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Patient-Derived Xenograft Models to Improve Targeted Therapy in Epithelial Ovarian Cancer Treatment

Overview of attention for article published in Frontiers in oncology, January 2013
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Title
Patient-Derived Xenograft Models to Improve Targeted Therapy in Epithelial Ovarian Cancer Treatment
Published in
Frontiers in oncology, January 2013
DOI 10.3389/fonc.2013.00295
Pubmed ID
Authors

Clare L. Scott, Marc A. Becker, Paul Haluska, Goli Samimi

Abstract

Despite increasing evidence that precision therapy targeted to the molecular drivers of a cancer has the potential to improve clinical outcomes, high-grade epithelial ovarian cancer (OC) patients are currently treated without consideration of molecular phenotype, and predictive biomarkers that could better inform treatment remain unknown. Delivery of precision therapy requires improved integration of laboratory-based models and cutting-edge clinical research, with pre-clinical models predicting patient subsets that will benefit from a particular targeted therapeutic. Patient-derived xenografts (PDXs) are renewable tumor models engrafted in mice, generated from fresh human tumors without prior in vitro exposure. PDX models allow an invaluable assessment of tumor evolution and adaptive response to therapy. PDX models have been applied to pre-clinical drug testing and biomarker identification in a number of cancers including ovarian, pancreatic, breast, and prostate cancers. These models have been shown to be biologically stable and accurately reflect the patient tumor with regards to histopathology, gene expression, genetic mutations, and therapeutic response. However, pre-clinical analyses of molecularly annotated PDX models derived from high-grade serous ovarian cancer (HG-SOC) remain limited. In vivo response to conventional and/or targeted therapeutics has only been described for very small numbers of individual HG-SOC PDX in conjunction with sparse molecular annotation and patient outcome data. Recently, two consecutive panels of epithelial OC PDX correlate in vivo platinum response with molecular aberrations and source patient clinical outcomes. These studies underpin the value of PDX models to better direct chemotherapy and predict response to targeted therapy. Tumor heterogeneity, before and following treatment, as well as the importance of multiple molecular aberrations per individual tumor underscore some of the important issues addressed in PDX models.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 110 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
Netherlands 1 <1%
Australia 1 <1%
Unknown 106 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 29 26%
Researcher 23 21%
Student > Master 15 14%
Student > Bachelor 7 6%
Other 5 5%
Other 13 12%
Unknown 18 16%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 24 22%
Agricultural and Biological Sciences 22 20%
Medicine and Dentistry 21 19%
Pharmacology, Toxicology and Pharmaceutical Science 7 6%
Chemistry 4 4%
Other 9 8%
Unknown 23 21%
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 04 December 2013.
All research outputs
#22,759,802
of 25,374,917 outputs
Outputs from Frontiers in oncology
#15,918
of 22,416 outputs
Outputs of similar age
#258,420
of 289,004 outputs
Outputs of similar age from Frontiers in oncology
#194
of 328 outputs
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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 328 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.