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Impact of Resistance On Treatment Failure in Metastatic Prostate Cancer Patients

M Turk1*, D Valentinuzzi2, A Roth3, R Jeraj1,2,3, (1) Faculty of Mathematics and Physics, University of Ljubljana,Ljubljana, SI, (2) Jozef Stefan Institute, Ljubljana, SI (3) University of Wisconsin, Madison, WI

Presentations

(Sunday, 7/12/2020)   [Eastern Time (GMT-4)]

Room: AAPM ePoster Library

Purpose: response to systemic therapies is affected by evolution of resistance to a particular treatment. We aimed to evaluate impact of resistance on treatment response in metastatic prostate cancer (mPC) with a computational model.


Methods: population model, simulating dynamics of drug-sensitive and drug-resistant cells was used. Resistance was described with two model parameters, quantifying transition between drug-sensitive and drug-resistant cells, and proportion of intrinsically drug-resistant cells (IR), which was varying between lesions. The model was benchmarked with metastatic burden, extracted from 18F-NaF PET/CT scans of seven mPC patients receiving enzalutamide, acquired at baseline, month 3, and at the time of disease progression or two years (t?). Simulated lesions were considered to be correctly described, if their treatment response was correctly classified in treatment response categories. Time to treatment failure, defined as the time (t?) when lesion consists of only drug-resistant cells and heterogeneity of t? within a patient, defined with minimum and maximum t?, were calculated. The correlation between t? and IR was assessed.


Results: month 3 and at t?, the model correctly classified 93% and 70% of lesions in treatment response categories, respectively. Median IR across lesions was 0.09 (range: 0-1), with median variance of IR within a patient 0.03 (range: 0.00-0.14). Median t? between patients was 5.9 months (range: 5.3-6.4 months). Range of minimal t? and maximal t? was 0.7-2 months and 5.7-24.5 months, respectively. In 4/7 of patients, all lesions had t? lower than t?. t? had a correlation coefficient of 0.41(p<0.001) with IR.


Conclusion: modelling revealed that treatment failure is strongly affected by the proportion of intrinsically drug-resistant cells. According to model results, in some patients, for all lesions treatment with enzalutamide fails before clinical evidence of disease progression. In these patients, a change of therapy should be considered.

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