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Journal of Immunological Methods
Article . 1994 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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The genetic engineering of monoclonal antibodies

Authors: Owens, R; Young, R;

The genetic engineering of monoclonal antibodies

Abstract

A number of recent technological developments have greatly facilitated the genetic engineering of immunoglobulins. The use of PCR has permitted the variable regions to be rapidly cloned either from a specific hybridoma source or as a gene library from non-immunised cells. The conversion of the rodent antibody into a humanized version is now well established. To develop these antibodies for clinical use has required the development of high level expression systems. For the expression of large multimeric glycoproteins, mammalian cell systems generally provide the highest levels of secreted product and therefore are the methods of choice for producing whole recombinant antibodies. Novel antigen-binding units have been developed by joining the two variable domains of an antibody into single-chain polypeptides. Such fragments can be produced in high yield by secretion from E. coli raising the prospect of bulk preparation of these antibody fragments for the development of low-cost immunopurification and assay reagents. Finally, the ability to screen for antigen binding by displaying immunoglobulin variable regions on the surface of filamentous bacteriaphages has opened up the possibility of bypassing the immune system to generate novel antibody specificities in vitro.

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Keywords

Bacteria, Genes, Immunoglobulin, Recombinant Fusion Proteins, Molecular Sequence Data, Antibodies, Monoclonal, Gene Expression, CHO Cells, Protein Engineering, Cricetinae, Animals, Humans, Amino Acid Sequence

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    63
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
63
Average
Top 10%
Top 10%
Green