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Your search keyword '"Drebert, Zuzanna"' showing total 19 results
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19 results on '"Drebert, Zuzanna"'

2. Age at Type 2 Diabetes Diagnosis and Risk of Cancer: Cohort Study in Over 1 Million Individuals from the TriNetX US Collaborative Network

Author

Slater, Tommy, primary, Hernández Ibarburu, Gema, additional, Drebert, Zuzanna, additional, Henson, Joseph, additional, Zaccardi, Francesco, additional, Sargeant, Jack A., additional, Brown, Karen, additional, Webb, David R., additional, Papamargaritis, Dimitris, additional, Chan, Juliana C. N., additional, W. Gregg, Edward, additional, Khunti, Kamlesh, additional, Davies, Melanie J., additional, and Yates, Tom, additional

Published
2024
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6. Exploring Breast Cancer Systemic Drug Therapy Patterns in Real-World Data

Author

O'Rourke, Julia, Warnick, Jeff, Doole, John, De Keyser, Luc, Drebert, Zuzanna, Wan, Olivia, Thompson, Courtney N, London, Jack W., Fairchild, Karen, Palchuk, Matvey B., O'Rourke, Julia, Warnick, Jeff, Doole, John, De Keyser, Luc, Drebert, Zuzanna, Wan, Olivia, Thompson, Courtney N, London, Jack W., Fairchild, Karen, and Palchuk, Matvey B.

Abstract

PURPOSE: To explore medications and their administration patterns in real-world patients with breast cancer. METHODS: A retrospective study was performed using TriNetX, a federated network of deidentified, Health Insurance Portability and Accountability Act-compliant data from 21 health care organizations across North America. Patients diagnosed with breast cancer between January 1, 2013, and May 31, 2022, were included. We investigated a rule-based and unsupervised learning algorithm to extract medications and their administration patterns. To group similar administration patterns, we used three features in k-means clustering: total number of administrations, median number of days between administrations, and standard deviation of the days between administrations. We explored the first three lines of therapy for patients classified into six groups on the basis of their stage at diagnosis (early as stages I-III RESULTS: In early-stage HR+/ CONCLUSION: Although there is a general agreement with the NCCN Guidelines, real-world medication data exhibit variability in the medications and their administration patterns.

Published
2023

11. Colon cancer-derived myofibroblasts increase endothelial cell migration by glucocorticoid-sensitive secretion of a pro-migratory factor

Author

Drebert, Zuzanna, MacAskill, Mark, Doughty-Shenton, Dahlia, De Bosscher, Karolien, Bracke, Marc, Hadoke, Patrick W.F., and Beck, Ilse M.

Subjects
Male, Time Factors, Physiology, Angiogenesis Inhibitors, Dexamethasone, Tissue Culture Techniques, Glucocorticoid, Cancer-Associated Fibroblasts, Endothelial cell, Cell Movement, PROSTAGLANDINS, Tumor Microenvironment, Medicine and Health Sciences, Myofibroblasts, Cell Line, Transformed, Cancer, Neovascularization, Pathologic, Colonic Neoplasms, Molecular Medicine, Signal Transduction, GROWTH-FACTOR, Neovascularization, Physiologic, Article, TUMOR ANGIOGENESIS, MECHANISMS, TENASCIN-C, Paracrine Communication, Human Umbilical Vein Endothelial Cells, Animals, Humans, PLASMINOGEN-ACTIVATOR, Glucocorticoids, Angiopoietin-Like Protein 2, Cell Proliferation, Pharmacology, Myofibroblast, RECEPTOR, Endothelial Cells, Biology and Life Sciences, Ribonuclease, Pancreatic, IN-VITRO, Urokinase-Type Plasminogen Activator, Mice, Inbred C57BL, Angiopoietin-like Proteins, Culture Media, Conditioned, HEPATOCYTE GROWTH, Angiogenesis, Stromal Cells, Angiopoietins, GASTRIC-CANCER
Abstract

Angiogenesis is important in cancer progression and can be influenced by tumor-associated myofibroblasts. We addressed the hypothesis that glucocorticoids indirectly affect angiogenesis by altering the release of pro-angiogenic factors from colon cancer-derived myofibroblasts. Our study shows that glucocorticoids reduced prostanoids, urokinase-type plasminogen activator (uPA) and angiopoietin-like protein-2 (ANGPTL2) levels, but increased angiogenin (ANG) in supernatant from human CT5.3hTERT colon cancer-derived myofibroblasts. Conditioned medium from solvent- (CMS) and dexamethasone (Dex)-treated (CMD) myofibroblasts increased human umbilical vein endothelial cell (HUVEC) proliferation, but did not affect expression of pro-angiogenic factors or tube-like structure formation (by HUVECs or human aortic ECs). In a HUVEC scratch assay CMS-induced acceleration of wound healing was blunted by CMD treatment. Moreover, CMS-induced neovessel growth in mouse aortic rings ex vivo was also blunted using CMD. The latter effect could be ascribed to both Dex-driven reduction of secreted factors and potential residual Dex present in CMD (indicated using a dexamethasone-spiked CMS control). A similar control in the scratch assay, however, revealed that altered levels of factors in the CMD, and not potential residual Dex, were responsible for decreased wound closure. In conclusion, our results suggest that glucocorticoids indirectly alter endothelial cell function during tumor development in vivo., Graphical abstract Image 1

Published
2016

16. Correction: Compound A, a Selective Glucocorticoid Receptor Modulator, Enhances Heat Shock Protein Hsp70 Gene Promoter Activation

Author

Beck, Ilse M., primary, Drebert, Zuzanna J., additional, Hoya-Arias, Ruben, additional, Bahar, Ali A., additional, Devos, Michael, additional, Clarisse, Dorien, additional, Desmet, Sofie, additional, Bougarne, Nadia, additional, Ruttens, Bart, additional, Gossye, Valerie, additional, Denecker, Geertrui, additional, Lievens, Sam, additional, Bracke, Marc, additional, Tavernier, Jan, additional, Declercq, Wim, additional, Gevaert, Kris, additional, Berghe, Wim Vanden, additional, Haegeman, Guy, additional, and De Bosscher, Karolien, additional

Published
2013
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17. Compound A, a Selective Glucocorticoid Receptor Modulator, Enhances Heat Shock Protein Hsp70 Gene Promoter Activation

Author

Beck, Ilse M., primary, Drebert, Zuzanna J., additional, Hoya-Arias, Ruben, additional, Bahar, Ali A., additional, Devos, Michael, additional, Clarisse, Dorien, additional, Desmet, Sofie, additional, Bougarne, Nadia, additional, Ruttens, Bart, additional, Gossye, Valerie, additional, Denecker, Geertrui, additional, Lievens, Sam, additional, Bracke, Marc, additional, Tavernier, Jan, additional, Declercq, Wim, additional, Gevaert, Kris, additional, Berghe, Wim Vanden, additional, Haegeman, Guy, additional, and De Bosscher, Karolien, additional

Published
2013
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19. Potential of Text Mining in Data Integration and Network Biology for Plant Research: A Case Study on Arabidopsis.

Author

Landeghem, Sofie Van, Bodt, Stefanie De, Drebert, Zuzanna J., Inzé, Dirk, and Peer, Yves Van de

Subjects
TEXT mining, DATA mining, DATA integration, DATA libraries, ARABIDOPSIS
Abstract

Despite the availability of various data repositories for plant research, a wealth of information currently remains hidden within the biomolecular literature. Text mining provides the necessary means to retrieve these data through automated processing of texts. However, only recently has advanced text mining methodology been implemented with sufficient computational power to process texts at a large scale. In this study, we assess the potential of large-scale text mining for plant biology research in general and for network biology in particular using a state-of-the-art text mining system applied to all PubMed abstracts and PubMed Central full texts. We present extensive evaluation of the textual data for Arabidopsis thaliana , assessing the overall accuracy of this new resource for usage in plant network analyses. Furthermore, we combine text mining information with both protein–protein and regulatory interactions from experimental databases. Clusters of tightly connected genes are delineated from the resulting network, illustrating how such an integrative approach is essential to grasp the current knowledge available for Arabidopsis and to uncover gene information through guilt by association. All large-scale data sets, as well as the manually curated textual data, are made publicly available, hereby stimulating the application of text mining data in future plant biology studies. [ABSTRACT FROM AUTHOR]

Published
2013
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