| Literature DB >> 34206616 |
Heesu Chae1,2, Seulki Cho3, Munsik Jeong1, Kiyoung Kwon1, Dongwook Choi4, Jaeyoung Lee2, Woosuk Nam2, Jisu Hong1, Jiwoo Lee1, Seonjoo Yoon2, Hyojeong Hong1,3.
Abstract
The biophysical properties of therapeutic antibodies influence their manufacturability, efficacy, and safety. To develop an anti-cancer antibody, we previously generated a human monoclonal antibody (Ab417) that specifically binds to L1 cell adhesion molecule with a high affinity, and we validated its anti-tumor activity and mechanism of action in human cholangiocarcinoma xenograft models. In the present study, we aimed to improve the biophysical properties of Ab417. We designed 20 variants of Ab417 with reduced aggregation propensity, less potential post-translational modification (PTM) motifs, and the lowest predicted immunogenicity using computational methods. Next, we constructed these variants to analyze their expression levels and antigen-binding activities. One variant (Ab612)-which contains six substitutions for reduced surface hydrophobicity, removal of PTM, and change to the germline residue-exhibited an increased expression level and antigen-binding activity compared to Ab417. In further studies, compared to Ab417, Ab612 showed improved biophysical properties, including reduced aggregation propensity, increased stability, higher purification yield, lower pI, higher affinity, and greater in vivo anti-tumor efficacy. Additionally, we generated a highly productive and stable research cell bank (RCB) and scaled up the production process to 50 L, yielding 6.6 g/L of Ab612. The RCB will be used for preclinical development of Ab612.Entities:
Keywords: anti-cancer antibody; antibody engineering; biophysical properties; computational methods; research cell bank; therapeutic antibody
Mesh:
Substances:
Year: 2021 PMID: 34206616 PMCID: PMC8268072 DOI: 10.3390/ijms22136696
Source DB: PubMed Journal: Int J Mol Sci ISSN: 1422-0067 Impact factor: 5.923
Figure 1Schematic representation of the substitutions of Ab417 for improved biophysical properties. (A) Design of the VL and VH residue substitutions. (B) The 3D model of Ab417. The I31S and V96P in the VL and the R16G, D54E, K76A, and P88A in the VH are shown in red. Gray, VL; Green, VH; Lime, LCDR; Light green, HCDR.
Figure 2(A) Expression levels of antibodies using the ExpiCHO transient expression system. (B,C) Ab417 and Ab612 were purified by protein A affinity chromatography (B) and CIEX by stepwise gradient elution and linear gradient elution, respectively (C). (D) Final polishing was conducted using SEC. (E) SEC-HPLC of each antibody was performed to determine the purity and homogeneity following purification.
Figure 3Assessment of thermal stability of Ab417 (A) and Ab612 (B) by DLS. The blue line indicates the starting point of protein aggregation.
Figure 4Determination of the affinities of Ab417 and Ab612 for hL1-s1 (A) and mL1-s1 (B) by competitive ELISA and the Octet system (C). Kon, rate of association; Kdis, rate of dissociation; Full R^2, estimate of the goodness of the curve fit.
Figure 5Anti-tumor efficacy of Ab612 compared with Ab417 in a Choi-Ck cholangiocarcinoma xenograft nude mouse model (n = 8). When the tumor volume reached an average of 100 mm3, dosing (10 mpk) was initiated 3 times weekly for 22 days. Mean tumor volume (A), tumor weight (B), and body weight (C) are shown. (D) Photographs of the resected tumors at the end of the experiment. Each point represents the mean ± SD. * p < 0.05, ** p < 0.01, significant difference from the isotype control group by Dunnett’s t-test.
Figure 6(A) Schematic diagram showing the generation of a research cell bank (RCB). (B) Ab612 titer was measured to assess the expression level, and Qp was calculated as PCD = (pg/cell/day) using PA-HPLC. (C) The purity of Ab612 produced from the RCB was analyzed by SEC-HPLC after purification. (D) Ag binding activity was determined by sandwich ELISA.