Gene expression profile analysis of primary glioblastomas and non-neoplastic brain tissue: identification of potential target genes by oligonucleotide microarray and real-time quantitative PCR

The prognosis of glioblastomas is still extremely poor and the discovery of novel molecular therapeutic targets can be important to optimize treatment strategies. Gene expression analyses comparing normal and neoplastic tissues have been used to identify genes associated with tumorigenesis and potential therapeutic targets. We have used this approach to identify differentially expressed genes between primary glioblastomas and non-neoplastic brain tissues. We selected 20 overexpressed genes related to cell cycle, cellular movement and growth, proliferation and cell-to-cell signaling and analyzed their expression levels by real time quantitative PCR in cDNA obtained from microdissected fresh tumor tissue from 20 patients with primary glioblastomas and from 10 samples of non-neoplastic white matter tissue. The gene expression levels were significantly higher in glioblastomas than in non-neoplastic white matter in 18 out of 20 genes analyzed: P < 0.00001 for CDKN2C, CKS2, EEF1A1, EMP3, PDPN, BNIP2, CA12, CD34, CDC42EP4, PPIE, SNAI2, GDF15 and MMP23b; and NFIA (P: 0.0001), GPS1 (P: 0.0003), LAMA1 (P: 0.002), STIM1 (P: 0.006), and TASP1 (P: 0.01). Five of these genes are located in contiguous loci at 1p31-36 and 2 at 17q24-25 and 8 of them encode surface membrane proteins. PDPN and CD34 protein expression were evaluated by immunohistochemistry and they showed concordance with the PCR results. The present results indicate the presence of 18 overexpressed genes in human primary glioblastomas that may play a significant role in the pathogenesis of these tumors and that deserve further functional investigation as attractive candidates for new therapeutic targets.

Genomic deletions at 1p and 14q are associated with an abnormal cDNA microarray gene expression pattern in meningiomas but not in schwannomas

The molecular pathology of meningiomas and shwannomas involve the inactivation of the NF2 gene to generate grade I tumors. Genomic losses at 1p and 14q are observed in both neoplasms, although more frequently in meningiomas. The inactivation of unidentified genes located in these regions appears associated with tumor progression in meningiomas, but no clues to its molecular/clinical meaning are available in schwannomas. Recent microarray gene expression studies have demonstrated the existence of molecular subgroups in both entities. In the present study, we correlated the presence of genomic deletions at 1p, 14q, and 22q with the expression patterns of 96 tumor-related genes obtained by cDNA low-density microarrays in a series of 65 tumors including 42 meningiomas and 23 schwannomas. Two expression pattern groups were identified by cDNA mycroarray analysis when compared to the expression pattern in normal control RNA in both meningiomas and schwannomas, each one with patterns similar and different from the normal control. Meningioma and schwannoma subgroups differed in the expression of 38 and 16 genes, respectively. Using MLPA and microsatellites, we identified genomic losses at 1p, 14q, and 22q at nonrandom frequencies (12.5-69%) in meningiomas and schwannomas. Losses at 22q were almost equally frequent in both molecular expression subgroups in both neoplasms. However, deletions at 1p and 14q accumulated in meningiomas with a gene expression pattern different from the normal pattern, whereas the inverse situation occurred in schwannomas. Those anomalies characterized the schwannomas with expression pattern similar to the normal control. These findings suggest that deletions at 1p and 14q enhance the development of an abnormal tumor-related gene expression pattern in meningiomas, but this fact is not corroborated in schwannomas. (C) 2010 Elsevier Inc. All rights reserved.

The new craft skills of engineering: The impact of innovation technology on engineering practices

This chapter explores the impact of innovation technologies such as simulation, modelling, and rapid prototyping on engineering practice. Innovation technologies help redefine the role of engineers in the innovation process, creating a new division of innovative labour both with and across organizations. This chapter also explores the boundaries of experimentation and inertia within particular domains of problem-solving to create new opportunities and value.