Isocitrate dehydrogenase 1 mutation is associated with reduced levels of inflammation in glioma patients

Immunity in malignant brain tumors: Tumor entities, role of immunotherapy, and specific contribution of myeloid cells to the brain tumor microenvironment

Malignant brain tumors lack effective treatment, that can improve their poor overall survival achieved with standard of care. Advancement in different cancer treatments has shifted the focus in brain tumor research and clinical trials toward immunotherapy-based approaches. The investigation of the immune cell landscape revealed a dominance of myeloid cells in the tumor microenvironment. Their exact roles and functions are the subject of ongoing research. Current evidence suggests a complex interplay of tumor cells and myeloid cells with competing functions toward support vs. control of tumor growth. Here, we provide a brief overview of the three most abundant brain tumor entities: meningioma, glioma, and brain metastases. We also describe the field of ongoing immunotherapy trials and their results, including immune checkpoint inhibitors, vaccination studies, oncolytic viral therapy, and CAR-T cells. Finally, we summarize the phenotypes of microglia, monocyte-derived macrophages, border-associated macrophages, neutrophils, and potential novel therapy targets.

The Role of Inflammation in the Initiation and Progression of Myeloid Neoplasms

Myeloid malignancies are devastating hematologic cancers with limited therapeutic options. Inflammation is emerging as a novel driver of myeloid malignancy, with important implications for tumor composition, immune response, therapeutic options, and patient survival. Here, we discuss the role of inflammation in normal and malignant hematopoiesis, from clonal hematopoiesis to full-blown myeloid leukemia. We discuss how inflammation shapes clonal output from hematopoietic stem cells, how inflammation alters the immune microenvironment in the bone marrow, and novel therapies aimed at targeting inflammation in myeloid disease.

SIGNIFICANCE

Inflammation is emerging as an important factor in myeloid malignancies. Understanding the role of inflammation in myeloid transformation, and the interplay between inflammation and other drivers of leukemogenesis, may yield novel avenues for therapy.

Prognostic Values of Systemic Inflammatory Immunological Markers in Glioblastoma: A Systematic Review and Meta-Analysis

BACKGROUND

Neutrophils are an important part of the tumor microenvironment, which stimulates inflammatory processes through phagocytosis, degranulation, release of small DNA fragments (cell-free DNA), and presentation of antigens. Since neutrophils accumulate in peripheral blood in patients with advanced-stage cancer, a high neutrophil-to-lymphocyte ratio can be a biomarker of a poor prognosis in patients with glioblastoma. The present study aimed to explore the prognostic value of the preoperative levels of neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune inflammation index (SII), systemic inflammation response index (SIRI), and cell-free DNA (cfDNA) to better predict prognostic implications in the survival rate of glioblastoma patients.

METHODS

The meta-analysis was carried out according to the recommendations and standards established by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Databases of PubMed, EBSCO, and Medline were systematically searched to select all the relevant studies published up to December 2022.

RESULTS

Poorer prognoses were recorded in patients with a high NLR or PLR when compared with the patients with a low NLR or PLR (HR 1.51, 95% CI 1.24-1.83, p < 0.0001 and HR 1.34, 95% CI 1.10-1.63, p < 0.01, respectively). Similarly, a worse prognosis was reported for patients with a higher cfDNA (HR 2.35, 95% CI 1.27-4.36, p < 0.01). The SII and SIRI values were not related to glioblastoma survival (p = 0.0533 and p = 0.482, respectively).

CONCLUSIONS

Thus, NLR, PLR, and cfDNA, unlike SII and SIRI, appeared to be useful and convenient peripheral inflammatory markers to assess the prognosis in glioblastoma.

Neutrophils: New Critical Regulators of Glioma

In cancer, neutrophils are an important part of the tumour microenvironment (TME). Previous studies have shown that circulating and infiltrating neutrophils are associated with malignant progression and immunosuppression in gliomas. However, recent studies have shown that neutrophils have an antitumour effect. In this review, we focus on the functional roles of neutrophils in the circulation and tumour sites in patients with glioma. The mechanisms of neutrophil recruitment, immunosuppression and the differentiation of neutrophils are discussed. Finally, the potential of neutrophils as clinical biomarkers and therapeutic targets is highlighted. This review can help us gain a deeper and systematic understanding of the role of neutrophils, and provide new insights for treatment in gliomas.

Commentary: Evaluating potential glioma serum biomarkers, with future applications

Systemic inflammation within malignant glioma is a topic of ongoing significance. In this commentary, we highlight recent findings from Gandhi et al and discuss alternative approaches. We present a counter argument with findings that IL-6 markers are controversial. We highlight the potential benefit of looking at microRNAs and other biomarkers. Finally, we present ideas for future application involving differentiation between radiation necrosis and recurrence. The commentary is intended to serve as a catalyst for further scientific discovery.

Establishment of tumor inflammasome clusters with distinct immunogenomic landscape aids immunotherapy

Inflammasome signaling is a reaction cascade that influences immune response and cell death. Although the inflammasomes participate in tumorigenesis, their role as an oncogenic booster or a tumor suppresser is still controversial. Therefore, it is important to comprehensively investigate the inflammasome signaling status across various cancers to clarify its clinical and therapeutic significance.

Methods: A total of 9881 patients across 33 tumor types from The Cancer Genome Atlas database were included in this study. Five gene sets were identified to step-wisely profile inflammasome signaling. Unsupervised clustering was used for sample classification based on gene set enrichment. Machine learning and in vitro and in vivo experiments were used to confirm the implications of inflammasome classification.

Results: A hundred and forty-one inflammasome-signaling-related genes were identified to construct five gene sets representing the sensing, activation, and termination steps of the inflammasome signaling. Six inflammasome clusters were robustly established with distinct molecular, biological, clinical, and therapeutic features. Importantly, clusters with inflammasome signaling activation were found to be immunosuppressive and resistant to ICB treatment. Inflammasome inhibition reverted the therapeutic failure of ICB in inflammasome-activated tumors. Moreover, based on the proposed classification and therapeutic implications, an open website was established to provide tumor patients with comprehensive information on inflammasome signaling.

Conclusions: Our study conducted a systematical investigation on inflammasome signaling in various tumor types. These findings highlight the importance of inflammasome evaluation in tumor classification and provide a foundation for improving relevant therapeutic regimens.

A Simple Preoperative Blood Count to Stratify Prognosis in Isocitrate Dehydrogenase-Wildtype Glioblastoma Patients Treated with Radiotherapy plus Concomitant and Adjuvant Temozolomide

PURPOSE

The survival times of glioblastoma (GB) patients after the standard therapy including safe maximal resection followed by radiotherapy plus concomitant and adjuvant temozolomide are heterogeneous. In order to define a simple, reliable method for predicting whether patients with isocitrate dehydrogenase (IDH)-wildtype GB treated with the standard therapy will be short- or long-term survivors, we analyzed the correlation of preoperative blood counts and their combined forms with progression-free survival (PFS) and overall survival (OS) in these patients.

METHODS

Eighty-five patients with primary IDH-wildtype GB treated with the standard therapy between 2012 and 2019 were analyzed retrospectively. Cox proportional hazards models and Kaplan-Meier analysis were used to investigate the survival function of preoperative hematological parameters.

RESULTS

Preoperative high neutrophil-to-lymphocyte ratio (NLR, >2.42), high platelet count (>236 × 10⁹/L), and low red blood cell (RBC) count (≤4.59 × 10¹²/L) were independent prognostic factors for poorer OS (p = 0.030, p = 0.030, and p = 0.004, respectively). Moreover, a high NLR was an independent prognostic factor for shorter PFS (p = 0.010). We also found that, like NLR, preoperative high derived NLR (dNLR, >1.89) was of poor prognostic value for both PFS (p = 0.002) and OS (p = 0.033). A significant correlation was observed between NLR and dNLR (r = 0.88, p < 0.001), which had a similar prognostic power for OS (NLR: AUC = 0.58; 95% CI: [0.48; 0.68]; dNLR: AUC = 0.62; 95% CI: [0.51; 0.72]). Two scores, one based on preoperative platelet and RBC counts plus NLR and the other on preoperative platelet and RBC counts plus dNLR, were found to be independent prognostic factors for PFS (p = 0.006 and p = 0.002, respectively) and OS (p < 0.001 for both scores).

CONCLUSION

Cheap, routinely ordered, preoperative assessments of blood markers, such as NLR, dNLR, RBC, and platelet counts, can predict the survival outcomes of patients with IDH-wildtype GB treated with the standard therapy.

Recent Metabolic Advances for Preventing and Treating Acute and Chronic Graft Versus Host Disease

The therapeutic efficacy of allogeneic hematopoietic stem cell transplantation (allo-HSCT) is limited by the development of graft-versus-host disease (GVHD). In GVHD, rigorous pre-conditioning regimen resets the immune landscape and inflammatory milieu causing immune dysregulation, characterized by an expansion of alloreactive cells and a reduction in immune regulatory cells. In acute GVHD (aGVHD), the release of damage- and pathogen- associated molecular patterns from damaged tissue caused by the conditioning regimen sets the stage for T cell priming, activation and expansion further exacerbating tissue injury and organ damage, particularly in the gastrointestinal tract. Studies have shown that donor T cells utilize multiple energetic and biosynthetic pathways to mediate GVHD that can be distinct from the pathways used by regulatory T cells for their suppressive function. In chronic GVHD (cGVHD), donor T cells may differentiate into IL-21 producing T follicular helper cells or tissue resident T helper cells that cooperate with germinal center B cells or memory B cells, respectively, to produce allo- and auto-reactive antibodies with subsequent tissue fibrosis. Alternatively, donor T cells can become IFN- γ/IL-17 cytokine expressing T cells that mediate sclerodermatous skin injury. Patients refractory to the first line standard regimens for GVHD treatment have a poor prognosis indicating an urgent need for new therapies to restore the balance between effector and regulatory immune cells while preserving the beneficial graft-versus-tumor effect. Emerging data points toward a role for metabolism in regulating these allo- and auto-immune responses. Here, we will discuss the preclinical and clinical data available on the distinct metabolic demands of acute and chronic GVHD and recent efforts in identifying therapeutic targets using metabolomics. Another dimension of this review will examine the changing microbiome after allo-HSCT and the role of microbial metabolites such as short chain fatty acids and long chain fatty acids on regulating immune responses. Lastly, we will examine the metabolic implications of coinhibitory pathway blockade and cellular therapies in allo-HSCT. In conclusion, greater understanding of metabolic pathways involved in immune cell dysregulation during allo-HSCT may pave the way to provide novel therapies to prevent and treat GVHD.

Blood-Based Biomarkers for Glioma in the Context of Gliomagenesis: A Systematic Review

BACKGROUND

Gliomas are the most common and aggressive tumors of the central nervous system. A robust and widely used blood-based biomarker for glioma has not yet been identified. In recent years, a plethora of new research on blood-based biomarkers for glial tumors has been published. In this review, we question which molecules, including proteins, nucleic acids, circulating cells, and metabolomics, are most promising blood-based biomarkers for glioma diagnosis, prognosis, monitoring and other purposes, and align them to the seminal processes of cancer.

METHODS

The Pubmed and Embase databases were systematically searched. Biomarkers were categorized in the identified biomolecules and biosources. Biomarker characteristics were assessed using the area under the curve (AUC), accuracy, sensitivity and/or specificity values and the degree of statistical significance among the assessed clinical groups was reported.

RESULTS

7,919 references were identified: 3,596 in PubMed and 4,323 in Embase. Following screening of titles, abstracts and availability of full-text, 262 articles were included in the final systematic review. Panels of multiple biomarkers together consistently reached AUCs >0.8 and accuracies >80% for various purposes but especially for diagnostics. The accuracy of single biomarkers, consisting of only one measurement, was far more variable, but single microRNAs and proteins are generally more promising as compared to other biomarker types.

CONCLUSION

Panels of microRNAs and proteins are most promising biomarkers, while single biomarkers such as GFAP, IL-10 and individual miRNAs also hold promise. It is possible that panels are more accurate once these are involved in different, complementary cancer-related molecular pathways, because not all pathways may be dysregulated in cancer patients. As biomarkers seem to be increasingly dysregulated in patients with short survival, higher tumor grades and more pathological tumor types, it can be hypothesized that more pathways are dysregulated as the degree of malignancy of the glial tumor increases. Despite, none of the biomarkers found in the literature search seem to be currently ready for clinical implementation, and most of the studies report only preliminary application of the identified biomarkers. Hence, large-scale validation of currently identified and potential novel biomarkers to show clinical utility is warranted.

Role of neutrophil-lymphocyte ratio as a predictive factor of glioma tumor grade: A systematic review

Gliomas are the main type of intra-axial primary brain tumors. We performed a systematic review of studies on the neutrophil-to-lymphocyte ratio (NLR) and its role in the prognosis of patients with gliomas. An English-language literature-based search, using the PubMed and Biblioteca Virtual em Saúde databases, was conducted for papers published until May 2, 2020. The quality of the selected articles was stratified using the Newcastle-Ottawa scale's criteria. We found 137 publications for a query string. After applying the inclusion criteria, 13 articles were selected. Seven studies assessed overall survival and found high NLR values associated with poor overall survival. Six studies approached the issue of tumor grading and differential diagnosis and demonstrated that patients with high NLR values were diagnosed with high-grade gliomas. NLR is a low-cost method and an effective prognostic factor associated with tumor grading and OS in patients with gliomas.

Tricarboxylic Acid (TCA) Cycle Intermediates: Regulators of Immune Responses

The tricarboxylic acid cycle (TCA) is a series of chemical reactions used in aerobic organisms to generate energy via the oxidation of acetylcoenzyme A (CoA) derived from carbohydrates, fatty acids and proteins. In the eukaryotic system, the TCA cycle occurs completely in mitochondria, while the intermediates of the TCA cycle are retained inside mitochondria due to their polarity and hydrophilicity. Under cell stress conditions, mitochondria can become disrupted and release their contents, which act as danger signals in the cytosol. Of note, the TCA cycle intermediates may also leak from dysfunctioning mitochondria and regulate cellular processes. Increasing evidence shows that the metabolites of the TCA cycle are substantially involved in the regulation of immune responses. In this review, we aimed to provide a comprehensive systematic overview of the molecular mechanisms of each TCA cycle intermediate that may play key roles in regulating cellular immunity in cell stress and discuss its implication for immune activation and suppression.

N6-methyladenine-related genes affect biological behavior and the prognosis of glioma

Background

Although aberrant expression of N6‐methyladenine (m⁶A) methylation‐related genes contribute to tumorigenesis in many solid tumors, the prognostic value of the m⁶A‐related genes and their correlation with clinicopathological features in gliomas need advanced study.

Methods

The clinical and sequencing data of 288 patients with glioma were extracted from Chinese Glioma Genome Atlas database. By univariate and multivariable Cox regression analysis, the m⁶A‐related prognostic genes were identified, and their correlation with clinicopathological features was further analysis. A nomogram was constructed by R software and the performance of it was assessed by calibration and time‐dependent receiver operating characteristic curve.

Results

Nine m⁶A‐related genes were identified as independent prognostic factors, which were mostly enriched in RNA splicing, regulation of immune response and vesicle‐mediated transport. By expression value and regression coefficient of these genes, we constructed risk score of each patient, which was highly associated with clinicopathological features. Kaplan–Meier curve showed that the prognosis of patients with high‐risk scores was significantly worse than that with low‐risk scores (HR = 4.30, 95% CI = 3.16–5.85, p < 0.0001). A nomogram was constructed based on the nine m⁶A‐related genes signature and clinicopathological features with well‐fitted calibration curves (c‐index = 0.82), showing high specificity and sensitivity (area under the curve for 1‐, 3‐, and 5‐years survival probability = 0.874, 0.918, and 0.934).

Conclusions

A nine m⁶A‐related genes signature was identified in gliomas. The m⁶A‐related risk score is a novel prognostic factor for patients with glioma, and is associated with clinicopathological features. Moreover, the nomogram based on the nine m⁶A‐related genes signature and clinicopathological features had good efficacy in predicting the survival probability.

Identification and Validation of an Energy Metabolism-Related lncRNA-mRNA Signature for Lower-Grade Glioma

Energy metabolic processes play important roles for tumor malignancy, indicating that related protein-coding genes and regulatory upstream genes (such as long noncoding RNAs (lncRNAs)) may represent potential biomarkers for prognostic prediction. This study will develop a new energy metabolism-related lncRNA-mRNA prognostic signature for lower-grade glioma (LGG) patients. A GSE4290 dataset obtained from Gene Expression Omnibus was used for screening the differentially expressed genes (DEGs) and lncRNAs (DELs). The Cancer Genome Atlas (TCGA) dataset was used as the prognosis training set, while the Chinese Glioma Genome Atlas (CGGA) was for the validation set. Energy metabolism-related genes were collected from the Molecular Signatures Database (MsigDB), and a coexpression network was established between energy metabolism-related DEGs and DELs to identify energy metabolism-related DELs. Least absolute shrinkage and selection operator (LASSO) analysis was performed to filter the prognostic signature which underwent survival analysis and nomogram construction. A total of 1613 DEGs and 37 DELs were identified between LGG and normal brain tissues. One hundred and ten DEGs were overlapped with energy metabolism-related genes. Twenty-seven DELs could coexpress with 67 metabolism-related DEGs. LASSO regression analysis showed that 9 genes in the coexpression network were the optimal signature and used to construct the risk score. Kaplan-Meier curve analysis showed that patients with a high risk score had significantly worse OS than those with a low risk score (TCGA: HR = 3.192, 95%CI = 2.182‐4.670; CGGA: HR = 1.922, 95%CI = 1.431‐2.583). The predictive accuracy of the risk score was also high according to the AUC of the ROC curve (TCGA: 0.827; CGGA: 0.806). Multivariate Cox regression analyses revealed age, IDH1 mutation, and risk score as independent prognostic factors, and thus, a prognostic nomogram was established based on these three variables. The excellent prognostic performance of the nomogram was confirmed by calibration and discrimination analyses. In conclusion, our findings provided a new biomarker for the stratification of LGG patients with poor prognosis.

Robust detection of oncometabolic aberrations by 1H-13C heteronuclear single quantum correlation in intact biological specimens

Magnetic resonance (MR) spectroscopy has potential to non-invasively detect metabolites of diagnostic significance for precision oncology. Yet, many metabolites have similar chemical shifts, yielding highly convoluted ¹H spectra of intact biological material and limiting diagnostic utility. Here, we show that hydrogen–carbon heteronuclear single quantum correlation (¹H–¹³C HSQC) offers dramatic improvements in sensitivity compared to one-dimensional (1D) ¹³C NMR and significant signal deconvolution compared to 1D ¹H spectra in intact biological settings. Using a standard NMR spectroscope with a cryoprobe but without specialized signal enhancing features such as magic angle spinning, metabolite extractions or ¹³C-isotopic enrichment, we obtain well-resolved 2D ¹H–¹³C HSQC spectra in live cancer cells, in ex vivo freshly dissected xenografted tumors and resected primary tumors. This method can identify tumors with specific oncometabolite alterations such as IDH mutations by 2-hydroxyglutarate and PGD-deleted tumors by gluconate. Results suggest potential of ¹H–¹³C HSQC as a non-invasive diagnostic in precision oncology.

Barekatain et al. demonstrate that hydrogen–carbon heteronuclear single quantum correlation (HSQC) spectra, obtained using a standard NMR spectroscope, can detect tumours with specific oncometabolite alterations including IDH1 mutant glioblastoma, suggesting the feasibility of this method as a diagnostic tool.