Patient-Derived Xenografts and Organoids Recapitulate Castration-Resistant Prostate Cancer with Sustained Androgen Receptor Signaling

Darolutamide Added to Docetaxel Augments Antitumor Effect in Models of Prostate Cancer through Cell Cycle Arrest at the G1-S Transition

Resistance to taxane chemotherapy is frequently observed in metastatic prostate cancer. The androgen receptor (AR) is a major driver of prostate cancer and a key regulator of the G1-S cell-cycle checkpoint, promoting cancer cell proliferation by irreversible passage to the S-phase. We hypothesized that AR signaling inhibitor (ARSi) darolutamide in combination with docetaxel could augment antitumor effect by impeding the proliferation of taxane-resistant cancer cells. We monitored cell viability in organoids, tumor volume, and PSA secretion in patient-derived xenografts (PDX) and analyzed cell cycle and signaling pathway alterations. Combination treatment increased antitumor effect in androgen-sensitive, AR-positive prostate cancer organoids and PDXs. Equally beneficial effects of darolutamide added to docetaxel were observed in a castration-resistant model, progressive on docetaxel, enzalutamide, and cabazitaxel. In vitro studies showed that docetaxel treatment with simultaneous darolutamide resulted in a reduction of cells entering the S-phase in contrast to only docetaxel. Molecular analysis in the prostate cancer cell line LNCaP revealed an upregulation of cyclin-dependent kinase inhibitor p21, supporting blockade of S-phase entry and cell proliferation. Our results provide a preclinical support for combining taxanes and darolutamide as a multimodal treatment strategy in patients with metastatic prostate cancer progressive on ARSi and taxane chemotherapy.

Defining the challenges and opportunities for using patient-derived models in prostate cancer research

BACKGROUND

There are relatively few widely used models of prostate cancer compared to other common malignancies. This impedes translational prostate cancer research because the range of models does not reflect the diversity of disease seen in clinical practice. In response to this challenge, research laboratories around the world have been developing new patient-derived models of prostate cancer, including xenografts, organoids, and tumor explants.

METHODS

In May 2023, we held a workshop at the Monash University Prato Campus for researchers with expertise in establishing and using a variety of patient-derived models of prostate cancer. This review summarizes our collective ideas on how patient-derived models are currently being used, the common challenges, and future opportunities for maximizing their usefulness in prostate cancer research.

RESULTS

An increasing number of patient-derived models for prostate cancer are being developed. Despite their individual limitations and varying success rates, these models are valuable resources for exploring new concepts in prostate cancer biology and for preclinical testing of potential treatments. Here we focus on the need for larger collections of models that represent the changing treatment landscape of prostate cancer, robust readouts for preclinical testing, improved in vitro culture conditions, and integration of the tumor microenvironment. Additional priorities include ensuring model reproducibility, standardization, and replication, and streamlining the exchange of models and data sets among research groups.

CONCLUSIONS

There are several opportunities to maximize the impact of patient-derived models on prostate cancer research. We must develop large, diverse and accessible cohorts of models and more sophisticated methods for emulating the intricacy of patient tumors. In this way, we can use the samples that are generously donated by patients to advance the outcomes of patients in the future.

Engineering prostate cancer in vitro: what does it take?

A key challenge in the clinical management and cause of treatment failure of prostate cancer (PCa) is its molecular, cellular and clinical heterogeneity. Modelling systems that fully recapitulate clinical diversity and resistant phenotypes are urgently required for the development of successful personalised PCa therapies. The advent of the three-dimensional (3D) organoid model has revolutionised preclinical cancer research through reflecting heterogeneity and offering genomic and environmental manipulation that has opened up unparalleled opportunities for applications in disease modelling, high-throughput drug screening and precision medicine. Despite these remarkable achievements of organoid technology, several shortcomings in emulating the complex tumor microenvironment and dynamic process of metastasis as well as the epigenome profile limit organoids achieving true in vivo functionality. Technological advances in tissue engineering have enabled the development of innovative tools to facilitate the design of improved 3D cancer models. In this review, we highlight the current in vitro 3D PCa models with a special focus on organoids and discuss engineering approaches to create more physiologically relevant PCa organoid models and maximise their translational relevance that ultimately will help to realise the transformational power of precision medicine.

The future of patient-derived xenografts in prostate cancer research

Patient-derived xenografts (PDXs) are generated by engrafting human tumours into mice. Serially transplantable PDXs are used to study tumour biology and test therapeutics, linking the laboratory to the clinic. Although few prostate cancer PDXs are available in large repositories, over 330 prostate cancer PDXs have been established, spanning broad clinical stages, genotypes and phenotypes. Nevertheless, more PDXs are needed to reflect patient diversity, and to study new treatments and emerging mechanisms of resistance. We can maximize the use of PDXs by exchanging models and datasets, and by depositing PDXs into biorepositories, but we must address the impediments to accessing PDXs, such as institutional, ethical and legal agreements. Through collaboration, researchers will gain greater access to PDXs representing diverse features of prostate cancer.

A new tumorgraft panel to accelerate precision medicine in prostate cancer

Background

Despite the significant advances in the management of advanced prostate cancer (PCa), metastatic PCa is currently considered incurable. For further investigations in precision treatment, the development of preclinical models representing the complex prostate tumor heterogeneity are mandatory. Accordingly, we aimed to establish a resource of patient-derived xenograft (PDX) models that exemplify each phase of this multistage disease for accurate and rapid evaluation of candidate therapies.

Methods

Fresh tumor samples along with normal corresponding tissues were obtained directly from patients at surgery. To ensure that the established models reproduce the main features of patient's tumor, both PDX tumors at multiple passages and patient's primary tumors, were processed for histological characteristics. STR profile analyses were also performed to confirm patient identity. Finally, the responses of the PDX models to androgen deprivation, PARP inhibitors and chemotherapy were also evaluated.

Results

In this study, we described the development and characterization of 5 new PDX models of PCa. Within this collection, hormone-naïve, androgen-sensitive and castration-resistant (CRPC) primary tumors as well as prostate carcinoma with neuroendocrine differentiation (CRPC-NE) were represented. Interestingly, the comprehensive genomic characterization of the models identified recurrent cancer driver alterations in androgen signaling, DNA repair and PI3K, among others. Results were supported by expression patterns highlighting new potential targets among gene drivers and the metabolic pathway. In addition, in vivo results showed heterogeneity of response to androgen deprivation and chemotherapy, like the responses of patients to these treatments. Importantly, the neuroendocrine model has been shown to be responsive to PARP inhibitor.

Conclusion

We have developed a biobank of 5 PDX models from hormone-naïve, androgen-sensitive to CRPC primary tumors and CRPC-NE. Increased copy-number alterations and accumulation of mutations within cancer driver genes as well as the metabolism shift are consistent with the increased resistance mechanisms to treatment. The pharmacological characterization suggested that the CRPC-NE could benefit from the PARP inhibitor treatment. Given the difficulties in developing such models, this relevant panel of PDX models of PCa will provide the scientific community with an additional resource for the further development of PDAC research.

Viability Analysis and High-Content Live-Cell Imaging for Drug Testing in Prostate Cancer Xenograft-Derived Organoids

Tumor organoids have been pushed forward as advanced model systems for in vitro oncology drug testing, with the eventual goal to direct personalized cancer treatments. However, drug testing efforts suffer from a large variation in experimental conditions for organoid culturing and organoid treatment. Moreover, most drug tests are restricted to whole-well viability as the sole read-out, thereby losing important information about key biological aspects that might be impacted due to the use of administered drugs. These bulk read-outs also discard potential inter-organoid heterogeneity in drug responses. To tackle these issues, we developed a systematic approach for processing organoids from prostate cancer (PCa) patient-derived xenografts (PDXs) for viability-based drug testing and identified essential conditions and quality checks for consistent results. In addition, we generated an imaging-based drug testing procedure using high-content fluorescence microscopy in living PCa organoids to detect various modalities of cell death. Individual organoids and cell nuclei in organoids were segmented and quantified using a dye combination of Hoechst 33342, propidium iodide and Caspase 3/7 Green, allowing the identification of cytostatic and cytotoxic treatment effects. Our procedures provide important insights into the mechanistic actions of tested drugs. Moreover, these methods can be adapted for tumor organoids originating from other cancer types to increase organoid-based drug test validity, and ultimately, accelerate clinical implementation.