Considerations for optimization and validation of an in vitro PBMC derived T cell assay for immunogenicity prediction of biotherapeutics

Considerations for optimization and validation of an in vitro PBMC derived T cell assay for immunogenicity prediction of biotherapeutics

Clinical Immunology (2010) 137, 5–14 available at www.sciencedirect.com Clinical Immunology www.elsevier.com/locate/yclim Considerations for optimi...

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Clinical Immunology (2010) 137, 5–14

available at www.sciencedirect.com

Clinical Immunology www.elsevier.com/locate/yclim

Considerations for optimization and validation of an in vitro PBMC derived T cell assay for immunogenicity prediction of biotherapeutics Danika Wullner, Lei Zhou, Erica Bramhall, Andrew Kuck, Theresa J. Goletz, Steven Swanson, Narendra Chirmule, Vibha Jawa ⁎ Medical Sciences (Clinical Immunology and Biostatistics), Amgen, Thousand Oaks, CA, USA Received 6 November 2009; accepted with revision 29 June 2010 Available online 13 August 2010 KEYWORDS PBMC; ELISPOT; Immunogenicity prediction; Memory T cells; Biotherapeutics

Abstract An immune response to a biotherapeutic can be induced when the therapeutic is processed and presented by antigen presenting cell to T helper cells. This study evaluates the performance of an in vitro assay that can elicit antigen specific effector T cell responses. Two biotherapeutics with known clinical immunogenicity [FPX1 and FPX2] were assessed for their ability to induce antigen-specific IFN-γ secreting T cells in peripheral blood mononuclear cells (PBMC). The 24 amino acid peptide component of FPX1 elicited an antigen-specific response in 16/34 (47%) individual naïve healthy donors. This in vitro effect was consistent with high rate of immunogenicity which was observed when this drug was administered in clinical trials. FPX2 did not induce antigen-specific T cells in vitro, which correlates with the low rate of development of anti-drug antibody responses to this molecule in the clinic. The assay has the potential to predict immunogenicity and help in the selection of biotherapeutics at the early development stage of a clinical candidate. © 2010 Elsevier Inc. All rights reserved.

Introduction Novel protein engineering has resulted in development of various forms of therapeutic protein drugs. Fully human Abbreviations: ATA or ADA, anti-therapeutic/drug antibody; ELISPOT, enzyme-linked immunosorbent spot; FPX, fusion protein; PBMC, peripheral blood mono-nuclear cells; SFC, spot forming cells; SI, stimulation index. ⁎ Corresponding author. Amgen, Inc., One Amgen Center Drive, Thousand Oaks, CA 91320, USA. Fax: +1 805 480 1306. E-mail address: [email protected] (V. Jawa).

antibody based drugs and Fc-fusion proteins are two forms of targeted therapies being produced by the biotechnology industry. The administration of such drug products to humans may be associated with adverse events related to immune cell activation leading to T cell-dependent anti-drug antibody (ADA) responses. In addition to neutralizing the efficacy of the biotherapeutic, ADA responses can also be directed against a cross-reactive endogenous target that can lead to more serious undesired consequences [1]. Due to these potential safety effects, it is important to develop tools for screening the potential immunogenicity of biotherapeutics during clinical development.

1521-6616/$ – see front matter © 2010 Elsevier Inc. All rights reserved. doi:10.1016/j.clim.2010.06.018

6 In silico prediction algorithms have been used widely in the prediction of immune responses both in the area of vaccine and biotherapeutic development [2–4]. In the field of vaccine development, the algorithms have been useful in engineering proteins for their capacity to bind more effectively in the HLA pocket [5,6]. Similarly, in the area of protein therapeutic development, algorithm-generated information has helped reduce immunogenicity by eliminating/reducing agretopes of therapeutic proteins [7]. The limitation of the algorithm-based in silico predictions include, but are not limited to: (i) limited ability to assess tolerant epitopes, (ii) inability to account for the influence of neighboring amino acids (aa) or for aa outside the core 9mer, (iii) limited information on peptide stability in the HLA pocket [8], (iv) antigen processing and presentation within the antigen presenting cells [9], (v) ability to assess T cell activation thresholds, (vi) post-translational modifications like glycosylation, deamidation, formulation associated changes leading to aggregates or misfolding of the proteins cannot be predicted by sequence driven algorithms, and (vii) ability to predict B cell responses. PBMC-derived T cell immunogenicity assays to class II HLA peptides have been used in the field of transplantation for both immune monitoring, as well as prediction of outcomes [10,11]. Dendritic cell and CD4+ T cell co-culture assays have been used for studying immunogenicity induction by formulations containing aggregates [12]. We have evaluated an in vitro prediction assay using PBMC from naïve healthy donors derived from diverse HLA background. The requirements of the assays were as follows: (i) the ability to detect effector cell responses to proteins/peptides which bind to class II HLA, (ii) to be antigen-specific, and (iii) to be able to define acceptance criteria to differentiate responder from non-responder donors. The statistical considerations for defining acceptance criterion, assessing robustness and performance of the assay, and establishing cut point (CP) and stimulation index (SI) are presented.

D. Wullner et al. resins produced at Midwest Bio-Tech was used. F coupling reactions were performed using HBTU/HOBT active ester and FMOC removal was accomplished with 20% piperdine. Resin bound peptides were liberated from the solid support with high concentrations of TFA and precipitated with cold diethyl ether. Crude peptides were analyzed for mass identity with an ESMS mass spectrometer and then were purified using 25 × 250 mm preparative columns and purity identity was done with 2 × 50 mm analytical column. When the peptide reached purity requirements, fractions were lyophilized and weighed according to gravimetric weight needed.

Harvest and isolation of PBMC from drug naïve healthy donors PBMC were obtained from 39 naïve healthy donors from Amgen's environmental health and services department (EH&S). PBMC were isolated for functional assays using BD Vacutainer® CPT™ (Cell Preparation Tubes) with sodium heparin. The tubes were centrifuged for 30 min at 20 °C at 1600g. Plasma and PBMC were collected in 15 mL conical tubes and centrifuged for 15 min at 300g. The cell pellet was resuspended and washed with PBS twice and cryopreserved in freezing medium (Human AB serum with 10% DMSO).

HLA typing A high resolution HLA typing of whole blood was carried out by the American Red Cross (New England Region, Dedham MA). Briefly, genomic DNA was extracted using QIAGEN 96 blood kit. About 50 to 100 ng of DNA was used to group amplify HLA locus specific genes, e.g., HLA-A, HLA-B, HLADRB1, etc. All amplification primers were M13 tagged. All amplicons were purified and subsequently sequenced using M13 primer on ABI 96 capillary sequencer. The sequence data were compared to IMGT HLA gene database (January 2009) and assigned HLA alleles using Dynal analysis software.

Materials and methods Cell culture condition Human fusion protein FPX1 and FPX 2 FPX1 is a recombinant human fusion protein consisting of a human Fc fragment fused with two identical peptides comprising 24 amino acids with a high rate of predicted and clinical immunogenicity. FPX1 was synthesized internally at Amgen, Inc. as described before [13]. FPX2, a FDA approved fully human monoclonal antibody based therapeutic with low in silico predicted class II HLA amino-acid sequences and no known clinical immunogenicity, was obtained by a prescription. When experimental conditions are defined, the use of these materials in general terms is noted as “protein/peptides”.

Generation of FPX1 peptide fragments LL1 and LL2 The 24 amino acid peptide component of the fusion protein FPX1 was used in the study. To perform epitope mapping experiments, two peptides spanning amino acids LL1 (aa 1– 24, full length) and LL2 (aa 1–10, N-Terminus) were synthesized by Midwest Biotech Inc (Fishers, IN). The MOC based chemistry using pre-loaded Glu-wang and Trp-wang

Frozen PBMC (10 × 106cells/mL) were thawed using growth media at 37 °C containing 89% RPMI, 10% Human AB serum and 1% penicillin/streptomycin/glutamine mix. The cells were counted and assessed for viability using Trypan Blue stain using a Cellometer® (Nexcelom Biosciences LLC). Cells were plated at 2.0 × 106 to 2.5 × 106 cells per well in a total volume of 2 mL in a 24 well culture plate (Day 1). The viability was recorded before and after the cell culture in order to calculate the percent recovery.

PBMC stimulation assay The thawed cells were acclimatized in the culture plate overnight in a 5% CO2 incubator at 37 °C. On day 2 (24 h) following thawing of cells, medium containing recombinant human IL-2 and IL-7 (Sigma Aldrich) were added to all wells at a concentration of 10 ng/mL and 20 ng/mL, respectively. FPX1 derived LL1 and LL2, as well as FPX2, was added to the relevant wells at a concentration of 200 μg/mL. The cells were replenished with new media containing IL-2 and IL-7 on

Considerations for optimization and validation of an in vitro PBMC derived T cell assay days 5, 8 and 12 and a re-challenge with LL1 and LL2, as well as FPX2, was also performed at the previously stated challenge concentrations (a schematic of the multi-stimulation model is shown in Fig. 1). In some experiments, cells were pre-treated with anti-MHC class II antibody (L243, mouse IgG2a clone) for 30 min at a final concentration of 1 μg/mL before challenging with the test proteins [14,15].

IFN-γ ELISPOT assay Anti-human IFN-γ ELISPOT was performed using a kit (BD Pharmingen) following manufacturer's instructions. Cells from the stimulation assay described above were added to the ELISPOT plates. Briefly, 2 to 3 × 105 PBMC/100 μL were added to wells followed by 100 μL of media alone (media/ negative control), protein/peptide at 200 μg/mL, and PHA (ranging from 15 to 20 μg/mL containing 100 ng/mL of Ionomycin) was added to specific wells. IFN-γ secreting cells were counted on an Immunospot® reader (CTL, Inc.) following incubation with the secondary antibody and development with the substrate. Final results were expressed as ratios between the numbers of spot forming cells (SFCs) in wells incubated with protein/peptides or PHA and those counted in the negative control wells containing media. Table 1 provides abbreviations for the challenge antigens and their relevant stimulation during the 2 week culture and ELISPOT. The ratios that were evaluated for the controls and protein/peptide stimulated wells have also been summarized in Table 1. Assessment of recall response from FPX1 immunized donors was performed as described before [13].

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Table 1 Summary of the challenge antigens and their relevant stimulation during the 2-week culture and ELISPOT assay. Challenge during 2-week culture

ELISPOT challenge

Treatment abbreviations

Medium(M) Medium LL1(FPX1) LL1(FPX1) Medium LL2(FPX1) LL2(FPX1) Medium FPX2 FPX2

Medium(M) LL1(FPX1) Medium LL1(FPX1) LL2(FPX1) Medium LL2(FPX1) FPX2 Medium FPX2

M_M M_LL1 LL1_M LL1_LL1 M_LL2 LL2_M LL2_LL2 M_FPX2 FPX2_M FPX2_FPX2

Stimulation Index Ratio: (LL1_LL1, LL2_LL2, or FPX2_FPX2) / M_M. Specificity Ratio: (M_LL1, M_LL2, or M_FPX2) / M_M.

Prediction and characterization of T-helper epitopes FPX1 was screened for potential immunogenicity using EpiMatrix in silico system [16], as well as an in-house Tepitope based algorithm. Briefly, the 24-amino acid sequence was parsed into overlapping 9-mer frames where each frame overlaps the last by eight amino acids. Each frame was then scored for predicted binding to each of eight common Class II HLA alleles (DRB1*0101, DRB1*0301, DRB1*0401, DRB1*0701, DRB1*0801, DRB1*1101, DRB1*1301, and DRB1*1501). Due to their prevalence and their difference from each other, these eight alleles cover around 97% of human populations worldwide [17].

Phenotypic characterization of stimulated cells Antibody detection PBMC were collected at the time of re-challenge and assessed for integrity using phenotypic analysis by a flow based assay. Specifically the markers for T cells (CD4, CD3, and CD8), regulatory T cells (FoxP3), monocytes (CD14 and CD16), B cells (CD19) and NK cells (CD16/56) were assessed.

Figure 1

Antibodies directed against FPX1 were detected using a validated surface plasmon resonance (SPR)-based biosensor immunoassay using the Biacore 3000™ instrument (Biacore, Inc; Uppsala, Sweden) as previously published [13,18].

In vitro sensitization of PBMC assay format.

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Statistical methods The donor acceptance criteria and responder/non-responder criteria were established by examining the normal population on the distribution of SFC, relevant ratios and SI. The variability assessment was achieved by random effect model analysis. Logrithmic transformation of the data was performed when the SFC values could not be normally distributed both during establishing background responses and SI estimation. The comparison of stimulation index among the responders and non-responders to LL1 and LL2 peptides derived from FPX1 protein and FPX2 protein were conducted using Wilcoxon exact two sample t-test. The SFC response in medium challenged wells was compared to the respective protein challenged wells using Signed Rank statistics.

Results Optimization of the 2-week PBMC culture In comparison to a recall response where the PBMC can elicit an antigen specific response within 24 to 48 h, the antigenspecific response from PBMC derived from naïve donors' required significant optimization. Some of the parameters that were considered during the optimization were cell number, total culture time, co-stimulations, number and concentration of challenges with proteins/peptides, and optimization of readout from controls (protein/peptides, PHA and media alone). Cell concentration Cells were plated in 24-well plates at concentrations from 0.5 × 106 to 2.5 × 106 cells/ well. At the concentrations of 2 to 3.0 × 106 cells/ well, minimum impact on viability of cells was observed following 2 weeks of culture. The overall proliferation and response rate was lower and cell recovery was impacted when cell numbers lower than 2 × 106 cells were plated/well. Thus, the cell concentration used in the experiments in the 2-week culture was 2 × 106 cells/ well and above. Protein concentration for challenge The optimal dose for challenge was selected by stimulating the cells from 6 donors with a challenge dose of protein/peptides ranging from 10 to 400 μg/mL. A representative dose response curve for LL1 peptide of FPX1 is shown as Fig. 2. An increase in LL1-specific response was observed when cells were challenged with a dose curve ranging from 25 to 200 μg/mL of LL1 peptide of FPX1. The cell viability was impacted at high challenge concentrations of 400 μg/mL. Thus, an optimal IFNγ secreting T cell response was identified for FPX1 peptides/ FPX2 protein at concentration of 200 μg/mL and used for future challenge experiments for all the proteins/peptides. Each molecule to be evaluated in this assay format would need to be tested for toxicity, prior to evaluating for the immunogenicity potential. Number of challenges Fig. 3 shows the comparison of the number of IFN-γ secreting cells following single vs. multiple challenges with the FPX1 derived peptide (LL1). No measurable response was observed

D. Wullner et al. with a single challenge. A minimum of 4 challenges with the protein/peptide were required to elicit low frequency antigen specific T cells from the PBMC population.

Table 2 Details of individual donor haplotypes and their SI response to FPX1 (LL1), FPX1 (LL2) and FPX2. Donors HLA HLA Responder Responder Responder Allele 1 Allele 2 (LL1) (LL2) (FPX2) 1 401 1101 2 1302 1501 3 401 1405 4 701 1104 5 301 1501 6 701 1501 7 401 1101 8 404 1501 9 403 701 10 101 1501 11 901 1502 12 405 1501 13 1103 1302 14 701 901 15 701 801 16 301 1501 17 101 404 18 404 1501 19 1001 1301 20 701 1501 21 101 101 22 101 1502 23 701 1301 24 701 1301 25 901 1502 26 401 701 27 701 1501 28 1454 1501 29 301 701 30 301 1501 31 408 701 32 701 1201 33 901 1502 34 405 1501 35 1103 1302 36 301 1501 37 1301 1501 38 301 701 39 301 1401 Donors tested No of Responders

33.75 1.9 3.22 3.11 20.31 9.33 N N 4.0 3.60 N N na 1.83 N 3.3 N N N N 2.40 2.79 N N N 4.25 N 2.90 N N N na na na na N 1.85 18.20 3.44 34 16*

N N na N N na na na N na N 12 na na N na na na N na na na na na na na na N N na na N N N N na na na na 15 1

N N N N N N N N N N N na N na na na na na N na na na na na na na na na na N N N N N N na na na na 19 0

High resolution haplotyping for HLA-DR alleles was performed for 39 donors tested for reactivity to FPX1 (LL1, LL2) and/or FPX2 proteins. Thirty-four of the 39 donors were tested for reactivity to FPX1 (LL1), 15 of the 39 donors were tested for reactivity to LL2 and 19 of the 39 donors were tested for reactivity to FPX2. No significant associations of alleles and their reactivity could be made in the donors tested across all three molecules. na: in vitro assay not performed; SI values provided for donors with responses >/=1.82. N: did not meet the criterion for responders (SI b 1.82); * 1/17 donors did not pass all assay criterion and was hence excluded as a responder.

Considerations for optimization and validation of an in vitro PBMC derived T cell assay

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Phenotypic characterization PBMC were collected from various time-points of culture (days 1, 5, 9 and 12) and assessed for their cell surface markers and integrity. The predominant cell type present was CD4+ T cells (ranging from 41% to 51%). The numbers of antigen presenting cells present at the end of 2 weeks of culture were ~2% of CD14 positive cells, ~8% of CD16 positive cells, ~0.5% FoxP3 regulatory T cells and ~21% of CD19 positive B cells. To assess whether the 2 week long culture induced the generation of a bystander cell population, the natural killer (NK) cell population was assessed. The NK cell population reduced from ~7.5% to ~3.5% from day 1 to day 14. MHC class II restriction In order to confirm that the presentation of the proteins to the antigen presenting cells was in the context of Class II MHC, PBMC from the LL1 responders were pre-treated with an anti-HLA DR blocking antibody. An average reduction of 40% of response (IFN-γ secreting SFC) was observed in 6 donors tested.

Assessment of assay performance and robustness and establishing the acceptance criterion Assay precision and robustness The impact due to variables such as analyst, day, plate, and donors on the performance of the assay were evaluated. The inter-assay precision was evaluated by assessing the performance of negative (medium alone) and positive (PHA stimulated cells) control on PBMC from same individual donors run on different days, different plates and 2 different analysts. The ELISPOT SFC counts of cells cultured with medium alone showed that the donor to donor variability was highest due to the lower number of SFCs associated with control wells. In contrast, PHA-stimulated cells elicited a variability of 11%

Figure 3 Multiple challenges were required for eliciting a FPX1 (LL1) specific response. PBMC from 5 naïve healthy donors were thawed and plated in 24 well plates for 2 weeks. The induction of FPX1 (LL1) specific PBMC was assessed following single versus 4 challenges with FPX1 peptide LL1. For single challenge, the LL1 peptides were added to the d16 medium treated cells at a concentration of 200 μg/mL/well at d2 following thawing of cells. For multiple challenges, the PBMC were challenged with LL1 peptides on days 2, 5, 9 and 12. The LL1 specific PBMC were then assessed in cells from both the conditions using an IFN-γ ELISPOT assay. PBMC that were challenged multiple times presented with a higher stimulation index (fold rise over the medium treated unchallenged controls) than the PBMC that were challenged only once. Two donors (donors 1 and 3) did present with a 1.84 and 1.85 fold rise following single challenge, however, multiple challenges helped amplify the induction of LL1 specific cells several fold in these 2 subjects.

(donor to donor), 12% (within donor, repeatability) and 16% (overall) on the SFC scale. Reproducibility was assessed using a subset of the responders (n = 6) and non responders (n = 6) in multiple runs. All six responders and non-responders tested were consistent in their reactivity to LL1 when tested in 2 separate runs (data not shown).

Establishment of acceptance criteria for defining a responder Five separate acceptance criteria were established to determine a responder in the in vitro 2-week culture assay

Figure 2 Dose response of naive PBMC following challenge with increasing concentrations of LL1 peptide of FPX1 protein. PBMC from 6 naïve healthy donors were challenged with increasing concentrations of FPX1 (LL1) ranging from 0 to 400 μg/mL. The LL1 specific PBMC were evaluated using an IFN-γ ELISPOT assay. A dose-dependent increase in the LL1 specific PBMC was observed. A significant induction of LL1 SFC was observed at doses of 25 to 200 μg/mL (SI ranging from 2.2 to 5.9). A decline in LL1 specific SFC was observed at the highest dose of 400 μg/mL.

i) Cell viability criteria: The average viability of cells with an optimal functional response to PHA in the assay was determined to be 86% derived from the average response from all the 30 individuals tested that had a viability ranging from 73% to 95%. ii) PHA response criteria: For a donor to be considered for evaluation as a responder, the positive control response (PHA-stimulated cells) in both media treated cells and peptide/protein challenged cells had to be greater than an average count of 428 SFCs. iii) Cut point criteria for a background response: The number of IFN-γ secreting SFC in the wells challenged with the antigen (LL1, LL2 and FPX2 proteins) were normalized by

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D. Wullner et al. log transformation of values from donors tested (34 donors for LL1 peptide of FPX1, 15 donors for LL2 peptide of FPX1 and 19 donors for FPX2 protein) and prediction limits were evaluated. The cut point criterion for background response for cells treated with the relevant proteins was determined to be 19 SFCs, which is the geometric mean of the SFC responses derived from donors listed above. Thus, a minimal SFC criterion of 19 SFCs/ 3×105 PBMC was included as one of the criterion for a positive response. iv) Stimulation index (SI) criteria: SI is defined as a ratio of the SFCs from the protein/peptide challenged/ELISPOT treated PBMC (LL1_LL1, LL2_LL2, or FPX2_FPX2) divided by SFCs from unchallenged medium treated PBMC (M_M). A SI of 1.82 was established based on a geometric mean of the ratios from donors tested. Hence, any donor would be considered a responder if the ratio of SFCs from protein challenged PBMC/medium treated controls was 1.82 fold or greater. v) Specificity ratio (SR): A SR was calculated for all donors to confirm that the response at the end of the 2-week multiple challenge experiment was antigen specific. The SR helped eliminate any non-specific background/noise due to the cells being maintained in culture for 2 weeks and the impact on cell viability and function The ratio was defined as follows: SFC response from donor PBMC treated with the IL-2 and IL-7 containing medium for 2 weeks and challenged with protein/peptides at ELISPOT step (M_LL1, M_LL2, and M_FPX2) / SFC response from donor PBMC treated with the IL-2 and IL-7 containing medium for 2 weeks with no protein/peptide challenge (M_M). Hence, any donor would be removed as responder if the ratio was 1.82 fold or greater.

Elicitation of naïve human PBMC response from protein based therapeutics Using the optimized conditions and acceptance criterion described above, naïve human PBMC were exposed to 2 biotherapeutics; one was the 24 aa peptide component (LL1) of FPX1 that had been shown to induce immunogenicity in the clinic and another, a fully human monoclonal antibody based therapeutic (FPX2) that had no reported clinical immunogenicity. Both the molecules were assessed in the 2week in vitro assay using naïve PBMC from 39 unique healthy donors. All 39 donors met the criteria for cell viability (N 86%), and PHA responses (N428 SFC) [19]. Thirty-four of the 39 donors tested for induction of antigen specific T cells from drug naïve human PBMC with FPX1 (LL1), 17 donors met the acceptance criteria for a positive response as presented with a SI ≥ 1.82 fold compared to medium-treated cells. The antigen specificity was determined by assessing the lack of a response in cultures without protein/peptide. One donor demonstrated a SR ≥ 1.82 in the 2-week medium-cultured cells, stimulated with LL1 (described above under specificity criterion). This donor failed the specificity acceptance criteria and was not considered as a positive responder. The response (SFC/ 3 × 105cells/well) in all 16 responders was above the cut point of 19 SFCs (Fig. 4A). The FPX2 protein did not elicit an

antigen-specific response ≥ 1.82 fold from the 19 donors tested (Fig. 4B).

Mapping of the T cell response within peptides derived from FPX1 protein Eleven donors that were tested for reactivity to the LL1 peptide of FPX1 protein (24 amino acid peptide containing both N and C terminus regions) were also challenged with LL2 peptide (N-terminus region of the FPX1 peptide). One of the 6 responders to LL1 also elicited a response to LL2. Therefore, the C-terminus region of the LL1 peptide in FPX1 could be associated with regions of higher likelihood to induce T cell activation. These observations are consistent with the recall responses to the C-terminus region of LL1 previously published by our group [13].

Association of the LL1 specific PBMC response to clinical immunogenicity FPX1 and FPX2 proteins had been both administered in the clinical setting and their immunogenic potential had been established. LL1 had been shown to be immunogenic both in clinic and by in silico prediction. LL2, in comparison, was predicted to be non-immunogenic with no promiscuous epitopes or clusters, as determined by in silico prediction [13]. FPX2 is a fully human monoclonal antibody based therapeutic with very low rate (b1%) of reported immunogenicity. In silico prediction by EpiMatrix, showed no presence of agretopes against the 8 major alleles tested [20]. An association could be made between the higher rate of reactive PBMC elicited by LL1 (47%) and the immunogenicity observed in clinic from individuals dosed with FPX1 (40%) (Table 3). The mean of the recall response for LL1 stimulated PBMC was at a SI of 3.81 with 95% confidence interval (1.98, 7.33). Similarly, the mean of the recall response for LL2 stimulated PBMC was 1.21 with 95% confidence interval (1.03, 1.40). In contrast, the incidence of immunogenicity for FPX2 was only 1% in clinic that associated with absence of FPX2 reactive T cells in the assay.

Discussion We have evaluated the performance of an in vitro PBMC assay, which uses PBMC from healthy donors, cultured in the presence of exogenous cytokines, IL-2 and IL-7, to predict the potential immunogenicity of protein therapeutics. Acceptance criteria for establishing the cut-point for a positive response and overall response rate of the test population were defined with statistical and empirical considerations. Biotherapeutics undergo evaluation for immunogenicity during the toxicity and safety assessment stage of clinical development. While rodent and non-human primate models are both helpful and required for predicting dose limiting toxicity and dose ranges for designing first-in-human studies, they do not reliably predict immunogenicity in humans. Some specialized animal models like HLA transgenic mice and HuSCID mice have been used to predict anti-therapeutic immune response and vaccine antigenicity [20–23].

Considerations for optimization and validation of an in vitro PBMC derived T cell assay

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Figure 4 (A) Box-plot of IFN-γ secreting spot forming cells in PBMC from naïve healthy subjects challenged with FPX1 (LL1 and LL2 peptides) and FPX2 protein. The distribution of IFN-γ secreting spot forming cells (SFCs) /3e5 cells /well from PBMC derived from 39 naïve donors were summarized in this box-plot. The response was presented on the square root scale. The LL1 peptide (comprised of both Cterminus and N-terminus end of the 24 aa peptide from FPX1 protein) and LL2 (a 13 aa peptide derived from N-terminus end of LL1 peptide) were assessed separately for their ability to elicit the respective antigen specific response in the form of IFN-γ secreting T cells. The dot represents mean and the cross represents median. The top and bottom of the boxes are 25 and 75 percentiles and the top and bottom of whiskers are 75 percentile +1.5IQR and 25 percentile −1.5IQR, where IQR is the distance between 75 percentile and 25 percentile. All the observations are also presented in the graph as stars. An observation is identified as a statistical outlier if it falls outside the top and bottom of the whiskers. The response in medium challenged wells was compared to the respective protein challenged wells using signed rank statistics. The average background cut point was 19 SFCs which was derived from the distribution of the SFCs in the protein challenged cells for 2 weeks followed by media challenge at ELISPOT stage. A significant number of LL1 specific IFN-γ secreting cells were elicited as compared to the medium challenged cells (p b 0.001). In comparison, no significant increase in IFN-γ secreting cells was observed following LL2 (p b 0.4) and FPX2 (p b 0.5) challenge in the same set of donors. (B) Box-plot of stimulation Index of responders and non-responders to LL1 and LL2 peptides derived from FPX1 and FPX2 protein. The stimulation index of responders (SI ≥ 1.82 fold) and non-responders (SI ‹ 1.82) to LL1 and LL2 peptides of FPX1 protein and the whole FPX 2 protein were summarized in this box-plot. The stimulation index was presented on the square root scale. The LL1 peptide (comprised of both C-terminus and N-terminus end of the 24 aa peptide from FPX1 protein) and LL2 (a 13 aa peptide derived from N-terminus end of LL1 peptide) were assessed separately for their ability to elicit the respective antigen-specific response in the form of IFN-γ secreting T cells in PBMC from 39 naïve donors. The dot represents mean and the cross represents median. The top and bottom of the boxes are 25 and 75 percentiles and the top and bottom of whiskers are 75 percentile +1.5IQR and 25 percentile −1.5IQR, where IQR is the distance between 75 percentile and 25 percentile. All the observations are also presented in the graph as blue stars. An observation is identified as a statistical outlier if it falls outside the top and bottom of the whiskers. The responders and non-responders were compared between groups using Wilcoxon Exact Two Sample t-test. LL1/Responder was statistically different (p b 0.0001) from LL1/Non-responder, LL2/Non-responder and FPX2/Non-responder.

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Table 3 Summary of naïve and recall T cell responses from naïve donors and FPX1 and FPX2 dosed subjects and their correlation to the antibody incidence. PBMC challenge

Percent of responders from naïve donor derived Percent of responders from subjects Percent incidence of antiT cells (number of responders/total tested by in dosed with FPX1 (number of responders/ drug antibodies from subjects vitro T cell prediction assay) total tested by recall T cell assay) dosed with FPX 1 and FPX 2

LL1 (FPX1) 47 (16/34) LL2 (FPX1) 6.6 (1/15) FPX2 0 (0/19)

66.6 (10/15) 6.6 (1/15) NA

40 NA* 1

PBMC derived from healthy donors that were never exposed to FPX1 before were challenged multiple times (n = 4) in the in vitro assays with FPX1. The donors that elicited an effector T cell response as measured by IFN-γ secretion following multiple challenges with the 24 aa peptide component of FPX1 were considered as responders. LL2 (the N-terminus region of the LL1 peptide) and FPX2 protein both failed to elicit any response in the drug naïve donors. The recall effector T cell response to FPX1 in healthy subjects as measured by IFN-γ secretion following single dose subcutaneous/intravenous administration of FPX1 was also high compared to LL2 and FPX2 responses. The high effector response to LL1 was in agreement with the high incidence of anti drug antibodies in the serum from the FPX1 dosed subjects compared to FPX2. *LL2 is the N-terminus region of the FPX1 peptide. Hence, antibodies were tested against the whole protein and not against LL2 peptide alone.

Recent advances in in silico algorithms that identify potential HLA class II agretopes suggest a role for immunogenicity prediction to assess risk during drug development [24– 27]. These systems evaluate the potential binding of a peptide sequence to HLA molecules to predict immunogenicity. In order to measure the down-stream consequence of this MHC binding, we have optimized an in vitro T cell functional assay, which tests the ability of PBMC to respond to antigen-specific stimulation with an IFN-γ ELISPOT assay. The advantages of the ELISPOT assay are that it is relatively simple to perform, does not require large numbers of cells, can utilize previously frozen cells, and is sensitive [28]. During the design of experimental conditions, exogenous IL-2 and IL-7 was added in the culture to partially mimic the cytokine environment in the lymph node. IL-7, made by stromal and epithelial cells in the secondary lymph nodes promotes survival, and IL-2 has been shown to favor the generation of effector T cells [29]. The precursor frequency of polyclonal naïve CD4+ T cells to a particular antigen ranges from 20 to 200 cells/1 × 106 PBMC [30]. In order to observe optimal stimulation of such low precursor frequency T cells, optimization experiments demonstrated that at least 4 stimulations cycles were necessary to induce detectable ELISPOT response, consistently. The dose of the protein therapeutic for stimulation was at a concentration representing the in vivo Cmax of the pharmacokinetic profile of the FPX1. Validation of the assay conditions resulted in several run- and sample-passing acceptance criteria. The cut-point for background ELISPOT responses was established using a nonparametric approach, following log-transformation. Consistent with the other groups [31,32], the coefficient of variation was dependent on the strength of the SFC response. Thus, the intraassay precision for PBMC from different donors was within a CV of 20% for PHA stimulated cells, and N 50% for negative controls, where the SFCs were less than 50. Analysis of contributors of variability demonstrated that biological variability across donors was the highest contributor. The in vitro assay predicted LL1 peptide of FPX1 molecule to be more immunogenic than LL2 peptide [13]. However, no direct association with HLA-binding agretopes and in vitro prediction among the 16 responding donors was observed (Table 2). This observation suggests that several other factors such as heterozygosity of the alleles, stability of peptide–HLA complex, internalization and antigen processing, role of regulatory T cells, etc. could play a role in the final outcome

of the in vitro assay. The peptides (LL1 and LL2) used in the current assay can bypass processing and can be presented directly to T cells unlike a whole protein (FPX2) that would require processing to be presented. The lack of reactivity of FPX2 in the assay could be due to lack of immunogenic epitopes or presence of regulatory T cell epitopes and needs further investigation. The advantages of the in vitro PBMC include the limited requirement of blood volume, the ease of performance of the assay providing the potential for high throughput. The in vitro PBMC assay has some limitations. As the PBMC in the current assay format are derived from naïve donors and not from in vivo antigen primed subjects, the precursor frequency of the antigen specific cells is expected to be low. The use of total PBMC which contain several cell types which could secrete IFN-γ (NK cells, NKT cells, CD8 T cells), and are not involved in the HLA class IITCR activation pathway can contribute to non-specificity. The optimized in vitro concentration of protein required for challenge may be non-physiologic, potentially due to limited antigen presenting population and/or co-stimulation. The response rate of T cells could be further optimized by coculture of optimal antigen presenting cells: T cell ratios. Assessment of other read-outs of T cells, such as activation induced cell surface markers, a panel of cytokines, proliferation and apoptosis, could further improve the sensitivity of the in vitro response. In this respect, Baker et al. [33] have utilized purified CD4+ T cells and dendritic cells and demonstrate that T cell responses to an HLA-class II binding epitope could be eliminated through de-immunization. Some attempts to replicate the human environment have been made by the artificial lymph-node assays [34,35]. However, their ability to predict immunogenicity of therapeutic protein remains to be evaluated. The advantage of co-culture assays is the use of various ratios of purified antigen presenting cells with autologous T cells for processing and presenting of the protein/peptides. Thus, further refinement of the in vitro conditions may provide a better probability of developing T cell prediction assays. In summary, we have developed an in vitro PBMC derived T cell assay, to predict the immunogenicity potential of therapeutic proteins. The assay has the capability to elicit a response from a PBMC population with low frequency of antigen specific T cells, and is capable of distinguishing therapeutic proteins with high and low immunogenicity potential. The analysis of results from this assay will provide

Considerations for optimization and validation of an in vitro PBMC derived T cell assay guidelines in further development of more sensitive methods of in vitro and in vivo assays which can predict the immunogenicity of protein therapeutics. In silico and in vitro approaches can be used in conjunction to predict the immunogenicity of therapeutics during early development and rank order the candidates for their immunogenic potential. An overall approach to pre-clinical immunogenicity testing could initiate with a high-throughput in-silico screening, progress to ex-vivo evaluation (as described in this paper), and finish with in-vivo models based on transgenic animals. The impact of pre-clinical immunogenicity screening is to decrease the cost of drug development by avoiding costly immunogenicity problems in the clinical setting. A number of failures (related to immunogenicity) and successes (related to correctly predicting immunogenicity or identifying immunogenicity as the root cause of a serious adverse effect) have contributed to the acceptance of immunogenicity screening as an essential component of the drug-development process.

Acknowledgments We thank Keith Kelley and John Thomas for their help with the flow based assays; and Eugene Koren, Arunan Kaliyaperumal and John Ferbas for their helpful comments. This work was done at Amgen and all the authors hold company stock.

References [1] S. Swanson, J. Ferbas, P. Mayeux, N. Casadevall, Evaluation of methods to detect and characterize antibodies against recombinant human erythropoietin, Nephron Clin. Pract. 96 (2004) 88–95. [2] A. DeGroot, J. McMurry, L. Moise, Prediction of Immunogenicity: in silico paradigms, ex vivo and in vivo correlated, Curr. Opin. Pharmacol. 8 (2008) 620–626. [3] R. Vita, L. Zarebski, J. Greenbaum, H. Emami, I. Hoof, N. Salimi, R. Damle, A. Sette, B. Peters, The Immune Epitope Database 2.0, Nucleic Acids Res. 38 (2010) D854–D862. [4] B. Peters, A. Sette, Integrating epitope data into the emerging web of biomedical knowledge resources, Nat. Rev. Immunol. 7 (2007) 485–490. [5] A. DeGroot, B. Jesdale, W. Martin, C. Saint-Aubin, H. Sbai, A. Bosma, J. Lieberman, G. Skowron, F. Mansourati, K. Mayer, Mapping cross-clade HIV-1 vaccine epitopes using a bioinformatics approach, Vaccine 21 (2003) 4486–4504. [6] A. DeGroot, A. Bosma, N. Chinai, J. Frost, B. Jessdale, A. Gonzales, W. Martin, C. Saint-AubinS, B. Jesdale, From genome to vaccine: in silico predictions; ex vivo verification, Vaccine 19 (2001) 4385–4395. [7] P. Stas, I. Lasters, Strategies for preclinical immunogenicity assessment of protein therapeutics, IDrugs 12 (2009) 169–173. [8] I. Doytchinova, D. Flower, Towards the in silico identification of class II restricted T-cell epitopes: a partial least squares iterative self-consistent algorithm for affinity prediction, Bioinformatics 19 (2003) 2263–2270. [9] N. Petrovskya, V. Brusic, Virtual models of the HLA class I antigen processing pathway, Methods 34 (2004) 429–435. [10] N. Najafian, A. Salama, E. Fedoseyeva, G. Benichou, M. Sayegh, Enzyme-linked immunosorbent spot assay analysis of peripheral blood lymphocyte reactivity to donor HLA-DR peptides: potential novel assay for prediction of outcomes for renal transplant recipients, Am. Soc. Nephrol. 13 (2002) 252–259.

13

[11] M. Hernandez-Fuentes, A. Salama, In vitro assays for immune monitoring in transplantation, Transplantation immunology: methods and protocols, vol. 269, 2006, pp. 269–290. [12] A. Jaber, M. Baker, Assessment of the immunogenicity of different interferonbeta-1a formulations using ex vivo T-cell assays, J. Pharm. Biomed. Anal. 43 (2007) 1256–1261. [13] E. Koren, A. De Groot, V. Jawa, K. Beck, T. Boone, D. Rivera, L. Li, D. Mytych, M. Koscec, D. Weeraratne, S. Swanson, W. Martin, Clinical validation of the “in silico” prediction of immunogenicity of a human recombinant therapeutic protein, Clin. Immunol. 124 (2007) 26–32. [14] R. Thomas, P. Lipsky, Human peripheral blood dendritic cell subsets. Isolation and characterization of precursor and mature antigen-presenting cells, J. Immunol. 153 (1994) 4016. [15] D. Wilde, P. Marrack, J. Kappler, D. Dialynas, F. Fitch, Evidence implicating L3T4 in Class II MHC antigen reactivity; monoclonal antibody GK1.5 (ANTbL3T4a) blocks Class II MHC antigenspecific proliferation, release of lymphokines and binding by cloned murine helper T lymphocyte lines, J. Immunol. 131 (1983) 2178–2183. [16] A. De Groot, B. Jesdale, E. Szu, J. Schafer, R. Chicz, G. Deocampo, An interactive website providing MHC ligand predictions: application to HIV research, AIDS Res. Hum. Retroviruses 13 (1997) 539–541. [17] S. Southwood, J. Sidney, A. Kondo, M. Guercio, E. Appella, S. Hoffman, R. Kubo, R. Chestnut, H. Grey, A. Sette, Several common HLA-DR types share largely overlapping peptide binding repertoires, J. Immunol. 3 (1998) 3363–3373. [18] S. Mason, S. La, D. Mytych, S. Swanson, J. Ferbas, Validation of the BIACORE 3000 platform for detection of antibodies against erythropoietic agents in human serum samples, Curr. Med. Res. Opin. 9 (2003) 651–659. [19] Y. Liu, S. Daley, V. Evdokimova, D. Zdobinski, D. Potter, L. Butterfield, Hierarchy of fetoprotein (AFP)-specific T cell responses in subjects with AFP-positive hepatocellular cancer, J. Immunol. 177 (2006) 712–721. [20] A. De Groot, J. McMurry, L. Moise, Prediction of immunogenicity: in silico paradigms, ex vivo and in vivo correlated, Curr. Opin. Pharmacol. 8 (2008) 620–626. [21] G. Aldrovandi, G. Feuer, L. Gao, B. Jamieson, M. Kristeva, I. Chen, J. Zack, The SCID-hu mouse as a model for HIV-1 infection, Nat. Immunol. 363 (1993) 732–736. [22] C. Pendley, A. Schantz, C. Wagner, Immunogenicity of therapeutic monoclonal antibodies, Curr. Opin. Mol. Ther. 5 (2003) 172–179. [23] H. Kropshofer, T. Singer, Overview of cell-based tools for preclinical assessment of immunogenicity of biotherapeutics, J. Immunotoxicol. 3 (2006) 131–136. [24] I. Van Walle, Y. Gansemans, P. Parren, P. Stas, I. Lasters, Immunogenicity screening in protein drug development, Expert Opin. Biol. Ther. 7 (2007) 405–418. [25] P. Wang, J. Sidney, C. Dow, B. Mothe, A. Sette, B. Peters, A systematic assessment of MHC class II peptide binding predictions and evaluation of a consensus approach.", PLoS Comput. Biol. 4 (2008) 1–10. [26] Y. EL-Manzalawy, D. Dobbs, V. Honavar, On evaluating MHC-II binding peptide prediction methods, PLoS Comput. Biol. 3 (2008) 1–16. [27] Q. Zhang, P. Wang, Y. Kim, P. Haste-Anderson, J. Beaver, P. Bourne, H. Bui, S. Buus, S. Frankild, J. Greenbaum, O. Lund, C. Lundegaard, M. Nielsen, J. Ponomarenko, A. Sette, Z. Zhu, and B. Peters, Immune epitope database analysis resource (IEDBAR). Nucleic Acid Res. 36 W513-518. [28] A. Hobeika, M. Morse, T. Osada, M. Ghanyem, D. Niedzwicki, R. Barrier, H. Lyerly, T. Clay, Enumerating antigen-specific T cell responses in peripheral blood: a comparison of peptide MHC Tetramer, ELISpot and intracellular cytokine analysis, J. Immunother. 28 (2005) 63–72.

14 [29] A. Ma, R. Koka, P. Burkett, Diverse functions of IL-2, IL-15 and IL-7 in lymphoid homeostasis, Ann. Rev. Immunol. 24 (2006) 657–659. [30] J. Hataye, J. Moon, A. Khoruts, C. Reilly, M. Jenkins, Naive and memory CD4+ T cell survival controlled by clonal abundance, Science 312 (2006) 114–116. [31] S. Janetzki, J. Cox, N. Oden, G. Ferrari, Standardization and validation issues of the ELISPOT assay, Handbook of ELISPOT: Methods and Protocols, vol. 302, 2005, pp. 51–86. [32] J. Smith, H. Joseph, T. Green, J. Field, M. Wooters, R. Kaufhold, J. Antonello, M. Caulfield, Establishing acceptance criteria for cell-mediated immunity assays using frozen peripheral blood mononuclear cells stored under optimal and

D. Wullner et al. suboptimal conditions, Clin. Vaccine Immunol. 14 (2007) 527–537. [33] M. Baker, T. Jones, Identification and removal of immunogenicity in therapeutic proteins, Curr. Opin. Drug Discov. Dev. 10 (2007) 219. [34] C. Qu, V. Nguyen, M. Merad, and R.G., MHC Class I/peptide transfer between dendritic cells overcomes poor cross-presentation by monocyte-derived APCs that engulf dying cells. J. Immunology 182 3650. [35] C. Giese, U. Marx, Artificial Human Lymphnode: A device for Generation of Human Antibodies and Testing for Immune Functions in vitro, Cell Technology for Cell Products Book CHAPTER V, 2007, pp. 285–290.