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.

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.

Understanding the coordinated regulation of the hundreds of carbohydrate-active enzyme (CAZyme) genes occurring in the genomes of fungi has great practical importance. We recorded genome-wide transcriptional changes of Aspergillus nidulans cultivated on glucose, lactose, or arabinogalactan, as well as under carbon-starved conditions. We determined both carbon-stress-specific changes (weak or no carbon source vs. glucose) and carbon-source-specific changes (one type of culture vs. all other cultures). Many CAZyme genes showed carbon-stress-specific and/or carbon-source-specific upregulation on arabinogalactan (138 and 62 genes, respectively). Besides galactosidase and arabinan-degrading enzyme genes, enrichment of cellulolytic, pectinolytic, mannan, and xylan-degrading enzyme genes was observed. Fewer upregulated genes, 81 and 107 carbon stress specific, and 6 and 16 carbon source specific, were found on lactose and in carbon-starved cultures, respectively. They were enriched only in galactosidase and xylosidase genes on lactose and rhamnogalacturonanase genes in both cultures. Some CAZyme genes (29 genes) showed carbon-source-specific upregulation on glucose, and they were enriched in β-1,4-glucanase genes. The behavioral ecological background of these characteristics was evaluated to comprehensively organize our knowledge on CAZyme production, which can lead to developing new strategies to produce enzymes for plant cell wall saccharification.

Xenoestrogens are natural or synthetic compounds that mimic the effect of endogenous estrogens and might cause cancer. We aimed to compare the global transcriptomic response to zearalenone (ZEA; mycotoxin) and bisphenol A (BPA; plastic additive) with the effect of physiological estradiol (E2) in the PEO1 human ovarian cell line by mRNA and microRNA sequencing. Estrogen exposure induced remarkable transcriptomic changes: 308, 288 and 63 genes were upregulated (log₂FC > 1); 292, 260 and 45 genes were downregulated (log₂FC < −1) in response to E2 (10 nM), ZEA (10 nM) and BPA (100 nM), respectively. Furthermore, the expression of 13, 11 and 10 miRNAs changed significantly (log₂FC > 1, or log₂FC < −1) after exposure to E2, ZEA and BPA, respectively. Functional enrichment analysis of the significantly differentially expressed genes and miRNAs revealed several pathways related to the regulation of cell proliferation and migration. The effect of E2 and ZEA was highly comparable: 407 genes were coregulated by these molecules. We could identify 83 genes that were regulated by all three treatments that might have a significant role in the estrogen response of ovarian cells. Furthermore, the downregulation of several miRNAs (miR-501-5p, let-7a-2-3p, miR-26a-2-3p, miR-197-5p and miR-582-3p) was confirmed by qPCR, which might support the proliferative effect of estrogens in ovarian cells.

(1) Background: Glioblastoma (GBM) is one of the most aggressive brain tumors with a poor prognosis. Therefore, new insights into GBM diagnosis and treatment are required. In addition to differentially expressed mRNAs, miRNAs may have the potential to be applied as diagnostic biomarkers. (2) Methods: In this study, profiling of human miRNAs in combination with mRNAs was performed on total RNA isolated from tissue samples of five control and five GBM patients, using a high-throughput RNA sequencing (RNA-Seq) approach. (3) Results: A total of 35 miRNAs and 365 mRNAs were upregulated, while 82 miRNAs and 1225 mRNAs showed significant downregulation between tissue samples of GBM patients compared to the control samples using the iDEP tool to analyze RNA-Seq data. To validate our results, the expression of five miRNAs (hsa-miR-196a-5p, hsa-miR-21-3p, hsa-miR-10b-3p, hsa-miR-383-5p, and hsa-miR-490-3p) and fourteen mRNAs (E2F2, HOXD13, VEGFA, CDC45, AURKB, HOXC10, MYBL2, FABP6, PRLHR, NEUROD6, CBLN1, HRH3, HCN1, and RELN) was determined by RT-qPCR assay. The miRNet tool was used to build miRNA–target interaction. Furthermore, a protein–protein interaction (PPI) network was created from the miRNA targets by applying the NetworkAnalyst 3.0 tool. Based on the PPI network, a functional enrichment analysis of the target proteins was also carried out. (4) Conclusions: We identified an miRNA panel and several deregulated mRNAs that could play an important role in tumor development and distinguish GBM patients from healthy controls with high sensitivity and specificity using total RNA isolated from tissue samples.