Laser ablation synthesis of tellurium carbides using tellurium with nanodiamond nanocomposite.

RATIONALE: Carbides, including tellurium carbides (TeC), play crucial roles in diverse applications, but TeC synthesis has not been described in the literature. Laser ablation synthesis (LAS) coupled with mass spectrometry was used here for in situ TeC clusters synthesis and identification of the reaction products to better understand TeC formation. METHODS: Laser desorption ionization time-of-flight mass spectrometry (LDI-TOFMS) was used to generate the TeC clusters and determine their stoichiometry via computer modeling of isotopic patterns. RESULTS: A simple one-pot procedure was developed for Te-nanodiamond nanocomposite preparation. A suspension of fine-powdered Te was mixed with a suspension of nanodiamonds (both in acetonitrile), and the resulting precipitated nanocomposite was suitable for the synthesis of TemCn clusters using LDI. Various unary and binary clusters were formed. The stoichiometry of the novel TemCn clusters, determined via computer modeling of isotopic patterns, is reported here for the first time. CONCLUSIONS: The Te-nanodiamond composite was found to be the most suitable precursor for the generation of TemCn clusters. In total, 35 binary TemCn clusters were identified, when several of them were not obtained using commercial TeC material.

Combined efficacy of Cinnamomum zeylanicum and doxorubicin against leukemia through regulation of TRAIL and NF-kappa B pathways in rat model.

BACKGROUND: Recent discoveries in cancer therapeutics have proven combination therapies more effective than individual drugs. This study describes the efficacy of the combination of Cinnamomum zeylanicum and doxorubicin against benzene-induced leukemia. METHODS AND RESULTS: Brine shrimp assay was used to assess the cytotoxicity of C. zeylanicum, doxorubicin and their combination. After AML induction in Sprague Dawley rats, the same drugs were given to rat groups. Changes in organ weight, haematological profile, and hepatic enzymes were determined. Real-time PCR was used to elucidate the effect on the expression of STMN1, GAPDH, P53 and various TRAIL and NF-kappaB components. C. zeylanicum reduced the cytotoxicity of doxorubicin. The combination treatment showed better anti-leukemic results than any of the individual drugs as evident from STMN1 expression (p < 0.001). It was particularly effective in reducing total white blood cell counts and recovering lymphocytes, monocytes and eosinophils along with hepatic enzymes ALT and AST (p < 0.001). All doses recovered relative organ weights and improved blood parameters. The combination therapy was particularly effective in inducing apoptosis, inhibition of proliferation marker GAPDH (p < 0.001) and NF-kappaB pathway components Rel-A (p < 0.001) and Rel-B (p < 0.01). Expressions of TRAIL components c-FLIP (p < 0.001), TRAIL ligand (p < 0.001) and caspase 8 (p < 0.01) were also altered. CONCLUSION: Cinnamomum zeylanicum in combination with doxorubicin helps to counter benzene-induced cellular and hepatic toxicity and improves haematological profile. The anti-leukemic effects are potentially due to inhibition of GAPDH and NF-kappa B pathway, and through regulation of TRAIL pathway. Our data suggests the use of C. zeylanicum with doxorubicin to improve anti-leukemic therapeutic regimes.

Copper(II) Phenanthroline-Based Complexes as Potential AntiCancer Drugs: A Walkthrough on the Mechanisms of Action.

Copper is an endogenous metal ion that has been studied to prepare a new antitumoral agent with less side-effects. Copper is involved as a cofactor in several enzymes, in ROS production, in the promotion of tumor progression, metastasis, and angiogenesis, and has been found at high levels in serum and tissues of several types of human cancers. Under these circumstances, two strategies are commonly followed in the development of novel anticancer Copper-based drugs: the sequestration of free Copper ions and the synthesis of Copper complexes that trigger cell death. The latter strategy has been followed in the last 40 years and many reviews have covered the anticancer properties of a broad spectrum of Copper complexes, showing that the activity of these compounds is often multi factored. In this work, we would like to focus on the anticancer properties of mixed Cu(II) complexes bearing substituted or unsubstituted 1,10-phenanthroline based ligands and different classes of inorganic and organic auxiliary ligands. For each metal complex, information regarding the tested cell lines and the mechanistic studies will be reported and discussed. The exerted action mechanisms were presented according to the auxiliary ligand/s, the metallic centers, and the increasing complexity of the compound structures.

Laser ablation synthesis of carbon-phosphides from graphene/nanodiamond-phosphorus composite precursors: Laser desorption ionisation time-of-flight mass spectrometry.

RATIONALE: Carbon-phosphides are new and promising strategic materials with applications e.g. in optoelectronics. However, their chemistry and methods of synthesis are not completely understood, and only a limited number of C-P clusters have been detected up to now. Laser ablation synthesis (LAS) or laser desorption ionisation (LDI) has great potential to generate Cm Pn clusters in the gas phase and to act as the basis for the development of new technology. METHODS: The LAS of carbon phosphides using mixtures of nano-carbon sources (graphene, nanodiamonds) with phosphorus allotropes (red, black, and phosphorene) was examined. Since phosphorene is not commercially available, it was synthesised. A reflectron time-of-flight mass spectrometer was used to produce and identify the C-P clusters. A transmission electron microscope was used to characterise the prepared composites. RESULTS: LDI of various carbon-phosphorus composites generated a range of carbon-phosphides. From graphene-red phosphorus, Cm P+ (m = 3-47), Cm P2 + (m = 2-44), Cm P3 + (m = 1-42), Cm P4 + (m = 1-39), Cm P5 + (m = 1-37), Cm P6 + (m = 1-34), Cm P7 + (m = 1-31), Cm P8 + (m = 1-29), Cm P9 + (m = 1-26), Cm P10 + (m = 1-24), Cm P11 + (m = 1-21), and Cm P12 + (m = 1-19) clusters were detected, while nanodiamond composites with red/black phosphorus and with phosphorene yielded C24 P5 + 2n + (n = 0-28), C24 P5 + 2n + (n = 0-16), and C24 P5 + 2n + (n = 0-14) clusters, respectively. In total, over 300 new carbon-phosphide clusters were generated. CONCLUSIONS: The novel series of carbon-phosphide clusters generated from graphene or nanodiamond composites with red/black phosphorus or with phosphorene demonstrated rich carbon-phosphide chemistry that might inspire the development of novel nano-materials with specific properties.

Mass spectrometric discrimination of phospholipid patterns in cisplatin-resistant and -sensitive cancer cells.

RATIONALE: Development of therapy-resistant cancer is a major problem in clinical oncology, and there is an urgent need for novel markers identifying development of the resistant phenotype. Lipidomics represents a promising approach to discriminate lipid profiles of malignant phenotype cells. Alterations in phospholipid distribution or chemical composition have been reported in various pathologies including cancer. Here we were curious whether quantitative differences in phospholipid composition between cisplatin-resistant and -sensitive model cancer cell lines could be revealed by mass spectrometric means. METHODS: The phospholipid contents of cell membranes of the cancer cell lines CCRF-CEM and A2780, both responsive and resistant to cisplatin, were analyzed by solid-phase extraction (SPE) and electrospray ionization mass spectrometry (ESI-MS and tandem mass spectrometry (MS/MS)). Extracts were obtained by disruption of cells with a dounce tissue grinder set followed by centrifugation. To minimize the enzymatic activity, phospholipids were extracted from cell extracts by SPE immediately after the cell lysis and analyzed by MS. Both supernatant and pellet fractions of cell extracts were analyzed. RESULTS: A phospholipid profile specific for cell lines and their phenotypes was revealed. We have documented by quantitative analysis that phosphocholines PC P-34:0, PC 34:1, PC 20:2_16:0, LPC 18:1 and LPC 16:0 PLs were present in the 200-400 µM concentration range in CCRF-CEM cisplatin-responsive cells, but absent in their cisplatin-resistant cells. Similarly, PC 34:1, LPC 18:1 and LPC 16:0 were increased in cisplatin-responsive A2780 cells, and PC 20:2_16:0 was downregulated in cisplatin-resistant A2780 cells. CONCLUSIONS: In this work we showed that the ESI-MS analysis of the lipid content of the therapy-resistant and -sensitive cells can clearly distinguish the phenotypic pattern and determine the potential tumor response to cytotoxic therapy. Lipid entities revealed by mass spectrometry and associated with development of therapy resistance can thus support molecular diagnosis and provide a potential complementary cancer biomarker.

TUSC3: functional duality of a cancer gene.

Two decades ago, following a systematic screening of LOH regions on chromosome 8p22, TUSC3 has been identified as a candidate tumor suppressor gene in ovarian, prostate and pancreatic cancers. Since then, a growing body of evidence documented its clinical importance in various other types of cancers, and first initial insights into its molecular function and phenotypic effects have been gained, though the precise role of TUSC3 in different cancers remains unclear. As a part of the oligosaccharyltransferase complex, TUSC3 localizes to the endoplasmic reticulum and functions in final steps of N-glycosylation of proteins, while its loss evokes the unfolded protein response. We are still trying to figure out how this mechanistic function is reconcilable with its varied effects on cancer promotion. In this review, we focus on cancer-related effects of TUSC3 and envisage a possible role of TUSC3 beyond endoplasmic reticulum.

Alleviation of endoplasmic reticulum stress by tauroursodeoxycholic acid delays senescence of mouse ovarian surface epithelium.

Ovarian surface epithelium (OSE) forms a single layer of mostly cuboidal cells on surface of mammalian ovaries that is inherently exposed to cell stress evoked by tissue damage every ovulation and declines morphologically after menopause. Endoplasmic reticulum (ER) is a principal cell organelle involved in proteosynthesis, but also integrating various stress signals. ER stress evokes a conserved signaling pathway, the unfolded protein response (UPR), leading to cell death or adaptation to stress conditions. In this work, we document that mouse OSE suffers from ER stress during replicative senescence in vitro, develops abnormalities in ER and initiates UPR. Attenuation of ER stress in senescent OSE by tauroursodeoxycholic acid (TUDCA) reconditions ER architecture and leads to delayed onset of senescence. In summary, we show for the first time a mutual molecular link between ER stress response and replicative senescence leading to phenotypic changes of non-malignant ovarian surface epithelium.

Tumor suppressor candidate 3 (TUSC3) prevents the epithelial-to-mesenchymal transition and inhibits tumor growth by modulating the endoplasmic reticulum stress response in ovarian cancer cells.

Ovarian cancer is one of the most common malignancies in women and contributes greatly to cancer-related deaths. Tumor suppressor candidate 3 (TUSC3) is a putative tumor suppressor gene located at chromosomal region 8p22, which is often lost in epithelial cancers. Epigenetic silencing of TUSC3 has been associated with poor prognosis, and hypermethylation of its promoter provides an independent biomarker of overall and disease-free survival in ovarian cancer patients. TUSC3 is localized to the endoplasmic reticulum in an oligosaccharyl tranferase complex responsible for the N-glycosylation of proteins. However, the precise molecular role of TUSC3 in ovarian cancer remains unclear. In this study, we establish TUSC3 as a novel ovarian cancer tumor suppressor using a xenograft mouse model and demonstrate that loss of TUSC3 alters the molecular response to endoplasmic reticulum stress and induces hallmarks of the epithelial-to-mesenchymal transition in ovarian cancer cells. In summary, we have confirmed the tumor-suppressive function of TUSC3 and identified the possible mechanism driving TUSC3-deficient ovarian cancer cells toward a malignant phenotype.

Use of flower-like gold nanoparticles in time-of-flight mass spectrometry.

RATIONALE: Many kinds of nanoparticles (NPs) have been used for mass spectrometry (MS) so far. Here we report the first use of flower-like gold nanoparticles (AuNPs) as a mediator to enhance ionization in MS of peptides and proteins. METHODS: Flower-like AuNPs were characterized using transmission and scanning electron microscopy, UV-VIS spectrophotometry, and laser desorption/ionization (LDI)-MS and compared with polyhedral AuNPs. Mass spectra were obtained in positive ion mode using a time-of-flight (TOF) analyzer coupled with either matrix-assisted laser desorption/ionization (MALDI) or surface-assisted laser desorption/ionization (SALDI) methods. RESULTS: The intensities of peptide peaks (m/z 500-3500) were up to 7.5× and up to 7× higher using flower-like AuNPs and flower-like AuNPs-enriched α-cyano-4-hydroxycinnamic acid (CHCA) matrix respectively, than the classical CHCA matrix. The signals of higher mass peptide/protein peaks (m/z 3600-17000) were up to 2× higher with using flower-like AuNPs-enriched CHCA matrix than conventional CHCA matrix. The signal of profile peaks generated by intact cell MALDI-TOFMS of fibroblast suspension (m/z 4000-20000) was 2× higher with using flower-like AuNPs combined with sinapinic acid (SA) compared to SA matrix alone. The use of flower-like AuNPs as internal calibration standard for the calibration of MS spectra of peptides was performed. CONCLUSIONS: Flower-like AuNPs and flower-like AuNPs combined with CHCA or SA as combined matrices for MS measurement of peptides and proteins were used. Comparison of the conventional MALDI method and our method with flower-like AuNPs was carried out. In addition, gold clusters generated from flower-like AuNPs by SALDI provide a suitable internal calibration standard for MS analysis of peptides. Copyright © 2015 John Wiley & Sons, Ltd.

Intravenous insulin therapy during lung resection does not affect lung function or surfactant proteins.

BACKGROUND: The surgical resection of lung disrupts glucose homeostasis and causes hyperglycemia, as in any other major surgery or critical illness. We performed a prospective study where we carefully lowered hyperglycemia by insulin administration during the surgery, and for the first time we monitored immediate insulin effects on lung physiology and gene transcription. METHODS: The levels of blood gases (pH, pCO2, pO2, HCO3-, HCO3- std, base excess, FiO2, and pO2/FiO2) were measured at the beginning of surgery, at the end of surgery, and two hours after. Samples of healthy lung tissue surrounding the tumour were obtained during the surgery, anonymized and sent for subsequent blinded qPCR analysis (mRNA levels of surfactant proteins A1, A2, B, C and D were measured). This study was done on a cohort of 64 patients who underwent lung resection. Patients were randomly divided, and half of them received insulin treatment during the surgery. RESULTS: We demonstrated for the first time that insulin administered intravenously during lung resection does not affect levels of blood gases. Furthermore, it does not induce immediate changes in the expression of surfactant proteins. CONCLUSION: According to our observations, short insulin treatment applied intravenously during resection does not affect the quality of breathing.

Pulsed laser ablation synthesis of fresh Te nanoparticles for matrix assisted laser desorption/ionization mass spectrometry (MALDI-MS) applications.

This work aims to demonstrate the potential of pulsed laser ablation synthesis (PLA) of tellurium nanoparticles (Te NPs) for use in matrix assisted laser desorption/ionization mass spectrometry (MALDI-MS) applications. An experimental laboratory setup for PLA synthesis of fresh Te NPs was designed to prevent unwanted aggregation of uncoated Te NPs and avoid the need to use additional modifiers. Performing pulsed laser ablation synthesis in liquid (PLAL) using acetone was found to be the optimal way of preparing Te NPs. Another possibility is to use commercially available laser ablation devices for laser ablation - inductively coupled plasma mass spectrometry (LA-ICP-MS) to perform PLA in a helium atmosphere, but this approach is less efficient and results in the formation of unwanted larger particles. The prepared Te NPs were studied using the transmission electron microscopy (TEM) and dynamic light scattering (DLS) methods. TEM images showed the formation of Te NP nanochains composed of many crystallized Te NPs with sizes ranging from 8 to 15 nm. The various size distributions of the synthesized Te NPs identified using the DLS method correspond to the size distributions of aggregations rather than individual Te NPs. The synthesized Te NPs were used for a pilot study of their possible use with the MALDI-MS technique. An important effect was observed when Te NPs were used to perform a MALDI-MS analysis of the α-cyclodextrin (α-CD) and cucurbit[7]uril (CB7) macrocycles, which consisted in a decline in the formation of matrix adducts. Furthermore, several changes in MALDI-MS mass spectra of intact cells and a positive effect of Te NPs on the crystallization of the MALDI-MS matrix were observed.

Intact cell mass spectrometry coupled with machine learning reveals minute changes induced by single gene silencing.

Intact (whole) cell MALDI TOF mass spectrometry is a commonly used tool in clinical microbiology for several decades. Recently it was introduced to analysis of eukaryotic cells, including cancer and stem cells. Besides targeted metabolomic and proteomic applications, the intact cell MALDI TOF mass spectrometry provides a sufficient sensitivity and specificity to discriminate cell types, isogenous cell lines or even the metabolic states. This makes the intact cell MALDI TOF mass spectrometry a promising tool for quality control in advanced cell cultures with a potential to reveal batch-to-batch variation, aberrant clones, or unwanted shifts in cell phenotype. However, cellular alterations induced by change in expression of a single gene has not been addressed by intact cell mass spectrometry yet. In this work we used a well-characterized human ovarian cancer cell line SKOV3 with silenced expression of a tumor suppressor candidate 3 gene (TUSC3). TUSC3 is involved in co-translational N-glycosylation of proteins with well-known global impact on cell phenotype. Altogether, this experimental design represents a highly suitable model for optimization of intact cell mass spectrometry and analysis of spectral data. Here we investigated five machine learning algorithms (k-nearest neighbors, decision tree, random forest, partial least squares discrimination, and artificial neural network) and optimized their performance either in pure populations or in two-component mixtures composed of cells with normal or silenced expression of TUSC3. All five algorithms reached accuracy over 90 % and were able to reveal even subtle changes in mass spectra corresponding to alterations of TUSC3 expression. In summary, we demonstrate that spectral fingerprints generated by intact cell MALDI-TOF mass spectrometry coupled to a machine learning classifier can reveal minute changes induced by alteration of a single gene, and therefore contribute to the portfolio of quality control applications in routine cell and tissue cultures.

Metabolism of primary high-grade serous ovarian carcinoma (HGSOC) cells under limited glutamine or glucose availability.

BACKGROUND: High-grade serous ovarian carcinoma (HGSOC) is the most common and aggressive subtype of epithelial ovarian carcinoma. It is primarily diagnosed at stage III or IV when the 5-year survival rate ranges between 20% and 40%. Here, we aimed to validate the hypothesis, based on HGSOC cell lines, that proposed the existence of two distinct groups of HGSOC cells with high and low oxidative phosphorylation (OXPHOS) metabolism, respectively, which are associated with their responses to glucose and glutamine withdrawal. METHODS: We isolated and cultivated primary cancer cell cultures from HGSOC and nontransformed ovarian fibroblasts from the surrounding ovarium of 45 HGSOC patients. We tested the metabolic flexibility of the primary cells, particularly in response to glucose and glutamine depletion, analyzed and modulated endoplasmic reticulum stress, and searched for indices of the existence of previously reported groups of HGSOC cells with high and low OXPHOS metabolism. RESULTS: The primary HGSOC cells did not form two groups with high and low OXPHOS that responded differently to glucose and glutamine availabilities in the cell culture medium. Instead, they exhibited a continuum of OXPHOS phenotypes. In most tumor cell isolates, the responses to glucose or glutamine withdrawal were mild and surprisingly correlated with those of nontransformed ovarian fibroblasts from the same patients. The growth of tumor-derived cells in the absence of glucose was positively correlated with the lipid trafficking regulator FABP4 and was negatively correlated with the expression levels of HK2 and HK1. The correlations between the expression of electron transport chain (ETC) proteins and the oxygen consumption rates or extracellular acidification rates were weak. ER stress markers were strongly expressed in all the analyzed tumors. ER stress was further potentiated by tunicamycin but not by the recently proposed ER stress inducers based on copper(II)-phenanthroline complexes. ER stress modulation increased autophagy in tumor cell isolates but not in nontransformed ovarian fibroblasts. CONCLUSIONS: Analysis of the metabolism of primary HGSOC cells rejects the previously proposed hypothesis that there are distinct groups of HGSOC cells with high and low OXPHOS metabolism that respond differently to glutamine or glucose withdrawal and are characterized by ETC protein levels.

Ex-vivo 3D cellular models of pancreatic ductal adenocarcinoma: from embryonic development to precision oncology.

ABSTRACT: Pancreas is a vital gland of gastro-intestinal system with exocrine and endocrine secretory functions, interweaved into essential metabolic circuitries of the human body. Pancreatic ductal adenocarcinoma (PDAC) represents one of the most lethal malignancies, with a five-year survival rate of 11%. This poor prognosis is primarily attributed to the absence of early symptoms, rapid metastatic dissemination, and the limited efficacy of current therapeutic interventions. Despite recent advancements in understanding the etiopathogenesis and treatment of PDAC, there remains a pressing need for improved individualized models, the identification of novel molecular targets, and the development of unbiased predictors of disease progression. Here we aim to explore the concept of precision medicine utilizing three-dimensional, patient-specific cellular models of pancreatic tumors and discuss their potential applications in uncovering novel druggable molecular targets and predicting clinical parameters for individual patients.

Liquid biopsy of peripheral blood using mass spectrometry detects primary extramedullary disease in multiple myeloma patients.

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.

Methylation status of TUSC3 is a prognostic factor in ovarian cancer.

BACKGROUND: Current prognostic information in ovarian cancer is based on tumor stage, tumor grade, and postoperative tumor size. Reliable molecular prognostic markers are scarce. In this article, the authors describe epigenetic events in a frequently deleted region on chromosome 8p22 that influence the expression of tumor suppressor candidate 3 (TUSC3), a putative tumor suppressor gene in ovarian cancer. METHODS: Messenger RNA expression and promoter hypermethylation of TUSC3 were studied in ovarian cancer cell lines and in tumor samples from 2 large, independent ovarian cancer cohorts using polymerase chain reaction-based methods. RESULTS: The results indicated that TUSC3 expression is decreased significantly because of promoter methylation in malignant ovarian tumors compared with benign controls. Almost 33% of ovarian cancer samples had detectable TUSC3 promoter methylation. Furthermore, methylation status of the TUSC3 promoter had a significant and independent influence on progression-free and overall survival. CONCLUSIONS: TUSC3 hypermethylation predicted progression-free and overall survival in ovarian cancer. The current observations suggested a role for N-glycosylating events in ovarian cancer pathogenesis in general and identified the epigenetic silencing of TUSC3 as a prognostic factor in this disease.

A novel heteroleptic Cu(II)-phenanthroline-UDCA complex as lipoxygenase inhibitor and ER-stress inducer in cancer cell lines.

A new heteroleptic copper(II) compound named C0-UDCA was prepared by reaction of [Cu(phen)2(OH2)](ClO4)2 (C0) with the bile ursodeoxycholic acid (UDCA). The resulting compound is able to inhibit the lipoxygenase enzyme showing more efficacy than the precursors C0 and UDCA. Molecular docking simulations clarified the interactions with the enzyme as due to allosteric modulation. The new complex shows antitumoral effect on ovarian (SKOV-3) and pancreatic (PANC-1) cancer cells at the Endoplasmic Reticulum (ER) level by activating the Unfolded Protein Response. In particular, the chaperone BiP, the pro-apoptotic protein CHOP and the transcription factor ATF6 are upregulated in the presence of C0-UDCA. The combination of Intact Cell MALDI-MS and statistical analysis have allowed us to discriminate between untreated and treated cells based on their mass spectrometry fingerprints.

Improved Screening of Monoclonal Gammopathy Patients by MALDI-TOF Mass Spectrometry.

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.

Artificial Neural Networks Coupled with MALDI-TOF MS Serum Fingerprinting To Classify and Diagnose Pathological Pain Subtypes in Preclinical Models.

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.