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Expression profiling and characterization of 4200 genes cloned from primary neuroblastomas: identification of 305 genes differentially expressed between favorable and unfavorable subsets. | LitMetric

AI Article Synopsis

  • - Neuroblastoma (NBL) presents differently in children under and over 1 year old, with younger patients often experiencing tumor regression while older patients face aggressive growth and higher mortality.
  • - A study was conducted to analyze gene expression profiles in NBL by creating cDNA libraries from primary tumors classified as favorable (F) or unfavorable (UF), leading to the identification of over 4,200 sequenced cDNAs, with a significant percentage being genes of unknown functions.
  • - The research revealed that 278 genes were highly expressed in the F subset, mainly linked to neural development and differentiation, while only 27 genes had higher expression in the UF subset, which may influence neuronal growth, highlighting key differences in gene expression

Article Abstract

Neuroblastoma (NBL), one of the most common childhood solid tumors, has a distinct nature in different prognostic subgroups: NBL in patients under 1 year of age usually regresses spontaneously, whereas that in patients over 1 year of age often grows aggressively and eventually kills the patient. To understand the molecular mechanism of biology and tumorigenesis of NBL, we decided to perform a comprehensive approach to unveil the gene expression profiles among the NBL subsets. We constructed the subset-specific oligo-capping cDNA libraries from the primary NBL tissues with favorable (F: stage 1, high expression of TrkA and a single copy of MYCN) and unfavorable (UF: stage 3 or 4, decreased expression of TrkA and MYCN amplification) characteristics and randomly cloned 4654 cDNAs. Among 4243 cDNAs sequenced successfully, 1799 (42.4%) were the genes with unknown function. Excluding the housekeeping genes, an expression profile of each subset was extremely different. To determine the genes expressed differentially between F and UF subsets, we performed semiquantitative reverse transcriptase (RT)-PCR for each of the 1842 independent genes using RNA obtained from 16 F and 16 UF NBLs as template. This revealed that 278 genes were highly expressed in the F subset as compared to the UF one, while, surprisingly, only 27 genes were expressed at higher levels in the UF rather than the F subset. These differentially expressed genes included 194 genes with unknown function. Many of the genes expressed at high levels in the F subset were related to catecholamine biosynthesis, small GTPases, synapse formation, synaptic vesicle transport, and transcription factors regulating differentiation of the neural crest-derived cells. On the other hand, the genes expressed at high levels in the UF subset included transcription factors and/or receptors that might regulate neuronal growth and differentiation. The chromosomal mapping of those genes showed some clusters. Thus, our mass-identification and characterization of the differentially expressed genes between the subsets may become a powerful tool for finding the important genes of NBL as well as developing new diagnostic and therapeutic strategies against aggressive NBL.

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Source
http://dx.doi.org/10.1038/sj.onc.1206853DOI Listing

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