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Nam, Park, Kim, and Cho: Natural Killer Cell Assays: Clinical Applications and Future Directions
Review Article
Diagnostic Immunology

Ann Lab Med 2026;46(3):244-256.

Published online: 24 March 2026

DOI: https://doi.org/10.3343/alm.2025.0508

Natural Killer Cell Assays: Clinical Applications and Future Directions

Minjeong Nam, M.D., Ph.D.1, Wooseok Park, M.D.1, Hyun-Young Kim, M.D., Ph.D.1, , Duck Cho, M.D., Ph.D.1, 2, 3,

1Department of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea

2Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, Seoul, Korea

3Cell and Gene Therapy Institute, Samsung Medical Center, Seoul, Korea

Corresponding author: Hyun-Young Kim, M.D., Ph.D. Department of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea E-mail: hysck.kim@skku.edu

Co-corresponding author: Duck Cho, M.D., Ph.D. Department of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea E-mail: duck.cho@skku.edu

Received 27 August 2025       Revised 13 October 2025       Accepted 19 December 2025

© Korean Society for Laboratory Medicine

(open-access):

This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Natural killer (NK) cells play critical roles in immune surveillance and homeostasis maintenance through cytotoxicity and cytokine release. The ability of NK cells to eliminate target cells without the need for prior antigen recognition or antibody involvement has drawn considerable attention for translational and clinical applications. As clinical applications continue to broaden, interest in NK cell assays has been growing markedly. This review provides an in-depth discussion of current clinical applications of NK cell assays, including NK cell phenotype, frequency, and functional activity assessments. This review further highlights the diagnostic potential of these assays in terms of hemophagocytic lymphohistiocytosis and potential NK cell biomarker candidates in diverse pathological contexts, such as cancer, infection, autoimmune diseases, and other diseases. By integrating clinical insights with technological advancements, NK cell assays can serve as valuable tools for disease diagnosis, prognosis, and therapeutic monitoring.

Keywords: Autoimmune diseases, Cancer, Cytotoxicity, Functional assays, Hemophagocytic lymphohistocytosis, Infections, Natural killer cells

INTRODUCTION

Natural killer (NK) cells account for approximately 5%–15% of circulating lymphocytes and are first-line defenses against cancers and infections [1]. NK cells exert cytotoxicity through perforin- and granzyme-mediated cell lysis or by activating death receptors on target cells. NK cells also contribute to immune regulation by secreting pro-inflammatory cytokines and chemokines, including interferon-gamma (IFN-γ), tumor necrosis factor-alpha (TNF-α), and various interleukins (ILs) [2].
The phenotypic diversity and functional plasticity of NK cells facilitate the adaptation of NK cell assays across diverse physiological and pathological conditions. Recently, advanced technologies, such as single-cell RNA sequencing, high-dimensional flow cytometry, and mass cytometry enabled detailed characterizations of NK cell phenotypic diversity and functional plasticity [3]. In turn, various NK cell assays can help assess and identify phenotypic markers, frequencies, cytotoxic capacities, and cytokine production. Clinical applications of NK cell assays have expanded considerably, and NK cell assays can potentially offer valuable insights into disease diagnosis, prognosis, and therapeutic monitoring.
Impaired NK cell cytotoxicity has been considered as a hallmark characteristic for hemophagocytic lymphohistiocytosis (HLH) diagnosis [4]. Although recent revised HLH diagnostic guidelines place less emphasis on NK cell activity and favor more sensitive markers, such as soluble CD25, NK cell function assays remain clinically important [5]. NK cell assays provide valuable insights into HLH and are being investigated as potential biomarkers for various diseases, including cancer, infectious diseases, and autoimmune disorders [6–8].
This review provides a comprehensive overview of NK cell assays and describes their evolving roles in clinical practice. We highlight the translational potential of NK cell assays in improving diagnostic precision, prognostic assessment, and therapeutic monitoring across a variety of diseases.

DIVERSITY AND PLASTICITY OF NK CELLS

NK cells possess remarkable phenotypic and functional diversity, which helps them orchestrate appropriate immune responses in specific tissues under distinct physiological conditions [9]. NK cells are traditionally classified into CD56dim and CD56bright subsets. CD56dim NK cells are predominantly cytotoxic and circulate mainly in the peripheral blood (PB), whereas CD56bright NK cells produce immunoregulatory cytokines and are enriched in secondary lymphoid tissues [9]. More recently, high-dimensional single-cell analyses have suggested an additional functional framework for circulating NK cells, comprising three subsets: NK1 cells, which exhibit high cytotoxic potential with robust CD16 and cytotoxic granule expression; NK2 cells, characterized by enhanced cytokine responsiveness and high CD56 and CD27 expression; and NK3 cells, enriched for adaptive-like features, including expression of CD56, PRDM1, and NKG2C [3]. Tissue-resident NK cells exhibit unique phenotypic and functional profiles, largely driven by distinct expression patterns of chemokine receptor [10]. For example, uterine NK cells (uNKs), which express high levels of CD56, are critical for vascular remodeling during early pregnancy, thereby contributing to successful gestational outcomes [11]. Similarly, liver-resident NK cells, often identified by markers such as CD49a, support liver immune surveillance and homeostasis [12].
Beyond their inherent diversity, NK cells exhibit notable plasticity, enabling dynamic phenotypic and functional adaptations in response to environmental changes and pathologic conditions [9, 13]. In a transforming growth factor-β-rich tumor microenvironment, NK cells can acquire a decidual-like (dNK-like) phenotype, characterized by CD9 and CD49a expression [14]. NK cells with a dNK-like phenotype show reduced cytotoxic activity and secretion of pro-angiogenic factors, such as vascular endothelial growth factor, facilitating tumor progression and, thereby, correlating with poor clinical outcomes [13]. In acute viral infections, cytotoxic CD56dim NK cells can expand and migrate to infection sites after cytokine receptors such as IL-12, IL-18, and type-I interferons (IFNs) are upregulated [8]. In contrast, during chronic infections and prolonged inflammatory conditions, NK cells often become functionally exhausted, frequently characterized by CD56 downregulation and reduced cytotoxic and cytokine-production capacities [8, 15]. Given the phenotypic and functional diversity and plasticity of NK cells, various assays have been developed to help assess NK phenotype, frequency, activation state, and functional capacity.

NK CELL ASSAYS

NK cell assays have been used to evaluate NK cell phenotypes, frequencies, and functions. Newly-developed technologies enable more precise and comprehensive assessments of NK cell functional activity. These assays collectively encompass phenotypic profiling, cytotoxicity measurement, degranulation analysis, cytokine release quantification, gene-based characterization, and emerging instrument-assisted approaches. Fig. 1 provides an overview of the assay platform evaluated in this review.

Phenotypic and quantitative analysis

Traditionally, NK cell phenotypes have been defined by the relative expression levels of surface markers, such as CD56 and/or CD16, and the lack of CD3 expression [9]. Additional NK cell subsets can be distinguished using flow cytometry based on differential surface marker expression [16]. Phenotypic analysis also involves examining the activating and inhibitory receptors that regulate NK cell function, including natural cytotoxicity receptors (NKp30, NKp44, and NKp46), NKG2D, and killer immunoglobulin-like receptors (KIRs). Additionally, such analysis involves assessing cytokine receptors, including CD25 (IL-2Ra), CD122 (IL-2/IL-15Rβ), and CD132 (common γ-chain), as they reflect IL-2 responsiveness [17].
The activation state of NK cells is commonly monitored by assessing CD69 expression [18]. CD69 is a stimulatory receptor for NK cells and its expression is also reportedly to be negatively associated with T-cell immunity [19]. High-dimensional single-cell analyses, such as single-cell RNA sequencing and cellular indexing of transcriptomes and epitopes by sequencing, have identified diverse NK cell subsets based on distinct transcriptomic and protein biomarkers [3]. Additionally, a 29-color flow cytometry panel incorporating differentiation, cytotoxicity, tissue residency, and dysfunction markers was developed to comprehensively profile PB NK cells [20]. These technological approaches enable more refined phenotypic classifications and highlight functional diversity.
In addition to phenotype profiling, the absolute number of NK cells/μL in PB is determined to assess NK cell frequency. This calculation typically involves combining complete blood count (CBC) with differential and flow cytometry data: the absolute lymphocyte count (ALC) is obtained from the CBC, whereas flow cytometry defines the percentage of CD3–CD56+ cells. The absolute number of NK cells is then calculated as ALC×%CD3–CD56+ cells. Altered NK cell frequencies have been implicated in several immunological and pathologic conditions [16]. Of note, recent studies have suggested applying demographics-specific reference intervals, such as those based on age, sex, and ethnicity, for the quantitative analysis of lymphocyte subpopulations, including NK cells [21]. Mass cytometry (cytometry by time-of-flight [CyTOF]) is a next-generation platform that enables simultaneous quantification of over 40 markers without the need for fluorescence compensation and provides enhanced resolution for profiling NK cells with diverse receptor repertoires [22].

Cytotoxicity-based assays

NK cells induce target cell death through contact-dependent mechanisms, primarily by releasing perforin and granzymes and through death receptor pathways, such as the Fas ligand–Fas axis [1]. To assess NK cell cytotoxicity, different biomarkers associated with target cell death are measured in different functional assays.

51Cr-release assay

The 51Cr-release assay is considered the gold standard method for evaluating NK cell-mediated cytotoxicity. Target cells are first labeled with radioactive 51Cr; subsequently, NK cell cytotoxicity is quantified by measuring 51Cr release into the supernatant following target cell lysis. Elevated 51Cr release indicates a higher effector: target cell ratio, which correlates directly with the degree of cytotoxicity [23]. However, 51Cr-release assays have several limitations, including the need for a radioactive isotope, labor-intensive procedures, low sensitivity, and suboptimal labeling efficiency for certain target cells.

Cytotoxicity assay for measuring dead cells

Membrane integrity is a well-known indicator of cell death. Calcein-AM-release assays help measure NK cell-mediated cytotoxicity by detecting fluorescence released from lysed target cells preloaded with Calcein-AM, a membrane-permeable fluorescence dye [24]. This method serves as a safer and more sensitive alternative to 51Cr-release assays. However, variable Calcein-AM retention and spontaneous dye leakage from intact cells can affect accuracy and reproducibility [25]. A modified approach involving effector cell staining with Calcein-AM provides improved stability and reproducibility over conventional target cell staining methods [26].
Another commonly used indicator of target cell lysis is the release of cytoplasmic enzymes, such as lactate dehydrogenase (LDH) or intracellular proteases. LDH assays help quantify enzyme leakage using a colorimetric, non-radioactive method [27]. Although these assays are accessible and cost-effective, background LDH activity can reduce sensitivity and underestimate NK cytotoxicity [28]. Intracellular protease release can be measured using the CytoTox-Glo assay, wherein a luminogenic peptide substrate is proteolytically cleaved to produce a signal proportional to target cell death [29]. This method is highly sensitive, rapid, and provides a low-noise luminescence readout, enabling multiplexing with viability assays and real-time kinetic monitoring.

Flow cytometry-based cytotoxicity assays

Advanced cytotoxicity assays can help assess NK cell-mediated target cell death at the single-cell level. These assays utilize fluorescent markers, such as propidium iodide, annexin V, and 7-amino-actinomycin D to evaluate changes in cell size, granularity, and membrane integrity, which are key indicators of cell death [30]. Technological developments in flow cytometry have enabled the use of multicolor platforms with more fluorochromes for precise discrimination between effector and target cell populations [31]. Such assays provide high sensitivity and reproducibility through multiparametric analysis, making them powerful tools for evaluating NK cell cytotoxicity in both research and clinical applications [32].
When studying patient samples, NK cytotoxic activity is commonly assessed using peripheral blood mononuclear cells (PBMCs) as effector cells [33]. However, the number of NK cells can vary substantially between samples, and in some cases, obtaining sufficient PBMCs for analysis is difficult, necessitating the collection of relatively high blood volumes from patients. To overcome these challenges, a flow cytometry-based method using overnight cytokine-stimulated whole blood NK cells was developed. This approach eliminates the PBMC isolation step and enables reliable assessment of NK cytotoxicity [34]. The results from whole blood-based assay show good correlation with those from conventional PBMC-based assays.

Lysosomal-associated membrane protein-1 (CD107a)-based degranulation assays

Degranulation assays for evaluating NK cell cytotoxicity are based on assessing the release of cytotoxic granule markers, including perforin, granzymes, and CD107a [35]. Among these, CD107a-based degranulation assays are widely used to assess NK cell functional activity. CD107a is transiently expressed on NK cells during degranulation and serves as a surrogate biomarker of NK cell activation and cytotoxic function [36]. Flow cytometry is commonly employed to detect cell-surface CD107 expression, providing an indirect but reliable indicator of NK cell cytotoxic activity. Multiparametric flow cytometry can facilitate simultaneous assessment of CD107a expression and other phenotypic and functional biomarkers for enhanced accuracy and resolution in NK cell functional analysis [34, 37].

Cytokine-release assays

Cytokine-release assays are used to evaluate NK cell activity by measuring the secretion of key cytokines, including IFN-γ, TNF-α, IL-2, IL-12, and IL-15. IFN-γ enzyme-linked immunospot (ELISpot) assays enable simultaneous assessment of NK cell frequency and function by quantifying IFN-γ secretion from individual cells [38]. IFN-γ ELISpot assays provide high sensitivity and require relatively few cells for accurate quantification. ELISA is also commonly used to quantify cytokine concentrations [39]. NK cells do not spontaneously secrete effector cytokines without appropriate stimulation, necessitating in vitro stimulation for reliable detection [40]. The NK Vue Kit (ATgen, Seongnam, Korea) utilizes the engineered recombinant cytokine, PROMOCA, to stimulate NK cells, and subsequently, IFN-γ release is measured as an indicator of NK cell function [41]. Although NK cells represent the predominant source of IFN-γ, T cells and NKT cells can also contribute to IFN-γ production, albeit at lower levels [42]. The assay does not directly assess NK cell cytotoxic activity but instead evaluates immunostimulatory function by measuring cytokine release. Despite these limitations, the NK Vue Kit provides a standardized and minimally invasive method for monitoring NK cell activity and has been applied in diverse clinical settings [41, 43].

RNA-expression assays

RNA-expression assays help evaluate NK cell function, particularly in relation to phenotypic diversity and functional plasticity [44]. Quantitative reverse transcription-PCR (RT-qPCR) offers a highly sensitive and accessible method for quantifying the expression of genes associated with NK cell cytotoxicity and cytokine production [45]. Whole-genome sequencing and single-cell RNA sequencing technologies enable high-throughput, genome-wide profiling of NK cells. These methods provide systematic insights into molecular pathways and regulatory networks that influence NK cell function [44]. A novel approach (determining the “non-incubating NK score”) has been proposed for estimating NK cell cytotoxicity by quantifying mRNA-expression levels of effector molecules (such as NKp46, granzyme B, Fas ligand, TNF-α, and IFN-γ) in isolated NK cells [46]. Thus, RNA-expression assays can support the robust clinical translation of NK cell assays and enhance their applicability.

Emerging approaches for NK cell assays

Recent technological advancements have enhanced the accuracy, efficiency, and accessibility of NK cell assays. Live-cell imaging assays enable real-time visualization of dynamic NK cell functions, such as cytotoxic events and effector–target interactions [47]. Quantitative single-cell microscopy combined with tracking algorithms has further demonstrated NK cell migration toward targets and direct cell–cell interactions at the single-cell level [48, 49]. Spatial co-localization analysis has been applied to evaluate NK cell-mediated cytotoxicity by quantifying the number and proportion of lysed target cells within a defined imaging field [50]. The development of self-powered integrative magneto-microfluidic, cell-separation chips has enabled automated, high-purity NK cell isolation within a single workflow [51]. This technology reduces dependence on complex laboratory infrastructure, thereby improving the accessibility of high-quality NK cell assays for immune monitoring and personalized medicine applications. A novel platform was developed that simultaneously assesses both cytotoxicity and cytokine release, unlike conventional NK cell assays that measure these functions separately [52]. This method utilizes engineered microparticles, including antibodies for NK cell activation and cytokine detection, and peptides for granzyme B measurement. This integrated approach enables comprehensive evaluation of NK cell activity in a single assay and substantially improves assay efficiency while maintaining functional resolution.

CLINICAL APPLICATIONS OF NK CELL ASSAYS

The NK cell characteristics underscore their applicability in various clinical conditions, including HLH, cancer, infectious diseases, autoimmune disorders, reproductive disorders, and preventive health screening (Fig. 2). NK cell assays help evaluate cytotoxic function, phenotypic diversity, and cytokine production, and they can provide critical insights into physiological and pathological immune responses. These applications highlight the translational and diagnostic potential of NK cell assays, as summarized in Table 1.

Diagnostic significance in HLH

HLH is a life-threatening hyperinflammatory syndrome characterized by defective NK cell cytotoxicity [53]. Defective cytotoxicity prevents the efficient elimination of antigen-bearing target cells, causing persistent antigen presentation and continuous lymphocyte activation [53], which results in excessive IFN-γ, TNF-α, and GM-CSF secretion and triggers macrophage hyperactivation and amplified pro-inflammatory cytokine release. The ensuing cytokine storm promotes hemophagocytosis, cytopenia, and multiorgan hyperinflammation, establishing the central pathogenic cascade of HLH [54]. HLH is broadly classified into primary and secondary HLH. Primary HLH (or familial HLH) is caused by genetic defects related to cytotoxic function. The most commonly implicated genetic defects occur in UNC13D, LYST, PRF1, and STXBP2 [55], often resulting in reduced CD107a expression and impaired cytotoxic granule release. CD107a-based degranulation assays are clinically valuable for rapidly identifying defective degranulation in cytotoxic cells.
Secondary HLH is not associated with genetic defects but is typically induced by external conditions, such as infections, malignancies (e.g., lymphomas), or autoimmune diseases [56]. Primary HLH is characterized by profound cytotoxic dysfunction, whereas secondary HLH presents with variable NK cell activity, depending on the underlying cause and stage of disease progression [57]. Flow cytometry-based cytotoxicity assays have indicated that NK cell function and activity levels are lower in patients with primary HLH than in those with secondary HLH and healthy controls [58].
The HLH-2004 guidelines (a key framework for HLH diagnosis) designate low or absent NK cell activity as one of eight diagnostic criteria; HLH diagnosis is confirmed when five criteria are fulfilled or when a causative genetic defect is identified [4]. These guidelines emphasize interpretation relative to locally established reference intervals to account for inter-laboratory variability. For example, a single-center study defined a reference range of 11.8%–31.9%, with patients with HLH exhibiting significantly lower NK cell activity (8.3±8.9%) than those without HLH (20.1±7.8%) [59]. Oh et al. [60] reported reduced NK cytotoxic activity in secondary HLH (median 12.1% vs. 26.2% in non-HLH, P<0.001). Collectively, these findings underscore the diagnostic and prognostic significance of NK cell assays and highlight the necessity of locally validated reference intervals for reliable clinical application.
However, the diagnostic utility of measuring NK cell activity, particularly in secondary HLH, remains controversial. Recent revisions to clinical diagnostic guidelines reflect this situation with reduced emphasis on NK cell activity and favoring more sensitive and specific markers, such as soluble CD25 (sCD25) [11]. sCD25 is a highly reliable biomarker in adult HLH, with Hayden et al. [61] reporting 100% sensitivity (threshold: 2,515 U/mL; specificity: 72.5%) and Yoon et al. [62] showing a 90% sensitivity and an 80% specificity. Excluding NK cell activity from diagnostic criteria did not diminish the overall diagnostic performance; both sensitivity and specificity exceeded 95% [63].
In summary, NK cell assays can help provide important information regarding immune function, although they have become supplementary rather than central in HLH diagnosis. Their future utility may improve with standardized and automated assays, meeting a crucial need in HLH management.

Biomarkers for cancer diagnosis, prognosis, and therapeutic monitoring

NK cells can potently eliminate a wide range of tumor cell lines in vivo, underscoring their central role in tumor immune surveillance. Mice lacking NK cells exhibit accelerated tumor growth and metastasis, whereas adoptive transfer of activated NK cells significantly suppresses tumor progression [64]. In humans, abundant NK cell infiltration into the tumor microenvironment has been correlated with improved overall survival in malignancies, including hepatocellular carcinoma (HCC), gastric cancer (GC), colorectal cancer (CRC), and non-small cell lung cancer [65]. These findings strongly indicate that NK cells suppress tumorigenesis and help determine clinical outcomes.
Within the tumor microenvironment, NK cells undergo changes in phenotype, frequency, and functional activity through cytokine-mediated signaling and reconfiguration of co-expressed receptors. Given the plasticity of NK cells, multicolor flow cytometry-based assays are being increasingly recognized as valuable adjunctive tools for cancer diagnosis, prognosis, and monitoring cancer treatment efficacy. NK cell assays can help differentiate NK cell features in patients with cancer from those in healthy individuals, which can be used for diagnostic purposes. Patients with advanced invasive breast cancer have significantly higher proportions of CD56+CD16– and CD56dimCD16– NK cells in the PB than do patients with benign tumors [66], indicating a tumor-driven shift toward immature and non-cytotoxic NK cell subsets. Similarly, in HCC and liver metastasis, NK cells show an altered phenotype characterized by CD49a+Eomes+ NK subsets, which are associated with enhanced angiogenesis and reduced cytotoxic activity [67].
ELISA-based cytokine release assays can help in identifying NK cell alterations in patients with cancer. In GC, disease stage and progression are associated with IFN-γ production [68]. Genetic variation also influences NK cell function. In CRC, the C/C genotype of the NKG2D single-nucleotide polymorphism rs1049174 has been associated with reduced NK cell cytotoxicity and identified as an independent risk factor [69]. Conversely, patients with the G/G genotype are at a significantly lower risk for CRC (odds ratio, 0.47; 95% confidence interval [CI], 0.32–0.72) than are those harboring the C/C genotype. Transcriptomic profiling using Affymetrix microarrays in patients with CRC revealed lower expression of NK-specific genes (KLRB1, KLRC2, KLRC3, KLRD1, and KLRK1) and cytotoxicity-related genes (GzmB, CD226, CD247, and LCK), indicative of decreased NK cell activity in the cancer population [70].
NK cell phenotype and frequency are potential prognostic cancer biomarkers. Alterations in receptor expression, assessed using flow cytometry and PCR, provide prognostic insights across diverse cancers. Reduced expression of activating receptors (NKp30, NKp46, NKG2D, and DNAM-1) was associated with disease progression in GC, although it correlated with decreased overall survival in non-small cell lung cancer [71]. Similarly, upregulation of inhibitory receptors (including CD94/NKG2A) was associated with poor prognosis in patients with HCC [72]. In patients with CRC, the frequencies of CD3+CD56+ and CD3–CD56+ NK cells are significantly lower in metastatic liver tissues than in non-metastatic liver tissues (CD3+CD56+, 11.9±10.3 vs. 24.2± 13.6%, P=0.02; CD3–CD56+ cells, 10.1±11.6 vs. 16.6±8.9%, P=0.039), underscoring their prognostic relevance [73].
Recent investigations of genetic biomarkers associated with NK cells have identified novel candidates for therapeutic monitoring. Analyses of data obtained from single-cell sequencing and bulk RNA sequencing identified 12 NK cell-associated gene signatures in GC, from which risk scores were calculated using a defined algorithm [74]. Patients at high risk showed low immune cell infiltration, whereas patients at low risk demonstrated higher immune cell infiltration (particularly NK and CD8+ T cells) and consequently responded better to immunotherapy. Similar gene-based approaches have been applied in HCC to predict responses to immune checkpoint inhibitors [75]. The low-risk group, defined by NK cell-associated prognostic gene signatures, show lower NK dysfunction scores and more favorable responses to immune checkpoint inhibitors. With the advent of massive RNA-sequencing datasets from cancer immunotherapy studies and advances in artificial intelligence-based machine learning, RNA sequencing assays are poised to be more pivotal for assessing immune function and predicting therapeutic efficacy, thereby contributing to development of personalized treatment strategies.

Biomarkers for infectious diseases

NK cell assays can be clinically applied for early detection, prognosis, and therapeutic monitoring of infectious diseases [8]. Increased NK cell frequency and activity indicate acute infection caused by pathogens in otherwise healthy individuals, thereby aiding in diagnosis [76]. In patients with variable immunodeficiency, low circulating NK cell frequencies are associated with severe complications, including invasive infection, infectious pneumonia, and sepsis [77]. Thus, measuring NK cell frequency helps evaluate their protective role in preventing infection and related severe complications before adaptive immune response activation. In hepatitis C, Knapp et al. [78] demonstrated that KIR2DL3: HLA-C1 homozygosity, confirmed using RT-PCR, was more frequent in exposed but uninfected individuals (spontaneous resolvers) than in those with chronic hepatitis C (31.1% vs. 13.3%, P=0.0008, odds ratio=2.95, 95% CI: 1.59–5.49). This genetic profile was associated with enhanced NK cell degranulation in spontaneous resolvers, suggesting a protective role against progression to chronic infection.
Assessing the NK cell phenotype via flow cytometry, together with NK cell functional assays, can enable monitoring of infectious disease progression and immune responses following therapeutic interventions. In acute hepatitis C, the frequency of circulating CD56dim NK cells decreased, whereas the proportion of CD56bright NK cells increased, compared with the corresponding levels in healthy individuals [79]. In chronic hepatitis C, persistent antigen stimulation enhanced NK cell cytotoxic activity while impairing IFN-γ and TNF-α production [80]. Similarly, in coronavirus disease 2019 (COVID-19), NK cells showed upregulated expression of activation biomarkers, including CD38, HLA-DR, and CD69 [81]. Persistent severe acute respiratory syndrome coronavirus 2 exposure was associated with expansion of functionally exhausted CD56dimCD16– and CD56–CD16+ subsets, resulting in attenuated effector function and delayed NK cell recovery [82]. An increased frequency of CD56bright NK cells expressing TNF-related apoptosis-inducing ligand (TRAIL), a biomarker of type-I IFNs, was associated with favorable therapeutic responses to pegylated IFN-α treatment in patients with chronic hepatitis B [83]. Notably, in patients showing early NK cell responses, 61% of CD56bright NK cells expressed TRAIL within 6 hrs after the initial pegylated IFN-α treatment. These findings supported a greater decline in HBsAg levels, compared with those in non-responders. As research on NK cell phenotype, frequency, and function expands across infectious diseases, the clinical value of NK cell assays is expected to increase. Clinical applications of NK cell assays are becoming increasingly recognized as promising tools for refining diagnostic and therapeutic strategies.

Biomarkers for autoimmune diseases

NK cells play bifunctional roles in the pathogenesis of autoimmune diseases—mediating either protective immune regulation or pathogenic immune-mediated damage—depending on their phenotype, the surrounding microenvironment, and the specific diseases involved [84]. Certain NK cell subsets exert protective effects by eliminating immature dendritic cells and autoreactive lymphocytes or by suppressing NK activation via IL-10 secretion [85]. In contrast, pathogenic NK cells contribute to tissue injury by modulating cytotoxic activity, activating and inhibitory receptors, and cytokine production in target autologous cells [6]. Cytotoxicity assays (such as 51Cr-release assays, LDH-release assays, and CD107a-based degranulation assays) have been used to diagnose systemic lupus erythematosus and type 1 diabetes mellitus [86, 87]. Alterations in CD56bright/CD56dim ratios, activating and inhibitory receptors, and chemokine receptors (CX3CR1 and CXCR4) have been assessed via flow cytometry to support the diagnosis of systemic lupus erythematosus or rheumatoid arthritis [88, 89]. Beyond diagnostic applications, the NK cell: CD4+ T cell ratio has been proposed as a prognostic biomarker for predicting disease activity in multiple sclerosis [90]. Recent advances have facilitated NK cell activity measurements in autoimmune diseases through diverse approaches. Cytokine-quantification methods (e.g., ELISA, multiplex bead-based assays, and single-cell RNA sequencing) have been developed to evaluate pro-inflammatory cytokines (e.g., IL-15, IFN-γ, and TNF-α) and regulatory effects mediated by IL-10 [89]. Integrating results from these complementary NK cell assays enable researchers and clinicians to improve the clinical outcomes of the autoimmune diseases.

Biomarkers for reproductive disorders

During early pregnancy, NK cells constitute up to 70% of immune cells in the uterine decidua [91]. Under physiological pregnancy conditions, uterine NK (uNK) cells play crucial roles in immune tolerance, angiogenesis, and fetal development by secreting cytokines, such as vascular endothelial growth factor, IL-8, and IFN-γ [91]. In contrast, under pathological pregnancy conditions, including infertility and recurrent miscarriage (RM), the role of NK cells remains controversial [92]. Some data demonstrate that reduced uNK frequency or activity impaired placentation and resulted in adverse pregnancy outcomes. In contrast, other findings suggest that excessive uNK activity may contribute to pregnancy failure, partly through oxidative stress associated with early placental circulation [93]. Bagkou Dimakou et al. [94] reported that women with RM showed NK cell elevation in the PB and increased degranulation, although they were not accompanied by enhanced cytotoxicity, suggesting a complex state of immune dysregulation. Mass cytometry revealed reduced expression of human leukocyte antigen (HLA)-specific inhibitory receptors (e.g., KIRs and NKG2A, which interact with trophoblast HLA-C, HLA-E, and HLA-G) and decreased abundance of chemokine receptor CXCR3/CXCR4+ NK cell subsets associated with uterine migration, suggesting them as potential biomarkers for RM risk.
However, clinical applications involving uNK cells and PB NK cells have limitations. Although uNK cell analysis is potentially valuable for clinical decision-making, standardized reference intervals to define abnormal uNK cell levels or activity have not been established [95]. In the case of PB NK cells, substantial inter-individual variability was observed among healthy individuals and influenced by stress, hormonal changes, and the endometrial microenvironment, confounding data interpretation [96]. Reflecting these challenges, the American Society of Reproductive Medicine guidelines do not recommend NK cell assays or related immunological treatments as diagnostic or prognostic tools for reproductive disorders [97]. These findings highlight the potential of advanced diagnostic and prognostic platforms in reproductive disorders, as well as the limitations of conventional NK cell assays. Further research is required to clarify the functional roles of NK cells in reproductive disorders and establish standardized, evidence-based guidelines for clinical assessment.

Health screening and beyond

In clinical practice, the expenses associated with NK cell assays, including commercial IFN-γ release–based platforms (e.g., NK Vue), are reimbursed under the national health insurance system in Korea; however, the level of coverage is very limited. For certain indication such as prostate cancer, only about 10% of the total cost is covered by insurance, leaving approximately 90% as patient out-of-pocket payment. These assays have been primarily prescribed to healthy individuals during routine health screening programs and to patients with cancer for therapeutic monitoring, where NK cell activity serves as a supportive biomarker. The availability of insurance support has facilitated broader clinical applications, particularly in preventive medicine [98]. In a study involving 1,818 asymptomatic individuals undergoing health screening, NK cell assays performed using the NK Vue Kit concurrently with colonoscopy helped identify 245 cases of adenoma and 12 cases of advanced adenoma and revealed that NK cell activity declined with CRC progression [99].
Beyond cancer, NK cell activity is associated with lifestyle factors, metabolic status, and physical exercise. Low NK cell activity is associated with elevated blood pressure and an increased risk of hypertension, potentially mediated by endothelial dysfunction and vascular inflammation [100]. In a longitudinal cohort, Lee et al. [100] demonstrated that individuals with IFN-γ levels of <300 pg/mL had a 1.6-fold higher risk of developing hypertension over 2.13 yrs than did those with IFN-γ levels of >1,700 pg/mL (hazard ratio 0.625, P=0.042). Similarly, a large-scale study revealed that reduced NK cell activity was correlated with metabolic abnormalities, including elevated HbA1c, reduced HDL cholesterol, and extreme body mass index values [101]. Physical exercise can increase the NK cell frequency, depending on the intensity and duration; however, the relationship between NK cell function and exercise remains controversial [102]. Taken together, these findings suggest that measuring NK cell activities could provide clinically useful information in health screening programs and serve as indicators of pathological and physiological states. However, given that NK cell activity is influenced by both diseases and normal physiological variations, careful consideration of these confounding factors is essential to ensure accurate interpretation and optimize their clinical utility.

CONCLUSION

Advanced research on NK cells is currently focused on expanding the clinical applications of NK cell assays [103]. Innovations in flow cytometry, next-generation immunophenotyping, single-cell multi-omics, and artificial intelligence-driven analysis are expected to improve the diagnostic and prognostic utility of NK cell assays, and clinically, NK cell functional assays have historically played an important role in HLH diagnosis. Although recent guidelines have placed less emphasis on NK cell activity, they remain relevant in terms of HLH and continue to provide biological insights. Beyond HLH, NK cell assays show promise for application in various conditions, including cancer, infections, autoimmune diseases, reproductive disorders, and health screening programs [104].
However, some challenges remain, particularly regarding the methodological diversity and variability in reference intervals across institutions. Differences among cytotoxicity assays, cytokine release assays, and commercial kits highlight the need for greater harmonization to ensure consistent interpretation. Ongoing efforts to establish standardized protocols and validated reference intervals are expected to enhance the reliability and clinical applicability of NK cell assays. Nevertheless, challenges related to standardization, reproducibility, and physiological variability underscore the necessity for large-scale prospective studies to ensure their robust implementation in both research and clinical settings.
In conclusion, NK cell assays continue to evolve as a crucial link between basic immunology and clinical practice, with the potential to advance diagnosis, prognosis, and therapeutic monitoring across a broad spectrum of diseases.

ACKNOWLEDGEMENTS

None.

Notes

AUTHOR CONTRIBUTIONS

Nam M contributed to writing (original draft, review, and editing); Nam M and Park W were involved in investigation; Kim HY contributed to project supervision and writing (review and editing); Cho D contributed to conceptualization, project administration, supervision, and writing (review and editing).

CONFLICTS OF INTEREST

None declared.

RESEARCH FUNDING

This research was supported by the National Research Foundation of Korea (NRF), funded by the Korea Government (MSIT) (Grant Nos. RS-2023-00242443, RS-2024-00345126, and RS-2025-00519514), a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health and Welfare, Korea (Grant No. KH129441), and the Future Medicine 2030 Project of the Samsung Medical Center (Grant No. SMO1250091).

REFERENCES

1. Vivier E, Artis D, Colonna M, Diefenbach A, Di Santo JP, Eberl G, et al. 2018; Innate lymphoid cells: 10 years on. Cell. 174:1054–66. DOI: 10.1016/j.cell.2018.07.017. PMID: 30142344. PMCID: PMC10879818.
2. Fauriat C, Long EO, Ljunggren HG, Bryceson YT. 2010; Regulation of human NK-cell cytokine and chemokine production by target cell recognition. Blood. 115:2167–76. DOI: 10.1182/blood-2009-08-238469. PMID: 19965656. PMCID: PMC2844017.
3. Rebuffet L, Melsen JE, Escalière B, Basurto-Lozada D, Bhandoola A, Björkström NK, et al. 2024; High-dimensional single-cell analysis of human natural killer cell heterogeneity. Nat Immunol. 25:1474–88. DOI: 10.1038/s41590-024-01883-0. PMID: 38956378. PMCID: PMC11291291.
4. Henter JI, Horne A, Aricó M, Egeler RM, Filipovich AH, Imashuku S, et al. 2007; HLH-2004: diagnostic and therapeutic guidelines for hemophagocytic lymphohistiocytosis. Pediatr Blood Cancer. 48:124–31. DOI: 10.1002/pbc.21039. PMID: 16937360.
5. Zoref-Lorenz A, Murakami J, Hofstetter L, Iyer S, Alotaibi AS, Mohamed SF, et al. 2022; An improved index for diagnosis and mortality prediction in malignancy-associated hemophagocytic lymphohistiocytosis. Blood. 139:1098–110. DOI: 10.1182/blood.2021012764. PMID: 34780598. PMCID: PMC8854682.
6. Kucuksezer UC, Aktas Cetin E, Esen F, Tahrali I, Akdeniz N, Gelmez MY, et al. 2021; The role of natural killer cells in autoimmune diseases. Front Immunol. 12:622306. DOI: 10.3389/fimmu.2021.622306. PMID: 33717125. PMCID: PMC7947192. PMID: a03e8658da3e4737b83ecde589b7c474.
7. Coënon L, Geindreau M, Ghiringhelli F, Villalba M, Bruchard M. 2024; Natural killer cells at the frontline in the fight against cancer. Cell Death Dis. 15:614. DOI: 10.1038/s41419-024-06976-0. PMID: 39179536. PMCID: PMC11343846. PMID: 15c25e138a824336be3bad4ad2ceda72.
8. Björkström NK, Strunz B, Ljunggren HG. 2022; Natural killer cells in antiviral immunity. Nat Rev Immunol. 22:112–23. DOI: 10.1038/s41577-021-00558-3. PMID: 34117484. PMCID: PMC8194386.
9. Freud AG, Mundy-Bosse BL, Yu J, Caligiuri MA. 2017; The broad spectrum of human natural killer cell diversity. Immunity. 47:820–33. DOI: 10.1016/j.immuni.2017.10.008. PMID: 29166586. PMCID: PMC5728700.
10. Bernardini G, Gismondi A, Santoni A. 2012; Chemokines and NK cells: Regulators of development, trafficking and functions. Immunol Lett. 145:39–46. DOI: 10.1016/j.imlet.2012.04.014. PMID: 22698182. PMCID: PMC7112821.
11. Xie M, Li Y, Meng YZ, Xu P, Yang YG, Dong S, et al. 2022; Uterine natural killer cells: A rising star in human pregnancy regulation. Front Immunol. 13:918550. DOI: 10.3389/fimmu.2022.918550. PMID: 35720413. PMCID: PMC9198966. PMID: 8eda05ba89074622b67d0519b0afe773.
12. Peng H, Sun R. 2017; Liver-resident NK cells and their potential functions. Cell Mol Immunol. 14:890–4. DOI: 10.1038/cmi.2017.72. PMID: 28920584. PMCID: PMC5675959.
13. Liu S, Dhar P, Wu JD. 2019; NK cell plasticity in cancer. J Clin Med. 8:1492. DOI: 10.3390/jcm8091492. PMID: 31546818. PMCID: PMC6780970.
14. Albini A, Noonan DM. 2021; Decidual-like NK cell polarization: From cancer killing to cancer nurturing. Cancer Discov. 11:28–33. DOI: 10.1158/2159-8290.CD-20-0796. PMID: 33277305.
15. Parisi L, Bassani B, Tremolati M, Gini E, Farronato G, Bruno A. 2017; Natural killer cells in the orchestration of chronic inflammatory diseases. J Immunol Res. 2017:4218254. DOI: 10.1155/2017/4218254. PMID: 28428965. PMCID: PMC5385901. PMID: 59c8501204514f36af3449c4948cf36f.
16. Tognarelli S, Jacobs B, Staiger N, Ullrich E. 2016; Flow cytometry-based assay for the monitoring of NK cell functions. J Vis Exp. 116:54615. DOI: 10.3791/54615-v. PMID: 27842341. PMCID: PMC5226117.
17. Pegram HJ, Andrews DM, Smyth MJ, Darcy PK, Kershaw MH. 2011; Activating and inhibitory receptors of natural killer cells. Immunol Cell Biol. 89:216–24. DOI: 10.1038/icb.2010.78. PMID: 20567250.
18. Borrego F, Robertson MJ, Ritz J, Peña J, Solana R. 1999; CD69 is a stimulatory receptor for natural killer cell and its cytotoxic effect is blocked by CD94 inhibitory receptor. Immunology. 97:159–65. DOI: 10.1046/j.1365-2567.1999.00738.x. PMID: 10447727. PMCID: PMC2326810.
19. Gu Y, Bi Y, Huang Z, Liao C, Li X, Hu H, et al. 2025; CD69 expression is negatively associated with T-cell immunity and predicts antiviral therapy response in chronic hepatitis B. Ann Lab Med. 45:185–98. DOI: 10.3343/alm.2024.0178. PMID: 39703148. PMCID: PMC11788699.
20. Christensen EB, Schaefer M, Barnkob MB, Nielsen C, Barington T. 2025; OMIP-115: High-dimensional phenotypic characterization of human natural killer cells for therapeutic use. Cytometry A. 107:372–7. DOI: 10.1002/cyto.a.24941. PMID: 40452362.
21. Shin KH, Choi HW, Lim J, Kang ES. 2026; Reference values for extended lymphocyte subsets in Korean children: a multicenter study using the EuroFlow PIDOT panel. Ann Lab Med. 46:297–308. DOI: 10.3343/alm.2025.0241. PMID: 41220249.
22. Kay AW, Strauss-Albee DM, Blish CA. 2016; Application of mass cytometry (CyTOF) for functional and phenotypic analysis of natural killer cells. Methods Mol Biol. 1441:13–26. DOI: 10.1007/978-1-4939-3684-7_2. PMID: 27177653. PMCID: PMC5304457.
23. Elsner L, Dressel R. 2020; 51Cr-release to monitor NK cell cytotoxicity. Methods Enzymol. 631:497–512. DOI: 10.1016/bs.mie.2019.05.037. PMID: 31948566.
24. Lichtenfels R, Biddison WE, Schulz H, Vogt AB, Martin R. 1994; CARE-LASS (calcein-release-assay), an improved fluorescence-based test system to measure cytotoxic T lymphocyte activity. J Immunol Methods. 172:227–39. DOI: 10.1016/0022-1759(94)90110-4. PMID: 7518485.
25. Neri S, Mariani E, Meneghetti A, Cattini L, Facchini A. 2001; Calcein-acetyoxymethyl cytotoxicity assay: Standardization of a method allowing additional analyses on recovered effector cells and supernatants. Clin Diagn Lab Immunol. 8:1131–5. DOI: 10.1128/CDLI.8.6.1131-1135.2001. PMID: 11687452. PMCID: PMC96238.
26. Jang YY, Cho D, Kim SK, Shin DJ, Park MH, Lee JJ, et al. 2012; An improved flow cytometry-based natural killer cytotoxicity assay involving calcein AM staining of effector cells. Ann Clin Lab Sci. 42:42–9. PMID: 22371909.
27. Weyermann J, Lochmann D, Zimmer A. 2005; A practical note on the use of cytotoxicity assays. Int J Pharm. 288:369–76. DOI: 10.1016/j.ijpharm.2004.09.018. PMID: 15620877.
28. Tanito K, Oshiro Y, Tagawa H, Kishlmura A, Mori T, Katayama Y. 2021; Comparative evaluation of natural killer cell-mediated cell killing assay based on the leakage of an endogenous enzyme or a pre-loaded fluorophore. Anal Sci. 37:1571–5. DOI: 10.2116/analsci.21P117. PMID: 33967183.
29. Cho MH, Niles A, Huang R, Inglese J, Austin CP, Riss T, et al. 2008; A bioluminescent cytotoxicity assay for assessment of membrane integrity using a proteolytic biomarker. Toxicol In Vitro. 22:1099–106. DOI: 10.1016/j.tiv.2008.02.013. PMID: 18400464. PMCID: PMC2386563.
30. Alshehade SA, Almoustafa HA, Alshawsh MA, Chik Z. 2024; Flow cytometry-based quantitative analysis of cellular protein expression in apoptosis subpopulations: A protocol. Heliyon. 10:e33665. DOI: 10.1016/j.heliyon.2024.e33665. PMID: 39040270. PMCID: PMC11260931. PMID: 2232aff808064583bd47907a0608d591.
31. Zimmermann SY, Esser R, Rohrbach E, Klingebiel T, Koehl U. 2005; A novel four-colour flow cytometric assay to determine natural killer cell or T-cell-mediated cellular cytotoxicity against leukaemic cells in peripheral or bone marrow specimens containing greater than 20% of normal cells. J Immunol Methods. 296:63–76. DOI: 10.1016/j.jim.2004.10.014. PMID: 15680151.
32. Veluchamy JP, Delso-Vallejo M, Kok N, Bohme F, Seggewiss-Bernhardt R, van der Vliet HJ, et al. 2017; Standardized and flexible eight colour flow cytometry panels harmonized between different laboratories to study human NK cell phenotype and function. Sci Rep. 7:43873. DOI: 10.1038/srep43873. PMID: 28281564. PMCID: PMC5345017.
33. Ryu J, Choi J, Kim M, Cho YU, Hwang SH, Jang S, et al. 2023; Suitability of EDTA-anticoagulated blood for natural killer cell activity testing using flow cytometry. Ann Lab Med. 43:307–9. DOI: 10.3343/alm.2023.43.3.307. PMID: 36544345. PMCID: PMC9791016.
34. Kim J, Phan MT, Kweon S, Yu H, Park J, Kim KH, et al. 2020; A flow cytometry-based whole blood natural killer cell cytotoxicity assay using overnight cytokine activation. Front Immunol. 11:1851. DOI: 10.3389/fimmu.2020.01851. PMID: 32922399. PMCID: PMC7457041. PMID: ed9a150f52e040a9877f273015c07885.
35. Krzewski K, Coligan JE. 2012; Human NK cell lytic granules and regulation of their exocytosis. Front Immunol. 3:335. DOI: 10.3389/fimmu.2012.00335. PMID: 23162553. PMCID: PMC3494098. PMID: 705684a326a54e7bab5851a0bec0ccc1.
36. Krzewski K, Gil-Krzewska A, Nguyen V, Peruzzi G, Coligan JE. 2013; LAMP1/CD107a is required for efficient perforin delivery to lytic granules and NK-cell cytotoxicity. Blood. 121:4672–83. DOI: 10.1182/blood-2012-08-453738. PMID: 23632890. PMCID: PMC3674668.
37. Alter G, Malenfant JM, Altfeld M. 2004; CD107a as a functional marker for the identification of natural killer cell activity. J Immunol Methods. 294:15–22. DOI: 10.1016/j.jim.2004.08.008. PMID: 15604012.
38. Kalyuzhny AE. 2005; Handbook of ELISPOT. Methods in Molecular Biology. 302:323. DOI: 10.1385/1592599036.
39. Chiswick EL, Duffy E, Japp B, Remick D. 2012; Detection and quantification of cytokines and other biomarkers. Methods Mol Biol. 844:15–30. DOI: 10.1007/978-1-61779-527-5_2. PMID: 22262432. PMCID: PMC5659280.
40. Long EO, Kim HS, Liu D, Peterson ME, Rajagopalan S. 2013; Controlling natural killer cell responses: Integration of signals for activation and inhibition. Annu Rev Immunol. 31:227–58. DOI: 10.1146/annurev-immunol-020711-075005. PMID: 23516982. PMCID: PMC3868343.
41. Lee SB, Cha J, Kim IK, Yoon JC, Lee HJ, Park SW, et al. 2014; A high-throughput assay of NK cell activity in whole blood and its clinical application. Biochem Biophys Res Commun. 445:584–90. DOI: 10.1016/j.bbrc.2014.02.040. PMID: 24561245.
42. Nederby L, Jakobsen A, Hokland M, Hansen TF. 2018; Quantification of NK cell activity using whole blood: Methodological aspects of a new test. J Immunol Methods. 458:21–5. DOI: 10.1016/j.jim.2018.04.002. PMID: 29654815.
43. Choi SI, Lee SH, Park JY, Kim KA, Lee EJ, Lee SY, et al. 2019; Clinical utility of a novel natural killer cell activity assay for diagnosing non-small cell lung cancer: A prospective pilot study. Onco Targets Ther. 12:1661–9. DOI: 10.2147/OTT.S194473. PMID: 30881021. PMCID: PMC6398406.
44. Gunesch JT, Angelo LS, Mahapatra S, Deering RP, Kowalko JE, Sleiman P, et al. 2019; Genome-wide analyses and functional profiling of human NK cell lines. Mol Immunol. 115:64–75. DOI: 10.1016/j.molimm.2018.07.015. PMID: 30054012. PMCID: PMC6345623.
45. Mitsunaga F, Nakamura S. 2021; A sensitive and simple method to assess NK cell activity by RT-qPCR for granzyme B using spleen and blood. J Biosci Med. 9:27–38. DOI: 10.4236/jbm.2021.93004.
46. Nishimura Y, Kumagai-Takei N, Lee S, Matsuzaki H, Yoshiotme K, Otsuki T. Aribi M, editor. 2017. A new method to determine natural killer cell activity without target cells. Natural killer cells. IntechOpen;Rijeka: DOI: 10.5772/intechopen.71912.
47. Liu Z, Lavis LD, Betzig E. 2015; Imaging live-cell dynamics and structure at the single-molecule level. Mol Cell. 58:644–59. DOI: 10.1016/j.molcel.2015.02.033. PMID: 26000849.
48. Choi PJ, Mitchison TJ. 2013; Imaging burst kinetics and spatial coordination during serial killing by single natural killer cells. Proc Natl Acad Sci U S A. 110:6488–93. DOI: 10.1073/pnas.1221312110. PMID: 23576740. PMCID: PMC3631668.
49. Martinez AL, Shannon MJ, Eisman SE, Hegewisch-Solloa E, Asif AN, Ebrahim TAM, et al. 2022; Quantifying human natural killer cell migration by imaging and image analysis. Methods Mol Biol. 2463:129–51. DOI: 10.1007/978-1-0716-2160-8_10. PMID: 35344172. PMCID: PMC9159076.
50. Tran T, Galdina V, Urquidi O, Reis Galvão D, Rieben R, Adachi TBM, et al. 2024; Assessment of NK cytotoxicity and interactions with porcine endothelial cells by live-cell imaging in 2D static and 3D microfluidic systems. Sci Rep. 14:24199. DOI: 10.1038/s41598-024-75217-3. PMID: 39406778. PMCID: PMC11480498. PMID: b1361822f9134694ada866d6f34d8415.
51. Shin HS, Park J, Lee SY, Yun HG, Kim B, Kim J, et al. 2023; Integrative magneto-microfluidic separation of immune cells facilitates clinical functional assays. Small. 19:e2302809. DOI: 10.1002/smll.202302809. PMID: 37365959.
52. Park J, Shin Y, Kim JM, Kweon S, Song AY, Baek Y, et al. 2021; Multifunctional microparticles with stimulation and sensing capabilities for facile NK cell activity assay. ACS Sens. 6:693–7. DOI: 10.1021/acssensors.0c02138. PMID: 33606518.
53. Sztajnbok F, Fonseca AR, Campos LR, Lino K, Rodrigues MCF, Silva RM, et al. 2024; Hemophagocytic lymphohistiocytosis and macrophage activation syndrome: two rare sides of the same devastating coin. Adv Rheumatol. 64:28. DOI: 10.1186/s42358-024-00370-2. PMID: 38627860. PMID: df8667ebfca942c4920033bc5f49547e.
54. Risma K, Jordan MB. 2012; Hemophagocytic lymphohistiocytosis: updates and evolving concepts. Curr Opin Pediatr. 24:9–15. DOI: 10.1097/MOP.0b013e32834ec9c1. PMID: 22189397. PMCID: PMC10515965.
55. Zhang J, Sun Y, Shi X, Zhang R, Wang Y, Xiao J, et al. 2020; Genotype characteristics and immunological indicator evaluation of 311 hemophagocytic lymphohistiocytosis cases in China. Orphanet J Rare Dis. 15:112. DOI: 10.1186/s13023-020-01390-z. PMID: 32375849. PMCID: PMC7201972. PMID: e615883b20ba4370843b93b602c4ce43.
56. Ramos-Casals M, Brito-Zerón P, López-Guillermo A, Khamashta MA, Bosch X. 2014; Adult haemophagocytic syndrome. Lancet. 383:1503–16. DOI: 10.1016/S0140-6736(13)61048-X. PMID: 24290661.
57. Filipovich AH. 2009; Hemophagocytic lymphohistiocytosis (HLH) and related disorders. Hematology Am Soc Hematol Educ Program. 127–31. DOI: 10.1182/asheducation-2009.1.127. PMID: 20008190.
58. Chiang SCC, Bleesing JJ, Marsh RA. 2019; Current flow cytometric assays for the screening and diagnosis of primary HLH. Front Immunol. 10:1740. DOI: 10.3389/fimmu.2019.01740. PMID: 31396234. PMCID: PMC6664088. PMID: e7fd498508f34ab393d96f2b97adbe2a.
59. Chung HJ, Park CJ, Lim JH, Jang S, Chi HS, Im HJ, et al. 2010; Establishment of a reference interval for natural killer cell activity through flow cytometry and its clinical application in the diagnosis of hemophagocytic lymphohistiocytosis. Int J Lab Hematol. 32:239–47. DOI: 10.1111/j.1751-553X.2009.01177.x. PMID: 19614711.
60. Oh EJ, Yoon JH, Park KH, Bae HJ, Yun SJ, Min GJ, et al. 2021; Natural-killer cell cytotoxicity as a diagnostic and prognostic marker for adult patients with secondary hemophagocytic lymphohistiocytosis: A prospective phase II observational study. Ther Adv Hematol. 12:20406207211020544. DOI: 10.1177/20406207211020544. PMID: 34104375. PMCID: PMC8172956. PMID: d474cdadf1c448ba96638e6e59502bb3.
61. Hayden A, Lin M, Park S, Pudek M, Schneider M, Jordan MB, et al. 2017; Soluble interleukin-2 receptor is a sensitive diagnostic test in adult HLH. Blood Adv. 1:2529–34. DOI: 10.1182/bloodadvances.2017012310. PMID: 29296904. PMCID: PMC5728644. PMID: f0a1c3366c91438ca120f9581c9d23c8.
62. Yoon SE, Eun Y, Huh K, Chung CR, Yoo IY, Cho J, et al. 2020; A comprehensive analysis of adult patients with secondary hemophagocytic lymphohistiocytosis: A prospective cohort study. Ann Hematol. 99:2095–104. DOI: 10.1007/s00277-020-04083-6. PMID: 32440790.
63. Henter JI, Sieni E, Eriksson J, Bergsten E, Hed Myrberg I, Canna SW, et al. 2024; Diagnostic guidelines for familial hemophagocytic lymphohistiocytosis revisited. Blood. 144:2308–18. DOI: 10.1182/blood.2024025077. PMID: 39046779. PMCID: PMC11619794.
64. Kiessling R, Klein E, Pross H, Wigzell H. 1975; "Natural" killer cells in the mouse. II. Cytotoxic cells with specificity for mouse Moloney leukemia cells. Characteristics of the killer cell. Eur J Immunol. 5:117–21. DOI: 10.1002/eji.1830050209. PMID: 1086218.
65. Nersesian S, Schwartz SL, Grantham SR, MacLean LK, Lee SN, Pugh-Toole M, et al. 2021; NK cell infiltration is associated with improved overall survival in solid cancers: A systematic review and meta-analysis. Transl Oncol. 14:100930. DOI: 10.1016/j.tranon.2020.100930. PMID: 33186888. PMCID: PMC7670197. PMID: 459862dc86a0479cbd9e1017de842184.
66. Mamessier E, Pradel LC, Thibult ML, Drevet C, Zouine A, Jacquemier J, et al. 2013; Peripheral blood NK cells from breast cancer patients are tumor-induced composite subsets. J Immunol. 190:2424–36. DOI: 10.4049/jimmunol.1200140. PMID: 23359508.
67. Stegmann KA, Robertson F, Hansi N, Gill U, Pallant C, Christophides T, et al. 2016; CXCR6 marks a novel subset of T-betloEomeshi natural killer cells residing in human liver. Sci Rep. 6:26157. DOI: 10.1038/srep26157. PMID: 27210614. PMCID: PMC4876507.
68. Lee J, Park KH, Ryu JH, Bae HJ, Choi A, Lee H, et al. 2017; Natural killer cell activity for IFN-gamma production as a supportive diagnostic marker for gastric cancer. Oncotarget. 8:70431–40. DOI: 10.18632/oncotarget.19712. PMID: 29050291. PMCID: PMC5642566.
69. Furue H, Matsuo K, Kumimoto H, Hiraki A, Suzuki T, Yatabe Y, et al. 2008; Decreased risk of colorectal cancer with the high natural killer cell activity NKG2D genotype in Japanese. Carcinogenesis. 29:316–20. DOI: 10.1093/carcin/bgm260. PMID: 18174257.
70. Xu Y, Xu Q, Ni S, Liu F, Cai G, Wu F, et al. 2011; Decrease in natural killer cell associated gene expression as a major characteristic of the immune status in the bloodstream of colorectal cancer patients. Cancer Biol Ther. 11:188–95. DOI: 10.4161/cbt.11.2.13670. PMID: 20962596.
71. Han B, Mao FY, Zhao YL, Lv YP, Teng YS, Duan M, et al. 2018; Altered NKp30, NKp46, NKG2D, and DNAM-1 expression on circulating NK cells is associated with tumor progression in human gastric cancer. J Immunol Res. 2018:6248590. DOI: 10.1155/2018/6248590. PMID: 30255106. PMCID: PMC6140275. PMID: b34ac744ccf8477da76410edb5c91e13.
72. Sun C, Xu J, Huang Q, Huang M, Wen H, Zhang C, et al. 2016; High NKG2A expression contributes to NK cell exhaustion and predicts a poor prognosis of patients with liver cancer. Oncoimmunology. 6:e1264562. DOI: 10.1080/2162402X.2016.1264562. PMID: 28197391. PMCID: PMC5283631.
73. Gulubova M, Manolova I, Kyurkchiev D, Julianov A, Altunkova I. 2009; Decrease in intrahepatic CD56+ lymphocytes in gastric and colorectal cancer patients with liver metastases. APMIS. 117:870–9. DOI: 10.1111/j.1600-0463.2009.02547.x. PMID: 20078551.
74. Sun JR, Kong CF, Ye YX, Wang Q, Qu XK, Jia LQ, et al. 2024; Integrated analysis of single-cell and bulk RNA-sequencing reveals a novel signature based on NK cell marker genes to predict prognosis and immunotherapy response in gastric cancer. Sci Rep. 14:7648. DOI: 10.1038/s41598-024-57714-7. PMID: 38561388. PMCID: PMC10985121. PMID: 4cb2a6c64beb4f6eb4c7b8d679022cc4.
75. Yang Y, She S, Ren L, Zhao B, Chen D, Chen H. 2023; Prognosis and therapeutic benefits prediction based on NK cell marker genes through single-cell RNA-seq with integrated bulk RNA-seq analysis for hepatocellular carcinoma. Front Oncol. 13:1208165. DOI: 10.3389/fonc.2023.1208165. PMID: 37554171. PMCID: PMC10406383. PMID: bdce064dc8d74808bc8d830f05adffdb.
76. Björkström NK, Lindgren T, Stoltz M, Fauriat C, Braun M, Evander M, et al. 2011; Rapid expansion and long-term persistence of elevated NK cell numbers in humans infected with hantavirus. J Exp Med. 208:13–21. DOI: 10.1084/jem.20100762. PMID: 21173105. PMCID: PMC3023129.
77. Ebbo M, Gérard L, Carpentier S, Vély F, Cypowyj S, Farnarier C, et al. 2016; Low circulating natural killer cell counts are associated with severe disease in patients with common variable immunodeficiency. EBioMedicine. 6:222–30. DOI: 10.1016/j.ebiom.2016.02.025. PMID: 27211564. PMCID: PMC4856746.
78. Knapp S, Warshow U, Ho KM, Hegazy D, Little AM, Fowell A, et al. 2011; A polymorphism in IL28B distinguishes exposed, uninfected individuals from spontaneous resolvers of HCV infection. Gastroenterology. 141:320–5.e1. DOI: 10.1053/j.gastro.2011.04.005. PMID: 21600205. PMCID: PMC3194089.
79. Alter G, Jost S, Rihn S, Reyor LL, Nolan BE, Ghebremichael M, et al. 2011; Reduced frequencies of NKp30+NKp46+, CD161+, and NKG2D+ NK cells in acute HCV infection may predict viral clearance. J Hepatol. 55:278–88. DOI: 10.1016/j.jhep.2010.11.030. PMID: 21168454. PMCID: PMC3729214.
80. Dessouki O, Kamiya Y, Nagahama H, Tanaka M, Suzu S, Sasaki Y, et al. 2010; Chronic hepatitis C viral infection reduces NK cell frequency and suppresses cytokine secretion: Reversion by anti-viral treatment. Biochem Biophys Res Commun. 393:331–7. DOI: 10.1016/j.bbrc.2010.02.008. PMID: 20138830.
81. Krämer B, Knoll R, Bonaguro L, ToVinh M, Raabe J, Astaburuaga-García R, et al. 2021; Early IFN-α signatures and persistent dysfunction are distinguishing features of NK cells in severe COVID-19. Immunity. 54:2650–69.e14. DOI: 10.1016/j.immuni.2021.09.002. PMID: 34592166. PMCID: PMC8416549.
82. Li M, Guo W, Dong Y, Wang X, Dai D, Liu X, et al. 2020; Elevated exhaustion levels of NK and CD8+ T cells as indicators for progression and prognosis of COVID-19 disease. Front Immunol. 11:580237. DOI: 10.3389/fimmu.2020.580237. PMID: 33154753. PMCID: PMC7591707. PMID: 4be8262569464d688ed9c799c57c1fff.
83. Nishio A, Bolte FJ, Takeda K, Park N, Yu ZX, Park H, et al. 2021; Clearance of pegylated interferon by Kupffer cells limits NK cell activation and therapy response of patients with HBV infection. Sci Transl Med. 13:eaba6322. DOI: 10.1126/scitranslmed.aba6322. PMID: 33790025. PMCID: PMC12109059.
84. Liu M, Liang S, Zhang C. 2021; NK cells in autoimmune diseases: Protective or pathogenic? Front Immunol. 12:624687. DOI: 10.3389/fimmu.2021.624687. PMID: 33777006. PMCID: PMC7994264. PMID: 1018bca2c1524421b0f3054211d60540.
85. Lünemann A, Lünemann JD, Münz C. 2009; Regulatory NK-Cell functions in inflammation and autoimmunity. Mol Med. 15:352–8. DOI: 10.2119/molmed.2009.00035. PMID: 19603102. PMCID: PMC2710290.
86. Hervier B, Beziat V, Haroche J, Mathian A, Lebon P, Ghillani-Dalbin P, et al. 2011; Phenotype and function of natural killer cells in systemic lupus erythematosus: Excess interferon-γ production in patients with active disease. Arthritis Rheum. 63:1698–706. DOI: 10.1002/art.30313. PMID: 21370226.
87. Yoon Kim D, Kwon Lee J. 2022; Type 1 and 2 diabetes are associated with reduced natural killer cell cytotoxicity. Cell Immunol. 379:104578. DOI: 10.1016/j.cellimm.2022.104578. PMID: 35908302.
88. Liu M, Liu J, Zhang X, Xiao Y, Jiang G, Huang X. 2021; Activation status of CD56dim natural killer cells is associated with disease activity of patients with systemic lupus erythematosus. Clin Rheumatol. 40:1103–12. DOI: 10.1007/s10067-020-05306-x. PMID: 32797360.
89. Chalan P, Bijzet J, Kroesen BJ, Boots AM, Brouwer E. 2016; Altered natural killer cell subsets in seropositive arthralgia and early rheumatoid arthritis are associated with autoantibody status. J Rheumatol. 43:1008–16. DOI: 10.3899/jrheum.150644. PMID: 27036380.
90. Mimpen M, Muris AH, Rolf L, Gerlach O, Kuhle J, Hupperts R, et al. 2021; Prognostic value of natural killer cell/T cell ratios for disease activity in multiple sclerosis. Eur J Neurol. 28:901–9. DOI: 10.1111/ene.14680. PMID: 33326677. PMCID: PMC7898592.
91. Zhang X, Wei H. 2021; Role of decidual natural killer cells in human pregnancy and related pregnancy complications. Front Immunol. 12:728291. DOI: 10.3389/fimmu.2021.728291. PMID: 34512661. PMCID: PMC8426434. PMID: 920ba5f6dbe04687a8e56f827ff2a039.
92. Nakimuli A, Chazara O, Hiby SE, Farrell L, Tukwasibwe S, Jayaraman J, et al. 2015; A KIR B centromeric region present in Africans but not Europeans protects pregnant women from pre-eclampsia. Proc Natl Acad Sci U S A. 112:845–50. DOI: 10.1073/pnas.1413453112. PMID: 25561558. PMCID: PMC4311823.
93. Quenby S, Nik H, Innes B, Lash G, Turner M, Drury J, et al. 2009; Uterine natural killer cells and angiogenesis in recurrent reproductive failure. Hum Reprod. 24:45–54. DOI: 10.1093/humrep/den348. PMID: 18835875.
94. Bagkou Dimakou D, Tamblyn J, Lissauer D, Richter A. 2025; Evaluation of peripheral NK tests offered to women with recurrent pregnancy loss and a search for novel candidate biomarkers. J Reprod Immunol. 169:104522. DOI: 10.1016/j.jri.2025.104522. PMID: 40112444.
95. Von Woon E, Greer O, Shah N, Nikolaou D, Johnson M, Male V. 2022; Number and function of uterine natural killer cells in recurrent miscarriage and implantation failure: A systematic review and meta-analysis. Hum Reprod Update. 28:548–82. DOI: 10.1093/humupd/dmac006. PMID: 35265977. PMCID: PMC9247428.
96. Angelo LS, Banerjee PP, Monaco-Shawver L, Rosen JB, Makedonas G, Forbes LR, et al. 2015; Practical NK cell phenotyping and variability in healthy adults. Immunol Res. 62:341–56. DOI: 10.1007/s12026-015-8664-y. PMID: 26013798. PMCID: PMC4470870.
97. Practice Committee of the American Society for Reproductive Medicine. 2012; Evaluation and treatment of recurrent pregnancy loss: A committee opinion. Fertil Steril. 98:1103–11. DOI: 10.1016/j.fertnstert.2012.06.048. PMID: 22835448.
98. National Evidence-Based Healthcare Collaborating Agency. NK cell activity tests. https://scholarworks.bwise.kr/neca/bitstream/2023.sw.neca/260/1/NR23-001-15.pdf. updated on Nov 2025. PMID: https://scholarworks.bwise.kr/neca/bitstream/2023.sw.neca/260/1/NR23-001-15.pdf.
99. Jung YS, Kwon MJ, Park DI, Sohn CI, Park JH. 2018; Association between natural killer cell activity and the risk of colorectal neoplasia. J Gastroenterol Hepatol. 33:831–6. DOI: 10.1111/jgh.14028. PMID: 29055146.
100. Lee YK, Suh E, Oh H, Haam JH, Kim YS. 2024; Decreased natural killer cell activity as a potential predictor of hypertensive incidence. Front Immunol. 15:1376421. DOI: 10.3389/fimmu.2024.1376421. PMID: 38715619. PMCID: PMC11074345. PMID: 3cea875e35054e86b662a3570351de28.
101. Jung YS, Park JH, Park DI, Sohn CI, Lee JM, Kim TI. 2018; Physical inactivity and unhealthy metabolic status are associated with decreased natural killer cell activity. Yonsei Med J. 59:554–62. DOI: 10.3349/ymj.2018.59.4.554. PMID: 29749139. PMCID: PMC5949298.
102. Brolinson PG, Elliott D. 2007; Exercise and the immune system. Clin Sports Med. 26:311–9. DOI: 10.1016/j.csm.2007.04.011. PMID: 17826186.
103. Jo H, Jo Y, Koh SK, Lee M, Kim J, Kweon SH, et al. 2026; Optimization of natural killer cell expansion with K562-mbIL-18/-21 feeder cells and assurance of feeder cell-free products. Ann Lab Med. 46:180–9. DOI: 10.3343/alm.2025.0168. PMID: 40701946. PMCID: PMC12915374.
104. Park JD, Shin HE, An YS, Jang HS, Park J, Kim SN, et al. 2025; Advancing natural killer cell therapy: genetic engineering strategies for enhanced cancer immunotherapy. Ann Lab Med. 45:145–59. DOI: 10.3343/alm.2024.0380. PMID: 39774132. PMCID: PMC11788708.

Fig. 1
Overview of NK cell assays. Various assays have been developed to evaluate the phenotype, frequency, and functional activity of NK cells. These assays include flow cytometry-based phenotypic analyses (e.g., CD56, CD16, NKG2D, NKp46, and KIRs); cytotoxicity assays, such as 51Cr-release and Calcein-AM-release assays; degranulation assays (e.g., CD107a expression); cytokine-release assays (e.g., ELISA and ELISpot tests for IFN-γ); gene-based methods, including RT-PCR and single-cell RNA sequencing; and advanced platforms, such as single-cell microscopy and magneto-microfluidic chips.
Abbreviations: NK, natural killer; KIR, killer immunoglobulin-like receptor; LDH, lactate dehydrogenase; ELISpot, enzyme-linked immunospot; PI, propidium iodide; 7-AAD, 7-aminoactinomycin D; GZMB, granzyme B; PRF1, perforin 1; NCR1, natural cytotoxicity triggering receptor 1 (NKp46); NCAM1, neural cell adhesion molecule 1 (CD56); FCGR3A, Fc gamma receptor IIIa (CD16a); IFN-γ, interferon gamma; TNF, tumor necrosis factor.
alm-46-3-244-f1.tif
Fig. 2
Clinical significance of NK cell assays. NK cells play important roles under various physiological and pathological conditions, including hemophagocytic lymphohistiocytosis, cancer, infections, autoimmune diseases, and reproductive disorders. Alterations in the frequency or function of NK cells may influence disease development and progression, underscoring their clinical relevance across a broad spectrum of immune-mediated conditions. To better understand and monitor these changes, various NK cell assays have been utilized for both research and clinical applications.
Abbreviation: NK, natural killer.
alm-46-3-244-f2.tif
Table 1
Diagnostic applications of NK cell assays for different diseases
Disease group Examples NK cell assay approach Diagnostic significance
Hyperinflammatory syndromes Primary and secondary HLH Flow cytometry-based cytotoxicity and CD107a-based degranulation assays Identifies impaired cytotoxic granule release; incorporated as a diagnostic criterion in the HLH-2004 guidelines; distinguishes primary (profound dysfunction) from secondary HLH (variable dysfunction)
Cancer Breast cancer, HCC, gastric cancer, and colorectal cancer Flow cytometric analysis of NK subsets and receptors; ELISA-based IFN-γ release assay; genetic assays (e.g., NKG2D) Differentiates benign vs. malignant tumors; reduced activating receptor expression and altered NK subset distribution correlate with diagnosis and progression
Infectious diseases Hepatitis C, hepatitis B, and COVID-19 Phenotypic profiling of NK subsets; cytokine release assays; KIR-HLA genotyping Early detection of acute infection; genetic predictors of spontaneous clearance in hepatitis C (KIR2DL3: HLA-C1); TRAIL+CD56bright NK cells predict therapeutic responses in hepatitis B
Autoimmune diseases SLE, type 1 diabetes, and RA Cytotoxicity assays (51Cr-release, LDH-release, CD107a-based degranulation assays); receptor profiling via flow cytometry Reduced NK cytotoxicity and altered receptor/chemokine expression provide supportive diagnostic markers in autoimmune pathology
Reproductive disorders Recurrent miscarriage and infertility uNK and PB NK cell phenotyping (flow/mass cytometry), degranulation assays Aberrant uNK frequency, altered inhibitory receptor expression (e.g., KIR, NKG2A), and reduced chemokine receptor subsets linked to adverse pregnancy outcomes
Health screening/preventive medicine Colorectal adenomas, hypertension, and metabolic syndrome Commercial NK cell activity kits (e.g., NK Vue for measuring IFN-γ release) Decline in NK activity associated with colorectal neoplasia, hypertension, and metabolic abnormalities; potential adjunctive marker in screening

Abbreviations: NK, natural killer; HLH, hemophagocytic lymphohistiocytosis; HCC, hepatocellular carcinoma; SNP, single-nucleotide polymorphism; HCV, hepatitis C virus; HBV, hepatitis B virus; COVID-19, coronavirus disease 2019; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; KIR, killer immunoglobulin-like receptor; SLE, systemic lupus erythematosus; RA, rheumatoid arthritis; LDH, lactate dehydrogenase; PB, peripheral blood; IFN, interferon; uNK, uterine natural killer cells.

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