Immunogenicity

Immunogenicity is the ability of a foreign substance, such as an antigen, to provoke an immune response in the body of a human or other animal. It may be wanted or unwanted:
A challenge in biotherapy is predicting the immunogenic potential of novel protein therapeutics. For example, immunogenicity data from high-income countries are not always transferable to low-income and middle-income countries. Another challenge is considering how the immunogenicity of vaccines changes with age. Therefore, as stated by the World Health Organization, immunogenicity should be investigated in a target population since animal testing and in-vitro models cannot precisely predict immune response in humans.
Antigenic immunogenic potency.
Many lipids and nucleic acids are relatively small molecules and/or have non-immunogenic properties. Consequently, they may require conjugation with an epitope such as a protein or polysaccharide to increase immunogenic potency so that they can evoke an immune response.
Antigen characteristics.
Immunogenicity is influenced by multiple characteristics of an antigen:
T cell epitopes.
T cell epitope content is one of the factors that contributes to antigenicity. Likewise, T Cell epitopes can cause unwanted immunogenicity, including the development of ADAs. A key determinant in T cell epitope immunogenicity is the binding strength of T cell epitopes to major histocompatibility complexes (MHC or HLA) molecules. Epitopes with higher binding affinities are more likely to be displayed on the surface of a cell. Because a T cell's T cell receptor recognizes a specific epitope, only certain T cells are able to respond to a certain peptide bound to MHC on a cell surface.
When protein drug therapeutics, (as in enzymes, monoclonals, replacement proteins) or vaccines are administrated, antigen presenting cells (APCs), such as a B cell or Dendritic Cell, will present these substances as peptides, which T cells may recognize. This may result in unwanted immunogenicity, including ADAs and autoimmmune diseases, such as autoimmune thrombocytopenia (ITP) following exposure to recombinant thrombopoietin and pure red cell aplasia, which was associated with a particular formulation of erythropoietin (Eprex).
Monoclonal antibodies.
Therapeutic monoclonal antibodies (mAbs) are used for several diseases, including cancer and Rheumatoid arthritis. Consequently, the high immunogenicity limited efficacy and was associated with severe infusion reactions. Although the exact mechanism is unclear, it is suspected that the mAbs are inducing infusion reactions by eliciting antibody antigen interactions, such as increased formation of immunoglobulin E (IgE) antibodies, which may bind onto mast cells and subsequent degranulation, causing allergy-like symptoms as well as the release of additional cytokines.
Several innovations in genetic engineering has resulted in the decrease in immunogenicity, (also known as deimmunization), of mAbs. Genetic engineering has led to the generation of humanized and chimeric antibodies, by exchanging the murine constant and complementary regions of the immunoglobulin chains with the human counterparts. Although this has reduced the sometimes extreme immunogenicity associated with murine mAbs, the anticipation that all fully human mAbs would have not possess unwanted immunogenic properties remains unfulfilled.
Evaluation methods.
In silico screening.
T cell epitope content, which is one of the factors that contributes to the risk of immunogenicity can now be measured relatively accurately using in silico tools. Immunoinformatics algorithms for identifying T-cell epitopes are now being applied to triage protein therapeutics into higher risk and low risk categories. These categories refer to assessing and analyzing whether an immunotherapy or vaccine will cause unwanted immunogenicity.
One approach is to parse protein sequences into overlapping nonamer (that is, 9 amino acid) peptide frames, each of which is then evaluated for binding potential to each of six common class I HLA alleles that “cover” the genetic backgrounds of most humans worldwide. By calculating the density of high-scoring frames within a protein, it is possible to estimate a protein's overall “immunogenicity score”. In addition, sub-regions of densely packed high scoring frames or “clusters” of potential immunogenicity can be identified, and cluster scores can be calculated and compiled.
Using this approach, the clinical immunogenicity of a novel protein therapeutics can be calculated. Consequently, a number of biotech companies have integrated in silico immunogenicity into their pre-clinical process as they develop new protein drugs.