Unexpected sensitivity of sst2 antagonists to N-terminal radiometal modifications

Chelated somatostatin agonists have been shown to be sensitive to N-terminal radiometal modifications, with Ga-DOTA agonists having significantly higher binding affinity than their Lu-, In-, and Y-DOTA correlates. Recently, somatostatin antagonists have been successfully developed as alternative tracers to agonists. The aim of this study was to evaluate whether chelated somatostatin antagonists are also sensitive to radiometal modifications and how. We have synthesized 3 different somatostatin antagonists, DOTA-p-NO(2)-Phe-c[D-Cys-Tyr-D-Aph(Cbm)-Lys-Thr-Cys]-D-Tyr-NH(2), DOTA-Cpa-c[D-Cys-Aph(Hor)-D-Aph(Cbm)-Lys-Thr-Cys]-D-Tyr-NH(2) (DOTA-JR11), and DOTA-p-Cl-Phe-c[D-Cys-Tyr-D-Aph(Cbm)-Lys-Thr-Cys]-D-Tyr-NH(2), and added various radiometals including In(III), Y(III), Lu(III), Cu(II), and Ga(III). We also replaced DOTA with 1,4,7-triazacyclononane,1-glutaric acid-4,7-acetic acid (NODAGA) and added Ga(III). The binding affinity of somatostatin receptors 1 through 5 was evaluated in all cases. In all 3 resulting antagonists, the Ga-DOTA analogs were the lowest-affinity radioligands, with a somatostatin receptor 2 binding affinity up to 60 times lower than the respective Y-DOTA, Lu-DOTA, or In-DOTA compounds. Interestingly, however, substitution of DOTA by the NODAGA chelator was able to increase massively its binding affinity in contrast to the Ga-DOTA analog. The 3 NODAGA analogs are antagonists in functional tests. In vivo biodistribution studies comparing (68)Ga-DOTATATE agonist with (68)Ga-DOTA-JR11 and (68)Ga-NODAGA-JR11 showed not only that the JR11 antagonist radioligands were superior to the agonist ligands but also that (68)Ga-NODAGA-JR11 was the tracer of choice and preferable to (68)Ga-DOTA-JR11 in transplantable HEK293-hsst(2) tumors in mice. One may therefore generalize that somatostatin receptor 2 antagonists are sensitive to radiometal modifications and may preferably be coupled with a (68)Ga-NODAGA chelator-radiometal complex.

RNA interference screening identifies a novel role for autocrine fibroblast growth factor signaling in neuroblastoma chemoresistance

Chemotherapeutic drug resistance is one of the major causes for treatment failure in high-risk neuroblastoma (NB), the most common extra cranial solid tumor in children. Poor prognosis is typically associated with MYCN amplification. Here, we utilized a loss-of-function kinome-wide RNA interference screen to identify genes that cause cisplatin sensitization. We identified fibroblast growth factor receptor 2 (FGFR2) as an important determinant of cisplatin resistance. Pharmacological inhibition of FGFR2 confirmed the importance of this kinase in NB chemoresistance. Silencing of FGFR2 sensitized NB cells to cisplatin-induced apoptosis, which was regulated by the downregulation of the anti-apoptotic proteins BCL2 and BCLX(L). Mechanistically, FGFR2 was shown to activate protein kinase C-δ to induce BCL2 expression. FGFR2, as well as the ligand fibroblast growth factor-2, were consistently expressed in primary NB and NB cell lines, indicating the presence of an autocrine loop. Expression analysis revealed that FGFR2 correlates with MYCN amplification and with advanced stage disease, demonstrating the clinical relevance of FGFR2 in NB. These findings suggest a novel role for FGFR2 in chemoresistance and provide a rational to combine pharmacological inhibitors against FGFR2 with chemotherapeutic agents for the treatment of NB.Oncogene advance online publication, 1 October 2012; doi:10.1038/onc.2012.416.

Echinococcus multilocularis primary cells: improved isolation, small-scale cultivation and RNA interference

In this study we demonstrate RNA interference mediated knock-down of target gene expression in Echinococcus multilocularis primary cells on both the transcriptional and translational level. In addition, we report on an improved method for generating E. multilocularis primary cell mini-aggregates from in vitro cultivated metacestode vesicles, and on the cultivation of small numbers of small interfering RNA-transfected cells in vitro over an extended period of time. This allows assessments on the effects of RNA interference performed on Echinococcus primary cells with regard to growth, proliferation, differentiation of the parasite and the formation of novel metacestode vesicles in vitro.

Dynamics of Spatial Game Theory Networks with Novel Modifications

Introduction: Advances in biotechnology have shed light on many biological processes. In biological networks, nodes are used to represent the function of individual entities within a system and have historically been studied in isolation. Network structure adds edges that enable communication between nodes. An emerging fieldis to combine node function and network structure to yield network function. One of the most complex networks known in biology is the neural network within the brain. Modeling neural function will require an understanding of networks, dynamics, andneurophysiology. It is with this work that modeling techniques will be developed to work at this complex intersection. Methods: Spatial game theory was developed by Nowak in the context of modeling evolutionary dynamics, or the way in which species evolve over time. Spatial game theory offers a two dimensional view of analyzingthe state of neighbors and updating based on the surroundings. Our work builds upon this foundation by studying evolutionary game theory networks with respect to neural networks. This novel concept is that neurons may adopt a particular strategy that will allow propagation of information. The strategy may therefore act as the mechanism for gating. Furthermore, the strategy of a neuron, as in a real brain, isimpacted by the strategy of its neighbors. The techniques of spatial game theory already established by Nowak are repeated to explain two basic cases and validate the implementation of code. Two novel modifications are introduced in Chapters 3 and 4 that build on this network and may reflect neural networks. Results: The introduction of two novel modifications, mutation and rewiring, in large parametricstudies resulted in dynamics that had an intermediate amount of nodes firing at any given time. Further, even small mutation rates result in different dynamics more representative of the ideal state hypothesized. Conclusions: In both modificationsto Nowak's model, the results demonstrate the network does not become locked into a particular global state of passing all information or blocking all information. It is hypothesized that normal brain function occurs within this intermediate range and that a number of diseases are the result of moving outside of this range.

Differences between RNA and DNA due to RNA editing in temporal lobe epilepsy

To investigate whether alterations in RNA editing (an enzymatic base-specific change to the RNA sequence during primary transcript formation from DNA) of neurotransmitter receptor genes and of transmembrane ion channel genes play a role in human temporal lobe epilepsy (TLE), this exploratory study analyzed 14 known cerebral editing sites in RNA extracted from the brain tissue of 41 patients who underwent surgery for mesial TLE, 23 with hippocampal sclerosis (MTLE+HS). Because intraoperatively sampled RNA cannot be obtained from healthy controls and the best feasible control is identically sampled RNA from patients with a clinically shorter history of epilepsy, the primary aim of the study was to assess the correlation between epilepsy duration and RNA editing in the homogenous group of MTLE+HS. At the functionally relevant I/V site of the voltage-gated potassium channel Kv1.1, an inverse correlation of RNA editing was found with epilepsy duration (r=-0.52, p=0.01) but not with patient age at surgery, suggesting a specific association with either the epileptic process itself or its antiepileptic medication history. No significant correlations were found between RNA editing and clinical parameters at other sites within glutamate receptor or serotonin 2C receptor gene transcripts. An "all-or-none" (≥95% or ≤5%) editing pattern at most or all sites was discovered in 2 patients. As a secondary part of the study, RNA editing was also analyzed as in the previous literature where up to now, few single editing sites were compared with differently obtained RNA from inhomogenous patient groups and autopsies, and by measuring editing changes in our mouse model. The present screening study is first to identify an editing site correlating with a clinical parameter, and to also provide an estimate of the possible effect size at other sites, which is a prerequisite for power analysis needed in planning future studies.

Generation and analysis of a mouse intestinal metatranscriptome through Illumina based RNA-sequencing

With the advent of high through-put sequencing (HTS), the emerging science of metagenomics is transforming our understanding of the relationships of microbial communities with their environments. While metagenomics aims to catalogue the genes present in a sample through assessing which genes are actively expressed, metatranscriptomics can provide a mechanistic understanding of community inter-relationships. To achieve these goals, several challenges need to be addressed from sample preparation to sequence processing, statistical analysis and functional annotation. Here we use an inbred non-obese diabetic (NOD) mouse model in which germ-free animals were colonized with a defined mixture of eight commensal bacteria, to explore methods of RNA extraction and to develop a pipeline for the generation and analysis of metatranscriptomic data. Applying the Illumina HTS platform, we sequenced 12 NOD cecal samples prepared using multiple RNA-extraction protocols. The absence of a complete set of reference genomes necessitated a peptide-based search strategy. Up to 16% of sequence reads could be matched to a known bacterial gene. Phylogenetic analysis of the mapped ORFs revealed a distribution consistent with ribosomal RNA, the majority from Bacteroides or Clostridium species. To place these HTS data within a systems context, we mapped the relative abundance of corresponding Escherichia coli homologs onto metabolic and protein-protein interaction networks. These maps identified bacterial processes with components that were well-represented in the datasets. In summary this study highlights the potential of exploiting the economy of HTS platforms for metatranscriptomics.