Glioblastoma multiforme (GBM) is a high-grade brain malignancy arising from astrocytes. Despite aggressive surgical approaches, optimized radiation therapy regimens, and the application of cytotoxic chemotherapies, the median survival of patients with GBM from time of diagnosis remains less than 15 months, having changed little in decades. Approaches that target genes and biological pathways responsible for tumorigenesis or potentiate the activity of current therapeutic modalities could improve treatment efficacy. In this regard, several genomic and proteomic strategies promise to impact significantly on the drug discovery process. High-throughput genome-wide screening with short interfering RNA (siRNA) is one strategy for systematically exploring possible therapeutically relevant targets in GBM. Statistical methods and protein-protein interaction network databases can also be applied to the screening data to explore the genes and pathways that underlie the pathological basis and development of GBM. In this study, we highlight several genome-wide siRNA screens and implement these experimental concepts in the T98G GBM cell line to uncover the genes and pathways that regulate GBM cell death and survival. These studies will ultimately influence the development of a new avenue of neurosurgical therapy by placing the drug discovery process in the context of the entire biological system.
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http://dx.doi.org/10.3171/2009.10.FOCUS09210 | DOI Listing |
Med Phys
January 2025
Paul Albrechtsen Research Institute, CancerCare Manitoba, Winnipeg, Canada.
Background: The treatment of glioblastomas (GBM) with radiation therapy is extremely challenging due to their invasive nature and high recurrence rate within normal brain tissue.
Purpose: In this work, we present a new metric called the tumour spread (TS) map, which utilizes diffusion tensor imaging (DTI) to predict the probable direction of tumour cells spread along fiber tracts. We hypothesized that the TS map could serve as a predictive tool for identifying patterns of likely recurrence in patients with GBM and, therefore, be used to modify the delivery of radiation treatment to pre-emptively target regions at high risk of tumour spread.
Neurosurg Rev
January 2025
Lab in Biotechnology and Biosignal Transduction, Department of Orthodontics, Saveetha Dental College and Hospital, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Chennai-77, Tamil Nadu, India.
Neurosurg Rev
January 2025
Lab in Biotechnology and Biosignal Transduction, Department of Orthodontics, Saveetha Dental College and Hospital, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Chennai-77, Tamil Nadu, India.
Cell Death Dis
January 2025
State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers, Department of Immunology, Fourth Military Medical University, Xi'an, Shaanxi Province, China.
Glioblastoma (GBM) is the most common malignant primary brain cancer with poor prognosis due to the resistant to current treatments, including the first-line drug temozolomide (TMZ). Accordingly, it is urgent to clarify the mechanism of chemotherapeutic resistance to improve the survival rate of patients. In the present study, by integrating comprehensive non-coding RNA-seq data from multiple cohorts of GBM patients, we identified that a series of miRNAs are frequently downregulated in GBM patients compared with the control samples.
View Article and Find Full Text PDFBiochemistry (Mosc)
December 2024
Moscow Institute of Physics and Technology, Dolgoprudny, 141701, Russia.
Activation of the p38 mitogen-activated protein kinase (MAPK) pathways is vital in regulating cell growth, differentiation, apoptosis, and stress response, significantly affecting tumorigenesis and cancer progression. We developed a bioinformatic technique to construct an interactome network-based molecular pathways for genes of interest and quantify their activation levels using high-throughput gene expression data. This study is focused on the p38α, p38β, p38γ, and p38δ kinases, examining their activation levels (PALs) based on transcriptomic data and their associations with survival and drug responsiveness across various cancer types.
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