Integrating Proteomics and Lipidomics for Evaluating the Risk of Breast Cancer Progression: A Pilot Study.

Metastasis is a serious and often life-threatening condition, representing the leading cause of death among women with breast cancer (BC). Although the current clinical classification of BC is well-established, the addition of minimally invasive laboratory tests based on peripheral blood biomarkers that reflect pathological changes in the body is of utmost importance. In the current study, the serum proteome and lipidome profiles for 50 BC patients with (25) and without (25) metastasis were studied. Targeted proteomic analysis for concertation measurements of 125 proteins in the serum was performed via liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM MS) using the BAK 125 kit (MRM Proteomics Inc., Victoria, BC, Canada). Untargeted label-free lipidomic analysis was performed using liquid chromatography coupled to tandem mass-spectrometry (LC-MS/MS), in both positive and negative ion modes. Finally, 87 serum proteins and 295 lipids were quantified and showed a moderate correlation with tumor grade, histological and biological subtypes, and the number of lymph node metastases. Two highly accurate classifiers that enabled distinguishing between metastatic and non-metastatic BC were developed based on proteomic (accuracy 90%) and lipidomic (accuracy 80%) features. The best classifier (91% sensitivity, 89% specificity, AUC = 0.92) for BC metastasis diagnostics was based on logistic regression and the serum levels of 11 proteins: alpha-2-macroglobulin, coagulation factor XII, adiponectin, leucine-rich alpha-2-glycoprotein, alpha-2-HS-glycoprotein, Ig mu chain C region, apolipoprotein C-IV, carbonic anhydrase 1, apolipoprotein A-II, apolipoprotein C-II and alpha-1-acid glycoprotein 1.

Search for New Participants in the Pathogenesis of High-Grade Serous Ovarian Cancer with the Potential to Be Used as Diagnostic Molecules.

Recent studies have attempted to develop molecular signatures of epithelial ovarian cancer (EOC) based on the quantitation of protein-coding and non-coding RNAs to predict disease prognosis. Due to the heterogeneity of EOC, none of the developed prognostic signatures were directly applied in clinical practice. Our work focuses on high-grade serous ovarian carcinoma (HGSOC) due to the highest mortality rate relative to other types of EOC. Using deep sequencing of small non-coding RNAs in combination with quantitative real-time PCR, we confirm the dualistic classification of epithelial ovarian cancers based on the miRNA signature of HGSOC (type 2), which differs from benign cystadenoma and borderline cystadenoma-precursors of low-grade serous ovarian carcinoma (type 1)-and identified two subtypes of HGSOC, which significantly differ in the level of expression of the progesterone receptor in the tumor tissue, the secretion of miR-16-5p, miR-17-5p, miR-93-5p, miR-20a-5p, the level of serum CA125, tumor size, surgical outcome (optimal or suboptimal cytoreduction), and response to chemotherapy. It was found that the combined determination of the level of miR-16-5p, miR-17-5p, miR-20a-5p, and miR-93-5p circulating in blood plasma of patients with primary HGSOC tumors makes it possible to predict optimal cytoreduction with 80.1% sensitivity and 70% specificity (p = 0.022, TPR = 0.8, FPR = 0.3), as well as complete response to adjuvant chemotherapy with 77.8% sensitivity and 90.9% specificity (p = 0.001, TPR = 0.78, FPR = 0.09). After the additional verification of the obtained data in a larger HGSOC patient cohort, the combined quantification of these four miRNAs is proposed to be used as a criterion for selecting patients either for primary cytoreduction or neoadjuvant chemotherapy followed by interval cytoreduction.

Shotgun Lipidomics for Differential Diagnosis of HPV-Associated Cervix Transformation.

A dramatic increase in cervical diseases associated with human papillomaviruses (HPV) in women of reproductive age has been observed over the past decades. An accurate differential diagnosis of the severity of cervical intraepithelial neoplasia and the choice of the optimal treatment requires the search for effective biomarkers with high diagnostic and prognostic value. The objective of this study was to introduce a method for rapid shotgun lipidomics to differentiate stages of HPV-associated cervix epithelium transformation. Tissue samples from 110 HPV-positive women with cervicitis (n = 30), low-grade squamous intraepithelial lesions (LSIL) (n = 30), high-grade squamous intraepithelial lesions (HSIL) (n = 30), and cervical cancers (n = 20) were obtained. The cervical epithelial tissue lipidome at different stages of cervix neoplastic transformation was studied by a shotgun label-free approach. It is based on electrospray ionization mass spectrometry (ESI-MS) data of a tissue extract. Lipidomic data were processed by the orthogonal projections to latent structures discriminant analysis (OPLS-DA) to build statistical models, differentiating stages of cervix transformation. Significant differences in the lipid profile between the lesion and surrounding tissues were revealed in chronic cervicitis, LSIL, HSIL, and cervical cancer. The lipids specific for HPV-induced cervical transformation mainly belong to glycerophospholipids: phosphatidylcholines, and phosphatidylethanolamines. The developed diagnostic OPLS-DA models were based on 23 marker lipids. More than 90% of these marker lipids positively correlated with the degree of cervix transformation. The algorithm was developed for the management of patients with HPV-associated diseases of the cervix, based on the panel of 23 lipids as a result. ESI-MS analysis of a lipid extract by direct injection through a loop, takes about 25 min (including preparation of the lipid extract), which is significantly less than the time required for the HPV test (several hours for hybrid capture and about an hour for PCR). This makes lipid mass spectrometric analysis a promising method for express diagnostics of HPV-associated neoplastic diseases of the cervix.

Interrelation between miRNAs Expression Associated with Redox State Fluctuations, Immune and Inflammatory Response Activation, and Neonatal Outcomes in Complicated Pregnancy, Accompanied by Placental Insufficiency.

Redox disbalance in placental cells leads to the hyperproduction of reactive oxygen species (ROS), it mediates the dysregulation of the maternal immune tolerance to a semi-allogenic fetus, inducing pro-inflammatory reactions, and it plays a central role in perinatal complications and neonatal disease programming. Microvesicles, which provide transplacental communication between a mother and fetus, contain microRNAs (miRNAs) that are sensitive to oxidative stress (OS) mediators and can control the balance of ROS production and utilization in target cells. In the context of this paradigm, we evaluated the markers of redox balance­MDA and 4-HNE for OS and GPx, and SOD, CAT, and GSH for the antioxidant system in the cord blood plasma of newborns diagnosed with fetal growth restriction (FGR)­by using polarography, spectrophotometry, and Western blotting. The expression of miRNAs associated with OS, immune and inflammatory responses in the blood plasma of newborns with intrauterine pneumonia (IP), neonatal sepsis (NS) and respiratory distress syndrome (RDS) was evaluated by a quantitative RT-PCR. Significant differences in the MDA level and reduced GPx and CAT activity were co-found for early-onset FGR (i.e., <34 gestational age). Significant correlations were found with a low birth weight by Apgar scores with reduced levels of antioxidant enzymes. Indeed, the level of OS markers increased in early-onset FGR in newborns with an extremely low body weight and high echogenicity of the periventricular zones, and reduced in late-onset FGR in newborns with IP, hyperbilirubinemia, intraventricular hemorrhage (IVH) and cerebral cysts. A prognostic model (AUC = 1; cutoff­0.5) was developed to assess the risk of IVH in newborns diagnosed with FGR based on the assessment of the OS markers (i.e., MDA + 4 HNE + CAT + GSH). A significant increase in the miR-127-3p expression was found in the plasma of newborns with NS (<32 GA; p ≤ 0.03 and >32 GA; p ≤ 0.009), IP (>32 GA; p ≤ 0.0001), and RDS (>32 GA; p ≤ 0.03). At the same time, the expression of miR-25-3p (p ≤ 0.03) was increased only in newborns with NS (>32 GA; p ≤ 0.03). The risk of developing IVH for premature newborns with IP (AUC = 0.8; cutoff­0.6) and NS (AUC = 0.68; cutoff­0.49) was assessed based on the miR-25-3p and miR-127-3p expression. Several key transcription factors were identified as the targets of studied miRNA since they are involved in the regulation of OS (NRF2), signaling and activation of the immune response (PRDM1, CCL26) and, also, inflammatory responses (NFKB1). The study of these miRNAs showed that they are involved in the modulation of processes leading to perinatal complications. Moreover, miR-127-3p is related to pro-inflammatory reactions and the formation of the macrophage phenotype in newborns with IP, NS, and RDS, while miR-25-3p is associated with an inhibition of macrophage migration and activation of antioxidant enzymes, which may prevent the development of oxidative damage in newborns with NS.

Clinical Relevance of Secreted Small Noncoding RNAs in an Embryo Implantation Potential Prediction at Morula and Blastocyst Development Stages.

Despite the improvements in biotechnological approaches and the selection of controlled ovarian hyperstimulation protocols, the resulting pregnancy rate from in vitro fertilization (IVF) protocols still does not exceed 30-40%. In this connection, there is an acute question of the development of a non-invasive, sensitive, and specific method for assessing the implantation potential of an embryo. A total of 110 subfertile couples were included in the study to undergo the IVF/ICSI program. Obtained embryos for transfer into the uterine cavity of patient cohort 1 (n = 60) and cohort 2 (n = 50) were excellent/good-quality blastocysts, and small noncoding RNA (sncRNA) content in the corresponding spent culture medium samples at the morula stage (n = 43) or at the blastocyst stage (n = 31) was analyzed by deep sequencing followed by qRT-PCR in real time. Two logistic regression models were developed to predict the implantation potential of the embryo with 100% sensitivity and 100% specificity: model 1 at the morula stage, using various combinations of hsa_piR_022258, hsa-let-7i-5p, hsa_piR_000765, hsa_piR_015249, hsa_piR_019122, and hsa_piR_008112, and model 2 at the blastocyst stage, using various combinations of hsa_piR_020497, hsa_piR_008113, hsa-miR-381-3p, hsa_piR_022258, and hsa-let-7a-5p. Protein products of sncRNA potential target genes participate in the selective turnover of proteins through the ubiquitination system and in the organization of the various cell cytoskeleton and nucleoskeleton structures, regulating the activity of the Hippo signaling pathway, which determines the fate specification of the blastomers.

Alterations in lipid profile upon uterine fibroids and its recurrence.

Uterine fibroids (UF) is the most common (about 70% cases) type of gynecological disease, with the recurrence rate varying from 11 to 40%. Because UF has no distinct symptomatology and is often asymptomatic, the specific and sensitive diagnosis of UF as well as the assessment for the probability of UF recurrence pose considerable challenge. The aim of this study was to characterize alterations in the lipid profile of tissues associated with the first-time diagnosed UF and recurrent uterine fibroids (RUF) and to explore the potential of mass spectrometry (MS) lipidomics analysis of blood plasma samples for the sensitive and specific determination of UF and RUF with low invasiveness of analysis. MS analysis of lipid levels in the myometrium tissues, fibroids tissues and blood plasma samples was carried out on 66 patients, including 35 patients with first-time diagnosed UF and 31 patients with RUF. The control group consisted of 15 patients who underwent surgical treatment for the intrauterine septum. Fibroids and myometrium tissue samples were analyzed using direct MS approach. Blood plasma samples were analyzed using high performance liquid chromatography hyphened with mass spectrometry (HPLC/MS). MS data were processed by discriminant analysis with projection into latent structures (OPLS-DA). Significant differences were found between the first-time UF, RUF and control group in the levels of lipids involved in the metabolism of glycerophospholipids, sphingolipids, lipids with an ether bond, triglycerides and fatty acids. Significant differences between the control group and the groups with UF and RUF were found in the blood plasma levels of cholesterol esters, triacylglycerols, (lyso) phosphatidylcholines and sphingomyelins. Significant differences between the UF and RUF groups were found in the blood plasma levels of cholesterol esters, phosphotidylcholines, sphingomyelins and triacylglycerols. Diagnostic models based on the selected differential lipids using logistic regression showed sensitivity and specificity of 88% and 86% for the diagnosis of first-time UF and 95% and 79% for RUF, accordingly. This study confirms the involvement of lipids in the pathogenesis of uterine fibroids. A diagnostically significant panel of differential lipid species has been identified for the diagnosis of UF and RUF by low-invasive blood plasma analysis. The developed diagnostic models demonstrated high potential for clinical use and further research in this direction.

Clusterin and Its Potential Regulatory microRNAs as a Part of Secretome for the Diagnosis of Abnormally Invasive Placenta: Accreta, Increta, and Percreta Cases.

Magnetic resonance imaging (MRI) and ultrasound methods used for the diagnosis of an abnormally invasive placenta (AIP) have a wide range of sensitivity (Se, 33-93%) and specificity (Sp, 71-100%) levels, which results in a high risk of unfavorable maternal and perinatal outcomes. The relevance of optimizing the diagnosis of AIP is beyond doubt. Given the epigenetic nature of trophoblast invasion, we aimed to quantitate microRNAs and proteins of their target genes that are potentially associated with AIP in blood plasma samples from 64 pregnant women at gestation weeks 30-34 by reverse transcription coupled with polymerase chain reaction (RT-PCR) and Western blotting, respectively. Statistically significant increases in the expression levels of hsa-miR-17-5p, hsa-miR-21-5p, hsa-miR-25-3p, hsa-miR-92a-3p, and hsa-miR-320a-3p were revealed in the groups of women with AIP (accreta, increta, percreta) relative to the group of women with scars on the uterus or to the group with placenta previa. Opposite changes in the expression level of "gene-target protein/miRNA" pairs were found for the α-subunit of the clusterin secretory form and any of the hsa-miR-21-5p, hsa-miR-25-3p, hsa-miR-92a-3p, hsa-miR-320a-3p, and hsa-miR-17-5p in all cases of AIP. The developed logistic regression models to diagnose AIP cases of various severity gave Se values of 88.8-100% and Sp values of 91.6-100% using a combination of hsa-miR-21-5p, hsa-miR-92a-3p, hsa-miR-320a-3p, or clusterin levels.

miRNAs and Their Gene Targets-A Clue to Differentiate Pregnancies with Small for Gestational Age Newborns, Intrauterine Growth Restriction, and Preeclampsia.

Despite the differences in the clinical manifestations of major obstetric syndromes, such as preeclampsia (PE) and intrauterine growth restriction (IUGR), their pathogenesis is based on the dysregulation of proliferation, differentiation, and invasion of cytotrophoblast cells that occur in the developing placenta, decidual endometrium, and myometrial parts of the spiral arteries. To understand the similarities and differences in the molecular mechanisms of PE and IUGR, samples of the placental bed and placental tissue were analyzed using protein mass spectrometry and the deep sequencing of small RNAs, followed by validation of the data obtained by quantitative RT-PCR in real time. A comparison of the transcriptome and proteomic profiles in the samples made it possible to conclude that the main changes in the molecular profile in IUGR occur in the placental bed, in contrast to PE, in which the majority of molecular changes occurs in the placenta. In placental bed samples, significant changes in the ratio of miRNA and its potential target gene expression levels were revealed, which were unique for IUGR (miR-30c-5p/VIM, miR-28-3p/VIM, miR-1-3p/ANXA2, miR-30c-5p/FBN1; miR-15b-5p/MYL6), unique for PE (miR-185-3p/FLNA), common for IUGR and PE (miR-30c-5p/YWHAZ and miR-654-3p/FGA), but all associated with abnormality in the hemostatic and vascular systems as well as with an inflammatory process at the fetal‒maternal interface.

Normalization methods for reducing interbatch effect without quality control samples in liquid chromatography-mass spectrometry-based studies.

Data normalization is an essential part of a large-scale untargeted mass spectrometry metabolomics analysis. Autoscaling, Pareto scaling, range scaling, and level scaling methods for liquid chromatography-mass spectrometry data processing were compared with the most common normalization methods, including quantile normalization, probabilistic quotient normalization, and variance stabilizing normalization. These methods were tested on eight datasets from various clinical studies. The efficiency of the data normalization was assessed by the distance between clusters corresponding to batches and the distance between clusters corresponding to clinical groups in the space of principal components, as well as by the number of features with a pairwise statistically significant difference between the batches and the number of features with a pairwise statistically significant difference between clinical groups. Autoscaling demonstrated the most effective reduction in interbatch variation and can be preferable to probabilistic quotient or quantile normalization in liquid chromatography-mass spectrometry data.

Comparison of the effectiveness of variable selection method for creating a diagnostic panel of biomarkers for mass spectrometric lipidome analysis.

Hundreds of compounds are detected during untargeted lipidomics analysis. The potential efficacy of lipids as disease markers makes it important to select the species with the most discriminative potential. Datasets based on a selected class of lipids allow the development of a high-quality diagnostic model using orthogonal projection on latent structure. The combination of selection of lipids by variable importance in projection and by Akaike information criteria makes it possible to build a reliable diagnostic model based on logistic regression.

Genetic diversity of SAD and FAD genes responsible for the fatty acid composition in flax cultivars and lines.

BACKGROUND: Flax (Linum usitatissimum L.) is grown for fiber and seed in many countries. Flax cultivars differ in the oil composition and, depending on the ratio of fatty acids, are used in pharmaceutical, food, or paint industries. It is known that genes of SAD (stearoyl-ACP desaturase) and FAD (fatty acid desaturase) families play a key role in the synthesis of fatty acids, and some alleles of these genes are associated with a certain composition of flax oil. However, data on genetic polymorphism of these genes are still insufficient. RESULTS: On the basis of the collection of the Institute for Flax (Torzhok, Russia), we formed a representative set of 84 cultivars and lines reflecting the diversity of fatty acid composition of flax oil. An approach for the determination of full-length sequences of SAD1, SAD2, FAD2A, FAD2B, FAD3A, and FAD3B genes using the Illumina platform was developed and deep sequencing of the 6 genes in 84 flax samples was performed on MiSeq. The obtained high coverage (about 400x on average) enabled accurate assessment of polymorphisms in SAD1, SAD2, FAD2A, FAD2B, FAD3A, and FAD3B genes and evaluation of cultivar/line heterogeneity. The highest level of genetic diversity was observed for FAD3A and FAD3B genes - 91 and 62 polymorphisms respectively. Correlation analysis revealed associations between particular variants in SAD and FAD genes and predominantly those fatty acids whose conversion they catalyze: SAD - stearic and oleic acids, FAD2 - oleic and linoleic acids, FAD3 - linoleic and linolenic acids. All except one low-linolenic flax cultivars/lines contained both the substitution of tryptophan to stop codon in the FAD3A gene and histidine to tyrosine substitution in the FAD3B gene, while samples with only one of these polymorphisms had medium content of linolenic acid and cultivars/lines without them were high-linolenic. CONCLUSIONS: Genetic polymorphism of SAD and FAD genes was evaluated in the collection of flax cultivars and lines with diverse oil composition, and associations between particular polymorphisms and the ratio of fatty acids were revealed. The achieved results are the basis for the development of marker-assisted selection and DNA-based certification of flax cultivars.

Validation of Breast Cancer Margins by Tissue Spray Mass Spectrometry.

Current methods for the intraoperative determination of breast cancer margins commonly suffer from the insufficient accuracy, specificity and/or low speed of analysis, increasing the time and cost of operation as well the risk of cancer recurrence. The purpose of this study is to develop a method for the rapid and accurate determination of breast cancer margins using direct molecular profiling by mass spectrometry (MS). Direct molecular fingerprinting of tiny pieces of breast tissue (approximately 1 × 1 × 1 mm) is performed using a home-built tissue spray ionization source installed on a Maxis Impact quadrupole time-of-flight mass spectrometer (qTOF MS) (Bruker Daltonics, Hamburg, Germany). Statistical analysis of MS data from 50 samples of both normal and cancer tissue (from 25 patients) was performed using orthogonal projections onto latent structures discriminant analysis (OPLS-DA). Additionally, the results of OPLS classification of new 19 pieces of two tissue samples were compared with the results of histological analysis performed on the same tissues samples. The average time of analysis for one sample was about 5 min. Positive and negative ionization modes are used to provide complementary information and to find out the most informative method for a breast tissue classification. The analysis provides information on 11 lipid classes. OPLS-DA models are created for the classification of normal and cancer tissue based on the various datasets: All mass spectrometric peaks over 300 counts; peaks with a statistically significant difference of intensity determined by the Mann-Whitney U-test (p < 0.05); peaks identified as lipids; both identified and significantly different peaks. The highest values of Q2 have models built on all MS peaks and on significantly different peaks. While such models are useful for classification itself, they are of less value for building explanatory mechanisms of pathophysiology and providing a pathway analysis. Models based on identified peaks are preferable from this point of view. Results obtained by OPLS-DA classification of the tissue spray MS data of a new sample set (n = 19) revealed 100% sensitivity and specificity when compared to histological analysis, the "gold" standard for tissue classification. "All peaks" and "significantly different peaks" datasets in the positive ion mode were ideal for breast cancer tissue classification. Our results indicate the potential of tissue spray mass spectrometry for rapid, accurate and intraoperative diagnostics of breast cancer tissue as a means to reduce surgical intervention.

Feature selection for OPLS discriminant analysis of cancer tissue lipidomics data.

The mass spectrometry-based molecular profiling can be used for better differentiation between normal and cancer tissues and for the detection of neoplastic transformation, which is of great importance for diagnostics of a pathology, prognosis of its evolution trend, and development of a treatment strategy. The aim of the present study is the evaluation of tissue classification approaches based on various data sets derived from the molecular profile of the organic solvent extracts of a tissue. A set of possibilities are considered for the orthogonal projections to latent structures discriminant analysis: all mass spectrometric peaks over 300 counts threshold, subset of peaks selected by ranking with support vector machine algorithm, peaks selected by random forest algorithm, peaks with the statistically significant difference of the intensity determined by the Mann-Whitney U test, peaks identified as lipids, and both identified and significantly different peaks. The best predictive potential is obtained for OPLS-DA model built on nonpolar glycerolipids (Q2 = 0.64, area under curve [AUC] = 0.95); the second one is OPLS-DA model with lipid peaks selected by random forest algorithm (Q2 = 0.58, AUC = 0.87). Moreover, models based on particular molecular classes are more preferable from biological point of view, resulting in new explanatory mechanisms of pathophysiology and providing a pathway analysis. Another promising features for OPLS-DA modeling are phosphatidylethanolamines (Q2 = 0.48, AUC = 0.86).

Cell-Free, Embryo-Specific sncRNA as a Molecular Biological Bridge between Patient Fertility and IVF Efficiency.

Small noncoding RNAs (sncRNAs) are key regulators of the majority of human reproduction events. Understanding their function in the context of gametogenesis and embryogenesis will allow insight into the possible causes of in vitro fertilization (IVF) implantation failure. The aim of this study was to analyze the sncRNA expression profile of the spent culture media on day 4 after fertilization and to reveal a relationship with the morphofunctional characteristics of gametes and resultant embryos, in particular, with the embryo development and implantation potential. Thereto, cell-free, embryo-specific sncRNAs were identified by next generation sequencing (NGS) and quantified by reverse transcription coupled with polymerase chain reaction (RT-PCR) in real-time. Significant differences in the expression level of let-7b-5p, let-7i-5p, piR020401, piR16735, piR19675, piR20326, and piR17716 were revealed between embryo groups of various morphological gradings. Statistically significant correlations were found between the expression profiles of piR16735 and piR020401 with the oocyte-cumulus complex number, let-7b-5p and piR020401 with metaphase II oocyte and two pronuclei embryo numbers, let-7i-5p and piR20497 with the spermatozoid count per milliliter of ejaculate, piR19675 with the percentage of linearly motile spermatozoids, let-7b-5p with the embryo development grade, and let-7i-5p with embryo implantation. According to partial least squares discriminant analysis (PLS-DA), the expression levels of let-7i-5p (Variable Importance in Projection score (VIP) = 1.6262), piR020401 (VIP = 1.45281), and piR20497 (VIP = 1.42765) have the strongest influences on the implantation outcome.

Label-free cervicovaginal fluid proteome profiling reflects the cervix neoplastic transformation.

Cervicovaginal fluid (CVF) is a valuable source of clinical information about the female reproductive tract in both nonpregnant and pregnant women. The aim of this study is to specify the CVF proteome at different stages of cervix neoplastic transformation by label-free quantitation approach based on liquid chromatography tandem mass spectrometry (LC-MS/MS) method. The proteome composition of CVF from 40 women of reproductive age with human papillomavirus (HPV)-associated cervix neoplastic transformation (low-grade squamous intraepithelial lesion [LSIL], high-grade squamous intraepithelial lesion [HSIL], and CANCER) was investigated. Hierarchical clustering and principal component analysis (PCA) of the proteomic data obtained by a label-free quantitation approach show the distribution of the sample set between four major clusters (no intraepithelial lesion or malignancy [NILM], LSIL, HSIL and CANCER) depending on the form of cervical lesion. Multisample ANOVA with subsequent Welch's t test resulted in 117 that changed significantly across the four clinical stages, including 27 proteins significantly changed in cervical cancer. Some of them were indicated as promising biomarkers previously (ACTN4, VTN, ANXA1, CAP1, ANXA2, and MUC5B). CVF proteomic data from the discovery stage were analyzed by the partial least squares-discriminant analysis (PLS-DA) method to build a statistical model, allowing to differentiate severe dysplasia (HSIL and CANCER) from the mild/normal stage (NILM and LSIL), and receiver operating characteristic (ROC) area under the curve (AUC) were obtained on an independent set of 33 samples. The sensitivity of the model was 77%, and the specificity was 94%; AUC was equal to 0.87. CVF proteome proved to be reflect the stage of cervical epithelium neoplastic process.

Molecular analysis of semen-like odor emitted by chestnut flowers using neutral desorption extractive atmospheric pressure chemical ionization mass spectrometry.

Knowledge about the chemical composition of floral volatile organic compounds (VOCs) is valuable in biological studies as well as for the flavor, cosmetic, and fragrance industries. The flowers of Chinese chestnut (Castanea mollissima) emit a distinctive semen-like odor; however, the chemical composition and biological role for the semen-like odor of chestnut flowers remain scarcely studied. Herein, we report the floral VOCs and the pollinators of chestnut flowers. A fast method based on a neutral desorption (ND) device coupled to extractive atmospheric pressure chemical ionization mass spectrometry (EAPCI-MS) was developed for the rapid identification of VOCs from freshly collected chestnut flowers without any chemical pretreatment. Chemical identification was performed using high-resolution MS analysis in combination with tandem MS analysis and whenever possible was confirmed by the analysis of standard reference compounds. Twenty volatiles were identified, most of which are nitrogen-containing. Out of the identified volatiles, 1-pyrroline is known to have a semen-like odor and is probably also responsible for the semen-like odor of the chestnut flowers. Four nitrogenous VOCs of chestnut flowers, including 1-pyrroline, 1-piperideine, 2-pyrrolidone, and phenethylamine, were also common in other semen-like odor flowers such as Photinia serrulata, Castanopsis sclerophylla, and Stemona japonica, suggesting similar chemical origin. The main visitors of chestnut flowers were dipteran species, such as Eristalis tenax, Eristalis arvorum, Episyrphus balteatus, Lucilia sericata, Chrysomya megacephala, Chrysochus asclepiadeus, and Adalia bipunctata. Our results suggest that the chestnut flowers and other semen-like odor flowers may present a new type of sapromyophily. This study also indicates that ND-EAPCI-MS provides more sensitive and simpler detection of many VOCs (particularly nitrogen-containing VOCs) than GC-MS and therefore can be used to complement traditional approaches for the higher chemical coverage of VOCs analysis. Graphical abstract ᅟ.

Methodology for Urine Peptidome Analysis Based on Nano-HPLC Coupled to Fourier Transform Ion Cyclotron Resonance Mass Spectrometry.

Urine is a sample of choice for noninvasive biomarkers search because it is easily available in large amounts and its molecular composition provides information on processes in the organism. The high potential of urine peptidomics has been demonstrated for clinical purpose. Several mass spectrometry based approaches have been successfully applied for urine peptidome analysis and potential biomarkers search. Summarizing literature data and our own experience we developed a protocol for comprehensive urine peptidome analysis. The technology includes several stages and consists of urine sample preparation by size exclusion chromatography and identification of featured peptides by nano-HPLC coupled to Fourier transform ion cyclotron resonance mass spectrometry, semiquantitative and statistical data analysis.

Identification of potential early biomarkers of preeclampsia.

INTRODUCTION: It is thought that poor placental perfusion caused by inadequate remodelling of the maternal spiral arteries leads to preeclampsia (PE). To identify novel signalling pathways that contribute to PE pathogenesis and to create prerequisites for the non-invasive diagnosis of PE before clinical manifestations of the disease, this study aimed to evaluate miRNA expression levels in the placenta and blood plasma of pregnant women. METHODS: miRNA deep sequencing followed by real-time quantitative RT-PCR was applied to compare miRNA expression profiles in the placenta and blood plasma from women with early- and late-onset PE relative to the control group. RESULTS: A more than two-fold decrease in miR-532-5p, -423-5p, -127-3p, -539-5p, -519a-3p, and -629-5p and let-7c-5p expression levels was observed in the placenta, while a more than two-fold increase in miR-423-5p, 519a-3p, and -629-5p and let-7c-5p was observed in the blood plasma of pregnant women with PE. The above-listed miRNAs are associated with PE for the first time in this study, except for miR-519a-3p, whose role in PE has already been postulated. Using a logistic regression, plasma samples were classified into the early-onset PE group (probability p = 0.01, 80% specificity, 87.5% sensitivity and 87.5% precision) and showed increased miR-423-5p expression levels that were confirmed by the 9.8-fold up-regulation (р = 0.0002498) of miR-423-5p expression observed in the blood plasma at 11-13 GW by RT-PCR in a group of pregnant women manifesting severe PE clinical signs at 28-33 GW. CONCLUSIONS: miR-423-5p may be considered a potential candidate for the early diagnosis of PE during the targeted management of high-risk pregnancies.

Endometriosis foci differentiation by rapid lipid profiling using tissue spray ionization and high resolution mass spectrometry.

Obtaining fast screening information on molecular composition of a tissue sample is of great importance for a disease biomarkers search and for online surgery control. In this study, high resolution mass spectrometry analysis of eutopic and ectopic endometrium tissues (90 samples) is done using direct tissue spray mass spectrometry in both positive and negative ion modes. The most abundant peaks in the both ion modes are those corresponding to lipids. Species of three lipid classes are observed, phosphatidylcholines (PC), sphingomyelins (SM) and phosphoethanolamines (PE). Direct tissue analysis gives mainly information on PC and SM lipids (29 species) in positive ion mode and PC, SM and PE lipids (50 species) in negative ion mode which gives complementary data for endometriosis foci differentiation. The biggest differences were found for phospholipids with polyunsaturated acyls and alkils. Although, tissue spray shows itself as appropriate tool for tissue investigation, caution should be paid to the interpretation of mass spectra because of their higher complexity with more possible adducts formation and multiple interferences must be taken into account. The present work extends the application of direct tissue analysis for the rapid differentiation between endometriotic tissues of different foci.