mRNA expression profiles of primary high-grade central osteosarcoma are preserved in cell lines and xenografts View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2011-12

AUTHORS

Marieke L Kuijjer, Heidi M Namløs, Esther I Hauben, Isidro Machado, Stine H Kresse, Massimo Serra, Antonio Llombart-Bosch, Pancras CW Hogendoorn, Leonardo A Meza-Zepeda, Ola Myklebost, Anne-Marie Cleton-Jansen

ABSTRACT

BACKGROUND: Conventional high-grade osteosarcoma is a primary malignant bone tumor, which is most prevalent in adolescence. Survival rates of osteosarcoma patients have not improved significantly in the last 25 years. Aiming to increase this survival rate, a variety of model systems are used to study osteosarcomagenesis and to test new therapeutic agents. Such model systems are typically generated from an osteosarcoma primary tumor, but undergo many changes due to culturing or interactions with a different host species, which may result in differences in gene expression between primary tumor cells, and tumor cells from the model system. We aimed to investigate whether gene expression profiles of osteosarcoma cell lines and xenografts are still comparable to those of the primary tumor. METHODS: We performed genome-wide mRNA expression profiling on osteosarcoma biopsies (n = 76), cell lines (n = 13), and xenografts (n = 18). Osteosarcoma can be subdivided into several histological subtypes, of which osteoblastic, chondroblastic, and fibroblastic osteosarcoma are the most frequent ones. Using nearest shrunken centroids classification, we generated an expression signature that can predict the histological subtype of osteosarcoma biopsies. RESULTS: The expression signature, which consisted of 24 probes encoding for 22 genes, predicted the histological subtype of osteosarcoma biopsies with a misclassification error of 15%. Histological subtypes of the two osteosarcoma model systems, i.e. osteosarcoma cell lines and xenografts, were predicted with similar misclassification error rates (15% and 11%, respectively). CONCLUSIONS: Based on the preservation of mRNA expression profiles that are characteristic for the histological subtype we propose that these model systems are representative for the primary tumor from which they are derived. More... »

PAGES

66

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/1755-8794-4-66

DOI

http://dx.doi.org/10.1186/1755-8794-4-66

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1035547780

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/21933437


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/1755-8794-4-66'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/1755-8794-4-66'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/1755-8794-4-66'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/1755-8794-4-66'


 

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