Epigenetic instability may alter cell state transitions and anticancer drug resistance

Area of Science:

• Oncology
• Epigenetics
• Computational Biology

Background:

• Drug resistance is a major challenge in anti-cancer therapy, leading to treatment failure.
• Cancer cells can adapt to targeted therapies, developing drug-resistant states.
• Cellular state plasticity is a potential target for overcoming drug resistance.

Purpose of the Study:

• To investigate the role of cell state and epigenetic instability in the development of anticancer drug resistance.
• To develop computational models simulating cell state dynamics and drug resistance.
• To evaluate the potential of epigenetic modifications to mitigate drug resistance.

Main Methods:

• Developed two stochastic cell state models and an integrated stochastic-deterministic model.
• Modeled transcriptionally-permissive and -restrictive cell states.
• Simulated the impact of varying levels of epigenetic instability on drug-resistant populations and MGMT dynamics.

Main Results:

• Moderate epigenetic instability reduced drug-resistant populations by ~60%; high instability reduced them by ~90%.
• Epigenetic instability decreased MGMT production, increasing O6mG adducts after temozolomide (TMZ) treatment.
• A decrease in MGMT correlated with increased O6mG adducts under a multi-dose TMZ regimen.

Conclusions:

• Epigenetic instability can significantly reduce drug-resistant cancer cell populations.
• Targeting epigenetic instability may be a viable strategy to overcome resistance to therapies like TMZ.
• Epigenetic modifier therapy could be a promising approach to enhance anti-cancer drug efficacy.