Identification of novel serological tumor markers for human prostate cancer using integrative transcriptome and proteome analysis

Identification of Molecular Markers Associated with Prostate Cancer Subtypes: An Integrative Bioinformatics Approach

Prostate cancer (PCa) is characterised by androgen dependency. Unfortunately, under anti-androgen treatment pressure, castration-resistant prostate cancer (CRPC) emerges, characterised by heterogeneous cell populations that, over time, lead to the development of different androgen-dependent or -independent phenotypes. Despite important advances in therapeutic strategies, CRPC remains incurable. Context-specific essential genes represent valuable candidates for targeted anti-cancer therapies. Through the investigation of gene and protein annotations and the integration of published transcriptomic data, we identified two consensus lists to stratify PCa patients' risk and discriminate CRPC phenotypes based on androgen receptor activity. ROC and Kaplan-Meier survival analyses were used for gene set validation in independent datasets. We further evaluated these genes for their association with cancer dependency. The deregulated expression of the PCa-related genes was associated with overall and disease-specific survival, metastasis and/or high recurrence risk, while the CRPC-related genes clearly discriminated between adeno and neuroendocrine phenotypes. Some of the genes showed context-specific essentiality. We further identified candidate drugs through a computational repositioning approach for targeting these genes and treating lethal variants of PCa. This work provides a proof-of-concept for the use of an integrative approach to identify candidate biomarkers involved in PCa progression and CRPC pathogenesis within the goal of precision medicine.

Gene-Transcript Expression in Urine Supernatant and Urine Cell-Sediment Are Different but Equally Useful for Detecting Prostate Cancer

There is considerable interest in urine as a non-invasive liquid biopsy to detect prostate cancer (PCa). PCa-specific transcripts such as the TMPRSS2:ERG fusion gene can be found in both urine extracellular vesicles (EVs) and urine cell-sediment (Cell) but the relative usefulness of these and other genes in each fraction in PCa detection has not been fully elucidated. Urine samples from 76 men (PCa n = 40, non-cancer n = 36) were analysed by NanoString for 154 PCa-associated genes-probes, 11 tissue-specific, and six housekeeping. Comparison to qRT-PCR data for four genes (PCA3, OR51E2, FOLH1, and RPLP2) was strong (r = 0.51-0.95, Spearman p < 0.00001). Comparing EV to Cells, differential gene expression analysis found 57 gene-probes significantly more highly expressed in 100 ng of amplified cDNA products from the EV fraction, and 26 in Cells (p < 0.05; edgeR). Expression levels of prostate-specific genes (KLK2, KLK3) measured were ~20× higher in EVs, while PTPRC (white-blood Cells) was ~1000× higher in Cells. Boruta analysis identified 11 gene-probes as useful in detecting PCa: two were useful in both fractions (PCA3, HOXC6), five in EVs alone (GJB1, RPS10, TMPRSS2:ERG, ERG_Exons_4-5, HPN) and four from Cell (ERG_Exons_6-7, OR51E2, SPINK1, IMPDH2), suggesting that it is beneficial to fractionate whole urine prior to analysis. The five housekeeping genes were not significantly differentially expressed between PCa and non-cancer samples. Expression signatures from Cell, EV and combined data did not show evidence for one fraction providing superior information over the other.

Potential Role of Seven Proteomics Tissue Biomarkers for Diagnosis and Prognosis of Prostate Cancer in Urine

As the currently available tests for the clinical management of prostate cancer (PCa) are still far from providing precise diagnosis and risk stratification, the identification of new molecular marker(s) remains a pertinent clinical need. Candidate PCa biomarkers from the published proteomic comparative studies of prostate tissue (2002-2020) were collected and systematically evaluated. AZGP1, MDH2, FABP5, ENO1, GSTP1, GSTM2, and EZR were chosen for further evaluation in the urine of 85 PCa patients and controls using ELISA. Statistically significant differences in protein levels between PCa and BPH showed FABP5 (p = 0.019) and ENO1 (p = 0.015). A biomarker panel based on the combination of FABP5, ENO1, and PSA provided the highest accuracy (AUC = 0.795) for PCa detection. The combination of FABP5, EZR, AZGP1, and MDH2 showed AUC = 0.889 in PCa prognosis, with 85.29% of the samples correctly classified into low and high Gleason score (GS) groups. The addition of PSA to the panel slightly increased the AUC to 0.914. AZGP1, FABP5, and EZR showed significant correlation with GS, stage, and percentage of positive biopsy cores. Although validation using larger patient cohorts will be necessary to establish the credibility of the proposed biomarker panels in a clinical context, this study opens a way for the further testing of more high-quality proteomics biomarkers, which could ultimately add value to the clinical management of PCa.

Characterization of Proteins Regulated by Androgen and Protein Kinase a Signaling in VCaP Prostate Cancer Cells

Androgen signaling via the androgen receptor (AR) is involved in normal prostate development and prostate cancer progression. In addition to androgen binding, a variety of protein kinases, including cyclic AMP-dependent protein kinase A (PKA), can activate the AR. Although hormone deprivation, especially that of androgen, continues to be an important strategy for treating prostate cancer patients, the disease ultimately progresses to castration-resistant prostate cancer (CRPC), despite a continuous hormone-deprived environment. To date, it remains unclear which pathways in this progression are active and targetable. Here, we performed a proteomic analysis of VCaP cells stimulated with androgen or forskolin to identify proteins specific for androgen-induced and androgen-bypassing signaling, respectively. Patterns of differentially expressed proteins were quantified, and eight proteins showing significant changes in expression were identified. Functional information, including a Gene Ontology analysis, revealed that most of these proteins are involved in metabolic processes and are associated with cancer. The mRNA and protein expression of selected proteins was validated, and functional correlations of identified proteins with signaling in VCaP cells were assessed by measuring metabolites related to each enzyme. These analyses offered new clues regarding effector molecules involved in prostate cancer development, insights that are supported by the demonstration of increased expression levels of the eight identified proteins in prostate cancer patients and assessments of the progression-free interval. Taken together, our findings show that aberrant levels of eight proteins reflect molecular changes that are significantly regulated by androgen and/or PKA signaling pathways, suggesting possible molecular mechanisms of CRPC.

Circular RNA hsa_circ_0102231 sponges miR-145 to promote non-small cell lung cancer cell proliferation by up-regulating the expression of RBBP4

Circular RNAs (circRNAs) are important regulators in various cancers. Previous studies have found that hsa_circ_0102231 is an oncogene in lung adenocarcinoma. Here, we investigated its mechanism in the development of non-small cell lung cancer (NSCLC). We detected the levels of hsa_circ_0102231 in five NSCLC cell lines and one normal bronchial epithelium cell line. The interaction between hsa_circ_0102231 and miR-145 was predicted and confirmed by pull-down and luciferase assays. The nuclear mass separation assay and fluorescence in situ hybridization were used to detect the distribution of hsa_circ_0102231. Cell Counting Kit-8 and Transwell assays were used to assess the cell proliferative and invasive ability. Western blot and RT-qPCR, respectively, detected the protein and mRNA levels of RBBP4. The RBBP4 promoter activity was detected with a luciferase assay. We found that hsa_circ_0102231 level was higher in NSCLC cells. hsa_circ_0102231 is mainly localized to the cytoplasm. hsa_circ_0102231 promotes NSCLC cell proliferation and invasion by sponge for miR-145. miR-145 significantly decreases the RBBP4 promoter activity, and its mRNA and protein levels. RBBP4 is an oncogene to promote proliferation and invasion ability. Our findings suggest that hsa_circ_0102231 promotes proliferation and invasion by mediating the miR-145/RBBP4 axis in NSCLC, indicating that it might be a potential target for NSCLC treatment.

A Proteomics- and Metabolomics-Based Study Revealed That Disorder of Palmitic Acid Metabolism by Aconitine Induces Cardiac Injury

Currently, research on cardiac injury by aconitine focuses on its effect to directly interfere with the function of cardiac ion channels. Further, abnormal lipid metabolism could cause cardiac injury via inflammatory signaling pathway. In our preliminary study, we discovered that aconitine could alter the metabolism processes of various substances, including palmitic acid. Inspired by these studies, we investigated how elevation of palmitic acid by aconitine causes cardiac injury. Aconitine induced cardiac injury in rats (0.32 mg/kg, d = 7), and the cardiac injury was confirmed by electrocardiogram and serum biochemical study. The proteomic and metabolomic results showed that the palmitic acid level increases in heart tissue, and the NOD-like receptor (NLR) signaling pathway showed a strong effect of cardiac injury. The palmitic acid results in cell viability decline and activates NLR signaling in vitro. The shRNA-mediated knockdown of NLRP3 and NOD1/2 attenuates palmitic acid-induced inhibitory effect on cells and inhibited activation of the NLR signaling pathway. Collectively, this study reveals that aconitine provoked palmitic acid elevation could aggravate cardiac injury via the NLR signaling pathway. This study suggests that drug triggered disorder of the metabolism process could evoke cardiac injury and could propose a new strategy to study drug cardiac injury.

ARNT-dependent CCR8 reprogrammed LDH isoform expression correlates with poor clinical outcomes of prostate cancer

Lactate dehydrogenase isozyme (LDH) is a tetramer constituted of two isoforms, LDHA and LDHB, the expression of which is associated with cell metabolism and cancer progression. Our previous study reveals that CC-chemokine ligand-18 (CCL18) is involved in progression of prostate cancer (PCa).This study aims to investigate how CCL18 regulates LDH isoform expression, and therefore, contributes to PCa progression. The data revealed that the expression of LDHA was upregulated and LDHB was downregulated in PCa cells by CCL18 at both messenger RNA and protein levels. The depletion of CCR8 reduced the ability of CCL18 to promote the proliferation, migration, and lactate production of PCa cells. Depletion of a CCR8 regulated transcription factor, ARNT, significantly reduced the expression of LDHA. In addition, The Cancer Genome Atlas dataset analyses revealed a positive correlation between CCR8 and ARNT expression. Two dimension difference gel electrophoresis revealed that the LDHA/LDHB ratio was increased in the prostatic fluid of patients with PCa and PCa tissues. Furthermore, increased LDHA/LDHB ratio was associated with poor clinical outcomes of patients with PCa. Together, our results indicate that the CCR8 pathway programs LDH isoform expression in an ARNT dependent manner and that the ratio of LDHA/LDHB has the potential to serve as biomarkers for PCa diagnosis and prognosis.

The expression and prognostic role of IMPDH2 in ovarian cancer

OBJECT

Inosine 5'-monophosphate dehydrogenase type II (IMPDH2), as an oncogene, is reported to be involved in tumor formation and progression. However, the role of IMPDH2 in ovarian cancer remains unclear. Present study is aimed to investigate the expression and clinical significance of IMPDH2 in ovarian cancer.

METHODS

The mRNA and protein levels of IMPDH2 were measured in 126 ovarian cancer and matched adjacent normal tissues by quantificational real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC), respectively. Then, the association of IMPDH2 with clinicalpathological characters and prognosis was further evaluated.

RESULTS

Significant higher mRNA levels of IMPDH2 were observed in ovarian cancer compared with those in normal tissues (P < 0.001). IHC results shown the high-expression rate of IMPDH2 in ovarian cancer was 56.3%, which was obviously higher compared with that in normal tissues (23.8%, P < 0.0001). Moreover, IMPDH2 high-expression significantly correlated with tumor types and Federation International of Gynecology and Obstetrigue (FIGO) stages in ovarian cancer (P < 0.05). IMPDH2 overexpression predicted poorer prognosis and could serve as an independent prognostic factor.

CONCLUSIONS

IMPDH2 is highly expressed in ovarian cancer and correlates with prognosis, which may serve as a potential prognostic biomarker.

Integrative analysis of genetic and epigenetic profiling of lung squamous cell carcinoma (LSCC) patients to identify smoking level relevant biomarkers

Background

Incidence and mortality of lung cancer have dramatically decreased during the last decades, yet still approximately 160,000 deaths per year occurred in United States. Smoking intensity, duration, starting age, as well as environmental cofactors including air-pollution, showed strong association with major types of lung cancer. Lung squamous cell carcinoma is a subtype of non-small cell lung cancer, which represents 25% of the cases. Thus, exploring the molecular pathogenic mechanisms of lung squamous cell carcinoma plays crucial roles in lung cancer clinical diagnosis and therapy.

Results

In this study, we performed integrative analyses on 299 comparative datasets of RNA-seq and methylation data, collected from 513 lung squamous cell carcinoma cases in The Cancer Genome Atlas. The data were divided into high and low smoking groups based on smoking intensity (Numbers of packs per year). We identified 1002 significantly up-regulated genes and 534 significantly down-regulated genes, and explored their cellular functions and signaling pathways by bioconductor packages GOseq and KEGG. Global methylation status was analyzed and visualized in circular plot by CIRCOS. RNA-and methylation data were correlatively analyzed, and 24 unique genes were identified, for further investigation of regional CpG sites' interactive patterns by bioconductor package coMET. AIRE, PENK, and SLC6A3 were the top 3 genes in the high and low smoking groups with significant differences.

Conclusions

Gene functions and DNA methylation patterns of these 24 genes are important and useful in disclosing the differences of gene expression and methylation profiling caused by different smoking levels.

Inosine monophosphate dehydrogenase 2 as a marker of aggressive and advanced prostate cancer

Introduction

There is a need for a new biochemical marker of aggressive prostate cancer (PCa). Inosine monophosphate dehydrogenase 2 (IMPDH2) is a candidate for such a marker – its activity is increased in certain tumors and neoplastic cell lines, including PCa, and may correlate with cancer aggressiveness.

Material and methods

IMPDH2 levels were measured in blood samples from 34 PCa patients. The results were analyzed and correlated with prostate-specific antigen (PSA), digital rectal examination (DRE), Gleason score, risk groups according to d'Amico and metastatic disease. Twenty healthy (non-PCa) patients served as the control group.

Results

There was no significant difference in IMPDH2 level between the PCa and control group, and no significant correlation between PSA and IMPDH2. IMPDH2 levels were significantly higher in the DRE (+) patients (148.5 ±174.8 vs. 33.4 ±46.4, p <0.05), in patients with metastatic disease (100.1 ±139.0 vs. 25.3 ±25.9, p <0.05) and in the high-risk group according to d'Amico (93.4 ±129.2 vs. 18.8 ±10.4, p <0.05). There was a significant correlation between the Gleason score and IMPDH2.

Conclusions

These results suggest that IMPDH2 is a promising candidate as a biomarker for those with advanced PCa and those at high risk of progression towards advanced PCa.

Promise and Implementation of Proteomic Prostate Cancer Biomarkers

Prostate cancer is one of the most commonly diagnosed malignancy and the fifth leading cause of cancer mortality in men. Despite the broad use of prostate-specific antigen test that resulted in an increase in number of diagnosed cases, disease management needs to be improved. Proteomic biomarkers alone and or in combination with clinical and pathological risk calculators are expected to improve on decreasing the unnecessary biopsies, stratify low risk patients, and predict response to treatment. To this end, significant efforts have been undertaken to identify novel biomarkers that can accurately discriminate between indolent and aggressive cancer forms and indicate those men at high risk for developing prostate cancer that require immediate treatment. In the era of “big data” and “personalized medicine” proteomics-based biomarkers hold great promise to provide clinically applicable tools, as proteins regulate all biological functions, and integrate genomic information with the environmental impact. In this review article, we aim to provide a critical assessment of the current proteomics-based biomarkers for prostate cancer and their actual clinical applicability. For that purpose, a systematic review of the literature published within the last 10 years was performed using the Web of Science Database. We specifically discuss the potential and prospects of use for diagnostic, prognostic and predictive proteomics-based biomarkers, including both body fluid- and tissue-based markers.

Genome-Wide Identification and Characterization of Long Non-Coding RNA in Wheat Roots in Response to Ca2+ Channel Blocker

It remains unclear whether plant lncRNAs are responsive to Ca²⁺-channel blocking. When using the Ca²⁺-channel blocker, LaCl₃, to treat germinated wheat seeds for 24 h, we found that both root length and mitosis were inhibited in the LaCl₃-treated groups. The effect of the Ca²⁺-channel blocker was verified in three ways: a [Ca²⁺]_cyt decrease detected using Fluo-3/AM staining, a decrease in the Ca content measured using inductively coupled plasma mass spectrometry, and an inhibition of Ca²⁺ influx detected using Non-invasive Micro-test Technology. Genome-wide high throughput RNA-seq and bioinformatical methods were used to identify lncRNAs, and found 177 differentially expressed lncRNAs that might be in responsive to Ca²⁺-channel blocking. Among these, 108 were up-regulated and 69 were down-regulated. The validity of identified lncRNAs data from RNA-seq was verified using qPCR. GO and KEGG analysis indicated that a number of lncRNAs might be involved in diverse biological processes upon Ca²⁺-channel blocking. Further GO analysis showed that 23 lncRNAs might play roles as transcription factor (TF); Moreover, eight lncRNAs might participate in cell cycle regulation, and their relative expressions were detected using qPCR. This study also provides diverse data on wheat lncRNAs that can deepen our understanding of the function and regulatory mechanism of Ca²⁺-channel blocking in plants.

Quantitative Mass Spectrometry-Based Proteomic Profiling for Precision Medicine in Prostate Cancer

Prostate cancer (PCa) is one of the most frequently diagnosed cancer among men in the western societies. Many PCa patients bear tumors that will not threat their lives if left untreated or if treatment is delayed. Our inability for early identification of these patients has resulted in massive overtreatment. Therefore, there is a great need of finding biomarkers for patient stratification according to prognostic risk; as well as there is a need for novel targets that can allow the development of effective treatments for patients that progress to castration-resistant PCa. Most biomarkers in cancer are proteins, including the widely-used prostate-specific antigen (PSA). Recent developments in mass spectrometry allow the identification and quantification of thousands of proteins and posttranslational modifications from small amounts of biological material, including formalin-fixed paraffin-embedded tissues, and biological fluids. Novel diagnostic and prognostic biomarkers have been identified in tissue, blood, urine, and seminal plasma of PCa patients, and new insights in the ethology and progression of this disease have been achieved using this technology. In this review, we summarize these findings and discuss the potential of this technology to pave the way toward the clinical implementation of precision medicine in PCa.

HnRNP-L promotes prostate cancer progression by enhancing cell cycling and inhibiting apoptosis

Expression of the RNA-binding protein HnRNP-L was previously shown to associate with tumorigenesis in liver and lung cancer. In this study, we examined the role of HnRNP-L in prostate cancer (Pca). We found that HnRNP-L is overexpressed in prostate tissue samples from 160 PC patients compared with tissue samples from 32 donors with cancers other than Pca. Moreover, HnRNP-L positively correlated with aggressive tumor characteristics. HnRNP-L knockdown inhibited cell proliferation and promoted cell apoptosis of Pca cell lines in vitro, and suppressed tumor growth when the cells were subcutaneously implanted in an athymic mouse model. Conversely, overexpression of HnRNP-L promoted cell proliferation and tumor growth while prohibiting cell apoptosis. HnRNP-L promoted cell proliferation and tumor growth in Pca in part by interacting with endogenous p53 mRNA, which was closely associated with cyclin p21. In addition, HnRNP-L affected cell apoptosis by directly binding the classical apoptosis protein BCL-2. These observations suggest HnRNP-L is an important regulatory factor that exerts pro-proliferation and anti-apoptosis effects in Pca through actions affecting the cell cycle and intrinsic apoptotic signaling. Thus HnRNP-L could potentially serve as a valuable molecular biomarker or therapeutic target in the treatment of Pca.

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.

c-Myc Antagonises the Transcriptional Activity of the Androgen Receptor in Prostate Cancer Affecting Key Gene Networks

Prostate cancer (PCa) is the most common non-cutaneous cancer in men. The androgen receptor (AR), a ligand-activated transcription factor, constitutes the main drug target for advanced cases of the disease. However, a variety of other transcription factors and signaling networks have been shown to be altered in patients and to influence AR activity. Amongst these, the oncogenic transcription factor c-Myc has been studied extensively in multiple malignancies and elevated protein levels of c-Myc are commonly observed in PCa. Its impact on AR activity, however, remains elusive. In this study, we assessed the impact of c-Myc overexpression on AR activity and transcriptional output in a PCa cell line model and validated the antagonistic effect of c-MYC on AR-targets in patient samples. We found that c-Myc overexpression partially reprogrammed AR chromatin occupancy and was associated with altered histone marks distribution, most notably H3K4me1 and H3K27me3. We found c-Myc and the AR co-occupy a substantial number of binding sites and these exhibited enhancer-like characteristics. Interestingly, c-Myc overexpression antagonised clinically relevant AR target genes. Therefore, as an example, we validated the antagonistic relationship between c-Myc and two AR target genes, KLK3 (alias PSA, prostate specific antigen), and Glycine N-Methyltransferase (GNMT), in patient samples. Our findings provide unbiased evidence that MYC overexpression deregulates the AR transcriptional program, which is thought to be a driving force in PCa.

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c-MYC and AR share one third of chromatin binding with enhancer-like features.

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c-MYC can repress the expression of a subset prostate cancer biomarkers, including PSA.

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c-MYC and AR antagonize the expression of, Glycine N-Methyltransferase (GNMT), responsible for sarcosine biosynthesis.

Prostate cancer is a heterogeneous disease. The most frequently used biomarker in clinical setting, a well described androgen receptor target gene, PSA, still performs poorly in stratifying patients at real risk of death due to the disease. Despite this, therapeutic approaches focus on suppressing androgen receptor signaling. However, this is only one of the recurrent alterations found in patients. This study focuses on c-MYC and the effects of its deregulation in advanced prostate cancer. We find that there is an inverse relationship between established biomarkers expression, including PSA. This inverse relationship could be used in clinics to select beneficial therapeutic approaches for a subset of prostate cancer cases.

Prostate cancer proteomics: Current trends and future perspectives for biomarker discovery

The clinical and fundamental research in prostate cancer - the most common urological cancer in men - is currently entering the proteomic and genomic era. The focus has switched from one single marker (PSA) to panels of biomarkers (including proteins involved in ribosomal function and heat shock proteins). Novel genetic markers (such as Transmembrane protease serine 2 (TMPRSS2)-ERG fusion gene mRNA) or prostate cancer gene 3 (PCA3) had already entered the clinical practice, raising the question whether subsequent protein changes impact the evolution of the disease and the response to treatment. Proteomic technologies such as MALDI-MS, SELDI-MS, i-TRAQ allow a qualitative/quantitative analysis of the proteome variations, in both serum and tumor tissue. A new trend in prostate cancer research is proteomic analysis of prostasomes (prostate-specific exosomes), for the discovery of new biomarkers. This paper provides an update of novel clinical tests used in research and clinical diagnostic, as well as of potential tissue or fluid biomarkers provided by extensive proteomic research data.

The Role of Proteomics in Biomarker Development for Improved Patient Diagnosis and Clinical Decision Making in Prostate Cancer

Prostate Cancer (PCa) is the second most commonly diagnosed cancer in men worldwide. Although increased expression of prostate-specific antigen (PSA) is an effective indicator for the recurrence of PCa, its intended use as a screening marker for PCa is of considerable controversy. Recent research efforts in the field of PCa biomarkers have focused on the identification of tissue and fluid-based biomarkers that would be better able to stratify those individuals diagnosed with PCa who (i) might best receive no treatment (active surveillance of the disease); (ii) would benefit from existing treatments; or (iii) those who are likely to succumb to disease recurrence and/or have aggressive disease. The growing demand for better prostate cancer biomarkers has coincided with the development of improved discovery and evaluation technologies for multiplexed measurement of proteins in bio-fluids and tissues. This review aims to (i) provide an overview of these technologies as well as describe some of the candidate PCa protein biomarkers that have been discovered using them; (ii) address some of the general limitations in the clinical evaluation and validation of protein biomarkers; and (iii) make recommendations for strategies that could be adopted to improve the successful development of protein biomarkers to deliver improvements in personalized PCa patient decision making.

Construction and analysis of protein-protein interaction networks based on proteomics data of prostate cancer

Currently, using human prostate cancer (PCa) tissue samples to conduct proteomics research has generated a large amount of data; however, only a very small amount has been thoroughly investigated. In this study, we manually carried out the mining of the full text of proteomics literature that involved comparisons between PCa and normal or benign tissue and identified 41 differentially expressed proteins verified or reported more than 2 times from different research studies. We regarded these proteins as seed proteins to construct a protein-protein interaction (PPI) network. The extended network included one giant network, which consisted of 1,264 nodes connected via 1,744 edges, and 3 small separate components. The backbone network was then constructed, which was derived from key nodes and the subnetwork consisting of the shortest path between seed proteins. Topological analyses of these networks were conducted to identify proteins essential for the genesis of PCa. Solute carrier family 2 (facilitated glucose transporter), member 4 (SLC2A4) had the highest closeness centrality located in the center of each network, and the highest betweenness centrality and largest degree in the backbone network. Tubulin, beta 2C (TUBB2C) had the largest degree in the giant network and subnetwork. In addition, using module analysis of the whole PPI network, we obtained a densely connected region. Functional annotation indicated that the Ras protein signal transduction biological process, mitogen-activated protein kinase (MAPK), neurotrophin and the gonadotropin-releasing hormone (GnRH) signaling pathway may play an important role in the genesis and development of PCa. Further investigation of the SLC2A4, TUBB2C proteins, and these biological processes and pathways may therefore provide a potential target for the diagnosis and treatment of PCa.

Myc-dependent purine biosynthesis affects nucleolar stress and therapy response in prostate cancer

The androgen receptor is a key transcription factor contributing to the development of all stages of prostate cancer (PCa). In addition, other transcription factors have been associated with poor prognosis in PCa, amongst which c-Myc (MYC) is a well-established oncogene in many other cancers. We have previously reported that the AR promotes glycolysis and anabolic metabolism; many of these metabolic pathways are also MYC-regulated in other cancers. In this study, we report that in PCa cells de novo purine biosynthesis and the subsequent conversion to XMP is tightly regulated by MYC and independent of AR activity. We characterized two enzymes, PAICS and IMPDH2, within the pathway as PCa biomarkers in tissue samples and report increased efficacy of established anti-androgens in combination with a clinically approved IMPDH inhibitor, mycophenolic acid (MPA). Treatment with MPA led to a significant reduction in cellular guanosine triphosphate (GTP) levels accompanied by nucleolar stress and p53 stabilization. In conclusion, targeting purine biosynthesis provides an opportunity to perturb PCa metabolism and enhance tumour suppressive stress responses.

Bioinformatics analysis of differentially expressed proteins in prostate cancer based on proteomics data

We mined the literature for proteomics data to examine the occurrence and metastasis of prostate cancer (PCa) through a bioinformatics analysis. We divided the differentially expressed proteins (DEPs) into two groups: the group consisting of PCa and benign tissues (P&b) and the group presenting both high and low PCa metastatic tendencies (H&L). In the P&b group, we found 320 DEPs, 20 of which were reported more than three times, and DES was the most commonly reported. Among these DEPs, the expression levels of FGG, GSN, SERPINC1, TPM1, and TUBB4B have not yet been correlated with PCa. In the H&L group, we identified 353 DEPs, 13 of which were reported more than three times. Among these DEPs, MDH2 and MYH9 have not yet been correlated with PCa metastasis. We further confirmed that DES was differentially expressed between 30 cancer and 30 benign tissues. In addition, DEPs associated with protein transport, regulation of actin cytoskeleton, and the extracellular matrix (ECM)–receptor interaction pathway were prevalent in the H&L group and have not yet been studied in detail in this context. Proteins related to homeostasis, the wound-healing response, focal adhesions, and the complement and coagulation pathways were overrepresented in both groups. Our findings suggest that the repeatedly reported DEPs in the two groups may function as potential biomarkers for detecting PCa and predicting its aggressiveness. Furthermore, the implicated biological processes and signaling pathways may help elucidate the molecular mechanisms of PCa carcinogenesis and metastasis and provide new targets for clinical treatment.

Quantitative proteomic study of human prostate cancer cells with different metastatic potentials

Metastatic dissemination is a feature of most cancers including prostate cancer (PCa), and is the main cause of treatment failure and mortality. The aim of the study is to explore the mechanisms of PCa metastasis and to search for potential prognostic markers using proteomics. Two-dimensional fluorescent differential gel electrophoresis (2D-DIGE) was used to quantify proteins in normal prostate epithelial cells, bone metastasis-derived PC-3 cells, and visceral metastasis-derived PC-3M cells. Metastatic potential was confirmed by flow cytometry, electron microscopy, proliferating cell nuclear antigen assay, and wound healing assay. Differential protein expression was compared between PCa cells with different metastatic potentials (LNcap, DU145, PC-3 and PC-3M) and normal prostate epithelial cells (RWPE-1). Selected candidate proteins in human prostate tissues were analyzed using GOA, UniProt and GeneCards analyses. Eighty-six proteins were differentially expressed between cell lines (>1.5-fold, P<0.05). Among them, twelve proteins were identified by MALDI-TOF-MS. One protein was upregulated in normal prostate epithelial cells, nine proteins were upregulated in PC-3, and two proteins were upregulated in PC-3M. Proteins were divided into five groups according to their functions. The SETDB1 protein was closely associated with the prognosis of PCa. Bioinformatics suggested that SETDB1 might promote PCa bone metastasis through the WNT pathway. In conclusion, SETDB1 might be associated with the development of bone metastases from PCa. Further study is necessary to assess its exact role in PCa.

Differential blood-based diagnosis between benign prostatic hyperplasia and prostate cancer: miRNA as source for biomarkers independent of PSA level, Gleason score, or TNM status

Since the benefit of prostate-specific antigen (PSA) screening remains controversial, new non-invasive biomarkers for prostate carcinoma (PCa) are still required. There is evidence that microRNAs (miRNAs) in whole peripheral blood can separate patients with localized prostate cancer from healthy individuals. However, the potential of blood-based miRNAs for the differential diagnosis of PCa and benign prostatic hyperplasia (BPH) has not been tested. We compared the miRNome from blood of PCa and BPH patients and further investigated the influence of the tumor volume, tumor-node-metastasis (TNM) classification, Gleason score, pretreatment risk status, and the pretreatment PSA value on the miRNA pattern. By microarray approach, we identified seven miRNAs that were significantly deregulated in PCa patients compared to BPH patients. Using quantitative real time PCR (qRT-PCR), we confirmed downregulation of hsa-miR-221* (now hsa-miR-221-5p) and hsa-miR-708* (now hsa-miR-708-3p) in PCa compared to BPH. Clinical parameters like PSA level, Gleason score, or TNM status seem to have only limited impact on the overall abundance of miRNAs in patients' blood, suggesting a no influence of these factors on the expression of deregulated miRNAs.

Transcriptomic and Proteomic Investigation of HSP90A as a Potential Biomarker for HCC

Background

Hepatocellular carcinoma (HCC) is the third most frequent cause of cancer-related death in adults. Despite recent advances in the clinical technologies, the screening and diagnostic efficacy for HCC remains poor. Discovering novel and reliable HCC biomarkers is urgently needed.

Material/Methods

We performed a transcriptome-proteome integrated assay to track the possible HCC biomarkers from the process of HCC-derived gene expression in malignant cells to its protein product released into serum.

Results

Our screening results demonstrated that heat shock protein 90A (HSP90A), which participates in the PI3K-Akt signaling pathway and many other cancer-related pathways, warrants further investigation. The expression of HSP90A was increased in the HCC cells, serum, and tissues. Immunohistochemistry analysis on 76 clinical tissue samples also suggested the relevance between HSP90A expression and HCC metastatic behavior.

Conclusions

These findings suggest a role for HSP90A in HCC pathogenesis and the potential use of HSP90A for the screening and diagnosis of this malignancy.

Dietary L-arginine supplementation affects the skeletal longissimus muscle proteome in finishing pigs

Forty-eight Duroc x Landrace x Large White gilts were used to determine the relationship between proteome changes of longissimus muscle and intramuscular fat (IMF) content in arginine-supplemented pigs. Beginning at 60 kg BW, pigs were fed a corn- and soybean meal-based diet supplemented or not with 1% L-arginine until they reached a BW of 100 kg. Supplementation with 1% L-arginine did not affect the growth performance or carcass traits, while it increased IMF content by 32% (P < 0.01), it also decreased the drip loss at 48 h post-mortem and the b* meat color value at 24 h post-mortem; supplementation with 1% dietary L-arginine did not change the proportion of SFA and MUFA in muscle lipids. The proteome changes in longissimus muscle between the control and supplemented pigs showed that L-arginine significantly influenced the abundance of proteins related to energy metabolism, fiber type and structure. The increase in IMF content was positively correlated with the increased abundance of slow twitch troponin I (TNNI1) protein and negatively correlated with myosin heavy chain IIb (MyHC IIb) protein content. It is suggested that the proteome changes in longissimus muscle contributed to the greater IMF content in L-arginine supplemented pigs.

Identification and validation of potential new biomarkers for prostate cancer diagnosis and prognosis using 2D-DIGE and MS

This study was designed to identify and validate potential new biomarkers for prostate cancer and to distinguish patients with and without biochemical relapse. Prostate tissue samples analyzed by 2D-DIGE (two-dimensional difference in gel electrophoresis) and mass spectrometry (MS) revealed downregulation of secernin-1 (P < 0.044) in prostate cancer, while vinculin showed significant upregulation (P < 0.001). Secernin-1 overexpression in prostate tissue was validated using Western blot and immunohistochemistry while vinculin expression was validated using immunohistochemistry. These findings indicate that secernin-1 and vinculin are potential new tissue biomarkers for prostate cancer diagnosis and prognosis, respectively. For validation, protein levels in urine were also examined by Western blot analysis. Urinary vinculin levels in prostate cancer patients were significantly higher than in urine from nontumor patients (P = 0.006). Using multiple reaction monitoring-MS (MRM-MS) analysis, prostatic acid phosphatase (PAP) showed significant higher levels in the urine of prostate cancer patients compared to controls (P = 0.012), while galectin-3 showed significant lower levels in the urine of prostate cancer patients with biochemical relapse, compared to those without relapse (P = 0.017). Three proteins were successfully differentiated between patients with and without prostate cancer and patients with and without relapse by using MRM. Thus, this technique shows promise for implementation as a noninvasive clinical diagnostic technique.

Elevated expression of IMPDH2 is associated with progression of kidney and bladder cancer

Novel molecular markers for cancer progression are valuable for the diagnosis and evaluation of treatment efficacies of the diseases. Expression of inosine 5'-monophosphate dehydrogenase type II (IMPDH2), a rate-limiting enzyme in the de novo guanine nucleotide biosynthesis, is up-regulated in various neoplasms, including prostate cancer and patient serum. However, whether IMPDH2 can serve as a biomarker for other urologic cancers is unknown. Paired patient tissue macroarrays were analyzed by immunohistochemistry, the IMPDH2 protein expression in these tissues was quantitated and expressed as immunoreactivity scores. Compared with non-cancerous tissues, IMPDH2 protein expression levels were significantly upregulated in kidney and bladder cancer, but no difference in testis cancer. In addition, expression of IMPDH2 was not associated with the disease clinical stages and pathological features. The findings suggest that overexpressed IMPDH2 can be used as a biomarker for kidney and bladder cancer diagnosis and is a potential therapeutic target for the diseases.

Enhanced expression of IMPDH2 promotes metastasis and advanced tumor progression in patients with prostate cancer

PURPOSE

Our previous study showed the upregulation of inosine 5'-monophosphate dehydrogenase type II (IMPDH2) protein in human prostate cancer (PCa) tissues and sera compared to non-cancerous controls by proteomics and ELISA analyses. However, the clinical significance of IMPDH2 in PCa has not been fully elucidated. Thus, the aim of the current study was to investigate the associations of IMPDH2 upregulation with tumor progression in patients with PCa.

METHODS

IMPDH2 expression at mRNA and protein levels in human PCa and non-cancerous prostate tissues was respectively detected by qRT-PCR, Western blot and immunohistochemistry analyses, which was validated by microarray-based Taylor Data. Then, the association of IMPDH2 expression with clinicopathological features of PCa patients was statistically analyzed.

RESULTS

Compared with non-cancerous prostate tissues, IMPDH2 mRNA and protein expression levels were both significantly upregulated (at mRNA level: 9.22 ± 2.49 vs 5.06 ± 1.45, P < 0.01; at protein level by Western blot: 0.674 ± 0.029 vs 0.418 ± 0.140, P < 0.001; at protein level by immunohistochemistry: 4.97 ± 0.760 vs 3.32 ± 1.66, P < 0.001) in PCa tissues, which were consistent with our previous data. In addition, the enhanced expression of IMPDH2 in PCa tissues was significantly correlated with the advanced clinical stage (for our cohort: P < 0.001; for Taylor data: P = 0.002), the presence of metastasis (for our cohort: P < 0.001; for Taylor data: P = 0.012) and the higher Gleason score (for our cohort: P = 0.002; for Taylor data: P = 0.028).

CONCLUSIONS

These findings suggest for the first time that the enhanced expression of IMPDH2 may promote the tumor metastasis and the advanced tumor progression in patients with PCa.

Decreased expression of myosin light chain MYL9 in stroma predicts malignant progression and poor biochemical recurrence-free survival in prostate cancer

The aim of this study was to investigate the associations of myosin light chain (MYL9) downregulation with tumor progression and prognosis in patients with prostate cancer (PCa). MYL9 protein expression in human PCa and non-cancerous prostate tissues was detected by Western blot and immunohistochemistry analyses, which was validated by microarray-based Taylor data at mRNA level. Then, the associations of MYL9 expression with clinicopathological features and clinical outcome of PCa patients were statistically analyzed. Both Western blot and immunohistochemistry analyses found that MYL9 expression was significantly decreased (both P < 0.001) in PCa tissues compared with those in non-cancerous prostate tissues. In addition, MYL9 was mainly expressed in the cytoplasm of stromal cells of prostate tissues, and the decreased expression of MYL9 in PCa tissues was significantly correlated with the older age of patients (P = 0.011), the higher Gleason score (P < 0.001), the advanced pathological stage (P = 0.002), the presence of metastasis (P < 0.001) and PSA failure (P = 0.001). Furthermore, both univariate and multivariate analyses showed that the downregulation of MYL9 was an independent predictor of shorter overall survival (P = 0.026 and P = 0.009, respectively) and biochemical recurrence-free survival (P = 0.001 and P = 0.002, respectively). Our data strongly confirmed for the first time that the decreased expression of MYL9 may play an important role in tumor progression of PCa. More importantly, the downregulation of MYL9 may efficiently predict both overall and biochemical recurrence-free survivals in PCa patients.

The present and future of prostate cancer urine biomarkers

In order to successfully cure patients with prostate cancer (PCa), it is important to detect the disease at an early stage. The existing clinical biomarkers for PCa are not ideal, since they cannot specifically differentiate between those patients who should be treated immediately and those who should avoid over-treatment. Current screening techniques lack specificity, and a decisive diagnosis of PCa is based on prostate biopsy. Although PCa screening is widely utilized nowadays, two thirds of the biopsies performed are still unnecessary. Thus the discovery of non-invasive PCa biomarkers remains urgent. In recent years, the utilization of urine has emerged as an attractive option for the non-invasive detection of PCa. Moreover, a great improvement in high-throughput “omic” techniques has presented considerable opportunities for the identification of new biomarkers. Herein, we will review the most significant urine biomarkers described in recent years, as well as some future prospects in that field.

An integrative proteomics and interaction network-based classifier for prostate cancer diagnosis

Aim

Early diagnosis of prostate cancer (PCa), which is a clinically heterogeneous-multifocal disease, is essential to improve the prognosis of patients. However, published PCa diagnostic markers share little overlap and are poorly validated using independent data. Therefore, we here developed an integrative proteomics and interaction network-based classifier by combining the differential protein expression with topological features of human protein interaction networks to enhance the ability of PCa diagnosis.

Methods and Results

By two-dimensional fluorescence difference gel electrophoresis (2D-DIGE) coupled with MS using PCa and adjacent benign tissues of prostate, a total of 60 proteins with the differential expression in PCa tissues were identified as the candidate markers. Then, their networks were analyzed by GeneGO Meta-Core software and three hub proteins (PTEN, SFPQ and HDAC1) were chosen. After that, a PCa diagnostic classifier was constructed by support vector machine (SVM) modeling based on the microarray gene expression data of the genes which encode the hub proteins mentioned above. Validations of diagnostic performance showed that this classifier had high predictive accuracy (85.96∼90.18%) and area under ROC curve (approximating 1.0). Furthermore, the clinical significance of PTEN, SFPQ and HDAC1 proteins in PCa was validated by both ELISA and immunohistochemistry analyses. More interestingly, PTEN protein was identified as an independent prognostic marker for biochemical recurrence-free survival in PCa patients according to the multivariate analysis by Cox Regression.

Conclusions

Our data indicated that the integrative proteomics and interaction network-based classifier which combines the differential protein expression and topological features of human protein interaction network may be a powerful tool for the diagnosis of PCa. We also identified PTEN protein as a novel prognostic marker for biochemical recurrence-free survival in PCa patients.

Down-regulation of the ErbB3 binding protein 1 in human bladder cancer promotes tumor progression and cell proliferation

The ErbB3 binding protein 1 (Ebp1) represents a downstream effector of the ErbB signaling network and has been demonstrated to be a potent tumor suppressor in various human malignancies, however, its involvement in human bladder cancer is still unclear.To investigate the clinical significance and potential role of ErbB3 binding protein 1 (Ebp1) in bladder cancer. Ebp1 expression at protein and gene levels in 52 surgically removed bladder cancer specimens as well as 21 adjacent normal bladder specimens were respectively detected by immunohistochemistry and qRT-PCR. The association of Ebp1 protein expression with the clinicopathological features of bladder cancer was also statistically analyzed. Its roles in bladder cancer cell line were further evaluated. The expression level of Ebp1 protein and gene in bladder cancer tissues was significantly lower than that in adjacent normal bladder tissues (P < 0.01). When categorized into low vs. high expression, the down-regulation of Ebp1 protein was associated with the advanced pathologic stage (P = 0.036) and the high histologic grade (P = 0.001) of patients with bladder cancer. Moreover, following the transfection of Ebp1 in bladder cancer cells, not only cell proliferation and cell invasion decreased significantly, but also the cell cycle was blocked at G0/G1 stage. Our data suggest for the first time that the down-regulation of Ebp1 closely correlates with advanced clinicopathological characteristics of human bladder cancer. Furthermore, Ebp1 plays an important role in the bladder cancer cells' proliferation by regulating the cancer cell cycle from G0/G1 to S.