IMR Press / FBL / Volume 19 / Issue 7 / DOI: 10.2741/4264

Frontiers in Bioscience-Landmark (FBL) is published by IMR Press from Volume 26 Issue 5 (2021). Previous articles were published by another publisher on a subscription basis, and they are hosted by IMR Press on as a courtesy and upon agreement with Frontiers in Bioscience.

Open Access Article
Insights into the next generation of cancer stem cell research
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1 Cancer Signaling Laboratory 1, Department of Pathology, The University of Melbourne, Parkville, VIC 3010, AUSTRALIA
Academic Editor:Stavros Taraviras
Front. Biosci. (Landmark Ed) 2014, 19(7), 1015–1027;
Published: 1 June 2014
(This article belongs to the Special Issue Insights into the next generation of cancer stem cell research)

The understanding of how cancer stem cells (CSCs) or tumor-initiating cells (TICs) behave is important in understanding how tumors are initiated and how they recur following initial treatment. More specifically to understand how CSCs behave, the different signaling mechanisms orchestrating their growth, cell cycle dynamics, differentiation, trans-differentiation and survival following cytotoxic challenges need to be deciphered. Ultimately this will advance the ability to predict how these cells will behave in individual patients and under different therapeutic conditions. Second or next-generation sequencing (NGS) capabilities have provided researchers a window into the molecular and genetic clockwork of CSCs at an unprecedented resolution and depth, with throughput capabilities allowing sequencing of hundreds of samples in relatively short timeframes and at relatively modest costs More specifically NGS gives us the ability to accurately determine the genomic and transcriptomic nature of CSCs. These technologies and the publicly available cancer genome databases, together with the ever increasing computing power available to researchers locally or via cloud-based servers are changing the way biomedical cancer research is approached.

Stem Cell
Cancer Stem Cells
Gene Expression
Next Generation Sequencing
Systems Biology
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