(2024) Electrochemical biosensors for early diagnosis of glioblastoma. Clinica Chimica Acta. p. 12. ISSN 0009-8981
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Abstract
Glioblastoma (GBM) is a highly aggressive and life-threatening neurological malignancy of predominant astrocyte origin. This type of neoplasm can develop in either the brain or the spine and is also known as glioblastoma multiforme. Although current diagnostic methods such as magnetic resonance imaging (MRI) and positron emission tomography (PET) facilitate tumor location, these approaches are unable to assess disease severity. Furthermore, interpretation of imaging studies requires significant expertise which can have substantial interobserver variability, thus challenging diagnosis and potentially delaying treatment. In contrast, biosensing systems offer a promising alternative to these traditional approaches. These technologies can continuously monitor specific molecules, providing valuable real-time data on treatment response, and could significantly improve patient outcomes. Among various types of biosensors, electrochemical systems are preferred over other types, as they do not require expensive or complex equipment or procedures and can be made with readily available materials and methods. Moreover, electrochemical biosensors can detect very small amounts of analytes with high accuracy and specificity by using various signal amplification strategies and recognition elements. Considering the advantages of electrochemical biosensors compared to other biosensing methods, we aim to highlight the potential application(s) of these sensors for GBM theranostics. The review's innovative insights are expected to antecede the development of novel biosensors and associated diagnostic platforms, ultimately restructuring GBM detection strategies.
Item Type: | Article |
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Keywords: | Glioblastoma Inflammation Biosensing techniques Electrochemical biosensors Point-of-care testing extracellular vesicles promoter methylation glioma-cells cancer tumor serum cd44 DNA inflammation association Medical Laboratory Technology |
Page Range: | p. 12 |
Journal or Publication Title: | Clinica Chimica Acta |
Journal Index: | ISI |
Volume: | 557 |
Identification Number: | https://doi.org/10.1016/j.cca.2024.117878 |
ISSN: | 0009-8981 |
Depositing User: | خانم ناهید ضیائی |
URI: | http://eprints.mui.ac.ir/id/eprint/29890 |
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