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  • Title: Identification of low intratumoral gene expression heterogeneity in neuroblastic tumors by genome-wide expression analysis and game theory.
    Author: Albino D, Scaruffi P, Moretti S, Coco S, Truini M, Di Cristofano C, Cavazzana A, Stigliani S, Bonassi S, Tonini GP.
    Journal: Cancer; 2008 Sep 15; 113(6):1412-22. PubMed ID: 18671248.
    Abstract:
    BACKGROUND: Neuroblastic tumors (NTs) are largely comprised of neuroblastic (Nb) cells with various quantities of Schwannian stromal (SS) cells. NTs show a variable genetic heterogeneity. NT gene expression profiles reported so far have not taken into account the cellular components. The authors reported the genome-wide expression analysis of whole tumors and microdissected Nb and SS cells. METHODS: The authors analyzed gene expression profiles of 10 stroma-poor NTs (NTs-SP) and 9 stroma-rich NTs (NTs-SR) by microarray technology. Nb and SS cells were isolated by laser microdissection from NTs-SP and NTs-SR and probed with microarrays. Gene expression data were analyzed by the Significance Analysis of Microarrays (SAM) and Game Theory (GT) methods, the latter applied for the first time to microarray data evaluation. RESULTS: SAM identified 84 genes differentially expressed between NTs-SP and NTs-SR, whereas 50 were found by GT. NTs-SP mainly express genes associated with cell replication, nervous system development, and antiapoptotic pathways, whereas NTs-SR express genes of cell-cell communication and apoptosis. Combining SAM and GT, the authors found 16 common genes driving the separation between NTs-SP and NTs-SR. Five genes overexpressed in NTs-SP encode for nuclear proteins (CENPF, EYA1, PBK, TOP2A, TFAP2B), whereas only 1 of 11 highly expressed genes in NTs-SR encodes for a nuclear receptor (NR4A2). CONCLUSIONS: The results showed that NT-SP and NT-SR gene signatures differ for a set of genes involved in distinct pathways, and the authors demonstrated a low intratumoral heterogeneity at the mRNA level in both NTs-SP and NTs-SR. The combination of SAM and GT methods may help to better identify gene expression profiling in NTs.
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