| Title |
IgG Fc engineering to modulate antibody effector functions
|
|---|---|
| Published in |
Protein & Cell, October 2017
|
| DOI | 10.1007/s13238-017-0473-8 |
| Pubmed ID | |
| Authors |
Xinhua Wang, Mary Mathieu, Randall J Brezski |
| Abstract |
Therapeutic monoclonal antibodies are among the most effective biotherapeutics to date. An important aspect of antibodies is their ability to bind antigen while at the same time recruit immune effector functions. The majority of approved recombinant monoclonal antibody therapies are of the human IgG1 subclass, which can engage both humoral and cellular components of the immune system. The wealth of information generated about antibodies has afforded investigators the ability to molecularly engineer antibodies to modulate effector functions. Here, we review various antibody engineering efforts intended to improve efficacy and safety relative to the human IgG isotype. Further, we will discuss proposed mechanisms by which engineering approaches led to modified interactions with immune components and provide examples of clinical studies using next generation antibodies. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 564 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 564 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 131 | 23% |
| Student > Ph. D. Student | 93 | 16% |
| Student > Master | 47 | 8% |
| Other | 36 | 6% |
| Student > Bachelor | 34 | 6% |
| Other | 50 | 9% |
| Unknown | 173 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 125 | 22% |
| Agricultural and Biological Sciences | 85 | 15% |
| Immunology and Microbiology | 66 | 12% |
| Pharmacology, Toxicology and Pharmaceutical Science | 26 | 5% |
| Medicine and Dentistry | 23 | 4% |
| Other | 53 | 9% |
| Unknown | 186 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 28. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 March 2024.
All research outputs
#1,410,787
of 25,837,817 outputs
Outputs from Protein & Cell
#49
of 827 outputs
Outputs of similar age
#28,067
of 334,388 outputs
Outputs of similar age from Protein & Cell
#4
of 16 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 827 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.8. This one has done particularly well, scoring higher than 93% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 334,388 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.