Microvesicles and Microvesicle-Associated microRNAs Reflect Glioblastoma Regression: Microvesicle-Associated miR-625-5p Has Biomarker Potential

Glioblastoma (GB) is the most aggressive and recurrent form of brain cancer in adults. We hypothesized that the identification of biomarkers such as certain microRNAs (miRNAs) and the circulating microvesicles (MVs) that transport them could be key to establishing GB progression, recurrence and therapeutic response. For this purpose, circulating MVs were isolated from the plasma of GB patients (before and after surgery) and of healthy subjects and characterized by flow cytometry. OpenArray profiling and the individual quantification of selected miRNAs in plasma and MVs was performed, followed by target genes’ prediction and in silico survival analysis. It was found that MVs’ parameters (number, EGFRvIII and EpCAM) decreased after the surgical resection of GB tumors, but the inter-patient variability was high. The expression of miR-106b-5p, miR-486-3p, miR-766-3p and miR-30d-5p in GB patients’ MVs was restored to control-like levels after surgery: miR-106b-5p, miR-486-3p and miR-766-3p were upregulated, while miR-30d-5p levels were downregulated after surgical resection. MiR-625-5p was only identified in MVs isolated from GB patients before surgery and was not detected in plasma. Target prediction and pathway analysis showed that the selected miRNAs regulate genes involved in cancer pathways, including glioma. In conclusion, miR-625-5p shows potential as a biomarker for GB regression or recurrence, but further in-depth studies are needed.


Introduction
The clinical hallmarks of glioblastoma (GB), the most aggressive form of adult brain cancer, are high tumor heterogeneity, extensive vascularization, fast growth and invasiveness, poor survival and minimal response to therapy [1,2]. The latest World Health Organization (WHO) classification of tumors of the central nervous system (CNS) [3] relies on clinical presentation and histological data, as well as molecular markers for the diagnosis of GB. Therefore, GB (GB, isocitrate dehydrogenase (IDH)-wildtype) is now classified as an adult-type diffuse and astrocytic glioma, characterized by "microvascular proliferation or necrosis or telomerase reverse transcriptase (TERT) promoter mutation or epidermal

Quantifying Circulating Plasma MVs and GB-Specific Surface Markers
Flow cytometry was used to analyze and characterize MVs isolated from plasma, including the detection of EGFR, EGFRvIII and EpCAM expression on their surface (Figures 1 and 2). Control subjects had significantly lower circulating MV levels (2.34 times) compared to Pre-op GB patients (Figure 1a), in agreement with previous reports [32,36], which suggests increased intercellular communication and possibly the release of MVs from GB tumors. In addition, the circulating plasma MV concentrations (Annexin-Vpositive MVs) decreased slightly (1.37 times) in GB patients' plasma after surgical resection (Figure 1a), in agreement with Skog et al. [13]. Moreover, Koch et al. [36] showed that MVs' number could be used to distinguish true progression from the pseudo-progression of GB. Representative dot-plots show the MV quantification and characterization strategy based on calibrated size beads and PS staining as a specific marker for MVs (Figure 1b). They also highlight the purity of MVs isolated, confirmed by PS staining with Annexin V-FITC (Figure 1b). , 23, x FOR PEER REVIEW 3 of 16 compared to Pre-op GB patients (Figure 1a), in agreement with previous reports [32,36], which suggests increased intercellular communication and possibly the release of MVs from GB tumors. In addition, the circulating plasma MV concentrations (Annexin-V-positive MVs) decreased slightly (1.37 times) in GB patients' plasma after surgical resection (Figure 1a), in agreement with Skog et al. [13]. Moreover, Koch et al. [36] showed that MVs' number could be used to distinguish true progression from the pseudo-progression of GB. Representative dot-plots show the MV quantification and characterization strategy based on calibrated size beads and PS staining as a specific marker for MVs (Figure 1b). They also highlight the purity of MVs isolated, confirmed by PS staining with Annexin V-FITC ( Figure 1b). Our flow cytometric analysis revealed that Annexin-V-positive MVs express GB-specific markers: EGFR, EGFRvIII and EpCAM ( Figure 2). There was no difference in EGFR expression on MVs' surface between the Pre-op and Post-op groups (Figure 2a). EGFRvIII expression decreased (2.85 times) after the surgical resection of GB tumors (Figure 2b), in  with results reported by Skog et al. [13], and EpCAM expression decreased slightly (1.36 times) after surgery (Figure 2c). Although we did not find statistically significant differences between the Pre-op and Post-op groups, these results are consistent with previously published reports [13,34] which show high variability in surface GB markers' expression between patients, most likely depending on the molecular profiles of their tumors.

MiRNA Expression Profile in Circulating Plasma MVs
The TaqMan OpenArray Human Advanced MicroRNA Panel, which allows the simultaneous quantification of 754 miRNAs, was used to determine the miRNA expression profile in circulating MVs isolated from the plasma of GB patients and Control subjects. By applying cutoffs for the good amplification quality of CRT < 28 and amplification score > 1, as previously suggested [37], we identified a total of 133 miRNAs expressed in all three groups of subjects ( Figure 3a). Compared to the Pre-op group, we identified 1 upregulated (fold change > 2) and 10 downregulated (fold change < 0.5) miRNAs in the Control group and 22 upregulated (fold change > 2) miRNAs in the Post-op group, presented in Figure 3b and Table 1. We found no miRNAs downregulated (fold change < 0.5) in the Post-op group compared to the Pre-op group.  Our flow cytometric analysis revealed that Annexin-V-positive MVs express GBspecific markers: EGFR, EGFRvIII and EpCAM ( Figure 2). There was no difference in EGFR expression on MVs' surface between the Pre-op and Post-op groups ( Figure 2a). EGFRvIII expression decreased (2.85 times) after the surgical resection of GB tumors (Figure 2b), in agreement with results reported by Skog et al. [13], and EpCAM expression decreased slightly (1.36 times) after surgery ( Figure 2c). Although we did not find statistically significant differences between the Pre-op and Post-op groups, these results are consistent with previously published reports [13,34] which show high variability in surface GB markers' expression between patients, most likely depending on the molecular profiles of their tumors.

miRNA Expression Profile in Circulating Plasma MVs
The TaqMan OpenArray Human Advanced MicroRNA Panel, which allows the simultaneous quantification of 754 miRNAs, was used to determine the miRNA expression profile in circulating MVs isolated from the plasma of GB patients and Control subjects. By applying cutoffs for the good amplification quality of C RT < 28 and amplification score > 1, as previously suggested [37], we identified a total of 133 miRNAs expressed in all three groups of subjects ( Figure 3a). Compared to the Pre-op group, we identified 1 upregulated (fold change > 2) and 10 downregulated (fold change < 0.5) miRNAs in the Control group and 22 upregulated (fold change > 2) miRNAs in the Post-op group, presented in Figure 3b and Table 1. We found no miRNAs downregulated (fold change < 0.5) in the Post-op group compared to the Pre-op group.
Int. J. Mol. Sci. 2022, 23, x FOR PEER REVIEW 4 agreement with results reported by Skog et al. [13], and EpCAM expression decr slightly (1.36 times) after surgery (Figure 2c). Although we did not find statisticall nificant differences between the Pre-op and Post-op groups, these results are cons with previously published reports [13,34] which show high variability in surfac markers' expression between patients, most likely depending on the molecular prof their tumors.

MiRNA Expression Profile in Circulating Plasma MVs
The TaqMan OpenArray Human Advanced MicroRNA Panel, which allows the ultaneous quantification of 754 miRNAs, was used to determine the miRNA expre profile in circulating MVs isolated from the plasma of GB patients and Control sub By applying cutoffs for the good amplification quality of CRT < 28 and amplification > 1, as previously suggested [37], we identified a total of 133 miRNAs expressed three groups of subjects ( Figure 3a). Compared to the Pre-op group, we identified regulated (fold change > 2) and 10 downregulated (fold change < 0.5) miRNAs in the trol group and 22 upregulated (fold change > 2) miRNAs in the Post-op group, pres in Figure 3b and Table 1. We found no miRNAs downregulated (fold change < 0.5) Post-op group compared to the Pre-op group.   Analyzing all data obtained in the OpenArray profiling, we selected five miRNAs for further analysis ( Figure 4): four miRNAs whose levels were restored to control-like levels after surgery (miR-106b-5p, miR-486-3p, miR-766-3p (upregulated) and miR-30d-5p (downregulated)) and one miRNA which was only expressed in the Pre-op group (miR-625-5p).  Analyzing all data obtained in the OpenArray profiling, we selected five miRNAs for further analysis ( Figure 4): four miRNAs whose levels were restored to control-like levels after surgery (miR-106b-5p, miR-486-3p, miR-766-3p (upregulated) and miR-30d-5p (downregulated)) and one miRNA which was only expressed in the Pre-op group (miR-625-5p).  To date, there are few studies investigating these selected miRNAs in GB progression. It has been reported that miR-106b-5p promotes glioma cell lines' proliferation, migration and invasion [38,39], regulates the M2 polarization of glioma-infiltrating macrophages [40] and inhibits tumor cell apoptosis in vitro and in vivo [39]. Furthermore, Liu et al. [39] showed that miR-106b-5p had significantly higher expression in GB tumor samples and cell lines than in normal brain tissue, correlated with disease grading. Regarding miR-486-3p, it was determined through in vitro and in vivo experiments that its overexpression increases chemosensitivity to temozolomide by directly targeting O6-methylguanine-DNA methyltransferase (MGMT) [41]. Furthermore, miR-486-3p was found to be overexpressed in primary glioma tissues, promoting glioma aggression, and its levels were correlated with tumor grade and poor overall survival [42]. MiR-766-3p was reported to act as a tumor suppressor in different types of cancers [43,44], but, to the best of our knowledge, its role in glioma has not been investigated. On the other hand, miR-30d-5p was demonstrated to be involved in the development and progression of different types of cancers [45], but, to the best of our knowledge, its involvement in glioma progression has not been investigated. It has been reported that miR-625-5p inhibits glioma cells' proliferation, migration and invasion and increases their chemosensitivity [46,47]. Furthermore, Zhang et al. [46] reported significantly lower miR-625 expression in tumor samples and cell lines compared to normal brain tissue and astrocytes.

miRNA Quantification in Circulating MVs and Plasma
Selected miRNAs were quantified using real-time PCR in circulating plasma MVs and plasma samples from GB patients and Control subjects. The individual quantification of miR-106b-5p, miR-486-3p, miR-766-3p, miR-30d-5p and miR-625-5p in MVs confirmed the OpenArray results.
The levels of miR-106b-5p (p = 0.0309, paired t-test), miR-486-3p and miR-766-3p were upregulated in MVs from Post-op patients compared to Pre-op (Figure 5a-c), while miR-30d-5p levels (p = 0.0285, paired t-test) were downregulated after surgical resection ( Figure 5d). Additionally, the levels of miR-30d-5p were significantly increased in MVs from Pre-op patients compared to Post-op (p = 0.0039, One-Way ANOVA) and Control MVs (p = 0.0013, One-Way ANOVA) (Figure 5d). In contrast to our results, Hallal et al. [48] found higher levels of miR-106b-5p and miR-486-3p and lower levels of miR-30d-5p in cavitron ultrasonic surgical aspirate (CUSA) and serum EVs from GB patients compared to Controls. However, the same study reported low levels of miR-766-3p in CUSA and serum-EVs compared to Controls and grade II-III glioma, respectively, and high levels of miR-30d-5p in CUSA EVs compared to grade II-III glioma [48], in agreement with our results. Confirming the OpenArray findings, miR-625-5p was only detected in MVs from Pre-op patients (Figure 5e). To the best of our knowledge, this is the first study which reports the quantification of miR-625-5p in circulating MVs from the plasma of GB patients.
Interestingly, miR-106b-5p and miR-30d-5p expression was significantly lower in patients' plasma (regardless of surgical status) compared to Control subjects' plasma ( Figure 6a,d). Additionally, plasma miR-30d-5p expression was significantly decreased (p = 0.0047, paired t-test) in GB patients' plasma after surgery (Figure 6d). Plasma miR-486-3p expression was also decreased in patients' plasma compared to Controls (Figure 6b). Given the fact that miR-106b-5p and miR-486-3p are significantly overexpressed in GB tumors compared to normal brain tissue [39], our results suggest a reduced export of miR-106b-5p and miR-486-3p to circulation in GB patients. The expression of miR-766-3p in plasma samples mirrored the results obtained for MVs, being decreased in Pre-op patients compared to Controls and Post-op patients (Figure 6c). Additionally, miR-625-5p was not detected in plasma samples from GB patients or Control subjects, suggesting it could be specifically transported by MVs. Interestingly, miR-106b-5p and miR-30d-5p expression was significantly lower in patients' plasma (regardless of surgical status) compared to Control subjects' plasma ( Figure  6a,d). Additionally, plasma miR-30d-5p expression was significantly decreased (p = 0.0047, paired t-test) in GB patients' plasma after surgery (Figure 6d). Plasma miR-486-3p expression was also decreased in patients' plasma compared to Controls (Figure 6b). Given the fact that miR-106b-5p and miR-486-3p are significantly overexpressed in GB tumors compared to normal brain tissue [39], our results suggest a reduced export of miR-106b-5p and miR-486-3p to circulation in GB patients. The expression of miR-766-3p in plasma samples mirrored the results obtained for MVs, being decreased in Pre-op patients compared to Controls and Post-op patients (Figure 6c). Additionally, miR-625-5p was not detected in plasma samples from GB patients or Control subjects, suggesting it could be specifically transported by MVs.

In Silico Survival Analysis
Using the OncoLnc online platform [51], we investigated whether the selected miR-NAs' expression was associated with GB patients' survival. In the first stage, we obtained the Cox regression results for the selected miRNAs in GB patients, presented in Table 2. The high expression of miRNAs is correlated with the risk of death if the Cox coefficient has a positive value, while the opposite is indicated by a negative Cox coefficient [51].

In Silico Survival Analysis
Using the OncoLnc online platform [51], we investigated whether the selected miRNAs' expression was associated with GB patients' survival. In the first stage, we obtained the Cox regression results for the selected miRNAs in GB patients, presented in Table 2. The high expression of miRNAs is correlated with the risk of death if the Cox coefficient has a positive value, while the opposite is indicated by a negative Cox coefficient [51]. The calculated Cox coefficients show that the high expression of miR-106b-5p correlates with the survival of GB patients. This, combined with miR-106b-5p levels increasing after surgical resection, suggests that MV-associated miR-106b-5p has biomarker potential for GB progression. On the other hand, the high expression of miR-766-3p is correlated with the risk of death, indicating an inverse relationship between tissue and circulating levels. The high expression of miR-30d-5p is correlated with the risk of death, which is in line with our results that miR-30d-5p expression is decreased in GB patients' MVs after surgery. However, these correlations are weak and lack statistical significance ( Table 2). On the other hand, the high expression of miR-625-5p correlates significantly (0.333, p = 0.035) with the risk of death, being in agreement with our results for miR-625-5p expression in MVs being restricted only to the Pre-op group. The OncoLnc platform did not return any results for miR-486-3p in GB.
In the second stage, we obtained the Kaplan-Meier curves and log-rank p-values for each miRNA, estimating the association between miRNA expression and GB patients' survival ( Figure 9). We observed the longer survival of patients with high levels of miR-766-3p, as well as of patients with low levels of miR-625-5p. However, the log-rank p-values were not significant. There was no difference between the survival time of patients with low or high expression levels of miR-106b-5p and miR-30d-5p.

Study Limitations
There are some limitations to our study that we feel we need to mention, namely: (1) freezing the platelet-poor plasma at −80 • C and its subsequent thawing can affect the integrity of MVs obtained by successive centrifugations and characterized by flow cytometry. This problem was prevented by the easy defrosting of samples at room temperature. (2) The contamination of MVs with blood components may exist. To avoid this situation, MVs were washed two times with PBS. (3) There was a risk of incorrectly counting MVs due to contamination of the samples rich in MVs (obtained at 20,000 g) with a small number of apoptotic bodies. The use of counting beads in flow cytometry experiments allowed us to set the MV gate according to their size distribution. (4) Although MVs isolated from plasma were washed with PBS several times, it is possible some plasma miRNAs could have been carried over. However, the specificity and sensitivity of the TaqMan technology mitigates this potential limitation. (5) Survival analysis using the OncoLnc platform was performed using normalized microarray values of miRNAs from tissue samples, and these values may not always correlate with circulating levels. Further studies are needed in this regard, and bio-banks containing body fluid samples from GB patients would be very useful. 3p, as well as of patients with low levels of miR-625-5p. However, the log-rank p-values were not significant. There was no difference between the survival time of patients with low or high expression levels of miR-106b-5p and miR-30d-5p.

Study Limitations
There are some limitations to our study that we feel we need to mention, namely: (1) freezing the platelet-poor plasma at -80˚C and its subsequent thawing can affect the integrity of MVs obtained by successive centrifugations and characterized by flow cytometry. This problem was prevented by the easy defrosting of samples at room temperature. (2) The contamination of MVs with blood components may exist. To avoid this situation, MVs were washed two times with PBS. (3) There was a risk of incorrectly counting MVs due to contamination of the samples rich in MVs (obtained at 20,000 g) with a small number of apoptotic bodies. The use of counting beads in flow cytometry experiments allowed us to set the MV gate according to their size distribution. (4) Although MVs isolated from plasma were washed with PBS several times, it is possible some plasma miRNAs could have been carried over. However, the specificity and sensitivity of the TaqMan technology mitigates this potential limitation. (5) Survival analysis using the OncoLnc platform was performed using normalized microarray values of miRNAs from tissue samples, and these values may not always correlate with circulating levels. Further studies are needed in this regard, and bio-banks containing body fluid samples from GB patients would be very useful.

Study Design and Sample Collection
Patients with GB from the North East region of Romania were recruited after presenting with specific symptomatology [52] at "Prof. Dr. Nicolae Oblu" Emergency Clinical Hospital, Iasi. Patients' selection was conducted without discrimination in terms of gender, ethnicity or religion. Exclusion criteria were non-compliant patients, autoimmune diseases or acute infections (including SARS-CoV-2). Patients underwent the typical diagnosis protocol, including anamnesis, neurological examination, routine blood tests and brain magnetic resonance imaging (MRI). Next, patients underwent the maximum safe surgical resection (aided by tumor fluorescence induced by 5-aminolevulinic acid (5-ALA)) [53]. Healthy volunteers (Controls) were recruited from the staff of the Centre of Advanced Research in Bionanoconjugates and Biopolymers, "Petru Poni" Institute of Macromolecular Chemistry, Iasi. The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Ethics Committee of "Prof. Dr. Nicolae Oblu" Emergency Clinical Hospital (no. 19092/21.11.2019). Informed consent was obtained from all subjects involved in the study.
Peripheral blood was collected on tripotassium ethylenediaminetetraacetic acid (K 3 -EDTA) anticoagulant from Control subjects (one time) and from GB patients before (Pre-op) and one week after the surgical resection of the tumor (Post-op). Peripheral blood was centrifuged at 2500× g for 10 min at 4 • C to collect the platelet-poor plasma (PPP) from the supernatant, which was then aliquoted and stored at −80 • C until further processing. Hemolyzed blood samples were not included in the study.

MV Isolation
Total circulating MVs were isolated from plasma by sequential centrifugations, using a previously published protocol [35] with some modifications. The platelet-poor plasma (PPP) was centrifuged at 16,000× g for 5 min at 4 • C to remove residual platelets, apoptotic bodies and collect the platelet-free plasma (PFP) in supernatant [54]. MVs were then isolated from PFP by centrifugation at 20,000× g for 90 min at 4 • C, and pelleted MVs were washed twice (20,000× g, 90 min, 4 • C) with Phosphate-Buffered Saline (PBS), re-suspended in PBS and stored at −80 • C until further analysis. For miRNA OpenArray profiling in MVs, equal amounts of plasma were pooled for each group: Control (n = 5), Pre-op (n = 5) and Post-op (n = 5), and MVs were isolated using the protocol described above.

MV Characterization by Flow Cytometry
MVs were analyzed by flow cytometry using a Gallios Flow Cytometer (Beckman Coulter Life Sciences, CA, USA). Resuspended MVs (10 µL) were mixed with 10 µL of counting beads (1000 beads/µL, 10 µm diameter) and 100 µL of PBS and counted for 60 s. The dot-plot representations (X = forward-scatter intensity, Y = sidescatter intensity) were analyzed in order to determine the number of MVs (0.1-1 µm diameter) in the samples according to the calculation formula: MVs as events/µL = [(MV count/bead count) × bead concentration/µL] × MV purity/100, as previously described [35]. In order to determine MV purity, 10 µL of resuspended MVs was incubated with 2.5 µL of Annexin V antibody (Annexin V Monoclonal Antibody (VAA-33), FITC, eBioscience, Thermo Fisher Scientific, Waltham, MA, USA) in the presence of 2 mM CaCl 2 for 40 min at room temperature in the dark, diluted with 100 µL of PBS and analyzed by flow cytometry, as previously described [35]. The isotype control experiments were performed as well.
The expression of GB-specific surface markers on MVs was determined using antibodies against EGFR (EGFR monoclonal antibody (

RNA Isolation
Total miRNAs were isolated from 200 µL of plasma or purified MVs (resuspended in 200 µL of PBS) using the miRNeasy Serum/Plasma Advanced kit (Qiagen, Hilden, Germany), according to the manufacturer's instructions. For technical normalization purposes, 25 fmol of synthetic cel-miR-39 (Qiagen, Hilden, Germany) was added as spike-in during miRNA isolation from plasma and MVs, as previously described [55]. Purified miRNAs were eluted with 18 µL of RNase-free water and stored at −80 • C until further analysis.

OpenArray Profiling of miRNAs in MVs
For miRNA OpenArray profiling, miRNAs purified from pooled plasma-derived MVs were used. A poly(A) tailing reaction, adaptor ligation reaction, reverse transcription (RT) and miR-amplification reactions were performed on a Veriti 96-Well Thermal Cycler, using the TaqMan Advanced miRNA cDNA Synthesis Kit (both from Applied Biosystems, Thermo Fisher Scientific, Waltham, MA, USA), according to the manufacturer's protocol. MiRNA profiling was performed using the TaqMan OpenArray Human Advanced MicroRNA Panel and the TaqMan OpenArray Real-Time PCR Master Mix on a QuantStudio 12K Flex Real-Time PCR System with OpenArray block and an AccuFill System (all from Applied Biosystems, Thermo Fisher Scientific, Waltham, MA, USA), according to the manufacturer's protocol. The obtained data were analyzed using the QuantStudio 12K Flex Software v1.2 and the ExpressionSuite Software v1.3 (both from Applied Biosystems, Thermo Fisher Scientific, Waltham, MA, USA). The expression level of each miRNA was determined relative to miR-16-5p, as recommended by the manufacturer, calculated using the 2 −∆∆Cq method [56] and represented as the fold change (relative quantification, RQ) of Pre-op values for each target. Raw data passed all quality control checks and were filtered by applying cutoffs of C RT < 28 and amp score > 1 (measures of good amplification) [37]. Significant miRNAs were identified and selected for measurement in individual MV and plasma samples.

Target Gene Prediction and Pathway Analysis
Target gene prediction was performed for miRNAs selected after OpenArray profiling using the miRWalk tool v3.0 (http://mirwalk.umm.uni-heidelberg.de/, accessed on 29 June 2022), with a score cutoff of ≥0.95 and miRTarBase filter in order to only obtain validated targets [49]. Pathway analysis was conducted with DIANA-miRPath using the miRTarBase algorithm [50].

In Silico Survival Analysis
The OncoLnc portal (http://www.oncolnc.org, accessed on 24 June 2022) was used to determine the associations between the selected miRNAs' expression and the survival of GB patients [51]. This platform returns multivariate Cox regression results, as well as Kaplan-Meier plots and log-rank p-values for the analysis [51]. The analysis was performed on data from 563 patients from the TCGA database using the upper 25% and lower 25% slices.

Statistical Analysis
GraphPad Prism 8 software (GraphPad Software Inc., San Diego, CA, USA) was used for statistical analysis. Data were expressed as means ± standard error of the mean and analyzed using a paired t-test (Pre-op vs. Post-op) or One-Way ANOVA with Tukey's multiple comparisons test, considering p < 0.05 as statistically significant.

Conclusions
Circulating plasma MV levels were positively correlated with GB severity. The surgical resection of GB tumors decreased MVs' parameters, namely their number, as well as the expression of the EGFRvIII and EpCAM receptors, but the inter-patient variability was high. The expression of miR-106b-5p, miR-486-3p, miR-766-3p and miR-30d-5p in GB patients' MVs was restored to control-like levels after surgery: miR-106b-5p, miR-486-3p and miR-766-3p were upregulated, while miR-30d-5p levels were downregulated after surgical resection. MiR-625-5p was only identified in MVs isolated from Pre-op GB patients and was not detected in plasma. Target prediction and pathway analysis showed that the selected miRNAs regulate genes involved in cancer pathways, including glioma.
In conclusion, miR-625-5p shows potential as a biomarker for GB regression or recurrence, but further in-depth studies are required in order to establish these miRNAs as biomarkers for GB severity and to elucidate their mechanisms of action in GB progression.  Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.

Data Availability Statement:
The data presented in this study are available on request from the corresponding author.