A systematic review of extracellular vesicles as non-invasive biomarkers in glioma diagnosis, prognosis, and treatment response monitoring

Retrospective Analysis of Glioblastoma Outcomes

This retrospective mono-center study focuses on 144 cases of glioblastoma treated over a time span of 12 years in our clinic in Romania. We offer critical insight into the dreadful aspect of this tumor by highlighting the principal characteristics such as localization, the genetic information of each case, progression-free survival (PFS), and overall survival (OS). A tenth of our patients underwent a second surgical procedure, providing a comparable OS to the other part of our study group, proving that surgical treatment as salvage therapy is a viable option. Also, our research reinforces the fact that utilizing the Karnofsky Performance Scale is a great predictor of patient outcomes in glioblastoma patients. Even though radiotherapy and chemotherapy have mild effects in the context of this oncological disease, our research shows that O6-methylguanine-DNA methyltransferase (MGMT) methylation status and epidermal growth factor receptor (EGFR) amplification have an important effect on OS. Moreover, the particularity of our study, that our patients did not start adjuvant therapy right after surgery, highlighted by a low OS compared to the international literature, sheds light on the fact that chemotherapy and radiotherapy must be started right after the surgical procedure, according to the Stupp protocol. To sum up, our research takes into consideration the factors that influence patient survival and outcome in the battle against glioblastoma.

Electrochemical biosensors for early diagnosis of glioblastoma

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.

Construct of qualitative diagnostic biomarkers specific for glioma by pairing serum microRNAs

BACKGROUND

Serum microRNAs (miRNAs) are promising non-invasive biomarkers for diagnosing glioma. However, most reported predictive models are constructed without a large enough sample size, and quantitative expression levels of their constituent serum miRNAs are susceptible to batch effects, decreasing their clinical applicability.

METHODS

We propose a general method for detecting qualitative serum predictive biomarkers using a large cohort of miRNA-profiled serum samples (n = 15,460) based on the within-sample relative expression orderings of miRNAs.

RESULTS

Two panels of miRNA pairs (miRPairs) were developed. The first was composed of five serum miRPairs (5-miRPairs), reaching 100% diagnostic accuracy in three validation sets for distinguishing glioma and non-cancer controls (n = 436: glioma = 236, non-cancers = 200). An additional validation set without glioma samples (non-cancers = 2611) showed a predictive accuracy of 95.9%. The second panel included 32 serum miRPairs (32-miRPairs), reaching 100% diagnostic performance in training set on specifically discriminating glioma from other cancer types (sensitivity = 100%, specificity = 100%, accuracy = 100%), which was reproducible in five validation datasets (n = 3387: glioma = 236, non-glioma cancers = 3151, sensitivity> 97.9%, specificity> 99.5%, accuracy> 95.7%). In other brain diseases, the 5-miRPairs classified all non-neoplastic samples as non-cancer, including stroke (n = 165), Alzheimer's disease (n = 973), and healthy samples (n = 1820), and all neoplastic samples as cancer, including meningioma (n = 16), and primary central nervous system lymphoma samples (n = 39). The 32-miRPairs predicted 82.2 and 92.3% of the two kinds of neoplastic samples as positive, respectively. Based on the Human miRNA tissue atlas database, the glioma-specific 32-miRPairs were significantly enriched in the spinal cord (p = 0.013) and brain (p = 0.015).

CONCLUSIONS

The identified 5-miRPairs and 32-miRPairs provide potential population screening and cancer-specific biomarkers for glioma clinical practice.

Current Advances in Technologies for Single Extracellular Vesicle Analysis and Its Clinical Applications in Cancer Diagnosis

Extracellular vesicles (EVs) have been regarded as one of the most potential diagnostic biomarkers for different cancers, due to their unique physiological and pathological functions. However, it is still challenging to precisely analyze the contents and sources of EVs, due to their heterogeneity. Herein, we summarize the advances in technologies for a single EV analysis, which may provide new strategies to study the heterogeneity of EVs, as well as their cargo, more specifically. Furthermore, the applications of a single EV analysis on cancer early diagnosis are also discussed.

[Extracellular vesicles for diagnosis and therapy of gliomas: problems and opportunities]

Glioblastoma is a primary brain tumor and one of the most aggressive malignant neoplasms. The prognosis remains poor with a short survival period after diagnosis even in the case of timely detection and early treatment with the use of advanced chemotherapy, radiation therapy and surgical treatment. In this regard, the research of the main pathogenetic links in the glioblastoma development continues. The current focus is on studying the molecular characteristics of tumours, including the analysis of extracellular vesicles, which play an essential role in intercellular communication processes. In this review, in order to provide up-to-date information on the role of extracellular vesicles in the diagnosis and therapy of gliomas, the analysis of the achieved results of Russian and foreign research related to this area has been carried out. The main goal of this review is to describe the features of extracellular vesicles as the containers and glioma marker transporters, as well as nucleic acids used in diagnosis and therapy.

MALDI-TOF/MS Analysis of Extracellular Vesicles Released by Cancer Cells

The direct shedding of extracellular vesicles (EVs) from the plasma membrane is a recognized fundamental method for the intercellular transfer of properties in both physiological and pathological conditions. EVs are classified according to origin, biogenesis, size, content, surface markers, and/or functional properties, and contain various bioactive molecules depending on the physiological state and the type of the cells of origin including lipids, nucleic acids, and proteins. The presence of tumor-derived EVs in body fluids such as blood, ascites, urine, and saliva, together with the important role played in the tumor microenvironment where they intervene at different levels from oncogenesis to metastasis, make EVs a priority target for cancer studies. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) can play a leading role in the analysis and characterization of EVs and their load due to its intrinsic advantages such as high throughput, low sample consumption, speed, the cost-effectiveness of the analysis, and the ease of use. This work reviews the main MALDI-TOF applications for the analysis and characterization of extracellular vesicles in the tumor field.