Kinesin Facilitates Phenotypic Targeting of Therapeutic Resistance in Advanced Prostate Cancer.

Understanding the mechanisms underlying resistance is critical to improving therapeutic outcomes in patients with metastatic castration-resistant prostate cancer (mCRPC). Previous work showed dynamic interconversions between epithelial-mesenchymal transition (EMT) to mesenchymal-epithelial transition (MET) defines the phenotypic landscape of prostate tumors, as a potential driver of emergence of therapeutic resistance. In this study, we use in vitro and in vivo preclinical MDA PCa PDX models of resistant human prostate cancer to determine molecular mechanisms of cross-resistance between anti-androgen therapy and taxane chemotherapy, underlying the therapeutically resistant phenotype. Transcriptomic profiling revealed that resistant and sensitive prostate cancer C4-2B cells have a unique differential gene signature response to cabazitaxel. Gene pathway analysis showed that sensitive cells exhibit increase in DNA damage, while resistant cells express genes associated with protein regulation in response to cabazitaxel. These PDX specimens are from patients who have metastatic lethal CRPC, treated with androgen-deprivation therapy (ADT), antiandrogens and chemotherapy including 2nd line taxane chemotherapy, cabazitaxel. Immunohistochemistry revealed high expression of E-cadherin and low expression of vimentin resulting in re-differentiation toward an epithelial phenotype. Furthermore, the mitotic kinesin-related protein (HSET) involved in microtubule binding and the SLCO1B3 transporter (implicated in cabazitaxel intracellular transport), associated with resistance in these prostate tumors. Combinational targeting of kinesins (ispinesib) with cabazitaxel was more effective than single monotherapies in inducing cell death in resistant prostate tumors. Implications: Our findings are of translational significance in identifying kinesin as a novel target of cross-resistance, towards enhancing therapeutic vulnerability and improved clinical outcomes in patients with advanced prostate cancer.

Integrative Molecular Analyses of the MD Anderson Prostate Cancer Patient-derived Xenograft (MDA PCa PDX) Series.

PURPOSE: Develop and deploy a robust discovery platform that encompasses heterogeneity, clinical annotation, and molecular characterization and overcomes the limited availability of prostate cancer models. This initiative builds on the rich MD Anderson (MDA) prostate cancer (PCa) patient-derived xenograft (PDX) resource to complement existing publicly available databases by addressing gaps in clinically annotated models reflecting the heterogeneity of potentially lethal and lethal prostate cancer. EXPERIMENTAL DESIGN: We performed whole-genome, targeted, and RNA sequencing in representative samples of the same tumor from 44 PDXs derived from 38 patients linked to donor tumor metadata and corresponding organoids. The cohort includes models derived from different morphologic groups, disease states, and involved organ sites (including circulating tumor cells), as well as paired samples representing heterogeneity or stages before and after therapy. RESULTS: The cohort recapitulates clinically reported alterations in prostate cancer genes, providing a data resource for clinical and molecular interrogation of suitable experimental models. Paired samples displayed conserved molecular alteration profiles, suggesting the relevance of other regulatory mechanisms (e.g., epigenomic) influenced by the microenvironment and/or treatment. Transcriptomically, models were grouped on the basis of morphologic classification. DNA damage response-associated mechanisms emerged as differentially regulated between adenocarcinoma and neuroendocrine prostate cancer in a cross-interrogation of PDX/patient datasets. CONCLUSIONS: We addressed the gap in clinically relevant prostate cancer models through comprehensive molecular characterization of MDA PCa PDXs, providing a discovery platform that integrates with patient data and benchmarked to therapeutically relevant consensus clinical groupings. This unique resource supports robust hypothesis generation and testing from basic, translational, and clinical perspectives.

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.

Patient-Derived Models of Cancer in the NCI PDMC Consortium: Selection, Pitfalls, and Practical Recommendations.

For over a century, early researchers sought to study biological organisms in a laboratory setting, leading to the generation of both in vitro and in vivo model systems. Patient-derived models of cancer (PDMCs) have more recently come to the forefront of preclinical cancer models and are even finding their way into clinical practice as part of functional precision medicine programs. The PDMC Consortium, supported by the Division of Cancer Biology in the National Cancer Institute of the National Institutes of Health, seeks to understand the biological principles that govern the various PDMC behaviors, particularly in response to perturbagens, such as cancer therapeutics. Based on collective experience from the consortium groups, we provide insight regarding PDMCs established both in vitro and in vivo, with a focus on practical matters related to developing and maintaining key cancer models through a series of vignettes. Although every model has the potential to offer valuable insights, the choice of the right model should be guided by the research question. However, recognizing the inherent constraints in each model is crucial. Our objective here is to delineate the strengths and limitations of each model as established by individual vignettes. Further advances in PDMCs and the development of novel model systems will enable us to better understand human biology and improve the study of human pathology in the lab.

Bone mimetic environments support engineering, propagation, and analysis of therapeutic response of patient-derived cells, ex vivo and in vivo.

Bone metastases are the most common milestone in the lethal progression of prostate cancer and prominent in a substantial portion of renal malignancies. Interactions between cancer and bone host cells have emerged as drivers of both disease progression and therapeutic resistance. To best understand these central host-epithelial cell interactions, biologically relevant preclinical models are required. To achieve this goal, we here established and characterized tissue-engineered bone mimetic environments (BME) capable of supporting the growth of patient-derived xenograft (PDX) cells, ex vivo and in vivo. The BME consisted of a polycaprolactone (PCL) scaffold colonized by human mesenchymal stem cells (hMSCs) differentiated into osteoblasts. PDX-derived cells were isolated from bone metastatic prostate or renal tumors, engineered to express GFP or luciferase and seeded onto the BMEs. BMEs supported the growth and therapy response of PDX-derived cells, ex vivo. Additionally, BMEs survived after in vivo implantation and further sustained the growth of PDX-derived cells, their serial transplant, and their application to study the response to treatment. Taken together, this demonstrates the utility of BMEs in combination with patient-derived cells, both ex vivo and in vivo. STATEMENT OF SIGNIFICANCE: Our tissue-engineered BME supported the growth of patient-derived cells and proved useful to monitor the therapy response, both ex vivo and in vivo. This approach has the potential to enable co-clinical strategies to monitor bone metastatic tumor progression and therapy response, including identification and prioritization of new targets for patient treatment.

Prostate lineage-specific metabolism governs luminal differentiation and response to antiandrogen treatment.

Lineage transitions are a central feature of prostate development, tumourigenesis and treatment resistance. While epigenetic changes are well known to drive prostate lineage transitions, it remains unclear how upstream metabolic signalling contributes to the regulation of prostate epithelial identity. To fill this gap, we developed an approach to perform metabolomics on primary prostate epithelial cells. Using this approach, we discovered that the basal and luminal cells of the prostate exhibit distinct metabolomes and nutrient utilization patterns. Furthermore, basal-to-luminal differentiation is accompanied by increased pyruvate oxidation. We establish the mitochondrial pyruvate carrier and subsequent lactate accumulation as regulators of prostate luminal identity. Inhibition of the mitochondrial pyruvate carrier or supplementation with exogenous lactate results in large-scale chromatin remodelling, influencing both lineage-specific transcription factors and response to antiandrogen treatment. These results establish reciprocal regulation of metabolism and prostate epithelial lineage identity.

Role of adenosine deaminase in prostate cancer progression.

Prostate cancer (PCa) is the second most common cancer and constitutes about 14.7% of total cancer cases. PCa is highly prevalent and more aggressive in African-American (AA) men than in European-American (EA) men. PCa tends to be highly heterogeneous, and its complex biology is not fully understood. We use metabolomics to better understand the mechanisms behind PCa progression and disparities in its clinical outcome. Adenosine deaminase (ADA) is a key enzyme in the purine metabolic pathway; it was found to be upregulated in PCa and is associated with higher-grade PCa and poor disease-free survival. The inosine-to-adenosine ratio, which is a surrogate for ADA activity was high in PCa patient urine and higher in AA PCa compared to EA PCa. To understand the significance of high ADA in PCa, we established ADA overexpression models and performed various in vitro and in vivo studies. Our studies have revealed that an acute increase in ADA expression during later stages of tumor development enhances in vivo growth in multiple pre-clinical models. Further analysis revealed that mTOR signaling activation could be associated with this tumor growth. Chronic ADA overexpression shows alterations in the cells' adhesion machinery and a decrease in cells' ability to adhere to the extracellular matrix in vitro. Losing cell-matrix interaction is critical for metastatic dissemination which suggests that ADA could potentially be involved in promoting metastasis. This is supported by the association of higher ADA expression with higher-grade tumors and poor patient survival. Overall, our findings suggest that increased ADA expression may promote PCa progression, specifically tumor growth and metastatic dissemination.

Monitoring Glucocorticoid Receptor in Plasma-derived Extracellular Vesicles as a Marker of Resistance to Androgen Receptor Signaling Inhibition in Prostate Cancer.

Disease progression following androgen ablation was shown to be associated with upregulation of the glucocorticoid receptor (GR). Longitudinal monitoring of GR expression in circulating extracellular vesicles (EV) may reflect changes in the tumor cell and facilitates detection of acquired resistance. We utilized LNCaP, LREX cells and a patient-derived xenograft, MDA PDX 322-2-6a, for in vitro and in vivo experiments. Plasma-derived EVs were isolated from patients with localized high-risk prostate cancer undergoing androgen ablation. The mRNA levels of GR in EVs and their responsive genes were detected by transcriptome analysis, qRT-PCR and the protein levels by Western blot analysis. We detected changes in GR expression at mRNA and protein levels in EVs derived from LNCaP and LREX cells in in vitro studies. In in vivo experiments, LNCaP and the PDX MDA 322-2-6a-bearing mice were treated with enzalutamide. GR levels in plasma-derived EVs were increased only in those tumors that did not respond to enzalutamide. Treatment of mice bearing enzalutamide-resistant tumors with a GR inhibitor in combination with enzalutamide led to a transient pause in tumor growth in a subset of tumors and decreased GR levels intracellular and in plasma-derived EVs. In a subgroup of patients with high-risk localized prostate cancer treated with androgen signaling inhibition, GR was found upregulated in matching tissue and plasma EVs. These analyses showed that GR levels in plasma-derived EVs may be used for monitoring the transition of GR expression allowing for early detection of resistance to androgen ablation treatment. SIGNIFICANCE: Longitudinal monitoring of GR expression in plasma-derived EVs from patients with prostate cancer treated with androgen signaling inhibitors facilitates early detection of acquisition of resistance to androgen receptor signaling inhibition in individual patients.

MYC is a regulator of androgen receptor inhibition-induced metabolic requirements in prostate cancer.

Advanced prostate cancers are treated with therapies targeting the androgen receptor (AR) signaling pathway. While many tumors initially respond to AR inhibition, nearly all develop resistance. It is critical to understand how prostate tumor cells respond to AR inhibition in order to exploit therapy-induced phenotypes prior to the outgrowth of treatment-resistant disease. Here, we comprehensively characterize the effects of AR blockade on prostate cancer metabolism using transcriptomics, metabolomics, and bioenergetics approaches. The metabolic response to AR inhibition is defined by reduced glycolysis, robust elongation of mitochondria, and increased reliance on mitochondrial oxidative metabolism. We establish DRP1 activity and MYC signaling as mediators of AR-blockade-induced metabolic phenotypes. Rescuing DRP1 phosphorylation after AR inhibition restores mitochondrial fission, while rescuing MYC restores glycolytic activity and prevents sensitivity to complex I inhibition. Our study provides insight into the regulation of treatment-induced metabolic phenotypes and vulnerabilities in prostate cancer.

ETV4 mediates dosage-dependent prostate tumor initiation and cooperates with p53 loss to generate prostate cancer.

The mechanisms underlying ETS-driven prostate cancer initiation and progression remain poorly understood due to a lack of model systems that recapitulate this phenotype. We generated a genetically engineered mouse with prostate-specific expression of the ETS factor, ETV4, at lower and higher protein dosage through mutation of its degron. Lower-level expression of ETV4 caused mild luminal cell expansion without histologic abnormalities, and higher-level expression of stabilized ETV4 caused prostatic intraepithelial neoplasia (mPIN) with 100% penetrance within 1 week. Tumor progression was limited by p53-mediated senescence and Trp53 deletion cooperated with stabilized ETV4. The neoplastic cells expressed differentiation markers such as Nkx3.1 recapitulating luminal gene expression features of untreated human prostate cancer. Single-cell and bulk RNA sequencing showed that stabilized ETV4 induced a previously unidentified luminal-derived expression cluster with signatures of cell cycle, senescence, and epithelial-to-mesenchymal transition. These data suggest that ETS overexpression alone, at sufficient dosage, can initiate prostate neoplasia.

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 3D Perfusable Platform for In Vitro Culture of Patient Derived Xenografts.

Many advanced cancer models, such as patient-derived xenografts (PDXs), offer significant benefits in their preservation of the native tumor's heterogeneity and susceptibility to treatments, but face significant barriers to use in their reliance on a rodent host for propagation and screening. PDXs remain difficult to implement in vitro, particularly in configurations that enable both detailed cellular analysis and high-throughput screening (HTS). Complex multilineage co-cultures with stromal fibroblasts, endothelium, and other cellular and structural components of the tumor microenvironment (TME) further complicate ex vivo implementation. Herein, the culture of multiple prostate cancer (PCa)-derived PDX models as 3D clusters within engineered biomimetic hydrogel matrices, in a HTS-compatible multiwell microfluidic format, alongside bone marrow-derived stromal cells and a perfused endothelial channel. Polymeric hydrogel matrices are customized for each cell type, enabling cell survival in vitro and facile imaging across all conditions. PCa PDXs demonstrate unique morphologies and reliance on TME partners, retention of known phenotype, and expected sensitivity or resistance to standard PCa therapeutics. This novel integration of technologies provides a fully human model, and expands the information to be gathered from each specimen, while avoiding the time and labor involved with animal-based testing.

Characterization of prostate cancer adrenal metastases: dependence upon androgen receptor signaling and steroid hormones.

BACKGROUND: Prostate cancer (PCa) typically spreads to the bone, and this distribution is attributed to the central role of the microenvironment in progression. However, metastasis to the adrenal glands, while not as common, does occur. The biology that accounts for adrenal metastases may be attributed to the unique local steroid metabolome and co-clinical characterization may elucidate the role steroid biosynthesis plays in PCa progression. METHODS: Three patients with metastatic PCa who had archived tumor tissue from an adrenalectomy were retrospectively identified, and one adrenal metastasis was developed into a xenograft (MDA-PCa-250). The adrenal metastases were characterized by performing somatic DNA whole exome sequencing (WES), RNA-Seq, immunohistochemistry (IHC), and steroid metabolite quantitation. The influence of steroid metabolites on adrenal metastasis cells and tumor growth was tested in vitro and in vivo. RESULTS: Clinically, adrenalectomy was performed during castration-resistant oligometastatic disease, and two men experienced resensitization to leuprolide. Somatic DNA WES revealed heterogeneous alterations in tumor suppressor and DNA damage repair pathway genes. Adrenal metastases had active androgen receptor (AR) signaling by IHC, and RNA-Seq supported a potential role for adrenal androgen precursor metabolism in activating the AR. Steroid quantitation suggested the adrenal androgen precursors were converted into testosterone in these metastases, and stable isotope tracing of an organoid from MDA-PCa-250 confirmed the capability of adrenal metastases to biosynthesize testosterone from adrenal precursors. In vitro testing of a cell line derived from MDA-PCa-250 showed that testosterone and cortisol stimulated tumor cell growth. In vivo experiments demonstrated that MDA-PCa-250 grew in intact mice with circulating testosterone, but not in castrated mice. CONCLUSIONS: PCa adrenal metastases depend upon AR signaling driven by androgen precursors, androstenedione and dehydroepiandrosterone, available in the microenvironment, despite the presence of heterogeneous somatic DNA alterations. Moreover, MDA-PCa-250 provides a preclinical model that can recapitulate the unique androgen-dependence of adrenal metastases. CLINICAL TRIAL REGISTRATION: This study does not report the clinical results of a clinical trial, but it does use samples from a completed clinical trial that is registered with clinicaltrials.gov (NCT01254864).

The ß-Secretase 1 Enzyme as a Novel Therapeutic Target for Prostate Cancer.

Recent studies have demonstrated the association of APP and Aß with cancer, suggesting that BACE1 may play an important role in carcinogenesis. In the present study, we assessed BACE1's usefulness as a therapeutic target in prostate cancer (PCa). BACE1 expression was observed in human PCa tissue samples, patient-derived xenografts (PDX), human PCa xenograft tissue in nude mice, and transgenic adenocarcinoma of the mouse prostate (TRAMP) tissues by immunohistochemistry (IHC) analysis. Additionally, the downstream product of BACE1 activity, i.e., Aß1-42 expression, was also observed in these PCa tissues by IHC as well as by PET imaging in TRAMP mice. Furthermore, BACE1 gene expression and activity was confirmed in several established PCa cell lines (LNCaP, C4-2B-enzalutamide sensitive [S], C4-2B-enzalutamide resistant [R], 22Rv1-S, 22Rv1-R, PC3, DU145, and TRAMP-C1) by real-time PCR and fluorometric assay, respectively. Treatment with a pharmacological inhibitor of BACE1 (MK-8931) strongly reduced the proliferation of PCa cells in in vitro and in vivo models, analyzed by multiple assays (MTT, clonogenic, and trypan blue exclusion assays and IHC). Cell cycle analyses revealed an increase in the sub-G1 population and a significant modulation in other cell cycle stages (G1/S/G2/M) following MK-8931 treatment. Most importantly, in vivo administration of MK-8931 intraperitoneal (30 mg/kg) strongly inhibited TRAMP-C1 allograft growth in immunocompetent C57BL/6 mice (approximately 81% decrease, p = 0.019). Furthermore, analysis of tumor tissue using the prostate cancer-specific pathway array revealed the alteration of several genes involved in PCa growth and progression including Forkhead O1 (FOXO1). All together, these findings suggest BACE1 as a novel therapeutic target in advanced PCa.

Pin-Pointing the Key Hubs in the IFN-γ Pathway Responding to SARS-CoV-2 Infection.

Interferon gamma (IFN-γ) may be potential adjuvant immunotherapy for COVID-19 patients. In this work, we assessed gene expression profiles associated with the IFN-γ pathway in response to SARS-CoV-2 infection. Employing a case-control study from SARS-CoV-2-positive and -negative patients, we identified IFN-γ-associated pathways to be enriched in positive patients. Bioinformatics analyses showed upregulation of MAP2K6, CBL, RUNX3, STAT1, and JAK2 in COVID-19-positive vs. -negative patients. A positive correlation was observed between STAT1/JAK2, which varied alongside the patient's viral load. Expression of MX1, MX2, ISG15, and OAS1 (four well-known IFN-stimulated genes (ISGs)) displayed upregulation in COVID-19-positive vs. -negative patients. Integrative analyses showcased higher levels of ISGs, which were associated with increased viral load and STAT1/JAK2 expression. Confirmation of ISGs up-regulation was performed in vitro using the A549 lung cell line treated with Poly (I:C), a synthetic analog of viral double-stranded RNA; and in different pulmonary human cell lines and ferret tracheal biopsies infected with SARS-CoV-2. A pre-clinical murine model of Coronavirus infection confirmed findings displaying increased ISGs in the liver and lungs from infected mice. Altogether, these results demonstrate the role of IFN-γ and ISGs in response to SARS-CoV-2 infection, highlighting alternative druggable targets that can boost the host response.

Genotype-to-Phenotype Associations in the Aggressive Variant Prostate Cancer Molecular Profile (AVPC-m) Components.

The aggressive variant prostate cancer molecular profile (AVPC-m), composed of combined defects in TP53, RB1 and PTEN, characterizes a subset of prostate cancers linked to androgen indifference and platinum sensitivity. To contribute to the optimization of the AVPC-m assessment for inclusion in prospective clinical trials, we investigated the status of the AVPC-m components in 28 patient tumor-derived xenografts (PDXs) developed at MDACC. We subjected single formalin-fixed, paraffin-embedded (FFPE) blocks from each PDX to immunohistochemistry (IHC), targeted next-generation genomic sequencing (NGS) and Clariom-S Affymetrix human microarray expression profiling. Standard validated IHC assays and a 10% labeling index cutoff resulted in high reproducibility across three separate laboratories and three independent readers for all tumor suppressors, as well as strong correlations with loss-of-function transcriptional scores (LOF-TS). Adding intensity assessment to labeling indices strengthened the association between IHC results and LOF-TS for TP53 and RB1, but not for PTEN. For TP53, genomic alterations determined by NGS had slightly higher agreement scores with LOF-TS than aberrant IHC, while for RB1 and PTEN, NGS and IHC determinations resulted in similar agreement scores with LOF-TS. Nonetheless, our results indicate that the AVPC-m components can be assessed reproducibly by IHC using various widely available standardized assays.

Bone Progenitors Pull the Strings on the Early Metabolic Rewiring Occurring in Prostate Cancer Cells.

Metastatic prostate cancer (PCa) cells soiling in the bone require a metabolic adaptation. Here, we identified the metabolic genes fueling the seeding of PCa in the bone niche. Using a transwell co-culture system of PCa (PC3) and bone progenitor cells (MC3T3 or Raw264.7), we assessed the transcriptome of PC3 cells modulated by soluble factors released from bone precursors. In a Principal Component Analysis using transcriptomic data from human PCa samples (GSE74685), the altered metabolic genes found in vitro were able to stratify PCa patients in two defined groups: primary PCa and bone metastasis, confirmed by an unsupervised clustering analysis. Thus, the early transcriptional metabolic profile triggered in the in vitro model has a clinical correlate in human bone metastatic samples. Further, the expression levels of five metabolic genes (VDR, PPARA, SLC16A1, GPX1 and PAPSS2) were independent risk-predictors of death in the SU2C-PCF dataset and a risk score model built using this lipid-associated signature was able to discriminate a subgroup of bone metastatic PCa patients with a 23-fold higher risk of death. This signature was validated in a PDX pre-clinical model when comparing MDA-PCa-183 growing intrafemorally vs. subcutaneously, and appears to be under the regulatory control of the Protein Kinase A (PKA) signaling pathway. Secretome analyses of conditioned media showcased fibronectin and type-1 collagen as critical bone-secreted factors that could regulate tumoral PKA. Overall, we identified a novel lipid gene signature, driving PCa aggressive metastatic disease pointing to PKA as a potential hub to halt progression.

Mesenchymal and stem-like prostate cancer linked to therapy-induced lineage plasticity and metastasis.

Bioinformatic analysis of 94 patient-derived xenografts (PDXs), cell lines, and organoids (PCOs) identifies three intrinsic transcriptional subtypes of metastatic castration-resistant prostate cancer: androgen receptor (AR) pathway + prostate cancer (PC) (ARPC), mesenchymal and stem-like PC (MSPC), and neuroendocrine PC (NEPC). A sizable proportion of castration-resistant and metastatic stage PC (M-CRPC) cases are admixtures of ARPC and MSPC. Analysis of clinical datasets and mechanistic studies indicates that MSPC arises from ARPC as a consequence of therapy-induced lineage plasticity. AR blockade with enzalutamide induces (1) transcriptional silencing of TP53 and hence dedifferentiation to a hybrid epithelial and mesenchymal and stem-like state and (2) inhibition of BMP signaling, which promotes resistance to AR inhibition. Enzalutamide-tolerant LNCaP cells re-enter the cell cycle in response to neuregulin and generate metastasis in mice. Combined inhibition of HER2/3 and AR or mTORC1 exhibits efficacy in models of ARPC and MSPC or MSPC, respectively. These results define MSPC, trace its origin to therapy-induced lineage plasticity, and reveal its sensitivity to HER2/3 inhibition.

Exploiting Interdata Relationships in Prostate Cancer Proteomes: Clinical Significance of HO-1 Interactors.

Prostate cancer (PCa) cells display abnormal expression of proteins resulting in an augmented capacity to resist chemotherapy and colonize distant organs. We have previously shown the anti-tumoral role of heme oxygenase 1 (HO-1) in this disease. In this work, we undertook a mass spectrometry-based proteomics study to identify HO-1 molecular interactors that might collaborate with its modulatory function in PCa. Among the HO-1 interactors, we identified proteins with nuclear localization. Correlation analyses, using the PCa GSE70770 dataset, showed a significant and positive correlation between HMOX1 and 6 of those genes. Alternatively, HMOX1 and YWHAZ showed a negative correlation. Univariable analyses evidenced that high expression of HNRNPA2B1, HSPB1, NPM1, DDB1, HMGA1, ZC3HAV1, and HMOX1 was associated with increased relapse-free survival (RFS) in PCa patients. Further, PCa patients with high HSPB1/HMOX1, DDB1/HMOX1, and YWHAZ/HMOX1 showed a worse RFS compared with patients with lower ratios. Moreover, a decrease in RFS for patients with higher scores of this signature was observed using a prognostic risk score model. However, the only factor significantly associated with a higher risk of relapse was high YWHAZ. Multivariable analyses confirmed HSPB1, DDB1, and YWHAZ independence from PCa clinic-pathological parameters. In parallel, co-immunoprecipitation analysis in PCa cells ascertained HO-1/14-3-3ζ/δ (protein encoded by YWHAZ) interaction. Herein, we describe a novel protein interaction between HO-1 and 14-3-3ζ/δ in PCa and highlight these factors as potential therapeutic targets.