Tpr-Met, the oncogenic counterpart of the Met receptor, has been detected in gastric cancers, as well as in precursor lesions and in the adjacent normal gastric mucosa. This has prompted the suggestion that Tpr-Met may predispose to the development of gastric tumors. Given the sequence specificity of RNA interference, oncogenes activated by point mutation or rearrangements can be targeted while spearing the product of the wild-type allele. In this work, we report specific suppression of Tpr-Met expression and inhibition of Tpr-Met-mediated transformation and tumorigenesis by means of a short interfering RNA (siRNA) directed toward the Tpr-Met junction (anti-TM2). When delivered by a lentiviral vector, anti-TM2 siRNA was effective also in mouse embryonal fibroblasts or epithelial cells expressing high levels of Tpr-Met. Our results suggest that lentiviral-mediated delivery of anti-TM2 siRNA may be developed into a powerful tool to treat Tpr-Met-positive cancers.
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http://dx.doi.org/10.1038/sj.cgt.7700815 | DOI Listing |
J Mammary Gland Biol Neoplasia
January 2025
Department of Histology and Embryology, Faculty of Medicine, Masaryk University, Brno, Czech Republic.
Fluorescent biosensors offer a powerful tool for tracking and quantifying protein activity in living systems with high temporospatial resolution. However, the expression of genetically encoded fluorescent proteins can interfere with endogenous signaling pathways, potentially leading to developmental and physiological abnormalities. The EKAREV-NLS mouse model, which carries a FRET-based biosensor for monitoring extracellular signal-regulated kinase (ERK) activity, has been widely utilized both in vivo and in vitro across various cell types and organs.
View Article and Find Full Text PDFChemMedChem
January 2025
Nankai University, State Key Laboratory of Elemento-Organic Chemistry and Department of Chemical Biology, College of Chemistry, 94 Weijin Road, 300071, Tianjin, CHINA.
Membrane proteins, a principal class of drug targets, play indispensable roles in various biological processes and are closely associated with essential life functions. Their study, however, is complicated by their low solubility in aqueous environments and distinctive structural characteristics, necessitating a suitable native-like environment for molecular analysis. Nanodisc technology has revolutionized this field, providing biochemists with a powerful tool to stabilize membrane proteins and significantly enhance their research possibilities.
View Article and Find Full Text PDFVirulence
December 2025
Manchester Fungal Infection Group (MFIG), Division of Evolution, Infection, and Genomics, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.
Sulfur metabolism is an essential aspect of fungal physiology and pathogenicity. Fungal sulfur metabolism comprises anabolic and catabolic routes that are not well conserved in mammals, therefore is considered a promising source of prospective novel antifungal targets. To gain insight into sulfur-related metabolism during infection, we used a NanoString custom nCounter-TagSet and compared the expression of 68 key metabolic genes in different murine models of invasive pulmonary aspergillosis, at 3 time-points, and under a variety of conditions.
View Article and Find Full Text PDFAnal Methods
November 2017
Centre de Recherche sur la Conservation (CRC), MNHN, Sorbonne-Universités CNRS, MCC, USR 3224, CP21, 36 rue Geoffroy Saint Hilaire, 75005 Paris, France.
Reflectance spectral imaging is a powerful tool for the non-invasive study of cultural heritage objects. Particular visible to short wave infrared (400-2500 nm) spectral features are linked to compositional information. Spectral images can hence be used to generate useful chemical maps.
View Article and Find Full Text PDFNat Commun
January 2025
National-Local Joint Engineering Laboratory of Druggability and New Drug Evaluation, National Engineering Research Center for New Drug and Druggability (cultivation), Guangdong Province Key Laboratory of New Drug Design and Evaluation, School of Pharmaceutical Sciences, Sun Yat-Sen University, Guangzhou, 510006, China.
Epitranscriptomic modifications, particularly N6-methyladenosine (mA), are crucial regulators of gene expression, influencing processes such as RNA stability, splicing, and translation. Traditional computational methods for detecting mA from Nanopore direct RNA sequencing (DRS) data are constrained by their reliance on experimentally validated labels, often resulting in the underestimation of modification sites. Here, we introduce pum6a, an innovative attention-based framework that integrates positive and unlabeled multi-instance learning (MIL) to address the challenges of incomplete labeling and missing read-level annotations.
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