Background & Objective: RNA interference (RNAi) technique is now widely used in studies of gene function, signal transduction pathway, and gene therapy because it can effectively and specifically inhibit gene expression. This study was designed to synthesize small interfering RNA (siRNA) by in vitro transcription, and construct retrovirus vectors to express small hairpin RNA (shRNA), detect RNAi in nasopharyngeal carcinoma cell lines, and to develop a RNAi technique platform.
Methods: siRNAs targeting green fluorescent protein (GFP) and luciferase (Luc) were synthesized by in vitro transcription, while shRNAs targeting GFP and Luc were constructed from pSUPER.retro. Cervical cancer cell line HeLa, nasopharyngeal carcinoma cell lines CNE1, CNE2, and 5-8F were co-transfected with siRNAs or shRNAs and reporter gene pEGFP-N1 or pGL3. The expression of GFP was detected by fluorescent microscopy and Western blot. The activity of luciferase was measured by Luciferase Enzyme Assay System.
Results: siRNA duplexes with 3' UU overhangs and shRNA specifically silenced GFP expression, while antisense RNA and siRNA without 3' UU overhangs did not trigger RNA interference of GFP. Quantitative luciferase activity analysis showed that siRNA inhibited Luc expression in HeLa, CNE1, CNE2, and 5-8F cell lines with inhibition rates of 91.43%, 78.01%, 90.30%, and 62.85%, respectively. Similarly, the inhibition rate was 78.22% when shRNA targeting Luc was co-transfected into HeLa cell line.
Conclusions: Both siRNAs and shRNAs can induce RNAi. 3' UU overhangs of siRNA may play a role in RNAi. RNAi can be triggered in both nasopharyngeal carcinoma cell lines and HeLa cell line.
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Eur J Epidemiol
January 2025
Department of Neurobiology, Care Sciences and Society, Division of Family Medicine and Primary Care, Karolinska Institutet, Stockholm, Sweden.
The Stockholm Early Detection of Cancer Study (STEADY-CAN) cohort was established to investigate strategies for early cancer detection in a population-based context within Stockholm County, the capital region of Sweden. Utilising real-world data to explore cancer-related healthcare patterns and outcomes, the cohort links extensive clinical and laboratory data from both inpatient and outpatient care in the region. The dataset includes demographic information, detailed diagnostic codes, laboratory results, prescribed medications, and healthcare utilisation data.
View Article and Find Full Text PDFNPJ Precis Oncol
January 2025
Zentalis Pharmaceuticals, Inc., San Diego, CA, USA.
Upregulation of Cyclin E1 and subsequent activation of CDK2 accelerates cell cycle progression from G1 to S phase and is a common oncogenic driver in gynecological malignancies. WEE1 kinase counteracts the effects of Cyclin E1/CDK2 activation by regulating multiple cell cycle checkpoints. Here we characterized the relationship between Cyclin E1/CDK2 activation and sensitivity to the selective WEE1 inhibitor azenosertib.
View Article and Find Full Text PDFSci Rep
January 2025
School of Medicine, Nankai University, Tianjin, 300071, China.
Cholangiocarcinoma (CCA), a highly aggressive form of cancer, is known for its high mortality rate. A Disintegrin and Metalloprotease Domain-like Protein Decysin-1 (ADAMDEC1) can promote the development and metastasis in various tumors by degrading the extracellular matrix. However, its regulatory mechanism in CCA remains unclear.
View Article and Find Full Text PDFAnn Hematol
January 2025
Department of Hematology, Navy Medical Center of PLA, Naval Medical University, No. 338 West Huaihai Road, Changning District, Shanghai, 200052, China.
Multiple myeloma(MM) remains incurable with high relapse and chemoresistance rates. Differentially expressed genes(DEGs) between newly diagnosed myeloma and secondary plasma cell leukemia(sPCL) were subjected to a weighted gene co-expression network analysis(WGCNA). Drug resistant myeloma cell lines were established.
View Article and Find Full Text PDFSci Rep
January 2025
School of Physics, Engineering and Technology, University of York, Heslington, York, YO10 5DD, UK.
Prostate cancer is a disease which poses an interesting clinical question: Should it be treated? Only a small subset of prostate cancers are aggressive and require removal and treatment to prevent metastatic spread. However, conventional diagnostics remain challenged to risk-stratify such patients; hence, new methods of approach to biomolecularly sub-classify the disease are needed. Here we use an unsupervised self-organising map approach to analyse live-cell Raman spectroscopy data obtained from prostate cell-lines; our aim is to exemplify this method to sub-stratify, at the single-cell-level, the cancer disease state using high-dimensional datasets with minimal preprocessing.
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