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Malignant Pleural Mesothelioma (MPM) is an aggressive tumor of the pleural lining that is usually identified at advanced stages and resistant to current therapies. Appropriate pre-clinical mouse tumor models are of pivotal importance to study its biology. Usually, tumor cells have been injected intraperitoneally or subcutaneously. Using three available murine mesothelioma cell lines with different histotypes (sarcomatoid, biphasic, epithelioid), we have set up a simplified model of in vivo growth orthotopically by inoculating tumor cells directly in the thorax with a minimally invasive procedure. Mesothelioma tumors grew along the pleura and spread on the superficial areas of the lungs, but no masses were found outside the thoracic cavity. As observed in human MPM, tumors were highly infiltrated by macrophages and T cells. The luciferase-expressing cells can be visualized in vivo by bioluminescent optical imaging to precisely quantify tumor growth over time. Notably, the bioluminescence signal detected in vivo correctly matched the tumor burden quantified with classical histology. In contrast, the subcutaneous or intraperitoneal growth of these mesothelioma cells was considered either non-representative of the human disease or unreliable to precisely quantify tumor load. Our non-invasive in vivo model of mesothelioma is simple and reproducible, and it reliably recapitulates the human disease.
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http://dx.doi.org/10.3390/cancers12082136 | DOI Listing |
Biomaterials
September 2025
Key Laboratory of Biopharmaceutical Preparation and Delivery, Institute of Process Engineering, Chinese Academy of Sciences, Beijing, 100190, PR China; University of Chinese Academy of Sciences, Beijing, 100049, PR China. Electronic address:
The stimulator of interferon genes (STING) pathway represents a promising target in cancer immunotherapy. However, the clinical translation of cyclic dinucleotide (CDN)-based STING agonists remains hindered by insufficient formation of functional CDN-STING complexes. This critical bottleneck arises from two interdependent barriers: inefficient cytosolic CDN delivery and tumor-specific STING silencing via DNA methyltransferase-mediated promoter hypermethylation.
View Article and Find Full Text PDFTurk J Pediatr
September 2025
Department of Obstetrics and Gynecology, Faculty of Medicine, Universitas Sumatera Utara, Medan, Indonesia.
Background: Glucocorticoids remain the primary treatment for acute lymphoblastic leukemia (ALL) in children. However, glucocorticoid-resistant ALL exhibits increased mortality rates. To overcome resistance and improve management strategies, alternative therapeutic agents are required.
View Article and Find Full Text PDFJMIR 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 PDFBlood 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.
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