BACKGROUND: Multiple myeloma (MM) represents the second most common hematological malignancy characterized by the infiltration of the bone marrow by plasma cells that produce monoclonal immunoglobulin. While the quality and length of life of MM patients have significantly increased, MM remains a hard-to-treat disease; almost all patients relapse. As MM is highly heterogenous, patients relapse at different times. It is currently not possible to predict when relapse will occur; numerous studies investigating the dysregulation of non-coding RNA molecules in cancer suggest that microRNAs could be good markers of relapse. RESULTS: Using small RNA sequencing, we profiled microRNA expression in peripheral blood in three groups of MM patients who relapsed at different intervals. In total, 24 microRNAs were significantly dysregulated among analyzed subgroups. Independent validation by RT-qPCR confirmed changed levels of miR-598-3p in MM patients with different times to relapse. At the same time, differences in the mass spectra between groups were identified using matrix-assisted laser desorption/ionization time of flight mass spectrometry. All results were analyzed by machine learning. CONCLUSION: Mass spectrometry coupled with machine learning shows potential as a reliable, rapid, and cost-effective preliminary screening technique to supplement current diagnostics.
- Publikační typ
- časopisecké články MeSH
Spinal cord injury (SCI) often leads to central neuropathic pain, a condition associated with significant morbidity and is challenging in terms of the clinical management. Despite extensive efforts, identifying effective biomarkers for neuropathic pain remains elusive. Here we propose a novel approach combining matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) with artificial neural networks (ANNs) to discriminate between mass spectral profiles associated with chronic neuropathic pain induced by SCI in female mice. Functional evaluations revealed persistent chronic neuropathic pain following mild SCI as well as minor locomotor disruptions, confirming the value of collecting serum samples. Mass spectra analysis revealed distinct profiles between chronic SCI and sham controls. On applying ANNs, 100% success was achieved in distinguishing between the two groups through the intensities of m/z peaks. Additionally, the ANNs also successfully discriminated between chronic and acute SCI phases. When reflexive pain response data was integrated with mass spectra, there was no improvement in the classification. These findings offer insights into neuropathic pain pathophysiology and underscore the potential of MALDI-TOF MS coupled with ANNs as a diagnostic tool for chronic neuropathic pain, potentially guiding attempts to discover biomarkers and develop treatments.
- MeSH
- biologické markery krev MeSH
- chronická bolest krev diagnóza etiologie MeSH
- myši inbrední C57BL MeSH
- myši MeSH
- neuralgie * krev diagnóza etiologie MeSH
- neuronové sítě * MeSH
- poranění míchy * komplikace krev MeSH
- spektrometrie hmotnostní - ionizace laserem za účasti matrice * metody MeSH
- zvířata MeSH
- Check Tag
- myši MeSH
- ženské pohlaví MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
Multiple myeloma (MM) is the second most prevalent hematological malignancy, characterized by infiltration of the bone marrow by malignant plasma cells. Extramedullary disease (EMD) represents a more aggressive condition involving the migration of a subclone of plasma cells to paraskeletal or extraskeletal sites. Liquid biopsies could improve and speed diagnosis, as they can better capture the disease heterogeneity while lowering patients' discomfort due to minimal invasiveness. Recent studies have confirmed alterations in the proteome across various malignancies, suggesting specific changes in protein classes. In this study, we show that MALDI-TOF mass spectrometry fingerprinting of peripheral blood can differentiate between MM and primary EMD patients. We constructed a predictive model using a supervised learning method, partial least squares-discriminant analysis (PLS-DA) and evaluated its generalization performance on a test dataset. The outcome of this analysis is a method that predicts specifically primary EMD with high sensitivity (86.4%), accuracy (78.4%), and specificity (72.4%). Given the simplicity of this approach and its minimally invasive character, this method provides rapid identification of primary EMD and could prove helpful in clinical practice.
- MeSH
- lidé středního věku MeSH
- lidé MeSH
- mnohočetný myelom * krev diagnóza MeSH
- nádorové biomarkery krev MeSH
- senioři MeSH
- spektrometrie hmotnostní - ionizace laserem za účasti matrice metody MeSH
- tekutá biopsie metody MeSH
- Check Tag
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
Pathological pain subtypes can be classified as either neuropathic pain, caused by a somatosensory nervous system lesion or disease, or nociplastic pain, which develops without evidence of somatosensory system damage. Since there is no gold standard for the diagnosis of pathological pain subtypes, the proper classification of individual patients is currently an unmet challenge for clinicians. While the determination of specific biomarkers for each condition by current biochemical techniques is a complex task, the use of multimolecular techniques, such as matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), combined with artificial intelligence allows specific fingerprints for pathological pain-subtypes to be obtained, which may be useful for diagnosis. We analyzed whether the information provided by the mass spectra of serum samples of four experimental models of neuropathic and nociplastic pain combined with their functional pain outcomes could enable pathological pain subtype classification by artificial neural networks. As a result, a simple and innovative clinical decision support method has been developed that combines MALDI-TOF MS serum spectra and pain evaluation with its subsequent data analysis by artificial neural networks and allows the identification and classification of pathological pain subtypes in experimental models with a high level of specificity.
Monoclonal gammopathies are a group of blood diseases characterized by presence of abnormal immunoglobulins in peripheral blood and/or urine of patients. Multiple myeloma and plasma cell leukemia are monoclonal gammopathies with unclear etiology, caused by malignant transformation of bone marrow plasma cells. Mass spectrometry with matrix-assisted laser desorption/ionization and time-of-flight detection is commonly used for investigation of the peptidome and small proteome of blood plasma with high accuracy, robustness, and cost-effectivity. In addition, mass spectrometry coupled with advanced statistics can be used for molecular profiling, classification, and diagnosis of liquid biopsies and tissue specimens in various malignancies. Despite the fact there have been fully optimized protocols for mass spectrometry of normal blood plasma available for decades, in monoclonal gammopathy patients, the massive alterations of biophysical and biochemical parameters of peripheral blood plasma often limit the mass spectrometry measurements. In this paper, we present a new two-step extraction protocol and demonstrated the enhanced resolution and intensity (>50×) of mass spectra obtained from extracts of peripheral blood plasma from monoclonal gammopathy patients. When coupled with advanced statistics and machine learning, the mass spectra profiles enabled the direct identification, classification, and discrimination of multiple myeloma and plasma cell leukemia patients with high accuracy and precision. A model based on PLS-DA achieved the best performance with 71.5% accuracy (95% confidence interval, CI = 57.1-83.3%) when the 10× repeated 5-fold CV was performed. In summary, the two-step extraction protocol improved the analysis of monoclonal gammopathy peripheral blood plasma samples by mass spectrometry and provided a tool for addressing the complex molecular etiology of monoclonal gammopathies.
BACKGROUND: The progenitors to lung airway epithelium that are capable of long-term propagation may represent an attractive source of cells for cell-based therapies, disease modeling, toxicity testing, and others. Principally, there are two main options for obtaining lung epithelial progenitors: (i) direct isolation of endogenous progenitors from human lungs and (ii) in vitro differentiation from some other cell type. The prime candidates for the second approach are pluripotent stem cells, which may provide autologous and/or allogeneic cell resource in clinically relevant quality and quantity. METHODS: By exploiting the differentiation potential of human embryonic stem cells (hESC), here we derived expandable lung epithelium (ELEP) and established culture conditions for their long-term propagation (more than 6 months) in a monolayer culture without a need of 3D culture conditions and/or cell sorting steps, which minimizes potential variability of the outcome. RESULTS: These hESC-derived ELEP express NK2 Homeobox 1 (NKX2.1), a marker of early lung epithelial lineage, display properties of cells in early stages of surfactant production and are able to differentiate to cells exhibitting molecular and morphological characteristics of both respiratory epithelium of airway and alveolar regions. CONCLUSION: Expandable lung epithelium thus offer a stable, convenient, easily scalable and high-yielding cell source for applications in biomedicine.
Intact (whole) cell matrix-assisted laser desorption/ionization mass spectrometry (MALDI-TOF MS) is an established method for biotyping in clinical microbiology as well as for revealing phenotypic shifts in cultured eukaryotic cells. Intact cell MALDI-TOF MS has recently been introduced as a quality control tool for long-term cultures of pluripotent stem cells. Despite the potential this method holds for revealing minute changes in cells, there is still a need for improving the ionization efficiency or peak reproducibility. Here we report for the first time that supplementation by fine particles of black phosphorus to the standard MALDI matrices, such as sinapinic and α-cyano-4-hydroxycinnamic acids enhance intensities of mass spectra of particular amino acids and peptides, presumably by interactions with aromatic groups within the molecules. In addition, the particles of black phosphorus induce the formation of small and regularly dispersed crystals of sinapinic acid and α-cyano-4-hydroxycinnamic acid with the analyte on a steel MALDI target plate. Patterns of mass spectra recorded from intact cells using black phosphorus-enriched matrix were more reproducible and contained peaks of higher intensities when compared to matrix without black phosphorus supplementation. In summary, enrichment of common organic matrices by black phosphorus can improve discrimination data analysis by enhancing peak intensity and reproducibility of mass spectra acquired from intact cells.
- MeSH
- aminokyseliny analýza chemie MeSH
- buněčné kultury metody MeSH
- buněčné linie MeSH
- fosfor chemie MeSH
- lidé MeSH
- lidské embryonální kmenové buňky MeSH
- peptidy analýza chemie MeSH
- reprodukovatelnost výsledků MeSH
- spektrometrie hmotnostní - ionizace laserem za účasti matrice metody normy MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Simple molecular descriptors of extensive series of 1,3,5-triazinyl sulfonamide derivatives, based on the structure of sulfonamides and their physicochemical properties, were designed and calculated. These descriptors were successfully applied as inputs for artificial neural network (ANN) modelling of the relationship between the structure and biological activity. The optimized ANN architecture was applied to the prediction of the inhibition activity of 1,3,5-triazinyl sulfonamides against human carbonic anhydrase (hCA) II, tumour-associated hCA IX, and their selectivity (hCA II/hCA IX).
- MeSH
- antigeny nádorové metabolismus MeSH
- inhibitory karboanhydras chemie metabolismus MeSH
- karboanhydrasa II antagonisté a inhibitory metabolismus MeSH
- karboanhydrasa IX antagonisté a inhibitory metabolismus MeSH
- lidé MeSH
- neuronové sítě * MeSH
- racionální návrh léčiv MeSH
- sulfonamidy chemie metabolismus MeSH
- triaziny chemie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
The novel copper complex [Cu(phen)2(salubrinal)](ClO4)2 (C0SAL) has been synthesised and characterised. Copper(ii) is coordinated by salubrinal through the thionic group, as shown by the UV-Vis, IR, ESI-MS and tandem mass results, together with the theoretical calculations. The formed complex showed a DPPH radical scavenging ability higher than that of salubrinal alone. Studies on lipid oxidation inhibition showed that the C0SAL concentration, required to inhibit the enzyme, was lower than that of salubrinal. The inhibition of the enzyme could take place via allosteric modulation, as suggested by docking calculations. C0SAL showed a good cytotoxic activity on A2780 cells, 82 fold higher than that of the precursor salubrinal and 1.4 fold higher than that of [Cu(phen)2(H2O)](ClO4)2. Treatment with C0SAL in SKOV3 ovarian cancer cells induced expression of GRP-78 and DDIT3 regulators of ER-stress response. The cytotoxic effect of C0SAL was reverted in the presence of TUDCA, suggesting that C0SAL induces cell death through ER-stress. In A2780 cells treated with C0SAL γ-H2AX was accumulated, suggesting that DNA damage was also involved.
- MeSH
- antivirové látky farmakologie MeSH
- cinnamáty farmakologie MeSH
- fenantroliny farmakologie MeSH
- kyselina taurochenodeoxycholová farmakologie MeSH
- lidé MeSH
- magnetická rezonanční spektroskopie MeSH
- měď farmakologie MeSH
- molekulární struktura MeSH
- nádorové buněčné linie MeSH
- peroxidace lipidů účinky léků MeSH
- poškození DNA účinky léků genetika MeSH
- thiomočovina analogy a deriváty farmakologie MeSH
- transkripční faktor CHOP genetika metabolismus MeSH
- transmisní elektronová mikroskopie MeSH
- viabilita buněk účinky léků MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
