Pancreatic cancer has the worst prognosis among all cancers. Cancer screening of body fluids may improve the survival time prognosis of patients, who are often diagnosed too late at an incurable stage. Several studies report the dysregulation of lipid metabolism in tumor cells, suggesting that changes in the blood lipidome may accompany tumor growth. Here we show that the comprehensive mass spectrometric determination of a wide range of serum lipids reveals statistically significant differences between pancreatic cancer patients and healthy controls, as visualized by multivariate data analysis. Three phases of biomarker discovery research (discovery, qualification, and verification) are applied for 830 samples in total, which shows the dysregulation of some very long chain sphingomyelins, ceramides, and (lyso)phosphatidylcholines. The sensitivity and specificity to diagnose pancreatic cancer are over 90%, which outperforms CA 19-9, especially at an early stage, and is comparable to established diagnostic imaging methods. Furthermore, selected lipid species indicate a potential as prognostic biomarkers.

The understanding of neurodegenerative diseases, traditionally considered to be well-defined entities with distinguishable clinical phenotypes, has undergone a major shift over the last 20 years. The diagnosis of neurodegenerative diseases primarily requires functional brain imaging techniques or invasive tests such as lumbar puncture to assess cerebrospinal fluid. A new biological approach and research efforts, especially in vivo, have focused on biomarkers indicating underlying proteinopathy in cerebrospinal fluid and blood serum. However, due to the complexity and heterogeneity of neurodegenerative processes within the central nervous system and the large number of overlapping clinical diagnoses, identifying individual proteinopathies is relatively difficult and often not entirely accurate. For this reason, there is an urgent need to develop laboratory methods for identifying specific biomarkers, understand the molecular basis of neurodegenerative disorders and classify the quantifiable and readily available tools that can accelerate efforts to translate the knowledge into disease-modifying therapies that can improve and simplify the areas of differential diagnosis, as well as monitor the disease course with the aim of estimating the prognosis or evaluating the effects of treatment. The aim of this review is to summarize the current knowledge about clinically relevant biomarkers in different neurodegenerative diseases.

2′-deoxy-5-ethynyluridine (EdU) has been previously shown to be a cell poison whose toxicity depends on the particular cell line. The reason is not known. Our data indicates that different efficiency of EdU incorporation plays an important role. The EdU-mediated toxicity was elevated by the inhibition of 2′-deoxythymidine 5′-monophosphate synthesis. EdU incorporation resulted in abnormalities of the cell cycle including the slowdown of the S phase and a decrease in DNA synthesis. The slowdown but not the cessation of the first cell division after EdU administration was observed in all of the tested cell lines. In HeLa cells, a 10 μM EdU concentration led to the cell death in the 100% of cells probably due to the activation of an intra S phase checkpoint in the subsequent S phase. Our data also indicates that this EdU concentration induces interstrand DNA crosslinks in HeLa cells. We suppose that these crosslinks are the primary DNA damage resulting in cell death. According to our results, the EdU-mediated toxicity is further increased by the inhibition of thymidylate synthase by EdU itself at its higher concentrations.

Background: Currently, it is not possible to predict whether patients with hyperuricemia (HUA) will develop gout and how this progression may be affected by urate-lowering treatment (ULT). Our study aimed to evaluate differences in plasma lipidome between patients with asymptomatic HUA detected ≤ 40 years (HUA ≤ 40) and > 40 years, gout patients with disease onset ≤ 40 years (Gout ≤ 40) and > 40 years, and normouricemic healthy controls (HC). Methods: Plasma samples were collected from 94 asymptomatic HUA (77% HUA ≤ 40) subjects, 196 gout patients (59% Gout ≤ 40), and 53 HC. A comprehensive targeted lipidomic analysis was performed to semi-quantify 608 lipids in plasma. Univariate and multivariate statistics and advanced visualizations were applied. Results: Both HUA and gout patients showed alterations in lipid profiles with the most significant upregulation of phosphatidylethanolamines and downregulation of lysophosphatidylcholine plasmalogens/plasmanyls. More profound changes were observed in HUA ≤ 40 and Gout ≤ 40 without ULT. Multivariate statistics differentiated HUA ≤ 40 and Gout ≤ 40 groups from HC with an overall accuracy of > 95%. Conclusion: Alterations in the lipidome of HUA and Gout patients show a significant impact on lipid metabolism. The most significant glycerophospholipid dysregulation was found in HUA ≤ 40 and Gout ≤ 40 patients, together with a correction of this imbalance with ULT.