Characterization of transcriptomic signature of primary prostate cancer analogous to prostatic small cell neuroendocrine carcinoma

Molecular Hallmarks of Prostate-specific Membrane Antigen in Treatment-naïve Prostate Cancer

BACKGROUND AND OBJECTIVE

We characterized tumor prostate-specific membrane antigen (PSMA) levels as a reflection of cancer biology and treatment sensitivities for treatment-naïve prostate cancer.

METHODS

We first correlated PSMA positron emission tomography (PET) maximum standardized uptake values (SUVmax) in primary prostate cancer with tumor FOLH1 (PSMA RNA abundance) to establish RNA as a proxy (n = 55). We then discovered and validated molecular pathways associated with PSMA RNA levels in two large primary tumor cohorts. We validated those associations in independent cohorts (18 total; 5684 tumor samples) to characterize the pathways and treatment responses associated with PSMA.

KEY FINDINGS AND LIMITATIONS

PSMA RNA abundance correlates moderately with SUVmax (ρ = 0.41). In independent cohorts, androgen receptor signaling is more active in tumors with high PSMA. Accordingly, patients with high PSMA tumors experienced longer cancer-specific survival when managed with androgen deprivation therapy for biochemical recurrence (adjusted hazard ratio [AHR] 0.54 [0.34-0.87]; n = 174). PSMA low tumors possess molecular markers of resistance to radiotherapy. Consistent with this, patients with high PSMA tumors experience longer time to recurrence following primary radiotherapy (AHR 0.50 [0.28-0.90]; n = 248). In the SAKK09/10 trial (n = 224), patients with high PSMA tumors who were managed with salvage radiotherapy experienced longer time to progression in the 64-Gy arm (restricted mean survival time [RMST] +7.60 [0.05-15.16]), but this effect was mitigated in the 70-Gy arm (RMST 3.52 [-3.30 to 10.33]). Limitations include using PSMA RNA as a surrogate for PET SUVmax.

CONCLUSIONS AND CLINICAL IMPLICATIONS

PSMA levels in treatment-naïve prostate cancer differentiate tumor biology and treatment susceptibilities. These results warrant validation using PET metrics to substantiate management decisions based on imaging.

Promising therapy for neuroendocrine prostate cancer: current status and future directions

Neuroendocrine prostate cancer (NEPC) is a highly aggressive variant of castration-resistant prostate cancer. It is characterized by low or no expression of the androgen receptor (AR), activation of AR-independent signaling, and increased neuroendocrine phenotype. Most of NEPC is induced by treatment of androgen deprivation therapy and androgen receptor pathway inhibitors (ARPIs). Currently, the treatment of NEPC follows the treatment strategy for small-cell lung cancer, lacking effective drugs and specific treatment options. This review summarizes potential novel targets and therapies for NEPC treatment, including epigenetic regulators (zeste homolog 2 inhibitors, lysine-specific demethylase 1 inhibitors), aurora kinase A inhibitors, poly-ADP-ribose polymerase inhibitors, delta-like ligand 3 targeted therapies, a combination of immunotherapies, etc. Other promising targets and future directions are also discussed in this review. These novel targets and therapies may provide new opportunities for the treatment of NEPC.

Identification of PRDX5 as A Target for The Treatment of Castration-Resistant Prostate Cancer

Treatment of castration-resistant prostate cancer (CRPC) is a long-standing clinical challenge. Traditionally, CRPC drugs work by either reducing dihydrotestosterone biosynthesis or blocking androgen receptor (AR) signaling. Here it is demonstrated that AR inhibitor treatment gives rise to a drug-tolerant persister (DTP) state. The thioredoxin/peroxiredoxin pathway is up-regulated in DTP cells. Peroxiredoxin 5 (PRDX5) promotes AR inhibitor resistance and CRPC development. Inhibition of PRDX5 suppresses DTP cell proliferation in culture, dampens CRPC development in animal models, and stabilizes PSA progression and metastatic lesions in patients. Therefore, the study provides a novel mechanism and potential target for the management of castration-resistant prostate cancer.

Tissue-Based Diagnostic Biomarkers of Aggressive Variant Prostate Cancer: A Narrative Review

Prostate cancer (PC) is a common malignancy among elderly men, characterized by great heterogeneity in its clinical course, ranging from an indolent to a highly aggressive disease. The aggressive variant of prostate cancer (AVPC) clinically shows an atypical pattern of disease progression, similar to that of small cell PC (SCPC), and also shares the chemo-responsiveness of SCPC. The term AVPC does not describe a specific histologic subtype of PC but rather the group of tumors that, irrespective of morphology, show an aggressive clinical course, dictated by androgen receptor (AR) indifference. AR indifference represents an adaptive response to androgen deprivation therapy (ADT), driven by epithelial plasticity, an inherent ability of tumor cells to adapt to their environment by changing their phenotypic characteristics in a bi-directional way. The molecular profile of AVPC entails combined alterations in the tumor suppressor genes retinoblastoma protein 1 (RB1), tumor protein 53 (TP53), and phosphatase and tensin homolog (PTEN). The understanding of the biologic heterogeneity of castration-resistant PC (CRPC) and the need to identify the subset of patients that would potentially benefit from specific therapies necessitate the development of prognostic and predictive biomarkers. This review aims to discuss the possible pathophysiologic mechanisms of AVPC development and the potential use of emerging tissue-based biomarkers in clinical practice.

Transcriptomic and clinical heterogeneity of metastatic disease timing within metastatic castration-sensitive prostate cancer

BACKGROUND

Metastatic castration-sensitive prostate cancer (mCSPC) is commonly classified into high- and low-volume subgroups which have demonstrated differential biology, prognosis, and response to therapy. Timing of metastasis has similarly demonstrated differences in clinical outcomes; however, less is known about any underlying biologic differences between these disease states. Herein, we aim to compare transcriptomic differences between synchronous and metachronous mCSPC and identify any differential responses to therapy.

PATIENTS AND METHODS

We performed an international multi-institutional retrospective review of men with mCSPC who completed RNA expression profiling evaluation of their primary tumor. Patients were stratified according to disease timing (synchronous versus metachronous). The primary endpoint was to identify differences in transcriptomic profiles between disease timing. The median transcriptomic scores between groups were compared with the Mann-Whitney U test. Secondary analyses included determining clinical and transcriptomic variables associated with overall survival (OS) from the time of metastasis. Survival analysis was carried out with the Kaplan-Meier method and multivariable Cox regression.

RESULTS

A total of 252 patients were included with a median follow-up of 39.6 months. Patients with synchronous disease experienced worse 5-year OS (39% versus 79%; P < 0.01) and demonstrated lower median androgen receptor (AR) activity (11.78 versus 12.64; P < 0.01) and hallmark androgen response (HAR; 3.15 versus 3.32; P < 0.01). Multivariable Cox regression identified only high-volume disease [hazard ratio (HR) = 4.97, 95% confidence interval (CI) 2.71-9.10; P < 0.01] and HAR score (HR = 0.51, 95% CI 0.28-0.88; P = 0.02) significantly associated with OS. Finally, patients with synchronous (HR = 0.47, 95% CI 0.30-0.72; P < 0.01) but not metachronous (HR = 1.37, 95% CI 0.50-3.92; P = 0.56) disease were found to have better OS with AR and non-AR combination therapy as compared with monotherapy (P value for interaction = 0.05).

CONCLUSIONS

We have demonstrated a potential biologic difference between metastatic timing of mCSPC. Specifically, for patients with low-volume disease, those with metachronous low-volume disease have a more hormone-dependent transcriptional profile and exhibit a better prognosis than synchronous low-volume disease.

Clinical testing of transcriptome-wide expression profiles in high-risk localized and metastatic prostate cancer starting androgen deprivation therapy: an ancillary study of the STAMPEDE abiraterone Phase 3 trial

Metastatic and high-risk localized prostate cancer respond to hormone therapy but outcomes vary. Following a pre-specified statistical plan, we used Cox models adjusted for clinical variables to test associations with survival of multi-gene expression-based classifiers from 781 patients randomized to androgen deprivation with or without abiraterone in the STAMPEDE trial. Decipher score was strongly prognostic (p<2×10-5) and identified clinically-relevant differences in absolute benefit, especially for localized cancers. In metastatic disease, classifiers of proliferation, PTEN or TP53 loss and treatment-persistent cells were prognostic. In localized disease, androgen receptor activity was protective whilst interferon signaling (that strongly associated with tumor lymphocyte infiltration) was detrimental. Post-Operative Radiation-Therapy Outcomes Score was prognostic in localized but not metastatic disease (interaction p=0.0001) suggesting the impact of tumor biology on clinical outcome is context-dependent on metastatic state. Transcriptome-wide testing has clinical utility for advanced prostate cancer and identified worse outcomes for localized cancers with tumor-promoting inflammation.

Activation of neural lineage networks and ARHGEF2 in enzalutamide-resistant and neuroendocrine prostate cancer and association with patient outcomes

Background

Treatment-emergent neuroendocrine prostate cancer (NEPC) after androgen receptor (AR) targeted therapies is an aggressive variant of prostate cancer with an unfavorable prognosis. The underlying mechanisms for early neuroendocrine differentiation are poorly defined and diagnostic and prognostic biomarkers are needed.

Methods

We performed transcriptomic analysis on the enzalutamide-resistant prostate cancer cell line C4-2B MDVR and NEPC patient databases to identify neural lineage signature (NLS) genes. Correlation of NLS genes with clinicopathologic features was determined. Cell viability was determined in C4-2B MDVR and H660 cells after knocking down ARHGEF2 using siRNA. Organoid viability of patient-derived xenografts was measured after knocking down ARHGEF2.

Results

We identify a 95-gene NLS representing the molecular landscape of neural precursor cell proliferation, embryonic stem cell pluripotency, and neural stem cell differentiation, which may indicate an early or intermediate stage of neuroendocrine differentiation. These NLS genes positively correlate with conventional neuroendocrine markers such as chromogranin and synaptophysin, and negatively correlate with AR and AR target genes in advanced prostate cancer. Differentially expressed NLS genes stratify small-cell NEPC from prostate adenocarcinoma, which are closely associated with clinicopathologic features such as Gleason Score and metastasis status. Higher ARGHEF2, LHX2, and EPHB2 levels among the 95 NLS genes correlate with a shortened survival time in NEPC patients. Furthermore, downregulation of ARHGEF2 gene expression suppresses cell viability and markers of neuroendocrine differentiation in enzalutamide-resistant and neuroendocrine cells.

Conclusions

The 95 neural lineage gene signatures capture an early molecular shift toward neuroendocrine differentiation, which could stratify advanced prostate cancer patients to optimize clinical treatment and serve as a source of potential therapeutic targets in advanced prostate cancer.

Variation in Molecularly Defined Prostate Tumor Subtypes by Self-identified Race

Background

Socioeconomic and health care utilization factors are major drivers of prostate cancer (PC) mortality disparities in the USA; however, tumor molecular heterogeneity may also contribute to the higher mortality among Black men.

Objective

To compare differences in PC subtype frequency and genomic aggressiveness by self-identified race.

Design setting and participants

Five molecular subtype classifiers were applied for 426 Black and 762 White PC patients in the Decipher Genomics Resource Information Database (GRID).

Outcome measurements and statistical analysis

Differences in subtype frequency and tumor genomic risk (Decipher score >0.6) by race were evaluated using χ² tests and multivariable-adjusted logistic regression models.

Results and limitations

Subtype frequencies differed by race for four classifiers. Subtypes characterized by the presence of SPOP mutations, SPINK1 overexpression, and neuroendocrine differentiation were more common among Black men. ERG and ETS fusion-positive subtypes were more frequent among White men, with no clear differences for subtypes reflecting luminal versus basal lineage. The hypothesized low-risk Kamoun S2 subtype was associated with a lower Decipher score among White men only (p = 0.01 for heterogeneity), while the aggressive You PCS1 subtype was associated with a higher Decipher score among White men only (p = 0.001 for heterogeneity). The Tomlins ERG⁺ subtype was associated with a higher Decipher score relative to all other subtypes among Black men, with no association among White men (p = 0.007 for heterogeneity).

Conclusions

The frequency of PC molecular subtypes differed by self-identified race. Additional studies are required to evaluate whether our observations suggest differences in the tumor genomic risk of progression by self-identified race.

Patient summary

We studied five classifiers that identify subtypes of prostate tumors and found that subtypes differed in frequency between Black and White patients. Further research is warranted to evaluate how differences in tumor subtypes may contribute to disparities in prostate cancer mortality.

Antizyme Inhibitor 1 regulates matrikine expression and enhances the metastatic potential of aggressive primary prostate cancer

Molecular drivers of metastasis in patients with high-risk localized prostate cancer (PCa) are poorly understood. Therefore, we aim to study molecular drivers of metastatic progression in high-risk PCa patients. A retrospective matched case-control study of two clinico-pathologically identical groups of high-risk PCa patients was undertaken. One group developed metastatic recurrence (n=19) while the other did not (n=25). The primary index tumor was identified by a uro-pathologist, followed by DNA and RNA extraction for somatic copy number aberration (CNA) analysis and whole-transcriptome gene expression analysis. In vitro and in vivo studies included cell line manipulation and xenograft models. The integrative CNA and gene expression analyses identified an increase in AZIN1 gene expression within a focal amplification of 8q22.3, which was associated with metastatic recurrence of high-risk PCa patients in four independent cohorts. The effects of AZIN1 knockdown were evaluated, due to its therapeutic potential. AZIN1 knockdown effected proliferation and metastatic potential of PCa cells and xenograft models. RNA sequencing after AZIN1 knockdown in PCa cells revealed upregulation of genes coding for collagen subunits. The observed effect on cell migration after AZIN1 knockdown was mimicked when exposing PCa cells to bio-active molecules deriving from COL4A1 and COL4A2. Our integrated CNA and gene expression analysis of primary high-risk PCa identified the AZIN1 gene as a novel driver of metastatic progression, by altering collagen subunit expression. Future research should further investigate its therapeutic potential in preventing metastatic recurrence. Implications: AZIN1 was identified as driver of metastatic progression in high-risk PCa through matrikine regulation.

The long noncoding RNA H19 regulates tumor plasticity in neuroendocrine prostate cancer

Neuroendocrine (NE) prostate cancer (NEPC) is a lethal subtype of castration-resistant prostate cancer (PCa) arising either de novo or from transdifferentiated prostate adenocarcinoma following androgen deprivation therapy (ADT). Extensive computational analysis has identified a high degree of association between the long noncoding RNA (lncRNA) H19 and NEPC, with the longest isoform highly expressed in NEPC. H19 regulates PCa lineage plasticity by driving a bidirectional cell identity of NE phenotype (H19 overexpression) or luminal phenotype (H19 knockdown). It contributes to treatment resistance, with the knockdown of H19 re-sensitizing PCa to ADT. It is also essential for the proliferation and invasion of NEPC. H19 levels are negatively regulated by androgen signaling via androgen receptor (AR). When androgen is absent SOX2 levels increase, driving H19 transcription and facilitating transdifferentiation. H19 facilitates the PRC2 complex in regulating methylation changes at H3K27me3/H3K4me3 histone sites of AR-driven and NEPC-related genes. Additionally, this lncRNA induces alterations in genome-wide DNA methylation on CpG sites, further regulating genes associated with the NEPC phenotype. Our clinical data identify H19 as a candidate diagnostic marker and predictive marker of NEPC with elevated H19 levels associated with an increased probability of biochemical recurrence and metastatic disease in patients receiving ADT. Here we report H19 as an early upstream regulator of cell fate, plasticity, and treatment resistance in NEPC that can reverse/transform cells to a treatable form of PCa once therapeutically deactivated.

Elevated expression of long noncoding RNA H19 is seen in clinical samples of neuroendocrine prostate cancer (PCa). Here the authors show H19 promotes plasticity from luminal to neuroendocrine by epigenetic reprogramming.

Correlative analysis between two commercially available post-prostatectomy genomic tests

BACKGROUND

Multiple genomic tests are available following radical prostatectomy (RP), however, there is a lack of head-to-head evidence for these tests. We sought to compare the performance of two genomic tests in predicting post-RP oncological outcomes.

METHODS

A cohort of 16 post-RP patients with adverse pathological features who had obtained both Decipher (D) and Prolaris (P) testing. The Pearson correlation was used to compare scores from D and cell cycle progression (CCP) from P. Then, we derived a microarray CCP (mCCP) from D and correlated with P-CCP. The associations of D and mCCP with biochemical recurrence (BCR) and metastasis (M) was evaluated in multivariable survival analysis (MVA) in a large cohort of RP patients treated at Johns Hopkins University (1992-2010). In addition, we characterized the expression of the 31 P-CCP genes and mCCP scores in a cohort of 17,967 RP samples from Decipher platform.

RESULTS

There was significant correlation between the D score and P-CCP (r = 0.67, p = 0.004), and between the 10-year probability of BCR reported by P and 5-year probability of M reported by D (r = 0.69, p = 0.003). In this cohort, mCCP derived from the D platform was highly correlated to the reported P-CCP scores from the P platform (r = 0.88, p = 6.7e-6). In a comparative retrospective RP cohort, both mCCP and D were significantly associated with M outcome (p < 0.01 for both). On MVA, D was a predictor of M (HR 1.3, 95% CI [1.12-1.52], p = 0.0005), while mCCP was not a predictor of M (p = 0.62). In the D platform cohort, the 31 P-CCP genes were correlated to each other, and TOP2A was the most correlated to mCCP (r = 0.7).

CONCLUSIONS

We found that P and D scores post-RP were correlated and help in identifying patients who at high risk of BCR in this cohort. In a larger cohort with longer follow-up, D was predictor of M, whereas mCCP was not.

Molecular and Functional Links between Neurodevelopmental Processes and Treatment-Induced Neuroendocrine Plasticity in Prostate Cancer Progression

Simple Summary

Treatment-induced neuroendocrine prostate cancer (t-NEPC) is a subtype of castration-resistant prostate cancer (CRPC) which develops under prolonged androgen deprivation therapy. The mechanisms and pathways underlying the t-NEPC are still poorly understood and there are no effective treatments available. Here, we summarize the literature on the molecules and pathways contributing to neuroendocrine phenotype in prostate cancer in the context of their known cellular neurodevelopmental processes. We also discuss the role of tumor microenvironment in neuroendocrine plasticity, future directions, and therapeutic options under clinical investigation for neuroendocrine prostate cancer.

Abstract

Neuroendocrine plasticity and treatment-induced neuroendocrine phenotypes have recently been proposed as important resistance mechanisms underlying prostate cancer progression. Treatment-induced neuroendocrine prostate cancer (t-NEPC) is highly aggressive subtype of castration-resistant prostate cancer which develops for one fifth of patients under prolonged androgen deprivation. In recent years, understanding of molecular features and phenotypic changes in neuroendocrine plasticity has been grown. However, there are still fundamental questions to be answered in this emerging research field, for example, why and how do the prostate cancer treatment-resistant cells acquire neuron-like phenotype. The advantages of the phenotypic change and the role of tumor microenvironment in controlling cellular plasticity and in the emergence of treatment-resistant aggressive forms of prostate cancer is mostly unknown. Here, we discuss the molecular and functional links between neurodevelopmental processes and treatment-induced neuroendocrine plasticity in prostate cancer progression and treatment resistance. We provide an overview of the emergence of neurite-like cells in neuroendocrine prostate cancer cells and whether the reported t-NEPC pathways and proteins relate to neurodevelopmental processes like neurogenesis and axonogenesis during the development of treatment resistance. We also discuss emerging novel therapeutic targets modulating neuroendocrine plasticity.

MicroRNA determinants of neuroendocrine differentiation in metastatic castration-resistant prostate cancer

Therapy-induced neuroendocrine prostate cancer (NEPC), an extremely aggressive variant of castration-resistant prostate cancer (CRPC), is increasing in incidence with the widespread use of highly potent androgen receptor (AR)-pathway inhibitors (APIs) such as Enzalutamide (ENZ) and Abiraterone and arises via a reversible trans-differentiation process, referred to as neuroendocrine differentiation (NED). The molecular basis of NED is not completely understood leading to a lack of effective molecular markers for its diagnosis. Here, we demonstrate for the first time, that lineage switching to NE states is accompanied by key miRNA alterations including downregulation of miR-106a~363 cluster and upregulation of miR-301a and miR-375. To systematically investigate the key miRNAs alterations driving therapy-induced NED, we performed small RNA-NGS in a retrospective cohort of human metastatic CRPC clinical samples + PDX models with adenocarcinoma features (CRPC-adeno) vs those with neuroendocrine features (CRPC-NE). Further, with the application of machine learning algorithms to sequencing data, we trained a 'miRNA classifier' that could robustly classify 'CRPC-NE' from 'CRPC-Adeno' cases. The performance of classifier was validated in an additional cohort of mCRPC patients and publicly available PCa cohorts. Importantly, we demonstrate that miR-106a~363 cluster pleiotropically regulate cardinal nodal proteins instrumental in driving NEPC including Aurora Kinase A, N-Myc, E2F1 and STAT3. Our study has important clinical implications and transformative potential as our 'miRNA classifier' can be used as a molecular tool to stratify mCRPC patients into those with/without NED and guide treatment decisions. Further, we identify novel miRNA NED drivers that can be exploited for NEPC therapeutic targeting.

Powerful quantifiers for cancer transcriptomics

Every day, investigators find a new link between a form of cancer and a particular alteration in the sequence or/and expression level of a key gene, awarding this gene the title of “biomarker”. The clinician may choose from numerous available panels to assess the type of cancer based on the mutation or expression regulation (“transcriptomic signature”) of “driver” genes. However, cancer is not a “one-gene show” and, together with the alleged biomarker, hundreds other genes are found as mutated or/and regulated in cancer samples. Regardless of the platform, a well-designed transcriptomic study produces three independent features for each gene: Average expression level, expression variability and coordination with expression of each other gene. While the average expression level is used in all studies to identify what genes were up-/down-regulated or turn on/off, the other two features are unfairly ignored. We use all three features to quantify the transcriptomic change during the progression of the disease and recovery in response to a treatment. Data from our published microarray experiments on cancer nodules and surrounding normal tissue from surgically removed tumors prove that the transcriptomic topologies are not only different in histopathologically distinct regions of a tumor but also dynamic and unique for each human being. We show also that the most influential genes in cancer nodules [the Gene Master Regulators (GMRs)] are significantly less influential in the normal tissue. As such, “smart” manipulation of the cancer GMRs expression may selectively kill cancer cells with little consequences on the normal ones. Therefore, we strongly recommend a really personalized approach of cancer medicine and present the experimental procedure and the mathematical algorithm to identify the most legitimate targets (GMRs) for gene therapy.

Doublecortin Expression in Prostate Adenocarcinoma and Neuroendocrine Tumors

PURPOSE

Recent work using prostate cancer mouse models implicated doublecortin (DCX)-expressing neural progenitor cells in prostate adenocarcinoma, reporting a strong association between DCX expression and histologic grade and clinical outcome. We sought to evaluate the relationship between DCX expression and these variables in human prostate cancer.

METHODS AND MATERIALS

DCX expression was measured in transcriptome-wide microarray data from 18,501 patients with localized prostate cancer and 290 patients with metastatic castration-resistant prostate cancer (mCRPC) and compared across disease states, histologic grades, and clinical outcomes. Biochemical recurrence-free survival (BRFS), metastasis-free survival (MFS), and overall survival (OS) were analyzed using Cox proportional hazards.

RESULTS

DCX expression was not significantly different among normal prostate (n = 29), primary prostate cancer (n = 131), and metastases (n = 19) and did not increase with grade in a large cohort of radical prostatectomy samples (n = 17,967). Those with DCX expression above and below the median did not have significant differences in BRFS (HR 1.15 [95% confidence interval, 0.88-1.49], P = .31), MFS (HR 1.2 [0.84-1.7], P = .3), or OS (HR 1.15 [0.7-1.84], P = .56). In a cohort with untreated prostate cancer, DCX expression was higher in neuroendocrine tumors (n = 10) compared with grade group 5 prostate adenocarcinoma (n = 110) (P = .007). Similarly, in 2 cohorts with mCRPC (n = 290), DCX expression was higher in lesions with neuroendocrine features compared with adenocarcinoma (P < .001).

CONCLUSIONS

Contrary to recent data using mouse models, DCX expression did not differ by disease state or outcome and did not increase with grade in a large data set of patients with prostate adenocarcinoma. However, DCX expression appeared to correlate with neuroendocrine histology, a subgroup that can arise de novo or in the castrate-resistant setting. Further work is needed to define the role of DCX and its clinical significance in prostate cancer.

Characterization of the prognostic values and response to immunotherapy/chemotherapy of Krüppel-like factors in prostate cancer

At present, the overall genetic and epigenetic effects of Krüppel‐like factors (KLFs) on prostate cancer (PCa) remain unclear. Therefore, we systematically investigated the molecular differences in KLFs of transcription expression, promoter methylation and genetic alteration. Univariate and multivariate Cox proportional hazard regression was used to analyse the effect on RFS and establish the prognostic signature in the TCGA cohort, MSKCC and GSE116918 cohorts employed to validate the signature. Biological pathway enrichment and the potential response to immunotherapy and chemotherapy were inferred. The transcription levels of most KLFs are associated with the clinical outcome of PCa. Gleason score (P = .009), pathology T stage (P = .006), KLF3 (P = .034), KLF5 (P = .002) and KLF7 (P = .035) were independent prognostic factors. A prognostic signature was established in the TCGA cohort (P < .001) and validated in the MSKCC (P < .001) and GSE116918 cohorts (P = .006). Demethylation of KLF5 by 5‐azacytidine led to increased protein levels, whereas knockdown of KLF5 promoted cell proliferation. Patients in KLF‐F were more likely to respond to immunotherapy (P < .001) and bicalutamide (P < .001). In summary, we found that the KLFs and clinical feature‐based signatures may improve prognosis prediction in PCa and further promote patient stratification and disease management.

Gene Expression Signature Predictive of Neuroendocrine Transformation in Prostate Adenocarcinoma

Neuroendocrine prostate cancer (NEPC) can arise de novo, but much more commonly occurs as a consequence of a selective pressure from androgen deprivation therapy or androgen receptor antagonists used for prostate cancer (PCa) treatment. The process is known as neuroendocrine transdifferentiation. There is little molecular characterization of NEPCs and consequently there is no standard treatment for this kind of tumors, characterized by highly metastases rates and poor survival. For this purpose, we profiled 54 PCa samples with more than 10-years follow-up for gene and miRNA expression. We divided samples into two groups (NE-like vs. AdenoPCa), according to their clinical and molecular features. NE-like tumors were characterized by a neuroendocrine fingerprint made of known neuroendocrine markers and novel molecules, including long non-coding RNAs and components of the estrogen receptor signaling. A gene expression signature able to predict NEPC was built and tested on independently published datasets. This study identified molecular features (protein-coding, long non-coding, and microRNAs), at the time of surgery, that may anticipate the NE transformation process of prostate adenocarcinoma. Our results may contribute to improving the diagnosis and treatment of this subgroup of tumors for which traditional therapy regimens do not show beneficial effects.

Androgen deprivation upregulates SPINK1 expression and potentiates cellular plasticity in prostate cancer

Emergence of an aggressive androgen receptor (AR)-independent neuroendocrine prostate cancer (NEPC) after androgen-deprivation therapy (ADT) is well-known. Nevertheless, the majority of advanced-stage prostate cancer patients, including those with SPINK1-positive subtype, are treated with AR-antagonists. Here, we show AR and its corepressor, REST, function as transcriptional-repressors of SPINK1, and AR-antagonists alleviate this repression leading to SPINK1 upregulation. Increased SOX2 expression during NE-transdifferentiation transactivates SPINK1, a critical-player for maintenance of NE-phenotype. SPINK1 elicits epithelial-mesenchymal-transition, stemness and cellular-plasticity. Conversely, pharmacological Casein Kinase-1 inhibition stabilizes REST, which in cooperation with AR causes SPINK1 transcriptional-repression and impedes SPINK1-mediated oncogenesis. Elevated levels of SPINK1 and NEPC markers are observed in the tumors of AR-antagonists treated mice, and in a subset of NEPC patients, implicating a plausible role of SPINK1 in treatment-related NEPC. Collectively, our findings provide an explanation for the paradoxical clinical-outcomes after ADT, possibly due to SPINK1 upregulation, and offers a strategy for adjuvant therapies.

Differential Expression of Glucose Transporters and Hexokinases in Prostate Cancer with a Neuroendocrine Gene Signature: A Mechanistic Perspective for 18F-FDG Imaging of PSMA-Suppressed Tumors

Although the incidence of de novo neuroendocrine prostate cancer (PC) is rare, recent data suggest that low expression of prostate-specific membrane antigen (PSMA) is associated with a spectrum of neuroendocrine hallmarks and androgen receptor (AR) suppression in PC. Previous clinical reports indicate that PCs with a phenotype similar to neuroendocrine tumors can be more amenable to imaging by ¹⁸F-FDG than by PSMA-targeting radioligands. In this study, we evaluated the association between neuroendocrine gene signature and ¹⁸F-FDG uptake-associated genes including glucose transporters (GLUTs) and hexokinases, with the goal of providing a genomic signature to explain the reported ¹⁸F-FDG avidity of PSMA-suppressed tumors. Methods: Data-mining approaches, cell lines, and patient-derived xenograft models were used to study the levels of 14 members of the SLC2A family (encoding GLUT proteins), 4 members of the hexokinase family (genes HK1-HK3 and GCK), and PSMA (FOLH1 gene) after AR inhibition and in correlation with neuroendocrine hallmarks. Also, we characterize a neuroendocrine-like PC (NELPC) subset among a cohort of primary and metastatic PC samples with no neuroendocrine histopathology. We measured glucose uptake in a neuroendocrine-induced in vitro model and a zebrafish model by nonradioactive imaging of glucose uptake using a fluorescent glucose bioprobe, GB2-Cy3. Results: This work demonstrated that a neuroendocrine gene signature associates with differential expression of genes encoding GLUT and hexokinase proteins. In NELPC, elevated expression of GCK (encoding glucokinase protein) and decreased expression of SLC2A12 correlated with earlier biochemical recurrence. In tumors treated with AR inhibitors, high expression of GCK and low expression of SLC2A12 correlated with neuroendocrine histopathology and PSMA gene suppression. GLUT12 suppression and upregulation of glucokinase were observed in neuroendocrine-induced PC cell lines and patient-derived xenograft models. A higher glucose uptake was confirmed in low-PSMA tumors using a GB2-Cy3 probe in a zebrafish model. Conclusion: A neuroendocrine gene signature in neuroendocrine PC and NELPC associates with a distinct transcriptional profile of GLUTs and hexokinases. PSMA suppression correlates with GLUT12 suppression and glucokinase upregulation. Alteration of ¹⁸F-FDG uptake-associated genes correlated positively with higher glucose uptake in AR- and PSMA-suppressed tumors. Zebrafish xenograft tumor models are an accurate and efficient preclinical method for monitoring nonradioactive glucose uptake.