Comparing Transcriptome Profiles of Neurons Interfacing Adjacent Cells and Nanopatterned Substrates Reveals Fundamental Neuronal Interactions.

Developing neuronal axons are directed by chemical and physical signals toward a myriad of target cells. According to current dogma, the resulting network architecture is critically shaped by electrical interconnections, the synapses; however, key mechanisms translating neuronal interactions into neuronal growth behavior during network formation are still unresolved. To elucidate these mechanisms, we examined neurons interfacing nanopatterned substrates and compared them to natural interneuron interactions. We grew similar neuronal populations under three connectivity conditions, (1) the neurons are isolated, (2) the neurons are interconnected, and (3) the neurons are connected only to artificial substrates, then quantitatively compared both the cell morphologies and the transcriptome-expression profiles. Our analysis shows that whereas axon-guidance signaling pathways in isolated neurons are predominant, in isolated neurons interfacing nanotopography, these pathways are downregulated, similar to the interconnected neurons. Moreover, in nanotopography, interfacing neuron genes related to synaptogenesis and synaptic regulation are highly expressed, that is, again resembling the behavior of interconnected neurons. These molecular findings demonstrate that interactions with nanotopographies, although not leading to electrical coupling, play a comparable functional role in two major routes, neuronal guidance and network formation, with high relevance to the design of regenerative interfaces.

Immunological analysis of phase II glioblastoma dendritic cell vaccine (Audencel) trial: immune system characteristics influence outcome and Audencel up-regulates Th1-related immunovariables.

Audencel is a dendritic cell (DC)-based cellular cancer immunotherapy against glioblastoma multiforme (GBM). It is characterized by loading of DCs with autologous whole tumor lysate and in vitro maturation via "danger signals". The recent phase II "GBM-Vax" trial showed no clinical efficacy for Audencel as assessed with progression-free and overall survival in all patients. Here we present immunological research accompanying the trial with a focus on immune system factors related to outcome and Audencel's effect on the immune system. Methodologically, peripheral blood samples (from apheresis before Audencel or venipuncture during Audencel) were subjected to functional characterization via enzyme-linked immunospot (ELISPOT) assays connected with cytokine bead assays (CBAs) as well as phenotypical characterization via flow cytometry and mRNA quantification. GBM tissue samples (from surgery) were subjected to T cell receptor sequencing and immunohistochemistry. As results we found: Patients with favorable pre-existing anti-tumor characteristics lived longer under Audencel than Audencel patients without them. Pre-vaccination blood CD8+ T cell count and ELISPOT Granzyme B production capacity in vitro upon tumor antigen exposure were significantly correlated with overall survival. Despite Audencel's general failure to induce a significant clinical response, it nevertheless seemed to have an effect on the immune system. For instance, Audencel led to a significant up-regulation of the Th1-related immunovariables ELISPOT IFNγ, the transcription factor T-bet in the blood and ELISPOT IL-2 in a dose-dependent manner upon vaccination. Post-vaccination levels of ELISPOT IFNγ and CD8+ cells in the blood were indicative of a significantly better survival. In summary, Audencel failed to reach an improvement of survival in the recent phase II clinical trial. No clinical efficacy was registered. Our concomitant immunological work presented here indicates that outcome under Audencel was influenced by the state of the immune system. On the other hand, Audencel also seemed to have stimulated the immune system. Overall, these immunological considerations suggest that DC immunotherapy against glioblastoma should be studied further - with the goal of translating an apparent immunological response into a clinical response. Future research should concentrate on investigating augmentation of immune reactions through combination therapies or on developing meaningful biomarkers.

Quantification of read species behavior within whole genome sequencing of cancer genomes for the stratification and visualization of genomic variation.

The cancer genome is abnormal genome, and the ability to monitor its sequence had undergone a technological revolution. Yet prognosis and diagnosis remain an expert-based decision, with only limited abilities to provide machine-based decisions. We introduce a heterogeneity-based method for stratifying and visualizing whole-genome sequencing (WGS) reads. This method uses the heterogeneity within WGS reads to markedly reduce the dimensionality of next-generation sequencing data; it is available through the tool HiBS (Heterogeneity-Based Subclassification) that allows cancer sample classification. We validated HiBS using >200 WGS samples from nine different cancer types from The Cancer Genome Atlas (TCGA). With HiBS, we show progress with two WGS related issues: (i) differentiation between normal (NB) and tumor (TP) samples based solely on the information structure of their WGS data, and (ii) identification of specific regions of chromosomal amplification/deletion and their association with tumor stage. By comparing results to those obtained through available WGS analyses tools, we demonstrate some of the novelties obtained by the approach implemented in HiBS and also show nearly perfect normal/tumor classification, used to identify known and unknown chromosomal aberrations. Finally, the HiBS index has been associated with breast cancer tumor stage.

De novo transcriptome assembly databases for the central nervous system of the medicinal leech.

The study of non-model organisms stands to benefit greatly from genetic and genomic data. For a better understanding of the molecular mechanisms driving neuronal development, and to characterize the entire leech Hirudo medicinalis central nervous system (CNS) transcriptome we combined Trinity for de-novo assembly and Illumina HiSeq2000 for RNA-Seq. We present a set of 73,493 de-novo assembled transcripts for the leech, reconstructed from RNA collected, at a single ganglion resolution, from the CNS. This set of transcripts greatly enriches the available data for the leech. Here, we share two databases, such that each dataset allows a different type of search for candidate homologues. The first is the raw set of assembled transcripts. This set allows a sequence-based search. A comprehensive analysis of which revealed 22,604 contigs with high e-values, aligned versus the Swiss-Prot database. This analysis enabled the production of the second database, which includes correlated sequences to annotated transcript names, with the confidence of BLAST best hit.

Spatial regulation dominates gene function in the ganglia chain.

MOTIVATION: To understand the molecular mechanisms of neurons, it is imperative to identify genomic dissimilarities within the heterogeneity of the neural system. This is especially true for neuronal disorders in which spatial considerations are of critical nature. For this purpose, Hirudo medicinalis provides here an ideal system in which we are able to follow gene expression along the central nervous system, to affiliate location with gene behavior. RESULTS: In all, 221.1 million high-quality short reads were sequenced on the Illumina Hiseq2000 platform at the single ganglion level. Thereafter, a de novo assembly was performed using two state-of-the-art assemblers, Trinity and Trans-ABySS, to reconstruct a comprehensive de novo transcriptome. Classification of Trinity and Trans-ABySS transcripts produced a non-redundant set of 76 845 and 268 355 transcripts (>200 bp), respectively. Remarkably, using Trinity, 82% of the published medicinal leech messenger RNAs was identified. For the innexin family, all of the 21 recently reported genes were identified. Spatial regulation analysis across three ganglia throughout the entire central nervous system revealed distinct patterns of gene expression. These transcriptome data were combined with expression distribution to produce a spatio-transcripto map along the ganglia chain. This study provides a resource for gene discovery and gene regulation in future studies.