Electrochemical Biosensors for Early Diagnosis of Glioblastoma Publisher Pubmed

Summary: Electrochemical biosensors show promise for early glioblastoma detection, offering real-time, affordable monitoring over traditional imaging. #BrainCancer #Biosensors

Vatankhahan H¹ ; Esteki F² ; Jabalameli MA³ ; Kiani P⁴ ; Ehtiati S⁵ ; Movahedpour A⁶ ; Vakili O^{4, 7} ; Khatami SH⁸
Source: Clinica Chimica Acta Published:2024

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 inter-observer 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. © 2024 Elsevier B.V.