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Diffuse large B-cell lymphoma (DLBCL) is a malignant tumor and research on its therapeutic targets has received increasing attention. It has been reported that Leucyl-tRNA synthetase (LARS) contributes to the growth and migration of non-Hodgkin lymphoma (NHL), yet its effect on DLBCL progression remains to be elucidated. MTT and flow cytometry were carried out to determine the cellular phenotypes of DLBCL cells under LARS overexpression. The differentially expressed proteins (DEPs) were screened by mass spectrometry. ELISA, western blot, and xenograft tumor experiments were implemented to confirm the impact of LARS and the LRPPRC/HIF-1α axis on malignant progression and glycolysis. Dual-luciferase reporter assay and chromatin immunoprecipitation (ChIP) were applied for exploring the underlying mechanism by which LARS was regulated. LARS promoted the malignant phenotypes, such as increasing cell proliferation and inhibiting apoptosis, and enhanced abnormal glycolysis both in vitro and in vivo. Based on mass spectrometry and functional recovery experiments, we found that LARS upregulated LRPPRC expression. More importantly, overexpressing LRPPRC facilitated malignant phenotypes and glycolysis through the elevation of HIF-1α expression, which could be reversed by silenced HIF-1α. Mechanistically, LARS promoted the expression of HIF-1α by activating LRPPRC, which in turn enhanced the transcription of HK2, thereby facilitating malignant progression and abnormal glycolysis. LARS facilitated abnormal glycolysis via the LRPPRC/HIF-1α/HK2 axis, thereby promoting the malignant progression of DLBCL.
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http://dx.doi.org/10.1007/s13577-025-01267-y | DOI Listing |
JMIR Res Protoc
September 2025
Department of Medical Oncology, Early Phase Unit, Georges-François Leclerc Centre, Dijon, France.
Background: Sarcomas are rare cancer with a heterogeneous group of tumors. They affect both genders across all age groups and present significant heterogeneity, with more than 70 histological subtypes. Despite tailored treatments, the high metastatic potential of sarcomas remains a major factor in poor patient survival, as metastasis is often the leading cause of death.
View Article and Find Full Text PDFPurpose: In Armenia, a lower-middle-income country, cancer causes 21% of all deaths, with over half of cases diagnosed at advanced stages. Without universal health insurance, patients rely on out-of-pocket payments or black-market channels for costly immunotherapies, underscoring the need for real-world data to inform equitable policy reforms.
Methods: We conducted a multicenter, retrospective cohort study of patients who received at least one dose of an immune checkpoint inhibitor (ICI) between January 2017 and December 2023 across six Armenian oncology centers.
Blood Adv
September 2025
BC Cancer, Vancouver, British Columbia, Canada.
Classical Hodgkin Lymphoma (CHL) is characterized by a complex tumor microenvironment (TME) that supports disease progression. While immune cell recruitment by Hodgkin and Reed-Sternberg (HRS) cells is well-documented, the role of non-malignant B cells in relapse remains unclear. Using single-cell RNA sequencing (scRNA-seq) on paired diagnostic and relapsed CHL samples, we identified distinct shifts in B-cell populations, particularly an enrichment of naïve B cells and a reduction of memory B cells in early-relapse compared to late-relapse and newly diagnosed CHL.
View Article and Find Full Text PDFPLoS One
September 2025
Institute of Computational Science and Technology, Guangzhou University, Guangzhou, China.
MicroRNAs (miRNAs) are critical regulators of gene expression in cancer biology, yet their spatial dynamics within tumor microenvironments (TMEs) remain underexplored due to technical limitations in current spatial transcriptomics (ST) technologies. To address this gap, we present STmiR, a novel XGBoost-based framework for spatially resolved miRNA activity prediction. STmiR integrates bulk RNA-seq data (TCGA and CCLE) with spatial transcriptomics profiles to model nonlinear miRNA-mRNA interactions, achieving high predictive accuracy (Spearman's ρ > 0.
View Article and Find Full Text PDFPLoS One
September 2025
Department of Biomedical Data Intelligence, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Capturing the dynamic changes in patients' internal states as they approach death due to fatal diseases remains a major challenge in understanding individual pathologies and improving end-of-life care. However, existing methods primarily focus on specific test values or organ dysfunction markers, failing to provide a comprehensive view of the evolving internal state preceding death. To address this, we analyzed electronic health record (EHR) data from a single institution, including 8,976 cancer patients and 77 laboratory parameters, by constructing continuous mortality prediction models based on gradient-boosting decision trees and leveraging them for temporal analyses.
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