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Modeling Cytomegalovirus Infection in Mouse Tumor Models

Overview of attention for article published in Frontiers in oncology, March 2015
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Title
Modeling Cytomegalovirus Infection in Mouse Tumor Models
Published in
Frontiers in oncology, March 2015
DOI 10.3389/fonc.2015.00061
Pubmed ID
Authors

Richard Lee Price, Ennio Antonio Chiocca

Abstract

The hypothesis that cytomegalovirus (CMV) modulates cancer is evolving. Originally discovered in glioblastoma in 2002, the number of cancers, where intratumoral CMV antigen is detected, has increased in recent years suggesting that CMV actively affects the pathobiology of certain tumors. These findings are controversial as several groups have also reported inability to replicate these results. Regardless, several clinical trials for glioblastoma are underway or have been completed that target intratumoral CMV with anti-viral drugs or immunotherapy. Therefore, a better understanding of the possible pathobiology of CMV in cancer needs to be ascertained. We have developed genetic, syngeneic, and orthotopic malignant glioma mouse models to study the role of CMV in cancer development and progression. These models recapitulate for the most part intratumoral CMV expression as seen in human tumors. Additionally, we discovered that CMV infection in Trp53(-/+) mice promotes pleomorphic rhabdomyosarcomas. These mouse models are not only a vehicle for studying pathobiology of the viral-tumor interaction but also a platform for developing and testing cancer therapeutics.

X Demographics

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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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Czechia 1 4%
Unknown 26 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 33%
Student > Master 5 19%
Researcher 4 15%
Student > Bachelor 3 11%
Student > Doctoral Student 1 4%
Other 1 4%
Unknown 4 15%
Readers by discipline Count As %
Medicine and Dentistry 7 26%
Agricultural and Biological Sciences 6 22%
Pharmacology, Toxicology and Pharmaceutical Science 4 15%
Biochemistry, Genetics and Molecular Biology 2 7%
Immunology and Microbiology 2 7%
Other 3 11%
Unknown 3 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 17 March 2015.
All research outputs
#22,759,452
of 25,374,647 outputs
Outputs from Frontiers in oncology
#15,918
of 22,416 outputs
Outputs of similar age
#251,249
of 291,961 outputs
Outputs of similar age from Frontiers in oncology
#69
of 90 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 22,416 research outputs from this source. They receive a mean Attention Score of 3.0. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 90 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.