The Search for Secreted Proteins in Prostate Cancer by the Escherichia coli Ampicillin Secretion Trap: Expression of NBL1 Is Highly Restricted to the Prostate and Is Related to Cancer Progression

Aims: Genes expressed only in cancer tissue or specific organs will be useful molecular markers. To identify genes that encode secreted proteins present in prostate cancer (PCa), we generated Escherichia coli ampicillin secretion trap (CAST) libraries from PCa and normal prostate (NP). Methods and Results: We identified 15 candidate genes that encode secreted proteins present in PCa and NP. Quantitative RT-PCR analysis revealed that MSMB, NBL1 and AZGP1 were expressed with much higher specificity in PCa and NP than in 14 other kinds of normal tissue. We focused on NBL1, which was originally identified as a putative tumor suppressor gene. Western blot analysis revealed that NBL1 protein was highly expressed in both cell lysate and culture media of the DU145 PCa cell line. Immunohistochemical analysis showed that NBL1 expression was highly detected in and restricted to NP and PCa and was significantly down-regulated in PCa. NBL1 expression was significantly reduced according to the tumor stage, Gleason grade and preoperative prostate-specific antigen (PSA) value. Conclusion: NBL1 is a secreted protein that is highly restricted to the prostate. Underexpression of NBL1 correlated with PCa progression. NBL1 might be a candidate tumor marker for PCa in addition to PSA.     

Biomarker Discovery in Human Prostate Cancer: an Update in Metabolomics Studies

Prostate cancer (PCa) is the most frequently diagnosed cancer and the second leading cause of cancer death among men in Western countries. Current screening techniques are based on the measurement of serum prostate specific antigen (PSA) levels and digital rectal examination. A decisive diagnosis of PCa is based on prostate biopsies; however, this approach can lead to false-positive and false-negative results. Therefore, it is important to discover new biomarkers for the diagnosis of PCa, preferably noninvasive ones. Metabolomics is an approach that allows the analysis of the entire metabolic profile of a biological system. As neoplastic cells have a unique metabolic phenotype related to cancer development and progression, the identification of dysfunctional metabolic pathways using metabolomics can be used to discover cancer biomarkers and therapeutic targets. In this study, we review several metabolomics studies performed in prostatic fluid, blood plasma/serum, urine, tissues and immortalized cultured cell lines with the objective of discovering alterations in the metabolic phenotype of PCa and thus discovering new biomarkers for the diagnosis of PCa. Encouraging results using metabolomics have been reported for PCa, with sarcosine being one of the most promising biomarkers identified to date. However, the use of sarcosine as a PCa biomarker in the clinic remains a controversial issue within the scientific community. Beyond sarcosine, other metabolites are considered to be biomarkers for PCa, but they still need clinical validation. Despite the lack of metabolomics biomarkers reaching clinical practice, metabolomics proved to be a powerful tool in the discovery of new biomarkers for PCa detection.     

Diagnostic and prognostic potential of the proteomic profiling of serum-derived extracellular vesicles in prostate cancer

Extracellular vesicles (EVs) and their cargo represent an intriguing source of cancer biomarkers for developing robust and sensitive molecular tests by liquid biopsy. Prostate cancer (PCa) is still one of the most frequent and deadly tumor in men and analysis of EVs from biological fluids of PCa patients has proven the feasibility and the unprecedented potential of such an approach. Here, we exploited an antibody-based proteomic technology, i.e. the Reverse-Phase Protein microArrays (RPPA), to measure key antigens and activated signaling in EVs isolated from sera of PCa patients. Notably, we found tumor-specific protein profiles associated with clinical settings as well as candidate markers for EV-based tumor diagnosis. Among others, PD-L1, ERG, Integrin-β5, Survivin, TGF-β, phosphorylated-TSC2 as well as partners of the MAP-kinase and mTOR pathways emerged as differentially expressed endpoints in tumor-derived EVs. In addition, the retrospective analysis of EVs from a 15-year follow-up cohort generated a protein signature with prognostic significance. Our results confirm that serum-derived EV cargo may be exploited to improve the current diagnostic procedures while providing potential prognostic and predictive information. The approach proposed here has been already applied to tumor entities other than PCa, thus proving its value in translational medicine and paving the way to innovative, clinically meaningful tools.Subject terms: Tumour biomarkers, Protein-protein interaction networks     

Identification of clinically relevant protein targets in prostate cancer with 2D-DIGE coupled mass spectrometry and systems biology network platform

Prostate cancer (PCa) is the most common type of cancer found in men and among the leading causes of cancer death in the western world. In the present study, we compared the individual protein expression patterns from histologically characterized PCa and the surrounding benign tissue obtained by manual micro dissection using highly sensitive two-dimensional differential gel electrophoresis (2D-DIGE) coupled with mass spectrometry. Proteomic data revealed 118 protein spots to be differentially expressed in cancer (n = 24) compared to benign (n = 21) prostate tissue. These spots were analysed by MALDI-TOF-MS/MS and 79 different proteins were identified. Using principal component analysis we could clearly separate tumor and normal tissue and two distinct tumor groups based on the protein expression pattern. By using a systems biology approach, we could map many of these proteins both into major pathways involved in PCa progression as well as into a group of potential diagnostic and/or prognostic markers. Due to complexity of the highly interconnected shortest pathway network, the functional sub networks revealed some of the potential candidate biomarker proteins for further validation. By using a systems biology approach, our study revealed novel proteins and molecular networks with altered expression in PCa. Further functional validation of individual proteins is ongoing and might provide new insights in PCa progression potentially leading to the design of novel diagnostic and therapeutic strategies.     

Different techniques for urinary protein analysis of normal and lung cancer patients

Many components in urine are useful in clinical diagnosis and urinary proteins are known as important components to define many diseases such as proteinuria, kidney, bladder and urinary tract diseases. In this study, we focused on the comparison of different sample preparation methods for isolating urinary proteins prior to protein analysis of pooled healthy and lung cancer patient samples. Selective method was used for preliminary investigation of some putative urinary protein markers. Urine samples were passed first through a gel filtration column (PD-10 desalting column) to remove high salts and subsequently concentrated. Remaining interferences were removed by ultrafiltration or four precipitation methods. The analysis of urinary proteins by high-performance liquid chromatography and sodium dodecyl sulfate-polyacrylamide gel electrophoresis showed many similarities in profiles among preparation methods and a few profiles were different between normal and lung cancer patients. In contrast, the results of two-dimensional gel electrophoresis (2-DE) showed more distinctly different protein patterns. Our finding showed that the sequential preparation of urinary proteins by gel filtration and ultrafiltration could retain most urinary proteins which demonstrated the highest protein spots on 2-D gels and able to identify preliminary urinary protein markers related to cancer. Although sequential preparation of urine samples by gel filtration and protein precipitation resulted in low amounts of proteins on 2-D gels, high Mr proteins were easily detected. Therefore, there are alternative choices for urine sample preparation for studying the urinary proteome and identifying urinary protein markers important for further preclinical diagnostic and therapeutic applications.     

A web-based tool for in silico biomarker discovery based on tissue-specific protein profiles in normal and cancer tissues

Here we report the development of a publicly available Web-based analysis tool for exploring proteins expressed in a tissue- or cancer-specific manner. The search queries are based on the human tissue profiles in normal and cancer cells in the Human Protein Atlas portal and rely on the individual annotation performed by pathologists of images representing immunohistochemically stained tissue sections. Approximately 1.8 million images representing more than 3000 antibodies directed toward human proteins were used in the study. The search tool allows for the systematic exploration of the protein atlas to discover potential protein biomarkers. Such biomarkers include tissue-specific markers, cell type-specific markers, tumor type-specific markers, markers of malignancy, and prognostic or predictive markers of cancers. Here we show examples of database queries to generate sets of candidate biomarker proteins for several of these different categories. Expression profiles of candidate proteins can then subsequently be validated by examination of the underlying high resolution images. The present study shows examples of search strategies revealing several potential protein biomarkers, including proteins specifically expressed in normal cells and in cancer cells from specified tumor types. The lists of candidate proteins can be used as a starting point for further validation in larger patient cohorts using both immunological approaches and technologies utilizing more classical proteomics tools.     

Diagnosis and prognosis potential of four gene promoter hypermethylation in prostate cancer

The current prostate special antigen (PSA) test causes the overtreatment of indolent prostate cancer (PCa). It also increases the risk of delayed treatment of aggressive PCa. DNA methylation aberrations are important events for gene expression dysregulation during tumorigenesis and have been suggested as novel candidate biomarkers for PCa. This may improve the diagnosis and prognosis of PCa. This study assessed the differential methylation and messenger RNA (mRNA) expression between normal and PCa samples. Correlation between promoter methylation and mRNA expression was estimated using Pearson's correlation coefficients. Moreover, the diagnostic potential of candidate methylation markers was estimated by the receiver operating characteristic (ROC) curve using continuous beta values. Survival and Cox analysis was performed to evaluate the prognostic potential of the candidate methylation markers. A total of 359 hypermethylated sites 3435 hypomethylation sites, 483 upregulated genes, and 1341 downregulated genes were identified from The Cancer Genome Atlas database. Furthermore, 17 hypermethylated sites (covering 13 genes), including known genes associated with hypermethylation in PCa (e.g., AOX1 and C1orf114), showed high discrimination between adjacent normal tissues and PCa samples with the area under the ROC curve from 0.88 to 0.94. Notably, ANXA2, FGFR2, HAAO, and KCNE3 were identified as valuable prognostic markers of PCa through the Kaplan–Meier analysis. Using gene methylation as a continuous variable, four promoter hypermethylation was significantly associated with disease-free survival in univariate Cox regression and multivariate Cox regression. This study identified four novel diagnostic and prognostic markers for PCa. The markers provide important strategies for improving the timely diagnosis and prognosis of PCa.     

Bioinformatics analysis of the genes involved in the extension of prostate cancer to adjacent lymph nodes by supervised and unsupervised machine learning methods: The role of SPAG1 and PLEKHF2

The present study aimed to identify the genes associated with the involvement of adjunct lymph nodes of patients with prostate cancer (PCa) and to provide valuable information for the identification of potential diagnostic biomarkers and pathological genes in PCa metastasis. The most important candidate genes were identified through several machine learning approaches including K-means clustering, neural network, Naïve Bayesian classifications and PCA with or without downsampling.In total, 21 genes associated with lymph nodes involvement were identified. Among them, nine genes have been identified in metastatic prostate cancer, six have been found in the other metastatic cancers and four in other local cancers. The amplification of the candidate genes was evaluated in the other PCa datasets. Besides, we identified a validated set of genes involved in the PCa metastasis. The amplification of SPAG1 and PLEKHF2 genes were associated with decreased survival in patients with PCa.     

Search for potential markers for prostate cancer diagnosis, prognosis and treatment in clinical tissue specimens using amine-specific isobaric tagging (iTRAQ) with two-dimensional liquid chromatography and tandem mass spectrometry

This study aimed to identify candidate new diagnosis and prognosis markers and medicinal targets of prostate cancer (PCa), using state of the art proteomics. A total of 20 prostate tissue specimens from 10 patients with benign prostatic hyperplasia (BPH) and 10 with PCa (Tumour Node Metastasis [TNM] stage T1-T3) were analyzed by isobaric stable isotope labeling (iTRAQ) and two-dimensional liquid chromatography-tandem mass spectrometry (2DLC-MS/MS) approaches using a hybrid quadrupole time-of-flight system (QqTOF). The study resulted in the reproducible identification of 825 nonredundant gene products (p < or = 0.05) of which 30 exhibited up-regulation (> or =2-fold) and another 35 exhibited down-regulation (< or =0.5-fold) between the BPH and PCa specimens constituting a major contribution toward their global proteomic assessment. Selected findings were confirmed by immunohistochemical analysis of prostate tissue specimens. The proteins determined support existing knowledge and uncover novel and promising PCa biomarkers. The PCa proteome found can serve as a useful aid for the identification of improved diagnostic and prognostic markers and ultimately novel chemopreventive and therapeutic targets.     

Aberrant DNA methylation and prostate cancer

Prostate cancer (PCa) is the most prevalent cancer, a significant contributor to morbidity and a leading cause of cancer-related death in men in Western industrialized countries. In contrast to genetic changes that vary among individual cases, somatic epigenetic alterations are early and highly consistent events. Epigenetics encompasses several different phenomena, such as DNA methylation, histone modifications, RNA interference, and genomic imprinting. Epigenetic processes regulate gene expression and can change malignancy-associated phenotypes such as growth, migration, invasion, or angiogenesis. Methylations of certain genes are associated with PCa progression. Compared to normal prostate tissues, several hypermethylated genes have also been identified in benign prostate hyperplasia, which suggests a role for aberrant methylation in this growth dysfunction. Global and gene-specific DNA methylation could be affected by environmental and dietary factors. Among other epigenetic changes, aberrant DNA methylation might have a great potential as diagnostic or prognostic marker for PCa and could be tested in tumor tissues and various body fluids (e.g., serum, urine). The DNA methylation markers are simple in nature, have high sensitivity, and could be detected either quantitatively or qualitatively. Availability of genome-wide screening methodologies also allows the identification of epigenetic signatures in high throughput population studies. Unlike irreversible genetic changes, epigenetic alterations are reversible and could be used for PCa targeted therapies.     

The C-Terminal Fragment of Prostate-Specific Antigen,a 2331 Da Peptide,as a New Urinary Pathognomonic Biomarker Candidate for Diagnosing Prostate Cancer

Background and Objectives

Prostate cancer (PCa) is one of the most common cancers and leading cause of cancer-related deaths in men. Mass screening has been carried out since the 1990s using prostate-specific antigen (PSA) levels in the serum as a PCa biomarker. However, although PSA is an excellent organ-specific marker, it is not a cancer-specific marker. Therefore, the aim of this study was to discover new biomarkers for the diagnosis of PCa.

Materials and Methods

We focused on urine samples voided following prostate massage (digital rectal examination [DRE]) and conducted a peptidomic analysis of these samples using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF/MSⁿ). Urinary biomaterials were concentrated and desalted using CM-Sepharose prior to the following analyses being performed by MALDI-TOF/MSⁿ: 1) differential analyses of mass spectra; 2) determination of amino acid sequences; and 3) quantitative analyses using a stable isotope-labeled internal standard.

Results

Multivariate analysis of the MALDI-TOF/MS mass spectra of urinary extracts revealed a 2331 Da peptide in urine samples following DRE. This peptide was identified as a C-terminal PSA fragment composed of 19 amino acid residues. Moreover, quantitative analysis of the relationship between isotope-labeled synthetic and intact peptides using MALDI-TOF/MS revealed that this peptide may be a new pathognomonic biomarker candidate that can differentiate PCa patients from non-cancer subjects.

Conclusion

The results of the present study indicate that the 2331 Da peptide fragment of PSA may become a new pathognomonic biomarker for the diagnosis of PCa. A further large-scale investigation is currently underway to assess the possibility of using this peptide in the early detection of PCa.     

Steroidogenic enzymes and stem cell markers are upregulated during androgen deprivation in prostate cancer

Considerable levels of testosterone and dihydrotestosterone (DHT) are found in prostate cancer (PCa) tissue after androgen deprivation therapy. Treatment of surviving cancer-initiating cells and the ability to metabolize steroids from precursors may be the keystones for the appearance of recurrent tumors. To study this hypothesis, we assessed the expression of several steroidogenic enzymes and stem cell markers in clinical PCa samples and cell cultures during androgen depletion. Gene expression profiles were determined by microarray or qRT-PCR. In addition, we measured cell viability and analyzed stem cell marker expression in DuCaP cells by immunocytochemistry. Seventy patient samples from different stages of PCa, and the PCa cell line DuCaP were included in this study. The androgen receptor (AR) and enzymes (AKR1C3, HSD17B2, HSD17B3, UGT2B15 and UGT2B17 ) that are involved in the metabolism of adrenal steroids were upregulated in castration resistant prostate cancer (CRPC). In vitro, some DuCaP cells survived androgen depletion, and eventually gave rise to a culture adapted to these conditions. During and after this transition, most of the steroidogenic enzymes were upregulated. These cells also are enriched with stem/progenitor cell markers cytokeratin 5 (CK5) and ATP-binding cassette sub-family G member 2 (ABCG2). Similarly, putative stem/progenitor cell markers CK5, c-Kit, nestin, CD44, c-met, ALDH1A1, α2-integrin, CD133, ABCG2, CXCR4 and POU5F1 were upregulated in clinical CRPC. The upregulation of steroidogenic enzymes and stem cell markers in recurrent tumors suggests that cancer initiating cells can expand by adaptation to their T/DHT deprived environment. Therapies targeting the metabolism of adrenal steroids by the tumor may prove effective in preventing tumor regrowth.     

Prostate cancer susceptibility Loci identified on chromosome 12 in African Americans

Prostate cancer (PCa) is a complex disease that disproportionately affects African Americans and other individuals of African descent. A number of regions across the genome have been associated to PCa, most of them with moderate effects. A few studies have reported chromosomal changes on 12p and 12q that occur during the onset and development of PCa but to date no consistent association of the disease with chromosome 12 polymorphic variation has been identified. In order to unravel genetic risk factors that underlie PCa health disparities we investigated chromosome 12 using ancestry informative markers (AIMs), which allow us to distinguish genomic regions of European or West African origin, and tested them for association with PCa. Additional SNPs were genotyped in those areas where significant signals of association were detected. The strongest signal was discovered at the SNP rs12827748, located upstream of the PAWR gene, a tumor suppressor, which is amply expressed in the prostate. The most frequent allele in Europeans was the risk allele among African Americans. We also examined vitamin D related genes, VDR and CYP27B1, and found a significant association of PCa with the TaqI polymorphism (rs731236) in the former. Although our results warrant further investigation we have uncovered a genetic susceptibility factor for PCa in a likely candidate by means of an approach that takes advantage of the differential contribution of parental groups to an admixed population.     

Differentially expressed glycoproteins in pre- and post-digital rectal examination urine samples for detecting aggressive prostate cancer

Urinary glycoproteins associated with aggressive prostate cancer (AG-PCa) were previously reported using post-digital rectal examination (DRE) urine specimens. To explore the potential of using pre-DRE urine specimens for detecting AG-PCa, we compared glycoproteins between pre- and post-DRE urine specimens, verified the previously identified post-DRE AG-PCa-associated urinary glycoproteins in pre-DRE urine specimens, and explored potential new glycoproteins for AG-PCa detection in pre-DRE urine specimens. Quantitative glycoproteomic data were acquired for 154 pre-DRE urine specimens from 41 patients with no cancer at biopsy, 48 patients with non-AG-PCa (Gleason score = 6), and 65 patients with AG-PCa (Gleason score 7 or above). Compared to glycopeptides from the post-DRE urine data, humoral immunity-related proteins were enriched in pre-DRE urine samples, whereas cell mediated immune response proteins were enriched in post-DRE urine samples. Analyses of AG-PCa-associated glycoproteins from pre-DRE urine revealed that the three urinary glycoproteins, prostate-specific antigen (PSA), prostatic acid phosphatase (ACPP), and CD97 antigen (CD97) that were previously identified in post-DRE urine samples, were also observed as AG-PCa associated glycoproteins in pre-DRE urine. In addition, we identified three new glycoproteins, fibrillin 1 (FBN1), vitronectin (VTN), and hemicentin 2 (HMCN2), to be potentially associated with AG-PCa in pre-DRE urine specimens. In summary, glycoprotein profiles differ between pre- and post-DRE urine specimens. The identified AG-PCa-associated glycoproteins may be further evaluated in large cohort of pre-DRE urine specimens for detecting clinically significant PCa.     

Association of <Emphasis Type="Italic">HSP70-hom</Emphasis> genetic variant with prostate cancer risk

Because of the importance of androgens to prostate cancer (PCa) development, several candidate genes along androgen pathway have been under intensive study. Given the role of the molecular chaperone HSP70 in the regulation of the androgen receptor (AR) transactivation function, we first chose to explore the association between the HSP70-hom functional genetic variant (+2437 T > C) and prostate cancer risk by genotyping DNA samples from 101 unselected PCa patients and 105 healthy men. There was a trend towards lower frequency of TC and CC genotypes among patients when compared with healthy controls, however the difference did not reach the statistical significance (TC genotype: OR = 0.53, P = 0.05; CC genotype: OR = 0.42, P = 0.16). Moreover, individuals carrying at least one C allele have a statistically significant lower susceptibility for PCa (OR = 0.51 (0.26-0.97); P = 0.02). Since some factors may influence tumor progression rather than initiation, we also examined the relationship between the HSP70-hom polymorphism and the clinical characteristics of the malignancy at the time of diagnosis. The stratified analysis of the genotypes with the clinical stage and tumor grade showed that there was no significant difference in the risk estimates according to prognostic indicators of PCa disease in our population study. This is the first report on the studies of HSP70 SNPs in PCa and our data suggest that this genetic variant may be a genetic marker for PCa susceptibility in Tunisians.