Glioblastoma is the most common and malignant primary brain tumor, defined by its highly aggressive nature. Despite the advances in diagnostic and surgical techniques, and the development of novel therapies in the last decade, the prognosis for glioblastoma is still extremely poor. One major factor for the failure of existing therapeutic approaches is the highly invasive nature of glioblastomas. The extreme infiltrating capacity of tumor cells into the brain parenchyma makes complete surgical removal difficult; glioblastomas almost inevitably recur in a more therapy-resistant state, sometimes at distant sites in the brain. Therefore, there are major efforts to understand the molecular mechanisms underpinning glioblastoma invasion; however, there is no approved therapy directed against the invasive phenotype as of now. Here, we review the major molecular mechanisms of glioblastoma cell invasion, including the routes followed by glioblastoma cells, the interaction of tumor cells within the brain environment and the extracellular matrix components, and the roles of tumor cell adhesion and extracellular matrix remodeling. We also include a perspective of high-throughput approaches utilized to discover novel players for invasion and clinical targeting of invasive glioblastoma cells.
Experimentation of nanomedicine is labor‐intensive, time‐consuming, and requires costly laboratory consumables. Constructing a reliable mathematical model for such systems is also challenging due to the difficulties in gathering a sufficient number of data points. Artificial neural networks (ANNs) are indicated as an efficient approach in nanomedicine to investigate the cause‐effect relationships and predict output variables. Herein, an ANN is adapted into plasmid DNA (pDNA) encapsulated and PEGylated chitosan nanoparticles cross‐linked with sodium tripolyphosphate (TPP) to investigate the effects of critical parameters on the transfection efficiencies of nanoparticles. The ANN model is developed based on experimental results with three independent input variables: 1) polyethylene glycol (PEG) molecular weight, 2) PEG concentration, and 3) nanoparticle concentration, along with one output variable as a percentage of green fluorescent protein (GFP) expression, which refers to transfection efficiency. The constructed model is further validated with the leave‐p‐out cross‐validation method. The results indicate that the developed model has good prediction capability and is influential in capturing the transfection efficiencies of different nanoparticle groups. Overall, this study reveals that the ANN could be an efficient tool for nanoparticle‐mediated gene delivery systems to investigate the impacts of critical parameters in detail with reduced experimental effort and cost.
B-type lamins are critical nuclear envelope proteins that interact with the 3D genomic architecture. However, identifying the direct roles of B-lamins on dynamic genome organization has been challenging as their joint depletion severely impacts cell viability. To overcome this, we engineered mammalian cells to rapidly and completely degrade endogenous B-type lamins using Auxin-inducible degron (AID) technology. Paired with a suite of novel technologies, live-cell Dual Partial Wave Spectroscopic (Dual-PWS) microscopy, in situ Hi-C, and CRISPR-Sirius, we demonstrate that lamin B1 and lamin B2 depletion transforms chromatin mobility, heterochromatin positioning, gene expression, and loci-positioning with minimal disruption to mesoscale chromatin folding. Using the AID system, we show that the disruption of B-lamins alters gene expression both within and outside lamin associated domains, with distinct mechanistic patterns depending on their localization. Critically, we demonstrate that chromatin dynamics, positioning of constitutive and facultative heterochromatic markers, and chromosome positioning near the nuclear periphery are significantly altered, indicating that the mechanism of action of B-type lamins is derived from their role in maintaining chromatin dynamics and spatial positioning. Our findings suggest that the mechanistic role of B-type lamins is stabilization of heterochromatin and chromosomal positioning along the nuclear periphery. We conclude that degrading lamin B1 and lamin B2 has several functional consequences related to both structural disease and cancer.
Nearly 70% of Uterine fibroid (UF) tumors are driven by recurrent MED12 hotspot mutations. Unfortunately, no cellular models could be generated because the mutant cells have lower fitness in 2D culture conditions. To address this, we employ CRISPR to precisely engineer MED12 Gly44 mutations in UF-relevant myometrial smooth muscle cells. The engineered mutant cells recapitulate several UF-like cellular, transcriptional, and metabolic alterations, including altered Tryptophan/kynurenine metabolism. The aberrant gene expression program in the mutant cells is, in part, driven by a substantial 3D genome compartmentalization switch. At the cellular level, the mutant cells gain enhanced proliferation rates in 3D spheres and form larger lesions in vivo with elevated production of collagen and extracellular matrix deposition. These findings indicate that the engineered cellular model faithfully models key features of UF tumors and provides a platform for the broader scientific community to characterize genomics of recurrent MED12 mutations.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.