Fc gamma receptor polymorphisms in antibody therapy: implications for bioassay development to enhance product quality

Abstract

The effectiveness of therapeutic antibodies is often associated with their Fc-mediated effector functions, such as antibody-dependent cellular cytotoxicity and antibody-dependent cellular phagocytosis. These functions rely on interactions between Fc gamma receptors (FcγRs) on immune cells and the Fc region of antibodies. Genetic variations in these receptors, known as FcγR polymorphisms, can influence therapeutic outcomes by altering receptor expression levels, affinity, and function. This review examines the impact of FcγR polymorphisms on antibody therapy, emphasizing their role in developing and optimizing functional bioassays to assess product quality. Understanding these polymorphisms is essential for refining bioassays, which are crucial for accurately characterizing antibody products and ensuring consistency in manufacturing processes.

Introduction

Monoclonal antibodies (mAbs) are essential in modern medicine, transforming treatments for cancer, infectious diseases, and autoimmune disorders [1, 2]. Their ability to precisely target specific molecules is enabled by antigen-binding (Fab) and crystallizable (Fc) fragments, underscoring their therapeutic potential. For some antibodies, Fc effector functions are crucial for both clinical efficacy and safety [3–6]. These functions include antibody-dependent cellular cytotoxicity (ADCC), complement-dependent cytotoxicity (CDC), and antibody-dependent cellular phagocytosis (ADCP). Additionally, antibody-dependent enhancement (ADE) is a phenomenon where antiviral antibodies can enhance antiviral protection or contribute to pathogenesis [7]. CDC operates differently from ADCC and ADCP by triggering cell lysis through the complement cascade rather than through Fc gamma receptors (FcγRs). In contrast, ADCC and ADCP rely on FcγRs on immune cells to induce cytotoxicity, illustrating distinct pathways for targeted cell killing.

FcγRs are categorized into type-I classical, type-II, and nonclassical type I receptors, each with unique expression patterns and functions. The term FcγRs commonly refers to type-I classical FcγRs, although type-II and nonclassical type-I receptors are also expressed in nonimmune cells [8, 9]. Located on immune cells, FcγRs are essential for mediating ADCC or ADCP by binding to antibodies’ Fc portion, thereby recruiting cytotoxic or phagocytic innate effector cells expressing specific FcγRs, such as natural killer (NK) cells or macrophages [5, 6]. In oncology, antibodies like rituximab and trastuzumab rely on ADCC activation for effective tumor killing in lymphoma and breast cancer. The effectiveness of therapeutic antibodies can be influenced by genetic variations in FcγRs, known as FcγR polymorphisms, which affect receptor expression levels, affinity, and function. Single-nucleotide polymorphisms (SNPs) of FcγR can alter receptor expression levels, Immunoglobulin G (IgG) subclass affinity, and overall receptor function [10]. Some clinical studies have linked specific FcγR genotypes, such as FcγRIIIa-158V/V and FcγRIIa-131H/H to improved clinical outcomes, though this may be disease and treatment specific [11–17].

Bioassays are tests designed to measure the potency or effect of a pharmaceutical product on a biological system, such as animals or cells. Ensuring that a bioassay aligns with the product’s mechanism of action (MoA) is critical for comparing potency across product batches (ensuring lot-to-lot consistency) and/or verifying the analytical comparability between biosimilar candidates with reference products. Bioassays assessing Fc effector functions should incorporate evaluation of how FcγR structural variations, including FcγR polymorphisms, affect an antibody’s biological function to manage risks and ensure product quality. Comprehensive testing of Fc-FcγR interactions and their impact on relevant effector functions (e.g. ADCC or ADCP) requires well-designed binding and cell-based assays. Understanding the molecular mechanisms by which FcγR polymorphisms influence antibody efficacy is key to developing bioassays that effectively measure bioactivity and potency.

This review examines the impact of FcγR polymorphisms on antibody therapy, focusing on considerations in developing and optimizing bioassays (potency assays) to evaluate the quality, stability, and safety of therapeutic mAbs and relevant biological products. Understanding an antibody’s varied biological activities aids in selecting appropriate characterization methods to define and monitor critical quality attributes of the product, ensuring product quality and manufacturing consistency throughout the product lifecycle.

Key factors influencing Fc-FcγR interactions

Fc-mediated effector functions are essential for the therapeutic efficacy of many therapeutic antibodies, which represent ~50% of US Food and Drug Administration approved antibodies [2]. These antibodies exert their effects through a combination of mechanisms involving both their Fab and Fc regions. The Fab region directly binds to specific antigens on target cells, blocking or activating signaling pathways, disrupting disease-related functions, and inhibiting cell growth or inducing cell death. The Fc portion of IgG antibodies interacts with FcγR on immune cells like macrophages, natural killer (NK) cells, and neutrophils. This interaction may activate immune responses such as ADCC and ADCP, which help eliminate target cells and enhance immune responses against pathogens or tumor cells, contributing to therapeutic efficacy [3]. For instance, when the Fab domain of an antibody binds to a target cell, the Fc region can activate FcγRIIIa (CD16) receptors on NK cells and myeloid cells. This interaction, which occurs at a 1:1 binding ratio [18], prompts these cells to release cytokines and cytotoxic granules such as perforin and granzyme A/B, causing target cell lysis and apoptosis through ADCC [19–21]. Moreover, some antibodies can induce ADCP, wherein macrophages and other FcγR-expressing cells engulf and digest antibody-bound targets, such as tumor cells or pathogens.

The outcomes of these immune responses are influenced by various factors, including the antibody subclass, the types of immune cells involved, and the status of FcγR, such as their expression levels or allotypes. Evaluating FcγR-mediated functions is more complex than assays focused solely on antigen binding or virus neutralization because it involves various immune cells, differing Fc receptor expression, and the intricate signaling pathways activated during Fc-FcγR interactions (see Fig. 1).

Antibody subclass

The type of antibody used in therapy significantly influences how immune cells respond and how complement proteins become activated [6]. Most therapeutic mAbs are part of the human IgG class [2], which consists of four subclasses: IgG1, IgG2, IgG3, and IgG4. Each of these IgG subtypes has distinct properties in mediating Fc effector functions. IgG1, for instance, is often chosen for cancer treatment because it can strongly trigger ADCC leading to the destruction of targeted cancer cells [22]. In contrast, IgG2 and IgG4 have a lower affinity for FcγRs, resulting in minimal immune effector functions. While IgG4 weakly activates the classic complement pathway at high antigen densities and high antibody concentrations [23], it can still induce various immune responses, including Ca²⁺ signaling, degranulation, intracellular cytokine production, and ADCC [24]. Besides the type of antibody, several other factors affect how immune cells become activated. These include the location and manner of antibody binding to its target [25], the ratio of antibody to antigen (reflecting the receptor density on targeted cells), and the binding strength between the antibody and its target, as well as the corresponding Fc receptor.

FcγR type

The Fc effector functions ADCC and ADCP are mediated by interactions with specific FcγRs on immune cells. In humans, FcγRs comprise four activating receptors (FcγRI, FcγRIIa, FcγRIIc, and FcγRIIIa) and one inhibitory receptor (FcγRIIb) [19]. These receptors transduce signals within immune cells, either activating via their intracellular immunoreceptor tyrosine-based activation motif (ITAM) or inhibiting through their immunoreceptor tyrosine–based inhibition motif (ITIM) [26, 27]. Uniquely, FcγRIIIb lacks an intracellular signaling motif. Instead, it cooperates with other FcγRs to promote phagocytosis by human neutrophils and acts as a negative regulator of neutrophil ADCC [28]. Despite its lack of a signaling motif, research shows that FcγRIIIb can signal in neutrophils through the Tec family of tyrosine kinases [29], trigger raft-dependent calcium flux [30], and induce nuclear phosphorylation of ERK and of Elk-1 independently of Syk, PI3K, or MEK [30]. In neutrophils, FcγRIIa and FcγRIIIb facilitate phagocytosis, while FcγRI initiates signaling cascades that result in elevated intracellular calcium levels [31]. The extent of ADCC and ADCP is influenced by the balance of these activating or inhibiting receptors, which dynamically respond to their microenvironment [20].

FcγRI is a high-affinity receptor predominantly expressed on macrophages, monocytes, and dendritic cells. It plays a crucial role in ADCP, facilitating both the engulfment of targets and the initiation of immune responses. Unlike other FcγRs, FcγRI can bind to monomeric IgG due to its high-affinity binding, while other FcγRs typically bind only to opsonized targets or immune complexes [26, 32, 33]. The classification of FcγRs based on binding affinity comes from observations of the binding of IgGs as monomers (soluble) to immobilized FcγRs, often studied using surface plasma resonance (SPR).

FcγRII exists as three separate receptors (FcγRIIa, FcγRIIb, FcγRIIc) encoded by different genes. These receptors are present on various immune cells, including B cells, monocytes, neutrophils, and dendritic cells. FcγRII plays distinct roles in ADCC and ADCP and are also involved in the clearance of immune complexes. The expression levels of FcγRIIb on mononuclear phagocytes are a negative regulator of ADCP activation, counterbalancing FcγRIIa and FcγRIIc signaling when co-expressed on the effector cells [25, 34]. Each receptor is linked with ADCC, ADCP, or both and is also involved in the clearance of immune complexes. FcγRIIc is only found in NK cells of people with the open reading frame allele. NK cells are the primary cell type involved in ADCC due to the lack of the inhibitory FcγRIIb protein [35]. Notably, there are nonclassical variations in FcγRII expression. Although FcγRIIb is typically absent in NK cells and neutrophils, certain population variations can lead to its expression in these cells. Additionally, FcγRIIc is not expressed in most of the population due to an in-frame termination codon [36, 37]. However, ~30% of Caucasian population with a specific genotype can express FcγRIIc on their neutrophils, monocytes, and NK cells [38]. When expressed, FcγRIIc influences both ADCC and phagocytosis [39, 40].

FcγRIII exists in two forms: FcγRIIIa and FcγRIIIb. These receptors are predominantly expressed in NK cells, macrophages, and a subset of T cells. Both FcγRIIIa and FcγRIIIb are primarily involved in ADCC and the promotion of cytokine production. FcγRIIa and FcγRIIIb are known for their lower affinity to IgG antibodies, with FcγRIIa being a low affinity and FcγRIIIb having an intermediate affinity [22, 32]. FcγRIIIb is distinctly expressed on certain granulocytes and functions by capturing IgG-containing immune complexes without initiating cell activation.

The Fc portion of a therapeutic antibody can also interact with FcRn, known as the neonatal Fc receptor, which binds antibodies in intracellular transport vesicles and releases them into the bloodstream. This interaction prevents their lysosomal degradation, thereby prolonging the in vivo half-life of the therapeutic antibody. FcRn binds to the interface between CH2 and CH3 domains of IgG-heavy chains in the Fc region of the IgG molecule under mildly acidic conditions (~pH 6) and releases it at neutral pH (~7.4) [32]. Through this pH-dependent interaction, FcRn maintains serum IgG levels, contributing to IgG homeostasis in human adults [41].

Fc effector function arises from a complex interplay of responses driven by an mAb’s ability to form immune complexes with FcγRI, FcγRII, and/or FcγRIII [42]. The co-expression and co-aggregation of FcγRs on various immune cells activate both ITAM and ITIM pathways, resulting in a range of immunomodulatory reactions that may be synergistic or antagonistic [7, 43]. These complex antibody-immune interactions highlight the need for carefully designed clinical studies to evaluate their impact on the clinical safety and efficacy of antibody therapies.

Fc glycosylation

The variety of Fc-FcγR interactions is also influenced by the heterogeneity of Fc glycosylation at Asn-297 in the CH2/CH3 domain junction of the Fc, a conserved site among IgG subclasses [3, 32]. For instance, IgG1 antibodies that lack core fucose at Asn-297 show increased binding affinity to FcγRIIIa, leading to enhanced ADCC. In contrast, terminal α2,6-sialylation promotes the anti-inflammatory activity of intravenous immunoglobulin therapy by interacting with type II Fc receptors [25, 26, 44, 45]. Therapeutic IgG1 antibodies often carry heterogeneous N-glycans at the Fc domain, impacting their ability to bind FcγRs and thus their therapeutic efficacy. High levels of mannose, hyper-galactosylation, and high levels of sialic acid are also reported to impact ADCC activation [44, 45]. Therefore, glycosylation patterns must be appropriately characterized and controlled during product development [3, 4].

Other post-translational modifications (PTMs), such as deamidation and oxidation, can affect Fc-FcγR interactions and alter antibody effector functions [46]. For instance, deamidation at the asparagine 325 (N325) residue of a therapeutic IgG1 monoclonal antibody has been shown to disrupt the binding between the IgG1 Fc and FcγRIIIa, resulting in a loss of ADCC activity [47]. Similarly, metal ion–induced oxidation of methionine 255 (M255) in the CH2 domain and methionine 431 (M431) in the CH3 domain of trastuzumab and trastuzumab emtansine has been associated with reduced ADCC activity [48]. These PTMs, which may result from the manufacturing process, changes in manufacturing, or stress conditions, may also affect product stability and antigen binding affinity [47]. Consequently, implementing well-developed bioassays, alongside other robust analytical methods, to monitor these PTMs throughout the manufacturing process can enhance both process consistency and product quality.

FcγR polymorphisms

FcγR polymorphisms refer to genetic variations found in genes encoding Fcγ receptors, including FCGR1A, FCGR2A, FCGR2B, FCGR2C, FCGR3A, and FCGR3B located on chromosome 1q23.3-q24.3. These variations encompass single nucleotide polymorphisms (SNPs) and copy number variations (CNVs), which can potentially alter ligand binding as noted in multiple studies (Table 1) [33, 49, 50]. As a result, they may affect receptor function, change the level of receptor expression, and influence the magnititude of immune responses, particularly in mAb-based treatments [51–53]. Another aspect to consider is the prevalence of these genetic variants across different ethnic groups in the population. The percentages for each allele among the variants differ across clinical study cohort size, with a consensus that the 158 V/V allele is reported to be the least abundant relative to the 158F/F allele and 158 V/F allele [54–61].

FcγRIIa-R131H

One extensively studied FcγR polymorphism is the FcγRIIa gene polymorphism, resulting in an amino acid change from arginine to histidine at position 131 (R131H) in the extracellular domain of FcγRIIa [33]. This alteration affects the binding affinity for different IgG subclasses. Specifically, the -131H variant exhibits increased affinity for IgG2 and IgG3 compared to the −131R variant, but a reduced affinity to IgG4 [25, 26]. FcγRIIa signaling is believed to be activated through antigen-mediated receptor dimerization, with the higher-affinity variant resulting in enhanced receptor clustering [25]. This occurs because the FcγRIIa-131R binds to a shallow pocket on the Fc near the glycosylation site, preventing multiple IgG antibodies from binding and clustering the receptor. In contrast, the −131H, or higher-affinity variant, allows access for multiple IgG2 monomer binding, resulting in crosslinking and activation [25]. Consequently, individuals carrying the −131H variant may exhibit enhanced ADCC and phagocytosis against targets opsonized with IgG2 or IgG3 antibodies compared to those carrying the −131R [33].

FcγRIIIa-V158F

Similarly, polymorphisms in FcγRIIIa can impact receptor affinity and effector functions. The FCGR3A gene is reported to be highly polymorphic, with ~40 variants located in exon 4 [54]. The FcγRIIIa-158 V/F polymorphism results in either a valine (V) or phenylalanine (F) at position 158 of the receptor’s extracellular domain [62]. The change from F to V at 158 increases Fc-FcγR binding affinity, thereby requiring lower antibody dosage to achieve ADCC effects [4, 32]. These alleles are co-dominantly expressed, with the −158 V variant displaying higher affinity for IgG1 and IgG3 antibodies and inducing IgG4 binding capability [3, 26, 32]. Activation of FcγRIIIa-158 V also results in much higher calcium release relative to the −158F variant [62], indicating stronger signaling initiation. Alternatively, FcγRIIIa-158F is reported to have low to negligible binding to IgG2 and IgG4 [26]. Notably, the FCGR3A gene has a tri-allelic SNP, rs10127939 (L66H/R), which influences the binding capacities of different IgG subclass binding capabilities to the FcγRIIIa receptor [63].

FcγRIIIb NA1/2

Another well-studied polymorphism occurs in FcγRIIIb. The neutrophil antigen (NA) 1/2 polymorphism is specific to neutrophils and is a biallelic polymorphism with co-dominant expression [61]. The amino acid difference between the variants impacts the N-linked glycosylation of the receptor. The NA1 variant has a higher affinity for IgG1 and IgG3 antibodies, which can lead to higher levels of decoy prevention of ADCC and ADCP in individuals who carry the NA1 allele [33, 61]. Another SNP (SH/A78D) linked to the NA1/NA2 variant has a less defined function, and its effects remain unclear [64].

FcγRI

Three novel variants in the FCGR1A gene have been recently reported [56]. At position −131 (rs1848781), an SNP occurs where cytosine is substituted for guanine. This SNP occurs in the proximal gene promoter region and has been shown to increase promoter activity, leading to increased expression of FcγRI [56]. The second variant that was identified is an indel mutation, which causes either a six-nucleotide insertion or deletion near the splicing acceptor site of exon 6. The deletion variant contributes to decreased expression of FcγRI [56]. The third variant is caused by a nonsynonymous SNP, at position 970 (rs1050204) where guanine is substituted for adenine. The mutation has been found to increase FcγRI-mediated phagocytosis, degranulation, and pro-inflammatory cytokine production [56].

FcγRIIb

Several polymorphisms have been reported in FcγRIIb that do not affect ligand binding. For example, at position −386, an SNP occurs where guanine is substituted for cytosine [65]. Another SNP occurs at position −120, where thymine is substituted for adenine [65]. Both SNPs have been linked with increased promoter activity, which leads to increased expression of FcγRIIb [65]. Several other SNPs were also identified in the promoter region, and they may also influence promoter activity [65]. At position −343, guanine is substituted for cytosine, which was linked to decreased promoter activity and therefore less expression of FcγRIIb [66]. The I232T polymorphism located in the transmembrane portion of FcγRIIb is associated with a conformational change, tilting the receptor toward the membrane and preventing binding to IgGs [67]. This change impacts B-cell activation, resulting in disease onset of systemic lupus erythematosus [60, 67, 68].

Like FcγRIIb, some polymorphisms have been reported in FcγRIIc that do not affect ligand binding but rather influence promoter activity. For example, at position −386 guanine is substituted for cytosine, and, at position −120, cytosine is substituted for adenine, impacting the promotor and transcriptional activity [49].

Effect of copy number variation in FcγR-encoding genes

CNVs involve the duplication or deletion of DNA base pairs, which can increase or decrease the amount of the FcγRs expressed in the immune cells [49, 50, 69]. The presence of multiple copies of FcγRIIIa-158 V can lead to a greater ADCC response with some mAbs used in cancer therapy [70]. CNVs have been reported in the FCGR3A, FCGR2C, and FCGR3B genes, but none so far have been reported in the FCGR2A and FCGR2B genes [33, 50, 52, 69]. Having more than two gene copies is reported to increase receptor levels, resulting in increased IgG binding and effector responses [33].

FcγR genotypes in antibody therapy

Accumulating evidence shows that FcγR polymorphisms significantly affect the clinical effectiveness of therapeutic antibodies across various diseases, including cancer, autoimmune disorders, and infectious diseases. For example, in cancer immunotherapy, monoclonal antibodies like rituximab (anti-CD20), cetuximab (anti-EGFR), and trastuzumab (anti-HER2) rely on FcγR-mediated mechanisms to effectively eliminate tumor cells. Despite success in some patients, a notable proportion experience no clinical benefits [12, 13, 71]. This variability may result from differences in an individual’s FcR genetic background and the therapy’s modulation of the immune system, especially for treatment of autoimmune disorders [62, 71, 72]. Ongoing clinical studies investigate the relationship between polymorphisms in activating FcγRIIa and FcγRIIIa and treatment outcomes, showing varying results depending on the therapy [71, 73, 74].

For example, studies on rituximab’s efficacy in non-Hodgkin’s lymphoma patients have shown links between FcγR polymorphisms and response rates [4, 71, 74], with patients with the homozygous FcγRIIIa-158V/V genotype often exhibiting higher response rates compared to those with the heterozygous FcγRIIIa-158V/F or homozygous FcγRIIIa-158F/F genotypes [13, 45, 71]. Responses to the anti-EGFR IgG1 mAb cetuximab have shown associations between progression-free and overall survival and FcγRIIa-131H/H and FcγRIIIa-158V/V homozygous genotypes [72]. Patients treated with trastuzumab have reported differing results across clinical trials, with some reporting no associations in response rates and FcγRIIIa polymorphisms when patients were treated with trastuzumab alone, with others showing significant improvements in the −158 V/V patients [12, 75–77].

These genetic correlations have been extensively discussed, emphasizing the need to evaluate their impact on drug potency [13, 19, 20, 71, 72, 76]. The variability in clinical outcomes underscores the importance of considering FcγR polymorphisms in therapeutic mAb development and the continued evaluation of whether single or combination polymorphisms may be used as predictive biomarkers [71]. This entails efforts in patient stratification, treatment selection, and designing bioassays for a comprehensive assessment of relevant bioactivities.

Optimization of bioassays for evaluating therapeutic antibodies

Therapeutic mAbs are complex molecules with varied MoAs. Ensuring their consistent production and sustained efficacy throughout the product’s shelf life requires bioassays, also known as potency assays, as per International Council for Harmonisation Q6B [78]. Unlike physicochemical methods, which can be compendial or platform-based, bioassays are tailored to each product, demanding special considerations to meet regulatory standards. They are essential for determining potency, conducting comparability assessments after manufacturing changes, facilitating biosimilar development, and ensuring regulatory compliance.

Here, we discuss bioassay strategies for anticancer mAbs, focusing on five key functional attributes (Fig. 2): (i) antibody–antigen binding kinetics, (ii) cytotoxicity (e.g. cell death, growth inhibition), (iii) Fc glycan profile, (iv) antibody–FcγR binding affinity and cell-based Fc effector activities, and (v) FcRn binding affinity. Fc glycan profile analysis reveals the carbohydrate structures attached to the Fc region, which significantly affect Fc-mediated effector functions and pharmacokinetics. More detailed information on Fc glycan profiling and its impacts can be found elsewhere [2, 45, 79–81] and exceeds the scope of this manuscript.

When designing Fc effector bioassays, it is crucial to consider FcγR polymorphisms because of the varied nature of Fc-FcγR interactions as described above. This encompasses assays for comparative studies using purified recombinant Fc receptor proteins or stable effector cell lines expressing individual FcγR variants, such as FcγRIIIa-F158V and FcγRIIa-R131H [82].

Binding assays

The determination of antigen binding affinity involves evaluating the specificity and the kinetics of interaction between the mAb and its target antigen. Techniques such as SPR [83], biolayer interferometry (BLI) [84], and enzyme-linked immunosorbent assays (ELISAs) [85] are commonly used for this purpose. SPR and BLI provide label-free, real-time detection of protein–protein interactions with high sensitivity. Real-time kinetic analysis offers more comprehensive information compared to ELISA because SPR/BLI provide both association (K_on) and dissociation (K_off) rates [26, 84].

Cytotoxicity assays

Cytotoxicity assays evaluate how effectively mAbs kill cancer cells. One common approach is to measure cell viability in cancer cell lines that express the target protein for the mAb. This is typically done using dyes like 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) [86] or AlamarBlue [87, 88], which selectively detect living cells. Another method involves lactate dehydrogenase (LDH) release assays, which quantify the amount of LDH released from cells that have been damaged or killed by the mAb [89–91]. Flow cytometry analyzes cell populations based on markers like Annexin V for apoptosis [92], while clonogenic assays measure colony-forming ability post-mAb treatment. Real-time cell analysis is a cutting-edge technique that monitors cell behavior in real time using impedance assays [93, 94]. Additionally, apoptosis assays, such as caspase activation, provide insights into the mechanisms of programmed cell death triggered by mAbs. It is important to note that these assays focus solely on the signaling events initiated by mAbs and subsequent cellular responses, excluding any interactions with immune cells.

Fc effector function assays

Fc effector function evaluation includes assessing the mAb’s engagement of FcγRs on immune cells and initiation of effector mechanisms like ADCC, CDC, and ADCP. Techniques such as SPR or BLI measure binding affinity, while cell-based assays provide further insights. Finally, FcRn binding affinity evaluation examines the mAb’s interaction with the neonatal Fc receptor, crucial for antibody recycling and half-life in circulation [95]. Techniques such as SPR, BLI, or cellular-based assays inform on pharmacokinetic properties and dosing regimens.

ADCC assays typically utilize primary immune cells such as peripheral blood mononuclear cells (PBMCs) [94, 96] or isolated NK cells [97] to assess the killing of target cells, often cancer cells, induced by therapeutic antibodies. The FcγRIIIa-F158V polymorphism can be tested using NK cells from donors with different variants [98–100]. However, assays based on primary cells for effector functions are known for their inherent variability. These assays are commonly employed in product characterization rather than release testing. Additionally, the primary cells selected for F158V and H131R not only differ in these polymorphisms but also in numerous other genetic variations that might have broader effects on ADCC. Optimizing the target-to-effector cell ratio is crucial due to variations in receptor densities among donors. For readouts, radioactive tracers (e.g. 51-Cr) [100] or fluorescent dyes (e.g. calcein-AM) [98, 99] loaded into target cells (e.g. cancer cell lines) are measured for release, indicating target cell killing.

CDC activity is unaffected by the polymorphisms in FcγR as these assays do not require effector cells. In these assays, target cells labeled with radioactive or fluorescent agents are incubated with mAbs of interest in the presence of human serum containing C1q [101]. The release of radioactivity or fluorescence indicates CDC activity.

ADCP assays are often considered the most challenging among the three effector function assays. These assays employ macrophages derived from PBMCs to evaluate phagocytosis. Flow cytometry is used to construct dose–response curves to measure this activity [102]. One challenge with ADCP assays is that due to major histocompatibility complex restrictions, effector cells from different donors cannot be mixed. This restriction necessitates testing across multiple donors to mitigate variability. Moreover, the process of differentiating monocytes into macrophages is both labor-intensive and time-consuming. Endpoint analysis in ADCP assays involves using labeled target cells and employing meticulous flow cytometry gating to distinguish subsets based on labeling and dye detection. This process is more technically demanding compared to plate-reader-based assays for assessing ADCC or CDC. In ADCP assays, the key players include CD64 (FcγRI) on monocytes and CD32a (FcγRIIa) on macrophages. To overcome donor variability, THP-1 cells, a stable macrophage cell line, are commonly used [102–104]. When designing assays to assess ADCP activity, it is important to consider the polymorphism of these receptors, such as FcγRIIa-R131H.

Reporter gene assays using engineered Jurkat T cells as effector cells offer a powerful alternative to primary cell assays for studying FcγR-mediated activities [82, 93, 96]. These Jurkat cells are engineered to express specific FcγR variants, such as FcγRIIIa-158V or FcγRIIIa-158F for ADCC, and FcγRI or FcγRIIa-131R or FcγRIIa-131H for ADCP. The cells are equipped with a luciferase reporter gene under the nuclear factor of activated T-cell (NFAT) control [93, 105, 106]. In these assays, mAbs simultaneously bind to the target and the Jurkat reporter cells, activating NFAT signaling. This activation is detected by measuring changes in luminescent signals following substrate (luciferin) digestion. In addition to Jurkat cells, several human natural killer cell lines, such as NK-92 and KHYG-1 [105, 107–111], can be engineered to serve as ADCC effector cells. Moreover, other promotors, such as NFκB and AP-1 [93, 112–114], can also be targeted to drive luciferase expression, enabling the monitoring of intracellular signaling pathways relevant to the product’s MoA.

Compared to traditional PBMC assays, reporter gene assays demonstrate excellent performance, making them an ideal choice for assessing Fc-FcγR interactions to support product characterization, process control, and comparability assessment [96, 114]. Although the readout serves as a surrogate for ADCC, these assays eliminate the need for primary cells, providing a more efficient method for studying FcγR-mediated activities. Additionally, receptor gene assays can be customized to examine the effects of FcγR polymorphisms by specifically engineering the effector cells to express different FcγR variants [96]. Their suitability can be further validated by correlating data with primary cell studies. If Fc effector function is established as part of the MoA of the product, ADCC reporter gene assays may be used as release potency assays. In such cases, the assay must be well optimized and robust, particularly for afucosylated mAb products with enhanced ADCC activities, as variations in afucosylation levels during manufacture can significantly impact product potency.

Understanding how Fc-FcγR interactions contribute to antibody-mediated protection against infections like Human Immunodeficiency Virus, Ebola, and SARS-CoV-2 is vital for vaccine and antiviral antibody development (reviewed by Bournazos et al. [7]). However, assessing these interactions is challenging due to the complexity of antiviral antibodies. Current in vitro assays often fail to capture the heterogeneity of FcγR-expressing cells, e.g. in lung tissues during SARS-CoV-2 infections [115–117]. Animal models also face limitations due to interspecies differences in FcγR genes and structures. To address this, FcγR humanized mice may offer a solution, allowing for a more precise investigation of antibody mechanisms and potential ADE.

Concluding remarks

The complexity of Fc effector functions, such as ADCC and ADCP, arises from the interplay of multiple factors, including the binding affinity of FcγRs to the Fc region of antibodies, antibody glycosylation patterns, receptor expression levels on immune cells, and genetic variability of FcγRs. FcγR polymorphisms can significantly influence the effectiveness and safety of therapeutic antibodies by modulating Fc-mediated effector functions. Integrating genetic information on FcγR polymorphisms into clinical practice holds promise for enhancing treatment outcomes and optimizing the use of antibody-based therapies across various diseases. This may involve genotyping patients to determine the allelic distributions of FcγRs, thus identifying subsets more likely to benefit from treatment [74, 76, 118, 119]. Additionally, it is vital to understand how antibodies interact with specific FcγR variants by employing suitable bioassays and preclinical models during the development of therapeutic mAbs (Fig. 2).

Recent advances in bioassay development to assess the impact of FcγR polymorphisms have focused on improving sensitivity, reproducibility, and clinical relevance. Cell-based assays, such as ADCC reporter bioassays and primary immune cell assays, now use engineered cells or donor-derived NK cells to evaluate antibody-mediated immune activation influenced by FcγRIIIa variants (e.g. −158 V and −158F). High-resolution techniques like BLI and SPR provide precise measurements of antibody–receptor interactions, while orthogonal techniques enable detailed glycan profiling to assess the role of Fc glycosylation in receptor binding. Effector function assays using primary effector cells (e.g. PBMCs, NK cells, macrophages) are valuable for characterizing mAb therapeutics in early development. However, their variability limits their suitability for product release testing in quality control labs. Reporter gene assays, designed to reflect a product’s MoA, offer a reliable and cost-effective alternative for assessing bioactivity during characterization, lot release, and stability testing [82, 96, 106].

Future advancements in understanding Fc effector functions may involve developing knock-in mouse models or humanized immune system mice expressing specific human FcγR variants. These models could more accurately replicate human immune responses, providing essential tools for studying the differential effects of FcγR polymorphisms in vivo. Additionally, integrating machine learning techniques holds significant potential for linking in vitro bioassay data to clinical responses. By analyzing large datasets from bioassays and clinical studies (e.g. genotypes, treatment outcomes), machine learning models could predict how FcγR polymorphisms influence antibody efficacy across diverse patient populations. This information will, in turn, guide the design of in vitro bioassays to better capture the clinically relevant bioactivity of the product.

Throughout product development, it is essential to individually test and characterize the binding affinities of antibodies to Fcγ receptors, including their relevant polymorphisms, and to assess subsequent effector activities (e.g. ADCC, CDC, and ADCP) using the most sensitive binding and cell-based assays available. For mAbs with known or potential Fc effector functions, product release testing should incorporate appropriate assays to ensure consistent and controlled activity.

These analytical strategies are applicable not only to mAb therapeutics but also to other modalities such as antibody–drug conjugates (ADCs). While the primary mode of action for ADCs involves direct cytotoxicity through the intracellular release of a cytotoxic drug after specific binding to the target tumor antigen, Fc-mediated recruitment of immune cells and triggering of effector functions may also significantly contribute to overall antitumor efficacy. Evaluating immune recruitment and effector functions as critical quality attributes can guide decisions regarding linker and payload optimization. Due to variability in characterizing FcγR binding and functional activities across different programs, factors such as the relevance of effector functions to MoA, risk levels, development stages, and available resources need consideration. Nonetheless, early assessment of key binding and functional activities remains crucial for effective risk mitigation strategies.

For biosimilar mAbs or ADCs, conducting a comprehensive comparison of all binding and functional activities using multiple methods during early development is imperative to ensure analytical comparability with originator products. This rigorous approach not only fulfills expectations for comparability testing but also facilitates clinical assessment, ultimately advancing the development and accessibility of high-quality antibody therapies.

To ensure product quality, bioassays are conducted at different stages of product development, including characterization, release, and stability testing. Choosing the appropriate bioassay(s) involves considering various factors such as the antibody’s characteristics (e.g. IgG isotypes, molecular targets), intended use (e.g. characterization or release testing), clinical indication (e.g. cancer or infectious diseases), MoA, developmental stage, and regulatory requirements. Fc polymorphisms should be considered when developing bioassays for therapeutic mAbs.

Acknowledgements

The authors would like to thank our FDA colleagues Dr. David Keire, Dr. David Frucht, Dr. Shen Luo, and Ms. Alexis Dean for their critical review of the manuscript.

Author contributions

Conceptualization, J.D.T. and B.Z.; writing—original draft preparation, review, and editing, J.D.T., S.G., and B.Z.; supervision, J.D.T. and B.Z.; funding acquisition, B.Z. All authors have read and agreed to the published version of the manuscript. Julianne D. Twomey (Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Supervision, Validation, Visualization, Writing—original draft, Writing—review & editing [equal], Resources [supporting]), Sasha George (Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing—original draft, Writing—review & editing [equal], Project administration, Resources [supporting]), and Baolin Zhang (Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Validation, Visualization, Writing—original draft [equal], Funding acquisition, Resources, Supervision, Writing—review & editing [lead]).

Conflict of interest

The authors are employed by the U.S. Food and Drug Administration.

Funding

This work was funded by the U.S. Food and Drug Administration, which supported the research through its intramural programs. The funder had no role in the literature search, decision to publish, or preparation of the manuscript.

Data availability

The data that support this review are available within the article and the corresponding references cited. All references are publicly available.

Ethics and consent statement

Not applicable.

Animal research statement

Not applicable.

Disclaimer

This article reflects the views of the authors and should not be construed to represent FDA’s views or policies.

References