Differential Gene Expression in Pediatric Embrionary Advanced Rhabdomyosarcomas. O. Perez-Gonzalez1, A. Hidalgo-Miranda1, I. Silva-Zolezzi1, R.M. Rivera-Luna2, G. Jimenez-Sanchez1. 1) National Institute of Genomic Medicine, Mexico; 2) National Institute of Pediatrics, Mexico.
Rabdomyosarcoma (RMS) is the most frequent soft tissue malignant tumors and accounts for ~6% of all neoplasias in chilhood. The overall survival rate has significantly improved with the current therapy. The allocation of the neoadyuvant antineoplasic treatment is based on the Intergroup Rhabdomyosarcoma Study (IRS) classification system. However, therapeutic response is still inconsistent even in patients under similar classification. Thus, a classification system for a more individualized allocation of the antineoplasic treatment would result in significant benefit to patients with this disease. To explore the existence of a differential gene expression in patients with identical histopathological diagnosis and different responses to neoadjuvant antineoplastic treatment, we analyzed total RNA of nine RMS from pediatric patients from 9 to 12 years old with advanced stages using Affymetrix U133 Plus 2.0 gene expression arrays. Histopatological samples were obtained before administration of neoadyuvant treatment based on the IRS staging system, after which all patients were re-evaluated to classify response rate into good, intermediate or poor, using the same system. We obtained a probe-calling rate of 35-54% and are performing a supervised cluster analysis to find gene expression profiles associated to specific response rates. Results will be confirmed by independent expression analysis methods and the number of samples is continuously increasing. We are currently performing hierarchical clustering analysis using MacOS_Mev_3_1, version 10.2. Differential gene expression profiles in RMS are being analyzed as a mean to provide a more accurate system to allocate neoadyuvant antineoplasic treatment in patients with this disease. In addition, this will allow considering new therapies for those patients with expression profiles consistent with poor response rates.