Glioblastoma is a primary Central Nervous System (CNS) malignancy with poor survival. Treatment options are scarce and despite the extremely heterogeneous nature of the disease, clinicians lack prognostic and predictive markers to characterize patients with different outcomes. Certain immunohistochemistry, FISH, or PCR-based molecular markers, including isocitrate dehydrogenase1/2 (IDH1/2) mutations, epidermal growth factor receptor variant III (EGFRvIII) mutation, vascular endothelial growth factor overexpression (VEGF) overexpression, or (O6-Methylguanine-DNA methyltransferase promoter) MGMT promoter methylation status, are well-described; however, their clinical usefulness and accuracy is limited, and tumor tissue samples are always necessary. Liquid biopsy is a developing field of diagnostics and patient follow up in multiple types of cancer. Fragments of circulating nucleic acids are collected in various forms from different bodily fluids, including serum, urine, or cerebrospinal fluid in order to measure the quality and quantity of these markers. Multiple types of nucleic acids can be analyzed using liquid biopsy. Circulating cell-free DNA, mitochondrial DNA, or the more stable long and small non-coding RNAs, circular RNAs, or microRNAs can be identified and measured by novel PCR and next-generation sequencing-based methods. These markers can be used to detect the previously described alterations in a minimally invasive method. These markers can be used to differentiate patients with poor or better prognosis, or to identify patients who do not respond to therapy. Liquid biopsy can be used to detect recurrent disease, often earlier than using imaging modalities. Liquid biopsy is a rapidly developing field, and similarly to other types of cancer, measuring circulating tumor-derived nucleic acids from biological fluid samples could be the future of differential diagnostics, patient stratification, and follow up in the future in glioblastoma as well.

Glioblastoma is the most common malignant central nervous system tumor. Patient outcome remains poor despite the development of therapy and increased understanding of the disease in the past decades. Glioma cells invade the peritumoral brain, which results in inevitable tumor recurrence. Previous studies have demonstrated that the extracellular matrix (ECM) is altered in gliomas and serves a major role in glioma invasion. The present study focuses on differences in the ECM composition of tumors in patients with poor and improved prognosis. The mRNA and protein expression of 16 invasion‑associated ECM molecules was determined using reverse trascription‑quantitiative polymerase chain reaction and immunohistochemistry, respectively. Clinical factors of patients with different prognoses was also analyzed. It was determined that age and postoperative Karnofsky performance score were associated with patient survival. Furthermore, Fms‑related tyrosine kinase 4/vascular endothelial growth factor receptor 3 (FLT4/VEGFR3), murine double minute 2 (MDM2) and matrix metallopeptidase 2 (MMP2) mRNA levels were significantly different between the two prognostic groups. Additionally, brevican, cluster of differentiation 44, hyaluronan mediated motility receptor, integrin‑αV and ‑β1, and MDM2 protein expression were indicated to be significantly different in immunohistochemistry slides. Using the expression profile, including the invasion spectrum of the samples, it was possible to identify the prognostic group of the sample with high efficacy, particularly in cases with poor prognosis. In conclusion, it was determined that ECM components exhibit different expression levels in tumors with different prognoses and thus the invasion spectrum can be used as a prognostic factor in glioblastoma.

Although treatment outcomes of glioblastoma, the most malignant central nervous system (CNS) tumor, has improved in the past decades, it is still incurable, and survival has only slightly improved. Advances in molecular biology and genetics have completely transformed our understanding of glioblastoma. Multiple classifications and different diagnostic methods were made according to novel molecular markers. Discovering tumor heterogeneity only partially explains the ineffectiveness of current anti-proliferative therapies. Dynamic heterogeneity secures resistance to combined oncotherapy. As tumor growth proceeds, new therapy-resistant sub clones emerge. Liquid biopsy is a new and promising diagnostic tool that can step up with the dynamic genetic change. Getting a ’real-time’ picture of a specific tumor, anti-invasion and multi-target treatment can be designed. During invasion to the peri-tumoral brain tissue, glioma cells interact with the extracellular matrix components. The expressional levels of these matrix molecules give a characteristic pattern, the invasion spectrum, which possess vast diagnostical, predictive and prognostic information. It is a huge leap forward combating tumor heterogeneity and searching for novel therapies. Using the invasion spectrum of a tumor sample is a novel tool to distinguish between histological subtypes, specifying the tumor grades or different prognostic groups. Moreover, new therapeutic methods and their combinations are under trial. These are crucial steps towards personalized oncotherapy.

(1) Background: Glioblastoma multiforme (GBM) is among the most aggressive cancers with a poor prognosis. Treatment options are limited, clinicians lack efficient prognostic and predictive markers. Circulating miRNAs—besides being important regulators of cancer development—may have potential as diagnostic biomarkers of GBM. (2) Methods: In this study, profiling of 798 human miRNAs was performed on blood plasma samples from 6 healthy individuals and 6 patients with GBM, using a NanoString nCounter Analysis System. To validate our results, five miRNAs (hsa-miR-433-3p, hsa-miR-362-3p, hsa-miR-195-5p, hsa-miR-133a-3p, and hsa-miR-29a-3p) were randomly chosen for RT-qPCR detection. (3) Results: In all, 53 miRNAs were significantly differentially expressed in plasma samples of GBM patients when data were filtered for FC 1 and FDR 0.1. Target genes of the top 39 differentially expressed miRNAs were identified, and we carried out functional annotation and pathway enrichment analysis of target genes via GO and KEGG-based tools. General and cortex-specific protein–protein interaction networks were constructed from the target genes of top miRNAs to assess their functional connections. (4) Conclusions: We demonstrated that plasma microRNA profiles are promising diagnostic and prognostic molecular biomarkers that may find an actual application in the clinical practice of GBM, although more studies are needed to validate our results.

Background Glioblastoma multiforme (GBM) is the most common malignant disease of the central nervous system. Its prognosis is unfavorable, and the median overall survival of patients is 16 to 24 months. The main cause of the poor survival data are the extensive invasion of cancer cells to the neighboring parenchyma, thus leading to inevitable local recurrence. The extracellular matrix (ECM) is a known factor in tumor invasion, and differences in the ECM of nontumor brain and glioblastoma has been proven. Methods In this research, 20 invasion-related expressions of ECM components were determined in 26 GBM flash-frozen samples using quantitative reverse transcription-polymerase chain reaction and proteomic measurements. Expression data were then set against the survival data of the patients. Results Significant alterations between groups with different survival rates could not be established in the individual evaluation of the expression level of the selected molecules. However, statistical analysis of the expression pattern of invasion-related molecules revealed a correlation with prognosis. The positive predictive values of the messenger RNA (mRNA) and the proteomic expression studies were 0.85 and 0.89, respectively. The receiver operation characteristic value was 0.775 for the mRNA expression data and 0.875 for the protein expression data. Furthermore, a group of molecules, including brevican, cadherin-12, integrin β1, integrin α3, laminin α4, and laminin β1, that play a prominent role in invasion were identified. Conclusions Joint assessment of the expression of invasion-related molecules provides a specific invasion spectrum of the tumor that correlates with the survival of glioblastoma patients. Using statistical classifiers enables the adoption of an invasion spectrum as a considerably accurate prognostic factor while gaining predictive information on potential molecular oncotherapeutic targets at the same time. ^* These authors contributed equally.