The etiopathogenesis of diffuse low-grade gliomas

New insights into glioma frequency maps: From genetic and transcriptomic correlate to survival prediction

Increasing evidence indicates that glioma topographic location is linked to the cellular origin, molecular alterations and genetic profile. This research aims to (a) reveal the underlying mechanisms of tumor location predilection in glioblastoma multiforme (GBM) and lower-grade glioma (LGG) and (b) leverage glioma location features to predict prognosis. MRI images from 396 GBM and 190 LGG (115 astrocytoma and 75 oligodendroglioma) patients were standardized to construct frequency maps and analyzed by voxel-based lesion-symptom mapping. We then investigated the spatial correlation between glioma distribution with gene expression in healthy brains. We also evaluated transcriptomic differences in tumor tissue from predilection and nonpredilection sites. Furthermore, we quantitively characterized tumor anatomical localization and explored whether it was significantly related to overall survival. Finally, we employed a support vector machine to build a survival prediction model for GBM patients. GBMs exhibited a distinct location predilection from LGGs. GBMs were nearer to the subventricular zone and more likely to be localized to regions enriched with synaptic signaling, whereas astrocytoma and oligodendroglioma tended to occur in areas associated with the immune response. Synapse, neurotransmitters and calcium ion channel-related genes were all activated in GBM tissues coming from predilection regions. Furthermore, we characterized tumor location features in terms of a series of tumor-to-predilection distance metrics, which were able to predict GBM 1-year survival status with an accuracy of 0.71. These findings provide new perspectives on our understanding of tumor anatomic localization. The spatial features of glioma are of great value in individual therapy and prognosis prediction.

A Personalized Longitudinal Strategy in Low-Grade Glioma Patients: Predicting Oncological and Neural Interindividual Variability and Its Changes over Years to Think One Step Ahead

Diffuse low-grade glioma (LGG) is a rare cerebral cancer, mostly involving young adults with an active life at diagnosis. If left untreated, LGG widely invades the brain and becomes malignant, generating neurological worsening and ultimately death. Early and repeat treatments for this incurable tumor, including maximal connectome-based surgical resection(s) in awake patients, enable postponement of malignant transformation while preserving quality of life owing to constant neural network reconfiguration. Due to considerable interindividual variability in terms of LGG course and consecutive cerebral reorganization, a multistage longitudinal strategy should be tailored accordingly in each patient. It is crucial to predict how the glioma will progress (changes in growth rate and pattern of migration, genetic mutation, etc.) and how the brain will adapt (changes in patterns of spatiotemporal redistribution, possible functional consequences such as epilepsy or cognitive decline, etc.). The goal is to anticipate therapeutic management, remaining one step ahead in order to select the optimal (re-)treatment(s) (some of them possibly kept in reserve), at the appropriate time(s) in the evolution of this chronic disease, before malignization and clinical worsening. Here, predictive tumoral and non-tumoral factors, and their ever-changing interactions, are reviewed to guide individual decisions in advance based on patient-specific markers, for the treatment of LGG.

Preoperative imaging features: Are they useful tools for predicting IDH1 mutation status in gliomas Grades II–IV?

Background:

It is already known that gliomas biomolecular parameters have a reliable prognostic value. However, an invasive procedure is required to determine them. Our aim was to better understand the clinical characteristics of gliomas Grades II–IV and to assess the usefulness of imaging features in magnetic resonance imaging (MRI) to predict the isocitrate dehydrogenase one (IDH1) mutation.

Methods:

Preoperative MRI characteristics were retrospectively reviewed and molecular diagnosis of gliomas was tested in adult patients between 2014 and 2021 in two institutions. We applied a biological criterion to divide the brain in cerebral compartments.

Results:

A total of 108 patients met the inclusion criteria. Contrast enhancement (CE) in MRI was significantly associated with wild-type IDH1 (IDH1-Wt) (P < 0.00002). Furthermore, the positive predictive value of CE for IDH1-Wt was of 87.1%. On the other hand, the negative predictive value of non-CE for mutated IDH1 (IDH1-Mut) was of 52.6%; 60.2% of gliomas were located in the neocortical and 24.1% in the allocortical/mesocortical telencephalon. Considering gliomas Grades II–III, 66.7% of IDH1-Mut and 28.6% of IDH1-Wt gliomas were located in the neocortex, without statistical significance.

Conclusion:

Our research revealed that CE is useful for predicting IDH1-Wt in gliomas. On the contrary, nonCE is not useful for predicting IDH1-Mut gliomas. Thus, the traditional concept of associating non-CE MRI with a low-grade glioma should be reviewed, as it can lead to an underestimation of the potential aggressiveness of the tumor. If this association was validated with the future prospective studies, a noninvasive tool would be available for predicting gliomas IDH1 mutation status.

Prognostic Model and Nomogram Construction and Validation With an Autophagy-Related Gene Signature in Low-Grade Gliomas

Background: Autophagy plays a vital role in cancer development. However, the prognostic value of autophagy-related genes (ARGs) in low-grade gliomas (LGG) is unclear. This research aimed to investigate whether ARGs correlated with overall survival (OS) in LGG patients.

Methods: RNA-sequencing data were obtained from The Cancer Genome Atlas (TCGA) TARGET GTEx database. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis of ARGs were performed by the “clusterprofile” R package. Cox regression with the wald χ² test was employed to identify prognostic significant ARGs. Next, the receiver operator characteristic curves were established to evaluate the feasibility of risk score (riskscore=h0(t)exp(∑j=1nCoefj×Xj)) and other clinical risk factors to predict prognosis. A nomogram was constructed. Correlations between clinical features and ARGs were further verified by a t-test or Kruskal–Wallis test. In addition, the correlations between autophagy and immune cells were assessed through the single-sample gene set enrichment analysis (ssGSEA) and tumor immune estimation resource database. Last, the prediction model was verified by LGG data downloaded from the Chinese Glioma Genome Atlas (CGGA) database.

Results: Overall, 35 DE-ARGs were identified. Functional enrichment analysis showed that these genes were mainly related to oxidative stress and regulation of autophagy. Nine ARGs (BAX, BIRC5, CFLAR, DIRAS3, GRID2, MAPK9, MYC, PTK6, and TP53) were significantly associated with OS. Age (Hazard ratio (HR) = 1.063, 95% CI: 1.046–1.080), grade (HR = 3.412, 95% CI: 2.164–5.379), histological type (HR = 0.556, 95% CI: 0.346–0.893), and risk score (HR = 1.135, 95% CI: 1.104–1.167) were independent prognostic risk factors (all p < 0.05). In addition, BIRC5, CFLAR, DIRAS3, TP53, and risk scores were found to correlate significantly with age and tumor grade (all p < 0.05). Immune cell enrichment analysis demonstrated that the types of immune cells and their expression levels in the high-risk group were significantly different from those in the low-risk group (all p < 0.05). A prognostic nomogram was constructed to predict 1-, 3-, and 5-year survival, and the prognostic value of sorted ARGs were verified in the CGGA database and clinical samples.

Conclusion: Our findings suggest that the 9 DE-ARGs’ risk score model could serve as diagnostic and prognostic biomarkers. The prognostic nomograms could be useful for individualized survival prediction and improved treatment strategies.

White Matter Tracts and Diffuse Lower-Grade Gliomas: The Pivotal Role of Myelin Plasticity in the Tumor Pathogenesis, Infiltration Patterns, Functional Consequences and Therapeutic Management

For many decades, interactions between diffuse lower-grade glioma (LGG) and brain connectome were neglected. However, the neoplasm progression is intimately linked to its environment, especially the white matter (WM) tracts and their myelin status. First, while the etiopathogenesis of LGG is unclear, this tumor seems to appear during the adolescence, and it is mostly located within anterior and associative cerebral areas. Because these structures correspond to those which were myelinated later in the brain maturation process, WM myelination could play a role in the development of LGG. Second, WM fibers and the myelin characteristics also participate in LGG diffusion, since glioma cells migrate along the subcortical pathways, especially when exhibiting a demyelinated phenotype, which may result in a large invasion of the parenchyma. Third, such a migratory pattern can induce functional (neurological, cognitive and behavioral) disturbances, because myelinated WM tracts represent the main limitation of neuroplastic potential. These parameters are critical for tailoring an individualized therapeutic strategy, both (i) regarding the timing of active treatment(s) which must be proposed earlier, before a too wide glioma infiltration along the WM bundles, (ii) and regarding the anatomic extent of surgical resection and irradiation, which should take account of the subcortical connectivity. Therefore, the new science of connectomics must be integrated in LGG management, based upon an improved understanding of the interplay across glioma dissemination within WM and reactional neural networks reconfiguration, in order to optimize long-term oncological and functional outcomes. To this end, mechanisms of activity-dependent myelin plasticity should be better investigated.

Development and validation of an MRI-based nomogram for the preoperative prediction of tumor mutational burden in lower-grade gliomas

BACKGROUND

High tumor mutational burden (TMB) is an emerging biomarker of sensitivity to immune checkpoint inhibitors. In this study, we aimed to determine the value of magnetic resonance (MR)-based preoperative nomogram in predicting TMB status in lower-grade glioma (LGG) patients.

METHODS

Overall survival (OS) data were derived from The Cancer Genome Atlas (TCGA) and then analyzed by using the Kaplan-Meier method and time-dependent receiver operating characteristic (tdROC) analysis. The magnetic resonance imaging (MRI) data of 168 subjects obtained from The Cancer Imaging Archive (TCIA) were retrospectively analyzed. The correlation was explored by univariate and multivariate regression analyses. Finally, we performed tenfold cross validation. TMB values were retrieved from the supplementary information of a previously published article.

RESULTS

The high TMB subtype was associated with the shortest median OS (high vs. low: 50.9 vs. 95.6 months, P<0.05). The tdROC for the high-TMB tumors was 74% (95% CI: 61-86%) for survival at 12 months, and 71% (95% CI: 60-82%) for survival at 24 months. Multivariate logistic regression analysis confirmed that three risk factors [extranodular growth: odds ratio (OR): 8.367, 95% CI: 3.153-22.199, P<0.01; length-width ratio ≥ median: OR: 1.947, 95% CI: 1.025-3.697, P<0.05; frontal lobe: OR: 0.455, 95% CI: 0.229-0.903, P<0.05] were significant independent predictors of high-TMB tumors. The nomogram showed good calibration and discrimination. This model had an area under the curve (AUC) of 0.736 (95% CI: 0.655-0.817). Decision curve analysis (DCA) demonstrated that the nomogram was clinically useful. The average accuracy of the tenfold cross validation was 71.6% for high-TMB tumors.

CONCLUSIONS

Our results indicated that a distinct OS disadvantage was associated with the high TMB group. In addition, extranodular growth, nonfrontal lobe tumors and length-width ratio ≥ median can be conveniently used to facilitate the prediction of high-TMB tumors.

METTL21B is a prognostic biomarker and potential therapeutic target in low-grade gliomas

A considerable amount of literature has demonstrated that eukaryotic translation elongation factor 1A (eEF1A) is closely related to tumors. As a newly identified lysine specific methyltransferase targeting eEF1A at Lys-165, too little attention has been paid to the function of METTL21B. To determine the potential significance and prognostic value of METTL21B in low grade glioma (LGG), we analyzed the expression, methylation level and copy number variations (CNV) of METTL21B and its effect on prognosis in patients with LGG by 4 public databases in conjunction with experimental examination of LGG patient samples. As a result, we found that high expression, hypomethylation and gain/amplification of CNV of METTL21B were associated with poor prognosis in LGG. The potential functions of METTL21B in LGG may be involved in cell adhesion, angiogenesis and cell proliferation of tumor by enrichment analysis. In addition, METTL21B may facilitate immune evasion of tumor and affect prognosis by mediating macrophage polarization from M1 to M2 and regulating expression of immune checkpoints. Nevertheless, patients with high METTL21B level are likely to have better response to immune checkpoints blockage therapy. Because of its substrate specificity, METTL21B is expected to be a promising target for the treatment of glioma.

An autophagic gene-based signature to predict the survival of patients with low-grade gliomas

Background

Since autophagy remains an important topic of investigation, the RNA‐sequence profiles of autophagy‐related genes (ARGs) can provide insights into predicting low‐grade gliomas (LGG) prognosis.

Methods

The RNA‐seq profiles of autophagic genes and prognosis data of LGG were integrated from the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA). Univariate Cox analysis and the least absolute shrinkage and selection operator (LASSO) regression model were carried out to identify the differentially expressed prognostic autophagy‐related genes. Then, the autophagic‐gene signature was formed and verified in TCGA test set and external CGGA cohorts. Time‐dependent receiver operating characteristic (ROC) was examined to test the accuracy of this signature feature. A nomogram was conducted to meet the needs of clinicians. Sankey diagrams were performed to visualize the relationship between the multigene signatures and clinic‐pathological features.

Results

Twenty‐four ARGs were finally identified most relevant to LGG prognosis. According to the specific prediction index formula, the patients were classified into low‐risk or high‐risk groups. Prognostic accuracy was proved by time‐dependent ROC analysis, with AUC 0.9, 0.93, and 0.876 at the survival time of 2‐, 3‐, and 5‐year, respectively, which was superior to the AUC of the isocitrate dehydrogenase (IDH) mutation. The result was confirmed while validated in the TCGA test set and external validation CGGA cohort. A nomogram was constructed to meet individual needs. With a visualization approach, Sankey diagrams show the relationship of the histological type, IDH status, and predict index. In TCGA and CGGA cohorts, both low‐risk groups displayed better survival rate in LGG while histological type and IDH status did not show consistency results.

Conclusions

24‐ARGs may play crucial roles in the progression of LGG, and LGG patients were effectively divided into low‐risk and high‐risk groups according to prognostic prediction. Overall, our study will provide novel strategies for clinical applications.

Association between health insurance status and malignant glioma

Background

Prior studies have suggested an association between patient socioeconomic status and brain tumors. In the present study we attempt to indirectly validate the findings, using health insurance status as a proxy for socioeconomic status.

Methods

There are 2 types of health insurance in Germany: statutory and private. Owing to regulations, low- and middle-income residents are typically statutory insured, whereas high-income residents have the option of choosing a private insurance. We compared the frequencies of privately insured patients suffering from malignant neoplasms of the brain with the corresponding frequencies among other neurosurgical patients at our hospital and among the German population. To correct for age, sex, and distance from the hospital, we included these variables as predictors in logistic and binomial regression.

Results

A significant association (odds ratio [OR] = 1.59, CI = 1.45-1.74, P < .001) between health insurance status and brain tumors was found. The association is independent of patients' sex or age. Whereas privately insured patients generally tend to come from farther away, such a relationship was not observed for patients suffering from brain tumors. Comparing the out of house and in-house brain tumor patients showed no selection bias on our side.

Conclusion

Previous studies have found that people with a higher income, level of education, or socioeconomic status are more likely to suffer from malignant brain tumors. Our findings are in line with these studies. Although the reason behind the association remains unclear, the probability that our results are due to some random effect in the data is extremely low.

Angiotensin-converting enzyme insertion/deletion gene polymorphisms and the risk of glioma in an Algerian population

Introduction

Just recently, it has been established that the angiotensin-converting enzyme (ACE) insertion/deletion (I/D) polymorphism is linked to the pathogenesis and to the evolution of human cancers. Therefore, the present study was concerned with the investigation of an eventual association between glioma and I/D polymorphism of the ACE gene.

Methods

The expression of ACE gene was detected by polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP) analysis in 36 Algerian patients with glioma and 195 healthy controls.

Results

In glioma cases, allelic frequencies and genotypes distribution of the ACE I/D polymorphism were different from controls cases. ACE DD genotype were highly presented in glioma cases (63.9%) than controls (33.8%) and conferred 3.64-fold risk for predisposition in glioma cases (vs ID genotype, p<0.001). Recessive model (ACE II + ID genotypes vs DD) was associated with a 72% reduced risk of glioma (OR = 0.28, 95% CI: 0.13-0.60, p <0.001). Per copy D allele frequency was found higher in glioma cases (79.2%) than in controls (63.3 %), OR = 2.20, 95% CI: 1.20 - 4.03, p = 0.009.

Conclusion

The obtained data showed that the presence of the D allele might be a risk factor for the development of glioma. Further studies considering different ethnic groups with large samples are required to confirm this finding.

Epidemiology and Molecular Epidemiology

Incidence, prevalence, and survival for diffuse low-grade gliomas and diffuse anaplastic gliomas (including grade II and grade III astrocytomas and oligodendrogliomas) varies by histologic type, age at diagnosis, sex, and race/ethnicity. Significant progress has been made in identifying potential risk factors for glioma, although more research is warranted. The strongest risk factors that have been identified thus far include allergies/atopic disease, ionizing radiation, and heritable genetic factors. Further analysis of large, multicenter epidemiologic studies, and well-annotated "omic" datasets, can potentially lead to further understanding of the relationship between gene and environment in the process of brain tumor development.

Brain Mapping as Helpful Tool in Brain Glioma Surgical Treatment-Toward the "Perfect Surgery"?

Gliomas are the most common primary malignant brain tumours in adults, representing nearly 80%, with poor prognosis in their high-grade forms. Several variables positively affect the prognosis of patients with high-grade glioma: young age, tumour location, radiological features, recurrence, and the opportunity to perform post-operative adjuvant therapy. Low-grade gliomas are slow-growing brain neoplasms of adolescence and young-adulthood, preferentially involving functional areas, particularly the eloquent ones. It has been demonstrated that early surgery and higher extent rate ensure overall longer survival time regardless of tumour grading, but nowadays, functional preservation that is as complete as possible is imperative. To achieve the best surgical results, along with the best functional results, intraoperative mapping and monitoring of brain functions, as well as different anaesthesiology protocols for awake surgery are nowadays being widely adopted. We report on our experience at our institution with 28 patients affected by malignant brain tumours who underwent brain mapping-aided surgical resection of neoplasm: 20 patients underwent awake surgical resection and 8 patients underwent asleep surgical resection. An analysis of the results and a review of the literature has been performed.

An attempt to conceptualize the individual onco-functional balance: Why a standardized treatment is an illusion for diffuse low-grade glioma patients

In the era of evidence-based medicine, clinicians aim to establish standards of care from randomized studies. Following, personalized medicine has emerged, as new individualized biomarkers could help to predict sensitivity to specific treatment. In this paper, we show that, for diffuse low-grade glioma, some specificities - dual goal of both survival and functional gain, long duration of the disease with multistep treatments, multiparametric evaluation of the onco-functional balance of each treatment modality - call for a change of paradigm. After summarizing how to weight the benefits and risks of surgery, chemotherapy and radiotherapy, we show that the overall efficacy of a treatment modality cannot be assessed per se, as it depends on its integration in the whole sequence. Then, we revisit the notion of personalized medicine: instead of decision-making based solely on molecular profile, we plead for a recursive algorithm, allowing a dynamic evaluation of the onco-functional balance, integrating many individual characteristics of the patient's tumor and brain function.

Network Plasticity and Intraoperative Mapping for Personalized Multimodal Management of Diffuse Low-Grade Gliomas

Gliomas are the most frequent primary brain tumors and include a variety of different histological tumor types and malignancy grades. Recent achievements in terms of molecular and imaging fields have created an unprecedented opportunity to perform a comprehensive interdisciplinary assessment of the glioma pathophysiology, with direct implications in terms of the medical and surgical treatment strategies available for patients. The current paradigm shift considers glioma management in a comprehensive perspective that takes into account the intricate connectivity of the cerebral networks. This allowed significant improvement in the outcome of patients with lesions previously considered inoperable. The current review summarizes the current theoretical framework integrating the adult human brain plasticity and functional reorganization within a dynamic individualized treatment strategy for patients affected by diffuse low-grade gliomas. The concept of neuro-oncology as a brain network surgery has major implications in terms of the clinical management and ensuing outcomes, as indexed by the increased survival and quality of life of patients managed using such an approach.