Interactions of Age and Blood Immune Factors and Noninvasive Prediction of Glioma Survival

Structural- and DTI- MRI enable automated prediction of IDH Mutation Status in CNS WHO Grade 2-4 glioma patients: a deep Radiomics Approach

BACKGROUND

The role of isocitrate dehydrogenase (IDH) mutation status for glioma stratification and prognosis is established. While structural magnetic resonance image (MRI) is a promising biomarker, it may not be sufficient for non-invasive characterisation of IDH mutation status. We investigated the diagnostic value of combined diffusion tensor imaging (DTI) and structural MRI enhanced by a deep radiomics approach based on convolutional neural networks (CNNs) and support vector machine (SVM), to determine the IDH mutation status in Central Nervous System World Health Organization (CNS WHO) grade 2-4 gliomas.

METHODS

This retrospective study analyzed the DTI-derived fractional anisotropy (FA) and mean diffusivity (MD) images and structural images including fluid attenuated inversion recovery (FLAIR), non-enhanced T1-, and T2-weighted images of 206 treatment-naïve gliomas, including 146 IDH mutant and 60 IDH-wildtype ones. The lesions were manually segmented by experienced neuroradiologists and the masks were applied to the FA and MD maps. Deep radiomics features were extracted from each subject by applying a pre-trained CNN and statistical description. An SVM classifier was applied to predict IDH status using imaging features in combination with demographic data.

RESULTS

We comparatively assessed the CNN-SVM classifier performance in predicting IDH mutation status using standalone and combined structural and DTI-based imaging features. Combined imaging features surpassed stand-alone modalities for the prediction of IDH mutation status [area under the curve (AUC) = 0.846; sensitivity = 0.925; and specificity = 0.567]. Importantly, optimal model performance was noted following the addition of demographic data (patients' age) to structural and DTI imaging features [area under the curve (AUC) = 0.847; sensitivity = 0.911; and specificity = 0.617].

CONCLUSIONS

Imaging features derived from DTI-based FA and MD maps combined with structural MRI, have superior diagnostic value to that provided by standalone structural or DTI sequences. In combination with demographic information, this CNN-SVM model offers a further enhanced non-invasive prediction of IDH mutation status in gliomas.

Frequencies of 4 tumor-infiltrating lymphocytes potently predict survival in glioblastoma, an immune desert

BACKGROUND

GBM is an aggressive grade 4 primary brain tumor (BT), with a 5%-13% 5-year survival. Most human GBMs manifest as immunologically "cold" tumors or "immune deserts," yet the promoting or suppressive roles of specific lymphocytes within the GBM tumor microenvironment (TME) is of considerable debate.

METHODS

We used meticulous multiparametric flow cytometry (FC) to determine the lymphocytic frequencies in 102 GBMs, lower-grade gliomas, brain metastases, and nontumorous brain specimen. FC-attained frequencies were compared with frequencies estimated by "digital cytometry." The FC-derived data were combined with the patients' demographic, clinical, molecular, histopathological, radiological, and survival data.

RESULTS

Comparison of FC-derived data to CIBERSORT-estimated data revealed the poor capacity of digital cytometry to estimate cell frequencies below 0.2%, the frequency range of most immune cells in BTs. Isocitrate dehydrogenase (IDH) mutation status was found to affect TME composition more than the gliomas' pathological grade. Combining FC and survival data disclosed that unlike other cancer types, the frequency of helper T cells (Th) and cytotoxic T lymphocytes (CTL) correlated negatively with glioma survival. In contrast, the frequencies of γδ-T cells and CD56bright natural killer cells correlated positively with survival. A composite parameter combining the frequencies of these 4 tumoral lymphocytes separated the survival curves of GBM patients with a median difference of 10 months (FC-derived data; P < .0001, discovery cohort), or 4.1 months (CIBERSORT-estimated data; P = .01, validation cohort).

CONCLUSIONS

The frequencies of 4 TME lymphocytes strongly correlate with the survival of patients with GBM, a tumor considered an immune desert.

TMED2 promotes glioma tumorigenesis by being involved in EGFR recycling transport

Aberrant epidermal growth factor receptor (EGFR) signaling is the core signaling commonly activated in glioma. The transmembrane emp24 protein transport domain protein 2 (TMED2) interacts with cargo proteins involved in protein sorting and transport between endoplasmic reticulum (ER) and Golgi apparatus. In this study, we found the correlation between TMED2 with glioma progression and EGFR signaling through database analysis. Moreover, we demonstrated that TMED2 is essential for glioma cell proliferation, migration, and invasion at the cellular levels, as well as tumor formation in mouse models, underscoring its significance in the pathobiology of gliomas. Mechanistically, TMED2 was found to enhance EGFR-AKT signaling by facilitating EGFR recycling, thereby providing the initial evidence of TMED2's involvement in the membrane protein recycling process. In summary, our findings shed light on the roles and underlying mechanisms of TMED2 in the regulation of glioma tumorigenesis and EGFR signaling, suggesting that targeting TMED2 could emerge as a promising therapeutic strategy for gliomas and other tumors associated with aberrant EGFR signaling.

Oligodendroglioma patient survival is associated with circulating B-cells and age

Background

Variations in survival among patients with oligodendroglioma are unexplained by known prognostic factors. To assess the impact of peripheral immune profiles on prognosis, we applied immunomethylomics analyses-DNA methylation of archived whole blood samples, to characterize immune cells.

Methods

We compared the proportions of immune cells from patients with oligodendroglioma to other glioma subtypes and controls. We used recursive partitioning analysis (RPA) within the oligodendrogliomas to correlate with survival.

Results

Patients with oligodendrogliomas (141) were median age at diagnosis of 44 years; 57% male; 75% White; 60% prior chemotherapy; and 25% on dexamethasone at sample collection. Patients with oligodendrogliomas had immune profiles more similar to controls than other glioma subtypes, though with notably lower B-cells. RPA of patients with oligodendrogliomas delineated 2 survival groups based on an interaction between age and B-naïve cells. Patients with longer survival (median 24.2 years) were ≤42 years of age with higher B-naïve cells versus worse survival (median 16.9 years) who were ≤42 years of age with lower B-naïve cells or >42 years of age (P = .00032). Patients with worse survival also had lower CD4- and CD8-naïve T-cells. Similar immune profiles were observed in an independent cohort of oligodendroglioma patients prior to surgery.

Conclusions

Peripheral blood immune profiles in oligodendroglioma suggested that younger patients with lower B-naïve cells experienced shorter survival. Though our findings lack of validation cohort and use a heterogenous patient population, they suggest peripheral blood immune profiles may be prognostic for patients with glioma and warrant further investigation.

Recent Developments in Blood Biomarkers in Neuro-oncology

PURPOSE OF REVIEW

Given the invasive and high-risk nature of brain surgery, the need for non-invasive biomarkers obtained from the peripheral blood is greatest in tumors of the central nervous system (CNS). In this comprehensive review, we highlight recent advances in blood biomarker development for adult and pediatric brain tumors.

RECENT FINDINGS

We summarize recent blood biomarker development for CNS tumors across multiple key analytes, including peripheral blood mononuclear cells, cell-free DNA, cell-free RNA, proteomics, circulating tumor cells, and tumor-educated platelets. We also discuss methods for enhancing blood biomarker detection through transient opening of the blood-brain barrier. Although blood-based biomarkers are not yet used in routine neuro-oncology practice, this field is advancing rapidly and holds great promise for improved and non-invasive management of patients with brain tumors. Prospective and adequately powered studies are needed to confirm the clinical utility of any blood biomarker prior to widespread clinical implementation.

Genetic predisposition to altered blood cell homeostasis is associated with glioma risk and survival

Glioma is a highly fatal brain tumor comprised of molecular subtypes with distinct clinical trajectories. Observational studies have suggested that variability in immune response may play a role in glioma etiology. However, their findings have been inconsistent and susceptible to reverse causation due to treatment effects and the immunosuppressive nature of glioma. We applied genetic variants associated (p<5×10-8) with blood cell traits to a meta-analysis of 3418 glioma cases and 8156 controls. Genetically predicted increase in the platelet to lymphocyte ratio (PLR) was associated with an increased risk of glioma (odds ratio (OR)=1.25, p=0.005), especially in IDH-mutant (IDHmut OR=1.38, p=0.007) and IDHmut 1p/19q non-codeleted (IDHmut-noncodel OR=1.53, p=0.004) tumors. However, reduced glioma risk was observed for higher counts of lymphocytes (IDHmut-noncodel OR=0.70, p=0.004) and neutrophils (IDHmut OR=0.69, p=0.019; IDHmut-noncodel OR=0.60, p=0.009), which may reflect genetic predisposition to enhanced immune-surveillance. In contrast to susceptibility, there was no association with survival in IDHmut-noncodel; however, in IDHmut 1p/19q co-deleted tumors, we observed higher mortality with increasing genetically predicted counts of lymphocytes (hazard ratio (HR)=1.65, 95% CI: 1.24-2.20), neutrophils (HR=1.49, 1.13-1.97), and eosinophils (HR=1.59, 1.18-2.14). Polygenic scores for blood cell traits were also associated with tumor immune microenvironment features, with heterogeneity by IDH status observed for 17 signatures related to interferon signaling, PD-1 expression, and T-cell/Cytotoxic responses. In summary, we identified novel, immune-mediated susceptibility mechanisms for glioma with potential disease management implications.

Quantitative analysis using intraoperative contrast-enhanced ultrasound in adult-type diffuse gliomas with isocitrate dehydrogenase mutations: association between hemodynamics and molecular features

PURPOSE

The relationship between contrast-enhanced ultrasound (CEUS) hemodynamics and the molecular biomarkers of adult-type diffuse gliomas, particularly isocitrate dehydrogenase (IDH), remains unclear. This study was conducted to provide a comprehensive description of the vascularization of adult-type diffuse gliomas using quantitative indicators. Additionally, it was designed to identify any variables with the potential to intraoperatively predict IDH mutation status.

METHODS

This prospective study enrolled patients with adult-type diffuse gliomas between November 2021 and September 2022. Intraoperative CEUS was performed, and CEUS videos were recorded for 90-second periods. Hemodynamic parameters, including the peak enhancement (PE) difference, were calculated based on the time-intensity curve of the region of interest. A differential analysis was performed on the CEUS parameters with respect to molecular biomarkers and grades. Receiver operating characteristic curves for various parameters were analyzed to evaluate the ability of those parameters to predict IDH mutation status.

RESULTS

Sixty patients with adult-type diffuse gliomas were evaluated. All hemodynamic parameters, apart from rising time, demonstrated significant differences between IDH-mutant and IDH-wildtype adult-type diffuse gliomas. The PE difference emerged as the optimal indicator for differentiating between IDH-wildtype and IDH-mutant gliomas, with an area under the curve of 0.958 (95% confidence interval, 0.406 to 0.785). Additionally, the hemodynamic parameters revealed significant differences across both grades and types of adult-type diffuse gliomas.

CONCLUSION

Hemodynamic parameters can be used intraoperatively to effectively distinguish between IDHwildtype and IDH-mutant adult-type diffuse gliomas. Additionally, quantitative CEUS equips neurosurgeons with dynamic perfusion information for various types and grades of adult-type diffuse gliomas.

Advances in mitophagy and mitochondrial apoptosis pathway-related drugs in glioblastoma treatment

Glioblastoma (GBM) is the most common malignant tumor of the central nervous system (CNS). It is a leading cause of death among patients with intracranial malignant tumors. GBM exhibits intra- and inter-tumor heterogeneity, leading to drug resistance and eventual tumor recurrence. Conventional treatments for GBM include maximum surgical resection of glioma tissue, temozolomide administration, and radiotherapy, but these methods do not effectively halt cancer progression. Therefore, development of novel methods for the treatment of GBM and identification of new therapeutic targets are urgently required. In recent years, studies have shown that drugs related to mitophagy and mitochondrial apoptosis pathways can promote the death of glioblastoma cells by inducing mitochondrial damage, impairing adenosine triphosphate (ATP) synthesis, and depleting large amounts of ATP. Some studies have also shown that modern nano-drug delivery technology targeting mitochondria can achieve better drug release and deeper tissue penetration, suggesting that mitochondria could be a new target for intervention and therapy. The combination of drugs targeting mitochondrial apoptosis and autophagy pathways with nanotechnology is a promising novel approach for treating GBM.This article reviews the current status of drug therapy for GBM, drugs targeting mitophagy and mitochondrial apoptosis pathways, the potential of mitochondria as a new target for GBM treatment, the latest developments pertaining to GBM treatment, and promising directions for future research.

A novel DNA methylation-related gene signature for the prediction of overall survival and immune characteristics of ovarian cancer patients

BACKGROUND

Ovarian cancer (OC) is one of the most life-threatening cancers affecting women worldwide. Recent studies have shown that the DNA methylation state can be used in the diagnosis, treatment and prognosis prediction of diseases. Meanwhile, it has been reported that the DNA methylation state can affect the function of immune cells. However, whether DNA methylation-related genes can be used for prognosis and immune response prediction in OC remains unclear.

METHODS

In this study, DNA methylation-related genes in OC were identified by an integrated analysis of DNA methylation and transcriptome data. Prognostic values of the DNA methylation-related genes were investigated through least absolute shrinkage and selection operator (LASSO) and Cox progression analyses. Immune characteristics were investigated by CIBERSORT, correlation analysis and weighted gene co-expression network analysis (WGCNA).

RESULTS

Twelve prognostic genes (CA2, CD3G, HABP2, KCTD14, PI3, SERPINB5, SLAMF7, SLC9A2, STC2, TBP, TREML2 and TRIM27) were identified and a risk score signature and a nomogram based on prognostic genes and clinicopathological features were constructed for the survival prediction of OC patients in the training and two validation cohorts. Subsequently, the differences in the immune landscape between the high- and low-risk score groups were systematically investigated.

CONCLUSIONS

Taken together, our study explored a novel efficient risk score signature and a nomogram for the survival prediction of OC patients. In addition, the differences of the immune characteristics between the two risk groups were clarified preliminarily, which will guide the further exploration of synergistic targets to improve the efficacy of immunotherapy in OC patients.

Pathological perspectives in pilocytic astrocytomas: Extent of resection as the sole critical factor for recurrence-free survival, and the challenge of evaluating conclusions derived from limited data

Introduction: Pilocytic astrocytoma (PA) is one of the most common primary intracranial neoplasms in childhood with an overall favorable prognosis. Despite decades of experience, there are still diagnostic and treatment challenges and unresolved issues regarding risk factors associated with recurrence, most often due to conclusions of publications with limited data. We analyzed 499 patients with PA diagnosed in a single institution over 30 years in order to provide answers to some of the unresolved issues. Materials and Methods: We identified pilocytic astrocytomas diagnosed at the University of California, San Francisco, between 1989 and 2019, confirmed the diagnoses using the WHO 2021 essential and desirable criteria, and performed a retrospective review of the demographic and clinical features of the patients and the radiological, pathologic and molecular features of the tumors. Results: Among the patients identified from pathology archives, 499 cases fulfilled the inclusion criteria. Median age at presentation was 12 years (range 3.5 months - 73 years) and the median follow-up was 78.5 months. Tumors were predominantly located in the posterior fossa (52.6%). There were six deaths, but there were confounding factors that prevented a clear association of death to tumor progression. Extent of resection was the only significant factor for recurrence-free survival. Recurrence-free survival time was 321.0 months for gross total resection, compared to 160.9 months for subtotal resection (log rank, p <0.001). Conclusion: Multivariate analysis was able to identify extent of resection as the only significant variable to influence recurrence-free survival. We did not find a statistically significant association between age, NF1 status, tumor location, molecular alterations, and outcome. Smaller series with apparently significant results may have suffered from limited sample size, limited variables, acceptance of univariate analysis findings as well as a larger p value for biological significance. PA still remains a predominantly surgical disease and every attempt should be made to achieve gross total resection since this appears to be the most reliable predictor of recurrence-free survival.

Calcipotriol, a synthetic Vitamin D analog, promotes antitumor immunity via CD4+T-dependent CTL/NK cell activation

To overcome the hurdles of immunotherapy, we investigated whether calcipotriol, a synthetic vitamin D analog, could overcome the immune evasion of glioblastoma multiforme (GBM) by modulating immune responses and the immunosuppressive tumor microenvironment. Administration of calcipotriol considerably reduced tumor growth. Both in vivo and in vitro studies revealed that CD8+T and natural killer (NK) cell gene signatures were enriched and activated, producing high levels of IFN-γ and granzyme B. In contrast, regulatory T cells (Treg) were significantly reduced in the calcipotriol-treated group. The expression of CD127, the receptor for thymic stromal lymphopoietin (TSLP), is elevated in CD4+T cells and potentially supports T-cell priming. Depleting CD4+T cells, but not NK or CD8+T cells, completely abrogated the antitumor efficacy of calcipotriol. These data highlight that the calcipotriol/TSLP/CD4+T axis can activate CD8+T and NK cells with a concomitant reduction in the number of Tregs in GBM. Therefore, calcipotriol can be a novel therapeutic modality to overcome the immune resistance of GBM by converting immunologically "cold" tumors into "hot" tumors. DATA AVAILABILITY: Data are available upon reasonable request. The RNA-seq dataset comparing the transcriptomes of control and calcipotriol-treated GL261 tumors is available from the corresponding author upon request.

Pre-surgery immune profiles of adult glioma patients

INTRODUCTION

Although immunosuppression is a known characteristic of glioma, no previous large studies have reported peripheral blood immune cell profiles prior to patient surgery and chemoradiation. This report describes blood immune cell characteristics and associated variables prior to surgery among typical glioma patients seen at a large University practice.

METHODS

We analyzed pre-surgery blood samples from 139 glioma patients diagnosed with a new or recurrent grade II/III glioma (LrGG, n = 64) or new glioblastoma (GBM, n = 75) and 454 control participants without glioma. Relative cell fractions of CD4, CD8, B-cells, Natural Killer cells, monocytes, and neutrophils, were estimated via a validated deconvolution algorithm from blood DNA methylation measures from Illumina EPIC arrays.

RESULTS

Dexamethasone use at time of blood draw varied by glioma type being highest among patients with IDH wild-type (wt) GBM (75%) and lowest for those with oligodendroglioma (14%). Compared to controls, glioma patients showed statistically significant lower cell fractions for all immune cell subsets except for neutrophils which were higher (all p-values < 0.001), in part because of the higher prevalence of dexamethasone use at time of blood draw for IDHwt GBM. Patients who were taking dexamethasone were more likely to have a low CD4 count (< 200, < 500), increased neutrophils, low absolute lymphocyte counts, higher total cell count and higher NLR.

CONCLUSION

We show that pre-surgery blood immune profiles vary by glioma subtype, age, and more critically, by use of dexamethasone. Our results highlight the importance of considering dexamethasone exposures in all studies of immune profiles and of obtaining immune measures prior to use of dexamethasone, if possible.

Clinical significance and molecular annotation of cellular morphometric subtypes in lower-grade gliomas discovered by machine learning

BACKGROUND

Lower-grade gliomas (LGG) are heterogeneous diseases by clinical, histological, and molecular criteria. We aimed to personalize the diagnosis and therapy of LGG patients by developing and validating robust cellular morphometric subtypes (CMS) and to uncover the molecular signatures underlying these subtypes.

METHODS

Cellular morphometric biomarkers (CMBs) were identified with artificial intelligence technique from TCGA-LGG cohort. Consensus clustering was used to define CMS. Survival analysis was performed to assess the clinical impact of CMBs and CMS. A nomogram was constructed to predict 3- and 5-year overall survival (OS) of LGG patients. Tumor mutational burden (TMB) and immune cell infiltration between subtypes were analyzed using the Mann-Whitney U test. The double-blinded validation for important immunotherapy-related biomarkers was executed using immunohistochemistry (IHC).

RESULTS

We developed a machine learning (ML) pipeline to extract CMBs from whole-slide images of tissue histology; identifying and externally validating robust CMS of LGGs in multicenter cohorts. The subtypes had independent predicted OS across all three independent cohorts. In the TCGA-LGG cohort, patients within the poor-prognosis subtype responded poorly to primary and follow-up therapies. LGGs within the poor-prognosis subtype were characterized by high mutational burden, high frequencies of copy number alterations, and high levels of tumor-infiltrating lymphocytes and immune checkpoint genes. Higher levels of PD-1/PD-L1/CTLA-4 were confirmed by IHC staining. In addition, the subtypes learned from LGG demonstrate translational impact on glioblastoma (GBM).

CONCLUSIONS

We developed and validated a framework (CMS-ML) for CMS discovery in LGG associated with specific molecular alterations, immune microenvironment, prognosis, and treatment response.