Post-translational modifications of therapeutic proteins
This extract is part of a whitepaper on the use of CRISPR/CAS9 and other gene editing tools in cell line development and engineering. Download the full whitepaper for free here.
Advanced gene editing technologies such as CRISPR/ Cas9, TALE nucleases, RNA interference tools, as well as the combination of next-generation sequencing with systems biotechnology will further facilitate the enhancements in cell glycosylation processing. These tools will enable cell engineers to make even more highly refined and targeted modifications to fast-track the processing capability of these cells with consistent, improved product biologics’ yield, effectiveness, quality, and thus affordability for future health care needs.
We are witnessing a proliferation of enabling tools, as molecular and cell biologists have developed sophisticated techniques to decipher attributes critical to quality. Improving the glycosylation profile of biologics will definitively continue being a priority for the industry to enhance their quality and bioactivity. In fact, N-linked glycosylation plays a crucial role in the efficacy of therapeutic proteins and is therefore considered as one of the major quality attributes. Superior therapeutics with proven efficacy of various glycoengineered proteins has stimulated the development of novel optimized expression systems such as mammalian cells producing nonfucosylated antibodies.
Besides, it is now becoming feasible to produce material rapidly for pharmacology, formulation, and toxicology studies without having to establish a stable cell line. Furthermore, shortens the timeline for stable cell-line development, from six/nine months to three weeks, enabling generation of stable clones already at the research stage. At the same time, various production systems for glyco-optimized proteins, including yeast have already been engineered to produce the main steps of the human N-glycosylation pathway and enabled biobetter versions of therapeutic mAbs.
Furthermore, CRISPR/Cas9 tools gave rise to multiplexed knockout phenotypes. Similarly, upcoming achievements in (small) non-coding RNAs in CHO cells might also support functional genomics efforts to enhance producer cells. That will significantly expand the list of engineering targets in the organism (Obinutuzumab, an EMA, and FDA approved humanized and glycoengineered anti-CD20 mAb, with bisected afucosylated Fc region-carbohydrates, with GlycoMAb technology from Glycart-Roche).
Not far ago, CHO cells were considered as ‘black boxes’ due to the lack of genomic information. Thus hindering efforts to understand the molecular basis of high level, quality production of recombinant proteins in CHO cells.
Notably, impressive progress in CHO cell culture technology has been achieved by empirical approaches such as screening and process optimization enabling high yields (10 g/L and over). Although, such yields are often limited to only certain types of product. Also, a high degree of variability of rCHO cells requires laborious and expensive processes to select the best clone for the production of each new therapeutic candidate.
Given the fact that traditional recombinant cells are based on random plasmid integration and its expression cassette in the host genome. Transgenes are likely to be inserted in heterochromatin regions, which results in very weak gene expression levels. That implies screening a substantial number of clones (generally multiple hundreds to a few thousand, to find those rare ones with a stably integrated plasmid in highly transcriptionally active chromatin regions (“hotspots”).
Sequencing efforts have resulted in additional genomic sequence data being available for the Chinese hamster and various CHO cell lines. Moreover, an active effort is underway in the CHO community to refine the genome assembly and annotation for the Chinese hamster. Recently, several molecular and cellular biology tools have been developed for targeted site gene integration. Eventually minimizing the randomness of gene insertion and increasing the predictability of high transgene expression.