SEPT4 is regulated by the Notch signaling pathway

Discovery of a septin-4 covalent binder with antimetastatic activity in a mouse model of melanoma

Cancer spreading through metastatic processes is one of the major causes of tumour-related mortality. Metastasis is a complex phenomenon which involves multiple pathways ranging from cell metabolic alterations to changes in the biophysical phenotype of cells and tissues. In the search for new effective anti-metastatic agents, we modulated the chemical structure of the lead compound AA6, in order to find the structural determinants of activity, and to identify the cellular target responsible of the downstream anti-metastatic effects observed. New compounds synthesized were able to inhibit in vitro B16-F10 melanoma cell invasiveness, and one selected compound, CM365, showed in vivo anti-metastatic effects in a lung metastasis mouse model of melanoma. Septin-4 was identified as the most likely molecular target responsible for these effects. This study showed that CM365 is a promising molecule for metastasis prevention, remarkably effective alone or co-administered with drugs normally used in cancer therapy, such as paclitaxel.

Septin 4 controls CCNB1 stabilization via APC/CCDC20 during meiotic G2/M transition in mouse oocytes

In mammals, oocytes are arrested at G2/prophase for a long time, which is called germinal vesicle (GV) arrest. After puberty, fully-grown oocytes are stimulated by a gonadotropin surge to resume meiosis as indicated by GV breakdown (GVBD). CCNB1 is accumulated to a threshold level to trigger the activation of maturation promoting factor (MPF), inducing the G2/M transition. It is generally recognized that the anaphase-promoting complex/cyclosome (APC/C) and its cofactor CDH1 (also known as FZR1) regulates the accumulation/degradation of CCNB1. Here, by using small interfering RNA (siRNA) and messenger RNA (mRNA) microinjection, immunofluorescence and confocal microscopy, immunoprecipitation, time-lapse live imaging, and immunoblotting analysis, we showed that Septin 4 regulates the G2/M transition by regulating the accumulation of CCNB1 via APC/C^CDC20 . Depletion of Septin 4 caused GV arrest by reducing CCNB1 accumulation. Unexpectedly, the expression level of CDC20 was higher in Septin 4 siRNA-injected oocytes than in control oocytes, but there was no significant change in the expression level of CDH1. Importantly, the reduced GVBD after Septin 4 depletion could be rescued not only by over-expressing CCNB1 but also could be partially rescued by depleting CDC20. Taken together, our results demonstrate that Septin 4 may play a critical role in meiotic G2/M transition by indirect regulation of CCNB1 stabilization in mouse oocytes.

RNA-Seq reveals seven promising candidate genes affecting the proportion of thick egg albumen in layer-type chickens

Eggs with a much higher proportion of thick albumen are preferred in the layer industry, as they are favoured by consumers. However, the genetic factors affecting the thick egg albumen trait have not been elucidated. Using RNA sequencing, we explored the magnum transcriptome in 9 Rhode Island white layers: four layers with phenotypes of extremely high ratios of thick to thin albumen (high thick albumen, HTA) and five with extremely low ratios (low thick albumen, LTA). A total of 220 genes were differentially expressed, among which 150 genes were up-regulated and 70 were down-regulated in the HTA group compared with the LTA group. Gene Ontology (GO) analysis revealed that the up-regulated genes in HTA were mainly involved in a wide range of regulatory functions. In addition, a large number of these genes were related to glycosphingolipid biosynthesis, focal adhesion, ECM-receptor interactions and cytokine-cytokine receptor interactions. Based on functional analysis, ST3GAL4, FUT4, ITGA2, SDC3, PRLR, CDH4 and GALNT9 were identified as promising candidate genes for thick albumen synthesis and metabolism during egg formation. These results provide new insights into the molecular mechanisms of egg albumen traits and may contribute to future breeding strategies that optimise the proportion of thick egg albumen.

Artificial neural network inference (ANNI): a study on gene-gene interaction for biomarkers in childhood sarcomas

Objective

To model the potential interaction between previously identified biomarkers in children sarcomas using artificial neural network inference (ANNI).

Method

To concisely demonstrate the biological interactions between correlated genes in an interaction network map, only 2 types of sarcomas in the children small round blue cell tumors (SRBCTs) dataset are discussed in this paper. A backpropagation neural network was used to model the potential interaction between genes. The prediction weights and signal directions were used to model the strengths of the interaction signals and the direction of the interaction link between genes. The ANN model was validated using Monte Carlo cross-validation to minimize the risk of over-fitting and to optimize generalization ability of the model.

Results

Strong connection links on certain genes (TNNT1 and FNDC5 in rhabdomyosarcoma (RMS); FCGRT and OLFM1 in Ewing’s sarcoma (EWS)) suggested their potency as central hubs in the interconnection of genes with different functionalities. The results showed that the RMS patients in this dataset are likely to be congenital and at low risk of cardiomyopathy development. The EWS patients are likely to be complicated by EWS-FLI fusion and deficiency in various signaling pathways, including Wnt, Fas/Rho and intracellular oxygen.

Conclusions

The ANN network inference approach and the examination of identified genes in the published literature within the context of the disease highlights the substantial influence of certain genes in sarcomas.