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Canine cancer immunotherapy studies: linking mouse and human

Overview of attention for article published in Journal for Immunotherapy of Cancer, December 2016
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Title
Canine cancer immunotherapy studies: linking mouse and human
Published in
Journal for Immunotherapy of Cancer, December 2016
DOI 10.1186/s40425-016-0200-7
Pubmed ID
Authors

Jiwon S. Park, Sita S. Withers, Jaime F. Modiano, Michael S. Kent, Mingyi Chen, Jesus I. Luna, William T. N. Culp, Ellen E. Sparger, Robert B. Rebhun, Arta M. Monjazeb, William J. Murphy, Robert J. Canter

Abstract

Despite recent major clinical breakthroughs in human cancer immunotherapy including the use of checkpoint inhibitors and engineered T cells, important challenges remain, including determining the sub-populations of patients who will respond and who will experience at times significant toxicities. Although advances in cancer immunotherapy depend on preclinical testing, the majority of in-vivo testing currently relies on genetically identical inbred mouse models which, while offering critical insights regarding efficacy and mechanism of action, also vastly underrepresent the heterogeneity and complex interplay of human immune cells and cancers. Additionally, laboratory mice uncommonly develop spontaneous tumors, are housed under specific-pathogen free conditions which markedly impacts immune development, and incompletely model key aspects of the tumor/immune microenvironment. The canine model represents a powerful tool in cancer immunotherapy research as an important link between murine models and human clinical studies. Dogs represent an attractive outbred combination of companion animals that experience spontaneous cancer development in the setting of an intact immune system. This allows for study of complex immune interactions during the course of treatment while also directly addressing long-term efficacy and toxicity of cancer immunotherapies. However, immune dissection requires access to robust and validated immune assays and reagents as well as appropriate numbers for statistical evaluation. Canine studies will need further optimization of these important mechanistic tools for this model to fulfill its promise as a model for immunotherapy. This review aims to discuss the canine model in the context of existing preclinical cancer immunotherapy models to evaluate both its advantages and limitations, as well as highlighting its growth as a powerful tool in the burgeoning field of both human and veterinary immunotherapy.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 150 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 150 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 15%
Student > Master 21 14%
Researcher 20 13%
Student > Bachelor 18 12%
Student > Doctoral Student 10 7%
Other 28 19%
Unknown 31 21%
Readers by discipline Count As %
Veterinary Science and Veterinary Medicine 36 24%
Medicine and Dentistry 16 11%
Biochemistry, Genetics and Molecular Biology 15 10%
Agricultural and Biological Sciences 12 8%
Immunology and Microbiology 9 6%
Other 25 17%
Unknown 37 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 07 January 2017.
All research outputs
#14,783,193
of 25,371,288 outputs
Outputs from Journal for Immunotherapy of Cancer
#2,394
of 3,421 outputs
Outputs of similar age
#219,026
of 422,884 outputs
Outputs of similar age from Journal for Immunotherapy of Cancer
#26
of 31 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,421 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.4. This one is in the 29th percentile – i.e., 29% of its peers scored the same or lower than it.
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 422,884 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.