A-methylacyl-CoA racemase (AMACR) and prostate-cancer risk: a meta-analysis of 4,385 participants

Mitochondrial ribosomal proteins in metastasis and their potential use as prognostic and therapeutic targets

The mitochondrion is an essential cell organelle known as the powerhouse of the cell. Mitochondrial ribosomal proteins (MRPs) are nuclear encoded, synthesised in the cytoplasm but perform their main functions in the mitochondria, which includes translation, transcription, cell death and maintenance. However, MRPs have also been implicated in cancer, particularly advanced disease and metastasis across a broad range of cancer types, where they play a central role in cell survival and progression. For some, their altered expression has been investigated as potential prognostic markers, and/or therapeutic targets, which is the focus of this review. Several therapies targeting MRPs are currently approved by the Food and Drug Administration and the European Medicines Agency for use in other diseases, revealing the opportunity for repurposing their use in advanced and metastatic cancer. Herein, we review the evidence supporting key MRPs as molecular drivers of advanced disease in multiple cancer types. We also highlight promising avenues for future use of MRPs as precision targets in the treatment of late-stage cancers for which there are currently very limited effective treatment options.

Prostate cancer: Novel genetic and immunologic biomarkers

Prostate cancer (PCa) is considered one of the most prevalent male malignancies worldwide with a global burden estimated to increase over the next two decades. Due to significant mortality and debilitation of survival, early diagnosis has been described as key. Unfortunately, current diagnostic serum-based strategies have low specificity and sensitivity. Histologic examination is invasive and not useful for treatment and monitoring purposes. Hence, a plethora of studies have been conducted to identify and validate an efficient noninvasive approach in the diagnosis, staging, and prognosis of PCa. These investigations may be categorized as genetic (non-coding biomarkers and gene markers), immunologic (immune cells, interleukins, cytokines, antibodies, and auto-antibodies), and heterogenous (PSA-related markers, PHI-related indices, and urinary biomarkers) subgroups. This review examines current approaches and potential strategies using biomarker panels in PCa.

Analysis of genetic biomarkers, polymorphisms in ADME-related genes and their impact on pharmacotherapy for prostate cancer

Prostate cancer (PCa) is a non-cutaneous malignancy in males with wide variation in incidence rates across the globe. It is the second most reported cause of cancer death. Its etiology may have been linked to genetic polymorphisms, which are not only dominating cause of malignancy casualties but also exerts significant effects on pharmacotherapy outcomes. Although many therapeutic options are available, but suitable candidates identified by useful biomarkers can exhibit maximum therapeutic efficacy. The single-nucleotide polymorphisms (SNPs) reported in androgen receptor signaling genes influence the effectiveness of androgen receptor pathway inhibitors and androgen deprivation therapy. Furthermore, SNPs located in genes involved in transport, drug metabolism, and efflux pumps also influence the efficacy of pharmacotherapy. Hence, SNPs biomarkers provide the basis for individualized pharmacotherapy. The pharmacotherapeutic options for PCa include hormonal therapy, chemotherapy (Docetaxel, Mitoxantrone, Cabazitaxel, and Estramustine, etc.), and radiotherapy. Here, we overview the impact of SNPs reported in various genes on the pharmacotherapy for PCa and evaluate current genetic biomarkers with an emphasis on early diagnosis and individualized treatment strategy in PCa.

Sustained release of alpha-methylacyl-CoA racemase (AMACR) antibody-conjugated and free doxorubicin from silica nanoparticles for prostate cancer cell growth inhibition

This article presents silica nanoparticles for the sustained release of AMACR antibody-conjugated and free doxorubicin (DOX) for the inhibition of prostate cancer cell growth. Inorganic MCM-41 silica nanoparticles were synthesized, functionalized with phenylboronic acid groups (MCM-B), and capped with dextran (MCM-B-D). The nanoparticles were then characterized using Fourier-transform infrared spectroscopy, scanning electron microscopy, transmission electron microscopy, zeta potential analysis, nitrogen sorption, X-ray diffraction, and thermogravimetric analysis, before exploring their potential for drug loading and controlled drug release. This was done using a model prostate cancer drug, DOX, and a targeted prostate cancer drug, α-Methyl Acyl-CoA racemase (AMACR) antibody-conjugated DOX, which attaches specifically to AMACR proteins that are overexpressed on the surfaces of prostate cancer cells. The kinetics of sustained drug release over 30 days was then studied using zeroth order, first order, second order, Higuchi, and the Korsmeyer-Peppas models, while the thermodynamics of drug release was elucidated by determining the entropy and enthalpy changes. The flux of the released DOX was also simulated using the COMSOL Multiphysics software package. Generally, the AMACR antibody-conjugated DOX drug-loaded nanoparticles were more effective than the free DOX drug-loaded formulations in inhibiting the growth of prostate cancer cells in vitro over a 96 h period. The implications of the results are then discussed for the development of drug-eluting structures for the localized and targeted treatment of prostate cancer.

ETS transcription factor ELF3 (ESE-1) is a cell cycle regulator in benign and malignant prostate

This study aimed to elucidate the role of ELF3, an ETS family member in normal prostate growth and prostate cancer. Silencing ELF3 in both benign prostate (BPH-1) and prostate cancer (PC3) cell lines resulted in decreased colony forming ability, inhibition of cell migration and reduced cell viability due to cell cycle arrest, establishing ELF3 as a cell cycle regulator. Increased ELF3 expression in more advanced prostate tumours was shown by immunostaining of tissue microarrays and from analysis of gene expression and genetic alteration studies. This study indicates that ELF3 functions as part of normal prostate epithelial growth but also as a potential oncogene in advanced prostate cancers.

Diagnostic utility of a-methylacyl COA racemase in prostate cancer of the Iranian population

Background:

Considering the great variations in the reported prevalence of prostate cancer across the world possibly due to different genetic and environmental backgrounds, we aimed to determine the expression pattern and the diagnostic utility of α-methylacyl coenzyme A racemase (AMACR) among Iranian patients with prostate adenocarcinoma.

Materials and Methods:

In this cross-sectional study, formalin-fixed paraffin-embedded tissues of 58 patients with a definitive pathologic diagnosis of prostatic adenocarcinoma were evaluated. The expression of AMACR, intensity, and extensity of its staining was determined in selected samples by immunohistochemical technique.

Results:

AMACR expression was significantly higher in neoplastic compared to normal tissue (P < 0.05). The expression of AMACR was significantly associated with the age of the patients (P = 0.04). The intensity of the staining was associated with the grade of the prostate adenocarcinoma (P = 0.04). There was no significant relationship between AMACR expression and perineural invasion. The sensitivity, specificity, positive predictive value, and negative predictive value of AMACR were 90%, 96%, 96%, and 90%, respectively.

Conclusion:

Findings from our study indicate that AMACR could be used as a diagnostic tool for the diagnosis of prostate adenocarcinoma. However, due to false-positive staining in the mimicker of prostatic adenocarcinoma, it is recommended to use it in combination with basal cell markers.

Molecular mechanisms, immune cell infiltration, and potential drugs for prostate cancer

BACKGROUND

The molecular mechanisms involved in the prostate cancer and their relationship with immune cell infiltration are not fully understood. The prostate cancer patients undergoing standard androgen deprivation therapy eventually develop castration resistant prostate cancer (CRPC) for which there is no effective treatment currently available, and the hub genes involved in this process remain unclear.

OBJECTIVE

To study prostate cancer systematically and comprehensively.

METHODS

Differentially expressed genes (DEGs) of prostate cancer were screened in The Cancer Genome Atlas (TCGA) database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. Connectivity Map (Cmap) software was applied to discover potential treatment drugs. A protein-protein interaction (PPI) analysis was performed to obtained the hub genes, and the relationship between hub genes and immune cell infiltration was investigated. Next, RNAseq data of hormone-sensitive prostate cancer samples and CRPC samples obtained from TCGA database was further analyzed to identify DEGs. Finally, a PPI analysis was performed to obtain the hub genes.

RESULTS

A total of 319 DEGs were identified between prostate cancer samples and normal adjacent samples from TCGA database using comparative analysis. The KEGG pathway analysis showed significant correlations with drug metabolism, metabolism of xenobiotics by cytochrome P450, and chemical carcinogenesis. AMACR, FOLH1 and NPY, three hub genes, were found to be upregulated. FOLH1 was positively correlated with CD8+ T cell infiltration. FOLH1, AMACR, and NPY were negatively correlated with CD4+ T cell infiltration. A total of 426 DEGs were identified from RNAseq data of hormone-sensitive prostate cancer samples and CRPC samples using further comparative analysis. KEGG pathway enrichment analysis showed significant correlations with arachidonic acid metabolism, PPAR signaling pathway, AMPK signaling pathway, and metabolic pathways. The top 10 hub genes in PPI network were screened out, including PPARG, SREBF1, SCD, HMGCR, FASN, PTGS2, HMGCS2, SREBF2, FDFT1, and INSIG1. Among them, SCD and FASN are expected to be the potential therapeutic targets for CRPC.

CONCLUSIONS

AMACR, FOLH1 and NPY may be effective therapeutic targets and specific diagnostic markers for prostate cancer. AMACR, FOLH1, and NPY are also closely associated with immune cell infiltration in prostate cancer. Moreover, aminoglutethimide and resveratrol were found to be the promising drugs for treating prostate cancer. The progression of hormone-sensitive prostate cancer to CRPC may be related to arachidonic acid metabolism, PPAR signaling pathway, AMPK signaling pathway, and other metabolic pathways. SCD and FASN are expected to be the potential therapeutic targets for CRPC.

Screening of differentially expressed genes and identification of AMACR as a prognostic marker in prostate cancer

Prostate cancer, the second most common cancer found in male over the world, was estimated to have 191,930 new cases and 33,330 deaths in 2020 in the United States. Prostate cancer is very common in male, about 12.1% of men will acquire this cancer in their lifetime, and a higher risk was reported in older men and African American men. Gene deregulations have been found to be extensively associated with cancer development. To gain further insight into how gene deregulation affects prostate cancer, we analysed three gene profiling datasets of prostate cancer from Gene Expression Omnibus (GEO) applying bioinformatic tools in our study. Firstly, we identified common differently expressed genes (DEGs) shared by the three gene profiling datasets, constructed protein-protein interaction network and determined top 10 hub genes. Further DEGs validation in TCGA and Human Protein Atlas Database identified AMACR as the core gene. We then analysed the role of AMACR in prostate cancer cell lines and found that AMACR-knockdown resulted in the decreased cell proliferation and increased apoptosis. These results suggest an oncogenic role of AMACR in prostate cancer, and it could be a potential biomarker for the diagnosis of prostate cancer.

Sex-dependent expression of prostatic markers and hormone receptors in cystic tumor of the atrioventricular node: A histopathological study of three cases

We pathologically investigated three autopsy cases of cystic tumor of the atrioventricular node (CTAVN) with sudden death. Case 1 was a 36-year-old woman without any clinical history. Case 2 was a 76-year-old man with an implanted pacemaker for complete atrioventricular block. Case 3 was a 45-year-old man with a history of first-degree AV block and sinus bradycardia. Microscopically, all three cases showed the bilayered structure of tumor glands and corpora amylacea in the glandular lumens. Immunohistochemically, the inner cells of the tumor glands were positive for cytokeratin CAM5.2, CEA, EMA, olfactomedin-4 and alpha-methylacyl-coenzyme A racemase; the outer cells were positive for p63 and cytokeratin high molecular weight. In Case 1, androgen receptor and estrogen receptor were negative; progesterone receptor was focally positive in both the inner and outer cells. In Case 2, androgen receptor showed intermediate positivity in the inner cells; estrogen receptor and progesterone receptor were positive in the outer cells. Positive expression of both prostate-specific antigen and prostate-specific acid phosphate were found in the inner cells of both male cases. Because CTAVN cells exhibit different degrees of the prostatic phenotype depending on the patient's sex, we believe that CTAVN may originate from urogenital sinus tissue in some cases.

Association of polymorphisms of PTEN, AKT1, PI3K, AR, and AMACR genes in patients with prostate cancer

Polymorphic variants in the PTEN (rs2735343), PI3K (rs2699887), AKT1 (rs2494750), AR (rs17302090), and AMACR (rs3195676) genes were evaluated as possible molecular markers of susceptibility, prognosis, and progression of prostate cancer (PCa), in a case-control study. Samples consisted of 277 patients with PCa and 277 controls from Londrina, PR, Brazil. SNPs were analyzed by real-time PCR. A family history of cancer, including PCa, as well as level of schooling were risk factors for PCa. The data were obtained via logistic regression, using odds ratios with a CI 95%. The genotypes of AKT1 and AKT1+AR demonstrated an association with protection for the disease. The combination of SNPs with the histopathological tumor data between allele variants of AMACR, AKT1+AR, and AKT1+AMACR indicated an association with protection against seminal vesicle invasion. The polymorphisms AKT1+AR and PI3K+AR were associated with protection against tumor bilaterality. The genotype combinations PTEN+AMACR and PTEN+AR were associated with the risk of extracapsular extension. Of the five genes studied, two were associated with protection for PCa, four were associated with protection for some prognostic variables, and only one was associated with risk. Thus, these SNPs are candidates for markers to discriminate men with better or worse prognosis for PCa.

Circulating mRNA signature as a marker for high-risk prostate cancer

Prostate cancer (PCa) is the second most common cancer in men. The indolent course of the disease makes the treatment choice a challenge for physicians and patients. In this study, a minimally invasive method was used to evaluate the potential of molecular markers in identifying patients with aggressive disease. Cell-free plasma samples from 60 PCa patients collected before radical prostatectomy were used to evaluate the levels of expression of eight genes (AMACR, BCL2, NKX3-1, GOLM1, OR51E2, PCA3, SIM2 and TRPM8) by quantitative real-time PCR. Overexpression of AMACR, GOLM1, TRPM8 and NKX3-1 genes was significantly associated with aggressive disease characteristics, including extracapsular extension, tumor stage and vesicular seminal invasion. A trio of genes (GOLM1, NKX3-1 and TRPM8) was able to identify high-risk PCa cases (85% of sensitivity and 58% of specificity), yielding a better overall performance compared with the biopsy Gleason score and prostate-specific antigen, routinely used in the clinical practice. Although more studies are required, these circulating markers have the potential to be used as an additional test to improve the diagnosis and treatment decision of high-risk PCa patients.

Netrin 1 and Alpha-Methyl Acylcoenzim-A Racemase in diagnosis of prostate cancer

Objectives

To investigate serum and urine levels of Alpha-methylacyl-CoA-racemase (AMACR) and Netrin 1 in patients with and without prostate cancer and to determine whether these markers could be used as alternatives in diagnosis of prostate cancer instead of serum prostate specific antigen (PSA) levels.

Methods

One hundred and seventy five patients between 45-75 years to whom transrectal ultrasound guided biopsies were performed for abnormal serum PSA levels or digital rectal examinations were included. The levels of AMACR and Netrin 1 levels of blood and urine samples of 5 mL those were taken prior to biopsies were measured. .

Results

The mean age of the patients was 62.7 ±6.4 years. Prostate cancer was detected in 40 patients (22.8%) while 135 of them (77.2%) were diagnosed as benign prostate hyperplasia (BPH). In BPH group, serum and urine levels of AMACR and Netrin 1 were 13.4 ±16.9 ng/mL; 7.1 ±3.4 ng/mL; 164.1±46 pg/mL and 19.5 ±5.0 pg/mL respectively. The levels of serum and urine levels of AMACR and Netrin 1 were 10.2 ±9.8 ng/mL; 6.8 ±2.5 ng/mL; 159.1 ±44.1 pg/mL and 20.1 ±5.3 pg/mL respectively in prostate cancer group. There was no statistically significant difference or correlation between these two groups serum and urine AMACR and Netrin 1 results.

Conclusions

Serum and urine levels of AMACR and Netrin 1 were not found to be alternatives for serum PSA levels in the diagnosis of prostate cancer in this study.

Impairment of IGF2 gene expression in prostate cancer is triggered by epigenetic dysregulation of IGF2-DMR0 and its interaction with KLF4

Background

Human cancer cells often exhibit impaired IGF2 expression and the underlying mechanisms are multifaceted and complex. Besides the well-known imprinting control region IGF2/H19-ICR, the involvement of a differentially methylated region in the promoter P0 of IGF2 gene (IGF2-DMR0) has been suggested. Here, we evaluate several mechanisms potentially leading to up- and/or down-regulation of IGF2 expression in prostate cancer and present a novel role of Kruppel-like factor 4 (KLF4) as a transcriptional regulator of IGF2 binding in IGF2-DMR0.

Methods

Putative binding sites for transcription factors were identified in IGF2-DMR0 using JASPAR CORE database. Gene expressions were analyzed by RT-qPCR in prostate carcinoma and adjacent benign prostate hyperplasia samples obtained by radical prostatectomy (86 RP-PCa and 47 RP-BPH) and BPH obtained by transurethral prostate resection (13 TUR-BPH). Pyrosequencing and qMSP were used for DNA methylation studies in IGF2-DMR0, IGF2/H19-ICR and Glutathione-S-transferase-P1 (GSTP1) promoter. Loss of imprinting (LOI) was analyzed by RFLP. Copy number variation (CNV) test was performed using qBiomarker CNV PCR Assay. KLF4-binding and histone-modifications were analyzed by ChIP-qPCR in prostate cancer cell lines exhibiting differentially methylated IGF2-DMR0 (LNCaP hypomethylated and DU145 hypermethylated). KLF4 protein was analyzed by western blot. Statistical associations of gene expression to methylation, IGF2 LOI and CNV were calculated by Mann-Whitney-U-test. Correlations between gene expression and methylation levels were evaluated by Spearman’s-Rank-Correlation-test.

Results

We found a significant reduction of IGF2 expression in the majority of RP-PCa and RP-BPH in comparison to TUR-BPH. Analyzing potential molecular reasons, we found in RP-PCa and RP-BPH in comparison to TUR-BPH a significant hypomethylation of IGF2-DMR0, which coincided with hypermethylation of GSTP1-promoter, a prominent marker of prostate tumors. In contrast, IGF2 LOI and CNV did not associate significantly with up- and/or down-regulation of IGF2 expression in prostate tumors. By analyzing IGF2-DMR0, we detected a consensus sequence for KLF4 with a z-score of 7.6. Interestingly, we found that KLF4 binds to hypomethylated (17%) IGF2-DMR0 enriched with H3K9me3 and H3K27me3 (LNCaP), but does not bind under hypermethylated (85%) and H3K4me3-enriched conditions (DU145). KLF4 expression was detected in TUR-BPH as well as in RP-BPH and RP-PCa and showed a highly significant correlation to IGF2 expression.

Conclusions

Our study demonstrated that in human prostate cancer the impairment of IGF2 expression is accompanied by hypomethylation of IGF2-DMR0. We revealed that KLF4 is a putative transcriptional regulator of IGF2, which binds in IGF2-DMR0 in dependence of the prevailing epigenetic state in this region. Herewith we provide complementary new insights into IGF2 dysregulation mechanisms as a critical process in prostate tumorigenesis.

Urinary RNA-based biomarkers for prostate cancer detection

Prostate cancer (PCa) is the commonest malignancy in the male population worldwide. Serum prostate specific antigen (PSA) test is the most important biomarker for the detection, follow-up and therapeutic monitoring of PCa. Defects in PSA specificity have elicited research for new biomarkers to improve early diagnosis and avoid false-positive results. This review evaluates urinary RNA-based biomarkers. Urine is a versatile body fluid for non-invasive biomarker detection in case of urological malignancies. The importance of RNA-based biomarkers has been demonstrated by the current use of PCA3, a long non coding RNA biomarker already approved by the Food and Drugs Administration. Through the years, other urinary RNA biomarkers have been evaluated, including the well-known TMPRSS2:ERG transcript, as well as many messenger RNAs, long non coding RNAs and micro-RNA. Validation of a specific urinary RNA-based marker or an algorithm of different biomarkers levels as diagnostic markers for PCa could be useful to avoid unnecessary prostate biopsies.

Novel RNA biomarkers of prostate cancer revealed by RNA-seq analysis of formalin-fixed samples obtained from Russian patients

Due to heterogeneous multifocal nature of prostate cancer (PCa), there is currently a lack of biomarkers that stably distinguish it from benign prostatic hyperplasia (BPH), predict clinical outcome and guide the choice of optimal treatment. In this study RNA-seq analysis was applied to formalin-fixed paraffin-embedded (FFPE) tumor and matched normal tissue samples collected from Russian patients with PCa and BPH. We identified 3384 genes differentially expressed (DE) (FDR < 0.05) between tumor tissue of PCa patients and adjacent normal tissue as well as both tissue types from BPH patients. Overexpression of four of the discovered genes (ANKRD34B, NEK5, KCNG3, and PTPRT) was validated by RT-qPCR. Furthermore, the enrichment analysis of overrepresented microRNA and transcription factor (TF) recognition sites within DE genes revealed common regulatory elements of which 13 microRNAs and 53 TFs were thus linked to PCa for the first time. Moreover, 8 of these TFs (FOXJ2, GATA6, NFE2L1, NFIL3, PRRX2, TEF, EBF2 and ZBTB18) were found to be differentially expressed in this study making them not only candidate biomarkers of prostate cancer but also potential therapeutic targets.

The context of prostate cancer genomics in personalized medicine

Prostate cancer is one of the most common types of cancer in males. Heterogeneous genomic aberrations may lead to prostate cancer onset, progression and metastasis. This heterogeneity also contributes to the variety in cancer risk and outcomes, different drug responses and progression, observed between individual patients. Classical prognostic factors, including prostate-specific antigen, Gleason Score and clinical tumor staging, are not sufficient to portray the complexity of a clinically relevant cancer diagnosis, risk prognosis, treatment choice and therapy monitoring. There is a requirement for novel genetic biomarkers in order to understand the oncogenic heterogeneity in a patient-personalized clinical setting and to improve the efficacy of risk prognosis and treatment choice. A number of biomarkers and gene panels have been established from patient sample cohort studies. These previous studies have provided distinct information to the investigation of heterogeneous malignancy in prostate cancer, which aids in clinical decision-making. Biomarker-guided therapies may facilitate the effective selection of drugs during early treatment; therefore, are beneficial to the individual patient. A non-invasive approach allows for convenient and repeated sampling to screen for cancer and monitor treatment response without the requirement for invasive tissue biopsies. With the current availability of numerous advanced technologies, reliable detection of the minimal tumor residues present following treatment may become clinical practice and, therefore, inform further in the field of personalized medicine.

Role of tumor microenvironment in tumorigenesis

Tumorigenesis is a complex and dynamic process, consisting of three stages: initiation, progression, and metastasis. Tumors are encircled by extracellular matrix (ECM) and stromal cells, and the physiological state of the tumor microenvironment (TME) is closely connected to every step of tumorigenesis. Evidence suggests that the vital components of the TME are fibroblasts and myofibroblasts, neuroendocrine cells, adipose cells, immune and inflammatory cells, the blood and lymphatic vascular networks, and ECM. This manuscript, based on the current studies of the TME, offers a more comprehensive overview of the primary functions of each component of the TME in cancer initiation, progression, and invasion. The manuscript also includes primary therapeutic targeting markers for each player, which may be helpful in treating tumors.

A New Combinatorial Optimization Approach for Integrated Feature Selection Using Different Datasets: A Prostate Cancer Transcriptomic Study

Background

The joint study of multiple datasets has become a common technique for increasing statistical power in detecting biomarkers obtained from smaller studies. The approach generally followed is based on the fact that as the total number of samples increases, we expect to have greater power to detect associations of interest. This methodology has been applied to genome-wide association and transcriptomic studies due to the availability of datasets in the public domain. While this approach is well established in biostatistics, the introduction of new combinatorial optimization models to address this issue has not been explored in depth. In this study, we introduce a new model for the integration of multiple datasets and we show its application in transcriptomics.

Methods

We propose a new combinatorial optimization problem that addresses the core issue of biomarker detection in integrated datasets. Optimal solutions for this model deliver a feature selection from a panel of prospective biomarkers. The model we propose is a generalised version of the (α,β)-k-Feature Set problem. We illustrate the performance of this new methodology via a challenging meta-analysis task involving six prostate cancer microarray datasets. The results are then compared to the popular RankProd meta-analysis tool and to what can be obtained by analysing the individual datasets by statistical and combinatorial methods alone.

Results

Application of the integrated method resulted in a more informative signature than the rank-based meta-analysis or individual dataset results, and overcomes problems arising from real world datasets. The set of genes identified is highly significant in the context of prostate cancer. The method used does not rely on homogenisation or transformation of values to a common scale, and at the same time is able to capture markers associated with subgroups of the disease.

Evolving transcriptomic fingerprint based on genome-wide data as prognostic tools in prostate cancer

Background Information

Prostate cancer (PCa) is a common disease but only a small subset of patients are at risk of developing metastasis and lethal disease, and identifying which patients will progress is challenging because of the heterogeneity underlying tumour progression. Understanding this heterogeneity at the molecular level and the resulting clinical impact is a critical step necessary for risk stratification. Defining genomic fingerprint elucidates molecular variation and may improve PCa risk stratification, providing more accurate prognostic information of tumour aggressiveness (or lethality) for prognostic biomarker development. Therefore, we explored transcriptomic differences between patients with indolent disease outcome and patients who developed metastasis post‐radical prostatectomy using genome‐wide expression data in the post radical prostatectomy clinical space before metastatic spread.

Results

Based on differential expression analysis, patients with adverse pathological findings who are at higher risk of developing metastasis have a distinct transcriptomic fingerprint that can be detected on surgically removed prostate specimens several years before metastasis detection. Nearly half of the transcriptomic fingerprint features were non‐coding RNA highlighting their pivotal role in PCa progression. Protein‐coding RNA features in the fingerprint are involved in multiple pathways including cell cycle, chromosome structure maintenance and cytoskeleton organisation. The metastatic transcriptomic fingerprint was determined in independent cohorts verifying the association between the fingerprint and metastatic patients. Further, the fingerprint was confirmed in metastasis lesions demonstrating that the fingerprint represents early metastatic transcriptomic changes, suggesting its utility as a prognostic tool to predict metastasis and provide clinical value in the early radical prostatectomy setting.

Conclusions

Here, we show that transcriptomic patterns of metastatic PCa exist that can be detected early after radical prostatectomy. This metastatic fingerprint has potential prognostic ability that can impact PCa treatment management potentially circumventing the requirements for unnecessary therapies.

Significant association of alpha-methylacyl-CoA racemase gene polymorphisms with susceptibility to prostate cancer: a meta-analysis

BACKGROUND

Alpha-methylacyl-CoA racemase(AMACR) is thought to play key roles in diagnosis and prognosis of prostate cancer. However, studies of associations between AMACR gene polymorphisms and prostate cancer risk reported inconsistent results. Therefore, we conducted the present meta-analysis to clarify the link between AMACR gene polymorphisms and prostate cancer risk.

MATERIALS AND METHODS

A literature search was performed in PubMed, Embase, China National Knowledge Infrastructure (CNKI), Wanfang and Weipu databases. Odds ratios (ORs) and 95% confidence intervals (95%CIs) were calculated to assess the strength of any association between AMACR polymorphisms and prostate cancer risk. Subgroup analyses by ethnicity, source of controls, quality control and sample size were also conducted.

RESULTS

Five studies covering 3,313 cases and 3,676 controls on five polymorphisms (D175G, M9V, S201L, K277E and Q239H) were included in this meta-analysis. Significant associations were detected between prostate cancer and D175G (dominant model: OR=0.89, 95%CI=0.80-0.99, P=0.04) and M9V (dominant model: OR=0.87, 95%CI=0.78-0.97, P=0.01) polymorphisms as well as that in subgroup analyses. We also observed significant decreased prostate cancer risk in the dominant model (OR=0.90, 95%CI=0.81-0.99, P=0.04) for the S201L polymorphism. However, K277E and Q239H polymorphisms did not appear to be related to prostate cancer risk.

CONCLUSIONS

The current meta- analysis indicated that D175G and M9V polymorphisms of the AMACR gene are related to prostate cancer. The S201L polymorphism might also be linked with prostate cancer risk to some extent. However, no association was observed between K277E or Q239H polymorphisms and susceptibility to prostate cancer.

Prostate cancer and neuroendocrine differentiation: more neuronal, less endocrine?

Neuroendocrine differentiation (NED) marks a structural and functional feature of certain cancers, including prostate cancer (PCa), whereby the malignant tissue contains a significant proportion of cells displaying neuronal, endocrine, or mixed features. NED cells produce, and can secrete, a cocktail of mediators commonly encountered in the nervous system, which may stimulate and coordinate cancer growth. In PCa, NED appears during advanced stages, subsequent to treatment, and accompanies treatment resistance and poor prognosis. However, the term “neuroendocrine” in this context is intrinsically vague. This article seeks to provide a framework on which a unified view of NED might emerge. First, we review the mutually beneficial interplay between PCa and neural structures, mainly supported by cell biology experiments and neurological conditions. Next, we address the correlations between PCa and neural functions, as described in the literature. Based upon the integration of clinical and basic observations, we suggest that it is legitimate to seek for true neural differentiation, or neuromimicry, in cancer progression, most notably in PCa cells exhibiting what is commonly described as NED.

The oestrogen receptor alpha-regulated lncRNA NEAT1 is a critical modulator of prostate cancer

The androgen receptor (AR) plays a central role in establishing an oncogenic cascade that drives prostate cancer progression. Some prostate cancers escape androgen dependence and are often associated with an aggressive phenotype. The oestrogen receptor alpha (ERα) is expressed in prostate cancers, independent of AR status. However, the role of ERα remains elusive. Using a combination of chromatin immunoprecipitation (ChIP) and RNA-sequencing data, we identified an ERα-specific non-coding transcriptome signature. Among putatively ERα-regulated intergenic long non-coding RNAs (lncRNAs), we identified nuclear enriched abundant transcript 1 (NEAT1) as the most significantly overexpressed lncRNA in prostate cancer. Analysis of two large clinical cohorts also revealed that NEAT1 expression is associated with prostate cancer progression. Prostate cancer cells expressing high levels of NEAT1 were recalcitrant to androgen or AR antagonists. Finally, we provide evidence that NEAT1 drives oncogenic growth by altering the epigenetic landscape of target gene promoters to favour transcription.