scholarly journals CD66c is a novel marker for colorectal cancer stem cell isolation, and its silencing halts tumor growth in vivo

Cancer ◽  
2012 ◽  
Vol 119 (4) ◽  
pp. 729-738 ◽  
Author(s):  
Marica Gemei ◽  
Peppino Mirabelli ◽  
Rosa Di Noto ◽  
Claudia Corbo ◽  
Antonino Iaccarino ◽  
...  
2021 ◽  
pp. 2100985
Author(s):  
Yuanyuan Jia ◽  
Peiliang Shen ◽  
Tao Yan ◽  
Weijia Zhou ◽  
Jia Sun ◽  
...  

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.


2019 ◽  
Vol 15 (6) ◽  
pp. 755-773 ◽  
Author(s):  
Heena Jariyal ◽  
Chanchal Gupta ◽  
Vedika Sandeep Bhat ◽  
Jayant Ramakant Wagh ◽  
Akshay Srivastava

2020 ◽  
Vol 147 (6) ◽  
pp. 1694-1706 ◽  
Author(s):  
Alessia Brossa ◽  
Valentina Fonsato ◽  
Cristina Grange ◽  
Stefania Tritta ◽  
Marta Tapparo ◽  
...  

2014 ◽  
Author(s):  
Zoltan Wiener ◽  
Ville Hyvönen ◽  
Jenny Högström ◽  
Tanja Holopainen ◽  
Arja Band ◽  
...  

2015 ◽  
Author(s):  
Jan T Poleszczuk ◽  
Paul Macklin ◽  
Heiko Enderling

Computational modeling of tumor growth has become an invaluable tool to simulate complex cell-cell interactions and emerging population-level dynamics. Agent-based models are commonly used to describe the behavior and interaction of individual cells in different environments. Behavioral rules can be informed and calibrated by in vitro assays, and emerging population-level dynamics may be validated with both in vitro and in vivo experiments. Here, we describe the design and implementation of a lattice-based agent-based model of cancer stem cell driven tumor growth.


2012 ◽  
Vol 48 ◽  
pp. 122 ◽  
Author(s):  
Q. Xu ◽  
V.N. Kolev ◽  
C.M. Vidal ◽  
I.M. Shapiro ◽  
J.E. Ring ◽  
...  

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