Quantitative DNA methylation analysis of genes coding for kallikrein-related peptidases 6 and 10 as biomarkers for prostate cancer

DNA methylation plays an important role in carcinogenesis and is being recognized as a promising diagnostic and prognostic biomarker for a variety of malignancies including Prostate cancer (PCa). The human kallikrein-related peptidases (KLKs) have emerged as an important family of cancer biomarkers, with KLK3, encoding for Prostate Specific Antigen, being most recognized. However, few studies have examined the epigenetic regulation of KLKs and its implications to PCa. To assess the biological effect of DNA methylation on KLK6 and KLK10 expression, we treated PC3 and 22RV1 PCa cells with a demethylating drug, 5-aza-2′deoxycytidine, and observed increased expression of both KLKs, establishing that DNA methylation plays a role in regulating gene expression. Subsequently, we have quantified KLK6 and KLK10 DNA methylation levels in two independent cohorts of PCa patients operated by radical prostatectomy between 2007–2011 (Cohort I, n = 150) and 1998–2001 (Cohort II, n = 124). In Cohort I, DNA methylation levels of both KLKs were significantly higher in cancerous tissue vs. normal. Further, we evaluated the relationship between DNA methylation and clinicopathological parameters. KLK6 DNA methylation was significantly associated with pathological stage only in Cohort I while KLK10 DNA methylation was significantly associated with pathological stage in both cohorts. In Cohort II, low KLK10 DNA methylation was associated with biochemical recurrence in univariate and multivariate analyses. A similar trend for KLK6 DNA methylation was observed. The results suggest that KLK6 and KLK10 DNA methylation distinguishes organ confined from locally invasive PCa and may have prognostic value.     

Quantitative DNA methylation analysis of genes coding for kallikrein-related peptidases 6 and 10 as biomarkers for prostate cancer

DNA methylation plays an important role in carcinogenesis and is being recognized as a promising diagnostic and prognostic biomarker for a variety of malignancies including Prostate cancer (PCa). The human kallikrein-related peptidases (KLKs) have emerged as an important family of cancer biomarkers, with KLK3, encoding for Prostate Specific Antigen, being most recognized. However, few studies have examined the epigenetic regulation of KLKs and its implications to PCa. To assess the biological effect of DNA methylation on KLK6 and KLK10 expression, we treated PC3 and 22RV1 PCa cells with a demethylating drug, 5-aza-2′deoxycytidine, and observed increased expression of both KLKs, establishing that DNA methylation plays a role in regulating gene expression. Subsequently, we have quantified KLK6 and KLK10 DNA methylation levels in two independent cohorts of PCa patients operated by radical prostatectomy between 2007–2011 (Cohort I, n = 150) and 1998–2001 (Cohort II, n = 124). In Cohort I, DNA methylation levels of both KLKs were significantly higher in cancerous tissue vs. normal. Further, we evaluated the relationship between DNA methylation and clinicopathological parameters. KLK6 DNA methylation was significantly associated with pathological stage only in Cohort I while KLK10 DNA methylation was significantly associated with pathological stage in both cohorts. In Cohort II, low KLK10 DNA methylation was associated with biochemical recurrence in univariate and multivariate analyses. A similar trend for KLK6 DNA methylation was observed. The results suggest that KLK6 and KLK10 DNA methylation distinguishes organ confined from locally invasive PCa and may have prognostic value.     

Discovery of biomarkers for gastric cancer: a proteomics approach

Gastric cancer is the second leading cause of cancer-related deaths worldwide. Although many treatment options exist for patients with gastric tumors, the incidence and mortality rate of gastric cancer are on the rise. The early stages of gastric cancer are non-symptomatic, and the treatment response is unpredictable. This situation is further aggravated by a lack of diagnostic biomarkers that can aid in the early detection and prognosis of gastric cancer and in the prediction of chemoresistance. Moreover, clinical surgical specimens are rarely obtained, and traditional biomarkers of gastric cancer are not very effective. Many studies in the field of proteomics have contributed to the discovery and establishment of powerful diagnostic tools (e.g., ProteinChip array) in the management of cancer. The evolution in proteomic technologies has not only enabled the screening of a large number of samples but also enabled the identification of pathologically significant proteins, such as phosphoproteins, and the quantitation of difference in protein expression under different conditions. Multiplexed assays are used widely to accurately fractionate various complex samples such as blood, tissue, cells, and Helicobacter pylori-infected specimens to identify differentially expressed proteins. Biomarker detection studies have substantially contributed to the areas of secretome, metabolome, and phosphoproteome. Here, we review the development of potential biomarkers in the natural history of gastric cancer, with specific emphasis on the characteristics of target protein convergence.     

Comparison of the activity levels and localization of dipeptidyl peptidase IV in normal and tumor human lung cells

Dipeptidyl peptidase IV (DPPIV) was studied in three human lung cells - P (fetal lung-derived cells), A549 (lung adenocarcinoma) and SK-MES-1 (squamous cell carcinoma) using a fluorescent cytochemical procedure developed on the basis of the substrate 4-(glycyl-l-prolyl hydrazido)-N-hexyl-1,8-naphthalimide. The observed differences in the enzyme expression were confirmed by measuring the enzyme hydrolysis of glycyl-l-prolyl-para-nitroanilide. The surface and total dipeptidyl peptidase activities of P cells were correspondingly 7-8 and 3-10 times higher than those of SK-MES-1 and A549 cells. The ratio surface per total activity showed that in P (95%) and A549 (93%) cells the enzyme is associated with the plasmalemma while in SK-MES-1 cells (35%) it is bound to intracellular membranes. In order to compare the results from cell cultures with those in human tumor, the enzyme activity was investigated in cryo-sections of three cases of diagnosed squamous lung carcinoma. DPPIV activity was restricted to the connective tissue stroma surrounding the DPPIV-negative tumor foci.     

Mass spectrometry based proteomics and metabolomics in personalized oncology

Precision medicine (PM) means the customization of healthcare with decisions and practices adjusted to the individual patient. It includes personalized diagnostics, patients' sub-classification, individual treatment selection and the monitoring of its effectiveness. Currently, in oncology, PM is based on the molecular and cellular features of a tumor, its microenvironment and the patient's genetics and lifestyle. Surprisingly, the available targeted therapies were found effective only in a subset of patients. An in-depth understanding of tumor biology is crucial to improve their effectiveness and develop new therapeutic targets. Completion of genetic information with proteomics and metabolomics can give broader knowledge about tumor biology which consequently provides novel biomarkers and indicates new therapeutic targets. Recently, metabolomics and proteomics have extensively been applied in the field of oncology. In the context of PM, human studies, with the use of mass spectrometry (MS) which allows the detection of thousands of molecules in a large number of samples, are the most valuable. Such studies, focused on cancer biomarkers discovery or patients' stratification, are presented in this review. Moreover, the technical aspects of MS-based clinical proteomics and metabolomics are described.     

Progress and prospects for the discovery of biomarkers for gastric cancer: a focus on proteomics

Introduction: Patient outcomes from gastric cancer vary due to the complexity of stomach carcinogenesis. Recent research using proteomic technologies has targeted components of all of these systems in order to develop biomarkers to aid the early diagnosis of gastric cancer and to assist in prognostic stratification.

Areas covered: This review is comprised of evidence obtained from literature searches from PubMed. It covers the evidence of diagnostic, prognostic, and predictive biomarkers for gastric cancer using proteomic technologies, and provides up-to-date references.

Expert commentary: The proteomic technologies have not only enabled the screening of a large number of samples, but also enabled the identification of diagnostic, prognostic and predictive biomarkers for gastric cancer. While major challenges still remain, to date, proteomic studies in gastric cancer have provided a wealth of information in revealing proteome alterations associated with the disease.     

Clinical proteomics and mass spectrometry profiling for cancer detection

A key challenge in the clinical proteomics of cancer is the identification of biomarkers that would enable early detection, diagnosis and monitoring of disease progression to improve long-term survival of patients. Recent advances in proteomic instrumentation and computational methodologies offer a unique chance to rapidly identify these new candidate markers or pattern of markers. The combination of retentate affinity chromatography and mass spectrometry is one of the most interesting new approaches for cancer diagnostics using proteomic profiling. This review presents two technologies in this field, surface-enhanced laser desorption/ionization time-of-flight and Clinprot?, and aims to summarize the results of studies obtained with the first of them for the early diagnosis of human cancer. Despite promising results, the use of the proteomic profiling as a diagnostic tool brought some controversies and technical problems, and still requires some efforts to be standardized and validated.     

Mass spectrometry for high throughput quantitative proteomics in plant research: lessons from thylakoid membranes

Proteomics seeks to monitor the flux of protein through cells under variable developmental and environmental influences as programmed by the genome. Consequently, it is necessary to measure changes in protein abundance and turnover rate as faithfully as possible. In the absence of non-invasive technologies, the majority of proteomics approaches involve destructive sampling at various time points to obtain 'snapshots' that periodically report the genomes's product. The work has fallen to separations technologies coupled to mass spectrometry, for high throughput protein identification. Quantitation has become the major challenge facing proteomics as the field matures. Because of the variability of day-to-day measurements of protein quantities by mass spectrometry, a common feature of quantitative proteomics is the use of stable isotope coding to distinguish control and experimental samples in a mixture that can be profiled in a single experiment. To address limitations with separation technologies such as 2D-gel electrophoresis, alternative systems are being introduced including multi-dimensional chromatography. Strategies that accelerate throughput for mass spectrometry are also emerging and the benefits of these 'shotgun' protocols will be considered in the context of the thylakoid membrane and photosynthesis. High resolution Fourier-transform mass spectrometry is bringing increasingly accurate mass measurements to peptides and a variety of gas-phase dissociation mechanisms are permitting 'top-down' sequencing of intact proteins. Finally, a versatile workflow for sub-cellular compartments including membranes is presented that allows for intact protein mass measurements, localization of post-translational modifications and relative quantitation or turnover measurement.     

Dipeptidyl peptidase I: importance of progranzyme activation sequences,other dipeptide sequences,and the N-terminal amino group of synthetic substrates for enzyme activity

The broadly reactive cysteine protease dipeptidyl peptidase I (DPPI, cathepsin C) is thought to activate all progranzymes (zymogens of lymphocyte serine proteases) to form mature granzymes. We synthesized dipeptide 7-amino-4-methylcoumarin (AMC) substrates containing progranzyme activation sequences and showed that they were efficiently hydrolyzed by DPPI. However, DPPI will not hydrolyze Ile-Ile-AMC, the N-terminal dipeptide sequence found in mature granzymes. Introduction of the nonphysiological homophenylalanine (Hph) residue at P1 resulted in the best substrate Ala-Hph-AMC for DPPI (k(cat)/K(m)=9,000,000M(-1)s(-1)). The charged N-terminal amino group of the substrate was essential and replacement of the NH(2) group with OH or NH(CH(3)) in Gly-Phe-AMC reduced the k(cat)/K(m) value by two to three orders of magnitude. A hydrazide azaglycine analog, NH(2)NHCO-Phe-AMC, was not hydrolyzed at pH 5.5, but underwent slow hydrolysis at lower pHs where the amino group is partially protonated. DPPI also failed to hydrolyze NH(2)COCH(2)-Phe-AMC, where the NH(2) group is unprotonated. The results reported in this paper should be useful in the design of better DPPI inhibitors to block granzyme maturation and granzyme-dependent apoptosis.     

Peptide and protein imaging mass spectrometry in cancer research

MALDI mass spectrometry is able to acquire protein profiles directly from tissue that can describe the levels of hundreds of distinct proteins. MALDI imaging MS can simultaneously reveal how each of these proteins varies in heterogeneous tissues. Numerous studies have now demonstrated how MALDI imaging MS can generate different protein profiles from the different cell types in a tumor, which can act as biomarker profiles or enable specific candidate protein biomarkers to be identified.     

Advances in clinical cancer proteomics: SELDI-ToF-mass spectrometry and biomarker discovery.

For most cancers, survival rates depend on the early detection of the disease. So far, no biomarkers exist to cope with this difficult task. New proteomic technologies have brought the hope of discovering novel early cancer-specific biomarkers in complex biological samples and/or of the setting up of new clinically relevant test systems. Novel mass spectrometry-(MS) based technologies in particular, such as surface-enhanced laser desorption/ionisation time of flight (SELDI-ToF-MS), have shown promising results in the recent literature. Here, proteomic profiles of control and disease states are compared to find biomarkers for diagnosis. This paper aims to address the authors' own work and that of other groups in clinical cancer proteomics based on SELDI-ToF-MS. Shortcomings and hopes for the future are discussed.     

Lung cancer proteomics,clinical and technological considerations

The overall survival of lung cancer patients is disappointingly low. This is due to several factors, including the lack of an effective screening strategy to detect tumors at a potentially curable early stage, a marked resistance of lung cancer cells to drug treatment and a still superficial knowledge about the multifactorial cellular networks that are activated or suppressed during cancer progression. Furthermore, the armamentarium of clinicians and researchers in the field does not yet include reliable biomarkers to predict tumor response to treatment and foresee the natural history of the disease. In the present situation, a potential breakthrough is presented by proteomics technologies with the potential to discover relevant biomarkers which can be accurately quantified in multiplexed assays. Proteomics field can also contribute greatly in the understanding of mechanisms in tumor progression and treatment response.     

Mass spectrometry-based proteomics for translational research: a technical overview

Mass spectrometry-based investigation of clinical samples enables the high-throughput identification of protein biomarkers. We provide an overview of mass spectrometry-based proteomic techniques that are applicable to the investigation of clinical samples. We address sample collection, protein extraction and fractionation, mass spectrometry modalities, and quantitative proteomics. Finally, we examine the limitations and further potential of such technologies. Liquid chromatography fractionation coupled with tandem mass spectrometry is well suited to handle mixtures of hundreds or thousands of proteins. Mass spectrometry-based proteome elucidation can reveal potential biomarkers and aid in the development of hypotheses for downstream investigation of the molecular mechanisms of disease.     

Advances in mass spectrometry-based cancer research and analysis: from cancer proteomics to clinical diagnostics

Introduction: The last 20 years have seen significant improvements in the analytical capabilities of biological mass spectrometry (MS). Studies using advanced MS have resulted in new insights into cell biology and the etiology of diseases as well as its use in clinical applications.

Areas covered: This review discusses recent developments in MS-based technologies and their cancer-related applications with a focus on proteomics. It also discusses the issues around translating the research findings to the clinic and provides an outline of where the field is moving.

Expert commentary: Proteomics has been problematic to adapt for the clinical setting. However, MS-based techniques continue to demonstrate potential in novel clinical uses beyond classical cancer proteomics.     

KYSS: Mass spectrometry data quality assessment for protein analysis and large-scale proteomics

We introduce the computer tool “Know Your Samples” (KYSS) for assessment and visualisation of large scale proteomics datasets, obtained by mass spectrometry (MS) experiments. KYSS facilitates the evaluation of sample preparation protocols, LC peptide separation, and MS and MS/MS performance by monitoring the number of missed cleavages, precursor ion charge states, number of protein identifications and peptide mass error in experiments. KYSS generates several different protein profiles based on protein abundances, and allows for comparative analysis of multiple experiments. KYSS was adapted for blood plasma proteomics and provides concentrations of identified plasma proteins. We demonstrate the utility of the KYSS tool for MS based proteome analysis of blood plasma and for assessment of hydrogel particles for depletion of abundant proteins in plasma. The KYSS software is open source and is freely available at http://kyssproject.github.io/.     

Candidate proteomic biomarkers for non-alcoholic fatty liver disease (steatosis and non-alcoholic steatohepatitis) discovered with mass-spectrometry: a systematic review

Context: Non-alcoholic fatty liver disease (NAFLD) is characterized by lipid accumulation in the liver which is accompanied by a series of metabolic deregulations. There are sustained research efforts focusing upon biomarker discovery for NAFLD diagnosis and its prognosis in order investigate and follow-up patients as minimally invasive as possible.

Objective: The objective of this study is to critically review proteomic studies that used mass spectrometry techniques and summarize relevant proteomic NAFLD candidate biomarkers.

Methods: Medline and Embase databases were searched from inception to December 2014.

Results: A final number of 22 records were included that identified 251 candidate proteomic biomarkers. Thirty-three biomarkers were confirmed – 14 were found in liver samples, 21 in serum samples, and two from both serum and liver samples.

Conclusion: Some of the biomarkers identified have already been extensively studied regarding their diagnostic and prognostic capacity. However, there are also more potential biomarkers that still need to be addressed in future studies.     

The mitochondrial IMP peptidase of yeast: functional analysis of domains and identification of Gut2 as a new natural substrate

The mitochondrial inner membrane peptidase IMP of Saccharomyces cerevisiae is required for proteolytic processing of certain mitochondrially and nucleus-encoded proteins during their export from the matrix into the inner membrane or the intermembrane space. The membrane-associated signal peptidase complex is composed of the two catalytic subunits, Imp1 and Imp2, and the Som1 protein. The IMP subunits are thought to function in membrane association, interaction and stabilisation of subunits, substrate specificity, and proteolysis. We have analysed inner membrane peptidase mutants and substrates to gain more insight into the functions of various domains and investigate the basis of substrate recognition. The results suggest that certain conserved glycine residues in the second and third conserved regions of Imp1 and Imp2 are important for stabilisation of the Imp complex and for the proteolytic activity of the subunits, respectively. The non-conserved C-terminal parts of the Imp subunits are important for their proteolytic activities. The C-terminal region of Imp2, comprising a predicted second transmembrane segment, is dispensable for the stability of Imp2 and Imp1, and cannot functionally substitute for the C-terminal segment of Imp1. Alteration of the Imp2 cleavage site in cytochrome c ₁ (from AM to ND) reveals the specificity of the Imp2 peptidase. In addition, we have identified Gut2, the mitochondrial FAD-dependent glycerol-3-phosphate dehydrogenase, as a new substrate for Imp1. Failure to cleave the Gut2 precursor may contribute to the pet phenotype of certain imp mutants. Gut2 is associated with the inner membrane, and is essential for growth on glycerol-containing medium. Suggested functions of the analysed residues and domains of the IMP subunits, characteristics of the cleavage sites of substrates and implications for the phenotypes of imp mutants are discussed.Communicated by C. P. Hollenberg