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Updated: Jun 9, 2025

A High-throughput Automated Platform for the Development of Manufacturing Cell Lines for Protein Therapeutics
Published on: September 22, 2011
Development of a Mammalian Cell Line for Stable Production of Anti-PD-1
Erika Csató-Kovács1,2, Pál Salamon1,2,3, Szilvia Fikó-Lászlo3
1Department of Bioengineering, Faculty of Economics, Socio-Human Sciences and Engineering, Sapientia Hungarian University of Transylvania, 1 Libertatii Sq, 530104 Miercurea Ciuc, Romania.
Abstract:
Background/Objectives: Immune checkpoint blockade, particularly targeting the programmed cell death 1 (PD-1) receptor, is a promising strategy in cancer immunotherapy. The interaction between PD-1 and its ligands, PD-L1 and PD-L2, is crucial in immune evasion by tumors. Blocking this interaction with monoclonal antibodies like Nivolumab can restore anti-tumor immunity. This study aims to develop a stable expression system for Nivolumab-based anti-PD-1 in the Chinese Hamster Ovary (CHO) DG44 cell line using two different expression vector systems with various signal sequences. Methods: The heavy chain (HC) and light chain (LC) of Nivolumab were cloned into two expression vectors, pOptiVEC and pcDNA3.3. Each vector was engineered with two distinct signal sequences, resulting in the creation of eight recombinant plasmids. These plasmids were co-transfected into CHO DG44 cells in different combinations, allowing for the assessment of stable antibody production. Results: Both pOptiVEC and pcDNA3.3 vectors were successful in stably integrating and expressing the Nivolumab-based anti-PD-1 antibody in CHO DG44 cells. This study found that the choice of signal sequence significantly influenced the quantity of antibodies produced. The optimization of production conditions further enhanced antibody yield, indicating the potential for large-scale production. Conclusions: This study demonstrates that both pOptiVEC and pcDNA3.3 expression systems are effective for the stable production of Nivolumab-based anti-PD-1 in CHO DG44 cells. Signal sequences play a critical role in determining the expression levels, and optimizing production conditions can further increase antibody yield, supporting future applications in cancer immunotherapy.
Insights
This study developed a stable Chinese Hamster Ovary (CHO) DG44 cell expression system for Nivolumab-based anti-programmed cell death 1 (PD-1) antibody production. Signal sequences and optimized conditions significantly impacted antibody yield for cancer immunotherapy.
Area of Science:
- Biotechnology
- Immunology
- Oncology
Background:
- Immune checkpoint blockade, targeting programmed cell death 1 (PD-1), is a key cancer immunotherapy strategy.
- Tumors evade immune responses by exploiting the PD-1/PD-L1/PD-L2 interaction.
- Monoclonal antibodies like Nivolumab can restore anti-tumor immunity by blocking this interaction.
Purpose of the Study:
- To establish a stable Chinese Hamster Ovary (CHO) DG44 cell expression system for Nivolumab-based anti-PD-1 antibody.
- To evaluate two distinct expression vector systems (pOptiVEC and pcDNA3.3) with varied signal sequences for antibody production.
Main Methods:
- Cloning of Nivolumab heavy and light chains into pOptiVEC and pcDNA3.3 vectors, each with two signal sequences.
- Co-transfection of eight resulting recombinant plasmids into CHO DG44 cells for stable expression assessment.
- Optimization of production conditions to enhance antibody yield.
Main Results:
- Both pOptiVEC and pcDNA3.3 vectors facilitated stable integration and expression of the anti-PD-1 antibody in CHO DG44 cells.
- The selection of signal sequences critically influenced the quantity of antibodies produced.
- Optimized production conditions led to increased antibody yield, demonstrating scalability potential.
Conclusions:
- pOptiVEC and pcDNA3.3 expression systems are effective for stable Nivolumab-based anti-PD-1 production in CHO DG44 cells.
- Signal sequences are crucial determinants of antibody expression levels.
- Further optimization can enhance yield for future cancer immunotherapy applications.

