Evaluation of Small Molecule Drug Uptake in Patient-Derived Prostate Cancer Explants by Mass Spectrometry

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.

Spatial MS multiomics on clinical prostate cancer tissues

Mass spectrometry (MS) and MS imaging (MSI) are used extensively for both the spatial and bulk characterization of samples in lipidomics and proteomics workflows. These datasets are typically generated independently due to different requirements for sample preparation. However, modern omics technologies now provide higher sample throughput and deeper molecular coverage, which, in combination with more sophisticated bioinformatic and statistical pipelines, make generating multiomics data from a single sample a reality. In this workflow, we use spatial lipidomics data generated by matrix-assisted laser desorption/ionization MSI (MALDI-MSI) on prostate cancer (PCa) radical prostatectomy cores to guide the definition of tumor and benign tissue regions for laser capture microdissection (LCM) and bottom-up proteomics all on the same sample and using the same mass spectrometer. Accurate region of interest (ROI) mapping was facilitated by the SCiLS region mapper software and dissected regions were analyzed using a dia-PASEF workflow. A total of 5525 unique protein groups were identified from all dissected regions. Lysophosphatidylcholine acyltransferase 1 (LPCAT1), a lipid remodelling enzyme, was significantly enriched in the dissected regions of cancerous epithelium (CE) compared to benign epithelium (BE). The increased abundance of this protein was reflected in the lipidomics data with an increased ion intensity ratio for pairs of phosphatidylcholines (PC) and lysophosphatidylcholines (LPC) in CE compared to BE.

Selective inhibition of CDK9 in triple negative breast cancer

Targeted therapy for triple-negative breast cancers (TNBC) remains a clinical challenge due to tumour heterogeneity. Since TNBC have key features of transcriptionally addicted cancers, targeting transcription via regulators such as cyclin-dependent kinase 9 (CDK9) has potential as a therapeutic strategy. Herein, we preclinically tested a new selective CDK9 inhibitor (CDDD11-8) in TNBC using cell line, patient-derived organoid, and patient-derived explant models. In vitro, CDDD11-8 dose-dependently inhibited proliferation (IC50 range: 281-734 nM), induced cell cycle arrest, and increased apoptosis of cell lines, which encompassed the three major molecular subtypes of TNBC. On target inhibition of CDK9 activity was demonstrated by reduced RNAPII phosphorylation at a CDK9 target peptide and down-regulation of the MYC and MCL1 oncogenes at the mRNA and protein levels in all cell line models. Drug induced RNAPII pausing was evident at gene promoters, with strongest pausing at MYC target genes. Growth of five distinct patient-derived organoid models was dose-dependently inhibited by CDDD11-8 (IC50 range: 272-771 nM), including three derived from MYC amplified, chemo-resistant TNBC metastatic lesions. Orally administered CDDD11-8 also inhibited growth of mammary intraductal TNBC xenograft tumours with no overt toxicity in vivo (mice) or ex vivo (human breast tissues). In conclusion, our studies indicate that CDK9 is a viable therapeutic target in TNBC and that CDDD11-8, a novel selective CDK9 inhibitor, has efficacy in TNBC without apparent toxicity to normal tissues.

Let’s Go 3D! New Generation of Models for Evaluating Drug Response and Resistance in Prostate Cancer

Prostate cancer (PC) is the third most frequently diagnosed cancer worldwide and the second most frequent in men. Several risk factors can contribute to the development of PC, and those include age, family history, and specific genetic mutations. So far, drug testing in PC, as well as in cancer research in general, has been performed on 2D cell cultures. This is mainly because of the vast benefits these models provide, including simplicity and cost effectiveness. However, it is now known that these models are exposed to much higher stiffness; lose physiological extracellular matrix on artificial plastic surfaces; and show changes in differentiation, polarization, and cell–cell communication. This leads to the loss of crucial cellular signaling pathways and changes in cell responses to stimuli when compared to in vivo conditions. Here, we emphasize the importance of a diverse collection of 3D PC models and their benefits over 2D models in drug discovery and screening from the studies done so far, outlining their benefits and limitations. We highlight the differences between the diverse types of 3D models, with the focus on tumor–stroma interactions, cell populations, and extracellular matrix composition, and we summarize various standard and novel therapies tested on 3D models of PC for the purpose of raising awareness of the possibilities for a personalized approach in PC therapy.

Multiplatform Metabolomics Studies of Human Cancers With NMR and Mass Spectrometry Imaging

The status of metabolomics as a scientific branch has evolved from proof-of-concept to applications in science, particularly in medical research. To comprehensively evaluate disease metabolomics, multiplatform approaches of NMR combining with mass spectrometry (MS) have been investigated and reported. This mixed-methods approach allows for the exploitation of each individual technique's unique advantages to maximize results. In this article, we present our findings from combined NMR and MS imaging (MSI) analysis of human lung and prostate cancers. We further provide critical discussions of the current status of NMR and MS combined human prostate and lung cancer metabolomics studies to emphasize the enhanced metabolomics ability of the multiplatform approach.

Unravelling Prostate Cancer Heterogeneity Using Spatial Approaches to Lipidomics and Transcriptomics

Simple Summary

Prostate cancer is a heterogenous disease in terms of disease aggressiveness and therapy response, leading to dilemmas in treatment decisions. This heterogeneity reflects the multifocal nature of prostate cancer and its diversity in cellular and molecular composition, necessitating spatial molecular approaches. Here in view of the emerging importance of rewired lipid metabolism as a source of biomarkers and therapeutic targets for prostate cancer, we highlight recent advancements in technologies that enable the spatial mapping of lipids and related metabolic pathways associated with prostate cancer development and progression. We also evaluate their potential for future implementation in treatment decision-making in the clinical management of prostate cancer.

Abstract

Due to advances in the detection and management of prostate cancer over the past 20 years, most cases of localised disease are now potentially curable by surgery or radiotherapy, or amenable to active surveillance without treatment. However, this has given rise to a new dilemma for disease management; the inability to distinguish indolent from lethal, aggressive forms of prostate cancer, leading to substantial overtreatment of some patients and delayed intervention for others. Driving this uncertainty is the critical deficit of novel targets for systemic therapy and of validated biomarkers that can inform treatment decision-making and to select and monitor therapy. In part, this lack of progress reflects the inherent challenge of undertaking target and biomarker discovery in clinical prostate tumours, which are cellularly heterogeneous and multifocal, necessitating the use of spatial analytical approaches. In this review, the principles of mass spectrometry-based lipid imaging and complementary gene-based spatial omics technologies, their application to prostate cancer and recent advancements in these technologies are considered. We put in perspective studies that describe spatially-resolved lipid maps and metabolic genes that are associated with prostate tumours compared to benign tissue and increased risk of disease progression, with the aim of evaluating the future implementation of spatial lipidomics and complementary transcriptomics for prognostication, target identification and treatment decision-making for prostate cancer.

THE SPACE DIMENSION AT THE MICRO LEVEL: MASS SPECTROMETRY IMAGING OF DRUGS IN TISSUES

Mass spectrometry imaging (MSI) has seen remarkable development in recent years. The possibility of getting quantitative or semiquantitative data, while maintaining the spatial component in the tissues has opened up unique study possibilities. Now with a spatial window of few tens of microns, we can characterize the events occurring in tissue subcompartments in physiological and pathological conditions. For example, in oncology-especially in preclinical models-we can quantitatively measure drug distribution within tumors, correlating it with pharmacological treatments intended to modify it. We can also study the local effects of the drug in the tissue, and their effects in relation to histology. This review focuses on the main results in the field of drug MSI in clinical pharmacology, looking at the literature on the distribution of drugs in human tissues, and also the first preclinical evidence of drug intratissue effects. The main instrumental techniques are discussed, looking at the different instrumentation, sample preparation protocols, and raw data management employed to obtain the sensitivity required for these studies. Finally, we review the applications that describe in situ metabolic events and pathways induced by the drug, in animal models, showing that MSI makes it possible to study effects that go beyond the simple concentration of the drug, maintaining the space dimension. © 2020 John Wiley & Sons Ltd. Mass Spec Rev.

Patient-Derived Prostate Cancer Explants: A Clinically Relevant Model to Assess siRNA-Based Nanomedicines

Over the last thirty years, research in nanomedicine has widely been focused on applications in cancer therapeutics. However, despite the plethora of reported nanoscale drug delivery systems that can successfully eradicate solid tumor xenografts in vivo, many of these formulations have not yet achieved clinical translation. This issue particularly pertains to the delivery of small interfering RNA (siRNA), a highly attractive tool for selective gene targeting. One of the likely reasons behind the lack of translation is that current in vivo models fail to recapitulate critical elements of clinical solid tumors that may influence drug response, such as cellular heterogeneity in the tumor microenvironment. This study incorporates a more clinically relevant model for assessing siRNA delivery systems; ex vivo culture of prostate cancer harvested from patients who have undergone radical prostatectomy, denoted patient-derived explants (PDE). The model retains native human tissue architecture, microenvironment, and cell signaling pathways. Porous silicon nanoparticles (pSiNPs) behavior in this model is investigated and compared with commonly used 3D cancer cell spheroids for their efficacy in the delivery of siRNA directed against the androgen receptor (AR), a key driver of prostate cancer.

Removal of optimal cutting temperature (O.C.T.) compound from embedded tissue for MALDI imaging of lipids

Matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) is a common molecular imaging modality used to characterise the abundance and spatial distribution of lipids in situ. There are several technical challenges predominantly involving sample pre-treatment and preparation which have complicated the analysis of clinical tissues by MALDI-MSI. Firstly, the common embedding of samples in optimal cutting temperature (O.C.T.), which contains high concentrations of polyethylene glycol (PEG) polymers, causes analyte signal suppression during mass spectrometry (MS) by competing for available ions during ionisation. This suppressive effect has constrained the application of MALDI-MSI for the molecular mapping of clinical tissues. Secondly, the complexity of the mass spectra is obtained by the formation of multiple adduct ions. The process of analyte ion formation during MALDI can generate multiple m/z peaks from a single lipid species due to the presence of alkali salts in tissues, resulting in the suppression of protonated adduct formation and the generation of multiple near isobaric ions which produce overlapping spatial distributions. Presented is a method to simultaneously remove O.C.T. and endogenous salts. This approach was applied to lipid imaging in order to prevent analyte suppression, simplify data interpretation, and improve sensitivity by promoting lipid protonation and reducing the formation of alkali adducts.

MALDI MSI Reveals the Spatial Distribution of Protein Markers in Tracheobronchial Lymph Nodes and Lung of Pigs after Respiratory Infection

Respiratory infections are a real threat for humans, and therefore the pig model is of interest for studies. As one of a case for studies, Actinobacillus pleuropneumoniae (APP) caused infections and still worries many pig breeders around the world. To better understand the influence of pathogenic effect of APP on a respiratory system-lungs and tracheobronchial lymph nodes (TBLN), we aimed to employ matrix-assisted laser desorption/ionization time-of-flight mass spectrometry imaging (MALDI-TOF MSI). In this study, six pigs were intranasally infected by APP and two were used as non-infected control, and 48 cryosections have been obtained. MALDI-TOF MSI and immunohistochemistry (IHC) were used to study spatial distribution of infectious markers, especially interleukins, in cryosections of porcine tissues of lungs (necrotic area, marginal zone) and tracheobronchial lymph nodes (TBLN) from pigs infected by APP. CD163, interleukin 1β (IL‑1β) and a protegrin-4 precursor were successfully detected based on their tryptic fragments. CD163 and IL‑1β were confirmed also by IHC. The protegrin-4 precursor was identified by MALDI-TOF/TOF directly on the tissue cryosections. CD163, IL‑1β and protegrin‑4 precursor were all significantly (p < 0.001) more expressed in necrotic areas of lungs infected by APP than in marginal zone, TBLN and in control lungs.

Three-Dimensional Cell Cultures as an In Vitro Tool for Prostate Cancer Modeling and Drug Discovery

In the last decade, three-dimensional (3D) cell culture technology has gained a lot of interest due to its ability to better recapitulate the in vivo organization and microenvironment of in vitro cultured cancer cells. In particular, 3D tumor models have demonstrated several different characteristics compared with traditional two-dimensional (2D) cultures and have provided an interesting link between the latter and animal experiments. Indeed, 3D cell cultures represent a useful platform for the identification of the biological features of cancer cells as well as for the screening of novel antitumor agents. The present review is aimed at summarizing the most common 3D cell culture methods and applications, with a focus on prostate cancer modeling and drug discovery.