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  • 1
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    Endometriosis foci differentiation by rapid lipid profiling using tissue spray ionization and high resolution mass spectrometry
    Springer Science and Business Media LLC ; 2017
    In:  Scientific Reports Vol. 7, No. 1 ( 2017-05-31)
    Details
    In: Scientific Reports, Springer Science and Business Media LLC, Vol. 7, No. 1 ( 2017-05-31)
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 2045-2322
    URL: Article
    DOI: 10.1038/s41598-017-02708-x
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2017
    detail.hit.zdb_id: 2615211-3
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  • 2
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    miRNAs and Their Gene Targets—A Clue to Differentiate Pregnancies with Small for Gestational Age Newborns, Intrauterine Growth Restriction, and Preeclampsia
    MDPI AG ; 2021
    In:  Diagnostics Vol. 11, No. 4 ( 2021-04-20), p. 729-
    Details
    In: Diagnostics, MDPI AG, Vol. 11, No. 4 ( 2021-04-20), p. 729-
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 2075-4418
    URL: Article
    DOI: 10.3390/diagnostics11040729
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2662336-5
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  • 3
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    Validation of Breast Cancer Margins by Tissue Spray Mass Spectrometry
    MDPI AG ; 2020
    In:  International Journal of Molecular Sciences Vol. 21, No. 12 ( 2020-06-26), p. 4568-
    Details
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 21, No. 12 ( 2020-06-26), p. 4568-
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 1422-0067
    URL: Article
    DOI: 10.3390/ijms21124568
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2019364-6
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  • 4
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    Blood Plasma Small Non-Coding RNAs as Diagnostic Molecules for the Progesterone-Receptor-Negative Phenotype of Serous Ovarian Tumors
    MDPI AG ; 2023
    In:  International Journal of Molecular Sciences Vol. 24, No. 15 ( 2023-07-30), p. 12214-
    Details
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 24, No. 15 ( 2023-07-30), p. 12214-
    Abstract: The expression level of the progesterone receptor (PGR) plays a crucial role in determining the biological characteristics of serous ovarian carcinoma. Low PGR expression is associated with chemoresistance and a poorer outcome. In this study, our objective was to explore the relationship between tumor progesterone receptor levels and RNA profiles (miRNAs, piwiRNAs, and mRNAs) to understand their biological characteristics and behavior. To achieve this, we employed next-generation sequencing of small non-coding RNAs, quantitative RT-PCR, and immunohistochemistry to analyze both FFPE and frozen tumor samples, as well as blood plasma from patients with benign cystadenoma (BSC), serous borderline tumor (SBT), low-grade serous ovarian carcinoma (LGSOC), and high-grade serous ovarian carcinoma (HGSOC). Our findings revealed significant upregulation of MMP7 and MUC16, along with downregulation of PGR, in LGSOC and HGSOC compared to BSC. We observed significant correlations of PGR expression levels in tumor tissue with the contents of miR-199a-5p, miR-214-3p, miR-424-3p, miR-424-5p, and miR-125b-5p, which potentially target MUC16, MMP7, and MMP9, as well as with the tissue content of miR-16-5p, miR-17-5p, miR-20a-5p, and miR-93-5p, which are associated with the epithelial–mesenchymal transition (EMT) of cells. The levels of EMT-associated miRNAs were significantly correlated with the content of hsa_piR_022437, hsa_piR_009295, hsa_piR_020813, hsa_piR_004307, and hsa_piR_019914 in tumor tissues. We developed two optimal logistic regression models using the quantitation of hsa_piR_020813, miR-16-5p, and hsa_piR_022437 or hsa_piR_004307, hsa_piR_019914, and miR-93-5p in the tumor tissue, which exhibited a significant ability to diagnose the PGR-negative tumor phenotype with 93% sensitivity. Of particular interest, the blood plasma levels of miR-16-5p and hsa_piR_022437 could be used to diagnose the PGR-negative tumor phenotype with 86% sensitivity even before surgery and chemotherapy. This knowledge can help in choosing the most effective treatment strategy for this aggressive type of ovarian cancer, such as neoadjuvant chemotherapy followed by cytoreduction in combination with hyperthermic intraperitoneal chemotherapy and targeted therapy, thus enhancing the treatment’s effectiveness and the patient’s longevity.
    Type of Medium: Online Resource
    ISSN: 1422-0067
    URL: Article
    DOI: 10.3390/ijms241512214
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2019364-6
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  • 5
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    Label‐free cervicovaginal fluid proteome profiling reflects the cervix neoplastic transformation
    Wiley ; 2019
    In:  Journal of Mass Spectrometry Vol. 54, No. 8 ( 2019-08), p. 693-703
    Details
    In: Journal of Mass Spectrometry, Wiley, Vol. 54, No. 8 ( 2019-08), p. 693-703
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 1076-5174 , 1096-9888
    URL: Issue
    URL: Article
    DOI: 10.1002/jms.v54.8
    DOI: 10.1002/jms.4374
    Language: English
    Publisher: Wiley
    Publication Date: 2019
    detail.hit.zdb_id: 2197367-2
    detail.hit.zdb_id: 1472468-6
    detail.hit.zdb_id: 7414-7
    SSG: 11
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  • 6
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    Feature selection for OPLS discriminant analysis of cancer tissue lipidomics data
    Wiley ; 2020
    In:  Journal of Mass Spectrometry Vol. 55, No. 1 ( 2020-01)
    Details
    In: Journal of Mass Spectrometry, Wiley, Vol. 55, No. 1 ( 2020-01)
    Abstract: 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 ( Q 2 = 0.64, area under curve [AUC] = 0.95); the second one is OPLS‐DA model with lipid peaks selected by random forest algorithm ( Q 2 = 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 ( Q 2 = 0.48, AUC = 0.86).
    Type of Medium: Online Resource
    ISSN: 1076-5174 , 1096-9888
    URL: Issue
    URL: Article
    DOI: 10.1002/jms.v55.1
    DOI: 10.1002/jms.4457
    Language: English
    Publisher: Wiley
    Publication Date: 2020
    detail.hit.zdb_id: 2197367-2
    detail.hit.zdb_id: 1472468-6
    detail.hit.zdb_id: 7414-7
    SSG: 11
    SSG: 12
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  • 7
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    Investigation of urine proteome of preterm newborns with respiratory pathologies
    Elsevier BV ; 2016
    In:  Journal of Proteomics Vol. 149 ( 2016-10), p. 31-37
    Details
    In: Journal of Proteomics, Elsevier BV, Vol. 149 ( 2016-10), p. 31-37
    Type of Medium: Online Resource
    ISSN: 1874-3919
    URL: Article
    DOI: 10.1016/j.jprot.2016.06.012
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2016
    detail.hit.zdb_id: 2400835-7
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  • 8
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    Shotgun Lipidomics for Differential Diagnosis of HPV-Associated Cervix Transformation
    MDPI AG ; 2022
    In:  Metabolites Vol. 12, No. 6 ( 2022-05-31), p. 503-
    Details
    In: Metabolites, MDPI AG, Vol. 12, No. 6 ( 2022-05-31), p. 503-
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 2218-1989
    URL: Article
    DOI: 10.3390/metabo12060503
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2662251-8
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  • 9
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    Search for New Participants in the Pathogenesis of High-Grade Serous Ovarian Cancer with the Potential to Be Used as Diagnostic Molecules
    MDPI AG ; 2022
    In:  Life Vol. 12, No. 12 ( 2022-12-03), p. 2017-
    Details
    In: Life, MDPI AG, Vol. 12, No. 12 ( 2022-12-03), p. 2017-
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 2075-1729
    URL: Article
    DOI: 10.3390/life12122017
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2662250-6
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  • 10
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    Integrating Proteomics and Lipidomics for Evaluating the Risk of Breast Cancer Progression: A Pilot Study
    MDPI AG ; 2023
    In:  Biomedicines Vol. 11, No. 7 ( 2023-06-22), p. 1786-
    Details
    In: Biomedicines, MDPI AG, Vol. 11, No. 7 ( 2023-06-22), p. 1786-
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 2227-9059
    URL: Article
    DOI: 10.3390/biomedicines11071786
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2720867-9
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