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Characterization of patient-derived tumor xenograft models of endometrial cancer for preclinical evaluation of targeted therapies

Overview of attention for article published in Gynecologic Oncology, July 2015
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Title
Characterization of patient-derived tumor xenograft models of endometrial cancer for preclinical evaluation of targeted therapies
Published in
Gynecologic Oncology, July 2015
DOI 10.1016/j.ygyno.2015.07.104
Pubmed ID
Authors

Jeroen Depreeuw, Els Hermans, Stefanie Schrauwen, Daniela Annibali, Lieve Coenegrachts, Debby Thomas, Mathieu Luyckx, Ilse Gutierrez-Roelens, David Debruyne, Katrien Konings, Philippe Moerman, Ignace Vergote, Diether Lambrechts, Frédéric Amant

Abstract

Endometrial carcinoma (EC) is the sixth most common cancer in women and therapies are limited for advanced and recurrent disease. Patient-derived tumor xenograft (PDTX) models are becoming popular tools in translational research because of their histological and genetic similarity to the original tumors and the ability to predict therapeutic response to treatments. Here, we established and characterized a panel of 24 EC PDTX models which includes the major histological and genetic subtypes observed in patients. Fresh tumor tissues collected from primary, metastatic and recurrent type I and type II EC patients were engrafted in immunocompromised mice. Histology, vimentin, and cytokeratin expression were evaluated, together with Microsatellite instability (MSI), mutation profiling by Whole Exome Sequencing and copy number profiling by Whole Genome Low Coverage Sequencing. The efficacy of both PI3K and MEK inhibitors was evaluated in a model of endometrioid carcinoma harboring PTEN, PIK3CA and KRAS mutations. We observed good similarity between primary tumors and the corresponding xenografts, at histological and genetic level. Among the engrafted endometrioid models, we found a significant enrichment of MSI and POLE mutated tumors, compared to non-engrafted samples. Combination treatment with NVP-BEZ235 and AZD6244 showed the possibility to stabilize the tumor growth in one model originated from a patient who already received several lines of chemotherapy. The established EC PDTX models, resembling the original human tumors, promise to be useful for preclinical evaluation of novel combination and targeted therapies in specific EC subgroups.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 53 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 26%
Student > Master 11 21%
Researcher 6 11%
Other 5 9%
Student > Postgraduate 3 6%
Other 10 19%
Unknown 4 8%
Readers by discipline Count As %
Medicine and Dentistry 16 30%
Biochemistry, Genetics and Molecular Biology 10 19%
Agricultural and Biological Sciences 10 19%
Unspecified 1 2%
Computer Science 1 2%
Other 6 11%
Unknown 9 17%
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 02 August 2015.
All research outputs
#22,760,732
of 25,377,790 outputs
Outputs from Gynecologic Oncology
#4,570
of 4,957 outputs
Outputs of similar age
#235,376
of 275,428 outputs
Outputs of similar age from Gynecologic Oncology
#45
of 48 outputs
Altmetric has tracked 25,377,790 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 4,957 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one is in the 1st percentile – i.e., 1% 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 275,428 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 48 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.