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.

Introduction of Androgen Receptor Targeting shRNA Inhibits Tumor Growth in Patient-Derived Prostate Cancer Xenografts.

Patient-derived xenograft (PDX) models have been established as important preclinical cancer models, overcoming some of the limitations associated with the use of cancer cell lines. The utility of prostate cancer PDX models has been limited by an inability to genetically manipulate them in vivo and difficulties sustaining PDX-derived cancer cells in culture. Viable, short-term propagation of PDX models would allow in vitro transfection with traceable reporters or manipulation of gene expression relevant to different studies within the prostate cancer field. Here, we report an organoid culture system that supports the growth of prostate cancer PDX cells in vitro and permits genetic manipulation, substantially increasing the scope to use PDXs to study the pathobiology of prostate cancer and define potential therapeutic targets. We have established a short-term PDX-derived in vitro cell culture system which enables genetic manipulation of prostate cancer PDXs LuCaP35 and BM18. Genetically manipulated cells could be re-established as viable xenografts when re-implanted subcutaneously in immunocompromised mice and were able to be serially passaged. Tumor growth of the androgen-dependent LuCaP35 PDX was significantly inhibited following depletion of the androgen receptor (AR) in vivo. Taken together, this system provides a method to generate novel preclinical models to assess the impact of controlled genetic perturbations and allows for targeting specific genes of interest in the complex biological setting of solid tumors.

Performance of tumour microenvironment deconvolution methods in breast cancer using single-cell simulated bulk mixtures.

Cells within the tumour microenvironment (TME) can impact tumour development and influence treatment response. Computational approaches have been developed to deconvolve the TME from bulk RNA-seq. Using scRNA-seq profiling from breast tumours we simulate thousands of bulk mixtures, representing tumour purities and cell lineages, to compare the performance of nine TME deconvolution methods (BayesPrism, Scaden, CIBERSORTx, MuSiC, DWLS, hspe, CPM, Bisque, and EPIC). Some methods are more robust in deconvolving mixtures with high tumour purity levels. Most methods tend to mis-predict normal epithelial for cancer epithelial as tumour purity increases, a finding that is validated in two independent datasets. The breast cancer molecular subtype influences this mis-prediction. BayesPrism and DWLS have the lowest combined numbers of false positives and false negatives, and have the best performance when deconvolving granular immune lineages. Our findings highlight the need for more single-cell characterisation of rarer cell types, and suggest that tumour cell compositions should be considered when deconvolving the TME.

Characterisation of cell lines derived from prostate cancer patients with localised disease.

BACKGROUND: Prostate cancer is a broad-spectrum disease, spanning from indolent to a highly aggressive lethal malignancy. Prostate cancer cell lines are essential tools to understanding the basic features of this malignancy, as well as in identifying novel therapeutic strategies. However, most cell lines routinely used in prostate cancer research are derived from metastatic disease and may not fully elucidate the molecular events underlying the early stages of cancer development and progression. Thus, there is a need for new cell lines derived from localised disease to better span the disease spectrum. METHODS: Prostatic tissue from the primary site, and adjacent non-cancerous tissue was obtained from four patients with localised disease undergoing radical prostatectomy. Epithelial cell outgrowths were immortalised with human papillomavirus type 16 (HPV16) E6 and E7 to establish monoclonal cell lines. Chromosomal ploidy was imaged and STR profiles were determined. Cell morphology, colony formation and cell proliferation characteristics were assessed. Androgen receptor (AR) expression and AR-responsiveness to androgen treatment were analysed by immunofluorescence and RT-qPCR, respectively. RNA-seq analysis was performed to identify prostate lineage markers and expression of prostate cancer tumorigenesis-related genes. RESULTS: Two benign cell lines derived from non-cancer cells (AQ0420 and AQ0396) and two tumour tissue derived cancer cell lines (AQ0411 and AQ0415) were immortalised from four patients with localised prostatic adenocarcinoma. The cell lines presented an epithelial morphology and a slow to moderate proliferative rate. None of the cell lines formed anchorage independent colonies or displayed AR-responsiveness. Comparative RNA-seq expression analysis confirmed the prostatic lineage of the four cell lines, with a distinct gene expression profile from that of the metastatic prostate cancer cell lines, PC-3 and LNCaP. CONCLUSIONS: Comprehensive characterization of these cell lines may provide new in vitro tools that could bridge the current knowledge gap between benign, early-stage and metastatic disease.

hSSB1 (NABP2/OBFC2B) modulates the DNA damage and androgen-induced transcriptional response in prostate cancer.

BACKGROUND: Activation and regulation of androgen receptor (AR) signaling and the DNA damage response impact the prostate cancer (PCa) treatment modalities of androgen deprivation therapy (ADT) and radiotherapy. Here, we have evaluated a role for human single-strand binding protein 1 (hSSB1/NABP2) in modulation of the cellular response to androgens and ionizing radiation (IR). hSSB1 has defined roles in transcription and maintenance of genome stability, yet little is known about this protein in PCa. METHODS: We correlated hSSB1 with measures of genomic instability across available PCa cases from The Cancer Genome Atlas (TCGA). Microarray and subsequent pathway and transcription factor enrichment analysis were performed on LNCaP and DU145 prostate cancer cells. RESULTS: Our data demonstrate that hSSB1 expression in PCa correlates with measures of genomic instability including multigene signatures and genomic scars that are reflective of defects in the repair of DNA double-strand breaks via homologous recombination. In response to IR-induced DNA damage, we demonstrate that hSSB1 regulates cellular pathways that control cell cycle progression and the associated checkpoints. In keeping with a role for hSSB1 in transcription, our analysis revealed that hSSB1 negatively modulates p53 and RNA polymerase II transcription in PCa. Of relevance to PCa pathology, our findings highlight a transcriptional role for hSSB1 in regulating the androgen response. We identified that AR function is predicted to be impacted by hSSB1 depletion, whereby this protein is required to modulate AR gene activity in PCa. CONCLUSIONS: Our findings point to a key role for hSSB1 in mediating the cellular response to androgen and DNA damage via modulation of transcription. Exploiting hSSB1 in PCa might yield benefits as a strategy to ensure a durable response to ADT and/or radiotherapy and improved patient outcomes.

Computationally efficient framework for diagnosing, understanding and predicting biphasic population growth.

Throughout the life sciences, biological populations undergo multiple phases of growth, often referred to as biphasic growth for the commonly encountered situation involving two phases. Biphasic population growth occurs over a massive range of spatial and temporal scales, ranging from microscopic growth of tumours over several days, to decades-long regrowth of corals in coral reefs that can extend for hundreds of kilometres. Different mathematical models and statistical methods are used to diagnose, understand and predict biphasic growth. Common approaches can lead to inaccurate predictions of future growth that may result in inappropriate management and intervention strategies being implemented. Here, we develop a very general computationally efficient framework, based on profile likelihood analysis, for diagnosing, understanding and predicting biphasic population growth. The two key components of the framework are as follows: (i) an efficient method to form approximate confidence intervals for the change point of the growth dynamics and model parameters and (ii) parameter-wise profile predictions that systematically reveal the influence of individual model parameters on predictions. To illustrate our framework we explore real-world case studies across the life sciences.

Modelling the tumor immune microenvironment for precision immunotherapy.

The complexity of the cellular and acellular players within the tumor microenvironment (TME) allows for significant variation in TME constitution and role in anticancer treatment response. Spatial alterations in populations of tumor cells and adjacent non-malignant cells, including endothelial cells, fibroblasts and tissue-infiltrating immune cells, often have a major role in determining disease progression and treatment response in cancer. Many current standard systemic antineoplastic treatments target the cancer cells and could be further refined to directly target commonly dysregulated cell populations of the TME. Recent developments in immuno-oncology and bioengineering have created an attractive potential to model these complexities at the level of the individual patient. These developments, along with the increasing momentum in precision medicine research and application, have catalysed exciting new discoveries in understanding drug-TME interactions, target identification, and improved efficacy of therapies. While rapid progress has been made, there are still many challenges to overcome in the development of accurate in vitro, in vivo and ex vivo models incorporating the cellular interactions that take place in the TME. In this review, we describe how advances in immuno-oncology and patient-derived models, such as patient-derived organoids and explant cultures, have enhanced the landscape of personalised immunotherapy prediction and treatment of solid organ malignancies. We describe and compare different immunological targets and perspectives on two-dimensional and three-dimensional modelling approaches that may be used to better rationalise immunotherapy use, ultimately providing a knowledge base for the integration of the autologous TME into these predictive models.

Spatial expression of the FGFR2b splice isoform and its prognostic significance in endometrioid endometrial carcinoma.

Endometrial carcinoma (EC) is the most common gynecological malignancy and fibroblast growth factor receptor 2 (FGFR2) is a frequently dysregulated receptor tyrosine kinase. FGFR2b and FGFR2c are the two main splice isoforms of FGFR2 and are normally localized in epithelial and mesenchymal cells, respectively. Previously, we demonstrated that FGFR2c mRNA expression was associated with aggressive tumor characteristics, shorter progression-free survival (PFS), and disease-specific survival (DSS) in endometrioid ECs (EECs). The objectives of this study were to investigate the spatial expression of FGFR2b in normal and hyperplasia with and without atypia of human endometrium and to assess the prognostic significance of FGFR2b expression in EC. FGFR2b and FGFR2c mRNA expression was evaluated in normal (proliferative [n = 10], secretory [n = 15], and atrophic [n = 10] endometrium), hyperplasia with and without atypia (n = 19) as well as two patient cohorts of EC samples (discovery [n = 78] and Vancouver [n = 460]) using isoform-specific BaseScope RNA in situ hybridization assays. Tumors were categorized based on FGFR2 isoform expression (one, both, or neither) and categories were correlated with clinicopathologic markers, molecular subtypes, and clinical outcomes. The FGFR2b splice isoform was exclusively expressed in the epithelial compartment of normal endometrium and hyperplasia without atypia. We observed FGFR2c expression at the basalis layer of glands in 33% (3/9) of hyperplasia with atypia. In patients with EEC, FGFR2b+/FGFR2c- expression was found in 48% of the discovery cohort and 35% of the validation Vancouver cohort. In univariate analyses, tumors with FGFR2b+/FGFR2c- expression had longer PFS (hazard ratio [HR] 0.265; 95% CI 0.145-0.423; log-rank p < 0.019) and DSS (HR 0.31; 95% CI 0.149-0.622; log-rank p < 0.001) compared to tumors with FGFR2b-/FGFR2c+ expression in the large EEC Vancouver cohort. In multivariable Cox regression analyses, tumors with FGFR2b+/FGFR2c- expression were significantly associated with longer DSS (HR 0.37; 95% CI 0.153-0.872; log-rank p < 0.023) compared to FGFR2b-/FGFR2c+ tumors. In conclusion, FGFR2b+/FGFR2c- expression is associated with favorable clinicopathologic markers and clinical outcomes suggesting that FGFR2b could play a role in tailoring the management of EEC patients in the clinic if these findings are confirmed in an independent cohort.

Circulating Tumour Cells Indicate the Presence of Residual Disease Post-Castration in Prostate Cancer Patient-Derived Xenograft Models.

Castrate-resistant prostate cancer (CRPC) is the lethal form of prostate cancer. Epithelial mesenchymal plasticity (EMP) has been associated with disease progression to CRPC, and prostate cancer therapies targeting the androgen signalling axis, including androgen deprivation therapy (ADT), promote EMP. We explored effects of castration on EMP in the tumours and circulating tumour cells (CTCs) of patient-derived xenograft (PDX)-bearing castrated mice using human-specific RT-qPCR assays and immunocytochemistry. Expression of prostate epithelial cell marker KLK3 was below detection in most tumours from castrated mice (62%, 23/37 mice), consistent with its known up-regulation by androgens. Endpoint tumour size after castration varied significantly in a PDX model-specific pattern; while most tumours were castration-sensitive (BM18, LuCaP70), the majority of LuCaP105 tumours continued to grow following castration. By contrast, LuCaP96 PDX showed a mixed response to castration. CTCs were detected in 33% of LuCaP105, 43% of BM18, 47% of LuCaP70, and 54% of LuCaP96 castrated mice using RPL32 mRNA measurement in plasma. When present, CTC numbers estimated using human RPL32 expression ranged from 1 to 458 CTCs per ml blood, similar to our previous observations in non-castrated mice. In contrast to their non-castrated counterparts, there was no relationship between tumour size and CTC burden in castrated mice. Unsupervised hierarchical clustering of the gene expression profiles of CTCs collected from castrated and non-castrated mice revealed distinct CTC sub-groups within the pooled population that were classified as having mesenchymal, epithelial, or EMP hybrid gene expression profiles. The epithelial signature was only found in CTCs from non-castrated mice. Hybrid and mesenchymal signatures were detected in CTCs from both castrated and non-castrated mice, with an emphasis towards mesenchymal phenotypes in castrated mice. Post-castration serum PSA levels were either below detection or very low for all the CTC positive samples highlighting the potential usefulness of CTCs for disease monitoring after androgen ablation therapy. In summary, our study of castration effects on prostate cancer PDX CTCs showed that CTCs were often detected in the castrate setting, even in mice with no palpable tumours, and demonstrated the superior ability of CTCs to reveal residual disease over the conventional clinical biomarker serum PSA.

Direct bone marrow injection of human bone marrow-derived stromal cells into mouse femurs results in greater prostate cancer PC-3 cell proliferation, but not specifically proliferation within the injected femurs.

BACKGROUND: While prostate cancer (PCa) cells most often metastasize to bone in men, species-specific differences between human and mouse bone marrow mean that this pattern is not faithfully replicated in mice. Herein we evaluated the impact of partially humanizing mouse bone marrow with human bone marrow-derived stromal cells (BMSC, also known as "mesenchymal stem cells") on human PCa cell behaviour. METHODS: BMSC are key cellular constituents of marrow. We used intrafemoral injection to transplant 5 × 105 luciferase (Luc) and green fluorescence protein (GFP) expressing human BMSC (hBMSC-Luc/GFP) into the right femur of non-obese diabetic (NOD)-severe combined immunodeficiency (scid) interleukin (IL)-2γ-/- (NSG) mice. Two weeks later, 2.5 × 106 PC-3 prostate cancer cells expressing DsRed (PC-3-DsRed) were delivered into the mice via intracardiac injection. PC-3-DsRed cells were tracked over time using an In Vivo Imaging System (IVIS) live animal imaging system, X-ray and IVIS imaging performed on harvested organs, and PC-3 cell numbers in femurs quantified using flow cytometry and histology. RESULTS: Flow cytometry analysis revealed greater PC-3-DsRed cell numbers within femurs of the mice that received hBMSC-Luc/GFP. However, while there were overall greater PC-3-DsRed cell numbers in these animals, there were not more PC-3-DsRed in the femurs injected with hBMSC-Luc/GFP than in contralateral femurs. A similar proportion of mice in with or without hBMSC-Luc/GFP had bone lessions, but the absolute number of bone lesions was greater in mice that had received hBMSC-Luc/GFP. CONCLUSION: PC-3-DsRed cells preferentially populated bones in mice that had received hBMSC-Luc/GFP, although PC-3-DsRed cells not specifically localize in the bone marrow cavity where hBMSC-Luc/GFP had been transplanted. hBMSC-Luc/GFP appear to modify mouse biology in a manner that supports PC-3-DsRed tumor development, rather than specifically influencing PC-3-DsRed cell homing. This study provides useful insights into the role of humanizing murine bone marrow with hBMSC to study human PCa cell biology.

Chimeric Antigen Receptor T-Cell Therapy in Metastatic Castrate-Resistant Prostate Cancer.

Prostate cancer is the most commonly diagnosed solid-organ cancer amongst males worldwide. Metastatic castrate-resistant prostate cancer (mCRPC) is a rapidly fatal end-sequelae of prostate cancer. Therapeutic options for men with mCRPC are limited and are not curative in nature. The recent development of chimeric antigen receptor T-cell (CAR-T) therapy has revolutionised the treatment of treatment-resistant haematological malignancies, and several studies are underway investigating the utility of this technology in the treatment of solid tumours. In this review, we evaluate the current treatment options for men with mCRPC as well as the current landscape of preclinical and clinical trials of CAR-T cell therapy against prostate cancer. We also appraise the various prostate cancer-specific tumour-associated antigens that may be targeted by CAR-T cell technology. Finally, we examine the potential translational barriers of CAR-T cell therapy in solid tumours. Despite preclinical success, preliminary clinical trials in men with prostate cancer have had limited efficacy. Therefore, further clinically translatable preclinical models are required to enhance the understanding of the role of this investigational therapeutic in men with mCRPC. In the era of precision medicine, tailored immunotherapy administered to men in a tumour-agnostic approach provides hope to a group of men who otherwise have few treatment options available.

Urothelial Carcinoma and Prostate-specific Membrane Antigen: Cellular, Imaging, and Prognostic Implications.

CONTEXT: Staging, restaging, and surveillance of urothelial carcinoma (UC) is challenging due to suboptimal accuracy of standard of care imaging modalities. Prostate-specific membrane antigen (PSMA) imaging may serve to improve characterisation of UC. OBJECTIVE: To appraise available literature regarding cellular, imaging, and prognostic implications of PSMA for UC. EVIDENCE ACQUISITION: A systematic review was performed considering all available literature (including conference abstracts) published from 1990 to 2020 and reported according to Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines following registration in PROSPERO (CRD42020186744). All relevant texts relating to immunohistochemical analysis and PSMA-based imaging in UC were included and collated. Additionally, FOLH1 (gene encoding PSMA) expression according to The Cancer Genome Atlas (TCGA) database was analysed as well as according to consensus and TCGA molecular classification subtypes and subsequently compared with clinical outcomes. EVIDENCE SYNTHESIS: PSMA expression across UC tumour tissue was heterogeneous (0-100%) but appeared to decrease with increased grade and stage. The TCGA analysis demonstrated loss of FOLH1 expression with increasing T stage (p = 0.0180) and N stage (p = 0.0269), and reduced FOLH1 expression was associated with worse disease-free survival. PSMA expression in UC neovasculature was variable but mostly increased (44-100%). Eleven reports of PSMA-based imaging for UC were identified, reporting on 18 patients. PSMA positron emission tomography (PET) imaging was positive in 17 out of 18 patients. The included literature review data were limited by mostly low-quality, retrospective studies. CONCLUSIONS: Tissue PSMA, or FOLH1 expression, may inversely be associated with pathological and survival outcomes in localised UC. PSMA PET imaging may improve detection of metastatic disease and response to systemic therapy due to PSMA expression in neovasculature. Available evidence is limited; thus, larger, prospective studies are required to confirm early results and define populations that benefit most. PATIENT SUMMARY: In this systematic review, we assess the potential role of prostate-specific membrane antigen in urothelial cancer. We found that its utility is in expression of blood vessels surrounding metastasis. We conclude that it may be beneficial in detecting metastasis and response to systemic therapies.

Deep learning in cancer diagnosis, prognosis and treatment selection.

Deep learning is a subdiscipline of artificial intelligence that uses a machine learning technique called artificial neural networks to extract patterns and make predictions from large data sets. The increasing adoption of deep learning across healthcare domains together with the availability of highly characterised cancer datasets has accelerated research into the utility of deep learning in the analysis of the complex biology of cancer. While early results are promising, this is a rapidly evolving field with new knowledge emerging in both cancer biology and deep learning. In this review, we provide an overview of emerging deep learning techniques and how they are being applied to oncology. We focus on the deep learning applications for omics data types, including genomic, methylation and transcriptomic data, as well as histopathology-based genomic inference, and provide perspectives on how the different data types can be integrated to develop decision support tools. We provide specific examples of how deep learning may be applied in cancer diagnosis, prognosis and treatment management. We also assess the current limitations and challenges for the application of deep learning in precision oncology, including the lack of phenotypically rich data and the need for more explainable deep learning models. Finally, we conclude with a discussion of how current obstacles can be overcome to enable future clinical utilisation of deep learning.

Isomer-Resolved Imaging of Prostate Cancer Tissues Reveals Specific Lipid Unsaturation Profiles Associated With Lymphocytes and Abnormal Prostate Epithelia.

Prostate cancer is the fourth most common cancer worldwide with definitive diagnosis reliant on biopsy and human-graded histopathology. As with other pathologies, grading based on classical haematoxylin and eosin (H&E) staining of formalin fixed paraffin-embedded material can be prone to variation between pathologists, prompting investigation of biomolecular markers. Comprising around 50% of cellular mass, and with known metabolic variations in cancer, lipids provide a promising target for molecular pathology. Here we apply isomer-resolved lipidomics in combination with imaging mass spectrometry to interrogate tissue sections from radical prostatectomy specimens. Guided by the histopathological assessment of adjacent tissue sections, regions of interest are investigated for molecular signatures associated with lipid metabolism, especially desaturation and elongation pathways. Monitoring one of the most abundant cellular membrane lipids within these tissues, phosphatidylcholine (PC) 34:1, high positive correlation was observed between the n-9 isomer (site of unsaturation 9-carbons from the methyl terminus) and epithelial cells from potential pre-malignant lesions, while the n-7 isomer abundance was observed to correlate with immune cell infiltration and inflammation. The correlation of lipid isomer signatures with human disease states in tissue suggests a future role for isomer-resolved mass spectrometry imaging in assisting pathologists with prostate cancer diagnoses and patient stratification.

A humanized orthotopic tumor microenvironment alters the bone metastatic tropism of prostate cancer cells.

Prostate cancer (PCa) is the second most commonly diagnosed cancer in men, and bone is the most frequent site of metastasis. The tumor microenvironment (TME) impacts tumor growth and metastasis, yet the role of the TME in PCa metastasis to bone is not fully understood. We used a tissue-engineered xenograft approach in NOD-scid IL2Rγnull (NSG) mice to incorporate two levels of humanization; the primary tumor and TME, and the secondary metastatic bone organ. Bioluminescent imaging, histology, and immunohistochemistry were used to study metastasis of human PC-3 and LNCaP PCa cells from the prostate to tissue-engineered bone. Here we show pre-seeding scaffolds with human osteoblasts increases the human cellular and extracellular matrix content of bone constructs, compared to unseeded scaffolds. The humanized prostate TME showed a trend to decrease metastasis of PC-3 PCa cells to the tissue-engineered bone, but did not affect the metastatic potential of PCa cells to the endogenous murine bones or organs. On the other hand, the humanized TME enhanced LNCaP tumor growth and metastasis to humanized and murine bone. Together this demonstrates the importance of the TME in PCa bone tropism, although further investigations are needed to delineate specific roles of the TME components in this context.

Epithelial-to-Mesenchymal Transition Enhances Cancer Cell Sensitivity to Cytotoxic Effects of Cold Atmospheric Plasmas in Breast and Bladder Cancer Systems.

Cold atmospheric plasma (CAP) has emerged as a highly selective anticancer agent, most recently in the form of plasma-activated medium (PAM). Since epithelial-mesenchymal transition (EMT) has been implicated in resistance to various cancer therapies, we assessed whether EMT status is associated with PAM response. Mesenchymal breast cancer cell lines, as well as the mesenchymal variant in an isogenic EMT/MET human breast cancer cell system (PMC42-ET/LA), were more sensitive to PAM treatment than their epithelial counterparts, contrary to their responses to other therapies. The same trend was seen in luminal muscle-invasive bladder cancer model (TSU-Pr1/B1/B2) and the non-muscle-invasive basal 5637 bladder cancer cell line. Three-dimensional spheroid cultures of the bladder cancer cell lines were less sensitive to the PAM treatment compared to their two-dimensional counterparts; however, incrementally better responses were again seen in more mesenchymally-shifted cell lines. This study provides evidence that PAM preferentially inhibits mesenchymally-shifted carcinoma cells, which have been associated with resistance to other therapies. Thus, PAM may represent a novel treatment that can selectively inhibit triple-negative breast cancers and a subset of aggressive bladder cancers, which tend to be more mesenchymal. Our approach may potentially be utilized for other aggressive cancers exhibiting EMT and opens new opportunities for CAP and PAM as a promising new onco-therapy.

Diversity of Epithelial-Mesenchymal Phenotypes in Circulating Tumour Cells from Prostate Cancer Patient-Derived Xenograft Models.

Metastasis is the leading cause of cancer-related deaths worldwide. The epithelial-mesenchymal plasticity (EMP) status of primary tumours has relevance to metastatic potential and therapy resistance. Circulating tumour cells (CTCs) provide a window into the metastatic process, and molecular characterisation of CTCs in comparison to their primary tumours could lead to a better understanding of the mechanisms involved in the metastatic cascade. In this study, paired blood and tumour samples were collected from four prostate cancer patient-derived xenograft (PDX) models (BM18, LuCaP70, LuCaP96, LuCaP105) and assessed using an EMP-focused, 42 gene human-specific, nested quantitative RT-PCR assay. CTC burden varied amongst the various xenograft models with LuCaP96 having the highest number of CTCs per mouse (mean: 704; median: 31) followed by BM18 (mean: 101; median: 21), LuCaP70 (mean: 73; median: 16) and LuCaP105 (mean: 57; median: 6). A significant relationship was observed between tumour size and CTC number (p = 0.0058). Decreased levels of kallikrein-related peptidase 3 (KLK3) mRNA (which encodes prostate-specific antigen; PSA) were observed in CTC samples from all four models compared to their primary tumours. Both epithelial- and mesenchymal-associated genes were commonly expressed at higher levels in CTCs compared to the bulk primary tumour, although some common EMT-associated genes (CDH1, VIM, EGFR, EPCAM) remained unchanged. Immunofluorescence co-staining for pan-cytokeratin (KRT) and vimentin (VIM) indicated variable proportions of CTCs across the full EMP axis, even in the same model. EMP hybrids predominated in the BM18 and LuCaP96 models, but were not detected in the LuCaP105 model, and variable numbers of KRT+ and human VIM+ cells were observed in each model. SERPINE1, which encodes plasminogen activator inhibitor-1 (PAI-1), was enriched at the RNA level in CTCs compared to primary tumours and was the most commonly expressed mesenchymal gene in the CTCs. Co-staining for SERPINE1 and KRT revealed SERPINE1+ cells in 7/11 samples, six of which had SERPINE+KRT+ CTCs. Cell size variation was observed in CTCs. The majority of samples (8/11) contained larger CTCs ranging from 15.3 to 37.8 µm, whilst smaller cells (10.7 ± 4.1 µm, similar in size to peripheral blood mononuclear cells (PBMCs)) were identified in 6 of 11 samples. CTC clusters were also identified in 9/11 samples, containing 2-100 CTCs per cluster. Where CTC heterogeneity was observed in the clusters, epithelial-like cells (KRT+VIM-) were located on the periphery of the cluster, forming a layer around hybrid (KRT+VIM+) or mesenchymal-like (KRT-VIM+) cells. The CTC heterogeneity observed in these models emphasises the complexity in CTC isolation and classification and supports the increasingly recognised importance of the epithelial-mesenchymal hybrid state in cancer progression and metastasis.

A Suite of Activity-Based Probes To Dissect the KLK Activome in Drug-Resistant Prostate Cancer.

Kallikrein-related peptidases (KLKs) are a family of secreted serine proteases, which form a network (the KLK activome) with an important role in proteolysis and signaling. In prostate cancer (PCa), increased KLK activity promotes tumor growth and metastasis through multiple biochemical pathways, and specific quantification and tracking of changes in the KLK activome could contribute to validation of KLKs as potential drug targets. Herein we report a technology platform based on novel activity-based probes (ABPs) and inhibitors enabling simultaneous orthogonal analysis of KLK2, KLK3, and KLK14 activity in hormone-responsive PCa cell lines and tumor homogenates. Importantly, we identifed a significant decoupling of KLK activity and abundance and suggest that KLK proteolysis should be considered as an additional parameter, along with the PSA blood test, for accurate PCa diagnosis and monitoring. Using selective inhibitors and multiplexed fluorescent activity-based protein profiling (ABPP), we dissect the KLK activome in PCa cells and show that increased KLK14 activity leads to a migratory phenotype. Furthermore, using biotinylated ABPs, we show that active KLK molecules are secreted into the bone microenvironment by PCa cells following stimulation by osteoblasts suggesting KLK-mediated signaling mechanisms could contribute to PCa metastasis to bone. Together our findings show that ABPP is a powerful approach to dissect dysregulation of the KLK activome as a promising and previously underappreciated therapeutic target in advanced PCa.

Fibroblast Growth Factor Receptor 2 Isoforms Detected via Novel RNA ISH as Predictive Biomarkers for Progestin Therapy in Atypical Hyperplasia and Low-Grade Endometrial Cancer.

Women with atypical hyperplasia (AH) or well-differentiated early-stage endometrioid endometrial carcinoma (EEC) who wish to retain fertility and/or with comorbidities precluding surgery, are treated with progestin. Clinically approved predictive biomarkers for progestin therapy remain an unmet need. The objectives of this study were to document the overall response rate (ORR) of levonorgestrel intrauterine device (LNG-IUD) treatment, and determine the association of FGFR2b and FGFR2c expression with treatment outcome. BaseScope RNA ISH assay was utilized to detect expression of FGFR2b and FGFR2c mRNA in the diagnostic biopsies of 89 women (40 AH and 49 EEC) treated with LNG-IUD. Detailed clinical follow-up was available for 69 women which revealed an overall response rate (ORR) of 44% (30/69) with a higher ORR seen in AH (64%) compared to EEC (23%). The recurrence rate in women who initially responded to LNG-IUD was 10/30 (33.3%). RNA ISH was successful in 72 patients and showed FGFR2c expression in 12/72 (16.7%) samples. In the 59 women with detailed clinical follow-up and RNA-ISH data, women with tumours expressing FGFR2c were 5-times more likely to have treatment failure in both univariable (HR 5.08, p < 0.0001) and multivariable (HR 4.5, p < 0.002) Cox regression analyses. In conclusion, FGFR2c expression appears to be strongly associated with progestin treatment failure, albeit the ORR is lower in this cohort than previously reported. Future work to validate these findings in an independent multi-institutional cohort is needed.