Bioinformatics analysis of high-throughput data to validate potential novel biomarkers and small molecule drugs for glioblastoma multiforme

Small molecule drug discovery for glioblastoma treatment based on bioinformatics and cheminformatics approaches

Background: Glioblastoma (GBM) is a common and highly aggressive brain tumor with a poor prognosis for patients. It is urgently needed to identify potential small molecule drugs that specifically target key genes associated with GBM development and prognosis. Methods: Differentially expressed genes (DEGs) between GBM and normal tissues were obtained by data mining the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Gene function annotation was performed to investigate the potential functions of the DEGs. A protein-protein interaction (PPI) network was constructed to explore hub genes associated with GBM. Bioinformatics analysis was used to screen the potential therapeutic and prognostic genes. Finally, potential small molecule drugs were predicted using the DGIdb database and verified using chemical informatics methods including absorption, distribution, metabolism, excretion, toxicity (ADMET), and molecular docking studies. Results: A total of 429 DEGs were identified, of which 19 hub genes were obtained through PPI analysis. The hub genes were confirmed as potential therapeutic targets by functional enrichment and mRNA expression. Survival analysis and protein expression confirmed centromere protein A (CENPA) as a prognostic target in GBM. Four small molecule drugs were predicted for the treatment of GBM. Conclusion: Our study suggests some promising potential therapeutic targets and small molecule drugs for the treatment of GBM, providing new ideas for further research and targeted drug development.

Combination of single-cell and bulk RNA seq reveals the immune infiltration landscape and targeted therapeutic drugs in spinal cord injury

Background

In secondary spinal cord injury (SCI), the immune microenvironment of the injured spinal cord plays an important role in spinal regeneration. Among the immune microenvironment components, macrophages/microglia play a dual role of pro-inflammation and anti-inflammation in the subacute stage of SCI. Therefore, discovering the immune hub genes and targeted therapeutic drugs of macrophages/microglia after SCI has crucial implications in neuroregeneration. This study aimed to identify immune hub genes and targeted therapeutic drugs for the subacute phase of SCI.

Methods

Bulk RNA sequencing (bulk-RNA seq) datasets (GSE5296 and GSE47681) and single-cell RNA sequencing (scRNA-seq) dataset (GSE189070) were obtained from the Gene Expression Omnibus database. In the bulk RNA-seq, the R package 'limma,' 'WGCNA,' and 'CIBERSORT' were used to jointly screen key immune genes. Subsequently, the R package 'Seurat' and the R package 'celldex' were used to divide and annotate the cell clusters, respectively. After using the Autodock software to dock immune hub genes and drugs that may be combined, the effectiveness of the drug was verified using an in vivo experiment with the T9 SCI mouse model.

Results

In the bulk-RNA seq, B2m, Itgb5, and Vav1 were identified as immune hub genes. Ten cell clusters were identified in scRNA-seq, and B2m and Itgb5 were mainly located in the microglia, while Vav1 was mainly located in macrophages. Molecular docking results showed that the proteins corresponding to these immune genes could accurately bind to decitabine. In decitabine-treated mice, the pro-inflammatory factor (TNF-α, IL-1β) levels were decreased while anti-inflammatory factor (IL-4, IL-10) levels were increased at 2 weeks post-SCI, and macrophages/microglia transformed from M1 to M2. At 6 weeks post-SCI, the neurological function score and electromyography of the decitabine treatment group were also improved.

Conclusion

In the subacute phase of SCI, B2m, Itgb5, and Vav1 in macrophages/microglia may be key therapeutic targets to promote nerve regeneration. In addition, low-dose decitabine may promote spinal cord regeneration by regulating the polarization state of macrophages/microglia.

Advances in nano-based materials for glioblastoma multiforme diagnosis: A mini-review

The development of nano-based materials for diagnosis enables a more precise prognosis and results. Inorganic, organic, or hybrid nanoparticles using nanomaterials, such as quantum dots, extracellular vesicle systems, and others, with different molecular compositions, have been extensively explored as a better strategy to overcome the blood-brain barrier and target brain tissue and tumors. Glioblastoma multiforme (GBM) is the most common and aggressive primary tumor of the central nervous system, with a short, established prognosis. The delay in early detection is considered a key challenge in designing a precise and efficient treatment with the most encouraging prognosis. Therefore, the present mini-review focuses on discussing distinct strategies presented recently in the literature regarding nanostructures’ use, design, and application for GBM diagnosis.