Objective: Renal cell carcinoma (RCC) displays an increasing incidence and mortality rate worldwide in recent years. More and more evidence demonstrated microRNAs function as positive or negative regulatory factors in many cancers, while the role of miR-301a in RCC is still unclear.
Material And Methods: The expression and clinical significance of miR-301a were assessed via bioinformatic software on open microarray datasets of the Cancer Genome Atlas (TCGA) and then confirmed by quantitative real-time PCR (qRT-PCR) in RCC cell lines. Loss of function assays were performed in RCC cell lines both in vitro and in vivo. Cell Counting Kit-8 (CCK-8), flow cytometry, luciferase reporter assays, Western blotting, and immunohistochemistry were employed to explore the mechanisms of the effect of miR-301a on RCC.
Results: By analyzing RCC clinical specimens and cell lines, we found a uniform increased miR-301a in expression in comparison with normal renal tissue or normal human proximal tubule epithelial cell line (HK-2). In addition, miR-301a upregulation correlated advanced stage and poor prognosis of clear cell RCC (ccRCC). Anti-miR-301a could inhibit growth and cell cycle G1/S transition in RCC cell lines. Moreover, we found that PTEN was identified as a direct target of miR-301a that might partially interrupt miR-301a-induced G1/S transition. Importantly, nude-mouse models revealed that knockdown of miR-301a delayed tumor growth.
Conclusion: These results indicate that miR-301a functions as a tumor-promoting miRNA through regulating PTEN expression, representing a novel therapeutic target for RCC.
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http://dx.doi.org/10.2147/CMAR.S253533 | DOI Listing |
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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