Unlike other tumours, TP53 is rarely mutated in melanoma; however, it fails to function as a tumour suppressor. We assume that its functions might be altered through interactions with several families of proteins, including p53/p73, NME and GLI. To elucidate the potential interplay among these families we analysed the expression profiles of aforementioned genes and proteins in a panel of melanoma cell lines, metastatic melanoma specimens and healthy corresponding tissue. Using qPCR a higher level of NME1 gene expression and lower levels of Δ40p53β, ΔNp73, GLI1, GLI2 and PTCH1 were observed in tumour samples compared to healthy tissue. Protein expression of Δ133p53α, Δ160p53α and ΔNp73α isoforms, NME1 and NME2, and N'ΔGLI1, GLI1FL, GLI2ΔN isoforms was elevated in tumour tissue, whereas ∆Np73β was downregulated. The results in melanoma cell lines, in general, support these findings. In addition, we correlated expression profiles with clinical features and outcome. Higher Δ133p53β and p53α mRNA and both GLI1 mRNA and GLI3R protein expression had a negative impact on the overall survival. Shorter overall survival was also connected with lower p53β and NME1 gene expression levels. In conclusion, all examined genes may have implications in melanoma development and functional inactivity of TP53.
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http://dx.doi.org/10.1038/s41598-019-48882-y | DOI Listing |
Invest Ophthalmol Vis Sci
January 2025
Dr. Rolf M. Schwiete Center for Limbal Stem Cell and Congenital Aniridia Research, Homburg/Saar, Germany, Saarland University, Homburg/Saar, Germany.
Purpose: This study evaluates the microRNA (miRNA) expression profile in primary limbal epithelial cells (pLECs) of patients with aniridia.
Methods: Primary human LECs were sampled and isolated from 10 patients with aniridia and 10 healthy donors. The miRNA profile was analyzed using miRNA microarrays.
Appl Biochem Biotechnol
January 2025
Department of Pharmaceutical Sciences, Oregon State University, Corvallis, OR, 97333, USA.
Caves are a unique ecosystem that harbor diverse microorganisms, and provide a challenging environment to the dwelling microbial communities, which may boost gene expression and can lead to the production of inimitable bioactive natural products. In this study, we obtained 59 actinobacteria from four different caves located in Bahadurkhel, District Karak, Pakistan. On the basis of taxonomic characteristics, 30 isolates were selected and screened for secondary metabolites production and bioactivity profiling.
View Article and Find Full Text PDFTransgenic Res
January 2025
Shaanxi Tobacco Company Baoji City Company, Baoji, 721000, Shaanxi, China.
The involvement of Loose Plant Architecture 1 (LPA1) in regulating plant growth and leaf angle has been previously demonstrated. However, the fundamental genetic background remains unidentified. To further understand the tissue expression profile of the NtLPA1 gene, an overexpression vector (pBI121-NtLPA1) was developed and employed to modify tobacco using the leaf disc method genetically.
View Article and Find Full Text PDFCell Tissue Res
January 2025
Department of Animal Science, Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia.
Traditional transcriptomic studies often overlook the complex heterogeneity of skeletal muscle, as they typically isolate RNA from mixed muscle fibre and cell populations, resulting in an averaged transcriptomic profile that obscures fibre type-specific differences. This study assessed the potential of the recently developed Xenium platform for high-resolution spatial transcriptomic analysis of human skeletal muscle histological sections. Human vastus lateralis muscle samples from two individuals were analysed using the Xenium platform and Human Multi-Tissue and Cancer Panel targeting 377 genes complemented by staining of successive sections for Myosin Heavy Chain isoforms to differentiate between type 1 and type 2 muscle fibres.
View Article and Find Full Text PDFEnviron Geochem Health
January 2025
School of Environmental Science and Engineering, Shandong University, Qingdao, 266237, China.
Groundwater arsenic (As), contamination is a significant issue worldwide including China and Pakistan, particularly in canal command areas. In this study, 131 groundwater samples were collected, and three machine learning models [Random Forest (RF), Logistic Regression (LR), and Artificial Neural Network (ANN)] were employed to predict As concentration. Descriptive statistics helped to conclude that all of the samples were inside the permitted limit of WHO for pH, Ca, Mg, Turbidity, Cl, K, Na, SO, NO, F and beyond limit of WHO for EC, HCO, TDS, and As.
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