Proteomic analysis of Rana sylvatica reveals differentially expressed proteins in liver in response to anoxia, dehydration or freezing stress.

Ectothermic animals that live in seasonally cold regions must adapt to seasonal variation and specific environmental conditions. During the winter, some amphibians hibernate on land and encounter limited environmental water, deficient oxygen, and extremely low temperatures that can cause the whole body freezing. These stresses trigger physiological and biochemical adaptations in amphibians that allow them to survive. Rana sylvatica, commonly known as the wood frog, shows excellent freeze tolerance. They can slow their metabolic activity to a near halt and endure freezing of 65-70% of their total body water as extracellular ice during hibernation, returning to normal when the temperatures rise again. To investigate the molecular adaptations of freeze-tolerant wood frogs, a comprehensive proteomic analysis was performed on frog liver tissue after anoxia, dehydration, or freezing exposures using a label-free LC-MS/MS proteomic approach. Quantitative proteomic analysis revealed that 87, 118, and 86 proteins were significantly upregulated in dehydrated, anoxic, and frozen groups, suggesting potential protective functions. The presence of three upregulated enzymes, glutathione S-transferase (GST), aldolase (ALDOA), and sorbitol dehydrogenase (SORD), was also validated. For all enzymes, the specific enzymatic activity was significantly higher in the livers of frozen and anoxic groups than in the controls. This study reveals that GST, ALDOA, and SORD might participate in the freeze tolerance mechanism by contributing to regulating cellular detoxification and energy metabolism.

Gestational age at birth influences protein and RNA content in human milk extracellular vesicles.

Human milk extracellular vesicles (HM EVs) are proposed to protect against disease development in infants. This protection could in part be facilitated by the bioactive EV cargo of proteins and RNA. Notably, mothers birth infants of different gestational ages with unique needs, wherein the EV cargo of HM may diverge. We collected HM from lactating mothers within two weeks of a term or preterm birth. Following purification of EVs, proteins and mRNA were extracted for proteomics and sequencing analyses, respectively. Over 2000 protein groups were identified, and over 8000 genes were quantified. The total number of proteins and mRNA did not differ significantly between the two conditions, while functional bioinformatics of differentially expressed cargo indicated enrichment in immunoregulatory cargo for preterm HM EVs. In term HM EVs, significantly upregulated cargo was enriched in metabolism-related functions. Based on gene expression signatures from HM-contained single cell sequencing data, we proposed that a larger portion of preterm HM EVs are secreted by immune cells, whereas term HM EVs contain more signatures of lactocyte epithelial cells. Proposed differences in EV cargo could indicate variation in mother's milk based on infants' gestational age and provide basis for further functional characterisation.

Surface Proteome of Extracellular Vesicles and Correlation Analysis Reveal Breast Cancer Biomarkers.

Breast cancer (BC) is the second most frequently diagnosed cancer and accounts for approximately 25% of new cancer cases in Canadian women. Using biomarkers as a less-invasive BC diagnostic method is currently under investigation but is not ready for practical application in clinical settings. During the last decade, extracellular vesicles (EVs) have emerged as a promising source of biomarkers because they contain cancer-derived proteins, RNAs, and metabolites. In this study, EV proteins from small EVs (sEVs) and medium EVs (mEVs) were isolated from BC MDA-MB-231 and MCF7 and non-cancerous breast epithelial MCF10A cell lines and then analyzed by two approaches: global proteomic analysis and enrichment of EV surface proteins by Sulfo-NHS-SS-Biotin labeling. From the first approach, proteomic profiling identified 2459 proteins, which were subjected to comparative analysis and correlation network analysis. Twelve potential biomarker proteins were identified based on cell line-specific expression and filtered by their predicted co-localization with known EV marker proteins, CD63, CD9, and CD81. This approach resulted in the identification of 11 proteins, four of which were further investigated by Western blot analysis. The presence of transmembrane serine protease matriptase (ST14), claudin-3 (CLDN3), and integrin alpha-7 (ITGA7) in each cell line was validated by Western blot, revealing that ST14 and CLDN3 may be further explored as potential EV biomarkers for BC. The surface labeling approach enriched proteins that were not identified using the first approach. Ten potential BC biomarkers (Glutathione S-transferase P1 (GSTP1), Elongation factor 2 (EEF2), DEAD/H box RNA helicase (DDX10), progesterone receptor (PGR), Ras-related C3 botulinum toxin substrate 2 (RAC2), Disintegrin and metalloproteinase domain-containing protein 10 (ADAM10), Aconitase 2 (ACO2), UTP20 small subunit processome component (UTP20), NEDD4 binding protein 2 (N4BP2), Programmed cell death 6 (PDCD6)) were selected from surface proteins commonly identified from MDA-MB-231 and MCF7, but not identified in MCF10A EVs. In total, 846 surface proteins were identified from the second approach, of which 11 were already known as BC markers. This study supports the proposition that Evs are a rich source of known and novel biomarkers that may be used for non-invasive detection of BC. Furthermore, the presented datasets could be further explored for the identification of potential biomarkers in BC.

Cucurbita pepo contains characteristic proteins without a signal peptide in the xylem sap.

Xylem sap is a fluid that transfers water and nutrients from the rhizosphere. This sap contains relatively low concentrations of proteins that originate from the extracellular space among the root cells. One of the characteristic proteins in the xylem sap of the Cucurbitaceae family, which includes cucumber and zucchini, is a major latex-like protein (MLP). MLPs are responsible for crop contamination through the transport of hydrophobic pollutants from the roots. However, detailed information on the content of MLPs in the xylem sap is not available. Proteomic analysis of root and xylem sap proteins from the Cucurbita pepo cultivars Patty Green (PG) and Raven (RA) showed that the xylem sap of cv. RA, a high accumulator of hydrophobic pollutants, contained four MLPs that accounted for over 85% of the total xylem sap proteins in this cultivar. The xylem sap of PG, a low accumulator, mainly contained an uncharacterized protein. The amount of each root protein between the PG and RA cultivars was significantly and positively correlated in spite of being with and without a signal peptide (SP). However, the amount of xylem sap proteins without an SP was not correlated. These results suggest that cv. RA is characterized by MLPs in the xylem sap.

Monitoring of breast cancer progression via aptamer-based detection of circulating tumor cells in clinical blood samples.

Introduction: Breast cancer (BC) diagnostics lack noninvasive methods and procedures for screening and monitoring disease dynamics. Admitted CellSearch® is used for fluid biopsy and capture of circulating tumor cells of only epithelial origin. Here we describe an RNA aptamer (MDA231) for detecting BC cells in clinical samples, including blood. The MDA231 aptamer was originally selected against triple-negative breast cancer cell line MDA-MB-231 using cell-SELEX. Methods: The aptamer structure in solution was predicted using mFold program and molecular dynamic simulations. The affinity and specificity of the evolved aptamers were evaluated by flow cytometry and laser scanning microscopy on clinical tissues from breast cancer patients. CTCs were isolated form the patients' blood using the developed method of aptamer-based magnetic separation. Breast cancer origin of CTCs was confirmed by cytological, RT-qPCR and Immunocytochemical analyses. Results: MDA231 can specifically recognize breast cancer cells in surgically resected tissues from patients with different molecular subtypes: triple-negative, Luminal A, and Luminal B, but not in benign tumors, lung cancer, glial tumor and healthy epithelial from lungs and breast. This RNA aptamer can identify cancer cells in complex cellular environments, including tumor biopsies (e.g., tumor tissues vs. margins) and clinical blood samples (e.g., circulating tumor cells). Breast cancer origin of the aptamer-based magnetically separated CTCs has been proved by immunocytochemistry and mammaglobin mRNA expression. Discussion: We suggest a simple, minimally-invasive breast cancer diagnostic method based on non-epithelial MDA231 aptamer-specific magnetic isolation of circulating tumor cells. Isolated cells are intact and can be utilized for molecular diagnostics purposes.

Lysine Acetylome of Breast Cancer-Derived Small Extracellular Vesicles Reveals Specific Acetylation Patterns for Metabolic Enzymes.

Cancer-derived small extracellular vesicles have been proposed as promising potential biomarkers for diagnosis and prognosis of breast cancer (BC). We performed a proteomic study of lysine acetylation of breast cancer-derived small extracellular vesicles (sEVs) to understand the potential role of the aberrant acetylated proteins in the biology of invasive ductal carcinoma and triple-negative BC. Three cell lines were used as models for this study: MCF10A (non-metastatic), MCF7 (estrogen and progesterone receptor-positive, metastatic) and MDA-MB-231 (triple-negative, highly metastatic). For a comprehensive protein acetylation analysis of the sEVs derived from each cell line, acetylated peptides were enriched using the anti-acetyl-lysine antibody, followed by LC-MS/MS analysis. In total, there were 118 lysine-acetylated peptides, of which 22, 58 and 82 have been identified in MCF10A, MCF7 and MDA-MB-231 cell lines, respectively. These acetylated peptides were mapped to 60 distinct proteins and mainly identified proteins involved in metabolic pathways. Among the acetylated proteins identified in cancer-derived sEVs from MCF7 and MDA-MB-231 cell lines are proteins associated with the glycolysis pathway, annexins and histones. Five acetylated enzymes from the glycolytic pathway, present only in cancer-derived sEVs, were validated. These include aldolase (ALDOA), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), phosphoglycerate kinase (PGK1), enolase (ENO) and pyruvate kinase M1/2 (PKM). For three of these enzymes (ALDOA, PGK1 and ENO) the specific enzymatic activity was significantly higher in MDA-MB-231 when compared with MCF10A-derived sEVs. This study reveals that sEVs contain acetylated glycolytic metabolic enzymes that could be interesting potential candidates for early BC diagnostics.

A comprehensive proteomics analysis of the response of Pseudomonas aeruginosa to nanoceria cytotoxicity.

The increased commercial use and spread of nanoceria raises concerns about the risks associated with its effects on living organisms. Although Pseudomonas aeruginosa may be ubiquitous in nature, it is largely found in locations closely linked with human activity. P. aeruginosa san ai was used as a model organism for a deeper understanding of the interaction between biomolecules of the bacteria with this intriguing nanomaterial. A comprehensive proteomics approach along with analysis of altered respiration and production of targeted/specific secondary metabolites was conducted to study the response of P. aeruginosa san ai to nanoceria. Quantitative proteomics found that proteins associated with redox homeostasis, biosynthesis of amino acids, and lipid catabolism were upregulated. Proteins from outer cellular structures were downregulated, including transporters responsible for peptides, sugars, amino acids and polyamines, and the crucial TolB protein of the Tol-Pal system, required for the structural formation of the outer membrane layer. In accordance with the altered redox homeostasis proteins, an increased amount of pyocyanin, a key redox shuttle, and the upregulation of the siderophore, pyoverdine, responsible for iron homeostasis, were found. Production of extracellular molecules, e.g. pyocyanin, pyoverdine, exopolysaccharides, lipase, and alkaline protease, was significantly increased in P. aeruginosa san ai exposed to nanoceria. Overall, nanoceria at sublethal concentrations induces profound metabolic changes in P. aeruginosa san ai and provokes increased secretion of extracellular virulence factors, revealing the powerful influence this nanomaterial has on the vital functions of the microorganism.

Discovery of DNA aptamers targeting SARS-CoV-2 nucleocapsid protein and protein-binding epitopes for label-free COVID-19 diagnostics.

The spread of COVID-19 has affected billions of people across the globe, and the diagnosis of viral infection still needs improvement. Because of high immunogenicity and abundant expression during viral infection, SARS-CoV-2 nucleocapsid (N) protein could be an important diagnostic marker. This study aimed to develop a label-free optical aptasensor fabricated with a novel single-stranded DNA aptamer to detect the N protein. The N-binding aptamers selected using asymmetric-emulsion PCR-SELEX and their binding affinity and cross-reactivity were characterized by biolayer interferometry. The tNSP3 aptamer (44 nt) was identified to bind the N protein of wild type and Delta and Omicron variants with high affinity (KD in the range of 0.6-3.5 nM). Utilizing tNSP3 to detect the N protein spiked in human saliva evinced the potential of this aptamer with a limit of detection of 4.5 nM. Mass spectrometry analysis was performed along with molecular dynamics simulation to obtain an insight into how tNSP3 binds to the N protein. The identified epitope peptides are localized within the RNA-binding domain and C terminus of the N protein. Hence, we confirmed the performance of this aptamer as an analytical tool for COVID-19 diagnosis.

Three Diverse Granule Preparation Methods for Proteomic Analysis of Mature Rice (Oryza sativa L.) Starch Grain.

Starch is the primary form of reserve carbohydrate storage in plants. Rice (Oryza sativa L.) is a monocot whose reserve starch is organized into compounded structures within the amyloplast, rather than a simple starch grain (SG). The mechanism governing the assembly of the compound SG from polyhedral granules in apposition, however, remains unknown. To further characterize the proteome associated with these compounded structures, three distinct methods of starch granule preparation (dispersion, microsieve, and flotation) were performed. Phase separation of peptides (aqueous trypsin-shaving and isopropanol solubilization of residual peptides) isolated starch granule-associated proteins (SGAPs) from the distal proteome of the amyloplast and the proximal 'amylome' (the amyloplastic proteome), respectively. The term 'distal proteome' refers to SGAPs loosely tethered to the amyloplast, ones that can be rapidly proteolyzed, while proximal SGAPs are those found closer to the remnant amyloplast membrane fragments, perhaps embedded therein-ones that need isopropanol solvent to be removed from the mature organelle surface. These two rice starch-associated peptide samples were analyzed using nano-liquid chromatography-tandem mass spectrometry (Nano-HPLC-MS/MS). Known and novel proteins, as well as septum-like structure (SLS) proteins, in the mature rice SG were found. Data mining and gene ontology software were used to categorize these putative plastoskeletal components as a variety of structural elements, including actins, tubulins, tubulin-like proteins, and cementitious elements such as reticulata related-like (RER) proteins, tegument proteins, and lectins. Delineating the plastoskeletal proteome begins by understanding how each starch granule isolation procedure affects observed cytoplasmic and plastid proteins. The three methods described herein show how the technique used to isolate SGs differentially impacts the subsequent proteomic analysis and results obtained. It can thus be concluded that future investigations must make judicious decisions regarding the methodology used in extracting proteomic information from the compound starch granules being assessed, since different methods are shown to yield contrasting results herein. Data are available via ProteomeXchange with identifier PXD032314.

Comparative Proteomic Profiling of Secreted Extracellular Vesicles from Breast Fibroadenoma and Malignant Lesions: A Pilot Study.

Extracellular vesicles (EVs) shuttle proteins, RNA, DNA, and lipids crucial for cell-to-cell communication. Recent findings have highlighted that EVs, by virtue of their cargo, may also contribute to breast cancer (BC) growth and metastatic dissemination. Indeed, EVs are gaining great interest as non-invasive cancer biomarkers. However, little is known about the biological and physical properties of EVs from malignant BC lesions, and even less is understood about EVs from non-malignant lesions, such as breast fibroadenoma (FAD), which are clinically managed using conservative approaches. Thus, for this pilot study, we attempted to purify and explore the proteomic profiles of EVs from benign breast lesions, HER2+ BCs, triple-negative BCs (TNBCs), and continuous BC cell lines (i.e., BT-549, MCF-10A, and MDA-MB-231), combining experimental and semi-quantitative approaches. Of note, proteome-wide analyses showed 49 common proteins across EVs harvested from FAD, HER2+ BCs, TNBCs, and model BC lines. This is the first feasibility study evaluating the physicochemical composition and proteome of EVs from benign breast cells and primary and immortalized BC cells. Our preliminary results hold promise for possible implications in precision medicine for BC.

A study of the flexibility of the carbon catabolic pathways of extremophilic P. aeruginosa san ai exposed to benzoate versus glucose as sole carbon sources by multi omics analytical platform.

Polyextremophilic, hydrocarbonoclastic Pseudomonas aeruginosa san ai can survive under extreme environmental challenges in the presence of a variety of pollutants such as organic solvents and hydrocarbons, particularly aromatics, heavy metals, and high pH. To date, the metabolic plasticity of the extremophilic P. aeruginosa, has not been sufficiently studied in regard to the effect of changing carbon sources. Therefore, the present study explores the carbon metabolic pathways of polyextremophilic P. aeruginosa san ai grown on sodium benzoate versus glucose and its potential for aromatic degradation. P. aeruginosa san ai removed/metabolised nearly 430 mg/L of benzoate for 48 h, demonstrating a high capacity for aromatic degradation. Comparative functional proteomics, targeted metabolomics and genomics analytical approaches were employed to study the carbon metabolism of the P. aeruginosa san ai. Functional proteomic study of selected enzymes participating in the ß-ketoadipate and the Entner-Doudoroff pathways revealed a metabolic reconfiguration induced by benzoate compared to glucose. Metabolome analysis implied the existence of both catechol and protocatechuate branches of the ß-ketoadipate pathway. Enzymatic study of benzoate grown cultures confirmed the activity of the ortho- catechol branch of the ß-ketoadipate pathway. Even high concentrations of benzoate did not show increased stress protein synthesis, testifying to its extremophilic nature capable of surviving in harsh conditions. This ability of Pseudomonas aeruginosa san ai to efficiently degrade benzoate can provide a wide range of use of this strain in environmental and agricultural application.

Phosphoproteomic Analysis of Breast Cancer-Derived Small Extracellular Vesicles Reveals Disease-Specific Phosphorylated Enzymes.

Small membrane-derived extracellular vesicles have been proposed as participating in several cancer diseases, including breast cancer (BC). We performed a phosphoproteomic analysis of breast cancer-derived small extracellular vesicles (sEVs) to provide insight into the molecular and cellular regulatory mechanisms important for breast cancer tumor progression and metastasis. We examined three cell line models for breast cancer: MCF10A (non-malignant), MCF7 (estrogen and progesterone receptor-positive, metastatic), and MDA-MB-231 (triple-negative, highly metastatic). To obtain a comprehensive overview of the sEV phosphoproteome derived from each cell line, effective phosphopeptide enrichment techniques IMAC and TiO2, followed by LC-MS/MS, were performed. The phosphoproteome was profiled to a depth of 2003 phosphopeptides, of which 207, 854, and 1335 were identified in MCF10A, MCF7, and MDA-MB-231 cell lines, respectively. Furthermore, 2450 phosphorylation sites were mapped to 855 distinct proteins, covering a wide range of functions. The identified proteins are associated with several diseases, mostly related to cancer. Among the phosphoproteins, we validated four enzymes associated with cancer and present only in sEVs isolated from MCF7 and MDA-MB-231 cell lines: ATP citrate lyase (ACLY), phosphofructokinase-M (PFKM), sirtuin-1 (SIRT1), and sirtuin-6 (SIRT6). With the exception of PFKM, the specific activity of these enzymes was significantly higher in MDA-MB-231 when compared with MCF10A-derived sEVs. This study demonstrates that sEVs contain functional metabolic enzymes that could be further explored for their potential use in early BC diagnostic and therapeutic applications.

Hemojuvelin deficiency promotes liver mitochondrial dysfunction and predisposes mice to hepatocellular carcinoma.

Hemojuvelin (HJV) enhances signaling to the iron hormone hepcidin and its deficiency causes iron overload, a risk factor for hepatocellular carcinoma (HCC). We utilized Hjv-/- mice to dissect mechanisms for hepatocarcinogenesis. We show that suboptimal treatment with diethylnitrosamine (DEN) triggers HCC only in Hjv-/- but not wt mice. Liver proteomics data were obtained by mass spectrometry. Hierarchical clustering analysis revealed that Hjv deficiency and DEN elicit similar liver proteomic responses, including induction of mitochondrial proteins. Dietary iron overload of wt mice does not recapitulate the liver proteomic phenotype of Hjv-/- animals, which is only partially corrected by iron depletion. Consistent with these data, primary Hjv-/- hepatocytes exhibit mitochondrial hyperactivity, while aged Hjv-/- mice develop spontaneous HCC. Moreover, low expression of HJV or hepcidin (HAMP) mRNAs predicts poor prognosis in HCC patients. We conclude that Hjv has a hepatoprotective function and its deficiency in mice promotes mitochondrial dysfunction and hepatocarcinogenesis.

Characterization and differentiation of quinoa seed proteomes by label-free mass spectrometry-based shotgun proteomics.

Quinoa seed proteins are of prime importance in human nutrition and in plant breeding for cultivar identification and improvement. In this study, proteins from seeds of black, red, white quinoa from Peru and white quinoa from Bolivia (also known as royal) were extracted, digested and analyzed by nano-liquid chromatography coupled to Orbitrap tandem mass spectrometry (LC-MS/MS). The raw mass spectra data were processed for identification and label-free quantification (LFQ) using MaxQuant/Andromeda against a specific quinoa database from The National Center for Biotechnology Information (NCBI). In total, 1,211 quinoa proteins (85 were uncharacterized) were identified. Inspection and visualization using Venn diagrams, heat maps and Gene Ontology (GO) graphs revealed proteome similarities and differences between the four varieties. The presented data provides the most comprehensive experimental quinoa seed proteome map existing to date in the literature, as a starting point for more specific characterization and nutritional studies of quinoa and quinoa-containing foodstuff.

Breast Cancer-Derived Microvesicles Are the Source of Functional Metabolic Enzymes as Potential Targets for Cancer Therapy.

Membrane-derived extracellular vesicles, referred to as microvesicles (MVs), have been proposed to participate in several cancer diseases. In this study, MV fractions were isolated by differential ultracentrifugation from a metastatic breast cancer (BC) cell line MDA-MB-231 and a non-cancerous breast cell line MCF10A, then analyzed by nano-liquid chromatography coupled to tandem mass spectrometry. A total of 1519 MV proteins were identified from both cell lines. The data obtained were compared to previously analyzed proteins from small extracellular vesicles (sEVs), revealing 1272 proteins present in both MVs and sEVs derived from the MDA-MB-231 cell line. Among the 89 proteins unique to MDA-MB-231 MVs, three enzymes: ornithine aminotransferase (OAT), transaldolase (TALDO1) and bleomycin hydrolase (BLMH) were previously proposed as cancer therapy targets. These proteins were enzymatically validated in cells, sEVs, and MVs derived from both cell lines. The specific activity of OAT and TALDO1 was significantly higher in MDA-MB-231-derived MVs than in MCF10A MVs. BLMH was highly expressed in MDA-MB-231-derived MVs, compared to MCF10A MVs. This study shows that MVs carry functional metabolic enzymes and provides a framework for future studies of their biological role in BC and potential in therapeutic applications.

Functional cooperativity between the trigger factor chaperone and the ClpXP proteolytic complex.

A functional association is uncovered between the ribosome-associated trigger factor (TF) chaperone and the ClpXP degradation complex. Bioinformatic analyses demonstrate conservation of the close proximity of tig, the gene coding for TF, and genes coding for ClpXP, suggesting a functional interaction. The effect of TF on ClpXP-dependent degradation varies based on the nature of substrate. While degradation of some substrates are slowed down or are unaffected by TF, surprisingly, TF increases the degradation rate of a third class of substrates. These include λ phage replication protein λO, master regulator of stationary phase RpoS, and SsrA-tagged proteins. Globally, TF acts to enhance the degradation of about 2% of newly synthesized proteins. TF is found to interact through multiple sites with ClpX in a highly dynamic fashion to promote protein degradation. This chaperone-protease cooperation constitutes a unique and likely ancestral aspect of cellular protein homeostasis in which TF acts as an adaptor for ClpXP.

The proteomic analysis of breast cell line exosomes reveals disease patterns and potential biomarkers.

Cancer cells release small extracellular vesicles, exosomes, that have been shown to contribute to various aspects of cancer development and progression. Differential analysis of exosomal proteomes from cancerous and non-tumorigenic breast cell lines can provide valuable information related to breast cancer progression and metastasis. Moreover, such a comparison can be explored to find potentially new protein biomarkers for early disease detection. In this study, exosomal proteomes of MDA-MB-231, a metastatic breast cancer cell line, and MCF-10A, a non-cancerous epithelial breast cell line, were identified by nano-liquid chromatography coupled to tandem mass spectrometry. We also tested three exosomes isolation methods (ExoQuick, Ultracentrifugation (UC), and Ultrafiltration-Ultracentrifugation) and detergents (n-dodecyl ß-D-maltoside, Triton X-100, and Digitonin) for solubilization of exosomal proteins and enhanced detection by mass spectrometry. A total of 1,107 exosomal proteins were identified in both cell lines, 726 of which were unique to the MDA-MB-231 breast cancer cell line. Among them, 87 proteins were predicted to be relevant to breast cancer and 16 proteins to cancer metastasis. Three exosomal membrane/surface proteins, glucose transporter 1 (GLUT-1), glypican 1 (GPC-1), and disintegrin and metalloproteinase domain-containing protein 10 (ADAM10), were identified as potential breast cancer biomarkers and validated with Western blotting and high-resolution flow cytometry. We demonstrated that exosomes are a rich source of breast cancer-related proteins and surface biomarkers that may be used for disease diagnosis and prognosis.

Proteomics-Based Machine Learning Approach as an Alternative to Conventional Biomarkers for Differential Diagnosis of Chronic Kidney Diseases.

Diabetic nephropathy, hypertension, and glomerulonephritis are the most common causes of chronic kidney diseases (CKD). Since CKD of various origins may not become apparent until kidney function is significantly impaired, a differential diagnosis and an appropriate treatment are needed at the very early stages. Conventional biomarkers may not have sufficient separation capabilities, while a full-proteomic approach may be used for these purposes. In the current study, several machine learning algorithms were examined for the differential diagnosis of CKD of three origins. The tested dataset was based on whole proteomic data obtained after the mass spectrometric analysis of plasma and urine samples of 34 CKD patients and the use of label-free quantification approach. The k-nearest-neighbors algorithm showed the possibility of separation of a healthy group from renal patients in general by proteomics data of plasma with high confidence (97.8%). This algorithm has also be proven to be the best of the three tested for distinguishing the groups of patients with diabetic nephropathy and glomerulonephritis according to proteomics data of plasma (96.3% of correct decisions). The group of hypertensive nephropathy could not be reliably separated according to plasma data, whereas analysis of entire proteomics data of urine did not allow differentiating the three diseases. Nevertheless, the group of hypertensive nephropathy was reliably separated from all other renal patients using the k-nearest-neighbors classifier "one against all" with 100% of accuracy by urine proteome data. The tested algorithms show good abilities to differentiate the various groups across proteomic data sets, which may help to avoid invasive intervention for the verification of the glomerulonephritis subtypes, as well as to differentiate hypertensive and diabetic nephropathy in the early stages based not on individual biomarkers, but on the whole proteomic composition of urine and blood.

Targeting Ephrin Receptor Tyrosine Kinase A2 with a Selective Aptamer for Glioblastoma Stem Cells.

Despite the benefits associated with radiotherapy and chemotherapy for glioblastoma (GBM) treatment, most patients experience a relapse following initial therapy. Recurrent or progressive GBM usually does not respond anymore to standard therapy, and this is associated with poor patient outcome. GBM stem cells (GSCs) are a subset of cells resistant to radiotherapy and chemotherapy and play a role in tumor recurrence. The targeting of GSCs and the identification of novel markers are crucial issues in the development of innovative strategies for GBM eradication. By differential cell SELEX (systematic evolution of ligands by exponential enrichment), we have recently described two RNA aptamers, that is, the 40L sequence and its truncated form A40s, able to bind the cell surface of human GSCs. Both aptamers were selective for stem-like growing GBM cells and are rapidly internalized into target cells. In this study, we demonstrate that their binding to cells is mediated by direct recognition of the ephrin type-A receptor 2 (EphA2). Functionally, the two aptamers were able to inhibit cell growth, stemness, and migration of GSCs. Furthermore, A40s was able to cross the blood-brain barrier (BBB) and was stable in serum in in vitro experiments. These results suggest that 40L and A40s represent innovative potential therapeutic tools for GBM.