In vitro assays for investigating the immunomodulatory properties of human mesenchymal stromal cells

Abstract

Mesenchymal stromal cells (MSCs) are widely recognized for their immunomodulatory properties, which underpin their therapeutic potential in inflammatory and immune-mediated diseases. Although MSC therapies have consistently proven safe, clinical efficacy remains inconclusive, maybe due to incomplete understanding of MSC interactions with the immune environment. This review evaluates current trends in MSC immunomodulation research, based on 318 studies published since 2019 until medio 2024. The most frequently used assays included characterization, proliferation, and polarization, employing methods such as flow cytometry, enzyme-linked immunosorbent assays and colorimetric assays, and polymerase chain reaction. Many studies incorporated strategies for priming of MSCs or included immune cells, most commonly peripheral blood mononuclear cells, T cells, and macrophages. We identify key sources of variability and propose a minimum reporting checklist including MSC source, priming conditions, assay design, and immune cell characteristics. We further recommend implementation of multi-assay workflows combining phenotypic characterization with at least one functional assay. These measures may improve transparency, comparability across studies, and guide robust assay design.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13287-026-04920-x.

Background

Mesenchymal stromal cells (MSCs) were previously coveted for their role in tissue homeostasis and maintenance of the stem cell niche, because of their ability to differentiate into various cell types. Furthermore, an important biological property was thought to be their ability to sense and home to damaged tissue in the local environment. However, in recent years, the focus has shifted, and now the primary role of MSCs is thought to be as orchestrators of the immune response [1, 2]. Inflammation is a complex state characterized by interplay between pro- and anti-inflammatory cytokines that regulate activity of leucocytes and surrounding tissue and plays a vital role in many acute and chronic progressive diseases. Therefore, the ability to adequately regulate the immune response is crucial in disease development and progression, and as MSCs have both immunomodulatory and anti-inflammatory properties, there is increasing interest in exploring their therapeutic potential [3–10]. MSCs affect their environment through paracrine signalling and crosstalk with innate and adaptive immune cells, affecting numerous biological processes, e.g., enabling them to alter proliferation rate and polarization state. Thereby, they assist in maintaining homeostasis of the tissue environment [4, 11, 12]. Paracrine signalling is facilitated by the MSC secretome, which consists of soluble factors such as cytokines, chemokines, or growth factors as well as extracellular vesicles and apoptotic bodies [13, 14]. MSCs are highly dynamic and plastic cells that perform different functions depending on the environment to which they are exposed. They can trigger a response from the immune system in response to external stimuli, such as damage or infection, yet they can also respond to immune activation by becoming immunosuppressive, thereby preventing an excessive immune response [7, 11]. However, the exact mechanisms by which these functions are exerted remain unknown. Owing to their immunomodulatory properties, MSCs have been suggested as a novel therapy for numerous clinical indications [9, 11, 15–28]. Despite the large number of clinical trials in which MSC therapy has been proven safe, the results concerning its efficacy have been inconclusive, maybe due to the complexity of the interactions between the tissue environment of patients and MSCs, which are not yet fully understood [7, 17–19, 29]. Various assays have been used to explore different aspects of MSC characteristics, but currently, there is no consensus for the existing bioassays on either design nor endpoints and thereby variability is introduced. As such, the development of relevant assays following minimum reporting standards is crucial for advancing the understanding of MSCs in an immunological context. This review aims to evaluate current trends in types of assays used to assess the MSC immunomodulatory potential, identify key challenges, and serve as a guide for future research.

Methods

Inclusion criteria

The search string used medicinal subject headings and title-abstract terms to include papers on MSCs, immunomodulation, and bioassays or methods (Fig. 1A). The search was conducted on the 15th of August 2024 in both the Embase and PubMed (Medline) databases, followed by screening of titles and abstracts and subsequent full-text screening in Covidence, as shown in Fig. 1B.

Fig. 1.

Search strategy and PRISMA diagram. A Search string used to include studies. Both medicinal subject headings (Mesh) (in cursive) and title-abstract terms are included. Reviews and systematic reviews were excluded. Filtered to only include studies on human cells written in English in the 5 years prior to conducting the search (15aug2024). B PRISMA diagram illustrating the screening process. The search was conducted in both Embase and PubMed (Medline). First, duplicates were removed before the initial screening of the title and abstract by one reviewer. The full texts of the included articles were screened by two reviewers, and a third reviewer resolved conflicts, omitting those with no online access. Studies were included or excluded during full-text screening based on the listed inclusion or exclusion criteria. In total, 318 studies were included. The criteria for MSCs were as defined by the International Society for Cellular Therapy (ISCT) [30]. The categorization into types of assays was performed by the reviewers. The percentages reflect the distribution of type of assay in relation to the number of included studies

In brief, the included papers had to be original, peer-reviewed, written in English, and published since 2019 and until the search was conducted on 15aug2024. Furthermore, the MSCs must conform to the minimal criteria described by the International Society for Cellular Therapy (ISCT) [30], and both the MSCs and other included cells should be of human origin. The papers should describe an in vitro assay investigating the immunomodulatory functions of MSCs. In total, 318 papers were included based on the established inclusion criteria (Fig. 1B). Further analysis of the included assays was conducted using R extension for Visual Studio Code (version 2.8.6) in Visual Studio Code (version 1.103.1), employing packages readxl [31], tidyverse [32], openxlsx [33], viridis [34], igraph [35], intergraph [36], sna [37], GGally [38], ggalluvial [38], and UpSet [39]. The assays were divided into ten predefined categories depending on the investigated immunomodulatory effect of the MSCs (Fig. 1B). A complete overview can be seen in Table 1, and an overview of assay types used across the included studies is shown in Fig. 2. Most papers described multiple assays and/or used several analytical methods to illustrate the multifaceted nature of MSC function, and a mean of 2.7 assays per paper were included. Both alone and in combination with other assays, the most used assays where characterization, proliferation, and polarisation, while assays investigating cell death, inflammatory pathways, migration, and differentiation were only used in combination with other assays (Fig. 2).

Table 1.

Overview of the types of assays and methods used in the included assays

Type of assay	Included immune cells	Method	References
Characterization assays (61.6%)	No	PCR (22.8%)	[5, 8, 12, 16, 51, 52, 55, 62, 73, 75, 76, 78, 85, 89, 92, 102, 105, 112, 115, 118, 121, 123–129, 133, 157, 166, 170, 174, 175, 179, 181, 182, 186, 198, 214, 216, 217, 226, 227, 238–241, 243–245, 275–285][342-344]
		ELISA (16.5%)	[13, 52, 58, 63, 69, 74, 76, 88, 99, 107, 112, 121, 125, 128, 138, 143–[145, 159, 165, 166, 168, 181, 184, 196, 217, 222, 226–228, 231, 239–241, 243, 245, 247, 248, 251, 265, 268, 278, 279, 282–284, 286–294]
		Sequencing (13.2%)	[6, 10, 19, 55, 66, 69, 100, 107, 120, 127, 134–141, 147, 155, 161, 171, 172, 179, 181, 196–198, 217, 222, 236, 251, 269, 276, 279, 281, 283, 285, 290, 293, 295–297]
		Western blot (7.8%)	[15, 16, 62, 73, 74, 78, 92, 102, 115, 121, 127, 128, 133, 147, 157, 164, 171, 182, 186, 190, 226, 244, 245, 292, 298, 299]
		Luminex (7.2%)	[55, 57, 58, 106, 136, 138, 148–151, 164, 167, 180, 223, 226, 229, 236, 246, 276, 279, 289, 299–301]
		Flow cytometry (6.9%)	[12, 19, 66, 71, 77, 142, 152, 157, 159, 180, 182, 184, 221, 234, 238, 239, 247, 251, 282, 290, 302, 303]
		Mass spectrometry (3.3%)	[58, 87, 100, 109, 122, 130, 136, 148, 246, 250, 277]
		Colorimetric assay (2.7%)	[146, 162, 190, 228, 239, 241, 244, 248, 292]
		Microscopy (1.2%)	[102, 121, 128, 288]
		NMR spectroscopy (0.6%)	[246, 250]
	PBMC, Macrophages, T cells, Monocytes	ELISA (7.2%)	[45, 53, 68, 81, 89, 91, 95, 97, 109, 154–158, 174, 178, 192, 193, 201, 202, 208, 209, 225, 245]
	PBMC, Macrophages, T cells	PCR (5.1%)	[80– [83, 105, 109, 154, 156, 158–161, 176, 177, 193, 206, 304]
	PBMC, T cells, Monocytes, Glial cells	Luminex (1.8%)	[5, 42, 83, 173, 305, 306]
	PBMC, Macrophages	Flow cytometry (0.9%)	[154, 199, 210]
	PBMC, T cells	Sequencing (0.9%)	[156, 206, 207]
	T cells, PBMC	Western blot (0.9%)	[119, 210, 305]
	PBMC, T cells	Colorimetric assay (0.3%)	[85]
	Monocytes	Mass spectrometry (0.3%)	[209]
	PBMC	Microscopy (0.3%)	[210]
Proliferation (56.6%)	PBMC, T cells, B cells, NK cells	Flow cytometry (71.3%)	[3–5, 9, 13, 14, 17, 18, 29, 41–43, 45, 58, 62, 66, 71, 73, 77, 78, 81, 82, 85, 99, 114, 117, 120–122, 127, 131–135, 138, 139, 147, 149, 156, 157, 159, 160, 162, 163, 165, 167, 169–171, 175, 179, 182, 184–186, 190, 193, 194, 196, 197, 200, 203, 206, 207, 211, 214, 217, 218, 220, 221, 225, 227, 232–237, 239–242, 244–251, 253, 256, 257, 261, 263, 264, 267, 268, 271, 276–279, 282, 286, 289, 290, 294–296, 298, 302, 304, 307–324]
	PBMC, T cells, Macrophages	Colorimetric assay (17%)	[15, 16, 50, 59, 68, 73, 79, 83, 94, 99, 110, 119, 126, 142, 166, 168, 170, 198, 199, 201, 204, 205, 220, 231, 232, 251, 269, 284, 293, 325, 326]
	PBMC, T cells	Radiation-based assay (6.4%)	[69, 72, 107, 140, 141, 164, 255, 270, 299, 327–329]
	PBMC, T cells	ELISA (3.7%)	[70, 103, 140, 195, 219, 288, 330]
	Macrophages	Cell count (0.5%)	[154]
	PBMC	Live Cell Imaging (0.5%)	[188]
	Macrophages	Microscopy (0.5%)	[98]
Polarization (44.7%)	PBMC, T cells, Macrophages, Dendritic cells, Monocytes, B cells, Full blood	Flow cytometry (44.7%)	[3, 7, 11, 13, 14, 43, 44, 47–49, 53, 56, 58, 60, 64, 70, 78–81, 85, 88, 90, 97–99, 102–105, 112, 113, 122, 130, 132, 134, 140, 146, 151, 160–164, 169, 170, 174–178, 183, 187, 189, 191, 192, 201, 207, 211, 212, 218, 220, 225, 230, 237, 247, 254, 255, 259, 260, 266, 276, 279, 286, 290, 298, 301, 309, 316, 317, 319, 331–336]
	PBMC, Macrophages, T cells, B cells, NK cells, Dendritic cells, Monocytes	ELISA (25.9%)	[3, 13, 16, 19, 44, 58, 59, 64, 65, 70, 79, 80, 84, 90, 91, 94, 99, 100, 104, 105, 107, 108, 110, 111, 115–117, 120, 133, 147, 151, 178, 185, 199, 200, 207, 212, 218, 240, 249, 254, 259, 263, 268, 308, 322, 327, 335, 337–339]
	Macrophages, PBMC, T cells, Monocytes, NK cells, B cells	PCR (18.3%)	[19, 44, 46, 48, 61, 64, 65, 67, 68, 84–86, 89, 90, 92, 94, 100, 102–104, 110, 113, 114, 116, 118, 178, 187, 199, 218, 237, 239, 254, 266, 304, 325, 340]
	Macrophages, T cells, PBMC, Dendritic cells, B cells, Full blood	Luminex (6.6%)	[82, 87, 93, 101, 139, 206, 207, 257, 261, 319, 321, 331, 338]
	Macrophages, PBMC	Microscopy (1.5%)	[101, 325, 335]
	T cells	Colorimetric assay (1%)	[121, 341]
	Macrophages, T cells	Western blot (1%)	[335, 341]
	Macrophages, Monocytes	OLINK (0.5%)	[191]
	NK cells	Sequencing (0.5%)	[117]
Enzyme activity (10.4%)	No	Colorimetric assay (68.6%)	[15, 16, 63, 67, 70, 77, 100, 114, 168, 187, 203, 223, 238–248, 250]
		Mass spectrometry (5.7%)	[251, 252]
		Western blot (5.7%)	[231, 252]
	PBMC, T cells	Colorimetric assay (14.3%)	[45, 77, 80, 159, 249]
	T cells, NK cells	Mass spectrometry (5.7%)	[207, 253]
Endocytosis (6.9%)	Macrophages, PBMC, Neutrophils, Dendritic cells, Full blood, Monocytes, T cells	Flow cytometry (52.2%)	[13, 14, 87, 90, 113, 133, 185, 191, 249, 254–256]
	Macrophages, Neutrophils, T cells, PBMC	Microscopy (43.5%)	[96, 97, 103, 109, 133, 213, 215, 257–259]
	Macrophages	Live Cell Imaging (4.3%)	[260]
Cell death (6.6%)	No	Microscopy (4%)	[115]
		PCR (4%)	[54]
		Western blot (4%)	[54]
	PBMC, Neutrophils, Macrophages, T cells, B cells, NK cells	Flow cytometry (64%)	[46, 60, 99, 127, 140, 169, 185, 213, 215, 237, 245, 253, 258, 261–263]
	PBMC	Cell count (4%)	[74]
	T cells	Colorimetric assay (4%)	[121]
	PBMC	ELISA (4%)	[264]
	T cells	Microscopy (4%)	[261]
	T cells	PCR (4%)	[261]
	T cells	Western blot (4%)	[261]
Cytotoxicity (3.8%)	Neutrophils, NK cells, PBMC	Colorimetric assay (40%)	[118–120, 213, 215, 258]
	PBMC, T cells, NK cells	Flow cytometry (33.3%)	[40, 118, 120, 220, 227]
	PBMC	Cell count (6.7%)	[231]
	PBMC	Live Cell Imaging (6.7%)	[265]
	Neutrophils	Microscopy (6.7%)	[97]
	NK cells	Radiation-based assay (6.7%)	[40]
Migration (1.9%)	PBMC, Macrophages	Western blot (50%)	[88, 106]
	Monocytes, PBMC	Flow cytometry (18.2%)	[11, 58]
	Macrophages, Monocytes, PBMC	PCR (18.2%)	[11, 17]
	Macrophages, Monocytes	ELISA (9.1%)	[11]
	Neutrophils	Live Cell Imaging (9.1%)	[87]
	PBMC	Luminex (9.1%)	[17]
	Macrophages, Monocytes	Sequencing (9.1%)	[11]
	Macrophages, Monocytes	Western blot (9.1%)	[11]
Inflammatory pathways (1.9%)	No	Western blot (33.3%)	[170, 243]
		PCR (16.7%)	[152]
	PBMC, Macrophages	Western blot (50%)	[46, 93, 266]
Differentiation (0.3%)	Dendritic cells, Macrophages	PCR (100%)	[255]

The type of assay appears in order of most to least frequently described. Percentage of each type of assay is calculated based on total number of papers included. Assays not including immune cells are indicated by “No”, and the immune cells included are listed by frequency. Methods are listed for each type of assay from most to least frequently used

Fig. 2.

Overview of assay usage across the included studies. A Assay frequency and co-occurrence. UpSet plot showing which assay types are most commonly used (left) and how frequently specific combinations occur (top). The matrix highlights the composition of each combination. B Distribution of studies across combinations. Box heights indicate how many studies contain each assay combination, providing an overview of how heterogeneously studies cluster across the field. C Assay co-usage relationships. Network representation illustrating how assay types relate to each other based on co-usage patterns. Node size reflects overall frequency, and edge thickness indicates how often two assay types appear together

Variation in MSC sources

This review included papers that used MSCs isolated from 28 different tissues, the most common of which were bone marrow, adipose tissue, and the umbilical cord (Fig. 3A).

Fig. 3.

Overview of MSC tissue sources and immune cells. A Chart illustrating the tissue origin of MSCs across all included papers. MSCs were isolated from 28 different tissue sites. The “Other” category includes MSCs of tissue origins, which are described in only one paper. B Use of immune cells in coculture assays in the included papers. The chart does not discern between use of primary cells or cell lines. PBMC: Peripheral blood mononuclear cells, NK: Natural killer

These sources accounted for 80% of the included MSCs. While most studies used MSCs from healthy donors, cells were also isolated from patients with inflammatory diseases [7, 40–67] or diabetes [68, 69], or from isolated tumor tissue [70, 71]. In a few cases, MSCs were isolated from deceased donors [29, 72], and one paper used immortalized cell lines [73]. Comparative studies revealed that the immunomodulatory properties of MSCs can vary considerably, reflecting differences in tissue source [6, 16, 74–78], donor health status (e.g., healthy vs. inflammatory conditions) [57, 70], and donor age [79]. This wide heterogeneity in MSC origin represents a major challenge for interpreting and comparing results across studies, as differences in cell source may significantly influence functional outcomes [70, 77] and similarly, differences in the expression of immunosuppressive cytokines by MSC from different sources also contributes to assay results [76].

Interactions between MSCs and the immune system

Immune cells can be incorporated to create a proinflammatory environment, enabling inference of MSC modes of action in an immunological setting that closely resembles in vivo settings (see Supplementary Table 1). The most prevalently utilized immune cells were peripheral blood mononuclear cells (PBMCs), isolated T cells, and macrophages (Fig. 3B). PBMCs are a heterogeneous cell population containing lymphoid cells such as T cells, B cells, monocytes, and natural killer (NK) cells, hence representing a diverse immunological environment with which the MSC may interact [80–83]. They are easy and accessible tools relevant for studying various areas, e.g., the effects of MSCs on the imbalance between T helper (Th)1, Th2 and regulatory T cells (Tregs), which are present in many diseases [44, 64, 84–86]. Some studies used whole blood from healthy donors [87, 88], thus including all blood components. The results obtained from studies using heterogeneous cell populations can be complex to interpret. Hence, it may be more feasible to use isolated cells for investigating the immunomodulatory effects of MSCs, e.g., monocytes that can be differentiated into macrophages known to have specific immunological properties based on their polarization state or isolated T cells [44, 64, 84–86, 89–92]. However, physiological conditions such as inflammation are characterized by cellular interactions and may be better reflected by more complex culture systems. This reflects that researchers face a wide range of possible cell types that can be included depending on the objective and desired outcome of the assay. While most assays used primary immune cells, some relied on cell lines such as THP1 to mimic the functions of monocytes and macrophages [13, 14, 16, 67, 78, 91–116], NK92 cells for NK cells [117–120] and Jurkat cells for T cells [73, 94, 121, 122]. The advantages of cell lines include an unlimited supply of cells, which ensures consistency, ease of use, and reduced interexperimental variation, but their results may not always translate to primary cells. It is therefore recommended that findings be validated using primary cells [93, 107, 117].

Characterization assays

To understand the immunomodulatory properties of MSCs, their expression of genes and proteins can be characterized to elucidate both constitutive expression and how it is affected by priming or other treatments.

The immunomodulatory effects of untreated MSCs

MSCs are frequently associated with anti-inflammatory functions, as evidenced via the use of inflammatory gene and protein panels, which show constitutive expression of immunomodulatory markers. The expression of genes in untreated MSCs was analysed via reverse transcription quantitative PCR (qPCR) [51, 52, 121, 123–133] and sequencing [6, 107, 127, 134–141]. The protein contents of the untreated MSC secretome were determined by enzyme-linked immunosorbent assay (ELISA) [52, 74, 107, 121, 125, 138, 142–145] and other colorimetric assays [146], western blotting [74, 121, 127, 133, 147], Luminex [106, 136, 138, 148–151], mass spectrometry [122, 130, 136, 148], transmission electron microscopy [121], and flow cytometry [152]. It is important to explore the inherent expression patterns of MSCs to observe any changes or responses to other stimuli, such as priming, the presence of immune cells, a combination of these, or other types of treatment.

The immunomodulatory functions of primed MSCs

MSCs can be primed with biological or chemical factors with the purpose of enhancing or suppressing their immunological function (as reviewed in depth by Hezam, Fu [153]). In half of the included assays, the MSCs were primed, especially in assays with MSCs in monoculture. Moreover, the MSCs were primed in fewer than half of the assays that introduced immune cells, which included macrophages [95, 97, 105, 109, 154], PBMCs [5, 45, 85, 155–158], and T cells [45, 85, 159–161]. Since activated immune cells can enhance the immunomodulatory function of MSCs, the amplified effect achieved by priming may not be necessary in assays that already include activated immune cells, as these cells provide the necessary signals to enhance the MSCs regulatory capabilities. MSCs were mainly primed with proinflammatory cytokines such as interferon (IFN)-γ, tumor necrosis factor (TNF)-α, and interleukin (IL)-1β either alone or in combination. Other stimulants, including proinflammatory cytokines and toll-like receptor agonists, were used to explore the immunological functions of MSCs. An overview of the references that used each priming reagent is shown in Supplementary Table 2. By using priming to block or neutralize potential mediators of the immunomodulatory function of MSCs, their involvement and impact on the effect of MSCs can be confirmed [45, 54, 140, 162–165]. A range of priming reagents were used to investigate specific aims; for example, MSC immunomodulation was enhanced with hydrocortisone [166, 167] or dexamethasone [167–169] and inhibited with immune inhibitors such as infliximab [158], tacrolimus, or cyclosporin [72, 167], among others [157, 170, 171]. The methods used to quantify gene and protein expression levels after MSC priming included PCR and sequencing for gene expression and ELISA, flow cytometry, Luminex, western blotting, mass spectrometry, immunofluorescence microscopy, and nuclear magnetic resonance spectroscopy for protein analysis. A complete list of references supporting each method is shown in Supplementary Table 3.

The immunomodulatory function of MSCs treated with other components

The MSCs were treated with other substances to investigate the effects of other conditions on MSC functionality. These treatments were not always known as immunoregulators or –suppressors and were therefore not necessarily linked to the immunomodulatory properties of MSCs. Nonetheless, their impact on MSC immunomodulatory properties was still assessed. For example, MSCs were treated with blood, plasma, or serum samples from patients [113, 172–177]; antioxidants such as vitamin E and selenium [178]; or environmental factors such as cigarette smoke extract [42], diesel exhaust particles [179], or insecticides [180] to investigate the effects of smoking, air pollution, and pesticide exposure, respectively. Furthermore, the MSCs were transfected to overexpress or knockout specific functions to elucidate their importance in the immunological functions of MSCs [11, 17, 53, 54, 90, 92, 109, 115, 120, 179–198], or they were treated with mitomycin [50, 68, 78, 104, 162, 199–203] or exposed to gamma-irradiation [86, 204, 205] to prevent cell division.

Effect of immune cell presence on untreated MSCs

In some cases, the MSCs were left untreated prior to coculture with immune cells to explore the effect of immune cells on the expression of inflammatory markers by the MSCs. This ability was measured by PCR [80–83, 206], sequencing [206, 207], ELISA [81, 91, 208, 209], Luminex [83], mass spectrometry [209], western blot [119, 210], flow cytometry [210], and immunofluorescence microscopy [210]. Both PBMCs [80–83, 119, 206, 208, 210], T cells [207], monocytes [209], and macrophages [91] were used to create a proinflammatory milieu that increased the immunomodulatory potential of MSCs.

Effect of experimental conditions on MSCs

During cell culture, numerous factors contribute to the immunological effect of MSCs. In most assays, cells were seeded together directly, enabling both juxtracrine and paracrine interactions. Additionally, the paracrine effects of supernatants harvested from MSC cultures or extracellular vesicles isolated from MSCs were investigated. The effects of MSCs may vary depending on whether they are investigated by direct cell contact, conditioned medium, or extracellular vesicles, as some functions rely on specific cellular interactions [211–215]. The remaining assays used other methods for cell culture, such as three-dimensional cultures [85, 101, 114, 126, 138, 151, 208, 216–218], engineered exofucosylated [219] or lyophilized MSCs [220], gels [91, 106, 125, 154, 198, 201, 209, 216, 221], scaffolds [91, 201, 222, 223], cell sheets [57, 145, 224, 225], or incubation in hypoxic environments [19, 57, 217, 226–230]. Additional experimental conditions included treating immune cells with apoptotic bodies derived from MSCs [14]. The immunomodulatory profile of the MSCs was affected by these experimental conditions, such as the constituents of the growth medium [149, 203], the number of passages [100], or differences in glucose [231] or oxygen [228] levels. The common goal was to create an environment that mimicked the in vivo environment in patients to understand how cell survival and retention after grafting of cells can be improved and ultimately increase the therapeutic potential.

Proliferation

Proliferation assays assessed the effect of MSCs on the proliferation of various immune cell types, including PBMCs, T cells, macrophages, B cells, and NK cells. To stimulate the proliferation of immune cells, mitogens or activating beads were commonly applied, or immune cells from several donors were used to initiate mixed lymphocyte reactions (MLRs) [3, 18, 156, 157, 196, 202–204, 220, 232–236]. Considerations for the assay design have previously been detailed [4]. In some assays, the effects of the presence of MSCs on the number of live macrophages [98, 154] or macrophage viability [99] were investigated. The proliferation response was measured by flow cytometry, colorimetric assays (including ELISA), radiation-based assays, enzyme-linked immunospot, live-cell imaging, immunofluorescence microscopy, or manual cell counting. A comprehensive mapping of methods, immune cell types, and references is provided in Table 1. In most studies, MSCs suppressed immune cell proliferation, although some studies reported increased proliferation depending on the context: Some assays investigated the proliferation of specific immune cell subsets that increased proliferation after treatment with MSCs, e.g., Tregs [14, 162, 170, 220] or regulatory B cells [163, 237]. Specific conditions, such as high- or low-glucose conditions [231], environmental factors [179], or the blocking of immunomodulatory proteins [45], affected the function of MSCs, resulting in increased proliferation of immune cells, i.e., decreased immunosuppressive effects. MSC-mediated inhibition of immune cell proliferation is extensively used to demonstrate the immunosuppressive effect of MSCs. By including multiple markers, predominantly active immune cell subgroups can be identified. This is important when investigating the modes and mechanisms of action behind the immunomodulatory potential of MSCs and enables the determination of whether reduced proliferation is due to immunosuppression or caused by immune cell killing by MSCs.

Polarization

Polarization assays investigated the effect of MSCs on phenotypes of various immune cells, primarily PBMCs, macrophages, and T cells, but also monocytes, dendritic cells, B cells, NK cells, and whole blood. Immune cells were exposed to inflammatory stimuli, and macrophages were typically polarized toward a proinflammatory phenotype. The immunomodulatory effects of MSCs were assessed by measuring cell surface and intracellular markers of immune activation or suppression via techniques such as PCR, sequencing, ELISA, flow cytometry, Luminex, western blotting, microscopy, and targeted proteomics (OLINK). A comprehensive list of references associated with each cell type and analytical method is provided in Table 1. The large number of polarization assays reflects the current hypothesis that MSCs interact with resident immune cells and orchestrate their response, thus modulating and resolving the inflammatory response. In the presence of immune cells, MSCs develop a more immunosuppressive phenotype, which was accompanied by activation of immune cells, maturation of dendritic cells, and polarization of macrophages towards an anti-inflammatory phenotype. The phenotype of immune cells can be determined based on surrogate markers, making this type of assay relatively simple. However, the relevance and reliability of any surrogate marker must be thoroughly established.

Enzyme activity

Enzyme activity assays primarily measured the activity of indoleamine 2,3-dioxygenase (IDO), which is part of tryptophan metabolism. IDO activity was measured by colorimetric assays [15, 16, 45, 63, 67, 70, 77, 80, 100, 114, 159, 168, 187, 203, 223, 238–250] and high-performance liquid chromatography [251]. MSCs do not express IDO constitutively, but IDO expression is upregulated by proinflammatory stimuli; therefore, the MSCs were primed [15, 16, 63, 67, 70, 77, 100, 114, 168, 187, 203, 223, 238–248, 250–252], cocultured with PBMCs [80], or both [45, 70, 77, 80, 249] or T cells [45, 77, 159] in the included studies. IDO is a known marker of MSC immunosuppressive effects, and IDO upregulation can be correlated with inhibited T cell proliferation [187, 245]. Thus, the enzyme activity assays were often conducted in combination with proliferation assays, to reflect on the influence of metabolism on the immunomodulatory capacity of MSCs, illustrated by correlation between increased IDO activity and decreased T cell proliferation, caused by tryptophan depletion and subsequent T cell starvation and death of T cells.

Adenosine diphosphate (ADO) is a well-established immunosuppressive mediator and has been employed as a functional readout of the immunomodulatory capacity of MSCs. It is generated through the stepwise hydrolysis of extracellular adenosine triphosphate, which results in upregulated ADO in MSCs both in monoculture [252] and after coculture with NK cells [253] or Tregs [207], as measured by western blot [252] and liquid chromatography [207, 252, 253]. In response to hyperglycemic conditions, the immunogenicity of MSCs was increased, as measured by colorimetric assay [231]. These assays illustrate the ever-changing nature of MSCs and how their metabolism affects their immunomodulatory characteristics. Furthermore, changes in enzyme activity reflect the immediate function of MSCs, thus providing a different perspective that can be gained through measurement of gene and/or protein expression, as enzyme activity can be inferred directly from the functionality of MSCs.

Endocytosis

Endocytosis assays examined the effects of MSCs on the endocytic activity of immune cells via flow cytometry [13, 14, 87, 90, 113, 133, 185, 191, 249, 254–256], microscopy [96, 97, 103, 109, 133, 213, 215, 257–259], or live-cell imaging [260]. Endocytic activity is defined as the cellular uptake of particles or other cells and was increased after interactions between MSCs and macrophages [13, 14, 96, 97, 103, 109, 113, 191, 260], dendritic cells [255], T cells [259], and PBMCs [14, 186, 249, 256, 257]. Furthermore, the number of phagocytic cells in whole blood was increased by treatment with extracellular vesicles derived from MSCs [87]. In a heterogeneous population, effective endocytic cells can be distinguished through the labelling of specific cell markers [14, 186, 249, 257]. In neutrophils, both phagocytosis and efferocytosis were increased after coculture with MSCs [90, 97, 185, 213, 215, 258]. Most of these assays investigated endocytosis by immune cells, but MSCs were able to clear apoptotic T cells through endocytosis; however, their uptake of living cells was hardly detectable [133]. Endocytosis by immune cells is often associated with their polarization towards an anti-inflammatory phenotype and can therefore be used to ensure the functionality of polarized immune cells, possibly in combination with a polarization assay.

Cell death

Intrinsically, MSCs can regulate cell death, for example, by upregulating inflammasomes related to apoptosis, as measured by qPCR and western blot [54] but also by regulating autophagy, which was increased by treatment with proinflammatory cytokines [115] and decreased after interaction with T cells [261], as measured by transmission electron microscopy [115, 261], qPCR [261], and western blot [261]. Furthermore, both flow cytometric analysis [46, 60, 99, 127, 140, 169, 185, 213, 215, 245, 258, 261–263] and ELISA [264] revealed that MSCs prevented the apoptosis of nearby immune cells. Interaction with MSCs resulted in decreased apoptosis of PBMCs [127, 140, 169, 245, 262], T cells [60, 121, 261], macrophages [46], neutrophils [213, 215, 258], and B cells [99]. While the apoptosis of NK cells increased after coculture with MSCs, this finding was not in concordance with previous findings from similar assays [253]. Treatment of PBMCs from patients with systemic lupus erythematosus with either MSCs or MSC-derived extracellular vesicles led to increased apoptosis [237]. Similarly, increased apoptosis was observed in PBMCs from MSC‒PBMC cocultures subjected to palmitate-induced metabolic stress [264]. These findings suggest that certain pathological or stress conditions may impair the responsiveness of PBMCs to the protective effects of MSCs. While autophagy and apoptosis in MSCs are primarily indicators of cellular well-being rather than direct measures of immunological function, they can indirectly influence their immunomodulatory capacity. Assessing MSC-induced apoptosis in neighbouring immune cells, in combination with other immune assays, helps distinguish whether the observed effects arise from immune cell death or from changes in the expression of immunological markers.

Cytotoxicity

MSCs can alter the cytotoxicity of immune cells. In NK cells [40, 118–120, 227], PBMCs [120, 220, 231], and T cells [220], cytotoxicity was decreased after coculture with MSCs, as shown by colorimetric assays [118–120], flow cytometry [40, 120, 220, 227], cell counting [231], and a Chromium-51 release assay [40]. However, the killing of target cells by PBMCs was increased after coculture with MSCs and stimulation with TLR agonists, as visualized by live-cell imaging [265].

The cytotoxic effect of neutrophils is primarily mediated through their initiation of respiratory bursts, generating reactive oxygen species crucial for the innate immune response. The effect of MSCs on respiratory bursts depended on the experimental conditions, as MSC-derived extracellular vesicles had a limited effect, whereas conditioned medium from MSCs increased respiratory burst activity, as measured by western blot [213, 215, 258]. Additionally, the combination of MSCs and alpha-1 antitrypsin inhibited respiratory bursts, as visualized by immunofluorescence microscopy [97]. These varying results may reflect the plasticity of MSCs, whereby they sense, adapt, and respond to specific phases and demands during an inflammatory response, an ability that may be vital for their prolonged survival in an inflammatory milieu.

Migration

MSCs can regulate the recruitment of immune cells to sites of inflammation, which is important for their role as regulators of the immune response and in the activation of the immune system. Indirect coculture with MSCs upregulated both monocyte migration and the expression of genes related to monocyte recruitment, as measured by flow cytometry [11], cell counting [106], and qPCR [11]. However, exposure of MSCs to blood components resulted in reduced recruitment of monocytes, as measured by cell counting [88]. Likewise, the immunomodulatory effects of conditioned medium from MSCs were investigated by flow cytometry, which revealed that the migration of PBMCs was inhibited [58]. The expression of chemokines by MSCs via qPCR and Luminex analysis was found to be increased and inversely correlated with T cell proliferation [17]. The migration of neutrophils was increased in response to treatment with extracellular vesicles or conditioned medium from primed MSCs, as measured by live-cell imaging [87]. Examining how MSCs influence resident immune cells can provide insight into the extent of their regulatory capacity in initiating and modulating immune responses. Migration assays have frequently demonstrated enhanced recruitment of immune cells, thus contributing to a proinflammatory environment that can further amplify the immunomodulatory effects of MSCs.

Inflammatory pathways

Small molecules such as metformin [243], chlorzoxazone [170], phytosomal curcumin [152], and suramin [93] have been used to enhance the anti-inflammatory properties of MSCs, with the aim of increasing their therapeutic efficacy in diseases such as systemic lupus erythematosus. While not strictly mechanistic studies, such interventions may provide indirect insights into key signalling pathways involved in MSC immunomodulation. Assays revealed the upregulation of anti-inflammatory pathways via western blotting [170, 243] and the downregulation of proinflammatory pathways via qPCR [152]. Proinflammatory pathways were downregulated in PBMCs derived from alopecia areata patients after coculture with MSCs [266], in macrophages cocultured with primed MSCs [93], and in macrophages from patients with coronary atherosclerotic heart disease treated with conditioned medium from autologous MSCs [46], all of which were measured via western blotting. Assays investigating inflammatory pathways can be used to discover mechanisms of action by examining the effects of specific mediators.

Differentiation

In response to inflammation, monocytes migrate to sites of inflammation, where they differentiate into macrophages or dendritic cells depending on the surrounding tissue milieu. When monocytes were cocultured with MSCs, both their activation and ability to differentiate into either macrophages or dendritic cells were decreased, as measured by qPCR [255]. Macrophages and dendritic cells perform effector functions that are crucial for promoting the inflammatory response. However, if uncontrolled and prolonged, this may become detrimental.

Discussion

Investigation of immunomodulatory properties of MSCs is a rapidly expanding area of research. Our literature search identified over 2000 publications since 2019 alone, underscoring the importance of evaluating the current landscape and future trajectory of this research area. MSCs are widely recognized for their immunomodulatory properties [1, 2], yet the underlying mechanisms of action remain incompletely understood. Interestingly, this review highlights that most studies still explore the characteristics of MSCs and functional assays focusing on proliferation and polarization (Fig. 2).

A critical challenge remains MSC heterogeneity, which impairs reproducibility and repeatability. Although papers that did not meet ISCT criteria [30] were excluded from this review (Fig. 1B), variability persisted and MSCs from different sources exhibited variable expression profiles and immunomodulatory potential [70, 76, 77], which has implications for consistent outcomes [2]. Furthermore, the culture conditions, such as hypoxia [57], also changed the MSC secretome and thereby their immunomodulatory effect. This complicates comparison between studies and assays and underscores the need for source-specific comparisons and transparent reporting of MSC origins. Some studies proposed standardized protocols for isolation and handling of MSCs [4, 15–17, 108, 141, 204, 205, 234, 235, 263, 267–271], thereby directly addressing the need for consensus in MSC research, which also aligns with broader initiatives within the scientific community [272]. Their efforts to create standardized and validated assays for testing MSC immunomodulatory potential based on accepted sets of guidelines from the International Conference on Harmonization and European Medicines Agency [273] and the U.S. Food and Drug Administration [274] are promising, especially regarding lymphocyte proliferation assays [4, 17, 204, 205, 234, 235, 263, 267, 271]. The guidelines suggest evaluation of assay robustness, repeatability, range, and precision, as well as specificity and selectivity of methods used for assay readout, e.g. flow cytometry. While adoption is uneven, this can help define the ability of the assay to produce reliable and reproducible results, thus ensuring comparability of MSC batches and between research groups. However, many studies still report results without disclosing critical parameters. Eliminating assay variability entirely may not be feasible, but transparent reporting of key features such as MSC source, passage, and experimental conditions is essential for reproducibility and meta-analysis. Moving forward, the field should prioritize harmonization of protocols and workflows, thus aiding development of relevant assays for evaluating therapeutic potential of MSC.

Another critical variable is the strategy used to mimic inflammatory environments. Priming with cytokines or drugs offers controlled dosing and timing, thus improving standardization, but may lack in vivo relevance due to its simplicity, and possibly does not reflect in vivo concentrations. Conversely, inclusion of immune cells increases physiological relevance but adds complexity and introduces variability. Direct co-culture enables cell–cell contact but complicates analysis while indirect methods simplify separation but exclude contact-dependent mechanisms. Emerging technologies such as single-cell sequencing may help overcome these limitations by enabling detailed analysis of individual cell contributions without physical separation. However, implementation of this technology may be hindered by the high cost. Furthermore, sequencing analyses may expose personally identifiable information, posing a risk to donor anonymity. Therefore, researchers must consider whether this violates the terms under which the tissue was obtained. Information on the priming strategy or the inclusion of immune cells is important, since so many different protocols exist, and these tend to yield different MSC responses. Future efforts to describe the mechanisms could foster the ability to selectively enhance or inhibit specific characteristics of the MSCs and may be valuable for translation to clinical applications. This may be achieved by designing more complex assays using multiple cell types, scaffolds and/or three-dimensional structures with improved physiological relevance while maintaining reproducibility. Both controlled priming of MSC, inclusion of immune cells, and more complex models can yield valuable insights, but the choice should be guided by desired outcome. If a simple model provides the required readout, added complexity is unnecessary and may hinder interpretation. Thus, complex models should be employed only when they offer clear advantages in terms of physiological relevance or understanding, as the design and analyses of these models are inherently more challenging.

Characterization assays represent the most frequently used approach in MSC immunomodulation research, likely due to their simplicity, cost-effectiveness, and ability to provide rapid information on MSC phenotype. While essential for confirming MSC identity, phenotype alone does not reliably predict immunomodulatory potency due to MSC heterogeneity and plasticity. Consequently, over-reliance on phenotypic characterization without functional validation, may hinder clinical translation, yet phenotypic markers can serve as surrogates for potency if their predictive value is sufficiently demonstrated through functional assays. As mitigation, we recommend integrated workflows that pairs phenotypic characterization with at least one functional assay. This approach provides further insights into MSC mode and mechanism of action, thus improving robustness and reliability by linking MSC identity to functional effect.

Functional assays showed greater complexity and variability in design and output measures compared to characterization assays, which complicated interpretation and reproducibility. Macrophage-related assays illustrated these challenges, and although most studies reported an anti-inflammatory shift, discrepancies persisted due to variable marker selection and differentiation protocols. Moreover, reliance on THP-1-derived macrophages raises concerns about translational validity, as cell lines may not fully reflect properties of primary cells. Additional insights could be gained through more studies using primary cells, focusing on development of reliable marker panels, and by combining characterization assays with functional assays, e.g., investigating endocytosis, assay robustness could be improved. These inconsistencies highlight the need for critical evaluation of assay performance. Notably, proliferation assays appeared to be more uniform, and commonly used buffy-coat-derived PBMCs. Despite variations in PBMC isolation and stimulation protocols, these assays consistently demonstrated MSC inhibition of PBMC and T cell proliferation and a shift towards Treg subsets with fairly consistent usage of specific markers. This reproducibility suggests that proliferation assays may serve as a benchmark for functional evaluation. Flow cytometry was extensively used, reflecting the ability to deliver high-throughput, multi-parameter, and quantitative analysis. The versatility and reproducibility of this method make it a cornerstone for functional evaluation.

Assays involving B cells, NK cells, and neutrophils were less frequent and showed greater variability, largely due to methodological differences. For B cells, technical challenges in isolation may explain their limited use. Proliferation results differed, with some reporting expansion of regulatory B cells [163] and other suppression, likely due to different activation protocols and B cell phenotype. NK cell study outcomes varied in cytotoxicity, polarization, and proliferation, which was influenced by MSC health status [40], use of the MSC secretome [40, 117], and use of cell lines instead of primary NK cells [117–120]. Neutrophil studies consistently showed increased endocytosis and reduced apoptosis but differed in released reactive oxygen species, depending on labelling of neutrophils [97] or MSC [215], and whether MSCs [213, 215], conditioned medium, or extracellular vesicles [213, 215] were used. These discrepancies highlight the impact of assay design on observed effects, underscoring the need for standardized protocols. Selecting immune cells that match the clinical indication is essential for ensuring translational relevance. More research on these less frequently used types of immune cells is needed to improve consistency of the reported results and clarify their predictive value.

Importantly, the categorization of assays in this review does not adequately reflect the synergistic value of combined approaches, and assigning papers to a single category creates a risk of oversimplification. Many studies employed multiple assay types to build a more comprehensive understanding of MSC function (Fig. 2B). For example, studies that paired flow cytometric evaluation of proliferation with investigation of IDO expression and/or activity by MSCs provided stronger evidence of immunomodulatory capacity than either approach alone [40, 117]. Finally, even when using primary human cells, in vitro systems cannot fully replicate the complexity of in vivo physiology. Thus, their ability to predict clinical efficacy should be interpreted cautiously.

Conclusions

Understanding the potential implications of MSC immunomodulation is critical for reliable translation of in vitro findings to clinical applications. MSCs primarily act through constitutive expression of immunomodulatory markers and, when exposed to proinflammatory stimuli, adopt an anti-inflammatory phenotype, that can help alleviate inflammation. Despite significant progress, the field still faces challenges that hinder clinical translation. To address these challenges, we propose a minimum reporting checklist that includes MSC source, priming conditions, assay design, and immune cell characteristics. These attributes have been identified in this review as major causes of variation. Such a framework would improve transparency, facilitate cross-study comparisons, help identify sources of variability, and guide robust assay design. Due to the complexity of MSC interactions, an array of assays is needed to fully assess their therapeutic potential. A robust strategy would include a characterization assay to confirm the MSC phenotype, alongside a proliferation assay, which currently represents the most standardized functional assay. Additional assays should be incorporated to further elucidate the immunomodulatory properties of MSCs, e.g., targeting specific functions, along with gene and protein expression analysis to identify biomarkers relevant to preclinical and clinical settings.

Supplementary Information

Below is the link to the electronic supplementary material.

Abbreviations

ADO

Adenosine diphosphate

ELISA

Enzyme-linked immunosorbent assay

IDO

Indoleamine 2,3-dioxygenase

IFN

Interferon

IL

Interleukin

ISCT

International Society for Cellular Therapy

MLR

Mixed lymphocyte reaction

MSC

Mesenchymal stromal cell

NK

Natural Killer

PBMC

Peripheral blood mononuclear cell

PCR

Polymerase chain reaction

qPCR

Quantitative polymerase chain reaction

Th

T helper

TNF

Tumor necrosis factor

Treg

Regulatory T cells

Author contributions

All authors contributed to the defined search string. L.L.L., S.B., and L.D.H. conducted the screening of all included papers. L.L.L. conducted data analysis and drafted the manuscript. All authors participated in data interpretation and revision of the manuscript. All authors have approved the submitted version.

Funding

Open access funding provided by Copenhagen University. Funded by Innovation Fund Denmark (IMPACT grant 3147-00003B).

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

A.E. is inventor of the patent “Stem cell therapy based on adipose-derived stem cells” (Publication WO 2017–068,140) and part of the management team in the company of Cell to Cure.