Molecular biomarkers and integrated pathological diagnosis in the reclassification of gliomas

The involvement of circRNAs in molecular processes and their potential use in therapy and diagnostics for glioblastoma

Glioblastoma, a type of brain tumor, is well-known for its aggressive nature and can affect individuals of all ages. Glioblastoma continues to be a difficult cancer to manage because of various resistance mechanisms. The blood-brain barrier restricts the delivery of drugs, and the heterogeneity of tumors, along with overlapping signaling pathways, complicates its effective treatment. Patients diagnosed with glioblastoma typically survive for no more than 2 years. Innovative therapies and early diagnostic tools for glioblastoma are essential. Circular RNAs have emerged as significant contributors to glioblastoma, and influence cancer mechanisms such as cell growth, death, invasion, and resistance to treatment. The circRNAs presence makes them essential candidates for treatment and practical diagnostic tools for glioblastoma. This review highlights the therapeutic approaches and diagnostic potential of circRNAs and explores their role in the molecular mechanisms underlying glioblastoma.

Clinical characteristics, molecular reclassification trajectories and DNA methylation patterns of long- and short-term survivors of WHO grade II and III glioma

PURPOSE

The prognosis of diffuse gliomas previously classified as "lower-grade" is heterogeneous and complicates clinical decisions. We aimed to investigate the molecular profile of clinical outliers to gain insight into biological drivers of long and short-term survivors.

METHODS

Here, patients aged ≥ 18 years and diagnosed with diffuse glioma, WHO grade II/2 or III/3 were included. Short-term survivors (STS) were defined as overall survival (OS) < 1 years, and long-term survivors (LTS) as OS > 10 years. DNA methylation profiling was performed using the Illumina EPIC 850k platform.

RESULTS

In total, 385 patients (294 LTS, 91 STS) were included. Median overall survival was 234 months (95%CI: 207-248) in LTS and 7.3 months (95%CI: 6.4-8.1) in STS. Compared to STS, LTS were younger, had higher Karnofsky Performance Status, more extensive resections, and lower symptomatic burden (p < 0.001, respectively). Molecular reclassification showed IDH-mutant gliomas in 240/246 (95.5%) LTS and 10/79 (12.7%) STS. Initial diagnosis (tumor type and/or grading) changed in 69/325 (21.2%) patients based on reclassification according to WHO 2016 and in 45/258 (17.4%) as per WHO 2021. DNA methylation analysis indicated two clusters, one with mainly STS (39/41, 95.1%) and heterogeneous IDH-wildtype tumors (cluster A) and one with mainly LTS (82/106, 77.4%) and IDH-mutant tumors (cluster B). Functional enrichment analysis of rare subtypes indicated altered Hippo/Notch and synaptic/neurotransmitter signaling pathway members.

CONCLUSION

LTS and STS show distinct clinical and molecular features, underscoring the importance of extended molecular workup for diagnosis. Further characterization of rare subtypes is needed to optimize treatment strategies and clinical trial planning.

Engineering dendritic cell biomimetic membrane as a delivery system for tumor targeted therapy

Targeted immunotherapies make substantial strides in clinical cancer care due to their ability to counteract the tumor's capacity to suppress immune responses. Advances in biomimetic technology with minimally immunogenic and highly targeted, are addressing issues of targeted drug delivery and disrupting the tumor's immunosuppressive environment to trigger immune activation. Specifically, the use of dendritic cell (DC) membranes to coat nanoparticles ensures targeted delivery due to DC's unique ability to activate naive T cells, spotlighting their role in immunotherapy aimed at disrupting the tumor microenvironment. The potential of DC's biomimetic membrane to mediate immune activation and target tumors is gaining momentum, enhancing the effectiveness of cancer treatments in conjunction with other immune responses. This review delves into the methodologies behind crafting DC membranes and the fusion of dendritic and tumor cell membranes for encapsulating therapeutic nanoparticles. It explores their applications and recent advancements in combating cancer, offering an all-encompassing perspective on DC biomimetic nanosystems, immunotherapy driven by antigen presentation, and the collaborative efforts of drug delivery in chemotherapy and photodynamic therapies. Current evidence shows promise in augmenting combined therapeutic approaches for cancer treatment and holds translational potential for various cancer treatments in a clinical setting.

Deep Learning Glioma Grading with the Tumor Microenvironment Analysis Protocol for Comprehensive Learning, Discovering, and Quantifying Microenvironmental Features

Gliomas are primary brain tumors that arise from neural stem cells, or glial precursors. Diagnosis of glioma is based on histological evaluation of pathological cell features and molecular markers. Gliomas are infiltrated by myeloid cells that accumulate preferentially in malignant tumors, and their abundance inversely correlates with survival, which is of interest for cancer immunotherapies. To avoid time-consuming and laborious manual examination of images, a deep learning approach for automatic multiclass classification of tumor grades was proposed. As an alternative way of investigating characteristics of brain tumor grades, we implemented a protocol for learning, discovering, and quantifying tumor microenvironment elements on our glioma dataset. Using only single-stained biopsies we derived characteristic differentiating tumor microenvironment phenotypic neighborhoods. The study was complicated by the small size of the available human leukocyte antigen stained on glioma tissue microarray dataset - 206 images of 5 classes - as well as imbalanced data distribution. This challenge was addressed by image augmentation for underrepresented classes. In practice, we considered two scenarios, a whole slide supervised learning classification, and an unsupervised cell-to-cell analysis looking for patterns of the microenvironment. In the supervised learning investigation, we evaluated 6 distinct model architectures. Experiments revealed that a DenseNet121 architecture surpasses the baseline's accuracy by a significant margin of 9% for the test set, achieving a score of 69%, increasing accuracy in discerning challenging WHO grade 2 and 3 cases. All experiments have been carried out in a cross-validation manner. The tumor microenvironment analysis suggested an important role for myeloid cells and their accumulation in the context of characterizing glioma grades. Those promising approaches can be used as an additional diagnostic tool to improve assessment during intraoperative examination or subtyping tissues for treatment selection, potentially easing the workflow of pathologists and oncologists.

Characterizing the Linkage of Systemic Hypoxia and Angiogenesis in High-Grade Glioma to Define the Changes in Tumor Microenvironment for Predicting Prognosis

High-grade gliomas (HGG) comprising WHO grades 3 and 4 have a poor overall survival (OS) that has not improved in the past decade. Herein, markers representing four components of the tumor microenvironment (TME) were identified to define their linked expression in TME and predict the prognosis in HGG, namely, interleukin6 (IL6, inflammation), inducible nitric oxide synthase(iNOS), heat shock protein-70 (HSP70, hypoxia), vascular endothelial growth receptor (VEGF), and endothelin1 (ET1) (angiogenesis) and matrix metalloprotease-14 (MMP14) and intercellular adhesion molecule1 (ICAM1, extracellular matrix). To establish a non-invasive panel of biomarkers for precise prognostication in HGG. Eighty-six therapy-naive HGG patients with 45 controls were analyzed for the defined panel. Systemic expression of extracellular/secretory biomarkers was screened dot-immune assay (DIA), quantified by ELISA, and validated by immunocytochemistry (ICC). Expression of iNOS, HSP70, IL-6, VEGF, ET1, MMP14, and ICAM1 was found to be positively associated with grade. Quantification of circulating levels of the markers by ELISA and ICC presented a similar result. The biomarkers were observed to negatively correlate with OS (p < 0.0001). Cox-regression analysis yielded all biomarkers as good prognostic indicators and independent of confounders. On applying combination statistics, the biomarker panel achieved higher sensitivity than single markers to define survival. The intra-association of all seven biomarkers was significant, hinting of a cross-talk between the TME components and a hypoxia driven systemic inflammation upregulating the expression of other components. This is a first ever experimental study of a marker panel that can distinguish between histopathological grades and also delineate differential survival using liquid biopsy, suggesting that markers of hypoxia can be a cornerstone for personalized therapy. The panel of biomarkers of iNOS, HSP70, IL-6, VEGF, ET1, MMP14, and ICAM1 holds promise for prognostication in HGG.

Preclinical Efficacy and Toxicology Evaluation of RAC1 Inhibitor 1A-116 in Human Glioblastoma Models

Simple Summary

Malignant gliomas are the most common primary central nervous system tumors in adults. Currently, this disease is associated with poor prognosis and is virtually incurable. There is a need to find novel targets and treatments to improve patient survival. This study shows the preclinical evaluation of 1A-116, a Rac1 inhibitor that showed in vitro antitumor activity on glioma cells. We also evaluated 1A-116 in vivo, showing a favorable toxicological profile and antitumor efficacy in an intracranial mouse tumor model. Altogether, our study provides important evidence of 1A-116 as a signal transduction-based precision therapy for glioma and also increases the evidence of Rac1 as a key molecular target in cancer.

Abstract

Malignant gliomas are the most common primary central nervous system tumor in adults. Despite current therapeutics, these tumors are associated with poor prognosis and a median survival of 16 to 19 months. This highlights the need for innovative treatments for this incurable disease. Rac1 has long been associated with tumor progression and plays a key role in glioma’s infiltrative and invasive nature. The aim of this study is to evaluate the 1A-116 molecule, a Rac1 inhibitor, as targeted therapy for this aggressive disease. We found that targeting Rac1 inhibits cell proliferation and cell cycle progression using different in vitro human glioblastoma models. Additionally, we evaluated 1A-116 in vivo, showing a favorable toxicological profile. Using in silico tools, 1A-116 is also predicted to penetrate the blood–brain barrier and present a favorable metabolic fate. In line with these results, 1A-116 i.p daily treatment resulted in a dose-dependent antitumor effect in an orthotopic IDH-wt glioma model. Altogether, our study provides a strong potential for clinical translation of 1A-116 as a signal transduction-based precision therapy for glioma and also increases the evidence of Rac1 as a key molecular target.

An update on the molecular biology of glioblastoma, with clinical implications and progress in its treatment

Glioblastoma multiforme (GBM) is the most aggressive and common malignant primary brain tumor. Patients with GBM often have poor prognoses, with a median survival of ∼15 months. Enhanced understanding of the molecular biology of central nervous system tumors has led to modifications in their classifications, the most recent of which classified these tumors into new categories and made some changes in their nomenclature and grading system. This review aims to give a panoramic view of the last 3 years' findings in glioblastoma characterization, its heterogeneity, and current advances in its treatment. Several molecular parameters have been used to achieve an accurate and personalized characterization of glioblastoma in patients, including epigenetic, genetic, transcriptomic and metabolic features, as well as age- and sex-related patterns and the involvement of several noncoding RNAs in glioblastoma progression. Astrocyte-like neural stem cells and outer radial glial-like cells from the subventricular zone have been proposed as agents involved in GBM of IDH-wildtype origin, but this remains controversial. Glioblastoma metabolism is characterized by upregulation of the PI3K/Akt/mTOR signaling pathway, promotion of the glycolytic flux, maintenance of lipid storage, and other features. This metabolism also contributes to glioblastoma's resistance to conventional therapies. Tumor heterogeneity, a hallmark of GBM, has been shown to affect the genetic expression, modulation of metabolic pathways, and immune system evasion. GBM's aggressive invasion potential is modulated by cell-to-cell crosstalk within the tumor microenvironment and altered expressions of specific genes, such as ANXA2, GBP2, FN1, PHIP, and GLUT3. Nevertheless, the rising number of active clinical trials illustrates the efforts to identify new targets and drugs to treat this malignancy. Immunotherapy is still relevant for research purposes, given the amount of ongoing clinical trials based on this strategy to treat GBM, and neoantigen and nucleic acid-based vaccines are gaining importance due to their antitumoral activity by inducing the immune response. Furthermore, there are clinical trials focused on the PI3K/Akt/mTOR axis, angiogenesis, and tumor heterogeneity for developing molecular-targeted therapies against GBM. Other strategies, such as nanodelivery and computational models, may improve the drug pharmacokinetics and the prognosis of patients with GBM.

Trophinin-associated protein expression correlates with shorter survival of patients with glioma: a study based on multiple data fusion analysis

BACKGROUND

Trophinin-associated protein (TROAP) mediates embryonic transfer, regulates microtubules, and is associated with the biological behavior of various cancers. However, there is limited information on the role of TROAP in glioma.

METHODS AND RESULTS

We obtained clinical information on 1948 patients with glioma from The Cancer Genome Atlas, Gene Expression Omnibus and the Chinese Glioma Genome Atlas. Basal assays were used to measure changes in TROAP expression levels in high-grade glioma cell lines and in normal human astrocytes. Quantitative reverse transcription polymerase chain reaction assays showed that TROAP expression was higher in glioma cell lines than in normal astrocytes. The expression level of TROAP in 749 glioma was significantly higher than that in 228 normal brain tissues using Student's t test. The expression of TROAP has a positive relationship with the clinical characteristics of poor prognosis, such as WHO grade, age and has negatively correlated with the indicators of beneficial prognosis, such as IDH mutation and 1p19q co-deletion. Kaplan-Meier survival curves, single multifactor analysis were used to analyze correlations between TROAP and clinical features and prognosis of gliomas. In addition, TROAP overexpression was an independent risk factor for glioma and was associated with reduced overall survival of patients with glioma particularly in patients with WHO grade III and grade IV glioma. Gene set enrichment analysis showed that homologous recombination, cell cycle, and p53 signaling pathways were enriched in samples overexpressing TROAP.

CONCLUSION

TROAP is a potential risk factor associated with poor prognosis in patients with glioma and may act as a highly specific biomarker, offering the possibility of individualized glioma treatment.