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As in many other cancers, highly malignant proliferation and disordered cell division play irreplaceable roles in the exceedingly easy recurrence and complex progression of glioblastoma multiforme (GBM); however, mechanistic studies of the numerous regulators involved in this process are still insufficiently thorough. The role of BCAS3 has been studied in other cancers, but its role in GBM is unclear. Here, our goal was to investigate the expression pattern of BCAS3 in GBM and its potential mechanism of action. Using TCGA database and human GBM samples, we found that BCAS3 expression was up-regulated in GBM, and its high expression predicted poor prognosis. To further investigate the relationship between BCAS3 and GBM characteristics, we up-regulated and down-regulated BCAS3 expression in GBM to detect its effect on cell proliferation and cell cycle. At the same time, we established U87 cells stably overexpressing BCAS3 and generated an intracranial xenograft model to investigate the Potential role of BCAS3 in vivo. Finally, based on in vitro cell experiments and in vivo GBM xenograft models, we observed that BCAS3 significantly regulates GBM cell proliferation and cell cycle and that this regulation is associated with p53/GADD45α Signaling pathway. Taken together, our findings suggest that BCAS3 is inextricably linked to the progression of GBM and that targeting BCAS3 may have therapeutic effects in GBM patients. [Display omitted] [ABSTRACT FROM AUTHOR]

Introduction: Ischemic stroke (IS) is a type of stroke that leads to high mortality and disability. Anoikis is a form of programmed cell death. When cells detach from the correct extracellular matrix, anoikis disrupts integrin junctions, thus preventing abnormal proliferating cells from growing or attaching to an inappropriate matrix. Although there is growing evidence that anoikis regulates the immune response, which makes a great contribution to the development of IS, the role of anoikis in the pathogenesis of IS is rarely explored., Methods: First, we downloaded GSE58294 set and GSE16561 set from the NCBI GEO database. And 35 anoikis-related genes (ARGs) were obtained from GSEA website. The CIBERSORT algorithm was used to estimate the relative proportions of 22 infiltrating immune cell types. Next, consensus clustering method was used to classify ischemic stroke samples. In addition, we used least absolute shrinkage and selection operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE) and random forest (RF) algorithms to screen the key ARGs in ischemic stroke. Next, we performed receiver operating characteristics (ROC) analysis to assess the accuracy of each diagnostic gene. At the same time, the nomogram was constructed to diagnose IS by integrating trait genes. Then, we analyzed the correlation between gene expression and immune cell infiltration of the diagnostic genes in the combined database. And gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) analysis were performed on these genes to explore differential signaling pathways and potential functions, as well as the construction and visualization of regulatory networks using NetworkAnalyst and Cytoscape. Finally, we investigated the expression pattern of ARGs in IS patients across age or gender., Results: Our study comprehensively analyzed the role of ARGs in IS for the first time. We revealed the expression profile of ARGs in IS and the correlation with infiltrating immune cells. And The results of consensus clustering analysis suggested that we can classify IS patients into two clusters. The machine learning analysis screened five signature genes, including AKT1, BRMS1, PTRH2, TFDP1 and TLE1. We also constructed nomogram models based on the five risk genes and evaluated the immune infiltration correlation, gene-miRNA, gene-TF and drug-gene interaction regulatory networks of these signature genes. The expression of ARGs did not differ by sex or age., Discussion: This study may provide a beneficial reference for further elucidating the pathogenesis of IS, and render new ideas for drug screening, individualized therapy and immunotherapy of IS., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Qin, Yi, Rong, Lu, Ji, Zhang, Ding, Wu and Chen.)