alexa Prediction of high risk Ewing's sarcoma by gene expression profiling.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Proteomics & Bioinformatics

Author(s): Ohali A, Avigad S, Zaizov R, Ophir R, HornSaban S,

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Abstract Ewing's sarcoma (ES) is the second most common primary malignant bone tumor in children and adolescents. Currently accepted clinical prognostic factors fail to classify ES patients' risk to relapse at diagnosis. We aimed to find a new strategy to distinguish between poor and good prognosis ES patients already at diagnosis. We analysed the gene expression profiles of 14 primary tumor specimens and six metastases from ES patients, using oligonucleotide microarray analysis. The over-expression of two genes was validated by quantitative PCR using the LightCycler system. We identified two distinct gene expression signatures distinguishing high-risk ES patients that are likely to progress from low-risk ES patients with a favorable prognosis of long-term progression-free survival. The microarray-based classification was superior to currently used prognostic parameters. Over-expressed genes in the poor prognosis patients included genes regulating the cell cycle and genes associated with invasion and metastasis, while among the downregulated genes were tumor suppressor genes and inducers of apoptosis. Our results indicate the existence of a specific gene expression signature of outcome in ES already at diagnosis, and provide a strategy to select patients who would benefit from risk-adapted improved therapy. This article was published in Oncogene and referenced in Journal of Proteomics & Bioinformatics

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