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Search Results (12)

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Keywords = afucosylated antibody

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17 pages, 1347 KiB  
Article
A Novel Glycoengineered Humanized Antibody Targeting DLK1 Exhibits Potent Anti-Tumor Activity in DLK1-Expressing Liver Cancer Cell Xenograft Models
by Koji Nakamura, Kota Takahashi, Izumi Sakaguchi, Takumi Satoh, Lingyi Zhang, Hiroyuki Yanai and Yukihito Tsukumo
Int. J. Mol. Sci. 2024, 25(24), 13627; https://doi.org/10.3390/ijms252413627 - 19 Dec 2024
Viewed by 424
Abstract
Delta-like 1 homolog (DLK1), a non-canonical Notch ligand, is highly expressed in various malignant tumors, especially in hepatocellular carcinoma (HCC). CBA-1205 is an afucosylated humanized antibody against DLK1 with enhanced antibody-dependent cellular cytotoxicity (ADCC). The binding characteristics of CBA-1205 were analyzed by enzyme-linked [...] Read more.
Delta-like 1 homolog (DLK1), a non-canonical Notch ligand, is highly expressed in various malignant tumors, especially in hepatocellular carcinoma (HCC). CBA-1205 is an afucosylated humanized antibody against DLK1 with enhanced antibody-dependent cellular cytotoxicity (ADCC). The binding characteristics of CBA-1205 were analyzed by enzyme-linked immunosorbent assay and fluorescence-activated cell sorting assay. The ADCC activity of CBA-1205 was assessed. The anti-tumor efficacy of CBA-1205 was evaluated in xenograft mouse models, and toxicity and toxicokinetic profiles of CBA-1205 were evaluated in cynomolgus monkeys. CBA-1205 selectively bound to DLK1 among the Notch ligands and only to monkey and human DLK1. The binding epitope was between epidermal growth factor-like domains 1 and 2 of DLK1, which are not involved in any known physiological functions. The ADCC activity of CBA-1205 was confirmed using human peripheral blood mononuclear cells as effector cells. CBA-1205 as a single agent and in combination with lenvatinib demonstrated long-lasting anti-tumor efficacy, including tumor regression, in two liver cancer xenograft models. The toxicity and toxicokinetic profiles of CBA-1205 in cynomolgus monkeys were favorable. These findings suggest that CBA-1205 has the potential to be a useful therapeutic option for drug treatment in HCC. A phase 1 study is ongoing in patients with advanced cancers (jRCT2080225288, NCT06636435). Full article
(This article belongs to the Special Issue New Wave of Cancer Therapeutics: Challenges and Opportunities)
19 pages, 9602 KiB  
Article
Temperature Upshifts in Mammalian Cell Culture: A Suitable Strategy for Biosimilar Monoclonal Antibodies?
by Lukas Marschall, Chitti Babu Gottimukkala, Biswajit Kayal, Veerabhadra Madurai Veeraraghavan, Samir Kumar Mandal, Suman Bandyopadhyay and Christoph Herwig
Bioengineering 2023, 10(10), 1149; https://doi.org/10.3390/bioengineering10101149 - 30 Sep 2023
Cited by 1 | Viewed by 2533
Abstract
Temperature downshifts are the gold standard when setting up control strategies for mammalian cell culture processes. These shifts are performed to prolong production phases and attain heightened levels of productivity. For the development of biosimilars, however, the bottleneck is in achieving a prespecified [...] Read more.
Temperature downshifts are the gold standard when setting up control strategies for mammalian cell culture processes. These shifts are performed to prolong production phases and attain heightened levels of productivity. For the development of biosimilars, however, the bottleneck is in achieving a prespecified product quality. In a late-stage development project, we investigated the impact of temperature shifts and other process parameters with the aim of optimizing the glycosylation profile of a monoclonal antibody (mAb). We applied a design of experiments approach on a 3 L scale. The optimal glycosylation profile was achieved when performing a temperature upshift from 35.8 °C to 37 °C. Total afucosylated glycan (TAF) decreased by 1.2%, and galactosylated glycan species (GAL) increased by up to 4.5%. The optimized control strategy was then successfully taken to the manufacturing scale (1000 L). By testing two sets of set points at the manufacturing scale, we demonstrated that the statistical models predicting TAF and GAL trained with small-scale data are representative of the manufacturing scale. We hope this study encourages researchers to widen the screening ranges in process development and investigate whether temperature upshifts are also beneficial for other mAbs. Full article
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Visual depiction of the screening range for the factors temperature before and after the shift (<b>A</b>). The different factor combinations (shown as blue circles) resulted in six temperature downshifts, two constant temperatures, and one temperature upshift (<b>B</b>). The ranges for both temperatures were defined in a risk assessment. The full DoE table is given in the <a href="#app1-bioengineering-10-01149" class="html-app">supplemental material</a>.</p> Full article ">Figure 2
<p>Quality profile and titer values at set-point conditions of the current process were calculated from 11 manufacturing runs. The error bars show the standard error of the responses. The optimization target is shown in green. The change in response to achieve the optimization target is shown as a green arrow. The mean values of (<b>A</b>) TAF, (<b>B</b>) GAL, and (<b>C</b>) titer at current set points on the manufacturing scale.</p> Full article ">Figure 3
<p>Univariate prediction plots for (<b>A</b>) TAF, (<b>B</b>) GAL, and (<b>C</b>) titer as a function of temperature before and after the shift. Each model parameter was varied within the screening range, whereas the other model parameters were kept at set-point conditions (grey dashed vertical line). Blocking effects were set to zero. The grey solid line shows the mean prediction at the respective parameter setting. The grey dashed lines represent the tolerance interval (95%/95%). The optimization target is shown as the green horizontal line. The DoE set-point runs are shown as blue dots.</p> Full article ">Figure 4
<p>Contour plots of (<b>A</b>) TAF, (<b>B</b>) GAL, and (<b>C</b>) titer as a function of temperature before and after the shift. All other parameters were kept at set-point conditions. The black dashed lines mark the point closest to the optimization target. For the titer, all values are higher than the required minimum to be achieved, and the black dashed lines show the highest titer. The temperature conditions described by the white lines are runs without temperature shift (i.e., constant temperature). Above the white line, a temperature downshift was performed; below the white line, an upshift was performed. The red dots mark the factor combinations tested in the experiments. The red areas demark the temperature combinations leading to high TAF, GAL, and titer values, whereas the blue areas demark temperature combinations with lower values.</p> Full article ">Figure 5
<p>Viability drop time was determined by interpolating the viability time series and extracting the time at which the signal dropped below 96%.</p> Full article ">Figure 6
<p>Contour plots of (<b>A</b>) viability drop time and (<b>B</b>) highest observed IVCD as a function of temperature before and after the shift. All other parameters were kept at set-point conditions. The grey dashed lines mark the optimum for the responses. The temperature conditions described by the black lines are conditions without temperature shift (i.e., constant temperature). Above the black line, a temperature downshift was performed; below the black line, an upshift was performed. The red dots mark the factor combinations tested in the experiments. The red areas demark the temperature combinations leading to high glycopattern and titer values, whereas the blue areas demark temperature combinations with lower values.</p> Full article ">Figure 7
<p>Change in (<b>A</b>) TAF, (<b>B</b>) GAL, and (<b>C</b>) titers before and after set-point optimization was assessed by calculating the difference in means of a group of runs with old set points and a group of runs with new set points. For manufacturing, 11 runs with the original set point and two runs with the temperature upshift process were available. For small scale, 15 runs with the original set point and 16 runs with the temperature upshift process were available. The error bars for the small scale and manufacturing scale represent the 95% confidence interval. For model prediction, the error bars are the root mean squared error divided by the square root of the number of DoE runs.</p> Full article ">Figure 8
<p>Contour plots of (<b>A</b>) specific lactate conversion rate after the temperature shift and (<b>B</b>) specific glucose uptake rate after the temperature shift as a function of temperature before and after the shift. All other parameters were kept at set-point (control) conditions. The temperature conditions described by the white lines are runs without temperature shift (i.e., constant temperature). Above the white line, a temperature downshift was performed; below the white line, an upshift was performed. The red dots mark the factor combinations tested in the experiments. The red areas demark temperature combinations, leading to high glycopattern and titer values, whereas the blue areas demark temperature combinations with lower values.</p> Full article ">Figure 9
<p>Comparison of (<b>A</b>) specific growth rate, (<b>B</b>) specific glucose uptake rate, and (<b>C</b>) specific lactate conversion rate before and after process optimization on the small scale. Fifteen runs with the original set point (control) and 15 runs with the temperature upshift process were available. The dashed lines represent the mean; the solid line in the middle of the box represents the median.</p> Full article ">
20 pages, 3558 KiB  
Article
Detection of Antibody-Dependent Cell-Mediated Cytotoxicity—Supporting Antibodies by NK-92-CD16A Cell Externalization of CD107a: Recognition of Antibody Afucosylation and Assay Optimization
by Judith Cruz Amaya, Bruce Walcheck, Julie Smith-Gagen, Vincent C. Lombardi and Dorothy Hudig
Antibodies 2023, 12(3), 44; https://doi.org/10.3390/antib12030044 - 27 Jun 2023
Viewed by 2690
Abstract
Antibody-dependent cell-mediated cytotoxicity (ADCC) by natural killer (NK) lymphocytes eliminates cells infected with viruses. Anti-viral ADCC requires three components: (1) antibody; (2) effector lymphocytes with the Fc-IgG receptor CD16A; and (3) viral proteins in infected cell membranes. Fc-afucosylated antibodies bind with greater affinity [...] Read more.
Antibody-dependent cell-mediated cytotoxicity (ADCC) by natural killer (NK) lymphocytes eliminates cells infected with viruses. Anti-viral ADCC requires three components: (1) antibody; (2) effector lymphocytes with the Fc-IgG receptor CD16A; and (3) viral proteins in infected cell membranes. Fc-afucosylated antibodies bind with greater affinity to CD16A than fucosylated antibodies; individuals’ variation in afucosylation contributes to differences in ADCC. Current assays for afucosylated antibodies involve expensive methods. We report an improved bioassay for antibodies that supports ADCC, which encompasses afucosylation. This assay utilizes the externalization of CD107a by NK-92-CD16A cells after antibody recognition. We used anti-CD20 monoclonal antibodies, GA101 WT or glycoengineered (GE), 10% or ~50% afucosylated, and CD20-positive Raji target cells. CD107a increased detection 7-fold compared to flow cytometry to detect Raji-bound antibodies. WT and GE antibody effective concentrations (EC50s) for CD107a externalization differed by 20-fold, with afucosylated GA101-GE more detectable. The EC50s for CD107a externalization vs. 51Cr cell death were similar for NK-92-CD16A and blood NK cells. Notably, the % CD107a-positive cells were negatively correlated with dead Raji cells and were nearly undetectable at high NK:Raji ratios required for cytotoxicity. This bioassay is very sensitive and adaptable to assess anti-viral antibodies but unsuitable as a surrogate assay to monitor cell death after ADCC. Full article
(This article belongs to the Special Issue Antibodies: 10th Anniversary)
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Figure 1

Figure 1
<p>Assay by NK-92-CD16A cell externalization of CD107a for antibodies that can support ADCC. The Raji cells were pre-incubated with GA101 anti-CD20 antibodies, then NK-92-CD16A cells were added at a 1:2 effector NK to Raji target ratio (E:T), and the cells incubated for 40 min at 37 °C. NK and Raji cells were also incubated without antibodies to measure CD107a externalization associated with NK activity. (<b>A</b>) Antibody detection by NK CD107a vs. by fluorescent secondary anti-IgG to Raji-bound antibodies. For the anti-CD20 antibody bound to Raji cells, the Rajis were stained with AF647-labeled donkey anti-human IgG. Both PE-anti-CD107a and AF647 anti-human IgG were detected by flow cytometry. (<b>A1</b>) Detection of target-cell bound antibody by NK CD107a or by fluorescent anti-human IgG. The EC<sub>50</sub>s for each method are indicated with arrows. EC<sub>50</sub> values are the effective concentrations of anti-CD20 that elicited 50% of maximum NK-92 antibody-specific (ADCC minus NK) CD107a externalization. The values for NK activity (without antibodies) are indicated by square symbols. (<b>A2</b>) The median fluorescent intensities (MFIs) of the CD107a-positive NK cells or AF647-anti-human IgG labeled Raji cells. The NK MFIs are for only the CD107a-positive cells. (<b>B</b>) CD107a externalization in response to antibodies with different Fc-fucosylation. The antibodies are from one mAb clone, GA101. The WT antibody is ~10% afucosylated; the GE antibody 50% afucosylated. (<b>B1</b>) EC<sub>50</sub>s for antibodies that differed in fucosylation. The EC<sub>50</sub>s associated with afucosylation were 20-fold apart in this experiment (<span class="html-italic">p</span> &lt; 0.05); similar differences were observed for three other experiments. (<b>B2</b>) The MFIs of the CD107a positive cells. The MFIs are for the CD107a positive in (<b>B1</b>). The CD107a per cell increased with afucosylation (<span class="html-italic">p</span> &lt; 0.001). (<b>C</b>) Antibody concentrations for CD107a externalization vs. death by ADCC. The CD107a values are the data of (<b>B1</b>). (<b>C1</b>,<b>C2</b>) Antibody EC<sub>50</sub>s for CD107a vs. for cell death, with GA101-WT or GA101-GE antibody. NK CD107a was determined at an E:T of 1:2. ADCC-mediated death was determined with <sup>51</sup>Cr-Raji cells at an E:T of 20:1. Both assays were stopped at 40 min. The 95% confidence limits for each EC<sub>50</sub> are color-coded and indicated at the top of the graphs. (<b>D</b>) Antibody detection by NK-92CD16A cell CD107a or by ADCC by peripheral blood NK cells. The donors’ genotypes encoding CD16A AA158, either lower affinity for Fc-IgG phenylalanine (F) or higher affinity valine (V), are indicated. The CD16A-positive blood NK cell to target (E:T) ratios were 4:1, 3:1, and 1:1 for donors 030, 035, and 038, respectively.</p> Full article ">Figure 2
<p>Conditions that affect CD107a externalization. (<b>A</b>) Time courses. The E:T was 1:2, and the antibody concentration was 1 µg/mL GA101 WT. (<b>A1</b>) Increases in the percentage of CD107a-positive NK-92-CD16A cells. The NK activity without antibodies is included to show its increase after antibody-dependent activity was complete. The inset illustrates that the antibody-dependent fraction (Total % − NK % positive) was unchanged after 40 min. (<b>A2</b>) Increases in CD107a expression. The MFIs are for the CD107a-positive cells from (<b>A1</b>). (<b>A3</b>) Side-by-side comparison of the % CD107a positive cells vs. CD107a. MFIs. The antibody-dependent data are from (<b>A1</b>,<b>A2</b>). (<b>B</b>) Effects of E:T ratios on CD107a externalization and death of Raji cells. The E:Ts varied from excess effectors to excess targets, as illustrated for two separate assays, one for NK CD107a externalization and another for ADCC by <sup>51</sup>Cr release. Both assays were for 40 min with 1 µg/mL GA101 WT antibody. (<b>B1</b>) % CD107a-pos cells vs. death by ADCC. The percentage of cells with external CD107a paradoxically decreased with increased E:T ratios. Note: each datum for the % CD107a positive cells represents the % of a varying number of effector cells that increased two-fold for each E:T. The color-matched asterisks indicate <span class="html-italic">p</span> &lt; 0.01compared to the E:T 1:8 values. (<b>B2</b>) Frequencies of CD107a-positive NK cell numbers vs. numbers of target cells killed by ADCC. The numbers (instead of percentages) of CD107a-positive cells at each E:T of (<b>B1</b>) were calculated and then re-expressed as percentages of the initial Raji cells, indicated in orange. The % Raji cell death is also from (<b>B1</b>). The CD107a-positive NK cells far exceeded the dead Raji cells (as indicated by the two ordinate scales). At the E:T of 8:1, the ratio of CD107a-pos NK cells to dead Raji cells was 13:1.</p> Full article ">Figure 3
<p>Variables that affect biosafety in future applications. Antibodies were heated to simulate inactivation of viruses. Formaldehyde treatment is routinely used to inactivate viruses. These assays were at an E:T of 1:2 for 40 min. (<b>A</b>) Heated antisera. GA101 WT antibody was heated with serum and then diluted with control heated serum to 1 μg/mL antibody in 10% heated human serum. The variables are indicated below each bar. (<b>B</b>) Formaldehyde fixation. Treatment was either (1) after addition of antibodies to Raji cells or (2) after the NK-92-CD16A-cells reacted with cell-bound antibodies. (<b>B</b>) Reactivity of the NK-92-CD16A cells to formaldehyde-treated GA101 IgG. Raji cells were treated with 1 or 0.01 µg/mL GA101 WT antibody, then 1% formaldehyde, washed, and used to stimulate NK-92-CD16A cells. The E:T was 1:2, and the assay was for 40 min. (<b>C</b>) Reactivity of PE-mAb anti-CD107a with formaldehyde-treated CD107a. Cells were treated with formaldehyde and washed prior to labeling.</p> Full article ">Figure A1
<p>Flow cytometric gating to detect CD107a externalization. (<b>A</b>–<b>E</b>) sequential gating for CD107a-positive NK-92-CD16A cells incubated with antibody and Raji cells. The assay conditions were an NK to Raji E:T of 1:2, with or without 10 ng/mL GA101-GE antibody, and 40 min of incubation at 37 °C. (<b>A</b>) Starting NK and Raji cells; (<b>B</b>) gating for single cells; (<b>C</b>) gating for GFP-bright NK-92-CD16A cells; (<b>D</b>) gating for CD56 bright GFP positive double-positive cells; (<b>E</b>) gating for the % CD107a-positive cells. (<b>F</b>) NK cells with Rajis without mAb. The data are from experiment JCA044, illustrated in <a href="#antibodies-12-00044-f001" class="html-fig">Figure 1</a>.</p> Full article ">Figure A2
<p>CD107a externalization after six assay conditions. The results are from JCA044 in which cells were cultured for 40 min, 1:2 NK to Raji target cells, without or with 0.04 or 10 ng/mL of GA-101 GE antibody or with phorbol myristic acid (PMA) and ionophore. (<b>A</b>) Unlabeled NK cells used to set gating for CD107a-positive cells. (<b>B</b>–<b>F</b>) Labeled cells. (<b>B</b>) NK-92-CD16A cells without Raji targets (repeat of <a href="#app1-antibodies-12-00044" class="html-app">Appendix A</a> <a href="#antibodies-12-00044-f0A1" class="html-fig">Figure A1</a>F). (<b>C</b>) cells with PMA &amp; calcium ionophore as a positive control. (<b>D</b>) NK activity towards Raji cells in the absence of anti-CD20 antibody. (<b>E</b>) NK plus Rajis with 0.04 ng/mL GA101 GE antibody. (<b>F</b>) NK plus Rajis with 10 ng/mL GA101-GE (repeat of <a href="#app1-antibodies-12-00044" class="html-app">Appendix A</a> <a href="#antibodies-12-00044-f0A1" class="html-fig">Figure A1</a>E).</p> Full article ">Figure A3
<p>Comparison of CD107a-positive cells for anti-CD20 dependent and independent at increasing E:Ts. Assays without antibody (NK activity) and with antibody (supporting ADCC) were 40 min with 1 µg/mL GA101 WT antibody. * <span class="html-italic">p</span> = or &lt;0.01 for <span class="html-italic">t</span>-test differences from the 1:8 E:T. (<b>A</b>) % CD107a positive cells. (<b>B</b>) CD107a MFIs. The MFIs are for the CD107a-positive cells of (<b>A</b>).</p> Full article ">Figure A4
<p>Model to explain why at the high E:Ts that support death, CD107a is hard to detect. CD107a externalization and 51Cr release were for 40 min with 1 µg/mL GA101 WT antibody. (<b>A</b>) Histograms of CD107a-positive cells E:T:Ts of 1:4 and 4:1 from <a href="#antibodies-12-00044-f002" class="html-fig">Figure 2</a>(B1). Note how many more CD107a-positive cells there are at the lower E:T of 1:4 and how much more CD107a the cells externalized. (<b>B</b>) Bar graph of ADCC at 1:4 and 4:1, from the data of <a href="#antibodies-12-00044-f002" class="html-fig">Figure 2</a>(B1) at 40 min and 4 h. (<b>C</b>) Model of additive attack to reconcile the low CD107a of the effector cells associated with killing. At low E:T, one effector releases multiple granules, but only one per target, which is insufficient to kill the target. At high E:T, each effector releases one granule and is barely CD107a-positive; however, the target received multiple hits and died. The black Y indicates the humanized anti-CD20 mAb that directed ADCC; the orange Y indicates the mouse PE fluor (*)-tagged mAb anti-CD107a.</p> Full article ">
8 pages, 446 KiB  
Brief Report
IgG1-Dominant Antibody Response Induced by Recombinant Trimeric SARS-CoV-2 Spike Protein with PIKA Adjuvant
by Jingxia Wang, Xinjia Mai, Yu He, Chenxi Zhu and Dapeng Zhou
Vaccines 2023, 11(4), 827; https://doi.org/10.3390/vaccines11040827 - 11 Apr 2023
Cited by 2 | Viewed by 2412
Abstract
Recombinant trimeric SARS-CoV-2 Spike protein with PIKA (polyI:C) adjuvant induces potent and durable neutralizing antibodies that protect against multiple SARS-CoV-2 variants. The immunoglobulin subclasses of viral-specific antibodies remain unknown, as do their glycosylation status on Fc regions. In this study, we analyzed immunoglobulins [...] Read more.
Recombinant trimeric SARS-CoV-2 Spike protein with PIKA (polyI:C) adjuvant induces potent and durable neutralizing antibodies that protect against multiple SARS-CoV-2 variants. The immunoglobulin subclasses of viral-specific antibodies remain unknown, as do their glycosylation status on Fc regions. In this study, we analyzed immunoglobulins adsorbed by plate-bound recombinant trimeric SARS-CoV-2 Spike protein from serum of Cynomolgus monkey immunized by recombinant trimeric SARS-CoV-2 Spike protein with PIKA (polyI:C) adjuvant. The results showed that IgG1 was the dominant IgG subclass as revealed by ion mobility mass spectrometry. The average percentage of Spike protein-specific IgG1 increased to 88.3% as compared to pre-immunization. Core fucosylation for Fc glycopeptide of Spike protein-specific IgG1 was found to be higher than 98%. These results indicate that a unique Th1-biased, IgG1-dominant antibody response was responsible for the effectiveness of PIKA (polyI:C) adjuvant. Vaccine-induced core-fucosylation of IgG1 Fc region may reduce incidence of severe COVID-19 disease associated with overstimulation of FCGR3A by afucosylated IgG1. Full article
(This article belongs to the Special Issue Antibody Response of Vaccines to SARS-CoV-2)
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Figure 1

Figure 1
<p>Percentage of IgG1 in Spike protein-specific immunoglobulins. Spike-specific immunoglobulins (Spike) were adsorbed by plate-bound recombinant trimeric Spike proteins and analyzed by LC-MS and quantified by XIC AUC. Protein A/G-adsorbed total serum immunoglobulins (Total) were also analyzed. Note that the IgG3 and IgG4 subclasses of rhesus monkey were summarized together due to identical characteristic peptide fragments after trypsin digestion. “*” means significant difference (<span class="html-italic">p</span> &lt; 0.05); “ns” means no significant difference.</p> Full article ">
12 pages, 1076 KiB  
Brief Report
The Effect of Belantamab Mafodotin on Primary Myeloma–Stroma Co-Cultures: Asymmetrical Mitochondrial Transfer between Myeloma Cells and Autologous Bone Marrow Stromal Cells
by Zsolt Matula, Ferenc Uher, István Vályi-Nagy and Gábor Mikala
Int. J. Mol. Sci. 2023, 24(6), 5303; https://doi.org/10.3390/ijms24065303 - 10 Mar 2023
Cited by 4 | Viewed by 2422
Abstract
Belantamab mafodotin (belamaf) is an afucosylated monoclonal antibody conjugated to the microtubule disrupter monomethyl auristatin-F (MMAF) that targets B cell maturation antigen (BCMA) on the surface of malignant plasma cells. Belamaf can eliminate myeloma cells (MMs) through several mechanisms. On the one hand, [...] Read more.
Belantamab mafodotin (belamaf) is an afucosylated monoclonal antibody conjugated to the microtubule disrupter monomethyl auristatin-F (MMAF) that targets B cell maturation antigen (BCMA) on the surface of malignant plasma cells. Belamaf can eliminate myeloma cells (MMs) through several mechanisms. On the one hand, in addition to inhibiting BCMA-receptor signaling and cell survival, intracellularly released MMAF disrupts tubulin polymerization and causes cell cycle arrest. On the other hand, belamaf induces effector cell-mediated tumor cell lysis via antibody-dependent cellular cytotoxicity and antibody-dependent cellular phagocytosis. In our in vitro co-culture model, the consequences of the first mentioned mechanism can be investigated: belamaf binds to BCMA, reduces the proliferation and survival of MMs, and then enters the lysosomes of malignant cells, where MMAF is released. The MMAF payload causes a cell cycle arrest at the DNA damage checkpoint between the G2 and M phases, resulting in caspase-3-dependent apoptosis. Here, we show that primary MMs isolated from different patients can vary widely in terms of BCMA expression level, and inadequate expression is associated with extremely high resistance to belamaf according to our cytotoxicity assay. We also reveal that primary MMs respond to increasing concentrations of belamaf by enhancing the incorporation of mitochondria from autologous bone marrow stromal cells (BM-MSCs), and as a consequence, MMs become more resistant to belamaf in this way, which is similar to other medications we have analyzed previously in this regard, such as proteasome inhibitor carfilzomib or the BCL-2 inhibitor venetoclax. The remarkable resistance against belamaf observed in the case of certain primary myeloma cell cultures is a cause for concern and points towards the use of combination therapies to overcome the risk of antigen escape. Full article
(This article belongs to the Special Issue Monoclonal Antibodies & Immunotherapy to Treat Cancer: Current Knowledge, Emerging Targets and Future Perspectives)
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Figure 1

Figure 1
<p>BCMA positivity of primary myeloma cells, the cytotoxic effect of belantamab mafodotin on BM-MSC–myeloma cell cultures, and the consequence of in vitro exposing the primary myeloma cell cultures to belantamab mafodotin regarding the bidirectional mitochondrial transfer between the malignant plasma cells and the bone marrow stromal cells. (<b>A</b>) CD38-positive primary myeloma cells from the BM-MSC–MM co-cultures were labeled with PE-conjugated anti-BCMA antibody or the corresponding isotype control and analyzed by flow cytometry; (<b>B</b>) the cytotoxic effect of increasing belantamab mafodotin concentrations (0.1–1000 µg/mL) was determined in myeloma (red line) and BM-MSC (green line) monocultures or the case of myeloma cells in BM-MSC–MM co-cultures (orange line); (<b>C</b>) the BCMA positivity of the three selected myeloma cell cultures for mitochondrial transfer assay with a high, medium, and low BCMA expression. Each column shows the average of three independent measurements; (<b>D</b>) the effect of belantamab mafodotin on mitochondrial transfer from BM-MSCs to MMs after 48 h of co-culture. BM-MSCs were labeled with Mitotracker Red FM and then cultured together with MMs in the presence or absence of belamaf and colcemid. BM-MSC-derived mitochondria<sup>+</sup> MMs were analyzed by flow cytometry within the CD38<sup>+</sup> myeloma cell population; (<b>E</b>) the effect of belantamab mafodotin on mitochondrial transfer from MMs to BM-MSCs after 48 h of co-culture. MMs were labeled with Mitotracker Red FM and then cultured together with BM-MSCs in the presence or absence of belamaf and colcemid. MM-derived mitochondria<sup>+</sup> BM-MSCs were analyzed by flow cytometry within the CD146<sup>+</sup> stromal cell population.</p> Full article ">
16 pages, 2322 KiB  
Article
Identification of Cell Culture Factors Influencing Afucosylation Levels in Monoclonal Antibodies by Partial Least-Squares Regression and Variable Importance Metrics
by Adam J. Rish, Zhuangrong Huang, Khandaker Siddiquee, Jianlin Xu, Carl A. Anderson, Michael C. Borys and Anurag Khetan
Processes 2023, 11(1), 223; https://doi.org/10.3390/pr11010223 - 10 Jan 2023
Cited by 5 | Viewed by 3592
Abstract
Retrospective analysis of historic data for cell culture processes is a powerful tool to develop further process understanding. In particular, deploying retrospective analyses can identify important cell culture process parameters for controlling critical quality attributes, e.g., afucosylation, for the production of monoclonal antibodies [...] Read more.
Retrospective analysis of historic data for cell culture processes is a powerful tool to develop further process understanding. In particular, deploying retrospective analyses can identify important cell culture process parameters for controlling critical quality attributes, e.g., afucosylation, for the production of monoclonal antibodies (mAbs). However, a challenge of analyzing large cell culture data is the high correlation between regressors (particularly media composition), which makes traditional analyses, such as analysis of variance and multivariate linear regression, inappropriate. Instead, partial least-squares regression (PLSR) models, in combination with machine learning techniques such as variable importance metrics, are an orthogonal or alternative approach to identifying important regressors and overcoming the challenge of a highly covariant data structure. A specific workflow for the retrospective analysis of cell culture data is proposed that covers data curation, PLS regression, model analysis, and further steps. In this study, the proposed workflow was applied to data from four mAb products in an industrial cell culture process to identify significant process parameters that influence the afucosylation levels. The PLSR workflow successfully identified several significant parameters, such as temperature and media composition, to enhance process understanding of the relationship between cell culture processes and afucosylation levels. Full article
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<p>Summary of the proposed PLSR workflow for identifying the influential independent regressors.</p> Full article ">Figure 2
<p>Correlation map between the cell culture parameters and afucosylation levels for mAb-δ.</p> Full article ">Figure 3
<p>Plot for selection of optimal number of latent variables (LV) for PLSR model predicting mAb-δ complex afucosylation. The arrow indicates the point of stabilization for the RMSEC and RMSECV that was used to select the final number of LVs.</p> Full article ">Figure 4
<p>(<b>A</b>) The plot of the scores on LV1 versus the scores on LV2 for the mAb-δ PLSR model. The color represents the complex afucosylation level. (<b>B</b>) The Q-residual vs. Reduced Hotelling’s T<sup>2</sup> diagnostic plots for mAb-δ PLSR model. The dashed line represents the significance threshold for the reduced Hotelling’s T<sup>2</sup>, with unusual samples circled in red.</p> Full article ">Figure 5
<p>Plots showing the values of the variable importance metrics calculated from the PLSR model predicting the complex afucosylation level of mAb-δ. The red dashed line indicates the significance threshold of the metric. Each different parameter is represented by a unique colored bar.</p> Full article ">
23 pages, 4891 KiB  
Article
Structural and Functional Analysis of CEX Fractions Collected from a Novel Avastin® Biosimilar Candidate and Its Innovator: A Comparative Study
by Busra Gurel, Melike Berksoz, Eda Capkin, Ayhan Parlar, Meltem Corbacioglu Pala, Aylin Ozkan, Yılmaz Capan, Duygu Emine Daglikoca and Meral Yuce
Pharmaceutics 2022, 14(8), 1571; https://doi.org/10.3390/pharmaceutics14081571 - 28 Jul 2022
Cited by 5 | Viewed by 3011
Abstract
Avastin® is a humanized recombinant monoclonal antibody used to treat cancer by targeting VEGF-A to inhibit angiogenesis. SIMAB054, an Avastin® biosimilar candidate developed in this study, showed a different charge variant profile than its innovator. Thus, it is fractionated into acidic, [...] Read more.
Avastin® is a humanized recombinant monoclonal antibody used to treat cancer by targeting VEGF-A to inhibit angiogenesis. SIMAB054, an Avastin® biosimilar candidate developed in this study, showed a different charge variant profile than its innovator. Thus, it is fractionated into acidic, main, and basic isoforms and collected physically by Cation Exchange Chromatography (CEX) for a comprehensive structural and functional analysis. The innovator product, fractionated into the same species and collected by the same method, is used as a reference for comparative analysis. Ultra-Performance Liquid Chromatography (UPLC) ESI-QToF was used to analyze the modifications leading to charge heterogeneities at intact protein and peptide levels. The C-terminal lysine clipping and glycosylation profiles of the samples were monitored by intact mAb analysis. The post-translational modifications, including oxidation, deamidation, and N-terminal pyroglutamic acid formation, were determined by peptide mapping analysis in the selected signal peptides. The relative binding affinities of the fractionated charge isoforms against the antigen, VEGF-A, and the neonatal receptor, FcRn, were revealed by Surface Plasmon Resonance (SPR) studies. The results show that all CEX fractions from the innovator product and the SIMAB054 shared the same structural variants, albeit in different ratios. Common glycoforms and post-translational modifications were the same, but at different percentages for some samples. The dissimilarities were mostly originating from the presence of extra C-term Lysin residues, which are prone to enzymatic degradation in the body, and thus they were previously assessed as clinically irrelevant. Another critical finding was the presence of different glyco proteoforms in different charge species, such as increased galactosylation in the acidic and afucosylation in the basic species. SPR characterization of the isolated charge variants further confirmed that basic species found in the CEX analyses of the biosimilar candidate were also present in the innovator product, although at lower amounts. The charge variants’ in vitro antigen- and neonatal receptor-binding activities varied amongst the samples, which could be further investigated in vivo with a larger sample set to reveal the impact on the pharmacokinetics of drug candidates. Minor structural differences may explain antigen-binding differences in the isolated charge variants, which is a key parameter in a comparability exercise. Consequently, such a biosimilar candidate may not comply with high regulatory standards unless the binding differences observed are justified and demonstrated not to have any clinical impact. Full article
(This article belongs to the Section Biologics and Biosimilars)
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<p>CEX results of AVT and SIMAB054. Overlay of CEX results of AVT and SIMAB054 and a comparative table of acidic, basic, and main charge variant percentages.</p> Full article ">Figure 2
<p>Each fraction was analyzed by CEX to confirm the presence of targeted charge variants. (<b>A</b>) CEX fractions collected from the innovator, AVT. (<b>B</b>) CEX fractions collected from SIMAB054.</p> Full article ">Figure 3
<p>SEC-HPLC analysis results of each fraction. (<b>A</b>) Overlay chromatograms of AVT08 charge variant fractions. (<b>B</b>) Overlay chromatograms of SIMAB054 charge variant fractions.</p> Full article ">Figure 4
<p>Intact protein analysis of charge variant fractions obtained from AVT and SIMAB054. (<b>A</b>) The list of the molecular mass of the dominant mass peak in each fraction. Each fraction was injected three times, and the mass ranges represent the minimum–maximum observed mass values. A, M, and B represent acidic, main, and basic fractions. (<b>B</b>) Illustration of glycoforms assigned for each molecular mass.</p> Full article ">Figure 5
<p>The VEGF-binding characteristics of the fractionated charge variants using the SPR using the Langmuir 1:1 binding model. The samples fractionated by the CEX method were obtained from the innovator (AVT) and the biosimilar candidate (SIMAB054) under the same operational conditions. A, M, and B, respectively, represent acidic, main, and basic fractions. The K<sub>D</sub> data were presented as the mean value obtained from at least five measurements. The inset (top-left) is a representative illustration of the prepared SPR chip surface. The inset (top-right) shows the proposed mechanism of action for Avastin<sup>®</sup>, adapted from reference [<a href="#B91-pharmaceutics-14-01571" class="html-bibr">91</a>].</p> Full article ">Figure 6
<p>The VEGF-binding characteristics of the fractionated charge variants using the SPR using the Langmuir 1:1 binding model. The samples fractionated by the CEX method were obtained from the innovator (AVT) and the biosimilar candidate (SIMAB054) under the same operational conditions. A, M, and B, respectively, represent acidic, main, and basic fractions. The means of K<sub>D</sub> values were obtained from at least five measurements, and an equivalence test was used to compare each charge variant of SIMAB054 with those of AVT.</p> Full article ">Figure 7
<p>The FcRn-binding characteristics of the fractionated charge variants were revealed by the SPR, using steady-state (<b>A</b>) and two-state binding models (<b>B</b>). The samples fractionated by the CEX method were obtained from the innovator (AVT08) and the biosimilar candidate (SIMAB054) under the same operational conditions. The A, M, and B represent acidic, main, and basic fractions. A lower K<sub>D</sub> value represents a better binding. The K<sub>D</sub> data were given as the mean value obtained from at least five measurements. The inset (top-left) is a representative illustration of the prepared SPR chip surface. The inset (top-right) shows the proposed mechanism of action for FcRn, adapted from reference [<a href="#B108-pharmaceutics-14-01571" class="html-bibr">108</a>].</p> Full article ">
18 pages, 3312 KiB  
Article
Afucosylated IgG Targets FcγRIV for Enhanced Tumor Therapy in Mice
by Rens Braster, Marijn Bögels, Hreinn Benonisson, Manfred Wuhrer, Rosina Plomp, Arthur E. H. Bentlage, Rianne Korthouwer, Remco Visser, J. Sjef Verbeek, Marjolein van Egmond and Gestur Vidarsson
Cancers 2021, 13(10), 2372; https://doi.org/10.3390/cancers13102372 - 14 May 2021
Cited by 7 | Viewed by 4054
Abstract
Promising strategies for maximizing IgG effector functions rely on the introduction of natural and non-immunogenic modifications. The Fc domain of IgG antibodies contains an N-linked oligosaccharide at position 297. Human IgG antibodies lacking the core fucose in this glycan have enhanced binding to [...] Read more.
Promising strategies for maximizing IgG effector functions rely on the introduction of natural and non-immunogenic modifications. The Fc domain of IgG antibodies contains an N-linked oligosaccharide at position 297. Human IgG antibodies lacking the core fucose in this glycan have enhanced binding to human (FcγR) IIIa/b, resulting in enhanced antibody dependent cell cytotoxicity and phagocytosis through these receptors. However, it is not yet clear if glycan-enhancing modifications of human IgG translate into more effective treatment in mouse models. We generated humanized hIgG1-TA99 antibodies with and without core-fucose. C57Bl/6 mice that were injected intraperitoneally with B16F10-gp75 mouse melanoma developed significantly less metastasis outgrowth after treatment with afucosylated hIgG1-TA99 compared to mice treated with wildtype hhIgG1-TA99. Afucosylated human IgG1 showed stronger interaction with the murine FcγRIV, the mouse orthologue of human FcγRIIIa, indicating that this glycan change is functionally conserved between the species. In agreement with this, no significant differences were observed in tumor outgrowth in FcγRIV-/- mice treated with human hIgG1-TA99 with or without the core fucose. These results confirm the potential of using afucosylated therapeutic IgG to increase their efficacy. Moreover, we show that afucosylated human IgG1 antibodies act across species, supporting that mouse models can be suitable to test afucosylated antibodies. Full article
(This article belongs to the Special Issue Pathophysiology and Treatment of Peritoneal Metastasis)
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<p>Afucosylated antibodies have minimal expression of fucose on glycans. LC-MS spectra of trypsin-generated human IgG1 glycopeptides. Glycopeptide species were observed in both triple-charged form (below <span class="html-italic">m</span>/<span class="html-italic">z</span> 1000) and double charged form (above <span class="html-italic">m</span>/<span class="html-italic">z</span> 1000). Top humanized fucosylated hIgG1-TA99 and bottom, afucosylated hIgG1-TA99. Green circle = mannose; yellow circle = galactose; blue square = <span class="html-italic">N</span>-acetylglucosamine; red triangle = fucose; * = unidentified peptide.</p> Full article ">Figure 2
<p>Lack of core fucose in the IgG1 Fc domain enhances antibody-mediated tumor killing by natural killer cells and human macrophages. (<b>A</b>–<b>E</b>) ADCC or ADCP (<b>F</b>) with B16F10-gp75 cells as targets opsonized with anti-GP75 TA99 hIgG1 (black bars) or control (grey bars, anti-2,4,6-trinitrophenol, TNP) antibodies, with or without core fucose (+F solid and -F striped bars resp.) by: (<b>A</b>) PBMC (<b>D</b>) PBL, (<b>C</b>) CD14<sup>+</sup> monocytes, (<b>D</b>) NK cells or (<b>E</b>) PMN cells (predominantly neutrophils). % Remaining tumor cells relative to the no antibody (white bars) co-culture were used as readout (<b>F</b>) ADCP by M-CSF cultured CD14<sup>+</sup> monocyte derived macrophages. Percentage of tumor cell<sup>+</sup>—macrophages in the co-culture. (<b>G</b>–<b>I</b>) FcγRIII (CD16) (<b>H</b>) FcγRII (CD32) (<b>I</b>) FcγRI (CD64) expression on M-CSF cultured CD14<sup>+</sup> monocyte-derived macrophages was determined by flow cytometry. Plots and graphs represent data obtained in 3 to 5 independent experiments and healthy donors. All graphs represent mean ±SEM. * <span class="html-italic">p</span> ≤ 0.05; ** <span class="html-italic">p</span> ≤ 0.01; *** <span class="html-italic">p</span> ≤ 0.001; **** <span class="html-italic">p</span> &lt; 0.0001, ns = Not Significant <span class="html-italic">p</span> &gt; 0.05.</p> Full article ">Figure 3
<p>Treatment with afucosylated jIgG1-TA99 decreased tumor outgrowth in vivo. (<b>A</b>) C57Bl/6 mice were injected intraperitoneally with 50.000 B16F10-gp75 and 50 μg nonspecific (○/●) or tumor specific hIgG1 TA199 antibodies) that were either fucosylated (□) or hypo-fucosylated (■). Fourteen days post injection mice were sacrificed and metastasis outgrowth in the peritoneum was scored. N = 6 for αTNP +Fucose, <span class="html-italic">n</span> = 13 for the other groups. (<b>B</b>) Populations identified in a peritoneal lavage. 5 populations are gated in a F4/80/GR1 plot, (1) F4/80<sup>+</sup>GR1<sup>−</sup>, (2) F4/80<sup>int</sup>GR1<sup>int</sup>, (3) F4/80<sup>−</sup>GR1<sup>+</sup>, (4) F4/80<sup>int</sup>GR1<sup>+</sup>, (5) F4/80<sup>+</sup>GR1<sup>+</sup>. The negative population was used to gate lymphocytes, CD3<sup>−</sup> cells and 6D) NK cells respectively. (<b>C</b>) Composition of the dominant myeloid and NK—effector populations in a peritoneal lavage of mice 24 h after intraperitoneal injection with PBS, B16F10-gp75 with or without antibodies. <span class="html-italic">N</span> ≥ 4. ** <span class="html-italic">p</span> ≤ 0.01, **** <span class="html-italic">p</span> ≤ 0.0001.</p> Full article ">Figure 4
<p>Affinity plots for fucosylated human IgG1 to mouse FcγR. Binding affinity was determined by Surface plasmon resonance using C-terminally site-specifically biotinylated FcγR coupled to streptavidin sensor arrays. hIgG1-TA99 flowed over the chip at concentrations ranging from 3.9 nM until to 337.5 nM at 1.5 dilutions for the different mouse FcγR at different densities as indicated. (<b>A</b>) Sensorgrams and (<b>B</b>) derived affinity plots. The affinities found at different receptor densities in (<b>B</b>) are indicated by vertical dotted lines, and used to calculated and interpolated of KD for Rmax of 500 (<a href="#cancers-13-02372-f005" class="html-fig">Figure 5</a>).</p> Full article ">Figure 5
<p>Affinity plots for afucosylated human IgG1 to mouse FcγR: Lack of fucose in the Fc domain results in increased binding to mouse FcγRIV. Experiment was carried out as described for <a href="#cancers-13-02372-f004" class="html-fig">Figure 4</a>, with (<b>A</b>) Sensorgrams and (<b>B</b>) derived affinity plots for 4 different ligand (FcγR) concentrations as indicated. (<b>C</b>) The derived KD from each affinity plots for fucosylated hIgG1 (<a href="#cancers-13-02372-f004" class="html-fig">Figure 4</a>B) and afucosylated IgG1 from (<b>B</b>) and Rmax of each ligand concentration plotted for interpolation of KD for both fucosylated and afucosylated IgG1 to a constant Rmax of 500 (vertical lines, tabulated in <a href="#cancers-13-02372-t001" class="html-table">Table 1</a>).</p> Full article ">Figure 6
<p>FcγRIV is essential in antibody therapy in the peritoneal cavity. (<b>A</b>,<b>B</b>) Fcγ receptor expression by effector cells in the peritoneal cavity (<b>A</b>) and in blood (<b>B</b>). Isotype control is shown in grey, FcγR-specific antibodies with a solid line. (<b>C</b>) C57Bl/6 mice lacking FcγRIV were injected intraperitoneally with 50,000 B16F10-gp75 and 50 μg nonspecific hypo-fucosylated hIgG1-anti-TNP (●) or humanized IgG1-TA99as either fucosylated (□) or hypo-fucosylated (■) variant. 14 Days post injection mice were sacrificed and metastasis outgrowth in the peritoneum was scored. <span class="html-italic">N</span> = 11 per group.</p> Full article ">
15 pages, 1663 KiB  
Article
Enhancing CDC and ADCC of CD19 Antibodies by Combining Fc Protein-Engineering with Fc Glyco-Engineering
by Sophia Roßkopf, Klara Marie Eichholz, Dorothee Winterberg, Katarina Julia Diemer, Sebastian Lutz, Ira Alexandra Münnich, Katja Klausz, Thies Rösner, Thomas Valerius, Denis Martin Schewe, Andreas Humpe, Martin Gramatzki, Matthias Peipp and Christian Kellner
Antibodies 2020, 9(4), 63; https://doi.org/10.3390/antib9040063 - 17 Nov 2020
Cited by 22 | Viewed by 6971
Abstract
Background: Native cluster of differentiation (CD) 19 targeting antibodies are poorly effective in triggering antibody-dependent cell-mediated cytotoxicity (ADCC) and complement-dependent cytotoxicity (CDC), which are crucial effector functions of therapeutic antibodies in cancer immunotherapy. Both functions can be enhanced by engineering the antibody’s Fc [...] Read more.
Background: Native cluster of differentiation (CD) 19 targeting antibodies are poorly effective in triggering antibody-dependent cell-mediated cytotoxicity (ADCC) and complement-dependent cytotoxicity (CDC), which are crucial effector functions of therapeutic antibodies in cancer immunotherapy. Both functions can be enhanced by engineering the antibody’s Fc region by altering the amino acid sequence (Fc protein-engineering) or the Fc-linked glycan (Fc glyco-engineering). We hypothesized that combining Fc glyco-engineering with Fc protein-engineering will rescue ADCC and CDC in CD19 antibodies. Results: Four versions of a CD19 antibody based on tafasitamab’s V-regions were generated: a native IgG1, an Fc protein-engineered version with amino acid exchanges S267E/H268F/S324T/G236A/I332E (EFTAE modification) to enhance CDC, and afucosylated, Fc glyco-engineered versions of both to promote ADCC. Irrespective of fucosylation, antibodies carrying the EFTAE modification had enhanced C1q binding and were superior in inducing CDC. In contrast, afucosylated versions exerted an enhanced affinity to Fcγ receptor IIIA and had increased ADCC activity. Of note, the double-engineered antibody harboring the EFTAE modification and lacking fucose triggered both CDC and ADCC more efficiently. Conclusions: Fc glyco-engineering and protein-engineering could be combined to enhance ADCC and CDC in CD19 antibodies and may allow the generation of antibodies with higher therapeutic efficacy by promoting two key functions simultaneously. Full article
(This article belongs to the Special Issue The Role of Complement in Cancer Immunotherapy)
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<p>Generation of Fc engineered CD19 antibodies. (<b>A</b>) Structural model of an IgG molecule and illustration of amino acid exchanges S267E/H268F/S324T/G236A/I332E (EFTAE modification; in yellow) in the antibody CH2 domain, and the critical fucose residue in red. The light and heavy chains are depicted in light grey and dark grey, respectively. The N297-associated carbohydrate is colored in blue. The model is based on the pdb-file provided by Dr. Mike Clark [<a href="#B42-antibodies-09-00063" class="html-bibr">42</a>] and was edited employing Discovery Studio Visualizer software (Biovia, San Diego, CA, USA). (<b>B</b>) Expression constructs for CD19 heavy chains with native (wt) or with EFTAE modified Fc domain sequences were generated and transfected into CHO-K1 and Lec13 cells for production of fucosylated antibodies (CD19-wt-CHO and CD19-EFTAE-CHO) as well as their afucosylated counterparts (CD19-wt-Lec13 and CD19-EFTAE-Lec13), respectively. (<b>C</b>) After purification by affinity chromatography antibodies were analyzed by SDS-PAGE and Coomassie blue staining under non-reducing (left gel) or reducing (right gel) conditions. Amounts of 1–2 µg protein were loaded on 6% and 12% polyacrylamide gels, respectively (Lanes: (1) CD19-EFTAE-Lec13, (2) CD19-EFTAE-CHO, (3) CD19-wt-Lec13, (4) CD19-wt-CHO). Results from one representative experiment are shown (<span class="html-italic">n</span> = 3). HC, heavy chain; LC, light chain. (<b>D</b>) The fucosylation status of the different antibody versions was determined by lectin blot experiments employing biotinylated A. aurantia lectin and HRP-conjugated neutrAvidin protein (upper panel), indicating that fucose was almost absent in antibodies produced in Lec13 cells. As a control, antibody heavy chains (HC) were detected in Western Transfer experiments with an HRP-coupled anti-human IgG Fc antibody (lower panel). Results from one representative experiment are shown (<span class="html-italic">n</span> = 3). Lanes: (1) CD19-EFTAE-Lec13 (2) CD19-EFTAE-CHO (3) CD19-wt-Lec13 (4) CD19-wt-CHO).</p> Full article ">Figure 2
<p>CD19 binding analysis. (<b>A</b>) CD19-positive Ramos cells were incubated with antibodies as indicated (concentration: 50 µg/mL; grey peaks) or in PBA buffer alone (white peaks), stained with FITC-coupled anti-human IgG Fc F(ab’)2 and then analyzed by flow cytometry. As a control, trastuzumab was added (IgG1). (<b>B</b>) CD19-wt-CHO, CD19-EFTAE-CHO, CD19-wt-Lec13 and CD19-EFTAE-Lec13 (concentration: 50 µg/mL) bound to CD19-expressing Ramos cells but did not react with CD19-negative SK-BR-3 cells. Bars indicate mean values ± SEM (<span class="html-italic">n</span> = 3) of mean fluorescence intensity (MFI). PE-labeled anti-human IgG Fc F(ab’)2 fragments were used as secondary antibodies. Trastuzumab was employed as a control antibody and bound to HER2-positive SK-BR-3 cells. (<b>C</b>) Binding of antibody versions to CHO-K1-CD19 cells was analyzed at varying concentrations employing FITC-coupled anti-human IgG Fc F(ab’)2 fragments as detection reagents and MFI values were determined by flow cytometry. Mean values ± SEM are shown (<span class="html-italic">n</span> = 4).</p> Full article ">Figure 3
<p>FcγRIIIA binding and induction of ADCC by differentially engineered CD19 antibodies. (<b>A</b>) Binding of antibodies CD19-wt-CHO, CD19-EFTAE-CHO, CD19-wt-Lec13 and CD19-EFTAE-Lec13 to transfected BHK cells stably expressing human FcγRIIIA-158V (BHK-CD16-158V) or FcγRIIIA-158F (BHK-CD16-158F) alleles was analyzed by flow cytometry. Secondary FITC-coupled anti-human IgG Fc F(ab’)2 fragments were employed for detection. MFI, mean fluorescence intensity. (<b>B</b>) Induction of ADCC by antibody versions (concentration: 2 µg/mL) was investigated in 51Cr release experiments using Raji as target cells and human MNC as effector cells. Similarly designed variants of trastuzumab were used as controls. Bars represent mean values of specific lysis ± SEM. Significant differences between CD19 antibodies and HER2-specific control antibodies or the control reaction performed in the absence of any added antibody (no Ab) are indicated (*, <span class="html-italic">p</span> ≤ 0.05; **, <span class="html-italic">p</span> ≤ 0.01; ***, <span class="html-italic">p</span> ≤ 0.001 <span class="html-italic">n</span> = 3). (<b>C</b>) Dose-dependent induction of ADCC by CD19 variants was analyzed using Raji (<span class="html-italic">n</span> = 3) or Ramos cells as targets and MNC as effector cells. Data points indicate mean values of specific lysis ± SEM. Statistically significant differences in ADCC between CD19 antibodies and the control antibody trastuzumab (IgG1) are indicated (*, <span class="html-italic">p</span> ≤ 0.05; **, <span class="html-italic">p</span> ≤ 0.01; <span class="html-italic">n</span> = 3). (<b>D</b>) Comparison of ADCC by the Fc double-engineered antibody CD19-EFTAE-Lec13 (purple) and by the CD20 antibody rituximab (black). Trastuzumab served as an additional negative control (IgG1). Raji cells were used as target cells and MNC served as effector cells. Mean values of specific lysis ± SEM are shown (<span class="html-italic">n</span> = 3).</p> Full article ">Figure 4
<p>C1q binding capacities and induction of CDC by CD19 antibody versions. (<b>A</b>) Raji cells were left untreated (white peaks) or coated with antibodies CD19-wt-CHO, CD19-EFTAE-CHO, CD19-wt-Lec13 or CD19-EFTAE-Lec13 (grey peaks) at a concentration of 50 µg/mL. Then cells were incubated with human serum (1%) as a source of C1q and C1q binding to antibody coated cells was determined using a FITC-conjugated mouse anti-human C1q antibody and flow cytometry. Rituximab, which binds C1q efficiently, and trastuzumab, which does not react with HER2-negative Raji cells, were included as control reagents. MFI, mean fluorescence intensity. (<b>B</b>) CDC by CD19 antibodies was determined by 51Cr release experiments with Ramos cells as target cells in the presence or in the absence of 25% human plasma. Antibodies were analyzed at a concentration of 10 µg/mL. Bars represent mean values of specific lysis ± SEM. Significant differences between antibody-treated groups and the control group without any added antibody (w/o Ab) are indicated (***, <span class="html-italic">p</span> ≤ 0.001; ns, not significant; <span class="html-italic">n</span> = 3). (<b>C</b>) CDC against Ramos by antibodies CD19-EFTAE-Lec13, CD19-EFTAE-CHO and CD19-wt-CHO compared to corresponding engineered control antibodies against HER2 and the native anti-HER2 IgG1 antibody trastuzumab. Antibodies were analyzed at a concentration of 10 µg/mL. Bars show mean values of specific lysis ± SEM. Significant differences between CD19 antibodies and the corresponding versions of the HER2-specific antibody trastuzumab or between antibody treatment and the control reaction without any added antibody (no Ab) are indicated (**, <span class="html-italic">p</span> ≤ 0.01; <span class="html-italic">n</span> = 3). (<b>D</b>) Dose-dependent induction of CDC against Ramos cells (<span class="html-italic">n</span> = 3). Human plasma (25%) was added as a source of complement. *, statistically significant differences (<span class="html-italic">p</span> ≤ 0.05) in CDC between CD19 antibodies and the native CD19-wt-CHO IgG1 molecule; #, statistically significant differences (<span class="html-italic">p</span> ≤ 0.05) between CD19-EFTAE-Lec13 and CD19-wt-Lec13. Trastuzumab served as an additional negative control (IgG1). (<b>E</b>) Comparison of CDC induced by the Fc double-engineered antibody CD19-EFTAE-Lec13 and by the CD20 antibody rituximab. Trastuzumab served as an additional negative control (IgG1). Ramos cells were employed as target cells and serum was added to 25% as a source for complement. Mean values of specific lysis ± SEM are shown (<span class="html-italic">n</span> = 3). (<b>F</b>) Left graph: CD19 antibody variants were analyzed at varying concentrations for their ability to induce CDC against Raji cells, which in comparison to Ramos cells are rather resistant to CDC. Mean values of specific lysis ± SEM are shown (<span class="html-italic">n</span> = 3). Right graph: CD19 antibody variants were compared with rituximab and an Fc engineered version of rituximab-containing the EFTAE modification (CD20-EFTAE-CHO). Trastuzumab served as an additional negative control (IgG1). Mean values of specific lysis ± SEM are shown and statistically significant differences are indicated (**, <span class="html-italic">p</span> &lt; 0.01).</p> Full article ">
24 pages, 4384 KiB  
Article
Dysregulated Antibody, Natural Killer Cell and Immune Mediator Profiles in Autoimmune Thyroid Diseases
by Tiphaine C. Martin, Kristina M. Ilieva, Alessia Visconti, Michelle Beaumont, Steven J. Kiddle, Richard J. B. Dobson, Massimo Mangino, Ee Mun Lim, Marija Pezer, Claire J. Steves, Jordana T. Bell, Scott G. Wilson, Gordan Lauc, Mario Roederer, John P. Walsh, Tim D. Spector and Sophia N. Karagiannis
Cells 2020, 9(3), 665; https://doi.org/10.3390/cells9030665 - 9 Mar 2020
Cited by 24 | Viewed by 6260
Abstract
The pathogenesis of autoimmune thyroid diseases (AITD) is poorly understood and the association between different immune features and the germline variants involved in AITD are yet unclear. We previously observed systemic depletion of IgG core fucosylation and antennary α1,2 fucosylation in peripheral blood [...] Read more.
The pathogenesis of autoimmune thyroid diseases (AITD) is poorly understood and the association between different immune features and the germline variants involved in AITD are yet unclear. We previously observed systemic depletion of IgG core fucosylation and antennary α1,2 fucosylation in peripheral blood mononuclear cells in AITD, correlated with anti-thyroid peroxidase antibody (TPOAb) levels. Fucose depletion is known to potentiate strong antibody-mediated NK cell activation and enhanced target antigen-expressing cell killing. In autoimmunity, this may translate to autoantibody-mediated immune cell recruitment and attack of self-antigen expressing normal tissues. Hence, we investigated the crosstalk between immune cell traits, secreted proteins, genetic variants and the glycosylation patterns of serum IgG, in a multi-omic and cross-sectional study of 622 individuals from the TwinsUK cohort, 172 of whom were diagnosed with AITD. We observed associations between two genetic variants (rs505922 and rs687621), AITD status, the secretion of Desmoglein-2 protein, and the profile of two IgG N-glycan traits in AITD, but further studies need to be performed to better understand their crosstalk in AITD. On the other side, enhanced afucosylated IgG was positively associated with activatory CD335- CD314+ CD158b+ NK cell subsets. Increased levels of the apoptosis and inflammation markers Caspase-2 and Interleukin-1α positively associated with AITD. Two genetic variants associated with AITD, rs1521 and rs3094228, were also associated with altered expression of the thyrocyte-expressed ligands known to recognize the NK cell immunoreceptors CD314 and CD158b. Our analyses reveal a combination of heightened Fc-active IgG antibodies, effector cells, cytokines and apoptotic signals in AITD, and AITD genetic variants associated with altered expression of thyrocyte-expressed ligands to NK cell immunoreceptors. Together, TPOAb responses, dysregulated immune features, germline variants associated with immunoactivity profiles, are consistent with a positive autoreactive antibody-dependent NK cell-mediated immune response likely drawn to the thyroid gland in AITD. Full article
(This article belongs to the Special Issue Molecular and Cellular Basis of Autoimmune Diseases)
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<p>Multi-omics computational analyses were used to study the components of antigen/antibody/effector cell complex structure in AITD. (1) We previously performed glycome-wide association studies of AITD and TPOAb levels using 3146 individuals from three European cohorts, including the TwinsUK cohort. We identified 17 AITD-IgG N-glycan traits in the discovery TwinsUK cohort, and seven of these 17 have been then replicated in two other cohorts [<a href="#B4-cells-09-00665" class="html-bibr">4</a>]. (2) In the present study, we studied the association of total IgG N-glycan traits with 23,485 immune cell traits in 383 individuals from the TwinsUK cohort (regardless of disease status). We showed that 6 out of the 17 AITD-IgG glycan traits were correlated with 51 immune cell traits featuring the CD335, CD134, and CD158b receptors. (3) None of these 51 immune cell traits appeared to be associated with AITD in 374 individuals (34 with AITD). (4) The heritability of AITD, TPOAb level and several -<span class="html-italic">omic</span> features (IgG N-glycan traits and immune cell traits) were performed in previous studies of the TwinsUK cohort [<a href="#B4-cells-09-00665" class="html-bibr">4</a>,<a href="#B27-cells-09-00665" class="html-bibr">27</a>,<a href="#B28-cells-09-00665" class="html-bibr">28</a>,<a href="#B29-cells-09-00665" class="html-bibr">29</a>]. Here we estimated the heritability of secreted proteins, but we could not determine shared additive genetic variance between different phenotypes studied (AITD status, TPOAb level, level of IgG N-glycan traits, of immune cell traits and of circulating proteins in the bloodstream). (5) We identified genetic variants that alter the expression of genes, proteins and cell-bound immune receptors (highlighted in this study) using the previous GWASs performed in the TwinsUK cohort or from GWAS catalog, eQTLs from GTEx project and pQTLs from INTERVAL project [<a href="#B27-cells-09-00665" class="html-bibr">27</a>,<a href="#B28-cells-09-00665" class="html-bibr">28</a>,<a href="#B30-cells-09-00665" class="html-bibr">30</a>,<a href="#B31-cells-09-00665" class="html-bibr">31</a>,<a href="#B32-cells-09-00665" class="html-bibr">32</a>,<a href="#B33-cells-09-00665" class="html-bibr">33</a>,<a href="#B34-cells-09-00665" class="html-bibr">34</a>,<a href="#B35-cells-09-00665" class="html-bibr">35</a>]. (6) We previously performed transcriptome-wide association studies of AITD, TPOAb level, and N-glycan structures in the whole blood of approximately 300 individuals and we found no significant associations [<a href="#B4-cells-09-00665" class="html-bibr">4</a>]. (7) We observed 3 out of 1113 circulating proteins tested in plasma of almost 300 individuals shown to be associated with AITD status (TSH, Caspase-2, and Interleukin-1α). (8) Several secreted proteins were correlated with the level of plasma IgG glycan traits in 164 individuals, but none of them were also associated with AITD. The sample sizes of these different studies are described in <a href="#app1-cells-09-00665" class="html-app">Table S1</a>. GlcNAc = N-acetylglucosamine. The numbers in black depict analyses performed previously [<a href="#B4-cells-09-00665" class="html-bibr">4</a>,<a href="#B27-cells-09-00665" class="html-bibr">27</a>,<a href="#B28-cells-09-00665" class="html-bibr">28</a>,<a href="#B29-cells-09-00665" class="html-bibr">29</a>] while the numbers in red depict analyses presented for the first time in the present study.</p> Full article ">Figure 2
<p>AITD-IgG N-glycan traits associated with a subpopulation of NK cells. (<b>a</b>) Heatmap of immune cell traits associated with AITD-IgG N-glycan traits. The 51 NK cell types were significantly associated with six out of 17 AITD-IgG N-glycan traits previously identified [<a href="#B4-cells-09-00665" class="html-bibr">4</a>]. Below the heatmap, there are one representative of IgG core afucose (IGP2) and one representative of IgG core fucose (IGP7), that were both associated with AITD and TPOAb levels [<a href="#B4-cells-09-00665" class="html-bibr">4</a>]. (<b>b</b>) Co-expressions between only 17 IgG N-glycan traits previously associated significantly with AITD status and TPOAb level [<a href="#B4-cells-09-00665" class="html-bibr">4</a>]. (<b>c</b>) Correlations between the profile of 51 immune cell traits that were associated significantly with at least one of 17 AITD-IgG N-glycan traits. The order of immune cell traits is the same as that in <a href="#cells-09-00665-f002" class="html-fig">Figure 2</a>a.</p> Full article ">Figure 3
<p>Association of immune cell traits with AITD status. Annotation tracks around <span class="html-italic">MIC-A, MIC-B</span> and <span class="html-italic">HLA-C</span> genes visualize significant GWAS hits for immune cell traits, the ligands of certain immunoreceptors (such as NK), and thyroid phenotypes previously identified in the TwinsUK cohort as well as chromatin states identified using chromHMM from whole blood from ENCODE [<a href="#B65-cells-09-00665" class="html-bibr">65</a>] and thyroid cells from CEMT [<a href="#B66-cells-09-00665" class="html-bibr">66</a>] and eQTLs from GTEx project [<a href="#B32-cells-09-00665" class="html-bibr">32</a>,<a href="#B33-cells-09-00665" class="html-bibr">33</a>]. The plot was produced using functions from R packages Gviz and coMET [<a href="#B67-cells-09-00665" class="html-bibr">67</a>].</p> Full article ">Figure 4
<p>Association of circulating protein abundances with thyroid diseases and with AITD-IgG N-glycan structures. (<b>a</b>) 1,113 circulating proteins were arranged in two dimensions based on the similarity of their secretion profiles in the serum by the dimensionality reduction technique UMAP [<a href="#B72-cells-09-00665" class="html-bibr">72</a>] using R package umapr [<a href="#B73-cells-09-00665" class="html-bibr">73</a>]. (<b>b</b>) Correlation of log10-transformed TSH measurements between two clinical FDA approved clinical immunoassays (Roche and Abbott) and SOMAscan assay in 217 individuals (122 using Roche immunoassay and 95 using Abbott immunoassay). (<b>c</b>) Box plot of the level of circulating TSH measured by SOMAscan assay in the serum according to the group of thyroid status. (<b>d</b>) Box plot of the level of circulating Caspase-2 measured by SOMAscan assay in the serum according to the group of TSH. (<b>e</b>) Box plot of the level of circulating IL-1α measured by SOMAscan assay. An extreme outlier sample in the group 4 with an IL-1 α of 250,000 mg/mL was discarded for the analysis. (<b>f</b>) Heatmap of circulating protein abundances associated with AITD-IgG N-glycan structures. In <a href="#cells-09-00665-f002" class="html-fig">Figure 2</a>c–e, participants were assigned to 4 categories according to TSH level and TPOAb status: 1 = hyperthyroidism (TSH &lt; = 0.1 mIU/L; 13 individuals), 2 = euthyroidism/TPOAb-negative (0.4 &lt; TSH &gt; 4 mIU/L &amp; TPOAb &lt; 6 IU/mL (Abbott) or TPOAb &lt; 34 IU/mL (Roche); 196 healthy individuals), 3 = hypothyroidism (TSH &gt; = 4 mIU/L; 21 individuals), and 4 = euthyroidism/TPOAb-positive (0.4 &lt; TSH &gt; 4 mIU/L &amp; TPOAb &gt; = 6 IU/mL (Abbott) or TPOAb &gt; = 34 IU/mL (Roche); 28 individuals). Wilcoxon-Mann-Whitney’s test has been performed between groups to estimate whether there are mean differences whereas Levene’s test has been performed between groups to estimate whether there are variance differences.</p> Full article ">Figure 4 Cont.
<p>Association of circulating protein abundances with thyroid diseases and with AITD-IgG N-glycan structures. (<b>a</b>) 1,113 circulating proteins were arranged in two dimensions based on the similarity of their secretion profiles in the serum by the dimensionality reduction technique UMAP [<a href="#B72-cells-09-00665" class="html-bibr">72</a>] using R package umapr [<a href="#B73-cells-09-00665" class="html-bibr">73</a>]. (<b>b</b>) Correlation of log10-transformed TSH measurements between two clinical FDA approved clinical immunoassays (Roche and Abbott) and SOMAscan assay in 217 individuals (122 using Roche immunoassay and 95 using Abbott immunoassay). (<b>c</b>) Box plot of the level of circulating TSH measured by SOMAscan assay in the serum according to the group of thyroid status. (<b>d</b>) Box plot of the level of circulating Caspase-2 measured by SOMAscan assay in the serum according to the group of TSH. (<b>e</b>) Box plot of the level of circulating IL-1α measured by SOMAscan assay. An extreme outlier sample in the group 4 with an IL-1 α of 250,000 mg/mL was discarded for the analysis. (<b>f</b>) Heatmap of circulating protein abundances associated with AITD-IgG N-glycan structures. In <a href="#cells-09-00665-f002" class="html-fig">Figure 2</a>c–e, participants were assigned to 4 categories according to TSH level and TPOAb status: 1 = hyperthyroidism (TSH &lt; = 0.1 mIU/L; 13 individuals), 2 = euthyroidism/TPOAb-negative (0.4 &lt; TSH &gt; 4 mIU/L &amp; TPOAb &lt; 6 IU/mL (Abbott) or TPOAb &lt; 34 IU/mL (Roche); 196 healthy individuals), 3 = hypothyroidism (TSH &gt; = 4 mIU/L; 21 individuals), and 4 = euthyroidism/TPOAb-positive (0.4 &lt; TSH &gt; 4 mIU/L &amp; TPOAb &gt; = 6 IU/mL (Abbott) or TPOAb &gt; = 34 IU/mL (Roche); 28 individuals). Wilcoxon-Mann-Whitney’s test has been performed between groups to estimate whether there are mean differences whereas Levene’s test has been performed between groups to estimate whether there are variance differences.</p> Full article ">Figure 5
<p>Model of different potential contributing players and their pathways activated in proposed antibody-dependent NK cell-mediated cytotoxicity in the thyroid gland of AITD patients. (1) The depletion of IgG core fucose was associated with TPOAb level and AITD status [<a href="#B4-cells-09-00665" class="html-bibr">4</a>]. (2) The IgG N-glycan traits associated with AITD were also associated with a subpopulation of NK cells in our current study; for example, the depletion of IgG core fucose is associated positively with NK cells with the patterns of co-receptors CD335<sup>−</sup> or CD335<sup>−</sup> CD158b<sup>+</sup> CD314<sup>+</sup>. (3) Previous studies showed that afucosylated antibodies had increased affinity for binding to CD16 (FcγRIIIa), cell receptors of NK cells, and to enhance ADCC [<a href="#B18-cells-09-00665" class="html-bibr">18</a>,<a href="#B19-cells-09-00665" class="html-bibr">19</a>,<a href="#B20-cells-09-00665" class="html-bibr">20</a>,<a href="#B21-cells-09-00665" class="html-bibr">21</a>] via (4) protein tyrosine kinase-dependent pathways, through crosstalk with (5) NKG2D receptor (CD314) [<a href="#B88-cells-09-00665" class="html-bibr">88</a>,<a href="#B89-cells-09-00665" class="html-bibr">89</a>]. (6) Two SNPs, rs3094228 and rs1521, were associated with GD and TPOAb-positivity [<a href="#B60-cells-09-00665" class="html-bibr">60</a>,<a href="#B61-cells-09-00665" class="html-bibr">61</a>,<a href="#B62-cells-09-00665" class="html-bibr">62</a>] and fall in gene regulatory regions of the <span class="html-italic">MIC-A</span> and <span class="html-italic">MIC-B</span> genes and increase their expression in thyroid cells [<a href="#B32-cells-09-00665" class="html-bibr">32</a>]. These two genes encode heavily glycosylated proteins that are ligands for the NKG2D type II receptor (CD314). (7) The KIR2DL (CD158b) receptor is known to regulate the cytotoxicity of NK cells by unknown pathways, whereas (8) the NCR1 (CD335) receptor can contribute to the increased potency of activated NK cells to mediate cell lysis by unknown pathway [<a href="#B54-cells-09-00665" class="html-bibr">54</a>,<a href="#B55-cells-09-00665" class="html-bibr">55</a>]. (9) The SNP, rs1521 associated with GD [<a href="#B60-cells-09-00665" class="html-bibr">60</a>], is also shown to reduce the expression of HLA-C gene, producing the ligand of CD158b, in thyroid cells [<a href="#B32-cells-09-00665" class="html-bibr">32</a>,<a href="#B33-cells-09-00665" class="html-bibr">33</a>,<a href="#B58-cells-09-00665" class="html-bibr">58</a>,<a href="#B59-cells-09-00665" class="html-bibr">59</a>]. (10) All together (the binding of NK cells with target cells through antibodies and their ligands), these lead to the activation of NK cells, which release cytotoxic granules containing perforin and granzymes. This release mediates ADCC of target cells (3), which are thyrocytes in AITD. Also, (11) a positive association between the circulation abundance of Caspase-2 protein and AITD were found in this study that could be associated with the destruction of thyrocytes. (12) A positive correlation of circulating abundance of IL-1α with AITD was also found in the bloodstream that could be a marker of lymphocyte infiltration in the thyroid gland of individuals with AITD, and thus of inflammation [<a href="#B80-cells-09-00665" class="html-bibr">80</a>,<a href="#B81-cells-09-00665" class="html-bibr">81</a>].</p> Full article ">
16 pages, 3056 KiB  
Article
In Vivo Glycan Engineering via the Mannosidase I Inhibitor (Kifunensine) Improves Efficacy of Rituximab Manufactured in Nicotiana benthamiana Plants
by Vally Kommineni, Matthew Markert, Zhongjie Ren, Sreenath Palle, Berenice Carrillo, Jasmine Deng, Armando Tejeda, Somen Nandi, Karen A. McDonald, Sylvain Marcel and Barry Holtz
Int. J. Mol. Sci. 2019, 20(1), 194; https://doi.org/10.3390/ijms20010194 - 7 Jan 2019
Cited by 26 | Viewed by 7904
Abstract
N-glycosylation has been shown to affect the pharmacokinetic properties of several classes of biologics, including monoclonal antibodies, blood factors, and lysosomal enzymes. In the last two decades, N-glycan engineering has been employed to achieve a N-glycosylation profile that is either more consistent or [...] Read more.
N-glycosylation has been shown to affect the pharmacokinetic properties of several classes of biologics, including monoclonal antibodies, blood factors, and lysosomal enzymes. In the last two decades, N-glycan engineering has been employed to achieve a N-glycosylation profile that is either more consistent or aligned with a specific improved activity (i.e., effector function or serum half-life). In particular, attention has focused on engineering processes in vivo or in vitro to alter the structure of the N-glycosylation of the Fc region of anti-cancer monoclonal antibodies in order to increase antibody-dependent cell-mediated cytotoxicity (ADCC). Here, we applied the mannosidase I inhibitor kifunensine to the Nicotiana benthamiana transient expression platform to produce an afucosylated anti-CD20 antibody (rituximab). We determined the optimal concentration of kifunensine used in the infiltration solution, 0.375 µM, which was sufficient to produce exclusively oligomannose glycoforms, at a concentration 14 times lower than previously published levels. The resulting afucosylated rituximab revealed a 14-fold increase in ADCC activity targeting the lymphoma cell line Wil2-S when compared with rituximab produced in the absence of kifunensine. When applied to the cost-effective and scalable N. benthamiana transient expression platform, the use of kifunensine allows simple in-process glycan engineering without the need for transgenic hosts. Full article
(This article belongs to the Section Molecular Plant Sciences)
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<p>Effect of kifunensine on plant-made rituximab. (<b>A</b>) Schematic representation of Immunoglobulin G 1 (IgG1) glycosylation. Complex-type plant glycans (black dotted lines) formed in the absence of kifunensine (black arrow) transformed into Oligomannose-type glycans (red dotted lines) in the presence of kifunensine (red arrow). The oligosaccharide structures are shown in the symbolic depiction suggested by the Consortium of Functional Glycomics (<a href="http://www.functionalglycomics.org" target="_blank">www.functionalglycomics.org</a>). Blue squares -N-acetylglucosamine; Green circles -Mannose; Orange Star- Xylose; and Red Triangle-Fucose. (<b>B</b>) Phenotype of <span class="html-italic">N. benthamiana</span> plants infiltrated under vacuum with <span class="html-italic">Agrobacterium</span> suspension ± kifunensine. Each experimental group received different concentrations of kifunensine in the <span class="html-italic">Agrobacterium</span> infiltration solution and concentrations are indicated on top of each treatment image. (<b>C</b>) Quantification of rituximab in crude protein extracts using Biolayer interferometry (BLItz<sup>®</sup>, ForteBio). Expression levels of rituximab in 7 dpi plant extracts with (orange) and without (green) kifinensine are reported in mg rituximab/kg fresh weight (FW). Error bars represent standard deviations of duplicated expression measurements, where <span class="html-italic">n</span> = 3. (<b>D</b>) SDS-PAGE (sodium dodecyl sulfate Polyacrylamide gel electrophoresis) analysis of purified rituximab samples under reduced and non-reduced conditions. Rituxan, plant-made rituximab with no kifunensine, 0.25 µM kifunensine, 2.5 µM kifunensine, and 5 µM kifunensine were separated on a 4–12% Bis-Tris gel along with Novex sharp pre-stained protein standard.</p> Full article ">Figure 2
<p>N-Glycan analysis of rituximab expressed in <span class="html-italic">N. benthamiana</span> plants with/without kifunensine. LC-MS (Liquid Chromatography-Mass Spectrometry) glycopeptide profiling of rituximab expressed in control and kifunensine treated plants. The distribution of glycoforms in each sample is illustrated and kifunensine concentrations are indicated on each image. Blue squares -N-acetylglucosamine; Green circles -Mannose; Orange Star- Xylose; and Red Triangle-Fucose.</p> Full article ">Figure 3
<p>LC-MS glycopeptide profiling of rituximab samples. The ratio between oligomannose glycoforms (Man<sub>8</sub>, Man<sub>9</sub>) and hybrid glycoforms (GnGn, GnGnXF, and GnGnX) are represented in histograms. Kifunensine concentrations are indicated on the X axis and glycoform percentages are indicated on each sample. Blue squares -N-acetylglucosamine; Green circles -Mannose; Orange Star- Xylose; and Red Triangle-Fucose. Statistical analysis derived from two biological and two technical replicates. Standard deviations (SD) are indicated next to the glycan percentage as follows: * SD value 0 to 1%, ** SD value from 1 to 3%, and *** SD value from 3 to 4%.</p> Full article ">Figure 4
<p>CD20 binding assay of rituximab treated with kifunensine 5 µM, 0.25 µM and untreated controls with Flow Cytometry analysis. Plant-made rituximab was used at concentrations of 50 nM, 25 nM and 12.5 nM. Antibodies bound to CD20 on Wil2-S were detected with goat anti-human IgG polyclonal antibodies conjugated with Fluorescein isothiocyanate (FITC). Median Fluorescence intensity (MFI) was derived from the median value of the fluorescence histogram.</p> Full article ">Figure 5
<p>Antibody-dependent cell-mediated cytotoxicity of rituximab samples expressed in the presence or absence of kifunensine. Assay was performed using Wil2-S target cells along with either high affinity V/V 158 FcγRIIIa variant (<b>A</b>,<b>C</b>) or low affinity F/F 158 FcγRIIIa variant (<b>B</b>,<b>D</b>) engineered Jurkat cells. The effector cell: target cell ratio was 10:1. Values are expressed as normalized RLUs (<b>A</b>,<b>B</b>) and represent the mean ± Standard Deviation (SD). for triplicate analyses. Summary of ADCC activity represented as EC<sub>50</sub> values. The horizontal dotted defines 100% and 50% value (<b>C</b>,<b>D</b>), normalized to the control 0 uM kifunensine control value, indicating relative activity. The error bars of each EC<sub>50</sub> value correspond to the standard error of the mean.</p> Full article ">
17 pages, 2674 KiB  
Article
Implementation of Glycan Remodeling to Plant-Made Therapeutic Antibodies
by Lindsay D. Bennett, Qiang Yang, Brian R. Berquist, John P. Giddens, Zhongjie Ren, Vally Kommineni, Ryan P. Murray, Earl L. White, Barry R. Holtz, Lai-Xi Wang and Sylvain Marcel
Int. J. Mol. Sci. 2018, 19(2), 421; https://doi.org/10.3390/ijms19020421 - 31 Jan 2018
Cited by 11 | Viewed by 6826
Abstract
N-glycosylation profoundly affects the biological stability and function of therapeutic proteins, which explains the recent interest in glycoengineering technologies as methods to develop biobetter therapeutics. In current manufacturing processes, N-glycosylation is host-specific and remains difficult to control in a production environment [...] Read more.
N-glycosylation profoundly affects the biological stability and function of therapeutic proteins, which explains the recent interest in glycoengineering technologies as methods to develop biobetter therapeutics. In current manufacturing processes, N-glycosylation is host-specific and remains difficult to control in a production environment that changes with scale and production batches leading to glycosylation heterogeneity and inconsistency. On the other hand, in vitro chemoenzymatic glycan remodeling has been successful in producing homogeneous pre-defined protein glycoforms, but needs to be combined with a cost-effective and scalable production method. An efficient chemoenzymatic glycan remodeling technology using a plant expression system that combines in vivo deglycosylation with an in vitro chemoenzymatic glycosylation is described. Using the monoclonal antibody rituximab as a model therapeutic protein, a uniform Gal2GlcNAc2Man3GlcNAc2 (A2G2) glycoform without α-1,6-fucose, plant-specific α-1,3-fucose or β-1,2-xylose residues was produced. When compared with the innovator product Rituxan®, the plant-made remodeled afucosylated antibody showed similar binding affinity to the CD20 antigen but significantly enhanced cell cytotoxicity in vitro. Using a scalable plant expression system and reducing the in vitro deglycosylation burden creates the potential to eliminate glycan heterogeneity and provide affordable customization of therapeutics’ glycosylation for maximal and targeted biological activity. This feature can reduce cost and provide an affordable platform to manufacture biobetter antibodies. Full article
(This article belongs to the Special Issue Recombinant Proteins)
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<p>(<b>A</b>) Schematic representation of in vivo <span class="html-italic">N</span>-glycan processing of recombinant proteins in standard plant expression systems (Option A) and when co-expressed with EndoH (Option B). The Option B pathway illustrates the in vivo deglycosylation strategy employed for rituximab custom glycosylation where high-mannose glycans attached to the protein of interest are cleaved off by EndoH, leaving a deglycosylated substrate for in vitro transglycosylation; (<b>B</b>) plots of rituximab expression levels in mg/kg of plant biomass. Protein was harvested from plants expressing rituximab alone (black bar) or coexpressing rituximab with EndoH (grey bar) (Values are means ± SEM, <span class="html-italic">n</span> = 4); (<b>C</b>) SDS-PAGE showing rituximab under reduced conditions, with or without EndoH coexpression. The light chain (RTX LC) species for both samples migrated similarly, while the heavy chain (RTX HC) from plants coexpressing EndoH underwent an increased mobility relative to the rituximab alone, indicating a decrease in molecular weight.</p> Full article ">Figure 1 Cont.
<p>(<b>A</b>) Schematic representation of in vivo <span class="html-italic">N</span>-glycan processing of recombinant proteins in standard plant expression systems (Option A) and when co-expressed with EndoH (Option B). The Option B pathway illustrates the in vivo deglycosylation strategy employed for rituximab custom glycosylation where high-mannose glycans attached to the protein of interest are cleaved off by EndoH, leaving a deglycosylated substrate for in vitro transglycosylation; (<b>B</b>) plots of rituximab expression levels in mg/kg of plant biomass. Protein was harvested from plants expressing rituximab alone (black bar) or coexpressing rituximab with EndoH (grey bar) (Values are means ± SEM, <span class="html-italic">n</span> = 4); (<b>C</b>) SDS-PAGE showing rituximab under reduced conditions, with or without EndoH coexpression. The light chain (RTX LC) species for both samples migrated similarly, while the heavy chain (RTX HC) from plants coexpressing EndoH underwent an increased mobility relative to the rituximab alone, indicating a decrease in molecular weight.</p> Full article ">Figure 2
<p>Nano liquid chromatography-electrospray ionization-quadrupole time of flight-mass spectrometry (NanoLC-QTOF-MS) analysis of plant-made rituximab. (<b>A</b>) Deconvoluted electrospray ionization (ESI)-mass spectrum of purified <sub>Nb</sub>RTX analyzed under non-reducing conditions showing fully glycosylated and hemiglycosylated rituximab; (<b>B</b>) Deconvoluted ESI-mass spectrum of purified <sub>Nb</sub>RTX<sup>GlcNAc</sup> analyzed under non-reducing conditions showing a decrease in molecular weight; (<b>C</b>) Deconvoluted ESI-mass spectrum of in vivo deglycosylated plant-made rituximab analyzed under reducing conditions. Note the mass shift between non-glycosylated rituximab heavy chain <sub>Nb</sub>RTX<sup>0</sup> (calculated <span class="html-italic">m</span>/<span class="html-italic">z</span> 49,217) and deglycosylated rituximab heavy chain <sub>Nb</sub>RTX<sup>GlcNAc</sup> (calculated <span class="html-italic">m</span>/<span class="html-italic">z</span> 49,420). As comparison, the NanoLC-QTOF-MS analysis of Rituxan<sup>®</sup> is provided in <a href="#app1-ijms-19-00421" class="html-app">Figure S2</a>.</p> Full article ">Figure 3
<p>Chemoenzymatic transglycosylation of plant-made rituximab. (<b>A</b>) Schematic representation of the chemoenzymatic transglycosylation reaction; (<b>B</b>) NanoLC-QTOF-MS analysis of reglycosylated plant-made rituximab. Deconvoluted ESI-mass spectrum of reglycosylated plant-made rituximab with the A2G2 glycan (<sub>Nb</sub>RTX<sup>A2G2</sup> heavy chain, calculated <span class="html-italic">m</span>/<span class="html-italic">z</span> 50,840) analyzed under reducing conditions.</p> Full article ">Figure 4
<p>Binding of Rituxan<sup>®</sup> (<b>A</b>,<b>B</b>) and <sub>Nb</sub>RTX<sup>A2G2</sup> (<b>C</b>,<b>D</b>) to Wil2-S and Daudi cells analyzed by flow cytometry. Rituxan<sup>®</sup> and <sub>Nb</sub>RTX<sup>A2G2</sup> were used at a concentration of 10 nM. All rituximab samples were measured in triplicates (red, green and blue lines). FITC-labeled mouse IgG2a (black line) and unstained cells (grey line) were used as controls. The X-axis represents the fluorescent signals of FITC whereas the Y-axis presents % of cell count.</p> Full article ">Figure 4 Cont.
<p>Binding of Rituxan<sup>®</sup> (<b>A</b>,<b>B</b>) and <sub>Nb</sub>RTX<sup>A2G2</sup> (<b>C</b>,<b>D</b>) to Wil2-S and Daudi cells analyzed by flow cytometry. Rituxan<sup>®</sup> and <sub>Nb</sub>RTX<sup>A2G2</sup> were used at a concentration of 10 nM. All rituximab samples were measured in triplicates (red, green and blue lines). FITC-labeled mouse IgG2a (black line) and unstained cells (grey line) were used as controls. The X-axis represents the fluorescent signals of FITC whereas the Y-axis presents % of cell count.</p> Full article ">Figure 5
<p>Antibody-dependent-cell-mediated cytotoxicity (ADCC) activity of Rituxan<sup>®</sup> and <sub>Nb</sub>RTX<sup>A2G2</sup> with (<b>A</b>) V/V 158 FcγRIIIa (high affinity) and (<b>B</b>) F/F 158 FcγRIIIa (low affinity) variant effector cells (engineered Jurkat cells with FcγRIIIa receptor). All experiments were carried out using human B lymphoma WIL2-S cells and Daudi cells as target cells. The effector cell: target cell ratio was 10:1. Data are expressed as fold of ADCC increase. Values represent mean ± S.D. for triplicate analyses.</p> Full article ">Figure 6
<p>Comparison of EC50 values of Rituxan<sup>®</sup>, plant-made rituximab (<sub>Nb</sub>RTX), deglycosylated plant-made rituximab (<sub>Nb</sub>RTX<sup>GlcNAc</sup>), and reglycosylated plant-made rituximab (<sub>Nb</sub>RTX<sup>A2G2</sup>) determined by the ADCC Reporter Bioassay using Wil2 V/V158 (Wil2/V) and F/F158 (Wil2/F) variant cells. The calculated EC50 values are shown above the respective histogram bars.</p> Full article ">
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