Host cell proteins (HCPs) are process-related impurities generated during biotherapeutic protein production. HCPs can be problematic if they pose a significant metabolic demand, degrade product ...quality, or contaminate the final product. Here, we present an effort to create a "clean" Chinese hamster ovary (CHO) cell by disrupting multiple genes to eliminate HCPs. Using a model of CHO cell protein secretion, we predict that the elimination of unnecessary HCPs could have a non-negligible impact on protein production. We analyze the HCP content of 6-protein, 11-protein, and 14-protein knockout clones. These cell lines exhibit a substantial reduction in total HCP content (40%-70%). We also observe higher productivity and improved growth characteristics in specific clones. The reduced HCP content facilitates purification of a monoclonal antibody. Thus, substantial improvements can be made in protein titer and purity through large-scale HCP deletion, providing an avenue to increased quality and affordability of high-value biopharmaceuticals.
Glycosylated biopharmaceuticals are important in the global pharmaceutical market. Despite the importance of their glycan structures, our limited knowledge of the glycosylation machinery still ...hinders controllability of this critical quality attribute. To facilitate discovery of glycosyltransferase specificity and predict glycoengineering efforts, here we extend the approach to model N-linked protein glycosylation as a Markov process. Our model leverages putative glycosyltransferase (GT) specificity to define the biosynthetic pathways for all measured glycans, and the Markov chain modeling is used to learn glycosyltransferase isoform activities and predict glycosylation following glycosyltransferase knock-in/knockout. We apply our methodology to four different glycoengineered therapeutics (i.e., Rituximab, erythropoietin, Enbrel, and alpha-1 antitrypsin) produced in CHO cells. Our model accurately predicted N-linked glycosylation following glycoengineering and further quantified the impact of glycosyltransferase mutations on reactions catalyzed by other glycosyltransferases. By applying these learned GT-GT interaction rules identified from single glycosyltransferase mutants, our model further predicts the outcome of multi-gene glycosyltransferase mutations on the diverse biotherapeutics. Thus, this modeling approach enables rational glycoengineering and the elucidation of relationships between glycosyltransferases, thereby facilitating biopharmaceutical research and aiding the broader study of glycosylation to elucidate the genetic basis of complex changes in glycosylation.
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Biosimilar drugs must closely resemble the pharmacological attributes of innovator products to ensure safety and efficacy to obtain regulatory approval. Glycosylation is one critical quality ...attribute that must be matched, but it is inherently difficult to control due to the complexity of its biogenesis. This usually implies that costly and time‐consuming experimentation is required for clone identification and optimization of biosimilar glycosylation. Here, a computational method that utilizes a Markov model of glycosylation to predict optimal glycoengineering strategies to obtain a specific glycosylation profile with desired properties is described. The approach uses a genetic algorithm to find the required quantities to perturb glycosylation reaction rates that lead to the best possible match with a given glycosylation profile. Furthermore, the approach can be used to identify cell lines and clones that will require minimal intervention while achieving a glycoprofile that is most similar to the desired profile. Thus, this approach can facilitate biosimilar design by providing computational glycoengineering guidelines that can be generated with a minimal time and cost.
Biosimilars must resemble the glycoprofile of the original protein drug. The authors present a computational method to predict the required perturbations in the glycosylation reaction network that will match a glycoprofile from a production cell line with the glycoprofile of the original product.
Abstract only The emergent market of new therapeutic glycoprofiles demands cost‐and‐labor efficient N‐linked glycoengineering, such as rational glycoengineering. However, rational glycoengineering ...remains challenging due to our limited understanding of the complex glycosyltransferase (GT) interactions. Predicting glycosylation outcomes of GT knockins/knockouts requires comprehensive and context‐specific knowledge of GT activities. To combat this issue, we proposed an improved low‐parameter Markov chain model to learn GT activities and used the learnt information to predict glycoprofiles impacted by complex glycoengineering. Specifically, we have quantified the impact of GT isozyme specificities and interactions by fitting the model with a compilation of single‐GT‐knockout erythropoietin (EPO) glycoprofiles for CHO cells. We then showed that the quantified GT impact can be generalized by our model framework to predict complex multiple‐GT‐knockout glycoprofiles of four diverse therapeutic drugs, including EPO, Rituximab, Enbrel, and alpha‐1 antitrypsin. Therefore, the proposed methodology allowed us to systematically unravel the complicated GT interactions beyond simple enzyme rules and with little a priori information. Such approach will further promote progress in rational glycoengineering by broadening our scope on the genetic basis of glycosylation, expediting product development for biopharmaceutical research. Support or Funding Information This work was conducted with support from the Novo Nordisk Foundation provided to the Center for Biosustainability at the Technical University of Denmark (NNF10CC1016517: A.L., A.W.T.C., A.H.H., B.G.V.) and NIGMS (R35 GM119850: N.E.L.) Figure 1
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Glycosylation is fundamentally important to the activity, stability and pharmacokinetics of biopharmaceuticals. Move on to the future, glycoengineering is a promising way to improve ...protein drug efficacy. Recently, several major advances in engineering efforts have successfully led to desired protein glycoforms, but some desirable glycoengineering designs have proven toxic to the host cells (e.g., CHO cell lines). Up to date, the critical barrier in controlling the glycan structures is the diversity and complexity of glycosylation. Moreover, there has not been a systematic study unraveling how engineering efforts impact the host cell and their protein secretion system. There is a great need to bridge the knowledge gap that enables rational glycoengineering and elucidate how such strategies impact the host cell. To accomplish this, we have comprehensively studied the impact of glycoengineering on a library of more than 180 CHO cell clones, wherein dozens of glycosyltransfersases were knocked out or knocked in. We integrate data that glycoprofiled all these clones, quantified the impact of different glycosyltransferase knockouts on the bioprocessing phenotypes of the CHO cells (e.g., cell size, growth, viability, and metabolism), and expression profiling these cells using RNA‐Seq data to identify dysregulated pathways and genes following glycoengineering. Here, we deployed an innovative systems biology approach to rapidly study the changes in glycosylation across all glycoengineered mutants and to study the molecular basis of the phenotypic changes. Our key results are (1) we identified dominant glycosyltransferses responsible for the N‐linked glycosylation in CHO cells, and the glycoengineered cells differentially expressed isozymes in response to a knockout; (2) we identified groups of glycosyltransferases whose perturbations led to a more severe impact on cell glycosylation and phenotypes; (3) we also identified key metabolic and signaling pathways are modulated when different glycosyltransferase families were perturbed. This research is the first study for gaining a comprehensive view of the complex cellular response to glycoengineering on the host cells producing the recombinant protein drugs. The insights from this study provides valuable knowledge that enables the rational engineering of glycosylation to be able to control this critical quality attribute on diverse recombinant protein drugs.
Support or Funding Information
This work was supported by generous funding from the Novo Nordisk Foundation provided to the Center for Biosustainability at the Technical University of Denmark (grant no. NNF10CC1016517).
Abstract Background We assessed the association of serine protease inhibitor Kazal type I (SPINK1) expression with clinicopathologic outcomes in urothelial carcinoma of the bladder (UCB) patients ...treated with radical cystectomy (RC). Materials and methods Tissue microarrays comprising 438 consecutive UCB patients treated with RC between 1988 and 2003 and 62 cases of normal urothelium controls were evaluated for SPINK1 protein expression by immunohistochemistry (IHC). Semiquantitative evaluation was performed by 2 pathologists blinded to clinical outcomes (loss of expression: <50% cells or intensity 0–2). Results In normal urothelium, SPINK1 expression was noted in umbrella cells of 32 of 62 controls (52%); 254 RC patients (57.9%) exhibited loss of SPINK1 expression. Loss of SPINK1 expression was significantly associated with higher pathologic stages ( P = 0.002) and presence of lymph node metastasis ( P = 0.04). At a median follow-up of 130 months (IQR: 98.4), loss of SPINK1 expression was associated with an increased risk of disease recurrence ( P = 0.02) and cancer-specific mortality ( P = 0.03). On multivariable analysis that adjusted for the effects of standard clinicopathologic parameters, SPINK1 was not an independent predictor of disease recurrence ( P = 0.09) or cancer-specific mortality ( P = 0.12). Conclusions Over half of UCB patients treated with RC exhibit loss of SPINK1 expression. Loss of SPINK1 correlates with features of biologically aggressive UCB. Although SPINK1 expression did not have independent prognostic value in RC patients, it may serve as a biomarker for tumor staging and may be useful as an adjunct in clinical decision-making.
A traditional approach in agricultural and veterinary research is focussing on the biological perspective where large cattle-databases are used to analyse the dairy herd. This approach has yielded ...valuable insights. However, recent research indicates that this knowledge-base can be further increased by examining agricultural and veterinary challenges from other perspectives. In this paper we suggest three perspectives that may supplement the biological perspective in agricultural and veterinary research; the economic-, the managerial-, and the social perspective. We review recent studies applying or combining these perspectives and discuss how multiple perspectives may improve our understanding and ability to handle cattle-health challenges.
Objective The results of rectal cancer surgery in Norway have been poor. In a national audit for the period 1986–88, 28% of the patients developed local recurrence (LR) following treatment with a ...curative intent. Five‐year overall survival was 55% for patients younger than 75 years. The aim of this study is to report how an initiative focusing on better surgery can improve the prognosis for rectal cancer patients on a national level.
Methods In 1994, the Norwegian Rectal Cancer Group was founded. The aim of this initiative was to improve the surgical standard by implementing total mesorectal excision (TME) on a national level and to evaluate the results. A number of courses were arranged to teach the surgeons the TME technique, and pathologists were trained to increase the standard of both macroscopic and microscopic assessment of specimens. A rectal cancer registry was established, and all surgical departments treating rectal cancer were invited to transfer their clinical data to this registry. Each department regularly receives its own results together with the national average for comparison and quality control.
Results The Rectal Cancer Registry includes all patients with rectal cancer diagnosed since November 1993. From then until December 1999, 5382 patients had a tumour located within 16 cm from the anal verge, and 3432 patients underwent rectal resection with a curative intent. Of these, 9% had adjuvant radiotherapy, and 2% were given chemotherapy. There was a rapid implementation of the new technique, as 78% underwent TME in 1994, increasing to 96% in 1998. After 39 months mean follow‐up the rate of local recurrence was 8%, and 5‐year overall survival was 71% for patients younger than 75 years.
Conclusions An optimized surgical technique (TME) for rectal cancer can reduce the rate of local recurrence and increase overall survival. This improved surgical treatment can be implemented on a national level within a few years. Specialization of surgeons, feedback of results and a separate rectal cancer registry are thought to be major contributors to the improved treatment.
In order to provide a legal framework within the European Union (EU) for the evaluation of existing chemicals (i.e., substances listed in the European Inventory of Existing Commercial Substances), ...Council Regulation (EEC) 793/93 was adopted, in which the evaluation of the existing chemicals is carried out by four steps, namely data collection, priority setting, risk assessment, and, if necessary, risk reduction. To fulfill the priority‐setting step the EU Risk Ranking Method (EURAM) was developed to produce rankings that are the basis for drawing up lists of substances, used for priority setting, among the so‐called high production volume chemicals appearing in the International Uniform Chemical Information database. The EURAM ranks substances on the basis of their potential risk to humans and the environment by using a simple exposure‐effect model, containing both human health and environmental effect endpoints as well as exposure parameters. The EURAM fulfills criteria for a good chemical ranking scheme and has been applied and used as a basis for selecting substances for the second and the third list of priority substances as foreseen under Council Regulation (EEC) 793/93.
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