Orchestrating osteogenic differentiation of mesenchymal stem cells--identification of placental growth factor as a mechanosensitive gene with a pro-osteogenic role.

Skeletogenesis is initiated during fetal development and persists through adult life as either a remodeling process in response to homeostatic regulation or as a regenerative process in response to physical injury. Mesenchymal stem cells (MSCs) play a crucial role providing progenitor cells from which osteoblasts, bone matrix forming cells are differentiated. The mechanical environment plays an important role in regulating stem cell differentiation into osteoblasts, however, the mechanisms by which MSCs respond to mechanical stimuli are yet to be fully elucidated. To increase understanding of MSC mechanotransuction and osteogenic differentiation, this study aimed to identify novel, mechanically augmented genes and pathways with pro-osteogenic functionality. Using collagen glycoaminoglycan scaffolds as mimics of native extracellular matrix, to create a 3D environment more representative of that found in bone, MSC-seeded constructs were mechanically stimulated in a flow-perfusion bioreactor. Global gene expression profiling techniques were used to identify potential candidates warranting further investigation. Of these, placental growth factor (PGF) was selected and expression levels were shown to strongly correlate to both the magnitude and duration of mechanical stimulation. We demonstrated that PGF gene expression was modulated through an actin polymerization-mediated mechanism. The functional role of PGF in modulating MSC osteogenic differentiation was interrogated, and we showed a concentration-dependent response whereby low concentrations exhibited the strongest pro-osteogenic effect. Furthermore, pre-osteoclast migration and differentiation, as well as endothelial cell tubule formation also maintained concentration-dependent responses to PGF, suggesting a potential role for PGF in bone resorption and angiogenesis, processes key to bone remodeling and fracture repair.

Rare deletions at 16p13.11 predispose to a diverse spectrum of sporadic epilepsy syndromes.

Deletions at 16p13.11 are associated with schizophrenia, mental retardation, and most recently idiopathic generalized epilepsy. To evaluate the role of 16p13.11 deletions, as well as other structural variation, in epilepsy disorders, we used genome-wide screens to identify copy number variation in 3812 patients with a diverse spectrum of epilepsy syndromes and in 1299 neurologically-normal controls. Large deletions (> 100 kb) at 16p13.11 were observed in 23 patients, whereas no control had a deletion greater than 16 kb. Patients, even those with identically sized 16p13.11 deletions, presented with highly variable epilepsy phenotypes. For a subset of patients with a 16p13.11 deletion, we show a consistent reduction of expression for included genes, suggesting that haploinsufficiency might contribute to pathogenicity. We also investigated another possible mechanism of pathogenicity by using hybridization-based capture and next-generation sequencing of the homologous chromosome for ten 16p13.11-deletion patients to look for unmasked recessive mutations. Follow-up genotyping of suggestive polymorphisms failed to identify any convincing recessive-acting mutations in the homologous interval corresponding to the deletion. The observation that two of the 16p13.11 deletions were larger than 2 Mb in size led us to screen for other large deletions. We found 12 additional genomic regions harboring deletions > 2 Mb in epilepsy patients, and none in controls. Additional evaluation is needed to characterize the role of these exceedingly large, non-locus-specific deletions in epilepsy. Collectively, these data implicate 16p13.11 and possibly other large deletions as risk factors for a wide range of epilepsy disorders, and they appear to point toward haploinsufficiency as a contributor to the pathogenicity of deletions.

Methyl-CpG-binding domain sequencing reveals a prognostic methylation signature in neuroblastoma.

Accurate assessment of neuroblastoma outcome prediction remains challenging. Therefore, this study aims at establishing novel prognostic tumor DNA methylation biomarkers. In total, 396 low- and high-risk primary tumors were analyzed, of which 87 were profiled using methyl-CpG-binding domain (MBD) sequencing for differential methylation analysis between prognostic patient groups. Subsequently, methylation-specific PCR (MSP) assays were developed for 78 top-ranking differentially methylated regions and tested on two independent cohorts of 132 and 177 samples, respectively. Further, a new statistical framework was used to identify a robust set of MSP assays of which the methylation score (i.e. the percentage of methylated assays) allows accurate outcome prediction. Survival analyses were performed on the individual target level, as well as on the combined multimarker signature. As a result of the differential DNA methylation assessment by MBD sequencing, 58 of the 78 MSP assays were designed in regions previously unexplored in neuroblastoma, and 36 are located in non-promoter or non-coding regions. In total, 5 individual MSP assays (located in CCDC177, NXPH1, lnc-MRPL3-2, lnc-TREX1-1 and one on a region from chromosome 8 with no further annotation) predict event-free survival and 4 additional assays (located in SPRED3, TNFAIP2, NPM2 and CYYR1) also predict overall survival. Furthermore, a robust 58-marker methylation signature predicting overall and event-free survival was established. In conclusion, this study encompasses the largest DNA methylation biomarker study in neuroblastoma so far. We identified and independently validated several novel prognostic biomarkers, as well as a prognostic 58-marker methylation signature.