Insulin, an established mitogen that promotes breast cancer cell growth, has been implicated in the link between obesity and an increased risk of breast cancer. However, the current understanding of signaling pathways that mediate the mitogenic action of insulin remains incomplete. Here we provide the first evidence that insulin is capable of activating both sphingosine kinase (SphK) 1 and SphK 2, two isoenzymes that often exhibit opposing effects in the regulation of cell survival and growth. Insulin stimulates the phosphorylation of both SphK1 and SphK2 in a similar time- and dose-dependent manner. Interestingly, both isoenzymes are responsible equally for insulin-induced cell cycle progression and proliferation of MCF7 breast cancer cells, although SphK1 and SphK2 display different roles in mediating insulin-induced ERK1/2 and Akt activation. Moreover, the sphingosine 1-phosphate receptor 3, a key component of the SphK signaling system, is important for insulin-mediated mitogenic action in breast cancer cells. Furthermore, insulin receptor and type 1 IGF receptor (IGF1R) are responsible for the insulin-promoted mitogenic action on MCF7 breast cancer cells. Notably, IGF1R mediates insulin-stimulated phosphorylation of both SphK1 and SphK2, whereas insulin receptor is involved only in SphK1, but not SphK2, activation. Collectively the current study illustrates a new signaling system controlling the mitogenic action of insulin in breast cancer cells, suggesting a new strategy that pharmaceutically targets both isoenzymes of SphK for the management of breast cancer.
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http://dx.doi.org/10.1210/me.2013-1237 | DOI Listing |
IUBMB Life
January 2025
Precision Medicine Laboratory, School of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang, China.
Triple-negative breast cancer (TNBC) remains a significant global health challenge, emphasizing the need for precise identification of patients with specific therapeutic targets and those at high risk of metastasis. This study aimed to identify novel therapeutic targets for personalized treatment of TNBC patients by elucidating their roles in cell cycle regulation. Using weighted gene co-expression network analysis (WGCNA), we identified 83 hub genes by integrating gene expression profiles with clinical pathological grades.
View Article and Find Full Text PDFCancer
February 2025
General Medicine Service, VA Puget Sound Health Care System, Seattle, Washington, USA.
Background: Breast cancer screening (BCS) inequities are evident at national and local levels, and many health systems want to address these inequities, but may lack data about contributing factors. The objective of this study was to inform health system interventions through an exploratory analysis of potential multilevel contributors to BCS inequities using health system data.
Methods: The authors conducted a cross-sectional analysis within a large academic health system including 19,774 individuals who identified as Black (n = 1445) or White (n = 18,329) race and were eligible for BCS.
J Adv Nurs
January 2025
Anesthesiology Department, Hebei Province Cangzhou Hospital of Integrated Traditional and Western Medicine, Cangzhou, Hebei, China.
Cancer
February 2025
Departmental Unit of Molecular and Genomic Diagnostics, Genomics Core Facility, G-STeP, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy.
Background: To date, 11 DNA polymerase epsilon (POLE) pathogenic variants have been declared "hotspot" mutations. Patients with endometrial cancer (EC) characterized by POLE hotspot mutations (POLEmut) have exceptional survival outcomes. Whereas international guidelines encourage deescalation of adjuvant treatment in early-stage POLEmut EC, data regarding safety in POLEmut patients with unfavorable characteristics are still under investigation.
View Article and Find Full Text PDFStat Med
February 2025
Department of Mathematical Sciences, University of Texas at Dallas, Richardson, Texas, USA.
Multi-gene panel testing allows efficient detection of pathogenic variants in cancer susceptibility genes including moderate-risk genes such as ATM and PALB2. A growing number of studies examine the risk of breast cancer (BC) conferred by pathogenic variants of these genes. A meta-analysis combining the reported risk estimates can provide an overall estimate of age-specific risk of developing BC, that is, penetrance for a gene.
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