The Quest for Non-Invasive Diagnosis: A Review of Liquid Biopsy in Glioblastoma

Glioblastoma multiforme (GBM) remains the most common and fatal primary brain tumour, with low survival rates due to its heterogeneous nature. Traditional diagnostic methods, such as magnetic resonance imaging (MRI), computed tomography (CT) scans, and invasive tissue biopsies for histopathological analysis, are often insufficient in differentiating treatment-related changes from tumour progression, leading to misdiagnosis and delays. Repeated biopsies are impractical for ongoing monitoring due to their invasive nature. A promising alternative is liquid biopsy, a minimally invasive procedure that analyses biofluids like blood and cerebrospinal fluid (CSF) for tumour-related biomarkers. Tumours release a variety of components into the bloodstream, including circulating tumour cells (CTCs), circulating tumour DNA (ctDNA), microRNAs (miRNAs), extracellular vesicles (EVs), and proteins, which can cross the blood-brain barrier and provide a non-invasive means of assessing genetic, epigenetic, proteomic, and metabolomic markers associated with GBM. Liquid biopsy can be performed multiple times throughout the disease course, offering a rapid way to gather critical and changing tumour information. However, challenges remain in the clinical implementation of liquid biopsies for GBM diagnosis, including low levels of circulating biomarkers and the lack of standardised assays for biofluid collection and analysis. Combining multiple biomarkers from various bio-elements, such as CTCs, ctDNA, miRNAs, and EVs, could enhance sensitivity and specificity, addressing some of these limitations. The integration of artificial intelligence (AI) for analysing liquid biopsy biomarkers holds great promise in overcoming these challenges. AI can enhance biomarker identification, improve diagnostic accuracy, and expand the clinical utility of liquid biopsy in GBM management. Further research, and large-scale clinical validation are needed to optimise these approaches. This review explores the potential of GBM biomarkers found in blood and CSF samples, focusing on their applications in diagnosis, prediction, and prognosis, and highlights recent advancements, challenges, and future perspectives, including the integration of AI to improve outcomes in GBM management. Liquid biopsies bridge the gap between invasive methods and emerging technologies, offering transformative potential for GBM diagnosis and treatment.