Gene expression profiling identifies clinically relevant subtypes of prostate cancer

Identification of distinct molecular subtypes of uterine carcinosarcoma

Uterine carcinosarcoma (UCS) is a rare but lethal neoplasm with high metastasis and recurrence rate, and to date, no molecular classification of UCS has been defined to achieve targeted therapies. In this study, we identified two distinct molecular subtypes of UCS with distinct gene expression patterns and clinicopathologic characteristics. Subtype I UCS recapitulates low-grade UCS, in contrast subtype II UCS represents high-grade UCS with higher tumor invasion rate and tumor weight. Interestingly, subtype I UCS is characterized by cell adhesion and apoptosis pathways, whereas genes over-expressed in subtype II UCS are more involved in myogenesis/muscle development. We also proposed certain potential subtype specific therapeutic targets, such as SYK (spleen tyrosine kinase) for subtype I and cell-cycle proteins for subtype II. Our findings provide a better recognition of UCS molecular subtypes and subtype specific oncogenesis mechanisms, and can help develop more specific targeted treatment options for these tumors.

Gene-Set Reduction for Analysis of Major and Minor Gleason Scores Based on Differential Gene-Set Expressions and Biological Pathways in Prostate Cancer

The Gleason score (GS) plays an important role in prostate cancer detection and treatment. It is calculated based on a sum between its major and minor components, each ranging from 1 to 5, assigned after examination of sample cells taken from each side of the prostate gland during biopsy. A total GS of at least 7 is associated with more aggressive prostate cancer. However, it is still unclear how prostate cancer outcomes differ for various distributions of GS between its major and minor components. This article applies Significance Analysis of Microarray for Gene-Set Reduction to a real microarray study of patients with prostate cancer and identifies 13 core genes differentially expressed between patients with a major GS of 3 and a minor GS of 4, or (3,4), vs patients with a combination of (4,3), starting from a less aggressive GS combination of (3,3), and moving toward a more aggressive one of (4,4) via gray areas of (3,4) and (4,3). The resulting core genes may improve understanding of prostate cancer in patients with a total GS of 7, the most common grade and most challenging with respect to prognosis.

LMO1 Synergizes with MYCN to Promote Neuroblastoma Initiation and Metastasis

A genome-wide association study identified LMO1, which encodes an LIM-domain-only transcriptional cofactor, as a neuroblastoma susceptibility gene that functions as an oncogene in high-risk neuroblastoma. Here we show that dβh promoter-mediated expression of LMO1 in zebrafish synergizes with MYCN to increase the proliferation of hyperplastic sympathoadrenal precursor cells, leading to a reduced latency and increased penetrance of neuroblastomagenesis. The transgenic expression of LMO1 also promoted hematogenous dissemination and distant metastasis, which was linked to neuroblastoma cell invasion and migration, and elevated expression levels of genes affecting tumor cell-extracellular matrix interaction, including loxl3, itga2b, itga3, and itga5. Our results provide in vivo validation of LMO1 as an important oncogene that promotes neuroblastoma initiation, progression, and widespread metastatic dissemination.

Screening of potential therapy targets for prostate cancer using integrated analysis of two gene expression profiles

The aim of the present study was to analyze potential therapy targets for prostate cancer using integrated analysis of two gene expression profiles. First, gene expression profiles GSE38241 and GSE3933 were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between prostate cancer and normal control samples were identified using the Linear Models for Microarray Data package. Pathway enrichment analysis of DEGs was performed using Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes. Furthermore, protein-protein interaction (PPI) networks of DEGs were constructed, on the basis of the Search Tool for the Retrieval of Interacting Genes/Proteins database. The Molecular Complex Detection was utilized to perform module analysis of the PPI networks. In addition, transcriptional regulatory networks were constructed on the basis of the associations between transcription factors (TFs) and target genes. A total of 529 DEGs were identified, including 129 upregulated genes that were primarily associated with to the cell cycle. Additionally, 400 downregulated genes were identified, which were principally enriched in the pathways associated with vascular smooth muscle contraction and focal adhesion. Cell Division Cycle Associated 8, Cell Division Cycle 45, Ubiquitin Conjugating Enzyme E2 C and Thymidine Kinase 1 were identified as hub genes in the upregulated sub-network. Furthermore, the upregulated TF E2F, and the downregulated TF Early Growth Response 1, were identified to be critical in the transcriptional regulatory networks. The identified DEGs and TFs may have critical roles in the progression of prostate cancer, and may be used as target molecules for treating prostate cancer.

Downregulation of AZGP1 by Ikaros and histone deacetylase promotes tumor progression through the PTEN/Akt and CD44s pathways in hepatocellular carcinoma

Increasing evidence has shown that zinc-alpha2-glycoprotein (AZGP1) is associated with the progression and prognosis of several tumor types. However, little is known regarding the underlying molecular mechanisms of AZGP1 in hepatocellular carcinoma (HCC). In this study, we report that transcription factor Ikaros bound to the AZGP1 promoter and increased its expression in HCC cells. The downregulation of AZGP1 was associated with histone deacetylation in HCC. In addition, the positive feedback regulation via acetylation of histone H4-mediated transactivation of the Ikaros promoter and the Ikaros-mediated transactivation of the acetylation of histone H4 were crucial for regulating AZGP1 expression in HCC cells. Moreover, low serum AZGP1 level in HCC patients was associated with poor prognosis. The ectopic overexpression of AZGP1 or recombinant AZGP1 protein inhibited HCC cell proliferation, migration and invasion in vitro and in vivo, whereas silencing AZGP1 expression resulted in increased cell proliferation, migration and invasion in vitro. In addition, we found that AZGP1 inhibited cell migration and invasion through the regulation of the PTEN/Akt and CD44s pathways. Collectively, our findings revealed the molecular mechanism of AZGP1 expression in HCC, providing new insights into the mechanisms underlying tumor progression.

High sensitivity HPLC method for determination of the allysine concentration in tissue by use of a naphthol derivative

Common to all fibrotic and metastatic diseases is the uncontrollable remodeling of tissue that leads to the accumulation of fibrous connective tissue components such as collagen and elastin. Build-up of fibrous tissue occurs through the cross-linking of collagen or elastin monomers, which is initiated through the oxidation of lysine residues to form α-aminoadipic-δ-semialdehyde (allysine). To provide a measure of the extent of collagen oxidation in disease models of fibrosis or metastasis, a rapid, sensitive HPLC method was developed to quantify the amount of allysine present in tissue. Allysine was reacted with sodium 2-naphthol-7-sulfonate under conditions typically applied for acid hydrolysis of tissues (6M HCl, 110°C, 24h) to prepare AL-NP, a fluorescent bis-naphthol derivative of allysine. High performance liquid chromatography was applied for analysis of allysine content. Under optimal reaction and detection conditions, successful separation of AL-NP was achieved with excellent analytical performance attained. Good linear relationship (R²=0.994) between peak area and concentration for AL-NP was attained for 0.35-175pmol of analyte. A detection limit of 0.02pmol in the standard sample with a 20μL injection was achieved for AL-NP, with satisfactory recovery from 88 to 100% determined. The method was applied in the quantification of allysine in healthy and fibrotic mouse lung tissue, with the fibrotic tissue showing a 2.5 fold increase in the content of allysine.

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.

Identification and Validation of PCAT14 as Prognostic Biomarker in Prostate Cancer

Rapid advances in the discovery of long noncoding RNAs (lncRNAs) have identified lineage- and cancer-specific biomarkers that may be relevant in the clinical management of prostate cancer (PCa). Here we assembled and analyzed a large RNA-seq dataset, from 585 patient samples, including benign prostate tissue and both localized and metastatic PCa to discover and validate differentially expressed genes associated with disease aggressiveness. We performed Sample Set Enrichment Analysis (SSEA) and identified genes associated with low versus high Gleason score in the RNA-seq database. Comparing Gleason 6 versus 9+ PCa samples, we identified 99 differentially expressed genes with variable association to Gleason grade as well as robust expression in prostate cancer. The top-ranked novel lncRNA PCAT14, exhibits both cancer and lineage specificity. On multivariate analysis, low PCAT14 expression independently predicts for BPFS (P = .00126), PSS (P = .0385), and MFS (P = .000609), with trends for OS as well (P = .056). An RNA in-situ hybridization (ISH) assay for PCAT14 distinguished benign vs malignant cases, as well as high vs low Gleason disease. PCAT14 is transcriptionally regulated by AR, and endogenous PCAT14 overexpression suppresses cell invasion. Thus, Using RNA-sequencing data we identify PCAT14, a novel prostate cancer and lineage-specific lncRNA. PCAT14 is highly expressed in low grade disease and loss of PCAT14 predicts for disease aggressiveness and recurrence.

Leucine-rich repeat-containing G protein-coupled receptor 4 (Lgr4) is necessary for prostate cancer metastasis via epithelial-mesenchymal transition

Prostate cancer is a highly penetrant disease among men in industrialized societies, but the factors regulating the transition from indolent to aggressive and metastatic cancer remain poorly understood. We found that men with prostate cancers expressing high levels of the G protein-coupled receptor LGR4 had a significantly shorter recurrence-free survival compared with patients with cancers having low LGR4 expression. LGR4 expression was elevated in human prostate cancer cell lines with metastatic potential. We therefore generated a novel transgenic adenocarcinoma of the mouse prostate (TRAMP) mouse model to investigate the role of Lgr4 in prostate cancer development and metastasis in vivo TRAMP Lgr4^-/- mice exhibited an initial delay in prostate intraepithelial neoplasia formation, but the frequency of tumor formation was equivalent between TRAMP and TRAMP Lgr4^-/- mice by 12 weeks. The loss of Lgr4 significantly improved TRAMP mouse survival and dramatically reduced the occurrence of lung metastases. LGR4 knockdown impaired the migration, invasion, and colony formation of DU145 cells and reversed epithelial-mesenchymal transition (EMT), as demonstrated by up-regulation of E-cadherin and decreased expression of the EMT transcription factors ZEB, Twist, and Snail. Overexpression of LGR4 in LNCaP cells had the opposite effects. Orthotopic injection of DU145 cells stably expressing shRNA targeting LGR4 resulted in decreased xenograft tumor size, reduced tumor EMT marker expression, and impaired metastasis, in accord with our findings in TRAMP Lgr4^-/- mice. In conclusion, we propose that Lgr4 is a key protein necessary for prostate cancer EMT and metastasis.

Identification of genes and pathways in nasopharyngeal carcinoma by bioinformatics analysis

Nasopharyngeal carcinoma is a metastatic malignant tumor originating from nasopharyngeal epithelium. Lacking or nonspecific symptoms of patients with early stage nasopharyngeal carcinoma have significantly reduced the accuracy of diagnosing and predicting nasopharyngeal carcinoma development. This study aimed to identify gene signatures of nasopharyngeal carcinoma and uncover potential mechanisms. Two gene expression profiles (GSE12452 and GSE13597) containing 56 nasopharyngeal carcinoma samples and 13 normal control samples were analyzed to identify the differentially expressed genes. In total, 179 up-regulated genes and 238 down-regulated genes were identified. Functional and pathway enrichment analysis showed that up-regulated genes were significantly involved in cell cycle, oocyte meiosis, DNA replication and p53 signaling pathway, while down-regulated genes were enriched in Huntington's disease,metabolic pathways. Subsequently, the top 10 hub genes, TOP2A (topoisomerase (DNA) II alpha), CDK1 (cyclin-dependent kinase 1), CCNB1 (cyclin B1), PCNA (proliferating cell nuclear antigen), MAD2L1 (mitotic arrest deficient 2 like 1), BUB1 (budding uninhibited by benzimidazoles 1 homolog), CCNB2 (cyclin B2), AURKA (aurora kinase A), CCNA2 (cyclin A2), CDC6 (cell division cycle 6 homolog), were identified from protein-protein interaction network. Furthermore, Module analysis revealed that the ten hub genes except TOP2A were belonged to module 1, indicating the upregulation of these hub genes associated molecular pathways in nasopharyngeal carcinoma might activate nasopharyngeal carcinoma pathogenesis. In conclusion, this study indicated that the identified differentially expressed genes and hub genes enrich our understanding of the molecular mechanisms of nasopharyngeal carcinoma, which could eventually translate into additional biomarkers to facilitate the early diagnosis and therapeutic approaches.

Nuclear mTOR acts as a transcriptional integrator of the androgen signaling pathway in prostate cancer

Audet-Walsh et al. reveal the existence of a nuclear mTOR–androgen receptor transcriptional axis integral to the metabolic rewiring of prostate cancer cells.

Androgen receptor (AR) signaling reprograms cellular metabolism to support prostate cancer (PCa) growth and survival. Another key regulator of cellular metabolism is mTOR, a kinase found in diverse protein complexes and cellular localizations, including the nucleus. However, whether nuclear mTOR plays a role in PCa progression and participates in direct transcriptional cross-talk with the AR is unknown. Here, via the intersection of gene expression, genomic, and metabolic studies, we reveal the existence of a nuclear mTOR–AR transcriptional axis integral to the metabolic rewiring of PCa cells. Androgens reprogram mTOR–chromatin associations in an AR-dependent manner in which activation of mTOR-dependent metabolic gene networks is essential for androgen-induced aerobic glycolysis and mitochondrial respiration. In models of castration-resistant PCa cells, mTOR was capable of transcriptionally regulating metabolic gene programs in the absence of androgens, highlighting a potential novel castration resistance mechanism to sustain cell metabolism even without a functional AR. Remarkably, we demonstrate that increased mTOR nuclear localization is indicative of poor prognosis in patients, with the highest levels detected in castration-resistant PCa tumors and metastases. Identification of a functional mTOR targeted multigene signature robustly discriminates between normal prostate tissues, primary tumors, and hormone refractory metastatic samples but is also predictive of cancer recurrence. This study thus underscores a paradigm shift from AR to nuclear mTOR as being the master transcriptional regulator of metabolism in PCa.

The cancer-associated cell migration protein TSPAN1 is under control of androgens and its upregulation increases prostate cancer cell migration

Cell migration drives cell invasion and metastatic progression in prostate cancer and is a major cause of mortality and morbidity. However the mechanisms driving cell migration in prostate cancer patients are not fully understood. We previously identified the cancer-associated cell migration protein Tetraspanin 1 (TSPAN1) as a clinically relevant androgen regulated target in prostate cancer. Here we find that TSPAN1 is acutely induced by androgens, and is significantly upregulated in prostate cancer relative to both normal prostate tissue and benign prostate hyperplasia (BPH). We also show for the first time, that TSPAN1 expression in prostate cancer cells controls the expression of key proteins involved in cell migration. Stable upregulation of TSPAN1 in both DU145 and PC3 cells significantly increased cell migration and induced the expression of the mesenchymal markers SLUG and ARF6. Our data suggest TSPAN1 is an androgen-driven contributor to cell survival and motility in prostate cancer.

mTORC1-dependent AMD1 regulation sustains polyamine metabolism in prostate cancer

Activation of the PTEN-PI3K-mTORC1 pathway consolidates metabolic programs that sustain cancer cell growth and proliferation. Here we show that mechanistic target of rapamycin complex 1 (mTORC1) regulates polyamine dynamics, a metabolic route that is essential for oncogenicity. By using integrative metabolomics in a mouse model and human biopsies of prostate cancer, we identify alterations in tumours affecting the production of decarboxylated S-adenosylmethionine (dcSAM) and polyamine synthesis. Mechanistically, this metabolic rewiring stems from mTORC1-dependent regulation of S-adenosylmethionine decarboxylase 1 (AMD1) stability. This novel molecular regulation is validated in mouse and human cancer specimens. AMD1 is upregulated in human prostate cancer with activated mTORC1. Conversely, samples from a clinical trial with the mTORC1 inhibitor everolimus exhibit a predominant decrease in AMD1 immunoreactivity that is associated with a decrease in proliferation, in line with the requirement of dcSAM production for oncogenicity. These findings provide fundamental information about the complex regulatory landscape controlled by mTORC1 to integrate and translate growth signals into an oncogenic metabolic program.

Telomeres and telomerase in prostate cancer development and therapy

Aberrations in telomere biology are among the earliest events in prostate cancer tumorigenesis and continue during tumour progression. Substantial telomere shortening occurs in prostate cancer cells and high-grade prostatic intraepithelial neoplasia. Not all mechanisms of telomere shortening are understood, but oxidative stress from local inflammation might accelerate prostatic telomere loss. Critically short telomeres can drive the accumulation of tumour-promoting genomic alterations; however, continued telomere erosion is unsustainable and must be mitigated to ensure cancer cell survival and unlimited replication potential. Prostate cancers predominantly maintain telomeres by activating telomerase, but alternative mechanisms of telomere extension can occur in metastatic disease. Telomerase activity and telomere length assessment might be useful in prostate cancer diagnosis and prognosis. Telomere shortening in normal stromal cells has been associated with prostate cancer, whereas variable telomere lengths in prostate cancer cells and telomere shortening in cancer-associated stromal cells correlated with lethal disease. Single-agent telomerase-targeted treatments for solid cancers were ineffective in clinical trials but have not been investigated in prostate cancer and might be useful in combination with established regimens. Telomere-directed strategies have not been explored as extensively. Telomere deprotection strategies have the advantage of being effective in both telomerase-dependent and telomerase-independent cancers. Disruption of androgen receptor function in prostate cancer cells results in telomere dysfunction, indicating telomeres and telomerase as potential therapeutic targets in prostate cancer.

GAC: Gene Associations with Clinical, a web based application

We present GAC, a shiny R based tool for interactive visualization of clinical associations based on high-dimensional data. The tool provides a web-based suite to perform supervised principal component analysis (SuperPC), an approach that uses both high-dimensional data, such as gene expression, combined with clinical data to infer clinical associations. We extended the approach to address binary outcomes, in addition to continuous and time-to-event data in our package, thereby increasing the use and flexibility of SuperPC.  Additionally, the tool provides an interactive visualization for summarizing results based on a forest plot for both binary and time-to-event data.  In summary, the GAC suite of tools provide a one stop shop for conducting statistical analysis to identify and visualize the association between a clinical outcome of interest and high-dimensional data types, such as genomic data. Our GAC package has been implemented in R and is available via http://shinygispa.winship.emory.edu/GAC/. The developmental repository is available at https://github.com/manalirupji/GAC.

Genetic association analysis of the RTK/ERK pathway with aggressive prostate cancer highlights the potential role of CCND2 in disease progression

The RTK/ERK signaling pathway has been implicated in prostate cancer progression. However, the genetic relevance of this pathway to aggressive prostate cancer at the SNP level remains undefined. Here we performed a SNP and gene-based association analysis of the RTK/ERK pathway with aggressive prostate cancer in a cohort comprising 956 aggressive and 347 non-aggressive cases. We identified several loci including rs3217869/CCND2 within the pathway shown to be significantly associated with aggressive prostate cancer. Our functional analysis revealed a statistically significant relationship between rs3217869 risk genotype and decreased CCND2 expression levels in a collection of 119 prostate cancer patient samples. Reduced expression of CCND2 promoted cell proliferation and its overexpression inhibited cell growth of prostate cancer. Strikingly, CCND2 downregulation was consistently observed in the advanced prostate cancer in 18 available clinical data sets with a total amount of 1,095 prostate samples. Furthermore, the lower expression levels of CCND2 markedly correlated with prostate tumor progression to high Gleason score and elevated PSA levels, and served as an independent predictor of biochemical relapse and overall survival in a large cohort of prostate cancer patients. Together, we have identified an association of genetic variants and genes in the RTK/ERK pathway with prostate cancer aggressiveness, and highlighted the potential importance of CCND2 in prostate cancer susceptibility and tumor progression to metastasis.

Risk Stratification of Newly Diagnosed Prostate Cancer with Genomic Platforms

INTRODUCTION

Interest in novel risk stratification tools for men with newly diagnosed prostate cancer has flourished, aiming to offer increasingly accurate predictions of future disease behavior to ultimately better guide clinical management. We highlight the use of genomic platforms attempting to refine clinical decisions at the point of initial diagnosis.

METHODS

In the context of a benchmark standard of clinical risk stratification tools we reviewed the role of genomic tests, including individual gene expression assays, as well as a growing number of tissue based expression tests assessing multiple gene panels, to improve predictions at initial diagnosis.

RESULTS

The role of single gene status including TMPRSS2:ERG fusion and PTEN expression has been investigated among men with newly diagnosed prostate cancer. Gene expression profiles incorporating panels of genes associated with prostate cancer outcome have received external validation and have commercial application in assays that incorporate baseline clinical risk to offer predictions of immediate pathological and downstream disease end points. Comparisons of gene signatures have offered insights into relative predictive performance in archival tissue. However, to date no studies appear to directly support a single genomic assay offering superior clinical usefulness for decision making at the time of diagnosis.

CONCLUSIONS

Risk stratification tools incorporating genomic analysis of prostate cancer have been developed which seek to improve the accuracy of initial predictions. Further study is warranted to define the additive clinical benefit associated with their use if implemented broadly.

Identification of relevant subtypes via preweighted sparse clustering

Cluster analysis methods are used to identify homogeneous subgroups in a data set. In biomedical applications, one frequently applies cluster analysis in order to identify biologically interesting subgroups. In particular, one may wish to identify subgroups that are associated with a particular outcome of interest. Conventional clustering methods generally do not identify such subgroups, particularly when there are a large number of high-variance features in the data set. Conventional methods may identify clusters associated with these high-variance features when one wishes to obtain secondary clusters that are more interesting biologically or more strongly associated with a particular outcome of interest. A modification of sparse clustering can be used to identify such secondary clusters or clusters associated with an outcome of interest. This method correctly identifies such clusters of interest in several simulation scenarios. The method is also applied to a large prospective cohort study of temporomandibular disorders and a leukemia microarray data set.

Endophilin B2 facilitates endosome maturation in response to growth factor stimulation, autophagy induction, and influenza A virus infection

Endocytosis, and the subsequent trafficking of endosomes, requires dynamic physical alterations in membrane shape that are mediated in part by endophilin proteins. The endophilin B family of proteins contains an N-terminal Bin/amphiphysin/Rvs (N-BAR) domain that induces membrane curvature to regulate intracellular membrane dynamics. Whereas endophilin B1 (SH3GLB1/Bif-1) is known to be involved in a number of cellular processes, including apoptosis, autophagy, and endocytosis, the cellular function of endophilin B2 (SH3GLB2) is not well understood. In this study, we used genetic approaches that revealed that endophilin B2 is not required for embryonic development in vivo but that endophilin B2 deficiency impairs endosomal trafficking in vitro, as evidenced by suppressed endosome acidification, EGFR degradation, autophagic flux, and influenza A viral RNA nuclear entry and replication. Mechanistically, although the loss of endophilin B2 did not affect endocytic internalization and lysosomal function, endophilin B2 appeared to regulate the trafficking of endocytic vesicles and autophagosomes to late endosomes or lysosomes. Moreover, we also found that despite having an intracellular localization and tissue distribution similar to endophilin B1, endophilin B2 is dispensable for mitochondrial apoptosis. Taken together, our findings suggest that endophilin B2 positively regulates the endocytic pathway in response to growth factor signaling, autophagy induction, and viral entry.

Association of elevated interleukin-17 and angiopoietin-2 with prostate size in benign prostatic hyperplasia

INTRODUCTION

Inflammation and angiogenesis are known to play a role in the development prostate tumors. The present study was designed to assess the levels of markers of inflammation and angiogenesis like interleukin-17 (IL-17) and angiopoietin-2 (ANGPT2) levels and their association with prostate size in patients with benign prostatic hyperplasia (BPH).

MATERIALS AND METHODS

42 BPH cases and 42 controls were enrolled in the study. IL-17 and ANGPT2 were estimated in both the groups.

RESULTS

IL-17 and ANGPT2 were significantly increased in BPH cases when compared with controls. Multivariate analysis showed that ANGPT2 predicts the prostate size in patients with BPH (R² = 0.203, beta = 0.355, p = 0.028). Linear regression analysis showed that IL-17 was significantly associated with ANGPT2 in BPH cases (R²=0.129, beta - 0.359, p = 0.020).

CONCLUSIONS

We conclude that IL-17 and ANGPT2 are elevated in BPH cases and ANGPT2 was associated with IL-17 and prostate size.

A novel microRNA regulator of prostate cancer epithelial-mesenchymal transition

The most frequent alteration in the prostate oncogenome is loss of chromosome (chr) 8p21 that has been associated with loss of NKX3.1 homeobox gene. Chr8p21 deletions increase significantly with tumor grade and are associated with poor prognosis in prostate cancer (PCa), suggesting critical involvement of this region in tumor progression. Recent studies suggest that apart from NKX3.1, this region harbors alternative tumor suppressors that are yet undefined. We proposed a novel, paradigm shifting hypothesis that this locus is associated with a miRNA gene cluster-miR-3622a/b- that plays a crucial suppressive role in PCa. Here we demonstrate the crucial role of miR-3622a in prostate cancer epithelial-to-mesenchymal transition (EMT). MicroRNA expression profiling in microdissected human PCa clinical tissues showed that miR-3622a expression is widely downregulated and is significantly correlated with poor survival outcome and tumor progression. To understand the functional significance of miR-3622a, knockdown and overexpression was performed using non-transformed prostate epithelial and PCa cell lines, respectively, followed by functional assays. Our data demonstrate that endogenous miR-3622a expression is vital to maintain the epithelial state of normal and untransformed prostate cells. miR-3622a expression inhibits EMT, progression and metastasis of PCa in vitro and in vivo. Further, we found that miR-3622a directly targets EMT effectors ZEB1 and SNAI2. In view of these data, we propose that frequent loss of miR-3622a at chr8p21 region leads to induction of EMT states that in turn, promotes PCa progression and metastasis. This study has potentially significant implications in the field of prostate cancer as it identifies an important miRNA component of a frequently lost chromosomal region with critical roles in prostate carcinogenesis which is a highly significant step towards understanding the mechanistic involvement of this locus. Also, our study indicates that miR-3622a is a novel PCa biomarker and potential drug target for developing therapeutic regimens against advanced PCa.

An Integrative Genomics Approach for Associating Genome-Wide Association Studies Information With Localized and Metastatic Prostate Cancer Phenotypes

High-throughput genotyping has enabled discovery of genetic variants associated with an increased risk of developing prostate cancer using genome-wide association studies (GWAS). The goal of this study was to associate GWAS information of patients with primary organ–confined and metastatic prostate cancer using gene expression data and to identify molecular networks and biological pathways enriched for genetic susceptibility variants involved in the 2 disease states. The analysis revealed gene signatures for the 2 disease states and a gene signature distinguishing the 2 patient groups. In addition, the analysis revealed molecular networks and biological pathways enriched for genetic susceptibility variants. The discovered pathways include the androgen, apoptosis, and insulinlike growth factor signaling pathways. This analysis established putative functional bridges between GWAS discoveries and the biological pathways involved in primary organ–confined and metastatic prostate cancer.

Trends in Gene Expression Profiling for Prostate Cancer Risk Assessment: A Systematic Review

OBJECTIVES

The aim of the study is to review biotechnology advances in gene expression profiling on prostate cancer (PCa), focusing on experimental platform development and gene discovery, in relation to different study designs and outcomes in order to understand how they can be exploited to improve PCa diagnosis and clinical management.

METHODS

We conducted a systematic literature review on gene expression profiling studies through PubMed/MEDLINE and Web of Science between 2000 and 2016. Tissue biopsy and clinical gene profiling studies with different outcomes (e.g., recurrence, survival) were included.

RESULTS

Over 3,000 papers were screened and 137 full-text articles were selected. In terms of technology used, microarray is still the most popular technique, increasing from 50 to 70% between 2010 and 2015, but there has been a rise in the number of studies using RNA sequencing (13% in 2015). Sample sizes have increased, as well as the number of genes that can be screened all at once, but we have also observed more focused targeting in more recent studies. Qualitative analysis on the specific genes found associated with PCa risk or clinical outcomes revealed a large variety of gene candidates, with a few consistent cross-studies.

CONCLUSIONS

The last 15 years of research in gene expression in PCa have brought a large volume of data and information that has been decoded only in part, but advancements in high-throughput sequencing technology are increasing the amount of data that can be generated. The variety of findings warrants the execution of both validation studies and meta-analyses. Genetic biomarkers have tremendous potential for early diagnosis of PCa and, if coupled with other diagnostics (e.g., imaging), can effectively be used to concretize less-invasive, personalized prediction of PCa risk and progression.

Molecular classification of prostate adenocarcinoma by the integrated somatic mutation profiles and molecular network

Prostate cancer is one of the most common cancers in men and a leading cause of cancer death worldwide, displaying a broad range of heterogeneity in terms of clinical and molecular behavior. Increasing evidence suggests that classifying prostate cancers into distinct molecular subtypes is critical to exploring the potential molecular variation underlying this heterogeneity and to better treat this cancer. In this study, the somatic mutation profiles of prostate cancer were downloaded from the TCGA database and used as the source nodes of the random walk with restart algorithm (RWRA) for generating smoothed mutation profiles in the STRING network. The smoothed mutation profiles were selected as the input matrix of the Graph-regularized Nonnegative Matrix Factorization (GNMF) for classifying patients into distinct molecular subtypes. The results were associated with most of the clinical and pathological outcomes. In addition, some bioinformatics analyses were performed for the robust subtyping, and good results were obtained. These results indicated that prostate cancers can be usefully classified according to their mutation profiles, and we hope that these subtypes will help improve the treatment stratification of this cancer in the future.

Epithelial protein lost in neoplasm (EPLIN): Beyond a tumor suppressor

The majority of cancer-related deaths are caused by tumor recurrence, metastasis and therapeutic resistance. During the late stages of tumor progression, multiple factors are involved, including the downregulation and/or loss of function of metastasis suppressors. Epithelial protein lost in neoplasm (EPLIN), an actin-binding protein, was initially identified as a putative tumor suppressor that is frequently downregulated in epithelial tumors. Recent evidence indicates that EPLIN may negatively regulate epithelia-to-mesenchymal transition (EMT), a crucial process by which cancer cells acquire invasive capabilities and therapeutic resistance. Importantly, downregulation of EPLIN is associated with clinical metastasis in a variety of solid tumors, suggesting that EPLIN could be a suppressor of metastasis. In this review, I will discuss the regulation and function of EPLIN in human cancer cells and explore the clinical significance of EPLIN in metastatic disease.

Upregulation of FAM84B during prostate cancer progression

Although the FAM84B gene lies within chromosome 8q24, a locus frequently altered in prostate cancer (PC), its alteration during prostate tumorigenesis has not been well studied. We report here FAM84B upregulation in DU145 cell-derived prostate cancer stem-like cells (PCSLCs) and DU145 cell-produced lung metastases compared to subcutaneous xenograft tumors. FAM84B protein was detected in bone metastases and primary PCs. Nanostring examination of 7 pairs of tumor adjacent normal and PC tissues revealed elevations in FAM84B mRNA levels in all carcinomas. Furthermore, through analysis of FAM84B expression using large datasets within the Gene Expression Omnibus and OncomineTM database, we demonstrate significant increases in FAM84B mRNA in 343 primary PCs versus 181 normal tissues, and elevations in the FAM84B gene copy number (GCN) in 171 primary PCs versus 61 normal tissues. While FAM84B was not detected at higher levels via immunohistochemistry in high grade (Gleason score/GS 8-10) tumors compared to GS6-7 PCs, analyses of FAM84B mRNA and GCN using datasets within the cBioPortal database demonstrated FAM84B upregulation in 12% (67/549) of primary PCs and 18% (73/412) of metastatic castration resistant PCs (mCRPCs), and GCN increases in 4.8% (26/546) of primary PCs and 26% (121/467) of mCRPCs, revealing an association of the aforementioned changes with CRPC development. Of note, an increase in FAM84B expression was observed in xenograft CRPCs produced by LNCaP cells. Furthermore, FAM84B upregulation and GCN increases correlate with decreases in disease free survival and overall survival. Collectively, we demonstrate a novel association of FAM84B with PC tumorigenesis and CRPC progression.

Comparison of statistical methods for subnetwork detection in the integration of gene expression and protein interaction network

Background

With the advancement of high-throughput technologies and enrichment of popular public databases, more and more research focuses of bioinformatics research have been on computational integration of network and gene expression profiles for extracting context-dependent active subnetworks. Many methods for subnetwork searching have been developed. Scoring and searching algorithms present a range of computational considerations and implementations. The primary goal of present study is to comprehensively evaluate the performance of different subnetwork detection methods. Eleven popular methods were selected for comprehensive comparison.

Results

First, taking into account the dependence of genes given a protein-protein interaction (PPI) network, we simulated microarray gene expression data under case and control conditions. Then each method was applied to the simulated data for subnetwork identification. Second, a large microarray data set of prostate cancer was used to assess the practical performance of each method. Using both simulation studies and a real data application, we evaluated the performance of different methods in terms of recall and precision.

Conclusions

jActiveModules, PinnacleZ and WMAXC performed well in identifying subnetwork with relative high precision and recall. BioNet performed very well only in precision. As none of methods outperformed other methods overall, users should choose an appropriate method based on the purposes of their studies.

Preclinical Development of a Nontoxic Oral Formulation of Monoethanolamine, a Lipid Precursor, for Prostate Cancer Treatment

Purpose: Most currently available chemotherapeutic agents target rampant cell division in cancer cells, thereby affecting rapidly dividing normal cells resulting in toxic side-effects. This nonspecificity necessitates identification of novel cellular pathways that are reprogrammed selectively in cancer cells and can be exploited to develop pharmacologically superior and less toxic therapeutics. Despite growing awareness on dysregulation of lipid metabolism in cancer cells, targeting lipid biosynthesis is still largely uncharted territory. Herein, we report development of a novel nontoxic orally deliverable anticancer formulation of monoethanolamine (Etn) for prostate cancer by targeting the Kennedy pathway of phosphatidylethanolamine (PE) lipid biosynthesis.Experimental Design: We first evaluated gastrointestinal tract stability, drug-drug interaction liability, pharmacokinetic, and toxicokinetic properties of Etn to evaluate its suitability as a nontoxic orally deliverable agent. We next performed in vitro and in vivo experiments to investigate efficacy and mechanism of action.Results: Our data demonstrate that Etn exhibits excellent bioavailability, gastrointestinal tract stability, and no drug-drug interaction liability. Remarkably, orally fed Etn inhibited tumor growth in four weeks by approximately 67% in mice bearing human prostate cancer PC-3 xenografts without any apparent toxicity. Mechanistically, Etn exploits selective overexpression of choline kinase in cancer cells, resulting in accumulation of phosphoethanolamine (PhosE), accompanied by downregulation of HIF-1α that induces metabolic stress culminating into cell death.Conclusions: Our study provides first evidence for the superior anticancer activity of Etn, a simple lipid precursor formulation, whose nontoxicity conforms to FDA-approved standards, compelling its clinical development for prostate cancer management. Clin Cancer Res; 23(14); 3781-93. ©2017 AACR.

A novel microRNA-1207-3p/FNDC1/FN1/AR regulatory pathway in prostate cancer

Prostate cancer (PCa) is the second most common cause of cancer-specific deaths in the U.S. Unfortunately, the underlying molecular mechanisms for its development and progression remain unclear. Studies have established that microRNAs (miRNAs) are dysregulated in PCa. The intron-derived microRNA-1207-3p (miR-1207-3p) is encoded at the non-protein coding gene locus PVT1 on the 8q24 human chromosomal region, an established PCa susceptibility locus. However, miR-1207-3p in PCa had not previously been investigated. Therefore, we explored if miR-1207-3p plays any regulatory role in PCa. We discovered that miR-1207-3p is significantly underexpressed in PCa cell lines in comparison to normal prostate epithelial cells, and that increased expression of microRNA-1207-3p in PCa cells significantly inhibits proliferation, migration, and induces apoptosis via direct molecular targeting of fibronectin type III domain containing 1 (FNDC1). Our studies also revealed significant overexpression of FNDC1, fibronectin (FN1) and the androgen receptor (AR) in human PCa cell lines as well as tissues, and FNDC1, FN1, and AR positively correlate with aggressive PCa. These findings, recently published in Experimental Cell Research, are the first to describe a novel miR-1207-3p/FNDC1/FN1/AR novel regulatory pathway in PCa.

Prostate Cancer Cells in Different Androgen Receptor Status Employ Different Leucine Transporters

BACKGROUND

Leucine stimulates cancer cell proliferation through the mTOR pathway, therefore, inhibiting leucine transporters may be a novel therapeutic target for cancer. L-type amino acid transporter (LAT) 1, a Na⁺ -independent amino acid transporter, is highly expressed in many tumor cells. However, leucine transporter(s) in different stages of prostate cancer, particularly in the stages of castration resistance with androgen receptor (AR) expression, is unclear.

METHODS

LNCaP and DU145 and PC-3 cell lines were used as a model of androgen dependent, and metastatic prostate cancer. A new "LN-cr" cell line was established after culturing LNCaP cells for 6 months under androgen-free conditions, which is considered a model of castration resistant prostate cancer (CRPC) with androgen AR expression. The expression of leucine transporters was investigated with quantitative PCR and immunofluorescence. Uptake of ¹⁴ C Leucine was examined in the presence or absence of BCH (a pan-LAT inhibitor), JPH203 (an LAT1-specific inhibitor), or Na⁺ . Cell growth was assessed with MTT assay. siRNA studies were performed to evaluate the indispensability of y⁺ LAT2 on leucine uptake and cell viability in LN-cr.

RESULTS

Cell viability showed a 90% decrease in the absence of leucine in all four cell lines. LNCaP cells principally expressed LAT3, and their leucine uptake was more than 90% Na⁺ -independent. BCH, but not JPH203, inhibited leucine uptake, and cell proliferation (IC_50BCH :15 mM). DU145 and PC-3 cells predominantly expressed LAT1. Leucine uptake and cell growth were suppressed by BCH or JPH203 in a dose-dependent manner (IC_50BCH : ∼20 mM, IC_50JPH203 : ∼5 µM). In LN-cr cells, Na⁺ -dependent uptake of leucine was 3.8 pmol/mgprotein/min, while, Na⁺ -independent uptake was only 0.52 (P < 0.05). Leucine uptake of LN-cr was largely (∼85%) Na⁺ -dependent. y⁺ LAT2 expression was confirmed in LN-cr. Knockdown of y⁺ LAT2 lead to significant leucine uptake inhibition (40%) and cell growth inhibition (20%).

CONCLUSIONS

New CRPC cell line with increased expression of y⁺ LAT2 as a leucine transporter was established in vitro. Anti-leucine transporter therapy could be an important option against prostate cancer. Prostate 77:222-233, 2017. © 2016 Wiley Periodicals, Inc.

Learning Parsimonious Classification Rules from Gene Expression Data Using Bayesian Networks with Local Structure

The comprehensibility of good predictive models learned from high-dimensional gene expression data is attractive because it can lead to biomarker discovery. Several good classifiers provide comparable predictive performance but differ in their abilities to summarize the observed data. We extend a Bayesian Rule Learning (BRL-GSS) algorithm, previously shown to be a significantly better predictor than other classical approaches in this domain. It searches a space of Bayesian networks using a decision tree representation of its parameters with global constraints, and infers a set of IF-THEN rules. The number of parameters and therefore the number of rules are combinatorial to the number of predictor variables in the model. We relax these global constraints to a more generalizable local structure (BRL-LSS). BRL-LSS entails more parsimonious set of rules because it does not have to generate all combinatorial rules. The search space of local structures is much richer than the space of global structures. We design the BRL-LSS with the same worst-case time-complexity as BRL-GSS while exploring a richer and more complex model space. We measure predictive performance using Area Under the ROC curve (AUC) and Accuracy. We measure model parsimony performance by noting the average number of rules and variables needed to describe the observed data. We evaluate the predictive and parsimony performance of BRL-GSS, BRL-LSS and the state-of-the-art C4.5 decision tree algorithm, across 10-fold cross-validation using ten microarray gene-expression diagnostic datasets. In these experiments, we observe that BRL-LSS is similar to BRL-GSS in terms of predictive performance, while generating a much more parsimonious set of rules to explain the same observed data. BRL-LSS also needs fewer variables than C4.5 to explain the data with similar predictive performance. We also conduct a feasibility study to demonstrate the general applicability of our BRL methods on the newer RNA sequencing gene-expression data.

Cancer Stem Cell Gene Variants Predict Disease Recurrence in Patients Treated with Radical Prostatectomy for Prostate Cancer

Background: Cancer stem cells (CSCs) are involved in tumor progression and drug resistance. We hypothesized that variants in CSC marker genes influence treatment outcomes in prostate cancer. Methods: Ten potentially functional single nucleotide polymorphisms (SNPs) in seven prostate CSC marker genes, TACSTD2, PROM1, ITGA2, POU5F1, EZH2, PSCA, and CD44, were selected for analysis of their association with disease recurrence by Kaplan-Meier analysis and Cox regression in a cohort of 320 patients with localized prostate cancer receiving radical prostatectomy. Results: We identified one independent SNP, rs2394882, in POU5F1 that was associated with prostate cancer recurrence (hazard ratio 0.32, 95% confidence interval 0.14-0.71, P = 0.005) after adjustment for known clinical predictors. Further in silico functional analyses revealed that rs2394882 affects POU5F1 expression, which in turn is significantly correlated with prostate cancer aggressiveness and patient prognosis. Conclusion: Our results suggest that rs2394882 is prognostically relevant in prostate cancer, possibly by modulating the expression of the CSC gene POU5F1.

Testing homogeneity in semiparametric mixture case-control models

Parametric and semiparametric mixture models have been widely used in applications from many areas, and it is often of interest to test homogeneity in these models. However, hypothesis testing is nonstandard due to the fact that several regularity conditions do not hold under the null hypothesis. We consider a semiparametric mixture case-control model, in the sense that the density ratio of two distributions is assumed to be of an exponential form, while the baseline density is unspecified. This model was first considered by Qin and Liang (2011, biometrics), and they proposed a modified score statistic for testing homogeneity. In this paper, we consider alternative testing procedures based on supremum statistics, which could improve power against certain types of alternatives. We demonstrate the connection and comparison among proposed and existing these approaches. In addition, we provide a unified theoretical justification of the supremum test and other existing test statistics from an empirical likelihood perspective. The finite sample performance of the supremum test statistics were evaluated in simulation studies.

Molecular subtyping of prostate cancer

PURPOSE OF REVIEW

The recent publication of The Cancer Genome Atlas molecular taxonomy of primary prostate cancer highlights the increased understanding of the genomic basis of human prostate cancer, but also emphasizes the complexity and heterogeneity of prostate cancer.

RECENT FINDINGS

Seven molecular subclasses have been defined on the basis of early genomic alterations, which are largely mutually exclusive.

SUMMARY

We review the recent advances in the genomic understanding of human prostate cancer, with focus on molecular subclassification. Broadly, prostate cancer can be classified based upon whether specific genomic rearrangements, such as the Transmembrane Protease, Serine 2-ETS-related gene fusion occur or whether specific alterations such as Speckle-type POZ protein and forkhead box A1 mutations occur. The molecular drivers remain to be identified in a further quarter of human prostate cancers. Depending upon the molecular subclassification and the coincident genomic alterations, specific clinical insights can be gained from this information, including associations with pathologic factors, race, and prognosis, as well as the possibility for future precision therapies.

LOX expression in primary nasopharyngeal carcinoma: correlation with prognostic parameters and outcome

Lysyl oxidase (LOX) is an extracellular matrix-remodeling enzyme that plays important roles in tumor development and progression. To evaluate the prognostic value of LOX levels in primary nasopharyngeal carcinoma, we performed an immunohistochemical analysis using 233 tissue biopsy specimens from as many patients. We found that the extent of immunohistochemical LOX staining correlated inversely with the clinicopathological features and survival. High LOX expression correlated with decreases in 5-year survival, overall survival, distant metastasis-free survival and disease-free survival (p < 0.05). Cox regression analysis confirmed that LOX was a significant prognostic indicator of increased risk of 5-year mortality for all patients (hazard ratio [HR], 1.670; 95% confidence interval [95% CI], 1.033-2.701 [p < .005]). Higher LOX expression was also an independent predictor of poor prognosis in patients with nasopharyngeal carcinoma. These findings suggest LOX may be a new biomarker predictive of NPC prognosis and may also be a useful treatment target.

Amplification of MUC1 in prostate cancer metastasis and CRPC development

Evidence supports the upregulation of MUC1 in prostate cancer (PC). However, this has not been thoroughly investigated. We report here an association of MUC1 upregulation with PC metastasis and the development of castration resistant PC (CRPC). MUC1 expression was specifically increased in DU145 cell-derived PC stem-like cells (PCSLCs) in comparison to their non-PCSLCs counterparts. While immunohistochemistry staining of 34 primary PCs revealed variability in MUC1 expression, Nanostring technology demonstrated elevated MUC1 mRNA levels in 4 of 7 PCs compared to their normal matched tissues. By analyzing MUC1 mRNA levels and gene copy number (GCN) using the OncomineTM database, elevations in MUC1 mRNA in 82 metastases versus 280 primary PCs and in MUC1 GCN in 37 metastases over 181 primary tumors were demonstrated. Analysis of genomic datasets within cBioPortal revealed increases in MUC1 GCN in 2% (6/333) of primary PCs, 6% (9/150) of metastatic PCs, and 33% (27/82) of CRPCs; in comparison, the respective increase in androgen receptor (AR) GCN was 1%, 63%, and 56%, revealing a specific increase in MUC1 GCN for CRPC. Furthermore, a 25-gene MUC1 network was amplified in 52% of CRPCs compared to 69% of CRPCs displaying increases in an AR co-regulator group. While genomic alterations in the MUC1 network largely overlap with those in the AR group, 18 CRPCs (66.7% being neuroendocrine PC) showed genomic alterations only in the MUC1 network. Moreover, genomic alterations in the MUC1 network correlated with PC relapse. Collectively, our observations suggest a combination therapy involving MUC1-based immunotherapy and androgen deprivation.

Loss of AZGP1 as a Superior Predictor of Relapse in Margin-Positive Localized Prostate Cancer

BACKGROUND

Positive surgical margins (PSMs) in localized prostate cancer (PC) confer a two- to three-fold increased risk of biochemical relapse (BR). Absent/weak AZGP1 expression and Gleason grade ≥4 at the margin are each independent predictors of BR in patients with PSMs. Our study aimed to determine whether the biomarkers AZGP1 expression and Gleason grade at the site of a PSM are significant independent markers of biochemical and clinical relapse (CR) when modeled together and whether one of these biomarkers may be superior in its capacity to predict outcome.

METHODS

A cohort of 275 consecutive patients with margin-positive localized PC following surgery were assessed for Gleason grade and AZGP1 expression at the PSM. BR-free survival was the primary end-point, while CR-free survival and PC-specific death were secondary endpoints. Kaplan-Meier Analysis and Cox Proportional Hazards Modeling were performed.

RESULTS

Absent AZGP1 expression was significantly associated with increased risk of BR (P = 0.001) and PC-specific death (P = 0.02). Gleason grade ≥4 at PSM was associated with BR (P = 0.02), CR (P = 0.003), and PC-specific death (P = 0.004). On multivariable analysis, absent AZGP1 expression remained an independent predictor of BR (HR 2.4, 95%CI 1.5-3.9, P < 0.001) when modeled with Gleason grade at margin (HR 1.3, 95%CI 0.9-1.9, P = 0.16), preoperative PSA (P = 0.002), seminal vesicle involvement (P = 0.002), extraprostatic extension (P = 0.001), Gleason score (P = 0.01), adjuvant treatment (P = 0.75), linear length of the involved margin (P = 0.001) and margin number (P = 0.09).

CONCLUSION

Absent AZGP1 expression is an independent predictor of BR in margin-positive localized PC and is associated with increased PC-specific mortality in a Phase II study. Absent AZGP1 expression was superior to Gleason grade at PSM in predicting relapse and should be incorporated into subsequent clinical trials of post-operative radiotherapy in men with margin-positive PC. Prostate 76:1491-1500, 2016. © 2016 Wiley Periodicals, Inc.

MicroRNA-383 located in frequently deleted chromosomal locus 8p22 regulates CD44 in prostate cancer

A major genomic alteration in prostate cancer (PCa) is frequent loss of chromosome (chr) 8p with a common region of loss of heterozygosity (LOH) at chr8p22 locus. Genomic studies implicate this locus in the initiation of clinically significant PCa and with progression to metastatic disease. However, the genes within this region have not been fully characterized to date. Here we demonstrate for the first time that a microRNA component of this region –miR-383- is frequently downregulated in prostate cancer, plays a critical role in determining tumor initiating potential and is involved in prostate cancer metastasis via direct regulation of CD44, a ubiquitous marker of PCa tumor initiating cells (TICs)/ stem cells. Expression analyses of miR-383 in PCa clinical tissues established that low miR-383 expression is associated with poor prognosis. Functional data suggests that miR-383 regulates PCa tumor initiating/ stem-like cells via CD44 regulation. Ectopic expression of miR-383 inhibited tumor initiating capacity of CD44+ PCa cells. Also, ‘anti-metastatic’ effects of ectopic miR-383 expression were observed in a PCa experimental metastasis model. In view of our results, we propose that frequent loss of miR-383 at chr8p22 region leads to tumor initiation and prostate cancer metastasis. Thus, we have identified a novel finding that associates a long observed genomic alteration to PCa stemness and metastasis. Our data suggests that restoration of miR-383 expression may be an effective therapeutic modality against PCa. Importantly, we identified miR-383 as a novel PCa tissue diagnostic biomarker with a potential that outperforms that of serum PSA.

ZFP91: A Noncanonical NF-κB Signaling Pathway Regulator with Oncogenic Properties Is Overexpressed in Prostate Cancer

Novel molecular targets are being searched to aid in prostate cancer diagnosis and therapy. Recently, ZFP91 zinc finger protein has been found to be upregulated in prostate cancer cell lines. It is a potentially important oncogenic protein; however only limited data regarding its biological function and expression patterns are available. To date, ZFP91 has been shown to be a key factor in activation of noncanonical NF-κB signaling pathway as well as to be involved in HIF-1α signaling in cancer cells. The present study aimed to characterize ZFP91 expression in prostate cancer specimens. Furthermore, since our earlier reports showed discrepancies between ZFP91 mRNA and protein levels, we studied this interrelationship in LNCaP and PC-3 prostate cancer cell lines using siRNA mediated knockdown. QPCR analysis revealed marked upregulation of ZFP91 mRNA in the majority of prostate cancer specimens. Transfection of prostate cancer cells with ZFP91 siRNA resulted in a 10-fold decrease in mRNA levels. On a protein level, however, no inhibitory effect was observed over the time of the cell culture. We conclude that ZFP91 is overexpressed in prostate cancer and that potential accumulation of the ZFP91 protein in studied cells may be of importance in prostate cancer biology.

MUC1 Expression by Immunohistochemistry Is Associated with Adverse Pathologic Features in Prostate Cancer: A Multi-Institutional Study

Background

The uncertainties inherent in clinical measures of prostate cancer (CaP) aggressiveness endorse the investigation of clinically validated tissue biomarkers. MUC1 expression has been previously reported to independently predict aggressive localized prostate cancer. We used a large cohort to validate whether MUC1 protein levels measured by immunohistochemistry (IHC) predict aggressive cancer, recurrence and survival outcomes after radical prostatectomy independent of clinical and pathological parameters.

Material and Methods

MUC1 IHC was performed on a multi-institutional tissue microarray (TMA) resource including 1,326 men with a median follow-up of 5 years. Associations with clinical and pathological parameters were tested by the Chi-square test and the Wilcoxon rank sum test. Relationships with outcome were assessed with univariable and multivariable Cox proportional hazard models and the Log-rank test.

Results

The presence of MUC1 expression was significantly associated with extracapsular extension and higher Gleason score, but not with seminal vesicle invasion, age, positive surgical margins or pre-operative serum PSA levels. In univariable analyses, positive MUC1 staining was significantly associated with a worse recurrence free survival (RFS) (HR: 1.24, CI 1.03–1.49, P = 0.02), although not with disease specific survival (DSS, P>0.5). On multivariable analyses, the presence of positive surgical margins, extracapsular extension, seminal vesicle invasion, as well as higher pre-operative PSA and increasing Gleason score were independently associated with RFS, while MUC1 expression was not. Positive MUC1 expression was not independently associated with disease specific survival (DSS), but was weakly associated with overall survival (OS).

Conclusion

In our large, rigorously designed validation cohort, MUC1 protein expression was associated with adverse pathological features, although it was not an independent predictor of outcome after radical prostatectomy.

miR-1207-3p regulates the androgen receptor in prostate cancer via FNDC1/fibronectin

Prostate cancer (PCa) is frequently diagnosed in men, and dysregulation of microRNAs is characteristic of many cancers. MicroRNA-1207-3p is encoded at the non-protein coding gene locus PVT1 on the 8q24 human chromosomal region, an established PCa susceptibility locus. However, the role of microRNA-1207-3p in PCa is unclear. We discovered that microRNA-1207-3p is significantly underexpressed in PCa cell lines in comparison to normal prostate epithelial cells. Increased expression of microRNA-1207-3p in PCa cells significantly inhibits proliferation, migration, and induces apoptosis via direct molecular targeting of FNDC1, a protein which contains a conserved protein domain of fibronectin (FN1). FNDC1, FN1, and the androgen receptor (AR) are significantly overexpressed in PCa cell lines and human PCa, and positively correlate with aggressive PCa. Prostate tumor FN1 expression in patients that experienced PCa-specific death is significantly higher than in patients that remained alive. Furthermore, FNDC1, FN1 and AR are concomitantly overexpressed in metastatic PCa. Consequently, these studies have revealed a novel microRNA-1207-3p/FNDC1/FN1/AR regulatory pathway in PCa.

Lentiviral vector-mediated insertional mutagenesis screen identifies genes that influence androgen independent prostate cancer progression and predict clinical outcome

Prostate cancer (PC) is the second leading cause of cancer related deaths in US men. Androgen deprivation therapy (ADT) improves clinical outcome, but tumors often recur and progress to androgen independent prostate cancer (AIPC) which no longer responds to ADT. The progression to AIPC is due to genetic alterations that allow PC cancer cells to grow in the absence of androgen. Here we performed an insertional mutagenesis screen using a replication-incompetent lentiviral vector (LV) to identify the genes that promote AIPC in an orthotopic mouse model. Androgen sensitive PC cells, LNCaP, were mutagenized with LV and injected into the prostate of male mice. After tumor development, mice were castrated to select for cells that proliferate in the absence of androgen. Proviral integration sites and nearby dysregulated genes were identified in tumors developed in an androgen deficient environment. Using publically available datasets, the expression of these candidate androgen independence genes in human PC tissues were analyzed. A total of 11 promising candidate AIPC genes were identified: GLYATL1, FLNA, OBSCN, STRA13, WHSC1, ARFGAP3, KDM2A, FAM83H, CLDN7, CNOT6, and B3GNT9. Seven out the 11 candidate genes; GLYATL1, OBSCN, STRA13, KDM2A, FAM83H, CNOT6, and B3GNT6, have not been previously implicated in PC. An in vitro clonogenic assay showed that knockdown of KDM2A, FAM83H, and GLYATL1 genes significantly inhibited the colony forming ability of LNCaP cells. Additionally, we showed that a combination of four genes, OBSCN, FAM83H, CLDN7, and ARFGAP3 could significantly predicted the recurrence risk in PC patients after prostatectomy (P = 5.3 × 10-5 ). © 2015 Wiley Periodicals, Inc.

Loss of Expression of AZGP1 Is Associated With Worse Clinical Outcomes in a Multi-Institutional Radical Prostatectomy Cohort

BACKGROUND

Given the uncertainties inherent in clinical measures of prostate cancer aggressiveness, clinically validated tissue biomarkers are needed. We tested whether Alpha-2-Glycoprotein 1, Zinc-Binding (AZGP1) protein levels, measured by immunohistochemistry, and RNA expression, by RNA in situ hybridization (RISH), predict recurrence after radical prostatectomy independent of clinical and pathological parameters.

METHODS

AZGP1 IHC and RISH were performed on a large multi-institutional tissue microarray resource including 1,275 men with 5 year median follow-up. The relationship between IHC and RISH expression levels was assessed using the Kappa analysis. Associations with clinical and pathological parameters were tested by the Chi-square test and the Wilcoxon rank sum test. Relationships with outcome were assessed with univariable and multivariable Cox proportional hazards models and the Log-rank test.

RESULTS

Absent or weak expression of AZGP1 protein was associated with worse recurrence free survival (RFS), disease specific survival, and overall survival after radical prostatectomy in univariable analysis. AZGP1 protein expression, along with pre-operative serum PSA levels, surgical margin status, seminal vesicle invasion, extracapsular extension, and Gleason score predicted RFS on multivariable analysis. Similarly, absent or low AZGP1 RNA expression by RISH predicted worse RFS after prostatectomy in univariable and multivariable analysis.

CONCLUSIONS

In our large, rigorously designed validation cohort, loss of AZGP1 expression predicts RFS after radical prostatectomy independent of clinical and pathological variables. Prostate 76:1409-1419, 2016. © 2016 Wiley Periodicals, Inc.

The 2016 John J. Abel Award Lecture: Targeting the Mechanical Microenvironment in Cancer

Past decades of cancer research have mainly focused on the role of various extracellular and intracellular biochemical signals on cancer progression and metastasis. Recent studies suggest an important role of mechanical forces in regulating cellular behaviors. This review first provides an overview of the mechanobiology research field. Then we specially focus on mechanotransduction pathways in cancer progression and describe in detail the key signaling components of such mechanotransduction pathways and extracellular matrix components that are altered in cancer. Although our understanding of mechanoregulation in cancer is still in its infancy, some agents against key mechanoregulators have been developed and will be discussed to explore the potential of pharmacologically targeting mechanotransduction in cancer.

CAFÉ-Map: Context Aware Feature Mapping for mining high dimensional biomedical data

Feature selection and ranking is of great importance in the analysis of biomedical data. In addition to reducing the number of features used in classification or other machine learning tasks, it allows us to extract meaningful biological and medical information from a machine learning model. Most existing approaches in this domain do not directly model the fact that the relative importance of features can be different in different regions of the feature space. In this work, we present a context aware feature ranking algorithm called CAFÉ-Map. CAFÉ-Map is a locally linear feature ranking framework that allows recognition of important features in any given region of the feature space or for any individual example. This allows for simultaneous classification and feature ranking in an interpretable manner. We have benchmarked CAFÉ-Map on a number of toy and real world biomedical data sets. Our comparative study with a number of published methods shows that CAFÉ-Map achieves better accuracies on these data sets. The top ranking features obtained through CAFÉ-Map in a gene profiling study correlate very well with the importance of different genes reported in the literature. Furthermore, CAFÉ-Map provides a more in-depth analysis of feature ranking at the level of individual examples.

AVAILABILITY

CAFÉ-Map Python code is available at: http://faculty.pieas.edu.pk/fayyaz/software.html#cafemap . The CAFÉ-Map package supports parallelization and sparse data and provides example scripts for classification. This code can be used to reconstruct the results given in this paper.