Author(s): Dorai H, Corisdeo S, Ellis D, Kinney C, Chomo M,
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Abstract One of the most important criteria for the successful manufacture of a therapeutic protein (e.g., an antibody) is to develop a mammalian cell line that maintains stability of production. Problems with process yield, lack of effective use of costly resources, and a possible delay in obtaining regulatory approval of the product may ensue otherwise. Therefore the stability of expression in a number of Chinese hamster ovary (CHO) derived production cell lines that were isolated using the glutamine synthetase (GS) selection system was investigated by defining a culture as unstable if the titer (which is a measure of productivity) of a cell line expressing an antibody or antibody-fusion protein declined by 20-30\% or more as it underwent 55 population doublings. Using this criterion, a significant proportion of the GS-selected CHO production cell lines were observed to be unstable. Reduced antibody titers correlated with the gradual appearance of a secondary, less productive population of cells as detected with flow cytometric analysis of intracellular antibody content. Where tested, it was observed that the secondary population arose spontaneously from the parental population following multiple passages, which suggested inherent clonal instability. Moreover, the frequency of unstable clones decreased significantly if the host cell line from which the candidate production cell lines were derived was apoptotic-resistant. This data suggested that unstable cell lines were more prone to apoptosis, which was confirmed by the fact that unstable cell lines had higher levels of Annexin V and caspase 3 activities. This knowledge has been used to develop screening protocols that identify unstable CHO production cell lines at an early stage of the cell line development process, potentially reducing the cost of biotherapeutic development. Copyright © 2011 Wiley Periodicals, Inc.
This article was published in Biotechnol Bioeng
and referenced in Journal of Proteomics & Bioinformatics