Up to 80% of endometrial and breast cancers express oestrogen receptor alpha (ERα). Unlike breast cancer, anti-oestrogen therapy has had limited success in endometrial cancer, raising the possibility that oestrogen has different effects in both cancers. We investigated the role of oestrogen in endometrial and breast cancers using data from The Cancer Genome Atlas (TCGA) in conjunction with cell line studies. Using phosphorylation of ERα (ERα-pSer118) as a marker of transcriptional activation of ERα in TCGA datasets, we found that genes associated with ERα-pSer118 were predominantly unique between tumour types and have distinct regulators. We present data on the alternative and novel roles played by SMAD3, CREB-pSer133 and particularly XBP1 in oestrogen signalling in endometrial and breast cancer.
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http://dx.doi.org/10.1530/ERC-17-0563 | DOI Listing |
Diabetes Obes Metab
January 2025
Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Major Diseases in the Population, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China.
Background: Fatty liver disease may be associated with increased risks of intrahepatic and extrahepatic cancers. Our objective was to investigate associations between new subcategories of steatotic liver disease (SLD) recently proposed by nomenclature consensus group and cancer risk.
Methods: A total of 283 238 participants from the UK Biobank were included.
Curr Mol Med
January 2025
Department of Laboratory, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran.
Long non-coding RNAs (lncRNAs) play vital roles in the development and progression of various tumors through multiple mechanisms. Among these, HOTTIP (HOXA transcript at the distal tip) stands out as an intriguing candidate with diverse functions in several malignancies, including breast cancer and gynecologic cancers such as ovarian, cervical, and endometrial cancers, which are significant global health concerns. HOTTIP interacts with key signaling pathways associated with these cancers, including Wnt/β-catenin, PI3K/AKT, and MEK/ERK pathways, enhancing their activation and downstream effects.
View Article and Find Full Text PDFGeroscience
January 2025
Dept. of Bioinformatics, Semmelweis University, 1094, Budapest, Hungary.
Glucagon-like peptide-1 receptor (GLP-1R) agonists, such as exenatide (Byetta, Bydureon), liraglutide (Victoza, Saxenda), albiglutide (Tanzeum), dulaglutide (Trulicity), lixisenatide (Lyxumia, Adlyxin), semaglutide (Ozempic, Rybelsus, Wegovy), and tirzepatide (Mounjaro, Zepbound), are widely used for the treatment of type 2 diabetes mellitus (T2DM) and obesity. While these agents are well known for their metabolic benefits, there is growing interest in their potential effects on cancer biology. However, the role of GLP-1R agonists in cancer remains complex and not fully understood, particularly across different tumor types.
View Article and Find Full Text PDFChem Biodivers
January 2025
Department of Pharmacy, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, Dhaka, Bangladesh.
Hinokitiol (HK), a monoterpenoid that naturally occurs in plants belonging to the Cupressaceae family, possesses important biological activities, including an anticancer effect. This review summarizes its anticancer potential and draws possible molecular interventions. In addition, it evaluates the biopharmaceutical, toxicological properties, and clinical application of HK to establish its viability for future advancement as a dependable anticancer medication.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Obstetrics and Gynecology, Mianyang Central Hospital, University of Electronic Science and Technology of China, Mianyang, 621000, Sichuan, China.
Objective Endometrial lesions are a frequent complication following breast cancer, and current diagnostic tools have limitations. This study aims to develop a machine learning-based nomogram model for predicting the early detection of endometrial lesions in patients. The model is designed to assess risk and facilitate individualized treatment strategies for premenopausal breast cancer patients.
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