Erratum to: Synthesis and Anticancer Activity of Functionalized Thieno[2,3-d]pyrimidine Compounds and Their Triazinyl and Tetrazinyl Derivatives

Russian Journal of Bioorganic Chemistry - erratum     

Recognition of gluconeogenic enzymes; Icl1, Fbp1, and Mdh2 by Gid4 ligase: A molecular docking study

The pro/N‐degron pathway is an evolved protein degradation pathway through the ubiquitin‐proteasome system. It is a vital pathway to attain protein homeostasis inside the liver cells with varying glucose levels. N‐terminal proline exists in more than 300 proteins in Saccharomyces cerevisiae, but only three of them are the gluconeogenic enzymes; isocitrate lyase (Icl1), fructose‐1,6‐bisphosphatase (Fbp1), and malate dehydrogenase (Mdh2). The present in silico study aims to structurally illustrate the binding of Icl1 enzyme to Gid4 ligase concerning its peers; Fbp1 and Mdh2. Based on the molecular docking scores and interactions, one can attribute the binding stability of Gid4 with degrons, to peptides of length six up to eight from the N‐terminal. Moreover, the percent change in the docking score provides a rationale for the unique Gid4‐Icl1^1‐4 interaction. The present study provides insights on the binding attitude of Gid4 ligase to degrons of different lengths, so one will consider in designing peptidomimetics to target Gid4 ligase.     

Proteomic Differences Between Hepatocellular Carcinoma and Nontumorous Liver Tissue Investigated by a Combined Gel-based and Label-free Quantitative Proteomics Study

Proteomics-based clinical studies have been shown to be promising strategies for the discovery of novel biomarkers of a particular disease. Here, we present a study of hepatocellular carcinoma (HCC) that combines complementary two-dimensional difference in gel electrophoresis (2D-DIGE) and liquid chromatography (LC-MS)-based approaches of quantitative proteomics. In our proteomic experiments, we analyzed a set of 14 samples (7 × HCC versus 7 × nontumorous liver tissue) with both techniques. Thereby we identified 573 proteins that were differentially expressed between the experimental groups. Among these, only 51 differentially expressed proteins were identified irrespective of the applied approach. Using Western blotting and immunohistochemical analysis the regulation patterns of six selected proteins from the study overlap (inorganic pyrophosphatase 1 (PPA1), tumor necrosis factor type 1 receptor-associated protein 1 (TRAP1), betaine-homocysteine S-methyltransferase 1 (BHMT)) were successfully verified within the same sample set. In addition, the up-regulations of selected proteins from the complements of both approaches (major vault protein (MVP), gelsolin (GSN), chloride intracellular channel protein 1 (CLIC1)) were also reproducible. Within a second independent verification set (n = 33) the altered protein expression levels of major vault protein and betaine-homocysteine S-methyltransferase were further confirmed by Western blots quantitatively analyzed via densitometry. For the other candidates slight but nonsignificant trends were detectable in this independent cohort. Based on these results we assume that major vault protein and betaine-homocysteine S-methyltransferase have the potential to act as diagnostic HCC biomarker candidates that are worth to be followed in further validation studies.Hepatocellular carcinoma (HCC)¹ currently is the fifth most common malignancy worldwide with an annual incidence up to 500 per 100,000 individuals depending on the geographic region investigated. Whereas 80% of new cases occur in developing countries, the incidence increases in industrialized nations including Western Europe, Japan, and the United States (1). To manage patients with HCC, tumor markers are very important tools for diagnosis, indicators of disease progression, outcome prediction, and evaluation of treatment efficacy. Several tumor markers have been reported for HCC, including α-fetoprotein (AFP) (2), Lens culinaris agglutinin-reactive fraction of AFP (AFP-L3) (3), and des-γ-carboxyl prothrombin (DCP) (4). However, none of these tumor markers show 100% sensitivity or specificity, which calls for new and better biomarkers.To identify novel biomarkers of HCC, many clinical studies using “omics”-based methods have been reported over the past decade (5–6). In particular, the proteomics-based approach has turned out to be a promising one, offering several quantification techniques to reveal differences in protein expression that are caused by a particular disease. In most studies, the well-established 2D-DIGE technique has been applied for protein quantification followed by identification via mass spectrometry (7–15). Even if the quantification is very accurate and sensitive in this gel-based approach, the relatively high amount of protein sample necessary for protein identification is the major disadvantage of this technique. Several mass-spectrometry-based quantitative studies using labeling-techniques like SILAC (stable isotope labeling by amino acids in cell culture) or iTRAQ (isobaric tags for relative and absolute quantification) have also been carried out for biomarker discovery of HCC (16–18). Here, the concomitant protein quantification and identification in a mass spectrometer allows high-throughput analyses. However, such experiments imply additional labeling reactions (in case of iTRAQ) or are limited to tissue culture systems (in case of SILAC). In the latter case, one can overcome the limitation by using the isotope-labeled proteins obtained from tissue culture as an internal standard added to a corresponding tissue sample. This approach is known as CDIT (culture-derived isotope tags) and was applied in a HCC study, very recently (19). Label-free proteomics approaches based on quantification by ion-intensities or spectral counting offer another possibility for biomarker discovery. These approaches are relatively cheap compared with the labeling approaches, because they do not require any labeling reagents and furthermore they allow for high-throughput and sensitive analyses in a mass spectrometer. A quantitative study of HCC using spectral counting has been reported (20), whereas to our knowledge an ion-intensity-based study has not been performed yet. Apart from these quantification strategies, protein alterations in HCC have been studied by MALDI imaging, as well. Here, the authors could show that based on its proteomic signature, hepatocellular carcinoma can be discriminated with high accuracy from liver metastasis samples or other cancer types (21) as well as liver cirrhosis (22). Based on these results, it could be assumed that MALDI imaging might be a promising alternative to standard histological methods in the future.Here, we report a quantitative proteomic study that combines two different techniques, namely the well-established 2D-DIGE approach and a label-free ion-intensity-based quantification via mass spectrometry and liquid chromatography. To our knowledge this is the first time such a combined study was performed with regard to hepatocellular carcinoma. By comparing the results of both studies, we aim to identify high-confident biomarker candidates of HCC, as gel- and LC-MS-based techniques are complementary. To verify the differential protein expressions detected in our proteomic studies we performed additional immunological verifications for selected proteins within two different sample sets (Fig. 1).Open in a separate windowFig. 1.Schematic representation of the applied workflow.     

The PPARα agonist fenofibrate suppresses B-cell lymphoma in mice by modulating lipid metabolism

Obesity is associated with an increased risk for malignant lymphoma development. We used Bcr/Abl transformed B cells to determine the impact of aggressive lymphoma formation on systemic lipid mobilization and turnover. In wild-type mice, tumor size significantly correlated with depletion of white adipose tissues (WAT), resulting in increased serum free fatty acid (FFA) concentrations which promote B-cell proliferation in vitro. Moreover, B-cell tumor development induced hepatic lipid accumulation due to enhanced hepatic fatty acid (FA) uptake and impaired FA oxidation. Serum triglyceride, FFA, phospholipid and cholesterol levels were significantly elevated. Consistently, serum VLDL/LDL-cholesterol and apolipoprotein B levels were drastically increased. These findings suggest that B-cell tumors trigger systemic lipid mobilization from WAT to the liver and increase VLDL/LDL release from the liver to promote tumor growth. Further support for this concept stems from experiments where we used the peroxisome proliferator-activated receptor α (PPARα) agonist and lipid-lowering drug fenofibrate that significantly suppressed tumor growth independent of angiogenesis and inflammation. In addition to WAT depletion, fenofibrate further stimulated FFA uptake by the liver and restored hepatic FA oxidation capacity, thereby accelerating the clearance of lipids released from WAT. Furthermore, fenofibrate blocked hepatic lipid release induced by the tumors. In contrast, lipid utilization in the tumor tissue itself was not increased by fenofibrate which correlates with extremely low expression levels of PPARα in B-cells. Our data show that fenofibrate associated effects on hepatic lipid metabolism and deprivation of serum lipids are capable to suppress B-cell lymphoma growth which may direct novel treatment strategies. This article is part of a Special Issue entitled Lipid Metabolism in Cancer.     

Reconstructing Coherent Networks from Electroencephalography and Magnetoencephalography with Reduced Contamination from Volume Conduction or Magnetic Field Spread

Volume conduction (VC) and magnetic field spread (MFS) induce spurious correlations between EEG/MEG sensors, such that the estimation of functional networks from scalp recordings is inaccurate. Imaginary coherency [1] reduces VC/MFS artefacts between sensors by assuming that instantaneous interactions are caused predominantly by VC/MFS and do not contribute to the imaginary part of the cross-spectral densities (CSDs). We propose an adaptation of the dynamic imaging of coherent sources (DICS) [2] - a method for reconstructing the CSDs between sources, and subsequently inferring functional connectivity based on coherences between those sources. Firstly, we reformulate the principle of imaginary coherency by performing an eigenvector decomposition of the imaginary part of the CSD to estimate the power that only contributes to the non-zero phase-lagged (NZPL) interactions. Secondly, we construct an NZPL-optimised spatial filter with two a priori assumptions: (1) that only NZPL interactions exist at the source level and (2) the NZPL CSD at the sensor level is a good approximation of the projected source NZPL CSDs. We compare the performance of the NZPL method to the standard method by reconstructing a coherent network from simulated EEG/MEG recordings. We demonstrate that, as long as there are phase differences between the sources, the NZPL method reliably detects the underlying networks from EEG and MEG. We show that the method is also robust to very small phase lags, noise from phase jitter, and is less sensitive to regularisation parameters. The method is applied to a human dataset to infer parts of a coherent network underpinning face recognition.     

Virulence of infecting Helicobacter pyloristrains and intensity of mononuclear cell infiltration are associated with levels of DNA hypermethylation in gastric mucosae

DNA methylation changes are known to occur in gastric cancers and in premalignant lesions of the gastric mucosae. In order to examine variables associated with methylation levels, we quantitatively evaluated DNA methylation in tumors, non-tumor gastric mucosae, and in gastric biopsies at promoters of 5 genes with methylation alterations that discriminate gastric cancers from non-tumor epithelia (EN1, PCDH10, RSPO2, ZIC1, and ZNF610). Among Colombian subjects at high and low risk for gastric cancer, biopsies from subjects from the high-risk region had significantly higher levels of methylation at these 5 genes than samples from subjects in the low risk region (p ≤ 0.003). When results were stratified by Helicobacter pylori infection status, infection with a cagA positive, vacA s1m1 strain was significantly associated with highest methylation levels, compared with other strains (p = 0.024 to 0.001). More severe gastric inflammation and more advanced precancerous lesions were also associated with higher levels of DNA methylation (p ≤ 0.001). In a multivariate model, location of residence of the subject and the presence of cagA and vacA s1m1 in the H. pylori strain were independent variables associated with higher methylation in all 5 genes. High levels of mononuclear cell infiltration were significantly related to methylation in PCDH10, RSPO2, and ZIC1 genes. These results indicate that for these genes, levels of methylation in precancerous lesions are related to H. pylori virulence, geographic region and measures of chronic inflammation. These genes seem predisposed to sustain significant quantitative changes in DNA methylation at early stages of the gastric precancerous process.     

External Validation of the Derived Neutrophil to Lymphocyte Ratio as a Prognostic Marker on a Large Cohort of Pancreatic Cancer Patients

Background

With growing evidence on the role of inflammation in cancer biology, the presence of a systemic inflammatory response has been postulated as having prognostic significance in a wide range of cancer types. The derived neutrophil to lymphocyte ratio (dNLR), which represents an easily determinable potential prognostic marker in daily practise and clinical trials, has never been externally validated in pancreatic cancer (PC) patients.

Methods

Data from 474 consecutive PC patients, treated between 2004 and 2012 at a single centre, were evaluated retrospectively. Cancer-specific survival (CSS) was assessed using the Kaplan-Meier method. To evaluate the prognostic relevance of dNLR, univariate and multivariate Cox regression models were applied.

Results

We calculated by ROC analysis a cut-off value of 2.3 for the dNLR to be ideal to discriminate between patients’ survival in the whole cohort. Kaplan-Meier curve reveals a dNLR≥2.3 as a factor for decreased CSS in PC patients (p<0.001, log-rank test). An independent significant association between high dNLR≥2.3 and poor clinical outcome in multivariate analysis (HR = 1.24, CI95% = 1.01–1.51, p = 0.041) was identified.

Conclusion

In the present study we confirmed elevated pre-treatment dNLR as an independent prognostic factor for clinical outcome in PC patients. Our data encourage independent replication in other series and settings of this easily available parameter as well as stratified analysis according to tumor resectability.     

Clinical significance of plasma MMP‐2 and MMP‐9 levels as biomarkers for tumor expression in breast cancer patients in Egypt

Matrix metallopeptidase 2 (MMP-2) and matrix metallopeptidase 9 (MMP-9) are involved in the breakdown of extracellular matrix in normal physiological processes as well as in disease processes, such as cancer metastasis. We conducted this work to study the role of MMP-2 and MMP-9 in breast cancer by measuring their plasma concentrations before and after surgery. Also, to examine if their levels can reflect the stage of disease and prognosis. Forty-eight breast cancer patients and 13 patients with benign breast diseases were included in the study. MMP-2 and MMP-9 levels were measured by ELISA and semi-quantitative real-time PCR. MMP-2 and MMP-9 levels in plasma were determined by ELISA immediately before surgery and during 6 to 12 months after curative surgery. We observed a significant increase in the level of MMP-9 mRNA expression in breast cancer patients in comparison to their normal breast tissues and to tissues of benign breast disease. In all TNM tumor stages, the plasma levels of MMP-2 and MMP-9 were increased significantly before curative surgery in the studied patients with breast carcinoma and decreased significantly after surgery. Both MMP-2 and MMP-9 may be used as a possible marker for follow-up or as a marker that reflects the response of the disease to treatment.