Internalization of therapeutic antibodies into dendritic cells as a risk factor for immunogenicity

Abstract

Introduction: Immunogenicity, the unwanted immune response triggered by therapeutic antibodies, poses significant challenges in biotherapeutic development. This response can lead to the production of anti-drug antibodies, potentially compromising the efficacy and safety of treatments. The internalization of therapeutic antibodies into dendritic cells (DCs) is a critical factor influencing immunogenicity. Using monoclonal antibodies, with differences in non-specific cellular uptake, as tools to explore the impact on the overall risk of immunogenicity, this study explores how internalization influences peptide presentation and subsequently T cell activation.

Materials and methods: To investigate the impact of antibody internalization on immunogenicity, untargeted toolantibodies with engineered positive or negative charge patches were utilized. Immature monocyte-derived DCs (moDCs), known for their physiologically relevant high endocytic activity, were employed for internalization assays, while mature moDCs were used for MHC-II associated peptide proteomics (MAPPs) assays. In addition to the lysosomal accumulation and peptide presentation, subsequent CD4+ T cell activation has been assessed. Consequently, a known CD4+ T cell epitope from ovalbumin was inserted into the tool antibodies to evaluate T cell activation on a single, shared epitope.

Results: Antibodies with positive charge patches exhibited higher rates of lysosomal accumulation and epitope presentation compared to those with negative charge patches or neutral surface charge. Furthermore, a direct correlation between internalization rate and presentation on MHC-II molecules could be established. To explore the link between internalization, peptide presentation and CD4+ T cell activation, tool antibodies containing the same OVA epitope were used. Previous observations were not altered by the insertion of the OVA epitope and ultimately, an enhanced CD4+ T cell response correlated with increased internalization in DCs and peptide presentation.

Discussion: These findings demonstrate that the biophysical properties of therapeutic antibodies, particularly surface charge, play a crucial role in their internalization into DCs. Antibodies internalized faster and processed by DCs, are also more prone to be presented on their surface leading to a higher risk of triggering an immune response. These insights underscore the importance of considering antibody surface charge and other properties that enhance cellular accumulation during the preclinical development of biotherapeutics to mitigate immunogenicity risks.

Keywords: biotherapeutics; charge patches; dendritic cells; immunogenicity; internalization.

Figure 1

The modification of biophysical properties such as the insertion of charge patches or the modification of charge distribution alters the internalization rate of untargeted antibody variants. The dot plot represents the relative internalization rate of each variant normalized to var1, where the internalization rate of var1 lies at 1 (each color representing a donor, n=9). The internalization rate corresponds to the slope of the mean fluorescence, (gMFI, subtracted for background over time (0, 120 min, normalized to each dosing solution fluorescence). The mean fold change to var1 is displayed for each group along with the 95% confidence interval. A mixed effect model with random donor intercepts on log transformed data has been applied and the effect of changing the antibody sequence (variants) compared to var1 (parental mAb) was assessed by the least squares mean method corrected for multiple comparison (p< 0.001= ***; p< 0.05= *). The isopotential surfaces of one of each antibodies’ Fabs (viewed from the top, looking at the CDR region) are shown (blue: positive charges; red: negative charges, gray neutral). Isocontour renderings shown were generated using Discovery Studio (BIOVIA, Dassault Systèmes, Discovery Studio 2019, version 19.1.0.18217, San Diego: Dassault Systèmes).

Figure 2

Increased cellular accumulation rate leads to increased peptide presentation. (A) Analysis of the T cell epitope content for the five antibody variants. The differences in amino acids to var1 are highlighted (color corresponding to the amino acid). Epitopes detected by MAPPs (in orange, annotated with the proportion of donors presenting the T cell epitope) are represented together with T cell epitope prediction (annotated with the number of strong binders, SB) along the amino acid sequence. T cell epitope predictions in blue are common to all variants whereas the ones in pink and red are respectively specific for var104 and var112. (B) Comparison of the MAPPs score for the different antibody variants. The MAPPs score summarizes the number of epitopes detected and their signal intensities (nepitopes x mean(log2(signal)) normalized to var1 (each color representing a donor, n=9). The mean fold change to var1 is displayed for each group along with the 95% confidence interval. A mixed effect model with random donor intercepts on log transformed data has been applied and the effect of changing the antibody sequence (variants) compared to var1 (parental mAb) was assessed by the least squares mean method corrected for multiple comparison (p< 0.01= **; p< 0.05= *). (C) Correlation plot of the MAPPs score according to the DC internalization rate. Relative MAPPs score and DC internalization rate were obtained by taking the mean of all the tested donors (n=9). Pearson’s correlation was used and the 95% confidence interval is displayed.

Figure 3

A donor propensity for faster cellular accumulation leads to an increased peptide presentation in MAPPs. Correlation plot of the MAPPs score according to the DC internalization rate. The change over batch average was obtained by taking the mean across all the 5 tested antibodies within a donor, divided by the average across all the donors and antibodies tested in the corresponding batch. Pearson’s correlation was used and the 95% confidence interval is displayed.

Figure 4

Generation and characterization of ovalbumin CD4+ T cell epitope (OVAp) containing variants. (A) Bar plot representing the relative internalization rates of mAb variants before (-) and after (+) the insertion of the OVAp (n=2, 95% confidence interval). (B) Bar plot representing the relative MAPPs score of mAb variants before (-) and after (+) the insertion of the OVAp (n=2, 95% confidence interval). (C) Analysis of the T cell epitope content of var1 and var112. The differences in amino acids to var1 are highlighted (color corresponding to the amino acid). Epitopes detected by MAPPs (annotated with the proportion of donors presenting the T cell epitope) of the initial variants (in orange) are represented together with the epitopes detected by MAPPs for the OVAp variants (in green) along the amino acid sequence. Only the predicted T cell epitopes induced by the insertion of the OVAp are represented (in blue, common to all variants).

Figure 5

Increased CD4+ T cell activation following increased internalization and peptide presentation directed towards a common epitope. (A) Representation of the assay response rate (n= 20) from 7 blood donors according to the treatment. The proportion of positive wells are shown in green, blue and red bars. As positive control T cells have been expanded using autologous moDCs incubated with KLH and their response has been assessed at week 4 by IFNy ELISPOT (red). For the antibody variants, T cells have been expanded using autologous moDCs incubated with var1 (green) or var112 (blue) and their response to autologous moDCs incubated with OVA has been assessed at week 4 by IFNy ELISPOT (see Material and Methods). (B) Estimation of the number of T cell precursors for the two tested variants. The calculation has been done according to Delluc et al., 2011. In short the Frequency = -Ln (negative wells/total wells tested)/(CD4 T cells/well)). A one-sided paired T-test has been performed (p< 0.05= *).