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Biology subjects

Balghonaim, S.

Publications and source records attributed to Balghonaim, S..

2 recordsLinked to original sources

Mechanotherapeutic Potential of Survivin in Glioblastoma

Glioblastoma Multiforme (GBM) is a highly aggressive brain cancer characterized by rapid proliferation and extensive remodeling of the extracellular matrix (ECM), leading to progressive tissue stiffening. Although ECM stiffness is known to promote GBM progression, the molecular mechanisms linking mechanical cues to tumor growth remain insufficiently defined. In this study, transcriptomic comparison of GBM tumors and non-neoplastic brain tissue revealed coordinated upregulation of cell cycle regulators and matrisome-associated genes, with survivin (BIRC5) identified as a central node linking proliferative signaling and ECM remodeling networks. Analysis of GBM patient specimens further showed strong nuclear survivin expression in regions with elevated collagen deposition. To directly evaluate stiffness-dependent regulation of survivin, GBM cells were cultured on fibronectin-infused hydrogels with tunable stiffness. Stiff matrices increased survivin expression along with cyclin D1 and cyclin A, consistent with increased cell cycle progression. Pharmacologic inhibition or siRNA-mediated suppression of survivin reduced stiffness-induced proliferation and attenuated expression of matrisome components, including collagens and lysyl oxidase. These findings indicate that survivin functions as a mechanosensitive regulator that coordinates cell cycle progression with ECM production in stiff tumor microenvironments. Collectively, this study identifies survivin as a key mediator linking ECM stiffness to GBM growth and matrisome remodeling. Targeting survivin and its effectors may offer a mechanosensitive strategy to limit GBM growth.

pathology↗

CT Radiomic Signatures of Neutrophil Extracellular Traps in Ischemic Stroke Thrombi

BackgroundRadiomic and transcriptomic analyses have independently identified features linked to mechanical thrombectomy (MT) outcomes in acute ischemic stroke (AIS). In this study, we integrate paired radiomic and transcriptomic profiling of AIS clots to identify Neutrophil Extracellular Trap (NET) enrichment as a predictor of first-pass MT success. We further assess the potential to non-invasively detect NET enrichment using pre-thrombectomy CT imaging. MethodsWe performed radiomic and transcriptomic analysis of 32 stroke clots retrieved by MT (n=16 each of modified first pass [mFP] success and failure). Clots were segmented from pre-MT CTA and nCCT scans and radiomic features (RFs) were extracted using pyRadiomics. Normality, equal variance, and two-sample testing were completed to identify which RFs were significantly different between mFP outcomes. Differentially expressed genes (DEGs) were identified between transcriptomes of mFP success and failure using the criteria of logFC[&ge;]1.5 and q<0.05. A NET enrichment score was computed from expression data and correlated with RFs to identify a RF signature predictive of NET enrichment. Immunofluorescence (IF) staining was completed on retrieved clot tissue to provide ground truth labeling of NETs. Results44 DEGs were identified between mFP outcomes. From ontology analysis, NET Formation, Neutrophil Degranulation, and the NET Signaling Pathway were among the most enriched terms in the mFP failure group, with related genes downregulated in the mFP success group. 40 RFs were significantly different between mFP outcomes. Of these, 6 were found to be correlated with and predictive of clot NET enrichment. IF quantification validated that transcriptomic NET signatures accurately reflected NET presence within clot tissues. ConclusionOur findings indicate that NET enrichment within thrombi is associated with reduced mFP success, and that radiomic features extracted from pre-thrombectomy CT imaging can serve as non-invasive biomarkers of clot NET content. This radiomic signature may aid in pre-procedural decision-making, including thrombolytic therapy planning and thrombectomy device selection.

pathology↗