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Biomarkers for Liquid Biopsies of Pituitary Neuroendocrine Tumors

Title:
Biomarkers for Liquid Biopsies of Pituitary Neuroendocrine Tumors
Authors:
Abstract:
Pituitary neuroendocrine tumors (PitNET) do not only belong to the most common intracranial neoplasms but seem to be generally more common than has been thought. Minimally invasive liquid biopsies have the potential to improve their early screening efficiency as well as monitor prognosis by facilitating the diagnostic procedures. This review aims to assess the potential of using liquid biopsies of different kinds of biomarker species that have only been obtained from solid pituitary tissues so far. Numerous molecules have been associated with the development of a PitNET, suggesting that it often develops from the cumulative effects of many smaller genetic or epigenetic changes. These minor changes eventually pile up to switch critical molecules into tumor-promoting states, which may be the key regulatory nodes representing the most potent marker substances for a diagnostic test. Drugs targeting these nodes may be superior for the therapeutic outcome and therefore the identification of such pituitary-specific cellular key nodes will help to accelerate their application in medicine. The ongoing genetic degeneration in pituitary adenomas suggests that repeated tumor profiling via liquid biopsies will be necessary for personalized and effective treatment solutions.
Year:
2020
Publication type:
Journal article
Journal:
Biomedicines
ISSN:
2227-9059
Number:
6
Volume:
8
Pages:
148
Language:
English
Document status:
Open access
PubListerURL:
https://publister.bib.th-wildau.de/publister/public/publication/2868
Gossing, W., Frohme, M., & Radke, L. (2020). Biomarkers for Liquid Biopsies of Pituitary Neuroendocrine Tumors Biomedicines. 8 (6), 148.
@article{2868,
    author           = {Gossing, Wilhelm and Frohme, Marcus and Radke, Lars},
    title            = {Biomarkers for Liquid Biopsies of Pituitary Neuroendocrine Tumors},
    journal          = {Biomedicines},
    year             = {2020},
    volume           = {8},
    number           = {6},
    pages            = {148},
    publisher        = {MDPI},
    doi              = {10.3390/biomedicines8060148},
}


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