Related Experiment Video
Updated: Jul 20, 2026
A Bioluminescent and Fluorescent Orthotopic Syngeneic Murine Model of Androgen-dependent and Castration-resistant Prostate Cancer
Published on: March 6, 2018
Optimizing heat shock protein expression induced by prostate cancer laser therapy through predictive computational
Marissa Nichole Rylander1, Yusheng Feng, Yongjie Zhang
1Virginia Tech, Department of Mechanical Engineering and School of Biomedical Engineering and Sciences (SBES), Corporate Research Center, Research Building 15 MC 0493, 1880 Pratt Drive, Blacksburg, Virginia 24061, USA. mnr@vt.edu
Hyperthermia treatment for cancer can be improved by predicting heat shock protein (HSP) expression. A new computational model accurately forecasts temperature and HSP levels, optimizing thermal therapy for better prostate cancer outcomes.
Area of Science:
- Oncology
- Biomedical Engineering
- Computational Modeling
Background:
- Thermal therapy efficacy is limited by heat shock protein (HSP) induction, which increases tumor cell survival and resistance to other cancer treatments.
- Understanding thermally induced HSP expression is crucial for optimizing hyperthermia treatment plans and predicting tissue response.
Purpose of the Study:
- To develop a computational model for predicting temperature, HSP27 and HSP70 expression, and tissue damage during laser-induced hyperthermia in prostate cancer.
- To integrate HSP expression kinetics and injury data into a predictive model for thermal therapies.
Main Methods:
- A treatment planning computational model was created using measured HSP27 and HSP70 expression kinetics and injury data from normal and cancerous prostate cells and tumors.
- The model predicts temperature, HSP27 and HSP70 expression, and damage fraction distributions associated with laser heating.
- An Arrhenius damage model was formulated based on experimental data.
Main Results:
- The computational model demonstrated high accuracy, with correlation coefficients of 0.98 for temperature and 0.99 for HSP27 and HSP70 expression between measured and predicted values.
- The model successfully predicts HSP expression and tissue injury distributions.
- This represents the first predictive model for HSP expression in the context of thermal therapy.
Conclusions:
- The developed treatment planning model accurately predicts thermal effects and HSP expression in prostate tissues.
- Incorporating this model into prostate cancer thermal therapy design can optimize treatment outcomes by controlling HSP expression and injury.
- This approach allows for better prediction of overall tissue response to hyperthermia.
