MMP-9 as Prognostic Marker for Brain Tumours: A Comparative Study on Serum-Derived Small Extracellular Vesicles

Association of Matrix Metalloproteinase-9 Genotypes With Nasopharyngeal Carcinoma Risk

BACKGROUND/AIM

The up-regulation of matrix metalloproteinase-9 (MMP-9) expression is a characteristic feature observed across various malignancies, including nasopharyngeal carcinoma (NPC). Nevertheless, the influence of MMP-9 genotype in the context of NPC remains underexplored. This study examined the implications of MMP-9 promoter rs3918242 genotypes on the susceptibility to NPC in Taiwan.

MATERIALS AND METHODS

In a cohort comprising 208 NPC cases and 416 healthy controls, genotyping of MMP-9 rs3918242 was conducted utilizing polymerase chain reaction-restriction fragment length polymorphism methodology.

RESULTS

Individuals harbouring the variant CT or TT genotype of MMP-9 rs3918242 did not demonstrate a discernible alteration in NPC risk when compared to wild-type CC carriers [odds ratio (OR)=0.83 and 0.79, with 95% confidence intervals (95%CI)=0.56-1.24 and 0.27-2.29; p=0.4205 and 0.8675, respectively]. Moreover, the presence of the variant T allele did not confer a modified risk of NPC (OR=0.84, 95%CI=0.60-1.19, p=0.3761). Intriguingly, a protective effect associated with the MMP-9 rs3918242 CT genotype against NPC risk was discerned among individuals abstaining from betel quid chewing behaviour (OR=0.51, 95%CI=0.30-0.87, p=0.0166). Notably, no significant association was established between the MMP-9 rs3918242 CT or TT genotype and NPC risk among individuals with or without smoking or alcohol consumption habits.

CONCLUSION

Presence of the variant CT or TT genotype at MMP-9 rs3918242 did not appear to substantially contribute to an elevated risk of NPC. Notably, a protective effect against NPC risk was observed in individuals carrying the CT genotype, particularly in those abstaining from betel quid chewing.

Effect of TIMPs and Their Minimally Engineered Variants in Blocking Invasion and Migration of Brain Cancer Cells

Matrix metalloproteinases (MMPs) play a pivotal role in extracellular matrix (ECM) remodeling, influencing various aspects of cancer progression including migration, invasion, angiogenesis, and metastasis. Overexpression of MMPs, particularly MMP-2 and MMP-9, is notably pronounced in glioblastoma multiforme (GBM), a highly aggressive primary brain tumor characterized by diffuse and infiltrative behavior. Previous attempts to develop small molecule MMP inhibitors have failed in clinical trials, necessitating the exploration of more stable and selective alternatives. Tissue inhibitors of metalloproteinases (TIMPs), endogenous human proteins, offer promising potential due to their stability and broader interaction interfaces compared to small molecule inhibitors. In this study, we examined the effectiveness of wild-type human TIMP-1 and TIMP-3, alongside engineered minimal TIMP variants (mTC1 and mTC3), specifically designed for targeted MMP inhibition to reduce the migratory and invasive capabilities of GBM cells. Our investigation focused on these minimal TIMP variants, which provide enhanced tissue penetration and cellular uptake due to their small molecular weight, aiming to validate their potential as therapeutic agents. The results demonstrated that mTC1 and mTC3 effectively inhibit MMP activity, a critical factor in GBM aggressiveness, thereby highlighting their promise in controlling tumor spread. Given the lethality of GBM and the limited effectiveness of current treatments, the application of engineered TIMP variants represents a novel and potentially transformative therapeutic approach. By offering targeted MMP inhibition, these variants may significantly improve patient outcomes, providing new avenues for treatment and enhancing the survival and quality of life for patients with this devastating disease.

Extracellular vesicles in glioblastoma: Biomarkers and therapeutic tools

Glioblastoma (GBM) is the most aggressive tumor among the gliomas and intracranial tumors and to date prognosis for GBM patients remains poor, with a median survival typically measured in months to a few years depending on various factors. Although standardized therapies are routinely employed, it is clear that these strategies are unable to cope with heterogeneity and invasiveness of GBM. Furthermore, diagnosis and monitoring of responses to therapies are directly dependent on tissue biopsies or magnetic resonance imaging (MRI) techniques. From this point of view, liquid biopsies are arising as key sources of a variety of biomarkers with the advantage of being easily accessible and monitorable. In this context, extracellular vesicles (EVs), physiologically shed into body fluids by virtually all cells, are gaining increasing interest both as natural carriers of biomarkers and as specific signatures even for GBM. What makes these vesicles particularly attractive is they are also emerging as therapeutical vehicles to treat GBM given their native ability to cross the blood-brain barrier (BBB). Here, we reviewed recent advances on the use of EVs as biomarker for liquid biopsy and nanocarriers for targeted delivery of anticancer drugs in glioblastoma.

Cysteamine Suppresses Cancer Cell Invasion and Migration in Glioblastoma through Inhibition of Matrix Metalloproteinase Activity

Glioblastoma (GBM) cells are highly invasive, infiltrating the surrounding normal brain tissue, thereby limiting the efficacy of surgical resection and focal radiotherapy. Cysteamine, a small aminothiol molecule that is orally bioavailable and approved for cystinosis, has potential as a cancer treatment by inhibiting tumor cell invasion and metastasis. Here we demonstrate that these potential therapeutic effects of cysteamine are likely due to the inhibition of matrix metalloproteinases (MMPs) in GBM. In vitro assays confirmed that micromolar concentrations of cysteamine were not cytotoxic, enabling the interrogation of the cellular effects without confounding tumor cell loss. Cysteamine's inhibition of MMP activity, especially the targeting of MMP2, MMP9, and MMP14, was observed at micromolar concentrations, suggesting the mechanism of action in suppressing invasion and cell migration is by inhibition of these MMPs. These findings suggest that achievable micromolar concentrations of cysteamine effectively inhibit cancer cell invasion and migration in GBM, supporting the potential for use as an adjunct cancer treatment.

System biology approach to identify the novel biomarkers in glioblastoma multiforme tumors by using computational analysis

Introduction: The most common primary brain tumor in adults is glioblastoma multiforme (GBM), accounting for 45.2% of all cases. The characteristics of GBM, a highly aggressive brain tumor, include rapid cell division and a propensity for necrosis. Regretfully, the prognosis is extremely poor, with only 5.5% of patients surviving after diagnosis. Methodology: To eradicate these kinds of complicated diseases, significant focus is placed on developing more effective drugs and pinpointing precise pharmacological targets. Finding appropriate biomarkers for drug discovery entails considering a variety of factors, including illness states, gene expression levels, and interactions between proteins. Using statistical techniques like p-values and false discovery rates, we identified differentially expressed genes (DEGs) as the first step in our research for identifying promising biomarkers in GBM. Of the 132 genes, 13 showed upregulation, and only 29 showed unique downregulation. No statistically significant changes in the expression of the remaining genes were observed. Results: Matrix metallopeptidase 9 (MMP9) had the greatest degree in the hub biomarker gene identification, followed by (periostin (POSTN) at 11 and Hes family BHLH transcription factor 5 (HES5) at 9. The significance of the identification of each hub biomarker gene in the initiation and advancement of glioblastoma multiforme was brought to light by the survival analysis. Many of these genes participate in signaling networks and function in extracellular areas, as demonstrated by the enrichment analysis.We also identified the transcription factors and kinases that control proteins in the proteinprotein interactions (PPIs) of the DEGs. Discussion: We discovered drugs connected to every hub biomarker. It is an appealing therapeutic target for inhibiting MMP9 involved in GBM. Molecular docking investigations indicated that the chosen complexes (carmustine, lomustine, marimastat, and temozolomide) had high binding affinities of -6.3, -7.4, -7.7, and -8.7 kcal/mol, respectively, the mean root-mean-square deviation (RMSD) value for the carmustine complex and marimastat complex was 4.2 Å and 4.9 Å, respectively, and the lomustine and temozolomide complex system showed an average RMSD of 1.2 Å and 1.6 Å, respectively. Additionally, high stability in root-mean-square fluctuation (RMSF) analysis was observed with no structural conformational changes among the atomic molecules. Thus, these in silico investigations develop a new way for experimentalists to target lethal diseases in future.

The potential and promise for clinical application of adoptive T cell therapy in cancer

Adoptive cell therapy has revolutionized cancer treatment, especially for hematologic malignancies. T cells are the most extensively utilized cells in adoptive cell therapy. Currently, tumor-infiltrating lymphocytes, T cell receptor-transgenic T cells and chimeric antigen receptor T cells are the three main adoptive T cell therapies. Tumor-infiltrating lymphocytes kill tumors by reinfusing enlarged lymphocytes that naturally target tumor-specific antigens into the patient. T cell receptor-transgenic T cells have the ability to specifically destroy tumor cells via the precise recognition of exogenous T cell receptors with major histocompatibility complex. Chimeric antigen receptor T cells transfer genes with specific antigen recognition structural domains and T cell activation signals into T cells, allowing T cells to attack tumors without the assistance of major histocompatibility complex. Many barriers have been demonstrated to affect the clinical efficacy of adoptive T cell therapy, such as tumor heterogeneity and antigen loss, hard trafficking and infiltration, immunosuppressive tumor microenvironment and T cell exhaustion. Several strategies to improve the efficacy of adoptive T cell therapy have been explored, including multispecific chimeric antigen receptor T cell therapy, combination with immune checkpoint blockade, targeting the immunosuppressive tumor microenvironment, etc. In this review, we will summarize the current status and clinical application, followed by major bottlenecks in adoptive T cell therapy. In addition, we will discuss the promising strategies to improve adoptive T cell therapy. Adoptive T cell therapy will result in even more incredible advancements in solid tumors if the aforementioned problems can be handled.

Innovation in Non-Invasive Diagnosis and Disease Monitoring for Meningiomas

Meningiomas are tumors of the central nervous system that vary in their presentation, ranging from benign and slow-growing to highly aggressive. The standard method for diagnosing and classifying meningiomas involves invasive surgery and can fail to provide accurate prognostic information. Liquid biopsy methods, which exploit circulating tumor biomarkers such as DNA, extracellular vesicles, micro-RNA, proteins, and more, offer a non-invasive and dynamic approach for tumor classification, prognostication, and evaluating treatment response. Currently, a clinically approved liquid biopsy test for meningiomas does not exist. This review provides a discussion of current research and the challenges of implementing liquid biopsy techniques for advancing meningioma patient care.

Exploring the therapeutic mechanisms and prognostic targets of Biochanin A in glioblastoma via integrated computational analysis and in vitro experiments

Glioblastoma (GBM) is the most aggressive brain tumor and is characterized by a poor prognosis and high recurrence and mortality rates. Biochanin A (BCA) exhibits promising clinical anti-tumor effects. In this study, we aimed to explore the pharmacological mechanisms by which BCA acts against GBM. Network pharmacology was employed to identify overlapping target genes between BCA and GBM. Differentially expressed genes from the Gene Expression Profiling Interactive Analysis 2 (GEPIA2) database were visualized using VolcaNose. Interactions among these overlapping genes were analyzed using the Search Tool for the Retrieval of Interacting Genes/Proteins database. Protein-protein interaction networks were constructed using Cytoscape 3.8.1. The Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology enrichment analyses were conducted using the Database for Annotation, Visualization, and Integrated Discovery. Survival analyses for these genes were performed using the GEPIA2 database. The Chinese Glioma Genome Atlas database was used to study the correlations between key prognostic genes. Molecular docking was confirmed using the DockThor database and visualized with PyMol software. Cell viability was assessed via the CCK-8 assay, apoptosis and the cell cycle stages were examined using flow cytometry, and protein expression was detected using western blotting. In all, 63 genes were initially identified as potential targets for BCA in treating GBM. Enrichment analysis suggested that the pharmacological mechanisms of BCA primarily involved cell cycle inhibition, induction of cell apoptosis, and immune regulation. Based on these findings, AKT1, EGFR, CASP3, and MMP9 were preliminarily predicted as key prognostic target genes for BCA in GBM treatment. Furthermore, molecular docking analysis suggested stable binding of BCA to the target protein. In vitro experiments revealed the efficacy of BCA in inhibiting GBM, with an IC50 value of 98.37 ± 2.21 μM. BCA inhibited cell proliferation, induced cell apoptosis, and arrested the cell cycle of GBM cells. Furthermore, the anti-tumor effects of BCA on U251 cells were linked to the regulation of the target protein. We utilized integrated bioinformatics analyses to predict targets and confirmed through experiments that BCA possesses remarkable anti-tumor activities. We present a novel approach for multi-target treatment of GBM using BCA.

Predictive role of glycocalyx components and MMP-9 in cardiopulmonary bypass patients for ICU stay

Background

Shedding of glycocalyx is relevant to worse prognosis in surgical patients, and elevated levels of serum matrix metalloproteinase-9 (MMP-9) are associated with this phenomenon. This study aimed to investigate the dynamic alterations of serum glycocalyx components and MMP-9 during cardiopulmonary bypass (CPB), and evaluate their predictive capacities for prolonged intensive care unit (ICU) stay, as well as their correlation with coagulation dysfunction.

Methods

This retrospective study analyzed serum levels of syndecan-1, heparan sulfate (HS), and MMP-9 at different time points during CPB, and assessed their association with prolonged ICU stay and coagulation dysfunction.

Results

Syndecan-1, HS, and MMP-9 exhibited divergent changes during CPB. Serum levels of syndecan-1 (AUC = 78.0 %) and MMP-9 (AUC = 78.4 %) were validated as reliable predictors for prolonged ICU stay, surpassing the predictive value of creatinine (AUC = 70.0 %). Syndecan-1 (rho = 0.566, P < 0.01 at T1 and rho = 0.526, P < 0.01 at T2) and HS (rho = 0.403, P < 0.05 at T4) exhibited correlations with activated partial thromboplastin time (APTT) ratio beyond the normal range.

Conclusions

Our findings advocate the potential efficacy of serum glycocalyx components and MMP-9 as early predictive indicators for extended ICU stay following cardiac surgery with CPB. Additionally, we observed a correlation between glycocalyx disruption during CPB and coagulation dysfunction. Further studies with expansive cohorts are warranted to consolidate our findings and explore the predictive potential of other glycocalyx components.

The coming of age of liquid biopsy in neuro-oncology

The clinical role of liquid biopsy in oncology is growing significantly. In gliomas and other brain tumours, targeted sequencing of cell-free DNA (cfDNA) from CSF may help differential diagnosis when surgery is not recommended and be more representative of tumour heterogeneity than surgical specimens, unveiling targetable genetic alterations. Given the invasive nature of lumbar puncture to obtain CSF, the quantitative analysis of cfDNA in plasma is a lively option for patient follow-up. Confounding factors may be represented by cfDNA variations due to concomitant pathologies (inflammatory diseases, seizures) or clonal haematopoiesis. Pilot studies suggest that methylome analysis of cfDNA from plasma and temporary opening of the blood-brain barrier by ultrasound have the potential to overcome some of these limitations. Together with this, an increased understanding of mechanisms modulating the shedding of cfDNA by the tumour may help to decrypt the meaning of cfDNA kinetics in blood or CSF.

Is There a Role for Machine Learning in Liquid Biopsy for Brain Tumors? A Systematic Review

The paucity of studies available in the literature on brain tumors demonstrates that liquid biopsy (LB) is not currently applied for central nervous system (CNS) cancers. The purpose of this systematic review focused on the application of machine learning (ML) to LB for brain tumors to provide practical guidance for neurosurgeons to understand the state-of-the-art practices and open challenges. The herein presented study was conducted in accordance with the PRISMA-P (preferred reporting items for systematic review and meta-analysis protocols) guidelines. An online literature search was launched on PubMed/Medline, Scopus, and Web of Science databases using the following query: "((Liquid biopsy) AND (Glioblastoma OR Brain tumor) AND (Machine learning OR Artificial Intelligence))". The last database search was conducted in April 2023. Upon the full-text review, 14 articles were included in the study. These were then divided into two subgroups: those dealing with applications of machine learning to liquid biopsy in the field of brain tumors, which is the main aim of this review (n = 8); and those dealing with applications of machine learning to liquid biopsy in the diagnosis of other tumors (n = 6). Although studies on the application of ML to LB in the field of brain tumors are still in their infancy, the rapid development of new techniques, as evidenced by the increase in publications on the subject in the past two years, may in the future allow for rapid, accurate, and noninvasive analysis of tumor data. Thus making it possible to identify key features in the LB samples that are associated with the presence of a brain tumor. These features could then be used by doctors for disease monitoring and treatment planning.