scholarly journals PTEN Takes Center Stage in Cancer Stem Cell Research, Works As Tumor Suppressor

2006 ◽  
Vol 98 (12) ◽  
pp. 808-809 ◽  
Author(s):  
Karyn Hede
2018 ◽  
Author(s):  
Deli Hong ◽  
Andrew J. Fritz ◽  
Kristiaan H. Finstad ◽  
Mark P. Fitzgerald ◽  
Adam L. Viens ◽  
...  

SummaryRecent studies have revealed that mutations in the transcription factor Runx1 are prevalent in breast tumors. Yet, how loss of Runx1 contributes to breast cancer (BCa) remains unresolved. We demonstrate for the first time that Runx1 represses the breast cancer stem cell (BCSC) phenotype and consequently, functions as a tumor suppressor in breast cancer. Runx1 ectopic expression in MCF10AT1 and MCF10CA1a BCa cells reduces (60%) migration, invasion and in vivo tumor growth in mouse mammary fat pad (P<0.05). Runx1 is decreased in BCSCs, and overexpression of Runx1 suppresses tumorsphere formation and reduces the BCSC population. Furthermore, Runx1 inhibits Zeb1 expression, while Runx1 depletion activates Zeb1 and the epithelial-mesenchymal transition. Mechanistically Runx1 functions as a tumor suppressor in breast cancer through repression of cancer stem cell activity. This key regulation of BCSCs by Runx1 may be shared in other epithelial carcinomas, highlighting the importance of Runx1 in solid tumors.


2013 ◽  
Vol 108 (3) ◽  
pp. 388-396 ◽  
Author(s):  
Rebecca Bütof ◽  
Anna Dubrovska ◽  
Michael Baumann

2016 ◽  
Vol 37 ◽  
pp. 83-92 ◽  
Author(s):  
Shu-pei Qiao ◽  
Yu-fang Zhao ◽  
Chun-feng Li ◽  
Yan-bin Yin ◽  
Qing-yuan Meng ◽  
...  

2009 ◽  
Vol 27 (1) ◽  
pp. 44-46 ◽  
Author(s):  
John E Dick

2021 ◽  
Author(s):  
Kirill Borziak ◽  
Irena Parvanova ◽  
Joseph Finkelstein

Recent studies demonstrated that comparative analysis of stem cell research data sets originating from multiple studies can produce new information and help with hypotheses generation. Effective approaches for incorporating multiple diverse heterogeneous data sets collected from stem cell projects into a harmonized project-based framework have been lacking. Here, we provide an intelligent informatics solution for integrating comprehensive characterizations of stem cells with research subject and project outcome information. Our platform is the first to seamlessly integrate information from iPSCs and cancer stem cell research into a single platform, using a multi-modular common data element framework. Heterogeneous data is validated using predefined ontologies and stored in a relational database, to ensure data quality and ease of access. Testing was performed using 103 published, publicly-available iPSC and cancer stem cell projects conducted in clinical, preclinical and in vitro evaluations. We validated the robustness of the platform, by seamlessly harmonizing diverse data elements, and demonstrated its potential for knowledge generation through the aggregation and harmonization of data. Future aims of this project include increasing the database size using crowdsourcing and natural language processing functionalities. The platform is publicly available at https://remedy.mssm.edu/.


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