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Oncopig Soft-Tissue Sarcomas Recapitulate Key Transcriptional Features of Human Sarcomas

Overview of attention for article published in Scientific Reports, June 2017
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Title
Oncopig Soft-Tissue Sarcomas Recapitulate Key Transcriptional Features of Human Sarcomas
Published in
Scientific Reports, June 2017
DOI 10.1038/s41598-017-02912-9
Pubmed ID
Authors

Kyle M. Schachtschneider, Yingkai Liu, Suvi Mäkeläinen, Ole Madsen, Laurie A. Rund, Martien A. M. Groenen, Lawrence B. Schook

Abstract

Human soft-tissue sarcomas (STS) are rare mesenchymal tumors with a 5-year survival rate of 50%, highlighting the need for further STS research. Research has been hampered by limited human sarcoma cell line availability and the large number of STS subtypes, making development of STS cell lines and animal models representative of the diverse human STS subtypes critical. Pigs represent ideal human disease models due to their similar size, anatomy, metabolism, and genetics compared to humans. The Oncopig encodes inducible KRAS (G12D) and TP53 (R167H) transgenes, allowing for STS modeling in a spatial and temporal manner. This study utilized Oncopig STS cell line (fibroblast) and tumor (leiomyosarcoma) RNA-seq data to compare Oncopig and human STS expression profiles. Altered expression of 3,360 and 7,652 genes was identified in Oncopig STS cell lines and leiomyosarcomas, respectively. Transcriptional hallmarks of human STS were observed in Oncopig STS, including altered TP53 signaling, Wnt signaling activation, and evidence of epigenetic reprogramming. Furthermore, master regulators of Oncopig STS expression were identified, including FOSL1, which was previously identified as a potential human STS therapeutic target. These results demonstrate the Oncopig STS model's ability to mimic human STS transcriptional profiles, providing a valuable resource for sarcoma research and cell line development.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Other 4 15%
Student > Master 4 15%
Student > Bachelor 4 15%
Professor 3 12%
Student > Ph. D. Student 2 8%
Other 3 12%
Unknown 6 23%
Readers by discipline Count As %
Agricultural and Biological Sciences 5 19%
Biochemistry, Genetics and Molecular Biology 4 15%
Medicine and Dentistry 4 15%
Decision Sciences 1 4%
Engineering 1 4%
Other 0 0%
Unknown 11 42%

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 03 June 2017.
All research outputs
#8,994,588
of 11,251,036 outputs
Outputs from Scientific Reports
#34,400
of 48,027 outputs
Outputs of similar age
#191,364
of 266,618 outputs
Outputs of similar age from Scientific Reports
#2,141
of 3,016 outputs
Altmetric has tracked 11,251,036 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
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We're also able to compare this research output to 3,016 others from the same source and published within six weeks on either side of this one. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.