scholarly journals Epigenetic instability may alter cell state transitions and anticancer drug resistance

2021 ◽  
Vol 17 (8) ◽  
pp. e1009307
Author(s):  
Anshul Saini ◽  
James M. Gallo

Drug resistance is a significant obstacle to successful and durable anti-cancer therapy. Targeted therapy is often effective during early phases of treatment; however, eventually cancer cells adapt and transition to drug-resistant cells states rendering the treatment ineffective. It is proposed that cell state can be a determinant of drug efficacy and manipulated to affect the development of anticancer drug resistance. In this work, we developed two stochastic cell state models and an integrated stochastic-deterministic model referenced to brain tumors. The stochastic cell state models included transcriptionally-permissive and -restrictive states based on the underlying hypothesis that epigenetic instability mitigates lock-in of drug-resistant states. When moderate epigenetic instability was implemented the drug-resistant cell populations were reduced, on average, by 60%, whereas a high level of epigenetic disruption reduced them by about 90%. The stochastic-deterministic model utilized the stochastic cell state model to drive the dynamics of the DNA repair enzyme, methylguanine-methyltransferase (MGMT), that repairs temozolomide (TMZ)-induced O6-methylguanine (O6mG) adducts. In the presence of epigenetic instability, the production of MGMT decreased that coincided with an increase of O6mG adducts following a multiple-dose regimen of TMZ. Generation of epigenetic instability via epigenetic modifier therapy could be a viable strategy to mitigate anticancer drug resistance.

2020 ◽  
Author(s):  
Anshul Saini ◽  
James M. Gallo

AbstractDrug resistance is a significant obstacle to successful and durable anti-cancer therapy. Targeted therapy is often effective during early phases of treatment; however, eventually cancer cells adapt and transition to drug-resistant cells states rendering the treatment ineffective. It is proposed that cell state can be a determinant of drug efficacy and manipulated to affect the development of anticancer drug resistance. In this work, we developed two stochastic cell state models – referenced to brain tumors - that included transcriptionally-permissive and -restrictive states based on the underlying hypothesis that epigenetic instability mitigates lock-in of drug-resistant states. One model used single-step state transitions, whereas the other considered a multi-step process to lock-in drug resistance. The latter model showed that with moderate epigenetic instability the drug-resistant cell populations were reduced, on average, by 60%, whereas a high level of epigenetic disruption reduced them by about 90%. Generation of epigenetic instability via epigenetic modifier therapy could be a viable strategy to mitigate anticancer drug resistance.


2004 ◽  
Vol 484 (2-3) ◽  
pp. 333-339 ◽  
Author(s):  
Emiko Asakura ◽  
Hironao Nakayama ◽  
Masami Sugie ◽  
Ying Lan Zhao ◽  
Masayuki Nadai ◽  
...  

2021 ◽  
Author(s):  
Yi Shi ◽  
Xiaojiang Wang ◽  
Qiong Zhu ◽  
Gang Chen

Abstract Background: Sorafenib is the first molecular-targeted drug for the treatment of advanced hepatocellular carcinoma (HCC). However, its treatment efficiency decreases after a short period of time because of the development of drug resistance. This study investigates the role of key genes in regulating sorafenib-resistance in hepatocellular carcinoma and elucidates the mechanism of drug resistance. Methods: The HCC HepG2 cells were used to generate a sorafenib-resistant cell model by culturing the cells in gradually increasing concentration of sorafenib. RNA microarray was applied to profile gene expression and screen key genes associated with sorafenib resistance. Specific targets were knockdown in sorafenib-resistant HepG2 cells for functional studies. The HCC model was established in ACI rats using Morris hepatoma3924A cells to validate selected genes associated with sorafenib resistance in vivo. Results: The HepG2 sorafenib-resistant cell model was successfully established. The IC50 of sorafenib was 9.988mM in HepG2 sorafenib-resistant cells. A total of 35 up-regulated genes were detected by expression profile chip. High-content screening technology was used and a potential drug-resistant gene RPL28 was filtered out. After knocking down of RPL28 in HepG2 sorafenib-resistant cells, the results of cell proliferation and apoptosis illustrated that RPL28 is the key drug-resistant gene in the cells. Furthermore, it was found that both RNA and protein expression of RPL28 increased in HepG2 sorafenib-resistant specimens of Morris Hepatoma rats. In addition, the expression of functional proteins Ki-67 increased in sorafenib-resistant cells. Conclusion: Our study suggested that RPL28 was a key gene for sorafenib resistance in HCC both in vitro and in vivo.


2011 ◽  
Vol 34 (3) ◽  
pp. 433-435 ◽  
Author(s):  
Yoshihiko Shibayama ◽  
Kou Nakano ◽  
Hiroshi Maeda ◽  
Miyuki Taguchi ◽  
Ryuji Ikeda ◽  
...  

2020 ◽  
Vol 49 ◽  
pp. 100671 ◽  
Author(s):  
Xin Cao ◽  
Jiayun Hou ◽  
Quanlin An ◽  
Yehuda G. Assaraf ◽  
Xiangdong Wang

2003 ◽  
Vol 64 (2) ◽  
pp. 259-268 ◽  
Author(s):  
Paul W. Schenk ◽  
Mariël Brok ◽  
Antonius W. M. Boersma ◽  
Jourica A. Brandsma ◽  
Hans Den Dulk ◽  
...  

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