Dynamical thermal dose models and dose time-profile effects.

Area of Science:

• Biophysics
• Cell Biology
• Mathematical Modeling

Background:

• Dose-effect models predict cell survival under stress.
• The CEM43 thermal dose model is a long-standing benchmark for hyperthermia.
• Regulatory network models offer alternative mechanistic approaches.

Purpose of the Study:

• To experimentally validate mechanistic models against the CEM43 model for hyperthermia.
• To assess the reliability of mechanistic models for time-asymmetric thermal dose protocols.
• To investigate the predictive accuracy of different hyperthermia models.

Main Methods:

• Experimental testing of HeLa cell cultures under controlled hyperthermia conditions.
• Utilizing dual staining (Annexin V-FITC and propidium iodide) to quantify cell death.
• Comparing survival data against predictions from CEM43 and a regulatory network model.

Main Results:

• Hyperthermia protocols with a fast temperature rise and slow decay were significantly more lethal than the inverse.
• HeLa cell survival experiments confirmed predictions of the network model over the CEM43 model.
• A notable difference in lethality (up to twofold) was observed between asymmetric profiles.

Conclusions:

• Mechanistic models, specifically network models, offer improved reliability for dynamic hyperthermia protocols.
• Limited cellular repair capacity is a key factor driving dose-asymmetry effects in thermal stress.
• A simplified nonlinear dynamic equation can refine thermal dose calculations for dynamic protocols.