Background: Cold inducible RNA-binding protein (CIRP) is an important danger-associated molecular pattern involved in tissue-specific and systemic inflammation related to inflammation and Alzheimer’s disease (AD). However, the precise roles and mechanism of CIRP in the functional changes in astrocytes during the development of AD are still unknown. This study aimed to assess gene expression alterations in astrocytes after they overexpress CIRP (oe-CIRP) and to explore the relationship between abnormal CIRP expression and AD. Methods: We created astrocyte cell lines with a CIRP or control vector expression using three human glioma cell lines U87, U251 and H4, and analyzed the mRNA expression profiles of 3 pairs of cells via microarray. Bioinformatics identified differentially expressed mRNAs between CIRP-overexpressing (ov-CIRP) and control groups, validated by q-PCR and Western blotting (WB). Finally, the effect of CIRP overexpression in astrocytes on neurons was observed in a coculture system. Results: We identified 119 mRNAs with obvious fold changes between the ov-CIRP and control groups for all 3 pairs of human glioma cell lines. The biological functional analysis indicated that urokinase plasminogen activator (uPA), a gene whose expression significantly decreased after CIRP overexpression, was closely associated with AD. WB and q-PCR confirmed that CIRP overexpression significantly inhibited uPA at both mRNA and protein levels in U87, U251 and H4 cells. Moreover, compared with those cocultured with control astrocytes, SH-SY5Y cells cocultured with CIRP-overexpressing astrocytes exhibited a significant increase in the expression of amyloid-β (Aβ)1– 42 and the hyperphosphorylated microtubule-associated protein tau (Tau). Conclusion: CIRP overexpression in astrocytes inhibits uPA expression, promoting Aβ 1-42 production and tau phosphorylation in neurons, thereby increasing AD risk. These results suggest that the overexpression of CIRP in astrocytes contributes to the development of AD.

Aims: This study aimed to discover plasma‐derived exosomal tsRNAs that serve as novel diagnostic biomarkers for glioma and to investigate the mechanism by which tsRNAs regulate glioma development. Methods: Differentially expressed tsRNAs in the plasma exosomes of glioma patients were identified using small RNA array sequencing. Bioinformatics analyses were used to predict the biological function of tsRNAs. The changes in the phenotypes of glioma cells treated with a tsRNA mimic and inhibitor were detected. The diagnostic and prognostic characteristics of potential target genes and their related functions in gliomas were further analyzed. The cell and animal experiments were used to analyze the molecular mechanisms. Results: Among the 453 differentially expressed tsRNAs identified in the plasma‐derived exosomes of glioma patients using small RNA sequencing, i‐tRF‐LeuCAA was associated with the prognosis and molecular diagnostic characteristics of glioma patients and promoted the migration, invasion, and proliferation of glioma cells and inhibited their apoptosis. In addition, TPM4 is a potential target of i‐tRF‐LeuCAA and is related to epithelial–mesenchymal transition in gliomas. Conclusions: i‐tRF‐LeuCAA could be served as a non‐invasive biomarker in the diagnosis and prognosis of glioma. i‐tRF‐LeuCAA may indirectly regulate TPM4 expression and influence epithelial–mesenchymal transition, which may promote glioma progression.

Background: The gut microbiota plays a crucial role in the development of glioma. With the evolution of artificial intelligence technology, applying AI to analyze the vast amount of data from the gut microbiome indicates the potential that artificial intelligence and computational biology hold in transforming medical diagnostics and personalized medicine. Methods: We conducted metagenomic sequencing on stool samples from 42 patients diagnosed with glioma after operation and 30 non‐intracranial tumor patients and developed a Gradient Boosting Machine (GBM) machine learning model to predict the glioma patients based on the gut microbiome data. Results: The AUC‐ROC for the GBM model was 0.79, indicating a good level of discriminative ability. Conclusions: This method's efficacy in discriminating between glioma cells and normal controls underscores the potential of machine learning models in leveraging large datasets for clinical insights.

Background: Glioblastoma (GBM) is one of the most aggressive and treatment‐resistant primary brain tumors, with the mesenchymal subtype exhibiting particularly poor prognosis. Tumor electric field therapy (TEFT) has emerged as a promising adjunctive treatment, but its underlying molecular mechanisms remain incompletely understood. Methods: GBM functional states were analyzed using CancerSEA datasets. GBM cell lines were treated with 200 kHz TEFT at 2.2 V/m for 72 h. C1R was knocked down using siRNA and shRNA. Cell morphology, migration, invasion, proliferation, and signaling pathways were assessed through various assays. Findings were validated in animal models and clinical specimens. Results: C1R was identified at the intersection of TEFT‐downregulated genes, poor prognosis markers, and functional state genes. C1R was significantly upregulated in mesenchymal GBM and strongly correlated with epithelial‐mesenchymal transition (EMT). Single‐cell RNA sequencing revealed C1R was predominantly expressed in MES‐like malignant cells with high EMT signature scores. TEFT treatment induced morphological changes from elongated spindle‐shaped to rounded epithelial‐like morphology, increased E‐cadherin expression, and decreased mesenchymal markers (N‐cadherin, Vimentin, YKL‐40). Mechanistically, TEFT suppressed the TGF‐β/SMAD2/3/STAT3 signaling pathway, downregulating C1R expression. C1R knockdown significantly reduced tumor growth in vivo, while exogenous TGF‐β restored C1R expression and reversed the mesenchymal phenotype in a dose‐ and time‐dependent manner. Conclusion: TEFT inhibits GBM progression by suppressing the TGF‐β/SMAD2/3/STAT3/C1R axis, thereby attenuating EMT and reducing tumor aggressiveness. These findings uncover a novel mechanism of TEFT and identify C1R as a potential biomarker and therapeutic target for GBM.

Background: Glioblastoma (GBM) is among the most aggressive and treatment‐resistant primary brain tumors. The mesenchymal subtype of GBM shows a particularly unfavorable prognosis. Epithelial‐mesenchymal transition (EMT) is a critical phenotypic characteristic of this subtype. Tumor electric field therapy (TEFT) has emerged as a promising adjuvant therapy, but its underlying anti‐GBM mechanisms remain incompletely elucidated. Methods: Key molecular targets of TEFT were identified through integrated multi‐omics data analysis. U87, U251, and T98G cell lines received TEFT treatment at 200 kHz and 2.2 V/cm for 72 h. Stable cell models with CXCL14 and c‐FOS knockdown or overexpression were established using lentiviral vectors. Cellular phenotypes were assessed via wound healing assays, transwell migration and invasion assays, and western blot analysis. The regulatory hierarchy between c‐FOS and CXCL14 was verified via chromatin immunoprecipitation (ChIP) assays and rescue experiments. Mechanistic insights were validated in orthotopic nude mouse models and clinical patient specimens. Results: CXCL14 was identified by integrated bioinformatics analysis. It showed significant overexpression in mesenchymal subtypes and was strongly associated with poor prognosis. Single‐cell sequencing analysis suggested a significant increase in the EMT score of the subgroup with high CXCL14 expression. TEFT induced a morphological shift from mesenchymal to epithelial‐like characteristics. It downregulated mesenchymal markers, including N‐cadherin, Vimentin, and Snail, while upregulating E‐cadherin. Mechanistic investigations demonstrated that TEFT promoted the degradation of c‐FOS, leading to CXCL14 downregulation and subsequent inhibition of EMT. In vivo experiments confirmed the critical role of the c‐FOS/CXCL14 axis in regulating GBM invasion and migration potential. Conclusion: This study first revealed a novel mechanism which TEFT suppressed EMT in GBM via the c‐FOS/CXCL14 axis. These findings provided a new therapeutic target and a theoretical foundation for optimizing TEFT efficacy.