Neurological diseases are one of the most pressing issues in modern times worldwide. It thus possesses explicit attention from researchers and medical health providers to guard public health against such an expanding threat. Various treatment modalities have been developed in a remarkably short time but, unfortunately, have yet to lead to the wished-for efficacy or the sought-after clinical improvement. The main hurdle in delivering therapeutics to the brain has always been the blood-brain barrier which still represents an elusive area with lots of mysteries yet to be solved. Meanwhile, nanotechnology has emerged as an optimistic platform that is potentially holding the answer to many of our questions on how to deliver drugs and treat CNS disorders using novel technologies rather than the unsatisfying conventional old methods. Nanocarriers can be engineered in a way that is capable of delivering a certain therapeutic cargo to a specific target tissue. Adding to this mind-blowing nanotechnology, the revolutionizing gene-altering biologics can have the best of both worlds, and pave the way for the long-awaited cure to many diseases, among those diseases thus far are Alzheimer's disease (AD), brain tumors (glioma and glioblastoma), Down syndrome, stroke, and even cases with HIV. The review herein collects the studies that tested the mixture of both sciences, nanotechnology, and epigenetics, in the context of brain therapeutics using three main categories of gene-altering molecules (siRNA, miRNA, and CRISPR) with a special focus on the advancements regarding the new favorite, intranasal route of administration.

Circular RNAs (circRNAs) are closely associated with cancer development in glioblastoma (GBM), and this study aims to explore the molecular mechanisms of a novel circular RNA circZNF652 in regulating GBM aggressiveness. The present study found that CircZNF652 and SERPINE1 were upregulated, while miR-486-5p was downregulated in GBM tissues and cell lines, and GBM patients with high expression of CircZNF652 and SERPINE1, and patients with low expression of miR-486-5p tended to have a worse prognosis. Further results validated that both silencing of circZNF652 and miR-486-5p overexpression suppressed cell growth, migration, invasion, epithelial-mesenchymal transition (EMT) and tumorigenesis in GBM cells in vitro and in vivo. Next, the underlying mechanisms were investigated, and we found that circZNF652 sponged miR-486-5p to upregulate SERPINE1 in GBM cells. Also, we validated that knock-down of circZNF652 regulated the miR-486-5p/SERPINE1 axis to reverse the malignant phenotypes in GBM cells. Interestingly, we noticed that GBM cells derived exosomes were characterized by high-expressed CircZNF652. Collectively, we concluded that targeting the circular RNA circZNF652/miR-486-5p/SERPINE1 axis was a novel and effective strategy to suppress cancer progression in GBM.

Background: Lung adenocarcinoma has increased incidence over the past years and is the cause for almost 50% of deaths attributable to lung cancer. The objective of this paper is to identify activated pathways associated with lung adenocarcinoma based on gene co-expression network analysis. Materials and Methods: Kyoto Encyclopedia of Genes and Genomes pathway analysis of dysregulated genes was performed based on Expression Analysis Systematic Explorer test to illuminate the biological pathways. Co-expression networks of lung adenocarcinoma in different tumor Stages (IA, IB, IIA, IIB, IIIA, IIIB, and IV) were constructed by Empirical Bayes approach to reweight gene pair scores. Pathway activity analysis was conducted to compute the distribution of pathways in different stages and to identify "activated" pathways in lung adenocarcinoma. Results: We evaluated 211 dysregulated genes between lung adenocarcinoma patients and normal controls. Pathway activity analysis was performed and P values of pathways, which obtained from co-expression networks (Stage IA, IB, IIA, IIB, IIIA, IIIB, and IV), were calculated. Cell cycle, progesterone-mediated oocyte maturation, and oocyte meiosis were activated during all stages in lung adenocarcinoma. Conclusions: We successfully identified three activated pathways (cell cycle, progesterone-mediated oocyte maturation, and oocyte meiosis) in different Stages (IA, IB, IIA, IIB, IIIA, IIIB, and IV) of lung adenocarcinoma.

Studies that only assess differentially-expressed (DE) genes do not contain the information required to investigate the mechanisms of diseases. A complete knowledge of all the direct and indirect interactions between proteins may act as a significant benchmark in the process of forming a comprehensive description of cellular mechanisms and functions. The results of protein interaction network studies are often inconsistent and are based on various methods. In the present study, a combined network was constructed using selected gene pairs, following the conversion and combination of the scores of gene pairs that were obtained across multiple approaches by a novel algorithm. Samples from patients with and without lung adenocarcinoma were compared, and the RankProd package was used to identify DE genes. The empirical Bayesian (EB) meta-analysis approach, the search tool for the retrieval of interacting genes/proteins database (STRING), the weighted gene coexpression network analysis (WGCNA) package and the differentially-coexpressed genes and links package (DCGL) were used for network construction. A combined network was also constructed with a novel rank-based algorithm using a combined score. The topological features of the 5 networks were analyzed and compared. A total of 941 DE genes were screened. The topological analysis indicated that the gene interaction network constructed using the WGCNA method was more likely to produce a small-world property, which has a small average shortest path length and a large clustering coefficient, whereas the combined network was confirmed to be a scale-free network. Gene pairs that were identified using the novel combined method were mostly enriched in the cell cycle and p53 signaling pathway. The present study provided a novel perspective to the network-based analysis. Each method has advantages and disadvantages. Compared with single methods, the combined algorithm used in the present study may provide a novel method to analyze gene interactions, with increased credibility.