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Establishing combination PAC-1 and TRAIL regimens for treating ovarian cancer based on patient-specific pharmacokinetic profiles using in silico clinical trials
  • +4
  • Olivia Cardinal,
  • Chloé Burlot,
  • Yangxin Fu,
  • Powel Crosley,
  • Mary Hitt,
  • Morgan Craig,
  • Adrianne Jenner
Olivia Cardinal
Concordia University
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Chloé Burlot
Université de Lyon
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Yangxin Fu
University of Alberta Faculty of Medicine & Dentistry
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Powel Crosley
University of Alberta Faculty of Medicine & Dentistry
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Mary Hitt
University of Alberta Faculty of Medicine & Dentistry
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Morgan Craig
Sainte-Justine Hospital Pediatric Research Centre

Corresponding Author:[email protected]

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Adrianne Jenner
Queensland University of Technology
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Abstract

Ovarian cancer is commonly diagnosed in its late stages, and new treatment modalities are needed to improve patient outcomes and survival. We have recently established the synergistic effects of combination tumour necrosis factor-related apoptosis-inducing ligand (TRAIL) and procaspase activating compound (PAC-1) therapies in granulosa cell tumours (GCT) of the ovary, a rare form of ovarian cancer, using a mathematical model of the effects of both drugs in a GCT cell line. Here, to understand the mechanisms of combined TRAIL and PAC-1 therapy, study the viability of this treatment strategy, and accelerate preclinical translation, we leveraged our mathematical model in combination with population pharmacokinetics (PopPK) models of both TRAIL and PAC-1 to expand a realistic heterogeneous cohort of virtual patients and optimize treatment schedules. Using this approach, we investigated treatment responses in this virtual cohort and determined optimal therapeutic schedules based on patient-specific pharmacokinetic characteristics. Our results showed that schedules with high initial doses of PAC-1 were required for therapeutic efficacy. Further analysis of individualized regimens revealed two distinct groups of virtual patients within our cohort: one with high PAC-1 elimination, and one with normal PAC-1 elimination. In the high elimination group, high weekly doses of both PAC-1 and TRAIL were necessary for therapeutic efficacy, however virtual patients in this group were predicted to have a worse prognosis when compared to those in the normal elimination group. Thus, PAC-1 pharmacokinetic characteristics, particularly clearance, can be used to identify patients most likely to respond to combined PAC-1 and TRAIL therapy. This work underlines the importance of quantitative approaches in preclinical oncology.
24 Jan 2022Submitted to Computational and Systems Oncology
25 Jan 2022Submission Checks Completed
25 Jan 2022Assigned to Editor
08 Feb 2022Reviewer(s) Assigned
25 Mar 2022Review(s) Completed, Editorial Evaluation Pending
27 Mar 2022Editorial Decision: Revise Major
02 May 20221st Revision Received
03 May 2022Submission Checks Completed
03 May 2022Assigned to Editor
03 May 2022Review(s) Completed, Editorial Evaluation Pending
04 May 2022Reviewer(s) Assigned
19 May 2022Editorial Decision: Accept