with 2 mL of sterile PBS.
2. Add 1 mL of trypsin-EDTA to the flask and put the flask back into a CO₂ incubator for 10 min.
3. After the incubation, tap the flask to check if JIMT-1 cells are detached.
4. Stop the digestion with 2 mL of JIMT-1 media and collect the cell suspension into a 15 mL tube.
5. Count the cells with 0.4% trypan blue (80 µL of the dye + 20 µL of the cell suspension) in a Bürker chamber and adjust the cell number to 133, 000 cells/mL.
6. Aspirate the coating medium from the 96 well plate (step 1.2).
7. Pipette 75 µL of the cell suspension to each well of the HCS plates (see Table of Materials).
8. Allow cells to attach during an overnight incubation at 37 °C in a CO₂ incubator.

3. Pre-treatment of JIMT-1 EGFP cells with the compound library

1. Aspirate the medium from the JIMT-1 cells and add 50 µL/well fresh JIMT-1 medium to the wells. Transfer the plate to the high-throughput screening laboratory.
   NOTE: Using a liquid handling robot makes the addition of compound libraries more efficient and reproducible.
2. Transfer the test compounds from the compound library plate to the assay plate with a pin tool calibrated to a 25 nL volume. Perform this four times. Four rounds of transfer give a final volume of 100 nL (and a 20 µM final concentration).
3. Between each step, wash the pin tool, first with 50% DMSO and then with 70% ethanol.
4. Incubate the plates for 1 h in a CO₂ incubator at 37 °C.

4. Starting the ADCC assay by adding the effector cells

NOTE: CD16.176V.NK92 cells (hereafter referred to as NK92 cells) were cultured in α-MEM supplemented with 20% FBS, 1% MEM-NEAA, 1% Na-pyruvate, 1% glutamine, 1% penicillin-streptomycin and 100 IU/mL IL-2.

1. Count NK92 cells with trypan blue (80 µL of the dye + 20 µL of the cell suspension). Adjust the cell number to 400,000 cells/mL.
2. Centrifuge 4 mL of the cell suspension at 150 x g for 3 min at room temperature.
3. Prepare the ADCC medium by adding 20 µg/mL anti-HER2 antibody (trastuzumab) to the JIMT-1 medium.
4. Resuspend the NK cell pellet in 5 mL ADCC medium.
5. Pipette 20,000 NK cells in 50 µL of ADCC medium to the target JIMT-1 cells. The final volume is 100 µL, and the final trastuzumab concentration is 10 µg/mL.
6. Place the assay plate into the high-content analysis equipment with a built-in incubator set at 37 °C.

5. Imaging

NOTE: The plates should be imaged at two time points, first, immediately after the addition of the effector cells to the target cells and second, at 3 h after the addition of NK cells. For imaging, the high-content analyzer and its software or suitable alternatives can be used (see Table of materials).

1. Select Plate type (96-well cell carrier ultra) from the list of plates.
2. Select the Two peak autofocus if the assay is carried out in plates.
3. Use 10x objective in non-confocal mode.
4. Select Binning 2 to double the signal to noise ratio.
5. Take brightfield images at 650-760 nm and fluorescent images of the EGFP-transduced JIMT-1 cells at 488 nm (excitation) and 500-550 nm (emission) wavelengths.
6. Select the number of fields and the number of timepoints for the imaging.

6. Image analysis

NOTE: To analyze the ADCC efficiency, the viable JIMT-1 cells are counted. Target cells killed by ADCC detach from the surface and move away from the focal plane of the microscope. Therefore, the difference between the number of viable cells at the beginning and at the end of the ADCC reaction corresponds to target cells eliminated by ADCC. To show how to build up the evaluation sequence, a control ADCC well is shown in the video.

1. Use the Find cells module to detect regions on the image that correspond to cells.
   NOTE: Each cell is detected as a region on the image with a higher fluorescence intensity than its surrounding.
2. Select cells using the built-in M algorithm with a minimum of 80 µm in diameter.
3. Set Splitting sensitivity, which parcels out a large object into smaller objects, to 0.5.
4. Set the Common threshold (the lowest level of pixel intensity) to 0.
5. Exclude the detection of background area with high EGFP fluorescence intensity in two steps.
   1. First, use the Calculate Intensity Properties function to determine the EGFP fluorescence intensity in the previously selected Cells region.
   2. Set the minimum and maximum intensity threshold using the Select population option.

Results

To demonstrate how the assay works in real life, we created a test library of 16 compounds selected randomly from the lab shelves (Figure 3). In addition, DMSO was also included as a negative control, and three microtubule polymerization inhibitor compounds (colchicine, vincristine, and podophyllotoxin) as positive controls. The latter were expected to inhibit ADCC by interfering with NK cell migration to the cancer cells and NK cell degranulation. All test compounds and DMSO were placed ont...

Discussion

The ADCC reaction has been described a relatively long time ago. Key molecular events of the process have also been described¹⁹. Methods for measuring ADCC range from the gold standard radioactive chromium release assay, cytoplasmic enzyme release assays to several fluorescence-based flow cytometry or microplate assays²⁰. However, a common limitation of these assays is that they are not amenable to high-throughput applications. Previously, we developed an image-based HCS as...

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
5-fluorouracil	Applichem	A7686	in compound library
96-well Cell Carrier Ultra plate	PerkinElmer	LLC 6055302
Betulin	Sigma	B9757	in compound library
CD16.176V.NK92 cells	Nankwest Inc.
Cerulenin	ChemCruz	sc-396822	in compound library
Cisplatin	Santa Cruz Biotechnology	sc-200896	in compound library
Colchicine	Sigma	C9754	in compound library
Concanavalin-A	Calbiochem	234567	in compound library
Dexamethasone	Sigma	D4902	in compound library
DMEM/F-12 medium	Sigma	D8437	in JIMT-1 EGFP medium
DMSO	Sigma	D2650	in compound library
Etoposide	Sigma	E1383	E1383
Fetal bovine serum (FBS)	Biosera	FB-1090/500	JIMT-1 EGFP and NK medium
Fisetin	Sigma	F4043	in compound library
Freedom EVO liquid handling robot	TECAN
Gallotannin	Fluka Chemical Corp.	16201	in compound library
Glutamine	Gibco	35,050–061	in NK medium
Harmony software	PerkinElmer
Humanized anti-HER2 monoclonal antibody (Herzuma)	EGIS Pharmaceuticals, Budapest Hungary	N/A
Humulin R (insulin)	Eli Lilly	HI0219	JIMT-1 EGFP medium
IL-2	Novartis Hungária Kft.	PHC0026	in NK medium
Isatin	Sigma	114618	in compound library
MEM Non-essential Amino Acids (MEM-NEAA)	Gibco	11,140–050	in NK medium
Na-pyruvate	Lonza	BE13-115E	in NK medium
Naringenin	Sigma	N5893	in compound library
NQDI-1	Sigma	SML0185	in compound library
Opera Phenix High-Content Analysis equipment	PerkinElmer
Penicillin–streptomycin	Biosera	LM-A4118	JIMT-1 EGFP and NK medium
Pentoxyfilline	Sigma	P1784	in compound library
Phosphate buffered saline (PBS)	Lonza	BE17-517Q	to wash the cells
Podophyllotoxin	Sigma	P4405	in compound library
Quercetin	Sigma	Q4951	in compound library
Tannic acid	Sigma	T8406	in compound library
Temozolomide	Sigma	T2577	in compound library
Trypan blue 0.4% solution	Sigma	T8154	for cell counting
Vincristine sulfate	Sigma	V0400000	in compound library
α-MEM	Sigma	M8042	in NK medium