Tumor metastasis remains an obstacle in cancer treatment and is responsible for most cancer-related deaths. Nm23-H1 is one of the first metastasis suppressor proteins discovered with the ability to inhibit metastasis of many cancers including breast, colon, and liver cancer. Although loss of Nm23-H1 is observed in aggressive cancers and correlated with metastatic potential, little is known regarding the mechanisms that regulate its cellular level. Here, we examined the mechanisms that control Nm23-H1 expression in breast cancer cells. Initial studies in aggressive MDA-MB-231 cells (expressing low Nm23-H1) and less invasive MCF-7 cells (expressing high Nm23-H1) revealed that mRNA levels correlated with protein expression, suggesting that transcriptional mechanisms may control Nm23-H1 expression. Truncational analysis of the Nm23-H1 promoter revealed a proximal and minimal promoter that harbor putative binding sites for transcription factors including CTCF and EGR1. CTCF and EGR1 induced Nm23-H1 expression and reduced cell migration of MDA-MB-231 cells. Moreover, CTCF and EGR1 were recruited to the Nm23-H1 promoter in MCF-7 cells and their expression correlated with Nm23-H1 levels. This study indicates that loss of Nm23-H1 in aggressive breast cancer is apparently caused by downregulation of CTCF and EGR1, which potentially drive Nm23-H1 expression to promote a less invasive phenotype.
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http://dx.doi.org/10.1038/s41598-020-79869-9 | DOI Listing |
medRxiv
November 2024
Center for Cardiovascular Research, Division of Cardiology, Department of Medicine, Washington University School of Medicine, Saint Louis, MO, 63110, USA.
Cancers (Basel)
March 2022
Department of Surgery, Open NBI Convergence Technology Research Laboratory, Severance Hospital, Yonsei Cancer Center, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea.
Notch signaling is a druggable target in high-grade serous ovarian cancers; however, its complexity is not clearly understood. Recent revelations of the biological roles of lncRNAs have led to an increased interest in the oncogenic action of lncRNAs in various cancers. In this study, we performed in silico analyses using The Cancer Genome Atlas data to discover novel Notch-related lncRNAs and validated our transcriptome data via NOTCH1/3 silencing in serous ovarian cancer cells.
View Article and Find Full Text PDFApoptosis
April 2022
Shandong Provincial Key Laboratory of Animal Cells and Developmental Biology, School of Life Science, Shandong University, Qingdao, 266237, People's Republic of China.
Myocardial apoptosis induced by myocardial ischemia and hyperlipemia are the main causes of high mortality of cardiovascular diseases. It is not clear whether there is a common mechanism responsible for these two kinds of cardiomyocyte apoptosis. Previous studies demonstrated that early growth response protein 1 (EGR-1) has a pro-apoptotic effect on cardiomyocytes under various stress conditions.
View Article and Find Full Text PDFSci Rep
January 2021
Division of Life Science and the Biotechnology Research Institute, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong.
Tumor metastasis remains an obstacle in cancer treatment and is responsible for most cancer-related deaths. Nm23-H1 is one of the first metastasis suppressor proteins discovered with the ability to inhibit metastasis of many cancers including breast, colon, and liver cancer. Although loss of Nm23-H1 is observed in aggressive cancers and correlated with metastatic potential, little is known regarding the mechanisms that regulate its cellular level.
View Article and Find Full Text PDFPhysiol Genomics
November 2019
Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, Michigan.
Genetics of multiple sclerosis (MS) are highly polygenic with few insights into mechanistic associations with pathology. In this study, we assessed MS genetics through linkage disequilibrium and missense variant interpretation to yield a MS gene network. This network of 96 genes was taken through pathway analysis, tissue expression profiles, single cell expression segregation, expression quantitative trait loci (eQTLs), genome annotations, transcription factor (TF) binding profiles, structural genome looping, and overlap with additional associated genetic traits.
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