miRNAs and related genetic biomarkers according to the WHO glioma classification: From diagnosis to future therapeutic targets

CNN-TumorNet: leveraging explainability in deep learning for precise brain tumor diagnosis on MRI images

Introduction

The early identification of brain tumors is essential for optimal treatment and patient prognosis. Advancements in MRI technology have markedly enhanced tumor detection yet necessitate accurate classification for appropriate therapeutic approaches. This underscores the necessity for sophisticated diagnostic instruments that are precise and comprehensible to healthcare practitioners.

Methods

Our research presents CNN-TumorNet, a convolutional neural network for categorizing MRI images into tumor and non-tumor categories. Although deep learning models exhibit great accuracy, their complexity frequently restricts clinical application due to inadequate interpretability. To address this, we employed the LIME technique, augmenting model transparency and offering explicit insights into its decision-making process.

Results

CNN-TumorNet attained a 99% accuracy rate in differentiating tumors from non-tumor MRI scans, underscoring its reliability and efficacy as a diagnostic instrument. Incorporating LIME guarantees that the model's judgments are comprehensible, enhancing its clinical adoption.

Discussion

Despite the efficacy of CNN-TumorNet, the overarching challenge of deep learning interpretability persists. These models may function as "black boxes," complicating doctors' ability to trust and accept them without comprehending their rationale. By integrating LIME, CNN-TumorNet achieves elevated accuracy alongside enhanced transparency, facilitating its application in clinical environments and improving patient care in neuro-oncology.

Comprehensive evaluation of EGFR and AKT targeting efficacy of resveratrol loaded PEGylated liposomes for the glioblastoma management: In silico, in vitro BBB permeation studies

Red grapes contain resveratrol (Resv), a polyphenol with anti-inflammatory, anti-diabetic, and anticancer properties. In this study, in silico molecular docking was used to assess the binding affinity of Resv to target proteins. Resv was encapsulated in PEGylated liposomes (LNPs) using Phospholipon 90G, cholesterol, and DSPE-mPEG2000. The particle size, surface charge, and structural details of the Res-LNPs and the Blank LNPs were determined. The effects of Res-LNPs and pure Resv were examined in vitro in C6 (rat glioma) and U87 MG (human glioblastoma) cell lines to evaluate cell survival, uptake, wound healing, and apoptosis. BBB permeability of the Res-LNPs was assessed using an in vitro BBB model with hCMEC/D3 cells. EGFR and AKT 1 and 2 expression levels in Resv-treated U87 MG cells were analyzed by RT-qPCR. Res-LNPs had a particle size of 155.0 ± 1.62 nm and an encapsulation efficiency (% EE) of 76.62 ± 3.43. FTIR, DSC, and XRD analyses confirmed the complete entrapment of Resv within the LNPs, displaying a unilamellar spherical morphology, as verified by SEM and TEM. In vitro studies on C6 and U87 MG cell lines showed that Res-LNPs significantly improved cell viability, uptake, migration, and apoptosis compared with Resv. An in vitro BBB model demonstrated that Res-LNPs efficiently crossed the BBB and accumulated in brain cancer cells. RT-qPCR results indicated that Resv treatment reduced EGFR and AKT 1 and 2 gene expression in U87 MG cells. These results suggest that Res-LNPs effectively crossed BBB and inhibited EGFR and its downstream pathways in glioma cell lines.

Exploring Extracellular Vesicle Surface Protein Markers Produced by Glioblastoma Tumors: A Characterization Study Using In Vitro 3D Patient-Derived Cultures

BACKGROUND/OBJECTIVES

Glioblastoma (GBM) is an aggressive brain cancer with limited treatment options. Extracellular vesicles (EVs) derived from GBM cells contain important biomarkers, such as microRNAs, proteins, and DNA mutations, which are involved in tumor progression, invasion, and resistance to treatment. Identifying surface markers on these EVs is crucial for their isolation and potential use in noninvasive diagnosis. This study aimed to use tumor-derived explants to investigate the surface markers of EVs and explore their role as diagnostic biomarkers for GBM.

METHODS

Tumor explants from nine GBM patients without IDH1/IDH2 mutations or 1p-19q co-deletion were cultured to preserve both tumor viability and cytoarchitecture. EVs were collected from the tumor microenvironment using differential centrifugation, filtration, and membrane affinity binding. Their surface protein composition was analyzed through multiplex protein assays. RNA-Seq data from TCGA and GTEx datasets, along with in silico single-cell RNA-seq data, were used to assess EV surface biomarker expression across large GBM patient cohorts.

RESULTS

The in vitro model successfully replicated the tumor microenvironment and produced EVs with distinct surface markers. Biomarker analysis in large datasets revealed specific expression patterns unique to GBM patients compared with healthy controls. These markers demonstrated potential as a GBM-specific signature and were correlated with clinical data. Furthermore, in silico single-cell RNA-seq provided detailed insights into biomarker distribution across different cell types within the tumor.

CONCLUSIONS

This study underscores the efficacy of the tumor-derived explant model and its potential to advance the understanding of GBM biology and EV production. A key innovation is the isolation of EVs from a model that faithfully mimics the tumor's original cytoarchitecture, offering a deeper understanding of the cells involved in EV release. The identified EV surface markers represent promising targets for enhancing EV isolation and optimizing their use as diagnostic tools. Moreover, further investigation into their molecular cargo may provide crucial insights into tumor characteristics and evolution.

Exploring hypoxia-induced ncRNAs as biomarkers and therapeutic targets in lung cancer

Lung cancer is a deadly disease, causing nearly 20 % of all cancer deaths globally. A key factor in lung cancer's development and resistance to treatment is hypoxia, a condition where tumor cells experience low oxygen levels. In this low-oxygen environment, special molecules called non-coding RNAs (ncRNAs) become critical players. NcRNAs, including lncRNAs, miRNAs, circRNAs, and siRNAs, control how genes function and how cells behave. Some ncRNAs, like HIF1A-AS2 and HOTAIR, are linked to the aggressive spread of lung cancer, making them potential targets for therapy. Others, like certain miRNAs, show promise as early detection tools due to their influence on tumor blood vessel formation and metabolism. This complex interplay between hypoxia and ncRNAs is crucial for understanding lung cancer. For example, circRNAs can control the activity of miRNAs, impacting how tumors respond to low oxygen. Additionally, siRNAs offer a potential strategy to overcome treatment resistance caused by hypoxia. By studying the intricate relationship between hypoxia and ncRNAs, scientists hope to uncover new biomarkers for lung cancer. This knowledge will pave the way for developing more effective and targeted treatments for this devastating disease.

The molecular conversations of sarcomas: exosomal non-coding RNAs in tumor's biology and their translational prospects

Exosomes mediate cell-to-cell crosstalk involving a variety of biomolecules through an intricate signaling network. In recent years, the pivotal role of exosomes and their non-coding RNAs cargo in the development and progression of several cancer types clearly emerged. In particular, tumor bulk and its microenvironment co-evolve through cellular communications where these nanosized extracellular vesicles are among the most relevant actors. Knowledge about the cellular, and molecular mechanisms involved in these communications will pave the way for novel exosome-based delivery of therapeutic RNAs as well as innovative prognostic/diagnostic tools. Despite the valuable therapeutic potential and clinical relevance of exosomes, their role on sarcoma has been vaguely reported because the rarity and high heterogeneity of this type of cancer. Here, we dissected the scientific literature to unravel the multifaceted role of exosomal non-coding RNAs as mediator of cell-to-cell communications in the sarcoma subtypes.

Circulating Liquid Biopsy Biomarkers in Glioblastoma: Advances and Challenges

Gliomas, particularly glioblastoma (GBM), represent the most prevalent and aggressive tumors of the central nervous system (CNS). Despite recent treatment advancements, patient survival rates remain low. The diagnosis of GBM traditionally relies on neuroimaging methods such as magnetic resonance imaging (MRI) or computed tomography (CT) scans and postoperative confirmation via histopathological and molecular analysis. Imaging techniques struggle to differentiate between tumor progression and treatment-related changes, leading to potential misinterpretation and treatment delays. Similarly, tissue biopsies, while informative, are invasive and not suitable for monitoring ongoing treatments. These challenges have led to the emergence of liquid biopsy, particularly through blood samples, as a promising alternative for GBM diagnosis and monitoring. Presently, blood and cerebrospinal fluid (CSF) sampling offers a minimally invasive means of obtaining tumor-related information to guide therapy. The idea that blood or any biofluid tests can be used to screen many cancer types has huge potential. Tumors release various components into the bloodstream or other biofluids, including cell-free nucleic acids such as microRNAs (miRNAs), circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), proteins, extracellular vesicles (EVs) or exosomes, metabolites, and other factors. These factors have been shown to cross the blood-brain barrier (BBB), presenting an opportunity for the minimally invasive monitoring of GBM as well as for the real-time assessment of distinct genetic, epigenetic, transcriptomic, proteomic, and metabolomic changes associated with brain tumors. Despite their potential, the clinical utility of liquid biopsy-based circulating biomarkers is somewhat constrained by limitations such as the absence of standardized methodologies for blood or CSF collection, analyte extraction, analysis methods, and small cohort sizes. Additionally, tissue biopsies offer more precise insights into tumor morphology and the microenvironment. Therefore, the objective of a liquid biopsy should be to complement and enhance the diagnostic accuracy and monitoring of GBM patients by providing additional information alongside traditional tissue biopsies. Moreover, utilizing a combination of diverse biomarker types may enhance clinical effectiveness compared to solely relying on one biomarker category, potentially improving diagnostic sensitivity and specificity and addressing some of the existing limitations associated with liquid biomarkers for GBM. This review presents an overview of the latest research on circulating biomarkers found in GBM blood or CSF samples, discusses their potential as diagnostic, predictive, and prognostic indicators, and discusses associated challenges and future perspectives.

Insights into brain tumor diagnosis: exploring in situ hybridization techniques

Objectives

Diagnosing brain tumors is critical due to their complex nature. This review explores the potential of in situ hybridization for diagnosing brain neoplasms, examining their attributes and applications in neurology and oncology.

Methods

The review surveys literature and cross-references findings with the OMIM database, examining 513 records. It pinpoints mutations suitable for in situ hybridization and identifies common chromosomal and gene anomalies in brain tumors. Emphasis is placed on mutations' clinical implications, including prognosis and drug sensitivity.

Results

Amplifications in EGFR, MDM2, and MDM4, along with Y chromosome loss, chromosome 7 polysomy, and deletions of PTEN, CDKN2/p16, TP53, and DMBT1, correlate with poor prognosis in glioma patients. Protective genetic changes in glioma include increased expression of ADGRB3/1, IL12B, DYRKA1, VEGFC, LRRC4, and BMP4. Elevated MMP24 expression worsens prognosis in glioma, oligodendroglioma, and meningioma patients. Meningioma exhibits common chromosomal anomalies like loss of chromosomes 1, 9, 17, and 22, with specific genes implicated in their development. Main occurrences in medulloblastoma include the formation of isochromosome 17q and SHH signaling pathway disruption. Increased expression of BARHL1 is associated with prolonged survival. Adenomas mutations were reviewed with a focus on adenoma-carcinoma transition and different subtypes, with MMP9 identified as the main metalloprotease implicated in tumor progression.

Discussion

Molecular-genetic diagnostics for common brain tumors involve diverse genetic anomalies. In situ hybridization shows promise for diagnosing and prognosticating tumors. Detecting tumor-specific alterations is vital for prognosis and treatment. However, many mutations require other methods, hindering in situ hybridization from becoming the primary diagnostic method.

Expression of overall survival-EMT-immune cell infiltration genes predict the prognosis of glioma

This study investigates the crucial role of immune- and epithelial-mesenchymal transition (EMT)-associated genes and non-coding RNAs in glioma development and diagnosis, given the challenging 5-year survival rates associated with this prevalent CNS malignant tumor. Clinical and RNA data from glioma patients were meticulously gathered from CGGA databases, and EMT-related genes were sourced from dbEMT2.0, while immune-related genes were obtained from MSigDB. Employing consensus clustering, novel molecular subgroups were identified. Subsequent analyses, including ESTIMATE, TIMER, and MCP counter, provided insights into the tumor microenvironment (TIME) and immune status. Functional studies, embracing GO, KEGG, GSVA, and GSEA analyses, unraveled the underlying mechanisms governing these molecular subgroups. Utilizing the LASSO algorithm and multivariate Cox regression, a prognostic risk model was crafted. The study unveiled two distinct molecular subgroups with significantly disparate survival outcomes. A more favorable prognosis was linked to low immune scores, high tumor purity, and an abundance of immune infiltrating cells with differential expression of non-coding RNAs, including miRNAs. Functional analyses illuminated enrichment of immune- and EMT-associated pathways in differentially expressed genes and non-coding RNAs between these subgroups. GSVA and GSEA analyses hinted at abnormal EMT status potentially contributing to glioma-associated immune disorders. The risk model, centered on OS-EMT-ICI genes, exhibited promise in accurately predicting survival in glioma. Additionally, a nomogram integrating the risk model with clinical characteristics demonstrated notable accuracy in prognostic predictions for glioma patients. In conclusion, OS-EMT-ICI gene and non-coding RNA expression emerges as a valuable indicator intricately linked to immune microenvironment dysregulation, offering a robust tool for precise prognosis prediction in glioma patients within the OBMRC framework.

The Role and Mechanism of the Histone Methyltransferase G9a in Tumors: Update

Methylation-mediated gene silencing is closely related to the occurrence and development of human tumors. The euchromatic histone lysine methyltransferase 2 (EHMT2, also known as G9a) is highly expressed in many tumors and is generally considered to be an oncogene, which is associated with the poor outcome of many tumors. Combined immunotherapy and immune checkpoint blockade therapy also have good efficacy and certain safety. However, there are still many difficulties in the drugs targeting G9a, and the combined effect and safety of G9a with many drugs is still under study. This article aims to summarize the role and mechanism of G9a and its inhibitors in tumors in the past two years, and to understand the application prospect of G9a from the perspective of diagnosis and treatment.

Mesenchymal-Stem-Cell-Based Therapy against Gliomas

Glioblastoma is the most aggressive, malignant, and lethal brain tumor of the central nervous system. Its poor prognosis lies in its inefficient response to currently available treatments that consist of surgical resection, radiotherapy, and chemotherapy. Recently, the use of mesenchymal stem cells (MSCs) as a possible kind of cell therapy against glioblastoma is gaining great interest due to their immunomodulatory properties, tumor tropism, and differentiation into other cell types. However, MSCs seem to present both antitumor and pro-tumor properties depending on the tissue from which they come. In this work, the possibility of using MSCs to deliver therapeutic genes, oncolytic viruses, and miRNA is presented, as well as strategies that can improve their therapeutic efficacy against glioblastoma, such as CAR-T cells, nanoparticles, and exosomes.

Circulating serum miR-362-3p and miR-6721-5p as potential biomarkers for classification patients with adult-type diffuse glioma

According to the fifth edition of the WHO Classification of Tumours of the Central Nervous System (CNS) published in 2021, grade 4 gliomas classification includes IDH-mutant astrocytomas and wild-type IDH glioblastomas. Unfortunately, despite precision oncology development, the prognosis for patients with grade 4 glioma remains poor, indicating an urgent need for better diagnostic and therapeutic strategies. Circulating miRNAs besides being important regulators of cancer development could serve as promising diagnostic biomarkers for patients with grade 4 glioma. Here, we propose a two-miRNA miR-362-3p and miR-6721-5p screening signature for serum for non-invasive classification of identified glioma cases into the highest-grade 4 and lower-grade gliomas. A total of 102 samples were included in this study, comprising 78 grade 4 glioma cases and 24 grade 2-3 glioma subjects. Using the NanoString platform, seven miRNAs were identified as differentially expressed (DE), which was subsequently confirmed via RT-qPCR analysis. Next, numerous combinations of DE miRNAs were employed to develop classification models. The dual panel of miR-362-3p and miR-6721-5p displayed the highest diagnostic value to differentiate grade 4 patients and lower grade cases with an AUC of 0.867. Additionally, this signature also had a high AUC = 0.854 in the verification cohorts by RT-qPCR and an AUC = 0.842 using external data from the GEO public database. The functional annotation analyses of predicted DE miRNA target genes showed their primary involvement in the STAT3 and HIF-1 signalling pathways and the signalling pathway of pluripotency of stem cells and glioblastoma-related pathways. For additional exploration of miRNA expression patterns correlated with glioma, we performed the Weighted Gene-Co Expression Network Analysis (WGCNA). We showed that the modules most associated with glioma grade contained as many as six DE miRNAs. In conclusion, this study presents the first evidence of serum miRNA expression profiling in adult-type diffuse glioma using a classification based on the WHO 2021 guidelines. We expect that the discovered dual miR-362-3p and miR-6721-5p signatures have the potential to be utilised for grading gliomas in clinical applications.