Oral 63rd Endocrine Society of Australia Annual Scientific Meeting 2020

Using patient-derived models to systematically identify synergistic drug combinations for advanced prostate cancer (#10)

Nicholas Choo 1 , Laura Porter 1 , Birunthi Niranjan 1 , Jennii Luu 2 , Susanne Ramm 2 , Kaylene Simpson 2 , Mitchell Lawrence 1 , Renea Taylor 3 , Gail Risbridger 1 4
  1. Monash Biomedicine Discovery Institute Cancer Program, Prostate Cancer Research Group, Department of Anatomy and Developmental Biology, Monash University, Clayton, VIC, Australia
  2. Victorian Centre for Functional Genomics, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
  3. Monash Biomedicine Discovery Institute Cancer Program, Prostate Cancer Research Group, Department of Physiology, Monash University, Clayton, VIC, Australia
  4. Melbourne Urological Research Alliance, Monash Biomedicine Discovery Institute Cancer Program, Monash University, Clayton, VIC, Australia

Advanced prostate cancer is typically treated sequentially with monotherapies, usually targeting the androgen receptor (AR). However, this inevitably produces more aggressive, drug-resistant tumours with varying aberrations in the AR pathway or AR loss altogether. Rational combination therapies may improve treatment of diverse phenotypes of prostate cancer. Yet, preclinical testing of new drug combinations is constrained by the paucity of patient-derived models spanning the diversity of prostate cancer, and the lack of methods for using them to assess drug synergy.

To identify effective combination treatments for AR-positive and AR-negative prostate cancer, we aimed to establish new methods for measuring drug synergy with patient-derived models.

We developed conditions to grow cells from patient-derived xenografts (PDXs) from the Melbourne Urological Research Alliance as organoids - 3D cultures embedded in Matrigel. Next, we used organoids to test drug synergy with a novel combination of talazoparib, a PARP inhibitor, and CX-5461, a small molecule that induces DNA damage. Combination therapy significantly decreased organoid viability based on overall metabolic activity. The effect was synergistic as shown with CompuSyn software. Combination therapy also enhanced DNA damage, marked by γH2AX, in AR-positive and AR-negative organoids.

To reveal the full complexity of drug synergy, we devised a novel, automated assay to measure the growth and composition of individual organoids. With segmentation-based analysis of confocal and brightfield microscopy, we showed that talazoparib and CX-5461 consistently and synergistically reduced the area, cellular density and uniformity of organoids.

In conclusion, talazoparib and CX-5461 synergistically inhibit the growth of advanced prostate cancer, regardless of AR expression. These results informed the design of a phase 1 clinical trial. For the first time, this shows that prostate cancer organoids can reveal drug synergy in high-throughput assays. This increases the scale and scope of organoid experiments, accelerating translation of new treatments for prostate cancer.