Genomic profiling defines subtypes of prostate cancer with the potential for therapeutic stratification

Defining the genetic profile of prostate cancer

Several studies indicated that prostate cancer has a hereditary component. In particular, a significant risk of prostate cancer has been linked to a tight familial lineage. However, to provide insight into how prostate cancer is inherited, characterising its genetic profile is essential. The current body of research on the analysis of genetic mutations in prostate cancer was reviewed to achieve this. This paper reports on the effects and underlying processes of prostate cancer that have been linked to decreased male fertility. Many research approaches used have resulted in the discovery of unique inheritance patterns and manifest traits, the onset and spread of prostate cancer have also been linked to many genes. Studies have specifically examined Androgen Receptor gene variants about prostate cancer risk and disease progression. Research has shown that genetic and environmental variables are important contributors to prostate cancer, even if the true origins of the disease are not fully recognised or established. Researchers studying the genetics of prostate cancer are using genome-wide association studies more and more because of their outstanding effectiveness in revealing susceptibility loci for prostate cancer. Genome-Wide Association Studies provides a detailed method for identifying the distinct sequence of a gene that is associated with cancer risk. Surgical procedures and radiation treatments are 2 of the treatment options for prostate cancer. Notwithstanding the compelling evidence shown in this work, suggests that more research must be done to detect the gene alterations and the use of genetic variants in the treatment of prostate cancer.

The microRNA-3622 family at the 8p21 locus exerts oncogenic effects by regulating the p53-downstream gene network in prostate cancer progression

For human prostate cancer, the chromosome 8p21 locus, which contains NKX3.1 and the microRNA (miR)-3622 family (miR-3622a/b), is a frequently deleted region. Thus, miR-3622 is proposed as a suppressor for prostate cancer, but its role remains debatable. In the present study, we found that expression of miR-3622a was lower, whereas expression of miR-3622b-3p was higher in human prostate cancer tissues than in normal prostate tissues. miR-3622a-3p inhibited cell migration and invasion of human prostate cancer cells, whereas miR-3622b-3p facilitated cell proliferation, migration, and invasion. To address the opposing roles of miR-3622 family members in various human prostate cancer cell lines, we knocked out (KO) endogenous miR-3622, including both miR-3622a/b. Our results showed that miR-3622 KO reduced cell proliferation, migration, and invasion in vitro and tumor growth and metastasis in vivo. Functional analyses revealed that miR-3622 regulated the p53-downstream gene network, including AIFM2, c-MYC, and p21, to control apoptosis and the cell cycle. Furthermore, using CRISPR interference, miRNA/mRNA immunoprecipitation assays, and dual-luciferase assays, we established that AIFM2, a direct target of miR-3622b-3p, is responsible for miR-3622 KO-induced apoptosis. We identified an miR-3622-AIFM2 axis that contributes to oncogenic function during tumor progression. In addition, miR-3622 KO inhibited the epithelial-mesenchymal transition involved in prostate cancer metastasis via upregulation of vimentin. The results show that miR-3622b-3p is upregulated in human prostate cancers and has an oncogenic function in tumor progression and metastasis via repression of p53 signaling, especially through an miR-3622-AIFM2 axis. In contrast, for human prostate cancer, deletion of the miR-3622 locus at 8p21 reduced the oncogenic effects on tumor progression and metastasis.

Impact of diverticular disease on prostate cancer risk among hypertensive men

INTRODUCTION

Prostate cancer (PCa) is a heterogenous disease with multiple etiological factors playing a role in its development. Recently, chronic and systemic inflammatory conditions such as inflammatory bowel disease were identified as key risk factors influencing its development. The study aimed to evaluate the relationship between diverticular disease (DD) (local and acute inflammation) and PCa.

METHODS

Hypertensive patients with DD and hypertensive controls were identified between 1995 and 2010 from the Statewide Planning and Research Cooperative System database. Cohorts were queried for PCa incidence through 2015. Univariable and multivariable logistic regression analyses were used for determining independent predictors of PCa diagnosis.

RESULTS

A total of 51,353 patients with DD and 111,541 controls were identified. In all, 6.26% of DD developed PCa, and 3.71% of controls developed PCa (p < 0.01). DD was a significant risk factor for PCa (OR: 1.27 CI: 1.19-1.34, p < 0.01). On subgroup analysis, the patients diagnosed with DD <50 years old had an OR of 3.39 for PCa (CI: 2.52-4.56, p < 0.01), age 50-59 had an OR of 2.12 (CI: 1.86-2.15, p < 0.01), and age 60-69 had an OR of 1.20 (CI: 1.10-1.31, p < 0.01). Finally, age and race stratification showed that white patients <50 had an OR of 2.56 (CI: 1.75-3.76, p < 0.01), while black patients <50 had an OR of 3.98 (CI: 2.61-6.07, p < 0.01). The trend in differing odds between these populations was the same for age groups 50-59 and 60-69.

CONCLUSION

Our analysis shows that DD is associated with diagnosis of PCa in hypertensive men. Importantly, the earlier the diagnosis of DD, the higher the odds for development of PCa, particularly in black men.

Use of RNA-Seq and a Transgenic Mouse Model to Identify Genes Which May Contribute to Mutant p53-Driven Prostate Cancer Initiation

Simple Summary

We use RNA-seq analysis to identify genes that may contribute to mutant p53-mediated prostate cancer initiation in a genetically engineered mouse model (B6.129S4-Trp53tm3.1Tyj/J). A total of 1378 differentially expressed genes, including wildtype p53 target genes (e.g. Cdkn1a, Bax, Bcl2, Kras, Mdm2), p53 gain-of-function-related genes (Mgmt, Id4), and prostate cancer-related genes (Cav-1, Raf1, Kras), were identified. Mice that were homozygous or heterozygous for the Trp53 R270H mutation developed grade one PIN lesions at 3 months and 5 months, respectively, whereas wildtype mice did not develop PIN. Immunohistochemical analysis revealed decreased levels of irradiation-mediated apoptosis in homozygous and heterozygous mice when compared to wildtype counterparts, and this aligned with observed differences in apoptosis-related gene expression.

Abstract

We previously demonstrated that the Trp53-R270H mutation can drive prostate cancer (CaP) initiation using the FVB.129S4 (Trp53^tm3Tyj/wt); FVB.129S (Nkx3-1^{tm3(cre)Mmswt}) genetically engineered mouse model (GEM). We now validate this finding in a different model (B6.129S4-Trp53^tm3.1Tyj/J mice) and use RNA-sequencing (RNA-Seq) to identify genes which may contribute to Trp53 R270H-mediated prostate carcinogenesis. Wildtype (Trp53^WT/WT), heterozygous (Trp53^R270H/WT), and homozygous mice (Trp53^R270H/R270H) were exposed to 5 Gy irradiation to activate and stabilize p53, and thereby enhance our ability to identify differences in transcriptional activity between the three groups of mice. Mouse prostates were harvested 6 h post-irradiation and processed for histological/immunohistochemistry (IHC) analysis or were snap-frozen for RNA extraction and transcriptome profiling. IHC analyses determined that presence of the Trp53-R270H mutation impacts apoptosis (lower caspase 3 activity) but not cell proliferation (Ki67). RNA-Seq analysis identified 1378 differentially expressed genes, including wildtype p53 target genes (E.g., Cdkn1a, Bax, Bcl2, Kras, Mdm2), p53 gain-of-function (GOF)-related genes (Mgmt, Id4), and CaP-related genes (Cav-1, Raf1, Kras). Further understanding the mechanisms which contribute to prostate carcinogenesis could allow for the development of improved preventive methods, diagnostics, and treatments for CaP.

Beyond Prostate Specific Antigen: New Prostate Cancer Screening Options

Prostate specific antigen (PSA) is one of the best-known biomarkers for screening, diagnosis and follow-up of patients for prostate cancer. Owing to several inherent limitations with PSA, various newer blood and urinary based biomarkers have been evaluated in pursuit of better detection and risk stratification of prostate cancer cases. A combination of these different markers, in adjunct with clinical risk factors, and recent advances in imaging promises to offer better diagnostic performance with clearer risk stratification guiding therapeutics. We carried out an extensive literature search for the different biomarkers available for screening and diagnosis of prostate cancer, compared their performance with serum PSA to allow clinicians to draw meaningful conclusions to offer their patients a more personalized medical care.

Epidemiology and genomics of prostate cancer in Asian men

Prostate cancer is a global health problem, but incidence varies considerably across different continents. Asia is traditionally considered a low-incidence area, but the incidence and mortality of prostate cancer have rapidly increased across the continent. Substantial differences in epidemiological features have been observed among different Asian regions, and incidence, as well as mortality-to-incidence ratio, is associated with the human development index. Prostate cancer mortality decreased in Japan and Israel from 2007 to 2016, but mortality has increased in Thailand, Kyrgyzstan and Uzbekistan over the same period. Genomic analyses have shown a low prevalence of ERG oncoprotein in the East Asian population, alongside a low rate of PTEN loss, high CHD1 enrichments and high FOXA1 alterations. Contributions from single-nucleotide polymorphisms to prostate cancer risk vary with ethnicity, but germline mutation rates of DNA damage repair genes in metastatic prostate cancer are comparable in Chinese and white patients from the USA and UK. Pharmacogenomic features of testosterone metabolism might contribute to disparities seen in the response to androgen deprivation between East Asian men and white American and European men. Overall, considerable diversity in epidemiology and genomics of prostate cancer across Asia defines disease characteristics in these populations, but studies in this area are under-represented in the literature. Taking into account this intracontinental and intercontinental heterogeneity, translational studies are required in order to develop ethnicity-specific treatment strategies.

Roles of circRNAs in prostate cancer: Expression, mechanism, application and potential

Circular RNA (circRNA) is a member of the non-coding RNA family that is formed by trans-splicing. Because of its unique structure and characteristics, it has extraordinary value for the diagnosis, treatment, and prognosis of diseases, particularly for tumors. Study of the role of circRNAs in the occurrence and development of prostate cancer has made considerable progress, but many areas remain that require further exploration and improvement. This article describes research into sequencing expression profiles, expression regulation, potential value as biomarkers, mechanism in the occurrence and development, therapy resistance, relationship with clinicopathological features, and prognostic value of circRNAs in prostate cancer from the past few years.

Prostate Carcinogenesis: Insights in Relation to Epigenetics and Inflammation

Prostate cancer is a multifactorial disease that mainly occurs due to the accumulation of somatic, genetic, and epigenetic changes, resulting in the inactivation of tumor-suppressor genes and activation of oncogenes. Mutations in genes, specifically those that control cell growth and division or the repair of damaged DNA, make the cells grow and divide uncontrollably to form a tumor. The risk of developing prostate cancer depends upon the gene that has undergone the mutation. Identifying such genetic risk factors for prostate cancer poses a challenge for the researchers. Besides genetic mutations, many epigenetic alterations, including DNA methylation, histone modifications (methylation, acetylation, ubiquitylation, sumoylation, and phosphorylation) nucleosomal remodeling, and chromosomal looping, have significantly contributed to the onset of prostate cancer as well as the prognosis, diagnosis, and treatment of prostate cancer. Chronic inflammation also plays a major role in the onset and progression of human cancer, via modifications in the tumor microenvironment by initiating epithelialmesenchymal transition and remodeling the extracellular matrix. In this article, the authors present a brief history of the mechanisms and potential links between the genetic aberrations, epigenetic changes, inflammation, and inflammasomes that are known to contribute to the prognosis of prostate cancer. Furthermore, the authors examine and discuss the clinical potential of prostate carcinogenesis in relation to epigenetics and inflammation for its diagnosis and treatment..

Immunotherapy as a Precision Medicine Tool for the Treatment of Prostate Cancer

Prostate cancer (PCa) is the most frequently diagnosed type of cancer among Caucasian males over the age of 60 and is characterized by remarkable heterogeneity and clinical behavior, ranging from decades of indolence to highly lethal disease. Despite the significant progress in PCa systemic therapy, therapeutic response is usually transient, and invasive disease is associated with high mortality rates. Immunotherapy has emerged as an efficacious and non-toxic treatment alternative that perfectly fits the rationale of precision medicine, as it aims to treat patients on the basis of patient-specific, immune-targeted molecular traits, so as to achieve the maximum clinical benefit. Antibodies acting as immune checkpoint inhibitors and vaccines entailing tumor-specific antigens seem to be the most promising immunotherapeutic strategies in offering a significant survival advantage. Even though patients with localized disease and favorable prognostic characteristics seem to be the ones that markedly benefit from such interventions, there is substantial evidence to suggest that the survival benefit may also be extended to patients with more advanced disease. The identification of biomarkers that can be immunologically targeted in patients with disease progression is potentially amenable in this process and in achieving significant advances in the decision for precision treatment of PCa.

Fundamentals of liquid biopsies in metastatic prostate cancer: from characterization to stratification

PURPOSE OF REVIEW

In this review, we provide an overview of the recent developments and prospects on the applications of blood-based liquid biopsies, including circulating tumor DNA and circulating tumor cells, in metastatic prostate cancer.

RECENT FINDINGS

Guidelines and consensus statements have been formulated to standardize preanalytical conditions that affect liquid biopsy analysis. Currently, there are four FDA approved assays for the analysis of liquid biopsies and many quantitative and qualitative assays are being developed. Comprehensive analyses of cell-free tumor DNA (ctDNA) and circulating tumor cells (CTCs) demonstrate that they adequately reflect the genomic makeup of the tumor and may thus complement or even replace tumor biopsies. The assessment of genomic aberrations in ctDNA can potentially predict therapy response and detect mechanisms of resistance. CTC count is not only a strong prognosticator in metastatic prostate cancer but can also measure therapy response.

SUMMARY

Liquid biopsies may provide a temporal snapshot of the biologic variables that affect tumor growth and progression in metastatic prostate cancer. Liquid biopsies could inform on prognostic, predictive, and response measures. However, prospective clinical trials need to be performed to provide definitive validation of the clinical value of the most advanced assays.

Identification of novel biomarkers correlated with prostate cancer progression by an integrated bioinformatic analysis

Prostate cancer (PCa) is a highly aggressive malignant tumor and the biological mechanisms underlying its progression remain unclear.We performed weighted gene co-expression network analysis in PCa dataset from the Cancer Genome Atlas database to identify the key module and key genes related to the progression of PCa. Furthermore, another independent datasets were used to validate our findings.A total of 744 differentially expressed genes were screened out and 5 modules were identified for PCa samples from the Cancer Genome Atlas database. We found the brown module was the key module and related to tumor grade (R2 = 0.52) and tumor invasion depth (R2 = 0.39). Besides, 24 candidate hub genes were screened out and 2 genes (BIRC5 and DEPDC1B) were identified and validated as real hub genes that associated with the progression and prognosis of PCa. Moreover, the biological roles of BIRC5 were related to G-protein coupled receptor signal pathway, and the functions of DEPDC1B were related to the G-protein coupled receptor signal pathway and retinol metabolism in PCa.Taken together, we identified 1 module, 24 candidate hub genes and 2 real hub genes, which were prominently associated with PCa progression. With more experiments and clinical trials, these genes may provide a promising future for PCa treatment.

BRCA2 gene mutation and prostate cancer risk. Comprehensive review and update

The second most common type of tumor worldwide is prostate cancer (PCa). Certain genetic factors contribute to a risk of developing PCa of as much as 40%. BRCA1 and BRCA2 mutations have linked with an increased risk for breast, ovarian, and PCa. However, BRCA2 is the most common gene found altered in early-onset of PCa in males younger than 65. BRCA2 mutation has a higher chance of developing an advanced stage of the disease, resulting in short survival time. This review aimed to describe the genetic changes in BRCA2 that contribute to the risk of PCa, to define its role in the early diagnosis in a man with a strong family history, and to outline the purpose of genetic testing and counseling. Also, the review summarizes the impact of BRCA2 gene mutation in localized PCa, and the treatment strategies have used for PCa patients with a BRCA2 modification.

The genomic landscape of metastatic castration-resistant prostate cancers reveals multiple distinct genotypes with potential clinical impact

Metastatic castration-resistant prostate cancer (mCRPC) has a highly complex genomic landscape. With the recent development of novel treatments, accurate stratification strategies are needed. Here we present the whole-genome sequencing (WGS) analysis of fresh-frozen metastatic biopsies from 197 mCRPC patients. Using unsupervised clustering based on genomic features, we define eight distinct genomic clusters. We observe potentially clinically relevant genotypes, including microsatellite instability (MSI), homologous recombination deficiency (HRD) enriched with genomic deletions and BRCA2 aberrations, a tandem duplication genotype associated with CDK12-/- and a chromothripsis-enriched subgroup. Our data suggests that stratification on WGS characteristics may improve identification of MSI, CDK12-/- and HRD patients. From WGS and ChIP-seq data, we show the potential relevance of recurrent alterations in non-coding regions identified with WGS and highlight the central role of AR signaling in tumor progression. These data underline the potential value of using WGS to accurately stratify mCRPC patients into clinically actionable subgroups.

ANKRD22 is involved in the progression of prostate cancer

Prostate cancer is a common malignant tumor in elderly men. As a novel metabolic-reprogramming molecule, the role of ankyrin repeat domain 22 (ANKRD22) in the tumorigenesis and progression of prostate cancer remains unknown. In the present study, mouse monoclonal antibodies against human ANKRD22 were prepared using recombinant ANKRD22 from prokaryotic expression and validated. Subsequently, these antibodies were used to evaluate ANKRD22 levels via immunohistochemical staining in prostate cancer tissues. Finally, the association between ANKRD22 levels and prostate cancer progression was analyzed in 636 samples of prostate cancer using The Cancer Genome Atlas (TCGA) database. A total of four anti-ANKRD22 monoclonal antibodies were generated and validated, which could be effectively blocked by recombinant ANKRD22 protein. Using these antibodies for immunohistochemical staining, ANKRD22 was detected in prostate cancer cells in both the cytoplasm and nucleus. Bioinformatics analysis demonstrated that the mRNA level of ANKRD22 was inversely associated with prostate cancer stage (P<0.05) and Gleason score (P<0.01) in TCGA database. Patients with higher ANKRD22 mRNA levels exhibited longer disease-free survival following radical prostatectomy. These findings suggest that ANKRD22 may negatively regulate the progression of prostate cancer. The prepared ANKRD22 antibodies with high specificity provide a powerful tool in ANKRD22 research.

Advancing Risk Assessment of Intermediate Risk Prostate Cancer Patients

The individual risk to progression is unclear for intermediate risk prostate cancer patients. To assess their risk to progression, we examined the level of genomic instability in circulating tumor cells (CTCs) using quantitative three-dimensional (3D) telomere analysis. Data of CTCs from 65 treatment-naïve patients with biopsy-confirmed D’Amico-defined intermediate risk prostate cancer were compared to radical prostatectomy pathology results, which provided a clinical endpoint to the study and confirmed pre-operative pathology or demonstrated upgrading. Hierarchical centroid cluster analysis of 3D pre-operative CTC telomere profiling placed the patients into three subgroups with different potential risk of aggressive disease. Logistic regression modeling of the risk of progression estimated odds ratios with 95% confidence interval (CI) and separated patients into “stable” vs. “risk of aggressive” disease. The receiver operating characteristic (ROC) curve showed an area under the curve (AUC) of 0.77, while prostate specific antigen (PSA) (AUC of 0.59) and Gleason 3 + 4 = 7 vs. 4 + 3 = 7 (p > 0.6) were unable to predict progressive or stable disease. The data suggest that quantitative 3D telomere profiling of CTCs may be a potential tool for assessing a patient’s prostate cancer pre-treatment risk.

A TMEFF2-regulated cell cycle derived gene signature is prognostic of recurrence risk in prostate cancer

Background

The clinical behavior of prostate cancer (PCa) is variable, and while the majority of cases remain indolent, 10% of patients progress to deadly forms of the disease. Current clinical predictors used at the time of diagnosis have limitations to accurately establish progression risk. Here we describe the development of a tumor suppressor regulated, cell-cycle gene expression based prognostic signature for PCa, and validate its independent contribution to risk stratification in several radical prostatectomy (RP) patient cohorts.

Methods

We used RNA interference experiments in PCa cell lines to identify a gene expression based gene signature associated with Tmeff2, an androgen regulated, tumor suppressor gene whose expression shows remarkable heterogeneity in PCa. Gene expression was confirmed by qRT-PCR. Correlation of the signature with disease outcome (time to recurrence) was retrospectively evaluated in four geographically different cohorts of patients that underwent RP (834 samples), using multivariate logistical regression analysis. Multivariate analyses were adjusted for standard clinicopathological variables. Performance of the signature was compared to previously described gene expression based signatures using the SigCheck software.

Results

Low levels of TMEFF2 mRNA significantly (p < 0.0001) correlated with reduced disease-free survival (DFS) in patients from the Memorial Sloan Kettering Cancer Center (MSKCC) dataset. We identified a panel of 11 TMEFF2 regulated cell cycle related genes (TMCC11), with strong prognostic value. TMCC11 expression was significantly associated with time to recurrence after prostatectomy in four geographically different patient cohorts (2.9 ≤ HR ≥ 4.1; p ≤ 0.002), served as an independent indicator of poor prognosis in the four RP cohorts (1.96 ≤ HR ≥ 4.28; p ≤ 0.032) and improved the prognostic value of standard clinicopathological markers. The prognostic ability of TMCC11 panel exceeded previously published oncogenic gene signatures (p = 0.00017).

Conclusions

This study provides evidence that the TMCC11 gene signature is a robust independent prognostic marker for PCa, reveals the value of using highly heterogeneously expressed genes, like Tmeff2, as guides to discover prognostic indicators, and suggests the possibility that low Tmeff2 expression marks a distinct subclass of PCa.

Electronic supplementary material

The online version of this article (10.1186/s12885-019-5592-6) contains supplementary material, which is available to authorized users.

Comprehensive Genomic Profiling of Androgen-Receptor-Negative Canine Prostate Cancer

Canine carcinomas have been considered natural models for human diseases; however, the genomic profile of canine prostate cancers (PCs) has not been explored. In this study, 14 PC androgen-receptor-negative cases, 4 proliferative inflammatory atrophies (PIA), and 5 normal prostate tissues were investigated by array-based comparative genomic hybridization (aCGH). Copy number alterations (CNAs) were assessed using the Canine Genome CGH Microarray 4 × 44K (Agilent Technologies). Genes covered by recurrent CNAs were submitted to enrichment and cross-validation analysis. In addition, the expression levels of TP53, MDM2 and ZBTB4 were evaluated in an independent set of cases by qPCR. PC cases presented genomic complexity, while PIA samples had a small number of CNAs. Recurrent losses covering well-known tumor suppressor genes, such as ATM, BRCA1, CDH1, MEN1 and TP53, were found in PC. The in silico functional analysis showed several cancer-related genes associated with canonical pathways and interaction networks previously described in human PC. The MDM2, TP53, and ZBTB4 copy number alterations were translated into altered expression levels. A cross-validation analysis using The Cancer Genome Atlas (TCGA) database for human PC uncovered similarities between canine and human PCs. Androgen-receptor-negative canine PC is a complex disease characterized by high genomic instability, showing a set of genes with similar alterations to human cancer.

Increased HSF1 expression predicts shorter disease-specific survival of prostate cancer patients following radical prostatectomy

Prostate cancer is a highly heterogeneous disease and the clinical outcome is varying. While current prognostic tools are regarded insufficient, there is a critical need for markers that would aid prognostication and patient risk-stratification. Heat shock transcription factor 1 (HSF1) is crucial for cellular homeostasis, but also a driver of oncogenesis. The clinical relevance of HSF1 in prostate cancer is, however, unknown. Here, we identified HSF1 as a potential biomarker in mRNA expression datasets on prostate cancer. Clinical validation was performed on tissue microarrays from independent cohorts: one constructed from radical prostatectomies from 478 patients with long term follow-up, and another comprising of regionally advanced to distant metastatic samples. Associations with clinical variables and disease outcomes were investigated. Increased nuclear HSF1 expression correlated with disease advancement and aggressiveness and was, independently from established clinicopathological variables, predictive of both early initiation of secondary therapy and poor disease-specific survival. In a joint model with the clinical Cancer of the Prostate Risk Assessment post-Surgical (CAPRA-S) score, nuclear HSF1 remained a predictive factor of shortened disease-specific survival. The results suggest that nuclear HSF1 expression could serve as a novel prognostic marker for patient risk-stratification on disease progression and survival after radical prostatectomy.

Micrornas in prostate cancer: an overview

Prostate cancer is the second highest cause of cancer mortality after lung tumours. In USA it affects about 2.8 million men and the incidence increases with age in many countries. Therefore, early diagnosis is a very important step for patient clinical evaluation and for a selective and efficient therapy. The study of miRNAs' functions and molecular mechanisms has brought new knowledge in biological processes of cancer. In prostate cancer there is a deregulation of several miRNAs that may function as tumour suppressors or oncogenes. The aim of this review is to analyze the progress made to our understanding of the role of miRNA dysregulation in prostate cancer tumourigenesis.

PBOV1 as a potential biomarker for more advanced prostate cancer based on protein and digital histomorphometric analysis

BACKGROUND

There are few tissue-based biomarkers that can accurately predict prostate cancer (PCa) progression and aggressiveness. We sought to evaluate the clinical utility of prostate and breast overexpressed 1 (PBOV1) as a potential PCa biomarker.

METHODS

Patient tumor samples were designated by Grade Groups using the 2014 Gleason grading system. Primary radical prostatectomy tumors were obtained from 48 patients and evaluated for PBOV1 levels using Western blot analysis in matched cancer and benign cancer-adjacent regions. Immunohistochemical evaluation of PBOV1 was subsequently performed in 80 cancer and 80 benign cancer-adjacent patient samples across two tissue microarrays (TMAs) to verify protein levels in epithelial tissue and to assess correlation between PBOV1 proteins and nuclear architectural changes in PCa cells. Digital histomorphometric analysis was used to track 22 parameters that characterized nuclear changes in PBOV1-stained cells. Using a training and test set for validation, multivariate logistic regression (MLR) models were used to identify significant nuclear parameters that distinguish Grade Group 3 and above PCa from Grade Group 1 and 2 PCa regions.

RESULTS

PBOV1 protein levels were increased in tumors from Grade Group 3 and above (GS 4 + 3 and ≥ 8) regions versus Grade Groups 1 and 2 (GS 3 + 3 and 3 + 4) regions (P = 0.005) as assessed by densitometry of immunoblots. Additionally, by immunoblotting, PBOV1 protein levels differed significantly between Grade Group 2 (GS 3 + 4) and Grade Group 3 (GS 4 + 3) PCa samples (P = 0.028). In the immunohistochemical analysis, measures of PBOV1 staining intensity strongly correlated with nuclear alterations in cancer cells. An MLR model retaining eight parameters describing PBOV1 staining intensity and nuclear architecture discriminated Grade Group 3 and above PCa from Grade Group 1 and 2 PCa and benign cancer-adjacent regions with a ROC-AUC of 0.90 and 0.80, respectively, in training and test sets.

CONCLUSIONS

Our study demonstrates that the PBOV1 protein could be used to discriminate Grade Group 3 and above PCa. Additionally, the PBOV1 protein could be involved in modulating changes to the nuclear architecture of PCa cells. Confirmatory studies are warranted in an independent population for further validation.

Integrative (epi) Genomic Analysis to Predict Response to Androgen-Deprivation Therapy in Prostate Cancer

Therapeutic resistance is a central problem in clinical oncology. We have developed a systematic genome-wide computational methodology to allow prioritization of patients with favorable and poor therapeutic response. Our method, which integrates DNA methylation and mRNA expression data, uncovered a panel of 5 differentially methylated sites, which explain expression changes in their site-harboring genes, and demonstrated their ability to predict primary resistance to androgen-deprivation therapy (ADT) in the TCGA prostate cancer patient cohort (hazard ratio = 4.37). Furthermore, this panel was able to accurately predict response to ADT across independent prostate cancer cohorts and demonstrated that it was not affected by Gleason, age, or therapy subtypes. We propose that this panel could be utilized to prioritize patients who would benefit from ADT and patients at risk of resistance that should be offered an alternative regimen. Such approach holds a long-term objective to build an adaptable accurate platform for precision therapeutics.

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Integrative DNA methylation and mRNA expression analysis discovers a panel of markers of treatment resistance.

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This panel can predict patients with predisposition to resistance and those who would benefit from the therapy.

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Our approach is applicable to a wide range of therapeutic regimens.

Therapeutic resistance is an emerging clinical problem, with detrimental implications in oncology. Here, we propose a computational approach that integrates genomic and epigenomic data to prioritize patients at risk of treatment resistance. We have integrated DNA methylation and mRNA expression patient profiles, which defined a comprehensive panel of markers of therapeutic response. We have demonstrated that this panel predicts patients with predisposition to resistance and those who would benefit from the therapy. Even though driven by a critical need to investigate resistance to androgen-deprivation therapy in prostate cancer, our approch is applicable to a wide range of therapeutic regimens.

In-Silico Integration Approach to Identify a Key miRNA Regulating a Gene Network in Aggressive Prostate Cancer

Like other cancer diseases, prostate cancer (PC) is caused by the accumulation of genetic alterations in the cells that drives malignant growth. These alterations are revealed by gene profiling and copy number alteration (CNA) analysis. Moreover, recent evidence suggests that also microRNAs have an important role in PC development. Despite efforts to profile PC, the alterations (gene, CNA, and miRNA) and biological processes that correlate with disease development and progression remain partially elusive. Many gene signatures proposed as diagnostic or prognostic tools in cancer poorly overlap. The identification of co-expressed genes, that are functionally related, can identify a core network of genes associated with PC with a better reproducibility. By combining different approaches, including the integration of mRNA expression profiles, CNAs, and miRNA expression levels, we identified a gene signature of four genes overlapping with other published gene signatures and able to distinguish, in silico, high Gleason-scored PC from normal human tissue, which was further enriched to 19 genes by gene co-expression analysis. From the analysis of miRNAs possibly regulating this network, we found that hsa-miR-153 was highly connected to the genes in the network. Our results identify a four-gene signature with diagnostic and prognostic value in PC and suggest an interesting gene network that could play a key regulatory role in PC development and progression. Furthermore, hsa-miR-153, controlling this network, could be a potential biomarker for theranostics in high Gleason-scored PC.

miR‑138 modulates prostate cancer cell invasion and migration via Wnt/β‑catenin pathway

The prognosis for prostate cancer patients with distant metastasis is poor, with an average survival rate of 24‑48 months. The exact mechanisms underlying prostate cancer metastasis remain to be elucidated, despite previous research efforts. The present study aimed to reveal the regulatory roles of miR‑138 via Wnt/β‑catenin pathway in prostate cancer cell migration and invasion. Reverse transcription‑quantitative polymerase chain reaction was used to examine the mRNA and protein expression levels and transwell assay was conducted to determine cell invasion and migration. A luciferase reporter assay was used to determine the target association between miR‑138 and β‑catenin. The present study identified microRNA (miR)‑138 as an invasion and migration regulator in prostate cancer. miR‑138 was downregulated in aggressive prostate cancer cell lines. Furthermore, followingmiR‑138 overexpression, prostate cancer cells exhibited impaired invasive and migratory abilities. E‑cadherin was upregulated and vimentin was downregulated. In addition, it was demonstrated that miR‑138 negatively regulated the Wnt/β‑catenin pathway activation in prostate cancer. The pathway was then activated via β‑catenin overexpression and this reversed the effects of miR‑138. The results suggest that miR‑138 downregulation may contribute to prostate cancer progression and metastasis. The findings provide a novel molecular therapeutic target in the treatment of prostate cancer metastasis.

Circulating tumor cells in prostate cancer: Precision diagnosis and therapy

The primary cause of tumor-associated mortality in prostate cancer (PCa) remains distant metastasis. The dissemination of tumor cells from the primary tumor to distant sites through the bloodstream cannot be detected early by standard imaging methods. Circulating tumor cells (CTCs) represent an effective prognostic and predictive biomarker, which are able to monitor efficacy of adjuvant therapies, detect early development of metastases, and finally, assess therapeutic responses of advanced disease earlier than traditional diagnostic methods. In addition, since repeated tissue biopsies are invasive, costly and not always feasible, the assessment of tumor characteristics on CTCs, by a peripheral blood sample as a liquid biopsy, represents an attractive opportunity. The implementation of molecular and genomic characterization of CTCs may contribute to improve the treatment selection and thus, to move toward more precise diagnosis and therapy in PCa. The present study summarizes the current advances in CTC enrichment and detection strategies and reviews how CTCs may contribute to significant insights in the metastatic process, as well as how they may be utilized in clinical application in PCa. Although it is proposed that CTCs may offer insights into the prognosis and management of PCa, there are a number of challenges in the study of circulating tumor cells, and their clinical utility remains under investigation.

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.

Tumour Heterogeneity: The Key Advantages of Single-Cell Analysis

Tumour heterogeneity refers to the fact that different tumour cells can show distinct morphological and phenotypic profiles, including cellular morphology, gene expression, metabolism, motility, proliferation and metastatic potential. This phenomenon occurs both between tumours (inter-tumour heterogeneity) and within tumours (intra-tumour heterogeneity), and it is caused by genetic and non-genetic factors. The heterogeneity of cancer cells introduces significant challenges in using molecular prognostic markers as well as for classifying patients that might benefit from specific therapies. Thus, research efforts for characterizing heterogeneity would be useful for a better understanding of the causes and progression of disease. It has been suggested that the study of heterogeneity within Circulating Tumour Cells (CTCs) could also reflect the full spectrum of mutations of the disease more accurately than a single biopsy of a primary or metastatic tumour. In previous years, many high throughput methodologies have raised for the study of heterogeneity at different levels (i.e., RNA, DNA, protein and epigenetic events). The aim of the current review is to stress clinical implications of tumour heterogeneity, as well as current available methodologies for their study, paying specific attention to those able to assess heterogeneity at the single cell level.

Kinesin Family Member 11 mRNA Expression Predicts Prostate Cancer Aggressiveness

BACKGROUND

KIF11 (kinesin family member 11), a molecular motor protein, is essential to mitosis and cell cycle progression. Inhibitors of KIF11 have been developed as chemotherapeutic agents for the treatment of various cancers. Regarding prostate cancer (PCa), clinical trials using KIF11 inhibitors for the treatment of castration-resistant PCa have been initiated. We hypothesized that a relationship might exist between KIF11 expression and PCa. To investigate the functional activities and clinical usefulness of KIF11 in PCa, we used quantitative real-time reverse transcriptase polymerase chain reaction to monitor the KIF11 expression patterns.

MATERIALS AND METHODS

Tissue samples from 134 patients with PCa were analyzed using gene expression profiling and compared with tissues from 61 patients with benign prostatic hyperplasia. KIF11 expression was evaluated by real-time reverse transcriptase polymerase chain reaction and compared with indicators of tumor aggressiveness, such as prostate-specific antigen (PSA) levels, Gleason score (GS), and tumor stage (TNM stage).

RESULTS

KIF11 mRNA expression in tissue was significantly greater in PCa patients with elevated serum PSA levels (≥ 10 ng/mL), GS ≥ 8 [58(43.3%)], T stage ≥ T3, or metastatic disease than in those with PSA levels < 10 ng/mL, GS of 7, or T2 stage. Additionally, the expression was remarkably greater in patients with a GS of ≥ 9 than in patients with a GS of 3+4.

CONCLUSION

KIF11 expression might be indicative of PCa aggressiveness and could be useful as a prognostic marker for patients with PCa.

Gene expression panel predicts metastatic-lethal prostate cancer outcomes in men diagnosed with clinically localized prostate cancer

Prognostic biomarkers are needed to distinguish patients with clinically localized prostate cancer (PCa) who are at high risk of metastatic progression. The tumor transcriptome may reveal its aggressiveness potential and have utility for predicting adverse patient outcomes. Genomewide gene expression levels were measured in primary tumor samples of 383 patients in a population‐based discovery cohort, and from an independent clinical validation dataset of 78 patients. Patients were followed for ≥ 5 years after radical prostatectomy to ascertain outcomes. Area under the receiver‐operating characteristic curve (AUC), partial AUC (pAUC, 95% specificity), and P‐value criteria were used to detect and validate the differentially expressed transcripts. Twenty‐three differentially expressed transcripts in patients with metastatic‐lethal compared with nonrecurrent PCa were validated (P < 0.05; false discovery rate < 0.20) in the independent dataset. The addition of each validated transcript to a model with Gleason score showed that 17 transcripts significantly improved the AUC (range: 0.83–0.88; all P‐values < 0.05). These differentially expressed mRNAs represent genes with diverse cellular functions related to tumor aggressiveness. This study validated 23 gene transcripts for predicting metastatic‐lethal PCa in patients surgically treated for clinically localized disease. Several of these mRNA biomarkers have clinical potential for identifying the subset of PCa patients with more aggressive tumors who would benefit from closer monitoring and adjuvant therapy.

DNA alterations in the tumor genome and their associations with clinical outcome in prostate cancer

Although most prostate cancer (PCa) cases are not life-threatening, approximately 293 000 men worldwide die annually due to PCa. These lethal cases are thought to be caused by coordinated genomic alterations that accumulate over time. Recent genome-wide analyses of DNA from subjects with PCa have revealed most, if not all, genetic changes in both germline and PCa tumor genomes. In this article, I first review the major, somatically acquired genomic characteristics of various subtypes of PCa. I then recap key findings on the relationships between genomic alterations and clinical parameters, such as biochemical recurrence or clinical relapse, metastasis and cancer-specific mortality. Finally, I outline the need for, and challenges with, validation of recent findings in prospective studies for clinical utility. It is clearer now than ever before that the landscape of somatically acquired aberrations in PCa is highlighted by DNA copy number alterations (CNAs) and TMPRSS2-ERG fusion derived from complex rearrangements, numerous single nucleotide variations or mutations, tremendous heterogeneity, and continuously punctuated evolution. Genome-wide CNAs, PTEN loss, MYC gain in primary tumors, and TP53 loss/mutation and AR amplification/mutation in advanced metastatic PCa have consistently been associated with worse cancer prognosis. With this recently gained knowledge, it is now an opportune time to develop DNA-based tests that provide more accurate patient stratification for prediction of clinical outcome, which will ultimately lead to more personalized cancer care than is possible at present.

Research Needs for Understanding the Biology of Overdiagnosis in Cancer Screening

Many cancers offer an extended window of opportunity for early detection and therapeutic intervention that could lead to a reduction in cause-specific mortality. The pursuit of early detection in screening settings has resulted in decreased incidence and mortality for some cancers (e.g., colon and cervical cancers), and increased incidence with only modest or no effect on cause-specific mortality in others (e.g., breast and prostate). Whereas highly sensitive screening technologies are better at detecting a number of suspected "cancers" that are indolent and likely to remain clinically unimportant in the lifetime of a patient, defined as overdiagnosis, they often miss cancers that are aggressive and tend to present clinically between screenings, known as interval cancers. Unrecognized overdiagnosis leads to overtreatment with its attendant (often long-lasting) side effects, anxiety, and substantial financial harm. Existing methods often cannot differentiate indolent lesions from aggressive ones or understand the dynamics of neoplastic progression. To correctly identify the population that would benefit the most from screening and identify the lesions that would benefit most from treatment, the evolving genomic and molecular profiles of individual cancers during the clinical course of progression or indolence must be investigated, while taking into account an individual's genetic susceptibility, clinical and environmental risk factors, and the tumor microenvironment. Practical challenges lie not only in the lack of access to tissue specimens that are appropriate for the study of natural history, but also in the absence of targeted research strategies. This commentary summarizes the recommendations from a diverse group of scientists with expertise in basic biology, translational research, clinical research, statistics, and epidemiology and public health professionals convened to discuss research directions. J. Cell. Physiol. 231: 1870-1875, 2016. © 2015 Wiley Periodicals, Inc.

A Balanced Tissue Composition Reveals New Metabolic and Gene Expression Markers in Prostate Cancer

Molecular analysis of patient tissue samples is essential to characterize the in vivo variability in human cancers which are not accessible in cell-lines or animal models. This applies particularly to studies of tumor metabolism. The challenge is, however, the complex mixture of various tissue types within each sample, such as benign epithelium, stroma and cancer tissue, which can introduce systematic biases when cancers are compared to normal samples. In this study we apply a simple strategy to remove such biases using sample selections where the average content of stroma tissue is balanced between the sample groups. The strategy is applied to a prostate cancer patient cohort where data from MR spectroscopy and gene expression have been collected from and integrated on the exact same tissue samples. We reveal in vivo changes in cancer-relevant metabolic pathways which are otherwise hidden in the data due to tissue confounding. In particular, lowered levels of putrescine are connected to increased expression of SRM, reduced levels of citrate are attributed to upregulation of genes promoting fatty acid synthesis, and increased succinate levels coincide with reduced expression of SUCLA2 and SDHD. In addition, the strategy also highlights important metabolic differences between the stroma, epithelium and prostate cancer. These results show that important in vivo metabolic features of cancer can be revealed from patient data only if the heterogeneous tissue composition is properly accounted for in the analysis.

Methylation profiling identified novel differentially methylated markers including OPCML and FLRT2 in prostate cancer

To develop new methods to distinguish indolent from aggressive prostate cancers (PCa), we utilized comprehensive high-throughput array-based relative methylation (CHARM) assay to identify differentially methylated regions (DMRs) throughout the genome, including both CpG island (CGI) and non-CGI regions in PCa patients based on Gleason grade. Initially, 26 samples, including 8 each of low [Gleason score (GS) 6] and high (GS ≥7) grade PCa samples and 10 matched normal prostate tissues, were analyzed as a discovery cohort. We identified 3,567 DMRs between normal and cancer tissues, and 913 DMRs distinguishing low from high-grade cancers. Most of these DMRs were located at CGI shores. The top 5 candidate DMRs from the low vs. high Gleason comparison, including OPCML, ELAVL2, EXT1, IRX5, and FLRT2, were validated by pyrosequencing using the discovery cohort. OPCML and FLRT2 were further validated in an independent cohort consisting of 20 low-Gleason and 33 high-Gleason tissues. We then compared patients with biochemical recurrence (n=70) vs. those without (n=86) in a third cohort, and they showed no difference in methylation at these DMR loci. When GS 3+4 cases and GS 4+3 cases were compared, OPCML-DMR methylation showed a trend of lower methylation in the recurrence group (n=30) than in the no-recurrence (n=52) group. We conclude that whole-genome methylation profiling with CHARM revealed distinct patterns of differential DNA methylation between normal prostate and PCa tissues, as well as between different risk groups of PCa as defined by Gleason scores. A panel of selected DMRs may serve as novel surrogate biomarkers for Gleason score in PCa.

Characterization of Heterogeneous Prostate Tumors in Targeted Pten Knockout Mice

Previously, we generated a preclinical mouse prostate tumor model based on PSA-Cre driven inactivation of Pten. In this model homogeneous hyperplastic prostates (4-5m) developed at older age (>10m) into tumors. Here, we describe the molecular and histological characterization of the tumors in order to better understand the processes that are associated with prostate tumorigenesis in this targeted mouse Pten knockout model. The morphologies of the tumors that developed were very heterogeneous. Different histopathological growth patterns could be identified, including intraductal carcinoma (IDC), adenocarcinoma and undifferentiated carcinoma, all strongly positive for the epithelial cell marker Cytokeratin (CK), and carcinosarcomas, which were negative for CK. IDC pattern was already detected in prostates of 7-8 month old mice, indicating that it could be a precursor stage. At more than 10 months IDC and carcinosarcoma were most frequently observed. Gene expression profiling discriminated essentially two molecular subtypes, denoted tumor class 1 (TC1) and tumor class 2 (TC2). TC1 tumors were characterized by high expression of epithelial markers like Cytokeratin 8 and E-Cadherin whereas TC2 tumors showed high expression of mesenchyme/stroma markers such as Snail and Fibronectin. These molecular subtypes corresponded with histological growth patterns: where TC1 tumors mainly represented adenocarcinoma/intraductal carcinoma, in TC2 tumors carcinosarcoma was the dominant growth pattern. Further molecular characterization of the prostate tumors revealed an increased expression of genes associated with the inflammatory response. Moreover, functional markers for senescence, proliferation, angiogenesis and apoptosis were higher expressed in tumors compared to hyperplasia. The highest expression of proliferation and angiogenesis markers was detected in TC2 tumors. Our data clearly showed that in the genetically well-defined PSA-Cre;Pten-loxP/loxP prostate tumor model, histopathological, molecular and biological heterogeneity occurred during later stages of tumor development.

PSA and beyond: alternative prostate cancer biomarkers

BACKGROUND

The use of biomarkers for prostate cancer screening, diagnosis and prognosis has the potential to improve the clinical management of the patients. Owing to inherent limitations of the biomarker prostate-specific antigen (PSA), intensive efforts are currently directed towards a search for alternative prostate cancer biomarkers, particularly those that can predict disease aggressiveness and drive better treatment decisions.

METHODS

A literature search of Medline articles focused on recent and emerging advances in prostate cancer biomarkers was performed. The most promising biomarkers that have the potential to meet the unmet clinical needs in prostate cancer patient management and/or that are clinically implemented were selected.

CONCLUSIONS

With the advent of advanced genomic and proteomic technologies, we have in recent years seen an enormous spurt in prostate cancer biomarker research with several promising alternative biomarkers being discovered that show an improved sensitivity and specificity over PSA. The new generation of biomarkers can be tested via serum, urine, or tissue-based assays that have either received regulatory approval by the US Food and Drug Administration or are available as Clinical Laboratory Improvement Amendments-based laboratory developed tests. Additional emerging novel biomarkers for prostate cancer, including circulating tumor cells, microRNAs and exosomes, are still in their infancy. Together, these biomarkers provide actionable guidance for prostate cancer risk assessment, and are expected to lead to an era of personalized medicine.

The Extraordinary Progress in Very Early Cancer Diagnosis and Personalized Therapy: The Role of Oncomarkers and Nanotechnology

The impact of nanotechnology on oncology is revolutionizing cancer diagnosis and therapy and largely improving prognosis. This is mainly due to clinical translation of the most recent findings in cancer research, that is, the application of bio- and nanotechnologies. Cancer genomics and early diagnostics are increasingly playing a key role in developing more precise targeted therapies for most human tumors. In the last decade, accumulation of basic knowledge has resulted in a tremendous breakthrough in this field. Nanooncology, through the discovery of new genetic and epigenetic biomarkers, has facilitated the development of more sensitive biosensors for early cancer detection and cutting-edge multifunctionalized nanoparticles for tumor imaging and targeting. In the near future, nanooncology is expected to enable a very early tumor diagnosis, combined with personalized therapeutic approaches.

High-Resolution Genomic Profiling of Disseminated Tumor Cells in Prostate Cancer

Circulating tumor cells and disseminated tumor cells (DTCs) are of great interest because they provide a minimally invasive window for assessing aspects of cancer biology, including tumor heterogeneity, a means to discover biomarkers of disease behavior, and a way to identify and prioritize therapeutic targets in the emerging era of precision oncology. However, the rarity of circulating tumor cells and DTCs poses a substantial challenge to the consistent success in analyzing their molecular features, including genomic aberrations. Herein, we describe optimized and robust methods to reproducibly detect genomic copy number alterations in samples of 2 to 40 cells after whole-genome amplification with the use of a high-resolution single-nuclear polymorphism-array platform and refined computational algorithms. We have determined the limit of detection for heterogeneity within a sample as 50% and also demonstrated success in analyzing single cells. We validated the genes in genomic regions that are frequently amplified or deleted by real-time quantitative PCR and nCounter copy number quantification. We further applied these methods to DTCs isolated from individuals with advanced prostate cancer to confirm their highly aberrant nature. We compared copy number alterations of DTCs with matched metastatic tumors isolated from the same individual to gain biological insight. These developments provide high-resolution genomic profiling of single and rare cell populations and should be applicable to a wide-range of sample sources.

Integrative enrichment analysis: a new computational method to detect dysregulated pathways in heterogeneous samples

BACKGROUND

Pathway enrichment analysis is a useful tool to study biology and biomedicine, due to its functional screening on well-defined biological procedures rather than separate molecules. The measurement of malfunctions of pathways with a phenotype change, e.g., from normal to diseased, is the key issue when applying enrichment analysis on a pathway. The differentially expressed genes (DEGs) are widely focused in conventional analysis, which is based on the great purity of samples. However, the disease samples are usually heterogeneous, so that, the genes with great differential expression variance (DEVGs) are becoming attractive and important to indicate the specific state of a biological system. In the context of differential expression variance, it is still a challenge to measure the enrichment or status of a pathway. To address this issue, we proposed Integrative Enrichment Analysis (IEA) based on a novel enrichment measurement.

RESULTS

The main competitive ability of IEA is to identify dysregulated pathways containing DEGs and DEVGs simultaneously, which are usually under-scored by other methods. Next, IEA provides two additional assistant approaches to investigate such dysregulated pathways. One is to infer the association among identified dysregulated pathways and expected target pathways by estimating pathway crosstalks. The other one is to recognize subtype-factors as dysregulated pathways associated to particular clinical indices according to the DEVGs' relative expressions rather than conventional raw expressions. Based on a previously established evaluation scheme, we found that, in particular cohorts (i.e., a group of real gene expression datasets from human patients), a few target disease pathways can be significantly high-ranked by IEA, which is more effective than other state-of-the-art methods. Furthermore, we present a proof-of-concept study on Diabetes to indicate: IEA rather than conventional ORA or GSEA can capture the under-estimated dysregulated pathways full of DEVGs and DEGs; these newly identified pathways could be significantly linked to prior-known disease pathways by estimated crosstalks; and many candidate subtype-factors recognized by IEA also have significant relation with the risk of subtypes of genotype-phenotype associations.

CONCLUSIONS

Totally, IEA supplies a new tool to carry on enrichment analysis in the complicate context of clinical application (i.e., heterogeneity of disease), as a necessary complementary and cooperative approach to conventional ones.

Dysregulation of the vascular endothelial growth factor and semaphorin ligand-receptor families in prostate cancer metastasis

Background

The vascular endothelial growth factor (VEGF) family is central to cancer angiogenesis. However, targeting VEGF as an anti-cancer therapeutic approach has shown success for some tumor types but not others. Here we examine the expression of the expanded VEGF family in prostate cancer, including the Semaphorin (Sema) family members that compete with VEGFs for Neuropilin binding and can themselves have pro- or anti-angiogenic activity.

Results

First, we used multivariate statistical methods, including partial least squares and clustering, to examine VEGF/Sema gene expression variability in previously published prostate cancer microarray datasets. We show that unlike some cancers, such as kidney cancer, primary prostate cancer is characterized by both a down-regulation of the pro-angiogenic members of the VEGF family and a down-regulation of anti-angiogenic members of the Sema family. We found pro-lymphangiogenic signatures, including the genes encoding VEGFC and VEGFD, associated with primary tumors that ultimately became aggressive. In contrast to primary prostate tumors, prostate cancer metastases showed increased expression of key pro-angiogenic VEGF family members and further repression of anti-angiogenic class III Sema family members. Given the lack of success of VEGF-targeting molecules so far in prostate cancer, this suggests that the reduction in anti-angiogenic Sema signaling may potentiate VEGF signaling and even promote resistance to VEGF-targeting therapies. Inhibition of the VEGF ‘accelerator’ may need to be accompanied by promotion of the Sema ‘brake’ to block cancer angiogenesis. To leverage our mechanistic understanding, and to link multigene expression changes to outcomes, we performed individualized computational simulations of competitive VEGF and Sema receptor binding across many tumor samples. The simulations suggest that loss of Sema expression promotes angiogenesis by lowering plexin signaling, not by potentiating VEGF signaling via relaxation of competition.

Conclusions

The combined analysis of bioinformatic data with computational modeling of ligand-receptor interactions demonstrated that enhancement of angiogenesis in prostate cancer metastases may occur through two different routes: elevation of VEGFA and reduction of class 3 Semaphorins. Therapeutic inhibition of angiogenesis in metastatic prostate cancer should account for both of these routes.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-015-0201-z) contains supplementary material, which is available to authorized users.

Enrichment of the Cancer Stem Phenotype in Sphere Cultures of Prostate Cancer Cell Lines Occurs through Activation of Developmental Pathways Mediated by the Transcriptional Regulator ΔNp63α

Background

Cancer stem cells (CSC) drive prostate cancer tumor survival and metastasis. Nevertheless, the development of specific therapies against CSCs is hindered by the scarcity of these cells in prostate tissues. Suspension culture systems have been reported to enrich CSCs in primary cultures and cell lines. However, the molecular mechanisms underlying this phenomenon have not been fully explored.

Methodology/Principal Findings

We describe a prostasphere assay for the enrichment of CD133⁺ CSCs in four commercial PCa cell lines: 22Rv1, DU145, LNCaP, and PC3. Overexpression of CD133, as determined by flow cytometric analysis, correlated with an increased clonogenic, chemoresistant, and invasive potential in vitro. This phenotype is concordant to that of CSCs in vivo. Gene expression profiling was then carried out using the Cancer Reference panel and the nCounter system from NanoString Technologies. This analysis revealed several upregulated transcripts that can be further explored as potential diagnostic markers or therapeutic targets. Furthermore, functional annotation analysis suggests that ΔNp63α modulates the activation of developmental pathways responsible for the increased stem identity of cells growing in suspension cultures.

Conclusions/Significance

We conclude that profiling the genetic mechanisms involved in CSC enrichment will help us to better understand the molecular pathways that underlie CSC pathophysiology. This platform can be readily adapted to enrich and assay actual patient samples, in order to design patient-specific therapies that are aimed particularly against CSCs.

A tumor deconstruction platform identifies definitive end points in the evaluation of drug responses

Tumor heterogeneity and the presence of drug-sensitive and refractory populations within the same tumor are almost never assessed in the drug discovery pipeline. Such incomplete assessment of drugs arising from spatial and temporal tumor cell heterogeneity reflects on their failure in the clinic and considerable wasted costs in the drug discovery pipeline. Here we report the derivation of a flow cytometry-based tumor deconstruction platform for resolution of at least 18 discrete tumor cell fractions. This is achieved through concurrent identification, quantification and analysis of components of cancer stem cell hierarchies, genetically instable clones and differentially cycling populations within a tumor. We also demonstrate such resolution of the tumor cytotype to be a potential value addition in drug screening through definitive cell target identification. Additionally, this real-time definition of intra-tumor heterogeneity provides a convenient, incisive and analytical tool for predicting drug efficacies through profiling perturbations within discrete tumor cell subsets in response to different drugs and candidates. Consequently, possible applications in informed therapeutic monitoring and drug repositioning in personalized cancer therapy would complement rational design of new candidates besides achieving a re-evaluation of existing drugs to derive non-obvious combinations that hold better chances of achieving remission.

Genomic Predictors of Outcome in Prostate Cancer

CONTEXT

Given the highly variable behavior and clinical course of prostate cancer (PCa) and the multiple available treatment options, a personalized approach to oncologic risk stratification is important. Novel genetic approaches offer additional information to improve clinical decision making.

OBJECTIVE

To review the use of genomic biomarkers in the prognostication of PCa outcome and prediction of therapeutic response.

EVIDENCE ACQUISITION

Systematic literature review focused on human clinical studies reporting outcome measures with external validation. The literature search included all Medline, Embase, and Scopus articles from inception through July 2014.

EVIDENCE SYNTHESIS

An improved understanding of the genetic basis of prostate carcinogenesis has produced an increasing number of potential prognostic and predictive tools, such as transmembrane protease, serine2:v-ets avian erythroblastosis virus E26 oncogene homolog (TMPRSS2:ERG) gene fusion status, loss of the phosphatase and tensin homolog (PTEN) gene, and gene expression signatures utilizing messenger RNA from tumor tissue. Several commercially available gene panels with external validation are now available, although most have yet to be widely used. The most studied commercially available gene panels, Prolaris, Oncotype DX Genomic Prostate Score, and Decipher, may be used to estimate disease outcome in addition to clinical parameters or clinical nomograms. ConfirmMDx is an epigenetic test used to predict the results of repeat prostate biopsy after an initial negative biopsy. Additional future strategies include using genetic information from circulating tumor cells in the peripheral blood to guide treatment decisions at the initial diagnosis and at subsequent decision points.

CONCLUSIONS

Major advances have been made in our understanding of PCa biology in recent years. Our field is currently exploring the early stages of a personalized approach to augment traditional clinical decision making using commercially available genomic tools. A more comprehensive appreciation of value, limitations, and cost is important.

PATIENT SUMMARY

We summarized current advances in genomic testing in prostate cancer with a special focus on the estimation of disease outcome. Several commercial tests are currently available, but further understanding is needed to appreciate the potential benefits and limitations of these novel tests.

Tracking the origins and drivers of subclonal metastatic expansion in prostate cancer

Tumour heterogeneity in primary prostate cancer is a well-established phenomenon. However, how the subclonal diversity of tumours changes during metastasis and progression to lethality is poorly understood. Here we reveal the precise direction of metastatic spread across four lethal prostate cancer patients using whole-genome and ultra-deep targeted sequencing of longitudinally collected primary and metastatic tumours. We find one case of metastatic spread to the surgical bed causing local recurrence, and another case of cross-metastatic site seeding combining with dynamic remoulding of subclonal mixtures in response to therapy. By ultra-deep sequencing end-stage blood, we detect both metastatic and primary tumour clones, even years after removal of the prostate. Analysis of mutations associated with metastasis reveals an enrichment of TP53 mutations, and additional sequencing of metastases from 19 patients demonstrates that acquisition of TP53 mutations is linked with the expansion of subclones with metastatic potential which we can detect in the blood.

Aberrant hypomethylation-mediated CD147 overexpression promotes aggressive tumor progression in human prostate cancer

Our previous study revealed the potential role of CD147 in human prostate cancer (PCa). Here, we investigated the CD147 promoter methylation status and the correlation with tumorigenicity in human PCa. CD147 mRNA and protein expression levels were both significantly higher in the 4 PCa cell lines, than in the 2 non-tumorigenic benign human prostatic epithelial cell lines (all P<0.01). We showed hypomethylation of promoter regions of CD147 in PCa cell lines with significant CD147 expression as compared to non-tumorigenic benign human prostatic epithelial cell lines slowly expressing CD147. Additionally, the treatment of methylated cell lines with 5-aza-2'-deoxycytidine increased CD147 expression significantly in low-expressing cell lines and also activated the expression of matrix metalloproteinase (MMP)-2, which may be one of the most important downstream targets of CD147. Furthermore, PCa tissues displayed decreased DNA methylation in the promoter region of CD147 compared to the corresponding non-cancerous prostate tissues, and methylation intensity correlated inversely with the CD147 mRNA levels. There was a significant negative correlation between CD147 mRNA levels and the number of methylated sites in PCa tissues (r=-0.467, P<0.01). In conclusion, our data offer convincing evidence for the first time that the DNA promoter hypomethylation of CD147 may be one of the regulatory mechanisms involved in the cancer-related overexpression of CD147 and may play a crucial role in the tumorigenesis of PCa.

Prostate Cancer Genetics: A Review

Over the past decades, research has focussed on identifying the genetic underpinnings of prostate cancer. It has been recognized that a number of forms of genetic changes coupled with epigenetic and gene expression changes can increase the prediction to develop prostate cancer. This review outlines the role of somatic copy number alterations (SCNAs), structural rearrangements, point mutations, and single nucleotide polymorphisms (SNPs) as well as miRNAs. Identifying relevant genetic changes offers the ability to develop novel biomarkers to allow early and accurate detection of prostate cancer as well as provide risk stratification of patients following their diagnosis. The concept of personalized or individualized medicine has gained significant attention. Therefore, a better understanding of the genetic and metabolic pathways underlying prostate cancer development offers the opportunity to explore new therapeutic interventions with the possibility of offering patient-specific targeted therapy.

Precision medicine for prostate cancer

Metastatic castration-resistant prostate cancer remains a lethal disease despite considerable progress in systemic therapy over the past decade. The recent advances in genomic sequencing have improved the molecular classification of prostate cancer. The translation of genomic data into clinically relevant prognostic and predictive biomarkers to guide therapy is still in its infancy and therapies for castration-resistant prostate cancer are still used empirically. We discuss these genomic aberrations in more detail, focusing on androgen receptor signaling, ETS transcription factor gene rearrangements and PTEN loss. The incorporation of this genomic data within early phase clinical trials is evolving and may prove significant in advancing personalized care in prostate cancer.