Glial Fibrillary Acidic Protein in the Diagnosis and Prognosis of Malignant Glial Tumors

Evaluation of GFAP, S100B, and UCHL-1 Levels in Children With Refractory Epilepsy

INTRODUCTION

A number of biomarkers are used to evaluate the duration of the epileptic seizure and the interictal period following neuronal injury. Invasive diagnostic methods are increasingly being replaced by peripheral or minimally invasive biomarkers that give results faster and are more secure.

PURPOSE

We aimed to evaluate serum glial fibrillary acidic protein (GFAP), S100B, and ubiquitin C-terminal hydrolase (UCHL-1) levels in children with epilepsy.

METHODS

Our study included 3 groups: a nonrefractory epilepsy group, a refractory epilepsy group, and a control group. The GFAP, S100B, and UCHL-1 levels in serum samples collected 2-24 hours after the last seizure were analyzed using enzyme-linked immunosorbent assays.

RESULTS

A total of 69 children participated in the study, with 35 participants in the refractory epilepsy group, 18 in the nonrefractory epilepsy group, and 16 in the control group. The GFAP values in the refractory (25.4 ng/mL) and nonrefractory (26.1 ng/mL) epilepsy groups were found to be statistically significantly higher than those in the control group (17.9 ng/mL; P = .001). The S100B values were found to be significantly higher in the refractory epilepsy group (34.13 pg/mL) than in both the control group and the nonrefractory epilepsy group (28.05 pg/mL; P = .028). No significant differences were observed in the UCHL-1 levels between the 3 groups.

CONCLUSIONS

We conclude that the observed differences may be due to the increased expression of S100B and GFAP caused by increased and repetitive neuronal damage in refractory epilepsies compared with nonrefractory epilepsies.

Stroke and Emerging Blood Biomarkers: A Clinical Prospective

Stroke constitutes the primary source of adult functional disability, exhibiting a paramount socioeconomic burden. Thus, it is of great importance that the prediction of stroke outcome be both prompt and accurate. Although modern neuroimaging and neurophysiological techniques are accessible, easily available blood biomarkers reflecting underlying stroke-related pathophysiological processes, including glial and/or neuronal death, neuroendocrine responses, inflammation, increased oxidative stress, blood–brain barrier disruption, endothelial dysfunction, and hemostasis, are required in order to facilitate stroke prognosis. A literature search of two databases (MEDLINE and Science Direct) was conducted in order to trace all relevant studies published between 1 January 2010 and 31 December 2021 that focused on the clinical utility of brain natriuretic peptide, glial fibrillary acidic protein, the red cell distribution width, the neutrophil-to-lymphocyte ratio, matrix metalloproteinase-9, and aquaporin-4 as prognostic tools in stroke survivors. Only full-text articles published in English were included. Twenty-eight articles were identified and are included in this review. All studied blood-derived biomarkers proved to be valuable prognostic tools poststroke, the clinical implementation of which may accurately predict the survivors’ functional outcomes, thus significantly enhancing the rehabilitation efficiency of stroke patients. Along with already utilized clinical, neurophysiological, and neuroimaging biomarkers, a blood-derived multi-biomarker panel is proposed as a reasonable approach to enhance the predictive power of stroke prognostic models.

GlioMarker: An integrated database for knowledge exploration of diagnostic biomarkers in gliomas

Gliomas are the most frequent malignant and aggressive tumors in the central nervous system. Early and effective diagnosis of glioma using diagnostic biomarkers can prolong patients' lives and aid in the development of new personalized treatments. Therefore, a thorough and comprehensive understanding of the diagnostic biomarkers in gliomas is of great significance. To this end, we developed the integrated and web-based database GlioMarker (http://gliomarker.prophetdb.org/), the first comprehensive database for knowledge exploration of glioma diagnostic biomarkers. In GlioMarker, accurate information on 406 glioma diagnostic biomarkers from 1559 publications was manually extracted, including biomarker descriptions, clinical information, associated literature, experimental records, associated diseases, statistical indicators, etc. Importantly, we integrated many external resources to provide clinicians and researchers with the capability to further explore knowledge on these diagnostic biomarkers based on three aspects. (1) Obtain more ontology annotations of the biomarker. (2) Identify the relationship between any two or more components of diseases, drugs, genes, and variants to explore the knowledge related to precision medicine. (3) Explore the clinical application value of a specific diagnostic biomarker through online analysis of genomic and expression data from glioma cohort studies. GlioMarker provides a powerful, practical, and user-friendly web-based tool that may serve as a specialized platform for clinicians and researchers by providing rapid and comprehensive knowledge of glioma diagnostic biomarkers to subsequently facilitates high-quality research and applications.

Liquid biopsies for early diagnosis of brain tumours: in silico mathematical biomarker modelling

Brain tumours are the biggest cancer killer in those under 40 and reduce life expectancy more than any other cancer. Blood-based liquid biopsies may aid early diagnosis, prediction and prognosis for brain tumours. It remains unclear whether known blood-based biomarkers, such as glial fibrillary acidic protein (GFAP), have the required sensitivity and selectivity. We have developed a novel in silico model which can be used to assess and compare blood-based liquid biopsies. We focused on GFAP, a putative biomarker for astrocytic tumours and glioblastoma multi-formes (GBMs). In silico modelling was paired with experimental measurement of cell GFAP concentrations and used to predict the tumour volumes and identify key parameters which limit detection. The average GBM volumes of 449 patients at Leeds Teaching Hospitals NHS Trust were also measured and used as a benchmark. Our model predicts that the currently proposed GFAP threshold of 0.12 ng ml-1 may not be suitable for early detection of GBMs, but that lower thresholds may be used. We found that the levels of GFAP in the blood are related to tumour characteristics, such as vasculature damage and rate of necrosis, which are biological markers of tumour aggressiveness. We also demonstrate how these models could be used to provide clinical insight.

Blood GFAP as an emerging biomarker in brain and spinal cord disorders

Blood-derived biomarkers for brain and spinal cord diseases are urgently needed. The introduction of highly sensitive immunoassays led to a rapid increase in the number of potential blood-derived biomarkers for diagnosis and monitoring of neurological disorders. In 2018, the FDA authorized a blood test for clinical use in the evaluation of mild traumatic brain injury (TBI). The test measures levels of the astrocytic intermediate filament glial fibrillary acidic protein (GFAP) and neuroaxonal marker ubiquitin carboxy-terminal hydrolase L1. In TBI, blood GFAP levels are correlated with clinical severity and extent of intracranial pathology. Evidence also indicates that blood GFAP levels hold the potential to reflect, and might enable prediction of, worsening of disability in individuals with progressive multiple sclerosis. A growing body of evidence suggests that blood GFAP levels can be used to detect even subtle injury to the CNS. Most importantly, the successful completion of the ongoing validation of point-of-care platforms for blood GFAP might ameliorate the decision algorithms for acute neurological diseases, such as TBI and stroke, with important economic implications. In this Review, we provide a systematic overview of the evidence regarding the utility of blood GFAP as a biomarker in neurological diseases. We propose a model for GFAP concentration dynamics in different conditions and discuss the limitations that hamper the widespread use of GFAP in the clinical setting. In our opinion, the clinical use of blood GFAP measurements has the potential to contribute to accelerated diagnosis and improved prognostication, and represents an important step forward in the era of precision medicine.

Investigation of glial fibrillary acidic protein (GFAP) in body fluids as a potential biomarker for glioma: a systematic review and meta-analysis

INTRODUCTION

Liquid biopsies are promising diagnostic tools for glioma. In this quantitative systematic review, we investigate whether the detection of intermediate filaments (IF) in body fluids can be used as a tool for glioma diagnosis and prognosis.

MATERIALS AND METHODS

We included all studies in which IF-levels were determined in patients with glioma and healthy controls. Of the 28 identified eligible studies, 12 focused on levels of GFAP in serum (sGFAP) and were included for metadata analysis.

RESULTS

In all studies combined, 62.7% of all grade IV patients had detectable levels of sGFAP compared to 12.7% of healthy controls. sGFAP did not surpass the limit of detection in lower grade patients or healthy controls, but sGFAP was significantly elevated in grade IV glioma (0.12 ng/mL (0.06 - 0.18), P < 0.001) and showed an average median difference of 0.15 ng/mL (0.04 - 0.25, P < 0.01) compared to healthy controls. sGFAP levels were linked to tumour volume, but not to patient outcome.

CONCLUSION

The presence of sGFAP is indicative of grade IV glioma, but additional studies are necessary to fully determine the usefulness of GFAP in body fluids as a tool for grade IV glioma diagnosis and follow-up.

Serum glial fibrillary acidic protein is a predictor of brain metastases in patients with metastatic breast cancer

In patients with metastatic breast cancer (MBC), brain metastases (BM) are associated with high morbidity and mortality. However, there is no validated serum biomarker that accurately predicts BM occurrence in these patients, and the role of serum biomarkers for prognosis remains unclear. Here, we evaluated the association of neurofilament light chain (NfL), ubiquitin C-terminal hydrolase L1 (UCHL1), glial fibrillary acidic protein (GFAP) and tau serum levels with BM presence and prognosis in patients with MBC. In serum samples from patients with MBC with (n = 100) and without BM (n = 47), we measured the biomarker serum levels using single molecule array (Simoa) technology (Neurology-4-Plex assay). To evaluate their accuracy to identify patients with BM, we determined the receiver operating characteristic curve and the area under the curve (AUC) for each biomarker and calculated their sensitivity and specificity. The median serum levels of NfL, UCHL1, tau and GFAP were significantly higher in patients with BM. The AUC for GFAP (0.82, 95% confidence interval [CI] 0.75-0.88) was significantly higher than those of the other biomarkers considered independently. Using the medians as cutoff values, elevated serum levels of NfL, UCHL1, tau and GFAP were associated with BM in univariate analysis, but only high GFAP levels in multivariate analysis (odd ratio 23.4, 95% CI 6.8-80.5, P < .001). Elevated serum GFAP levels were independently associated with poor outcome. GFAP outperforms NfL, UCHL1 and tau as diagnostic and prognostic factor of BM in patients with MBC. These results must now be validated in an independent cohort of patients.

Blood-Based Biomarkers for Glioma in the Context of Gliomagenesis: A Systematic Review

BACKGROUND

Gliomas are the most common and aggressive tumors of the central nervous system. A robust and widely used blood-based biomarker for glioma has not yet been identified. In recent years, a plethora of new research on blood-based biomarkers for glial tumors has been published. In this review, we question which molecules, including proteins, nucleic acids, circulating cells, and metabolomics, are most promising blood-based biomarkers for glioma diagnosis, prognosis, monitoring and other purposes, and align them to the seminal processes of cancer.

METHODS

The Pubmed and Embase databases were systematically searched. Biomarkers were categorized in the identified biomolecules and biosources. Biomarker characteristics were assessed using the area under the curve (AUC), accuracy, sensitivity and/or specificity values and the degree of statistical significance among the assessed clinical groups was reported.

RESULTS

7,919 references were identified: 3,596 in PubMed and 4,323 in Embase. Following screening of titles, abstracts and availability of full-text, 262 articles were included in the final systematic review. Panels of multiple biomarkers together consistently reached AUCs >0.8 and accuracies >80% for various purposes but especially for diagnostics. The accuracy of single biomarkers, consisting of only one measurement, was far more variable, but single microRNAs and proteins are generally more promising as compared to other biomarker types.

CONCLUSION

Panels of microRNAs and proteins are most promising biomarkers, while single biomarkers such as GFAP, IL-10 and individual miRNAs also hold promise. It is possible that panels are more accurate once these are involved in different, complementary cancer-related molecular pathways, because not all pathways may be dysregulated in cancer patients. As biomarkers seem to be increasingly dysregulated in patients with short survival, higher tumor grades and more pathological tumor types, it can be hypothesized that more pathways are dysregulated as the degree of malignancy of the glial tumor increases. Despite, none of the biomarkers found in the literature search seem to be currently ready for clinical implementation, and most of the studies report only preliminary application of the identified biomarkers. Hence, large-scale validation of currently identified and potential novel biomarkers to show clinical utility is warranted.