Towards Best Practice in Establishing Patient-Derived Xenografts

Meningioma animal models: a systematic review and meta-analysis

BACKGROUND

Animal models are widely used to study pathological processes and drug (side) effects in a controlled environment. There is a wide variety of methods available for establishing animal models depending on the research question. Commonly used methods in tumor research include xenografting cells (established/commercially available or primary patient-derived) or whole tumor pieces either orthotopically or heterotopically and the more recent genetically engineered models-each type with their own advantages and disadvantages. The current systematic review aimed to investigate the meningioma model types used, perform a meta-analysis on tumor take rate (TTR), and perform critical appraisal of the included studies. The study also aimed to assess reproducibility, reliability, means of validation and verification of models, alongside pros and cons and uses of the model types.

METHODS

We searched Medline, Embase, and Web of Science for all in vivo meningioma models. The primary outcome was tumor take rate. Meta-analysis was performed on tumor take rate followed by subgroup analyses on the number of cells and duration of incubation. The validity of the tumor models was assessed qualitatively. We performed critical appraisal of the methodological quality and quality of reporting for all included studies.

RESULTS

We included 114 unique records (78 using established cell line models (ECLM), 21 using primary patient-derived tumor models (PTM), 10 using genetically engineered models (GEM), and 11 using uncategorized models). TTRs for ECLM were 94% (95% CI 92-96) for orthotopic and 95% (93-96) for heterotopic. PTM showed lower TTRs [orthotopic 53% (33-72) and heterotopic 82% (73-89)] and finally GEM revealed a TTR of 34% (26-43).

CONCLUSION

This systematic review shows high consistent TTRs in established cell line models and varying TTRs in primary patient-derived models and genetically engineered models. However, we identified several issues regarding the quality of reporting and the methodological approach that reduce the validity, transparency, and reproducibility of studies and suggest a high risk of publication bias. Finally, each tumor model type has specific roles in research based on their advantages (and disadvantages).

SYSTEMATIC REVIEW REGISTRATION

PROSPERO-ID CRD42022308833.

Patient-derived xenograft (PDX) models, applications and challenges in cancer research

The establishing of the first cancer models created a new perspective on the identification and evaluation of new anti-cancer therapies in preclinical studies. Patient-derived xenograft models are created by tumor tissue engraftment. These models accurately represent the biology and heterogeneity of different cancers and recapitulate tumor microenvironment. These features have made it a reliable model along with the development of humanized models. Therefore, they are used in many studies, such as the development of anti-cancer drugs, co-clinical trials, personalized medicine, immunotherapy, and PDX biobanks. This review summarizes patient-derived xenograft models development procedures, drug development applications in various cancers, challenges and limitations.

Knowing what's growing: Why ductal and intraductal prostate cancer matter

Prostate cancer is a common malignancy, but only some tumors are lethal. Accurately identifying these tumors will improve clinical practice and instruct research. Aggressive cancers often have distinctive pathologies, including intraductal carcinoma of the prostate (IDC-P) and ductal adenocarcinoma. Here, we review the importance of these pathologies because they are often overlooked, especially in genomics and preclinical testing. Pathology, genomics, and patient-derived models show that IDC-P and ductal adenocarcinoma accompany multiple markers of poor prognosis. Consequently, "knowing what is growing" will help translate preclinical research to pinpoint and treat high-risk prostate cancer in the clinic.

High-Throughput Imaging Assay for Drug Screening of 3D Prostate Cancer Organoids

New treatments are required for advanced prostate cancer; however, there are fewer preclinical models of prostate cancer than other common tumor types to test candidate therapeutics. One opportunity to increase the scope of preclinical studies is to grow tissue from patient-derived xenografts (PDXs) as organoid cultures. Here we report a scalable pipeline for automated seeding, treatment and an analysis of the drug responses of prostate cancer organoids. We established organoid cultures from 5 PDXs with diverse phenotypes of prostate cancer, including castrate-sensitive and castrate-resistant disease, as well as adenocarcinoma and neuroendocrine pathology. We robotically embedded organoids in Matrigel in 384-well plates and monitored growth via brightfield microscopy before treatment with poly ADP-ribose polymerase inhibitors or a compound library. Independent readouts including metabolic activity and live-cell imaging–based features provided robust measures of organoid growth and complementary ways of assessing drug efficacy. Single organoid analyses enabled in-depth assessment of morphological differences between patients and within organoid populations and revealed that larger organoids had more striking changes in morphology and composition after drug treatment. By increasing the scale and scope of organoid experiments, this automated assay complements other patient-derived models and will expedite preclinical testing of new treatments for prostate cancer.

Recent Discoveries in the Androgen Receptor Pathway in Castration-Resistant Prostate Cancer

The androgen receptor (AR) is the main therapeutic target in advanced prostate cancer, because it regulates the growth and progression of prostate cancer cells. Patients may undergo multiple lines of AR-directed treatments, including androgen-deprivation therapy, AR signaling inhibitors (abiraterone acetate, enzalutamide, apalutamide, or darolutamide), or combinations of these therapies. Yet, tumors inevitably develop resistance to the successive lines of treatment. The diverse mechanisms of resistance include reactivation of the AR and dysregulation of AR cofactors and collaborative transcription factors (TFs). Further elucidating the nexus between the AR and collaborative TFs may reveal new strategies targeting the AR directly or indirectly, such as targeting BET proteins or OCT1. However, appropriate preclinical models will be required to test the efficacy of these approaches. Fortunately, an increasing variety of patient-derived models, such as xenografts and organoids, are being developed for discovery-based research and preclinical drug screening. Here we review the mechanisms of drug resistance in the AR signaling pathway, the intersection with collaborative TFs, and the use of patient-derived models for novel drug discovery.

PDX: Moving Beyond Drug Screening to Versatile Models for Research Discovery

Patient-derived xenografts (PDXs) are tools of the trade for many researchers from all disciplines and medical specialties. Most endocrinologists, and especially those working in oncology, commonly use PDXs for preclinical drug testing and development, and over the last decade large collections of PDXs have emerged across all tumor streams. In this review, we examine how the field has evolved to include PDXs as versatile resources for research discoveries, providing evidence for guidelines and changes in clinical practice.

Establishing a cryopreservation protocol for patient-derived xenografts of prostate cancer

BACKGROUND

Serially transplantable patient-derived xenografts (PDXs) are invaluable preclinical models for studying tumor biology and evaluating therapeutic agents. As these models are challenging to establish from prostate cancer specimens, the ability to preserve them through cryopreservation has several advantages for ongoing research. Despite this, there is still uncertainty about the ability to cryopreserve PDXs of prostate cancer. This study compared three different cryopreservation protocols to identify a method that can be used to reproducibly cryopreserve a diverse cohort of prostate cancer PDX models.

METHODS

One serially transplantable prostate cancer PDX from the Melbourne Urological Research Alliance cohort was used to compare three cryopreservation protocols: slow freezing in fetal calf serum (FCS) with 10% dimethyl sulfoxide (DMSO), FCS with 10% DMSO supplemented with the Rho-associated kinase (ROCK) inhibitor Y-27632 and vitrification. The efficiency of the slow freezing protocols was then assessed in 17 additional prostate cancer PDXs. Following cryopreservation, PDXs were re-established in host mice that were either intact and supplemented with testosterone or castrated. Graft take rate, tumor growth, histological features, and transcriptome profiles before and after cryopreservation were compared.

RESULTS

Slow freezing maintained the viability and histological features of prostate cancer PDXs, and the addition of a ROCK inhibitor increased their growth following cryopreservation. Using the slow freezing method, we re-established 100% of PDXs grown in either testosterone-supplemented or castrated host mice. Importantly, the long-term tumor growth rate and transcriptome profile were maintained following cryopreservation.

CONCLUSION

This study has identified a protocol to reliably cryopreserve and re-establish a diverse cohort of serially transplantable PDXs of prostate cancer. This study has the potential to significantly improve the practicality of maintaining PDX models. Cryopreservation may also increase the accessibility of these important resources and provide new opportunities for preclinical studies on a broader spectrum of prostate tumors.