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

Molecular Insights into the Breast and Prostate Cancer Cells in Response to the Change of Extracellular Zinc

Zinc dyshomeostasis is manifested in breast and prostate cancer cells. This study attempted to uncover the molecular details prodded by the change of extracellular zinc by employing a panel of normal and cancerous breast and prostate cell lines coupled with the top-down proteomics with two-dimensional gel electrophoresis followed by liquid chromatography-tandem mass spectrometry. The protein samples were generated from MCF-7 breast cancer cells, MCF10A normal breast cells, PC3 prostate cancer cells, and RWPE-1 normal prostate cells with or without exogenous zinc exposure in a time course (T0 and T120). By comparing the cancer cells vs respective normal epithelial cells without zinc treatment (T0), differentially expressed proteins (23 upregulated and 18 downregulated in MCF-7 cells; 14 upregulated and 30 downregulated in PC3 cells) were identified, which provides insights into the intrinsic differences of breast and prostate cancer cells. The dynamic protein landscapes in the cancer cells prodded by the extracellular zinc treatment reveal the potential roles of the identified zinc-responsive proteins (e.g., triosephosphate isomerase, S100A13, tumour proteins hD53 and hD54, and tumour suppressor prohibitin) in breast and prostate cancers. This study, for the first time, simultaneously investigated the two kinds of cancer cells related to zinc dyshomeostasis, and the findings shed light on the molecular understanding of the breast and prostate cancer cells in response to extracellular zinc variation.

Dimethylarginine Dimethylaminohydrolase - 1 expression is increased under tBHP-induced oxidative stress regulates nitric oxide production in PCa cells attenuates mitochondrial ROS-mediated apoptosis

Dimethylarginine dimethylaminohydrolase-1 (DDAH1) expression is frequently elevated in different cancers including prostate cancer (PCa) and enhances nitric oxide (NO) production in tumor cells by metabolising endogenous nitric oxide synthase (NOS) inhibitors. DDAH1 protects the PCa cells from cell death and promotes survival. In this study, we have investigated the cytoprotective role of DDAH1 and determined the mechanism of DDAH1 in protecting the cells in tumor microenvironment. Proteomic analysis of PCa cells with stable overexpression of DDAH1 has identified that oxidative stress-related activity is altered. Oxidative stress promotes cancer cell proliferation, survival and causes chemoresistance. A known inducer of oxidative stress, tert-Butyl Hydroperoxide (tBHP) treatment to PCa cells led to elevated DDAH1 level that is actively involved in protecting the PCa cells from oxidative stress induced cell damage. In PC3-DDAH1- cells, tBHP treatment led to higher mROS levels indicating that the loss of DDAH1 increases the oxidative stress and eventually leads to cell death. Under oxidative stress, nuclear Nrf2 controlled by SIRT1 positively regulates DDAH1 expression in PC3 cells. In PC3-DDAH1+ cells, tBHP induced DNA damage is well tolerated compared to wild-type cells while PC3-DDAH1- became sensitive to tBHP. In PC3 cells, tBHPexposure has increased the production of NO and GSH which may be acting as an antioxidant defence to overcome oxidative stress. Furthermore, in tBHP treated PCa cells, DDAH1 is controlling the expression of Bcl2, active PARP and caspase 3. Taken together, these results confirm that DDAH1 is involved in the antioxidant defence system and promotes cell survival.

Microfluidic-based prostate cancer model for investigating the secretion of prostate-specific antigen and microRNAs in vitro

The study of prostate cancer in vitro relies on established cell lines that lack important physiological characteristics, such as proper polarization and expression of relevant biomarkers. Microphysiological systems (MPS) can replicate cancer microenvironments and lead to cellular phenotypic changes that better represent organ physiology in vitro. In this study, we developed an MPS model comprising conventional prostate cancer cells to evaluate their activity under dynamic culture conditions. Androgen-sensitive (LNCaP) and androgen-insensitive (PC3) cells were grown in conventional and 3D cultures, both static and dynamic. Cell morphology, the secretion of prostate-specific antigen, and the expression of key prostate markers and microRNAs were analyzed. LNCaP formed spheroids in 3D and MPS cultures, with morphological changes supported by the upregulation of cytokeratins and adhesion proteins. LNCaP also maintained a constant prostate-specific antigen secretion in MPS. PC3 cells did not develop complex structures in 3D and MPS cultures. PSA expression at the gene level was downregulated in LNCaP-MPS and considerably upregulated in PC3-MPS. MicroRNA expression was altered by the 3D static and dynamic culture, both intra- and extracellularly. MicroRNAs associated with prostate cancer progression were mostly upregulated in LNCaP-MPS. Overall dynamic cell culture substantially altered the morphology and expression of LNCaP cells, arguably augmenting their prostate cancer phenotype. This novel approach demonstrates that microRNA expression in prostate cancer cells is sensitive to external stimuli and that MPS can effectively promote important physiological changes in conventional prostate cancer models.

Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice

Proteomics continues to forge significant strides in the discovery of essential biological processes, uncovering valuable information on the identity, global protein abundance, protein modifications, proteoform levels, and signal transduction pathways. Cancer is a complicated and heterogeneous disease, and the onset and progression involve multiple dysregulated proteoforms and their downstream signaling pathways. These are modulated by various factors such as molecular, genetic, tissue, cellular, ethnic/racial, socioeconomic status, environmental, and demographic differences that vary with time. The knowledge of cancer has improved the treatment and clinical management; however, the survival rates have not increased significantly, and cancer remains a major cause of mortality. Oncoproteomics studies help to develop and validate proteomics technologies for routine application in clinical laboratories for (1) diagnostic and prognostic categorization of cancer, (2) real-time monitoring of treatment, (3) assessing drug efficacy and toxicity, (4) therapeutic modulations based on the changes with prognosis and drug resistance, and (5) personalized medication. Investigation of tumor-specific proteomic profiles in conjunction with healthy controls provides crucial information in mechanistic studies on tumorigenesis, metastasis, and drug resistance. This review provides an overview of proteomics technologies that assist the discovery of novel drug targets, biomarkers for early detection, surveillance, prognosis, drug monitoring, and tailoring therapy to the cancer patient. The information gained from such technologies has drastically improved cancer research. We further provide exemplars from recent oncoproteomics applications in the discovery of biomarkers in various cancers, drug discovery, and clinical treatment. Overall, the future of oncoproteomics holds enormous potential for translating technologies from the bench to the bedside.

DIGE-Based Biomarker Discovery in Blood Cancers

Cancer of blood or bone marrow-derived cells dysregulates normal hematopoiesis and accounts for over 6% of all cancer cases annually. Proteomic analyses of blood cancers have improved our understanding of disease mechanisms and identified numerous proteins of clinical relevance. For many years, gel-based proteomic studies have aided in the discovery of novel diagnostic, prognostic, and predictive biomarkers, as well as therapeutic targets, in various diseases, including blood cancer. Fluorescence two-dimensional difference gel electrophoresis (2D-DIGE) facilitates comparative proteomic research to identify differential protein expression in a simple and reproducible manner. The versatility of 2D-DIGE as a quantitative proteomic technique has provided insight into various aspects of blood cancer pathology, including disease development, prognostic subtypes, and drug resistance. The ability to couple 2D-DIGE with additional downstream mass spectrometry-based techniques yields comprehensive workflows capable of identifying proteins of biological and clinical significance. The application of 2D-DIGE in blood cancer research has significantly contributed to the increasingly important initiative of precision medicine. This chapter will focus on the influential role of 2D-DIGE as a tool in blood cancer research.

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.

Identification of the Regulatory Targets of miR-3687 and miR-4417 in Prostate Cancer Cells Using a Proteomics Approach

MicroRNAs (miRNA) are ubiquitous non-coding RNAs that have a prominent role in cellular regulation. The expression of many miRNAs is often found deregulated in prostate cancer (PCa) and castration-resistant prostate cancer (CRPC). Although their expression can be associated with PCa and CRPC, their functions and regulatory activity in cancer development are poorly understood. In this study, we used different proteomics tools to analyze the activity of hsa-miR-3687-3p (miR-3687) and hsa-miR-4417-3p (miR-4417), two miRNAs upregulated in CRPC. PCa and CRPC cell lines were transfected with miR-3687 or miR-4417 to overexpress the miRNAs. Cell lysates were analyzed using 2D gel electrophoresis and proteins were subsequently identified using mass spectrometry (Maldi-MS/MS). A whole cell lysate, without 2D-gel separation, was analyzed by ESI-MS/MS. The expression of deregulated proteins found across both methods was further investigated using Western blotting. Gene ontology and cellular process network analysis determined that miR-3687 and miR-4417 are involved in diverse regulatory mechanisms that support the CRPC phenotype, including metabolism and inflammation. Moreover, both miRNAs are associated with extracellular vesicles, which point toward a secretory mechanism. The tumor protein D52 isoform 1 (TD52-IF1), which regulates neuroendocrine trans-differentiation, was found to be substantially deregulated in androgen-insensitive cells by both miR-3687 and miR-4417. These findings show that these miRNAs potentially support the CRPC by truncating the TD52-IF1 expression after the onset of androgen resistance.

HIF-1α and Nrf2 regulates hypoxia induced overexpression of DDAH1 through promoter activation in prostate cancer

Dimethylarginine dimethylaminohydrolase-1 (DDAH1) is overexpressed in prostate cancer (PCa) and promotes PCa progression in in vivo through the ADMA-NO pathway by degrading nitric oxide synthase (NOS) inhibitors such as asymmetric dimethylarginine (ADMA) and monomethylamine arginine (L-NMMA). In this study, we investigated the molecular mechanism involved in the overexpression of DDAH1 in PCa and examined its potential role as a therapeutic target. We observed that DDAH1expression is elevated in PCa (PC3, LNCaP, and DU145) cell lines under hypoxia. ChIP and reporter assay results confirmed that DDAH1 expression is positively regulated by HIF-1α through directly binding to the hypoxia response elements (HRE) located within the promoter region between - 1242/- 1238 upstream of its transcription start site (TSS). Under hypoxia, HIF-1α is translocated into the nucleus and activates its target gene expression in PC3 cells. Interestingly, in the event of HIF-1α inhibition or siRNA-mediated knockdown, an alternative transcription factor Nrf2 promotes DDAH1 expression through antioxidant response elements (AREs) on its promoter. ChIP assay results showed that Nrf2 binds to AREs located between -1016 / -1008 bp from the TSS of DDAH1. Furthermore, knockdown of PCa therapeutic target HSP90, an essential co-factor for both HIF-1α and Nrf2 causes attenuation of hypoxia induced DDAH1 overexpression in PCa cells. These results demonstrate that hypoxia induced upregulation of DDAH1 expression is positively regulated by HIF-1α and Nrf2 in association with HSP90. Therefore, targeting tumor angiogenesis promoting DDAH1 along with standard androgen receptor (AR) targeted therapy may offer an effective strategy to prevent PCa progression.

Gel-Based Proteomic Identification of Suprabasin as a Potential New Candidate Biomarker in Endometrial Cancer

Endometrial cancer (EC) is the most frequent gynaecologic cancer in postmenopausal women. We used 2D-DIGE and mass spectrometry to identify candidate biomarkers in endometrial cancer, analysing the serum protein contents of 10 patients versus 10 control subjects. Using gel-based proteomics, we identified 24 candidate biomarkers, considering only spots with a fold change in volume percentage ≥ 1.5 or intensity change ≤ 0.6, which were significantly different between cases and controls (p < 0.05). We used Western blotting analysis both in the serum and tissue of 43 patients for data validation. Among the identified proteins, we selected Suprabasin (SBSN), an oncogene previously associated with poor prognosis in different cancers. SBSN principal isoforms were subjected to Western blotting analysis in serum and surgery-excised tissue: both isoforms were downregulated in the tissue. However, in serum, isoform 1 was upregulated, while isoform 2 was downregulated. Data-mining on the TCGA and GTEx projects, using the GEPIA2.0 interface, indicated a diminished SBSN expression in the Uterine Corpus Endometrial Cancer (UCEC) database compared to normal tissue, confirming proteomic results. These results suggest that SBSN, specifically isoform 2, in tissue or serum, could be a potential novel biomarker in endometrial cancer.

Ubiquitin Carboxyl-Terminal Hydrolases and Human Malignancies: The Novel Prognostic and Therapeutic Implications for Head and Neck Cancer

Ubiquitin C-terminal hydrolases (UCHs), a subfamily of deubiquitinating enzymes (DUBs), have been found in a variety of tumor entities and play distinct roles in the pathogenesis and development of various cancers including head and neck cancer (HNC). HNC is a heterogeneous disease arising from the mucosal epithelia of the upper aerodigestive tract, including different anatomic sites, distinct histopathologic types, as well as human papillomavirus (HPV)-positive and negative subgroups. Despite advances in multi-disciplinary treatment for HNC, the long-term survival rate of patients with HNC remains low. Emerging evidence has revealed the members of UCHs are associated with the pathogenesis and clinical prognosis of HNC, which highlights the prognostic and therapeutic implications of UCHs for patients with HNC. In this review, we summarize the physiological and pathological functions of the UCHs family, which provides enlightenment of potential mechanisms of UCHs family in HNC pathogenesis and highlights the potential consideration of UCHs as attractive drug targets.

The expression of YWHAZ and NDRG1 predicts aggressive outcome in human prostate cancer

Some prostate cancers (PCas) are histo-pathologically grouped within the same Gleason Grade (GG), but can differ significantly in outcome. Herein, we aimed at identifying molecular biomarkers that could improve risk prediction in PCa. LC ESI-MS/MS was performed on human PCa and benign prostatic hyperplasia (BPH) tissues and peptide data was integrated with omic analyses. We identified high YWHAZ and NDRG1 expression to be associated with poor PCa prognosis considering all Gleason scores (GS). YWHAZ and NDRG1 defined two subpopulations of PCa patients with high and intermediate risk of death. Multivariable analyses confirmed their independence from GS. ROC analysis unveiled that YWHAZ outperformed GS beyond 60 months post-diagnosis. The genomic analysis of PCa patients with YWHAZ amplification, or increased mRNA or protein levels, revealed significant alterations in key DNA repair genes. We hereby state the relevance of YWHAZ in PCa, showcasing its role as an independent strong predictor of aggressiveness.

Overexpression of PRDX4 Modulates Tumor Microenvironment and Promotes Urethane-Induced Lung Tumorigenesis

Peroxiredoxin 4 (PRDX4), initially reported as an antioxidant, is overexpressed in lung cancer and participates in its progression. However, its role in the urethane-induced lung tumor model is undetermined. The aim of this study was to investigate the effect of PRDX4 overexpression on carcinogen-induced lung tumor development. Human PRDX4 overexpression transgenic (Tg) mice (hPRDX4^+/+) and non-Tg mice were intraperitoneally injected with urethane to induce lung tumor. After 6 months, tumor formation was compared between groups and possible mechanisms for the difference in tumor development were investigated. The serum and lung PRDX4 expressions were enhanced after urethane stimulation in Tg mice. Both the average number of tumors (≥0.5 mm) and tumor diameter per mouse in the Tg group were significantly larger than in non-Tg controls, while body weight was lower in the Tg group. Compared with non-Tg controls, tumor cell proliferation was enhanced, while tumor cell apoptosis was suppressed in Tg mice. Systemic oxidative stress and oxidative stress in lung tumors were inhibited by PRDX4 overexpression. The balance of prooxidant enzymes and antioxidant enzymes was also shifted to a decreased level in Tg tumor. In lung tumor tissue, the density of microvessel penetrated into tumor was higher in the Tg group; macrophage infiltration was enhanced in Tg tumors, while there was no difference in T lymphocyte infiltration; the expressions of cytokines, including interleukin-1 beta (IL-1β) and matrix metallopeptidase 9 (MMP9), were elevated in Tg tumors, which resulted from enhanced phosphorylation of nuclear factor-κB p65 (NF-κB p65) and c-Jun, respectively. In conclusion, PRDX4 overexpression modulated tumor microenvironment and promoted tumor development in the mouse urethane-induced lung cancer model.

Technological Advances in Preclinical Drug Evaluation: The Role of -Omics Methods

Preclinical drug development is an essential step in the drug development process where the evaluation of new chemical entities occurs. In particular, preclinical drug development phases include deep analysis of drug candidates' interactions with biomolecules/targets, their safety, toxicity, pharmacokinetics, metabolism by use of assays in vitro and in vivo animal assays. Legal aspects of the required procedures are well-established. Herein, we present a comprehensive summary of current state-of-the art approaches and techniques used in preclinical studies. In particular, we will review the potential of new, -omics methods and platforms for mechanistic evaluation of drug candidates and speed-up of the preclinical evaluation steps.

PRDX4 and Its Roles in Various Cancers

Reactive oxygen species play a vital role in cell survival by regulating physiological metabolism and signal transduction of cells. The imbalance of oxidant and antioxidant states induces oxidative stress within a cell. Redox regulation and oxidative stress are closely related to survival and proliferation of stem cells, cancer cells, and cancer stem cells. Peroxiredoxin 4, a typical endoplasmic reticulum-resident 2-Cys antioxidant of peroxiredoxins, can fine-tune hydrogen peroxide catabolism which affects cell survival by affecting redox balance, oxidative protein folding, and regulation of hydrogen peroxide signaling. Recent studies revealed the overexpression of peroxiredoxin 4 in several kinds of cancers, such as breast cancer, prostate cancer, ovarian cancer, colorectal cancer, and lung cancer. And it has been demonstrated that peroxiredoxin 4 causally contributes to tumorigenesis, therapeutic resistance, metastasis, and recurrence of tumors. In this article, the characteristics of peroxiredoxin 4 in physiological functions and the cancer-related research progress of mammalian peroxiredoxin 4 is reviewed. We believe that peroxiredoxin 4 has the potential of serving as a novel target for multiple cancers.

Inhibition of Dimethylarginine Dimethylaminohydrolase (DDAH) Enzymes as an Emerging Therapeutic Strategy to Target Angiogenesis and Vasculogenic Mimicry in Cancer

The small free radical gas nitric oxide (NO) plays a key role in various physiological and pathological processes through enhancement of endothelial cell survival and proliferation. In particular, NO has emerged as a molecule of interest in carcinogenesis and tumor progression due to its crucial role in various cancer-related events including cell invasion, metastasis, and angiogenesis. The dimethylarginine dimethylaminohydrolase (DDAH) family of enzymes metabolize the endogenous nitric oxide synthase (NOS) inhibitors, asymmetric dimethylarginine (ADMA) and monomethyl arginine (L-NMMA), and are thus key for maintaining homeostatic control of NO. Dysregulation of the DDAH/ADMA/NO pathway resulting in increased local NO availability often promotes tumor growth, angiogenesis, and vasculogenic mimicry. Recent literature has demonstrated increased DDAH expression in tumors of different origins and has also suggested a potential ADMA-independent role for DDAH enzymes in addition to their well-studied ADMA-mediated influence on NO. Inhibition of DDAH expression and/or activity in cell culture models and in vivo studies has indicated the potential therapeutic benefit of this pathway through inhibition of both angiogenesis and vasculogenic mimicry, and strategies for manipulating DDAH function in cancer are currently being actively pursued by several research groups. This review will thus provide a timely discussion on the expression, regulation, and function of DDAH enzymes in regard to angiogenesis and vasculogenic mimicry, and will offer insight into the therapeutic potential of DDAH inhibition in cancer based on preclinical studies.

Novel Cellularly Active Inhibitor Regresses DDAH1 Induced Prostate Tumor Growth by Restraining Tumor Angiogenesis through Targeting DDAH1/ADMA/NOS Pathway

Dimethylarginine dimethylaminohydrolase1 (DDAH1) inhibitors are important therapeutics by virtue of their ability to control nitric oxide (NO) production by elevating asymmetric dimethylarginine (ADMA) levels. In a screening campaign, we identified that DD1E5 (3-amino-6- tert-butyl-N-(1,3-thiazol-2-yl)-4-(trifluoromethyl)thieno[2,3- b]pyridine-2- carboxamide) inhibits the DDAH1 activity both in vitro and in cultured cells. Mechanistic studies found that DD1E5 is a competitive inhibitor (dissociation constant ( K_i) of 2.05 ± 0.15 μM). Enzyme kinetic assays showed time and concentration dependent inhibition of DDAH1 with DD1E5, which shows tight binding with an inactivation rate constant of 0.2756 ± 0.015 M^-1 S^-1. Treatment of cancer cells with DDAH1 inhibitors shows inhibition of cell proliferation and a subsequent decrease in NO production with ADMA accumulation. DD1E5 reversed the elevated VEGF, c-Myc, HIF-1α, and iNOS levels induced by exogenous DDAH1 overexpression in PCa cells. Moreover, DD1E5 significantly increased intracellular levels of ADMA and reduced NO production, suggesting its therapeutic potential for cancers in which DDAH1 is upregulated. In in vitro assays, DD1E5 abrogated the secretion of angiogenic factors (bFGF and IL-8) into conditional media, indicating its antiangiogenic potential. DD1E5 inhibited in vivo growth of xenograft tumors derived from PCa cells with DDAH1 overexpression, by reducing tumor endothelial content represented with low CD31 expression. VEGF, HIF-1α, and iNOS expression were reversed in DD1E5 treated tumors compared to respective control tumors. In this work, integrating multiple approaches shows DD1E5 is a promising tool for the study of methylarginine-mediated NO control and a potential therapeutic lead compound against pathological conditions with elevated NO production such as cancers and other diseases.

Drug Repositioning for Effective Prostate Cancer Treatment

Drug repositioning has gained attention from both academia and pharmaceutical companies as an auxiliary process to conventional drug discovery. Chemotherapeutic agents have notorious adverse effects that drastically reduce the life quality of cancer patients so drug repositioning is a promising strategy to identify non-cancer drugs which have anti-cancer activity as well as tolerable adverse effects for human health. There are various strategies for discovery and validation of repurposed drugs. In this review, 25 repurposed drug candidates are presented as result of different strategies, 15 of which are already under clinical investigation for treatment of prostate cancer (PCa). To date, zoledronic acid is the only repurposed, clinically used, and approved non-cancer drug for PCa. Anti-cancer activities of existing drugs presented in this review cover diverse and also known mechanisms such as inhibition of mTOR and VEGFR2 signaling, inhibition of PI3K/Akt signaling, COX and selective COX-2 inhibition, NF-κB inhibition, Wnt/β-Catenin pathway inhibition, DNMT1 inhibition, and GSK-3β inhibition. In addition to monotherapy option, combination therapy with current anti-cancer drugs may also increase drug efficacy and reduce adverse effects. Thus, drug repositioning may become a key approach for drug discovery in terms of time- and cost-efficiency comparing to conventional drug discovery and development process.

Interleukin-6 induced overexpression of valosin-containing protein (VCP)/p97 is associated with androgen-independent prostate cancer (AIPC) progression

Though Androgen deprivation therapy (ADT) is effective initially, numerous patients become resistant to it and develop castration resistant PCa (CRPC). Cytokines promotes ligand independent activation of AR. Interleukin-6 (IL-6) levels are elevated in CRPC patients and regulate AR activity. However, progression to CRPC is not fully understood. In this study, we analyzed differential protein expression in LNCaP cells treated with IL-6 using proteomics. Results revealed altered expression of 27 proteins and Valosin-containing protein (VCP)/p97 plays a predominant role in co-regulation of altered proteins. Interestingly, IL-6 induced VCP expression through Pim-1 via STAT3 is AR independent there by suggesting a role for VCP in CRPC. Transfection of LNCaP cells for VCP overexpression showed an increased cell proliferation, migration, and invasion where as its inhibition by NMS-873 showed the reverse effect causing cell death. Mechanistic studies demonstrate that cell death occurs due to apoptosis by endoplasmic reticulum (ER) stress, elevated cell cycle inhibitors p21, p27kip1, and active PARP and reduced Bcl-2. VCP promotes cell invasion and migration by altering E-cadherin and Vimentin levels inversely triggering EMT of PCa cells. VCP immunostaining revealed no staining in BPH but strong staining in PCa. This study determines VCP may play an important role in progression to CRPC and it can be a favorable target with to develop new therapies to treat ADT resistant prostate cancer.

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.

Database-augmented Mass Spectrometry Analysis of Exosomes Identifies Claudin 3 as a Putative Prostate Cancer Biomarker

In prostate cancer and other malignancies sensitive and robust biomarkers are lacking or have relevant limitations. Prostate specific antigen (PSA), the only biomarker widely used in prostate cancer, is suffering from low specificity. Exosomes offer new perspectives in the discovery of blood-based biomarkers. Here we present a proof-of principle study for a proteomics-based identification pipeline, implementing existing data sources, to exemplarily identify exosome-based biomarker candidates in prostate cancer.Exosomes from malignant PC3 and benign PNT1A cells and from FBS-containing medium were isolated using sequential ultracentrifugation. Exosome and control samples were analyzed on an LTQ-Orbitrap XL mass spectrometer. Proteomic data is available via ProteomeXchange with identifier PXD003651. We developed a scoring scheme to rank 64 proteins exclusively found in PC3 exosomes, integrating data from four public databases and published mass spectrometry data sets. Among the top candidates, we focused on the tight junction protein claudin 3. Retests under serum-free conditions using immunoblotting and immunogold labeling confirmed the presence of claudin 3 on PC3 exosomes. Claudin 3 levels were determined in the blood plasma of patients with localized (n = 58; 42 with Gleason score 6-7, 16 with Gleason score ≥8) and metastatic prostate cancer (n = 11) compared with patients with benign prostatic hyperplasia (n = 15) and healthy individuals (n = 15) using ELISA, without prior laborious exosome isolation. ANOVA showed different CLDN3 plasma levels in these groups (p = 0.004). CLDN3 levels were higher in patients with Gleason ≥8 tumors compared with patients with benign prostatic hyperplasia (p = 0.012) and Gleason 6-7 tumors (p = 0.029). In patients with localized tumors CLDN3 levels predicted a Gleason score ≥ 8 (AUC = 0.705; p = 0.016) and did not correlate with serum PSA.By using the described workflow claudin 3 was identified and validated as a potential blood-based biomarker in prostate cancer. Furthermore this workflow could serve as a template to be used in other cancer entities.

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.

Biological Networks for Cancer Candidate Biomarkers Discovery

Due to its extraordinary heterogeneity and complexity, cancer is often proposed as a model case of a systems biology disease or network disease. There is a critical need of effective biomarkers for cancer diagnosis and/or outcome prediction from system level analyses. Methods based on integrating omics data into networks have the potential to revolutionize the identification of cancer biomarkers. Deciphering the biological networks underlying cancer is undoubtedly important for understanding the molecular mechanisms of the disease and identifying effective biomarkers. In this review, the networks constructed for cancer biomarker discovery based on different omics level data are described and illustrated from recent advances in the field.

Brain Radiation Information Data Exchange (BRIDE): integration of experimental data from low-dose ionising radiation research for pathway discovery

BACKGROUND

The underlying molecular processes representing stress responses to low-dose ionising radiation (LDIR) in mammals are just beginning to be understood. In particular, LDIR effects on the brain and their possible association with neurodegenerative disease are currently being explored using omics technologies.

RESULTS

We describe a light-weight approach for the storage, analysis and distribution of relevant LDIR omics datasets. The data integration platform, called BRIDE, contains information from the literature as well as experimental information from transcriptomics and proteomics studies. It deploys a hybrid, distributed solution using both local storage and cloud technology.

CONCLUSIONS

BRIDE can act as a knowledge broker for LDIR researchers, to facilitate molecular research on the systems biology of LDIR response in mammals. Its flexible design can capture a range of experimental information for genomics, epigenomics, transcriptomics, and proteomics. The data collection is available at: .

Prostate Cancer Associated Lipid Signatures in Serum Studied by ESI-Tandem Mass Spectrometryas Potential New Biomarkers

Prostate cancer (PCa) is one amongst the most common cancersin western men. Incidence rate ofPCa is on the rise worldwide. The present study deals with theserum lipidome profiling of patients diagnosed with PCa to identify potential new biomarkers. We employed ESI-MS/MS and GC-MS for identification of significantly altered lipids in cancer patient’s serum compared to controls. Lipidomic data revealed 24 lipids are significantly altered in cancer patinet’s serum (n = 18) compared to normal (n = 18) with no history of PCa. By using hierarchical clustering and principal component analysis (PCA) we could clearly separate cancer patients from control group. Correlation and partition analysis along with Formal Concept Analysis (FCA) have identified that PC (39:6) and FA (22:3) could classify samples with higher certainty. Both the lipids, PC (39:6) and FA (22:3) could influence the cataloging of patients with 100% sensitivity (all 18 control samples are classified correctly) and 77.7% specificity (of 18 tumor samples 4 samples are misclassified) with p-value of 1.612×10⁻⁶ in Fischer’s exact test. Further, we performed GC-MS to denote fatty acids altered in PCa patients and found that alpha-linolenic acid (ALA) levels are altered in PCa. We also performed an in vitro proliferation assay to determine the effect of ALA in survival of classical human PCa cell lines LNCaP and PC3. We hereby report that the altered lipids PC (39:6) and FA (22:3) offer a new set of biomarkers in addition to the existing diagnostic tests that could significantly improve sensitivity and specificity in PCa diagnosis.

LEDGF/p75 Overexpression Attenuates Oxidative Stress-Induced Necrosis and Upregulates the Oxidoreductase ERP57/PDIA3/GRP58 in Prostate Cancer

Prostate cancer (PCa) mortality is driven by highly aggressive tumors characterized by metastasis and resistance to therapy, and this aggressiveness is mediated by numerous factors, including activation of stress survival pathways in the pro-inflammatory tumor microenvironment. LEDGF/p75, also known as the DFS70 autoantigen, is a stress transcription co-activator implicated in cancer, HIV-AIDS, and autoimmunity. This protein is targeted by autoantibodies in certain subsets of patients with PCa and inflammatory conditions, as well as in some apparently healthy individuals. LEDGF/p75 is overexpressed in PCa and other cancers, and promotes resistance to chemotherapy-induced cell death via the transactivation of survival proteins. We report in this study that overexpression of LEDGF/p75 in PCa cells attenuates oxidative stress-induced necrosis but not staurosporine-induced apoptosis. This finding was consistent with the observation that while LEDGF/p75 was robustly cleaved in apoptotic cells into a p65 fragment that lacks stress survival activity, it remained relatively intact in necrotic cells. Overexpression of LEDGF/p75 in PCa cells led to the upregulation of transcript and protein levels of the thiol-oxidoreductase ERp57 (also known as GRP58 and PDIA3), whereas its depletion led to ERp57 transcript downregulation. Chromatin immunoprecipitation and transcription reporter assays showed LEDGF/p75 binding to and transactivating the ERp57 promoter, respectively. Immunohistochemical analysis revealed significantly elevated co-expression of these two proteins in clinical prostate tumor tissues. Our results suggest that LEDGF/p75 is not an inhibitor of apoptosis but rather an antagonist of oxidative stress-induced necrosis, and that its overexpression in PCa leads to ERp57 upregulation. These findings are of significance in clarifying the role of the LEDGF/p75 stress survival pathway in PCa.

Integrated Genomic and Network-Based Analyses of Complex Diseases and Human Disease Network

A disease phenotype generally reflects various pathobiological processes that interact in a complex network. The highly interconnected nature of the human protein interaction network (interactome) indicates that, at the molecular level, it is difficult to consider diseases as being independent of one another. Recently, genome-wide molecular measurements, data mining and bioinformatics approaches have provided the means to explore human diseases from a molecular basis. The exploration of diseases and a system of disease relationships based on the integration of genome-wide molecular data with the human interactome could offer a powerful perspective for understanding the molecular architecture of diseases. Recently, subnetwork markers have proven to be more robust and reliable than individual biomarker genes selected based on gene expression profiles alone, and achieve higher accuracy in disease classification. We have applied one of these methodologies to idiopathic dilated cardiomyopathy (IDCM) data that we have generated using a microarray and identified significant subnetworks associated with the disease. In this paper, we review the recent endeavours in this direction, and summarize the existing methodologies and computational tools for network-based analysis of complex diseases and molecular relationships among apparently different disorders and human disease network. We also discuss the future research trends and topics of this promising field.

Proteomics analysis of malignant and benign prostate tissue by 2D DIGE/MS reveals new insights into proteins involved in prostate cancer

BACKGROUND

The key to a more effective diagnosis, prognosis, and therapeutic management of prostate cancer (PCa) could lie in the direct analysis of cancer tissue. In this study, by comparative proteomics analysis of PCa and benign prostate hyperplasia (BPH) tissues we attempted to elucidate the proteins and regulatory pathways involved in this disease.

METHODS

The samples used in this study were fresh surgical tissues with clinically and histologically confirmed PCa (n = 19) and BPH (n = 33). We used two dimensional difference in gel electrophoresis (2D DIGE) coupled with mass spectrometry (MS) and bioinformatics analysis.

RESULTS

Thirty-nine spots with statistically significant 1.8-fold variation or more in abundance, corresponding to 28 proteins were identified. The IPA analysis pointed out to 3 possible networks regulated within MAPK, ERK, TGFB1, and ubiquitin pathways. Thirteen of the identified proteins, namely, constituents of the intermediate filaments (KRT8, KRT18, DES), potential tumor suppressors (ARHGAP1, AZGP1, GSTM2, and MFAP4), transport and membrane organization proteins (FABP5, GC, and EHD2), chaperons (FKBP4 and HSPD1) and known cancer marker (NME1) have been associated with prostate and other cancers by numerous proteomics, genomics or functional studies. We evidenced for the first time the dysregulation of 9 proteins (CSNK1A1, ARID5B, LYPLA1, PSMB6, RABEP1, TALDO1, UBE2N, PPP1CB, and SERPINB1) that may have role in PCa. The UBE2N, PSMB6, and PPP1CB, involved in cell cycle regulation and progression were evaluated by Western blot analysis which confirmed significantly higher abundances of UBE2N and PSMB6 and significantly lower abundance of PPP1CB in PCa.

CONCLUSION

In addition to the identification of substantial number of proteins with known association with PCa, the proteomic approach in this study revealed proteins not previously clearly related to PCa, providing a starting point for further elucidation of their function in disease initiation and progression.

Cancer stratification by molecular imaging

The lack of specificity of traditional cytotoxic drugs has triggered the development of anticancer agents that selectively address specific molecular targets. An intrinsic property of these specialized drugs is their limited applicability for specific patient subgroups. Consequently, the generation of information about tumor characteristics is the key to exploit the potential of these drugs. Currently, cancer stratification relies on three approaches: Gene expression analysis and cancer proteomics, immunohistochemistry and molecular imaging. In order to enable the precise localization of functionally expressed targets, molecular imaging combines highly selective biomarkers and intense signal sources. Thus, cancer stratification and localization are performed simultaneously. Many cancer types are characterized by altered receptor expression, such as somatostatin receptors, folate receptors or Her2 (human epidermal growth factor receptor 2). Similar correlations are also known for a multitude of transporters, such as glucose transporters, amino acid transporters or hNIS (human sodium iodide symporter), as well as cell specific proteins, such as the prostate specific membrane antigen, integrins, and CD20. This review provides a comprehensive description of the methods, targets and agents used in molecular imaging, to outline their application for cancer stratification. Emphasis is placed on radiotracers which are used to identify altered expression patterns of cancer associated markers.

Proteomics analysis of urine reveals acute phase response proteins as candidate diagnostic biomarkers for prostate cancer

Despite the overall success of prostate specific antigen (PSA) in screening and detection of prostate cancer (PCa), its use has been limited due to the lack of specificity. The principal driving goal currently within PCa research is to identify non-invasive biomarker(s) for early detection of aggressive tumors with greater sensitivity and specificity than PSA. In this study, we focused on identification of non-invasive biomarkers in urine with higher specificity than PSA. We tested urine samples from PCa and benign prostatic hyperplasia (BPH) patients by 2-D DIGE coupled with MS and bioinformatics analysis. Statistically significant (p < 0.05), 1.8 fold variation or more in abundance, showed 41 spots, corresponding to 23 proteins. The Ingenuity Pathway Analysis showed significant association with the Acute Phase Response Signaling pathway. Nine proteins with differential abundances were included in this pathway: AMBP, APOA1, FGA, FGG, HP, ITIH4, SERPINA1, TF and TTR. The expression pattern of 4 acute phase response proteins differed from the defined expression in the canonical pathway. The urine levels of TF, AMPB and HP were measured by immunoturbidimetry in an independent validation set. The concentration of AMPB in urine was significantly higher in PCa while levels of TF and HP were opposite (p < 0.05). The AUC for the individual proteins ranged from 0.723 to 0.754. The combination of HP and AMBP yielded the highest accuracy (AUC = 0.848), greater than PSA. The proposed biomarker set is quickly quantifiable and economical with potential to improve the sensitivity and specificity of PCa detection.

From a 2DE-gel spot to protein function: lesson learned from HS1 in chronic lymphocytic leukemia

The identification of molecules involved in tumor initiation and progression is fundamental for understanding disease's biology and, as a consequence, for the clinical management of patients. In the present work we will describe an optimized proteomic approach for the identification of molecules involved in the progression of Chronic Lymphocytic Leukemia (CLL). In detail, leukemic cell lysates are resolved by 2-dimensional Electrophoresis (2DE) and visualized as "spots" on the 2DE gels. Comparative analysis of proteomic maps allows the identification of differentially expressed proteins (in terms of abundance and post-translational modifications) that are picked, isolated and identified by Mass Spectrometry (MS). The biological function of the identified candidates can be tested by different assays (i.e. migration, adhesion and F-actin polymerization), that we have optimized for primary leukemic cells.

Advances in Proteomic Technologies and Its Contribution to the Field of Cancer

Systematic studies of the cancer genome have generated a wealth of knowledge in recent years. These studies have uncovered a number of new cancer genes not previously known to be causal targets in cancer. Genetic markers can be used to determine predisposition to tumor development, but molecularly targeted treatment strategies are not widely available for most cancers. Precision care plans still must be developed by understanding and implementing basic science research into clinical treatment. Proteomics is continuing to make major strides in the discovery of fundamental biological processes as well as more recent transition into an assay platform capable of measuring hundreds of proteins in any biological system. As such, proteomics can translate basic science discoveries into the clinical practice of precision medicine. The proteomic field has progressed at a fast rate over the past five years in technology, breadth and depth of applications in all areas of the bioscience. Some of the previously experimental technical approaches are considered the gold standard today, and the community is now trying to come to terms with the volume and complexity of the data generated. Here I describe contribution of proteomics in general and biological mass spectrometry in particular to cancer research, as well as related major technical and conceptual developments in the field.

Activity of aaptamine and two derivatives, demethyloxyaaptamine and isoaaptamine, in cisplatin-resistant germ cell cancer

We analyzed the effects of all three marine alkaloids aaptamine, demethyloxyaaptamine and isoaaptamine in NT2-R, a cisplatin-resistant subline of the human embryonal carcinoma cell line NT2. All aaptamines were found to be equally effective in both cell lines, excluding cross-resistance between aaptamines and cisplatin in vitro. At the inhibitory concentration (IC50), aaptamine exerted an antiproliferative effect, whereas demethyloxyaaptamine and isoaaptamine were strong inducers of apoptosis. We analyzed the changes in the proteome of NT2-R cells treated with these compounds. 16-22 proteins were found to be significantly altered, of which several were validated by Western blotting and two-dimensional Western blotting analysis. Changes in the proteome pattern frequently resulted from post-transcriptional protein modifications, i.e. phosphorylation or hypusination in the case of eIF5A. Although the lists of altered proteins were heterogeneous and compound-specific, gene ontology analyses identified rather similar profiles regarding the affected molecular functions. Ingenuity pathway analysis by IPA put the following factors in a central position of the hypothetical networks: myc and p53 for aaptamine; tumor necrosis factor (TNF) for demethyloxyaaptamine; and all three, myc, p53, and TNF for isoaaptamine. Our results represent an important step towards a better understanding of the molecular basis underlying the observed bioactivity of these promising marine compounds.

BIOLOGICAL SIGNIFICANCE

We characterized the mode of action of three aaptamines, marine natural compound with anti-tumor activity, using a functional proteomics approach and the cisplatin-resistant pluripotent human embryonal carcinoma cell line NT2-R. The manuscript is of particular scientific interest, as we could reveal the similarities and differences of the modes of action. Furthermore, we were able to identify several new targets of these promising compounds. We found hypusination of eIF5A to be a prominent feature exclusively of aaptamine treatment, as this was not observed upon treatment with demethyloxyaaptamine or isoaaptamine. Our results are a step towards unraveling the mode of action of these interesting compounds.

Advances in the proteomic discovery of novel therapeutic targets in cancer

Proteomic approaches are continuing to make headways in cancer research by helping to elucidate complex signaling networks that underlie tumorigenesis and disease progression. This review describes recent advances made in the proteomic discovery of drug targets for therapeutic development. A variety of technical and methodological advances are overviewed with a critical assessment of challenges and potentials. A number of potential drug targets, such as baculoviral inhibitor of apoptosis protein repeat-containing protein 6, macrophage inhibitory cytokine 1, phosphoglycerate mutase 1, prohibitin 1, fascin, and pyruvate kinase isozyme 2 were identified in the proteomic analysis of drug-resistant cancer cells, drug action, and differential disease state tissues. Future directions for proteomics-based target identification and validation to be more translation efficient are also discussed.

Translational bioinformatics for diagnostic and prognostic prediction of prostate cancer in the next-generation sequencing era

The discovery of prostate cancer biomarkers has been boosted by the advent of next-generation sequencing (NGS) technologies. Nevertheless, many challenges still exist in exploiting the flood of sequence data and translating them into routine diagnostics and prognosis of prostate cancer. Here we review the recent developments in prostate cancer biomarkers by high throughput sequencing technologies. We highlight some fundamental issues of translational bioinformatics and the potential use of cloud computing in NGS data processing for the improvement of prostate cancer treatment.

MALDI mass spectrometry in prostate cancer biomarker discovery

Matrix-assisted laser desorption/ionisation (MALDI) mass spectrometry (MS) is a highly versatile and sensitive analytical technique, which is known for its soft ionisation of biomolecules such as peptides and proteins. Generally, MALDI MS analysis requires little sample preparation, and in some cases like MS profiling it can be automated through the use of robotic liquid-handling systems. For more than a decade now, MALDI MS has been extensively utilised in the search for biomarkers that could aid clinicians in diagnosis, prognosis, and treatment decision making. This review examines the various MALDI-based MS techniques like MS imaging, MS profiling and proteomics in-depth analysis where MALDI MS follows fractionation and separation methods such as gel electrophoresis, and how these have contributed to prostate cancer biomarker research. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.

Structure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive review

Despite considerable progress in genome- and proteome-based high-throughput screening methods and in rational drug design, the increase in approved drugs in the past decade did not match the increase of drug development costs. Network description and analysis not only give a systems-level understanding of drug action and disease complexity, but can also help to improve the efficiency of drug design. We give a comprehensive assessment of the analytical tools of network topology and dynamics. The state-of-the-art use of chemical similarity, protein structure, protein-protein interaction, signaling, genetic interaction and metabolic networks in the discovery of drug targets is summarized. We propose that network targeting follows two basic strategies. The "central hit strategy" selectively targets central nodes/edges of the flexible networks of infectious agents or cancer cells to kill them. The "network influence strategy" works against other diseases, where an efficient reconfiguration of rigid networks needs to be achieved by targeting the neighbors of central nodes/edges. It is shown how network techniques can help in the identification of single-target, edgetic, multi-target and allo-network drug target candidates. We review the recent boom in network methods helping hit identification, lead selection optimizing drug efficacy, as well as minimizing side-effects and drug toxicity. Successful network-based drug development strategies are shown through the examples of infections, cancer, metabolic diseases, neurodegenerative diseases and aging. Summarizing >1200 references we suggest an optimized protocol of network-aided drug development, and provide a list of systems-level hallmarks of drug quality. Finally, we highlight network-related drug development trends helping to achieve these hallmarks by a cohesive, global approach.

Combination of a proteomics approach and reengineering of meso scale network models for prediction of mode-of-action for tyrosine kinase inhibitors

In drug discovery, the characterisation of the precise modes of action (MoA) and of unwanted off-target effects of novel molecularly targeted compounds is of highest relevance. Recent approaches for identification of MoA have employed various techniques for modeling of well defined signaling pathways including structural information, changes in phenotypic behavior of cells and gene expression patterns after drug treatment. However, efficient approaches focusing on proteome wide data for the identification of MoA including interference with mutations are underrepresented. As mutations are key drivers of drug resistance in molecularly targeted tumor therapies, efficient analysis and modeling of downstream effects of mutations on drug MoA is a key to efficient development of improved targeted anti-cancer drugs. Here we present a combination of a global proteome analysis, reengineering of network models and integration of apoptosis data used to infer the mode-of-action of various tyrosine kinase inhibitors (TKIs) in chronic myeloid leukemia (CML) cell lines expressing wild type as well as TKI resistance conferring mutants of BCR-ABL. The inferred network models provide a tool to predict the main MoA of drugs as well as to grouping of drugs with known similar kinase inhibitory activity patterns in comparison to drugs with an additional MoA. We believe that our direct network reconstruction approach, demonstrated on proteomics data, can provide a complementary method to the established network reconstruction approaches for the preclinical modeling of the MoA of various types of targeted drugs in cancer treatment. Hence it may contribute to the more precise prediction of clinically relevant on- and off-target effects of TKIs.

Targeting to overexpressed glucose-regulated protein 78 in gastric cancer discovered by 2D DIGE improves the diagnostic and therapeutic efficacy of micelles-mediated system

The survivals of gastric cancer (GC) patients are associated with early diagnosis and effective treatments. Therefore, it is urgent for the discovery of early GC biomarkers and tumor-targeting therapeutics. The aim of this study was to uncover putative tissue biomarkers of GC using 2D DIGE and then apply one of these specific markers in GC treatment. We found three putative biomarkers of GC with significant differences in expression level compared to adjacent normal tissue, including glucose-regulated protein 78 (GRP78) and glutathione s-transferase pi (GSTpi) with increased expression level, and alpha-1 antitrypsin (A1AT) with reduced expression level. The overexpressed GRP78 was used as a targeted protein for guiding the drugs to tumor cells, leading to more effective treatment for GC xenografts. Our results demonstrated that the designated GRP78-binding peptide based on the sequence, WIFPWIQL, was selectively prone to recognize and bind to GC MKN45 cells in vitro, and also improve the delivery efficiency of polymeric micelles-encapsulated drugs into tumor cells and displayed better therapeutic outcome in experimental animals. This strategy of GRP78-mediated drug targeting system may bring chemotherapeutic drugs with more precise targeting to tumor cells, leading to minimize side effects on patients after chemotherapy.

The role of proteomics in prostate cancer research: biomarker discovery and validation

PURPOSE

Prostate Cancer (PCa) represents the second most frequent type of tumor in men worldwide. Incidence increases with patient age and represents the most important risk factor. PCa is mostly characterized by indolence, however in a small percentage of cases (3%) the disease progresses to a metastatic state. To date, the most important issue concerning PCa research is the difficulty in distinguishing indolent from aggressive disease. This problem frequently results in low-grade PCa patient overtreatment and, in parallel; an effective treatment for distant and aggressive disease is not yet available.

RESULT

Proteomics represents a promising approach for the discovery of new biomarkers able to improve the management of PCa patients. Markers more specific and sensitive than PSA are needed for PCa diagnosis, prognosis and response to treatment. Moreover, proteomics could represent an important tool to identify new molecular targets for PCa tailored therapy. Several possible PCa biomarkers sources, each with advantages and limitations, are under investigation, including tissues, urine, serum, plasma and prostatic fluids. Innovative high-throughput proteomic platforms are now identifying and quantifying new specific and sensitive biomarkers for PCa detection, stratification and treatment. Nevertheless, many putative biomarkers are still far from being applied in clinical practice.

CONCLUSIONS

This review aims to discuss the recent advances in PCa proteomics, emphasizing biomarker discovery and their application to clinical utility for diagnosis and patient stratification.

Protein-protein-interaction network organization of the hypusine modification system

Hypusine modification of eukaryotic initiation factor 5A (eIF-5A) represents a unique and highly specific post-translational modification with regulatory functions in cancer, diabetes, and infectious diseases. However, the specific cellular pathways that are influenced by the hypusine modification remain largely unknown. To globally characterize eIF-5A and hypusine-dependent pathways, we used an approach that combines large-scale bioreactor cell culture with tandem affinity purification and mass spectrometry: "bioreactor-TAP-MS/MS." By applying this approach systematically to all four components of the hypusine modification system (eIF-5A1, eIF-5A2, DHS, and DOHH), we identified 248 interacting proteins as components of the cellular hypusine network, with diverse functions including regulation of translation, mRNA processing, DNA replication, and cell cycle regulation. Network analysis of this data set enabled us to provide a comprehensive overview of the protein-protein interaction landscape of the hypusine modification system. In addition, we validated the interaction of eIF-5A with some of the newly identified associated proteins in more detail. Our analysis has revealed numerous novel interactions, and thus provides a valuable resource for understanding how this crucial homeostatic signaling pathway affects different cellular functions.

Canine olfactory detection of cancer versus laboratory testing: myth or opportunity?

According to the most recent global cancer statistics, the burden of malignancies continues to increase worldwide, so that there is a compelling need to reinforce the screening strategies and implement novel diagnostic approaches for early detection. Canines are widely used by police forces and civilian services for detecting explosives and drugs due to their superior olfactive apparatus, which is characterized by a detection threshold as low as parts per trillion. There is mounting evidence that dogs might be effectively trained to detect patients with various form of cancers due to the presence of a characteristic "odor signature". In particular, preliminary studies reported that appropriately trained dogs exhibit an extraordinary ability to detect melanoma as well as prostate, breast, ovary and lung cancers by recognizing a characteristic "odor signature" in body, urines, sweat, breath and even blood. The most problematic issue that has emerged so far is the large heterogeneity of performance across the different studies as well as within the same study, which might be dependent upon genetic characteristics or training methodology. This article is aimed to provide an overview of the available data on cancer sniffer dogs, highlighting the appealing perspectives and the potential drawbacks.