Europe PMC

This website requires cookies, and the limited processing of your personal data in order to function. By using the site you are agreeing to this as outlined in our privacy notice and cookie policy.

Abstract 


Radiotherapy is the most successful nonsurgical treatment for nasopharyngeal carcinoma (NPC). Despite this, the prognosis remains poor. Although NPCs initially respond well to a full course of radiation, recurrence is frequent. The cancer stem cell (CSC) hypothesis provides a framework for explaining the discrepancy between the response of NPC to therapy and the poor survival rate. In this study, a stem cell-like subpopulation (PKH26+) was identified in NPC cell lines using a label-retention technique. PKH26+ cells were enriched for clonogenicity, sphere formation, side-population cells, and resistance to radiotherapy. Using genomic approaches, we show that the proto-oncogene c-MYC (MYC) regulates radiotolerance through transcriptional activation of CHK1 (CHEK1) and CHK2 (CHEK2) checkpoint kinases through direct binding to the CHK1 and CHK2 promoters. Overexpression of c-MYC in the PKH26+ subpopulation leads to increased expression of CHK1 and CHK2 and subsequent activation of the DNA-damage-checkpoint response, resulting in radioresistance. Furthermore, loss of CHK1 and CHK2 expression reverses radioresistance in PKH26+ (c-MYC high expression) cells in vitro and in vivo. This study elucidates the role of the c-MYC-CHK1/CHK2 axis in regulating DNA-damage-checkpoint responses and stem cell characteristics in the PKH26+ subpopulation. Furthermore, these data reveal a potential therapeutic application in reversal of radioresistance through inhibition of the c-MYC-CHK1/CHK2 pathway.

Citations & impact 


Impact metrics

Jump to Citations
Jump to Data

Citations of article over time

Alternative metrics

Altmetric item for https://www.altmetric.com/details/1167661
Altmetric
Discover the attention surrounding your research
https://www.altmetric.com/details/1167661

Smart citations by scite.ai
Smart citations by scite.ai include citation statements extracted from the full text of the citing article. The number of the statements may be higher than the number of citations provided by EuropePMC if one paper cites another multiple times or lower if scite has not yet processed some of the citing articles.
Explore citation contexts and check if this article has been supported or disputed.
https://scite.ai/reports/10.1158/0008-5472.can-12-1408

Supporting
Mentioning
Contrasting
10
130
0

Article citations


Go to all (143) article citations

Data