No abstract

No abstract

Glioblastoma is the most malignant brain tumor, exhibiting remarkable resistance to treatment. Here we investigated the oncogenic potential of HOXA9 in gliomagenesis, the molecular and cellular mechanisms by which HOXA9 renders glioblastoma more aggressive, and how HOXA9 affects response to chemotherapy and survival. The prognostic value of HOXA9 in glioblastoma patients was validated in two large datasets from TCGA and Rembrandt, where high HOXA9 levels were associated with shorter survival. Transcriptomic analyses identified novel HOXA9-target genes with key roles in cancer-related processes, including cell proliferation, DNA repair, and stem cell maintenance. Functional studies with HOXA9-overexpressing and HOXA9-silenced glioblastoma cell models revealed that HOXA9 promotes cell viability, stemness and invasion, and inhibits apoptosis. Additionally, HOXA9 promoted the malignant transformation of human immortalized astrocytes in an orthotopic in vivo model, and caused tumor-associated death. HOXA9 also mediated resistance to temozolomide treatment in vitro and in vivo via upregulation of BCL2. Importantly, the pharmacological inhibition of BCL2 with the BH3 mimetic ABT-737 reverted temozolomide resistance in HOXA9-positive cells. These data establish HOXA9 as a driver of glioma initiation, aggressiveness and resistance to therapy. In the future, the combination of BH3 mimetics with temozolomide should be further explored as an alternative treatment for glioblastoma.

hyperpolarising factor. EETs are synthesised from arachidonic acids by cytochrome P450 enzymes, and soluble epoxide hydrolase (SEH) inhibition may up-regulate EETs. EETs signaling may be implicated in cardiovascular risk groups. The effects of two agonists in stimulating EETs release were compared, and the best agonist was chosen to investigate this pathway in cardiovascular patient groups, and to confirm target engagement in a first in human clinical trial of a novel SEH inhibitor. Methods: Healthy volunteers (12 male, 12 female) underwent 4 forearm venous occlusion plethysmography studies to compare the effects of intraarterial bradykinin and acetylcholine co-infused with saline, fluconazole (cytochrome P450 inhibitor), L-monomethylarginine (nitric oxide synthase inhibitor) plus aspirin (cyclo-oxygenase inhibitor) (LNMMA+ASA), or with all three inhibitors (Triple). Data were analysed by repeated measures analysis of variance. MeanAESEM are presented. Results: Fluconazole had no effect on basal tone (pZ0.25). Bradykinin and acetylcholine both caused dose related vasodilatation (p<0.0001 vs. p<0.001). Fluconazole inhibited bradykinin-induced flow, but not acetylcholine (p<0.0001 vs. pZ0.86). LNMMA+ASA inhibited bradykinin and acetylcholine induced vasodilatation (p<0.0001 vs. p<0.0001). There was no additive effect with triple inhibition. At top agonist doses, fluconazole inhibited bradykinin-induced flow, but not acetylcholine (-18.84AE5.08% vs. 3.36AE9.07%; pZ0.01). LNMMA+ASA inhibited bradykinin and acetylcholine induced flow (-35.74AE7.57% vs. -32.78AE10.60% pZ0.74). There were no gender differences. Conclusions: Basal tone is not dependent on EETs signaling. Bradykinininduced flow is EETs dependent, therefore bradykinin was chosen to probe EETs in cardiovascular patient groups.

Since the first measurements of neuronal avalanches [1], the critical brain hypothesis has gained traction [2]. However, if the brain is critical, what is the phase transition? For several decades it has been known that the cerebral cortex operates in a diversity of regimes [3], ranging from highly synchronous states (e.g. slow wave sleep [4], with higher spiking variability) to desynchronized states (e.g. alert waking [5], with lower spiking variability). Here, using independent signatures of criticality, we show that a phase transition occurs in an intermediate value of spiking variability. The critical exponents point to a universality class different from mean-field directed percolation (MF-DP). Importantly, as the cortex hovers around this critical point [6], it follows a linear relation between the avalanche exponents that encompasses previous experimental results from different setups [7,8] and is reproduced by a model. * AJF and NAPV contributed equally. †