Constitutively active TrkB confers an aggressive transformed phenotype to a neural crest-derived cell line.

Neuroblastoma arises from sympathoadrenal progenitors of the neural crest and expression of the neurotrophin receptor TrkB and its ligand, brain-derived neurotrophic factor (BDNF), is correlated with poor prognosis. Although activated TrkB signaling promotes a more aggressive phenotype in established neuroblastoma cell lines, whether TrkB signaling is sufficient to transform neural crest-derived cells has not been investigated. To address the role of TrkB signaling in malignant transformation, we removed two immunoglobulin-like domains from the extracellular domain of the full-length rat TrkB receptor to create a ΔIgTrkB that is constitutively active. In the pheochromocytoma-derived cell line PC12, ΔIgTrkB promotes differentiation by stimulating process outgrowth; however, in the rat neural crest-derived cell line NCM-1, ΔIgTrkB signaling produces a markedly transformed phenotype characterized by increased proliferation, anchorage-independent cell growth, anoikis resistance and matrix invasion. Furthermore, expression of ΔIgTrkB leads to the upregulation of many transcripts encoding cancer-associated genes including cyclind1, twist1 and hgf, as well as downregulation of tumor suppressors such as pten and rb1. In addition, ΔIgTrkB NCM-1 cells show a 21-fold increase in mRNA for MYCN, the most common genetic marker for a poor prognosis in neuroblastoma. When injected into NOD SCID mice, control GFP NCM-1 cells fail to grow whereas ΔIgTrkB NCM-1 cells form rapidly growing and invasive tumors necessitating euthanasia of all mice by 15 days post injection. In summary, these results indicate that activated TrkB signaling is sufficient to promote the formation of a highly malignant phenotype in neural crest-derived cells.

Gene expression profile in pelvic organ prolapse.

It was hypothesized that the processes contributing to pelvic organ prolapse (POP) may be identified by transcriptional profiling of pelvic connective tissue in conjunction with light microscopy. In order to test this, we performed a frequency-matched case-control study of women undergoing hysterectomy for POP and controls. Total RNA, extracted from uterosacral and round ligament samples used to generate labeled cRNA, was hybridized to microarrays and analyzed for the expression of 32 878 genes. Significance Analysis of Microarrays (Stanford University, CA, USA) identified differentially expressed genes used for ontoanalysis. Quantitative PCR (qPCR) confirmed results. Light microscopy confirmed the tissue type and assessed inflammatory infiltration. The analysis of 34 arrays revealed 249 differentially expressed genes with fold changes (FC) larger than 1.5 and false discovery rates < or =5.2%. Immunity and defense was the most significant biological process differentially expressed in POP. qPCR confirmed the elevated steady-state mRNA levels for four genes: interleukin-6 (FC 9.8), thrombospondin 1 (FC 3.5) and prostaglandin-endoperoxide synthase 2 (FC 2.4) and activating transcription factor 3 (FC 2.6). Light microscopy showed all the samples were composed of fibromuscular connective tissue with no inflammatory infiltrates. In conclusion, genes enriched for 'immunity and defense' contribute to POP independent of inflammatory infiltrates.

A quantitative evaluation of SAGE.

Serial Analysis of Gene Expression (SAGE) is an innovative technique that offers the potential of cataloging both the identity and relative frequencies of mRNA transcripts in a given poly(A(+)) RNA preparation. Although it is a very effective approach for determining the expression of mRNA populations, there are significant biases in the observed results that are inherent in the experimental process. These are caused by sampling error, sequencing error, nonuniqueness, and nonrandomness of tag sequences. The quantitative information desired from SAGE experiments consists of estimates of the number of genes and the frequency distribution of transcript copy numbers. Of additional concern is the extent to which a given tag sequence can be assumed to be unique to its gene. The present study takes these mathematical biases into account and presents a basis for maximum likelihood estimation of gene number and transcript copy frequencies given a set of experimental results. These estimates of the true state of genomic expression are markedly different from those based directly on the observations from the underlying experiments. It also is shown that while in many cases it is probable that a given tag sequence is unique within the genome, in larger genomes this cannot be safely assumed.