Lower Grade Gliomas

Leveraging FAM features to predict the prognosis of LGG patients and immunotherapy outcome

Heterogeneity at biological and transcriptomic levels poses a challenge in defining and typing low-grade glioma (LGG), leading to a critical need for specific molecular signatures to enhance diagnosis, therapy, and prognostic evaluation of LGG. This study focused on fatty acid metabolism (FAM) related genes and prognostic features to investigate the mechanisms and treatment strategies for LGG cell metastasis and invasion. By screening 158 FAM-related genes and clustering 512 LGG samples into two subtypes (C1 and C2), differential gene expression analysis and functional enrichment were performed. The immune cell scores and prognosis were compared between the two subtypes, with C1 showing poorer outcomes and higher immune scores. A four-gene signature (PHEX, SHANK2, HOPX, and LGALS1) was identified and validated across different datasets, demonstrating a stable predictive effect. Cellular experiments confirmed the roles of LGALS1 and HOPX in promoting tumor cell proliferation, migration, and invasion, while SHANK2 exhibited a suppressive effect. This four-gene signature based on FAM-related genes offers valuable insights for understanding the pathogenesis and clinical management of LGG.

Mitochondrial RNA modification-based signature to predict prognosis of lower grade glioma: a multi-omics exploration and verification study

Mitochondrial RNA modification (MRM) plays a crucial role in regulating the expression of key mitochondrial genes and promoting tumor metastasis. Despite its significance, comprehensive studies on MRM in lower grade gliomas (LGGs) remain unknown. Single-cell RNA-seq data (GSE89567) was used to evaluate the distribution functional status, and correlation of MRM-related genes in different cell types of LGG microenvironment. We developed an MRM scoring system by selecting potential MRM-related genes using LASSO regression analysis and the Random Survival Forest algorithm, based on multiple bulk RNA-seq datasets from TCGA, CGGA, GSE16011, and E-MTAB-3892. Analysis was performed on prognostic and immunological features, signaling pathways, metabolism, somatic mutations and copy number variations (CNVs), treatment responses, and forecasting of potential small-molecule agents. A total of 35 MRM-related genes were selected from the literature. Differential expression analysis of 1120 normal brain tissues and 529 LGGs revealed that 22 and 10 genes were upregulated and downregulated, respectively. Most genes were associated with prognosis of LGG. METLL8, METLL2A, TRMT112, and METTL2B were extensively expressed in all cell types and different cell cycle of each cell type. Almost all cell types had clusters related to mitochondrial RNA processing, ribosome biogenesis, or oxidative phosphorylation. Cell-cell communication and Pearson correlation analyses indicated that MRM may promoting the development of microenvironment beneficial to malignant progression via modulating NCMA signaling pathway and ICP expression. A total of 11 and 9 MRM-related genes were observed by LASSO and the RSF algorithm, respectively, and finally 6 MRM-related genes were used to establish MRM scoring system (TRMT2B, TRMT11, METTL6, METTL8, TRMT6, and TRUB2). The six MRM-related genes were then validated by qPCR in glioma and normal tissues. MRM score can predict the malignant clinical characteristics, abundance of immune infiltration, gene variation, clinical outcome, the enrichment of signaling pathways and metabolism. In vitro experiments demonstrated that silencing METTL8 significantly curbs glioma cell proliferation and enhances apoptosis. Patients with a high MRM score showed a better response to immunotherapies and small-molecule agents such as arachidonyl trifluoromethyl ketone, MS.275, AH.6809, tacrolimus, and TTNPB. These novel insights into the biological impacts of MRM within the glioma microenvironment underscore its potential as a target for developing precise therapies, including immunotherapeutic approaches.

Ultra-Rapid Droplet Digital PCR Enables Intraoperative Tumor Quantification

The diagnosis and treatment of tumors often depends on molecular-genetic data. However, rapid and iterative access to molecular data is not currently feasible during surgery, complicating intraoperative diagnosis and precluding measurement of tumor cell burdens at surgical margins to guide resections. To address this gap, we developed Ultra-Rapid droplet digital PCR (UR-ddPCR), which can be completed in 15 minutes from tissue to result with an accuracy comparable to standard ddPCR. We demonstrate UR-ddPCR assays for the IDH1 R132H and BRAF V600E clonal mutations that are present in many low-grade gliomas and melanomas, respectively. We illustrate the clinical feasibility of UR-ddPCR by performing it intraoperatively for 13 glioma cases. We further combine UR-ddPCR measurements with UR-stimulated Raman histology intraoperatively to estimate tumor cell densities in addition to tumor cell percentages. We anticipate that UR-ddPCR, along with future refinements in assay instrumentation, will enable novel point-of-care diagnostics and the development of molecularly-guided surgeries that improve clinical outcomes.

Identification and clinical validation of diverse cell-death patterns-associated prognostic features among low-grade gliomas

Low-grade glioma (LGG) is heterogeneous at biological and transcriptomic levels, and it is still controversial for the definition and typing of LGG. Therefore, there is an urgent need for specific and practical molecular signatures for accurate diagnosis, individualized therapy, and prognostic evaluation of LGG. Cell death is essential for maintaining homeostasis, developing and preventing hyperproliferative malignancies. Based on diverse programmed cell death (PCD) related genes and prognostic characteristics of LGG, this study constructed a model to explore the mechanism and treatment strategies for LGG cell metastasis and invasion. We screened 1161 genes associated with PCD and divided 512 LGG samples into C1 and C2 subtypes by consistent cluster analysis. We analyzed the two subtypes' differentially expressed genes (DEGs) and performed functional enrichment analysis. Using R packages such as ESTIMATE, CIBERSOTR, and MCPcounter, we assessed immune cell scores for both subtypes. Compared with C1, the C2 subtype has a poor prognosis and a higher immune score, and patients in the C2 subtype are more strongly associated with tumor progression. LASSO and COX regression analysis screened four characteristic genes (CLU, FHL3, GIMAP2, and HVCN1). Using data sets from different platforms to validate the four-gene feature, we found that the expression and prognostic correlation of the four-gene feature had a high degree of stability, showing stable predictive effects. Besides, we found downregulation of CLU, FHL3, and GIMAP2 significantly impairs the growth, migration, and invasive potential of LGG cells. Take together, the four-gene feature constructed based on PCD-related genes provides valuable information for further study of the pathogenesis and clinical treatment of LGG.

Identifying Diffuse Glioma Subtypes Based on Pathway Enrichment Evaluation

Gliomas are highly heterogeneous in molecular, histology, and microenvironment. However, a classification of gliomas by integrating different tumor microenvironment (TME) components remains unexplored. Based on the enrichment scores of 17 pathways involved in immune, stromal, DNA repair, and nervous system signatures in diffuse gliomas, we performed consensus clustering to uncover novel subtypes of gliomas. Consistently in three glioma datasets (TCGA-glioma, CGGA325, and CGGA301), we identified three subtypes: Stromal-enriched (Str-G), Nerve-enriched (Ner-G), and mixed (Mix-G). Ner-G was charactered by low immune infiltration levels, stromal contents, tumor mutation burden, copy number alterations, DNA repair activity, cell proliferation, epithelial-mesenchymal transformation, stemness, intratumor heterogeneity, androgen receptor expression and EGFR, PTEN, NF1 and MUC16 mutation rates, while high enrichment of neurons and nervous system pathways, and high tumor purity, estrogen receptor expression, IDH1 and CIC mutation rates, temozolomide response rate and overall and disease-free survival rates. In contrast, Str-G displayed contrastive characteristics to Ner-G. Our analysis indicates that the heterogeneity between glioma cells and neurons is lower than that between glioma cells and immune and stromal cells. Furthermore, the abundance of neurons is positively associated with clinical outcomes in gliomas, while the enrichment of immune and stromal cells has a negative association with them. Our classification method provides new insights into the tumor biology of gliomas, as well as clinical implications for the precise management of this disease.

Bioinformatics analyses and experimental validation of the role of phagocytosis in low-grade glioma

BACKGROUND

Phagocytosis is of vital importance in tumor immune response. The alteration of phagocytosis in low-grade glioma (LGG) has not been investigated.

METHODS

The mRNA, copy number variation, single nucleotide variation, and methylation levels of phagocytosis-related genes were summarized in pan-cancer. Non-negative matrix factorization clustering was utilized to identify two LGG subtypes. LASSO regression analysis was performed to construct a phagocytosis-related prognostic signature (PRPS). Immune characteristics, immunotherapy response, and targeted-drug sensitivity were further explored. The phagocytosis activity in glioma was evaluated using scRNA-seq data. Multiplex immunohistochemical (m-IHC) technology was performed to identify the tumor-infiltrating immune cells in LGG.

RESULTS

The phagocytosis-related genes altered obviously in pan-cancer compared with corresponding normal tissues. Two LGG subtypes were obtained and the subtype with poor prognosis was combined with lower tumor purity, more active immune-related pathways, increasing infiltration of CD4+ T cells, CD8+ T cells, and natural killer (NK) cells, decreasing infiltration of macrophages, mast cells, and neutrophils, distinct pathway activity and cell death status, greater response to immunotherapy, and higher sensitivity to cyclophosphamide, erlotinib, gefitinib, lapatinib, and sorafenib. In addition, a PRPS involving 10 genes (i.e., SLC11A1, CAMK1D, PLA2G5, STAP1, ALOX15, PLCG2, SFTPD, AZU1, RAB27A, and LAMTOR2) was constructed to estimate the risk level of each LGG sample and high risk LGG patients had poor prognosis, upregulated infiltration of neutrophil, macrophage, Treg, and myeloid dendritic cell, down regulated infiltration of monocyte and NK cell, and increasing expression of large number of immune checkpoint genes. The phagocytosis activity is notably active in monocyte/macrophage. The m-IHC results confirmed increased infiltration of macrophages and neutrophils in LGG samples with high SLC11A1 expression.

CONCLUSION

The molecular characteristics of phagocytosis were revealed and the PRPS laid the foundation for personalized therapy in LGG.

Complement and coagulation cascades are associated with prognosis and the immune microenvironment of lower-grade glioma

Background

Abnormal coagulation is a common feature of glioma. There is a strong correlation between coagulation and the complement system, named complement and coagulation cascades (CCC). However, the role of CCC genes in lower-grade glioma (LGG) remains unclear. This study aimed to investigate the role of CCC genes in LGG.

Methods

In total, 5,628 differential expressed genes were identified between 498 LGG tissues from The Cancer Genome Atlas (TCGA) and 207 normal brain tissues from Genotype-Tissue Expression Project (GTEx). Among them, 20 overlapped CCC genes were identified as differentially expressed CCC genes. Then, comprehensive bioinformatics analysis was used to investigate the role of CCC genes in LGG; 271 LGG tissues from the Chinese Glioma Genome Atlas (CGGA) were used as the validation dataset. Cell Counting Kit-8 (CCK8) proliferation assay, colony formation assay, and wound healing assay were conducted to explore the anti-glioma effect of the sensitive drugs we predicted.

Results

We constructed a risk signature consisting of six CCC genes, including F2R, SERPINA1, TFPI, C1QC, C2, and C3AR1. The CCC gene-based risk signature could accurately predict the prognosis of patients with LGG. In addition, we found that the JAK-STAT, NOD-like receptor, Notch, PI3K-Akt, and Rap1 signaling pathways might be activated and had crosstalk with CCC in the high-risk group. Our findings analyses demonstrated that samples in high- and low-risk groups had different immune landscapes. Moreover, patients in the high-risk group might have greater resistance to immunotherapy. We validated the accuracy of the risk signature in predicting immunotherapy response in two public immunotherapy cohorts, GSE135222 and GSE78220. By means of oncoPredict, MG-132, BMS-536924, PLX-4720, and AZD6482 were identified as potential sensitive drugs for high-risk patients, of which MG-132 was particularly recommended for high-risk patients. We performed in vitro experiments to explore the anti-glioma effect of MG-132, and the results demonstrated MG-132 could inhibit the proliferation and migration of glioma cells.

Conclusions

Our findings show that CCC genes are associated with the prognosis and immune infiltration of LGG and provide possible immunotherapeutic and novel chemotherapeutic strategies for patients with LGG based on the risk signature.

Leveraging a gene signature associated with disulfidptosis identified by machine learning to forecast clinical outcomes, immunological heterogeneities, and potential therapeutic targets within lower-grade glioma

Background

Disulfidptosis, a newly defined type of programmed cell death, has emerged as a significant regulatory process in the development and advancement of malignant tumors, such as lower-grade glioma (LGG). Nevertheless, the precise biological mechanisms behind disulfidptosis in LGG are yet to be revealed, considering the limited research conducted in this field.

Methods

We obtained LGG data from the TCGA and CGGA databases and performed comprehensive weighted co-expression network analysis, single-sample gene set enrichment analysis, and transcriptome differential expression analyses. We discovered nine genes associated with disulfidptosis by employing machine learning methods like Cox regression, LASSO regression, and SVM-RFE. These were later used to build a predictive model for patients with LGG. To confirm the expression level, functional role, and impact on disulfidptosis of ABI3, the pivotal gene of the model, validation experiments were carried out in vitro.

Results

The developed prognostic model successfully categorized LGG patients into two distinct risk groups: high and low. There was a noticeable difference in the time the groups survived, which was statistically significant. The model's predictive accuracy was substantiated through two independent external validation cohorts. Additional evaluations of the immune microenvironment and the potential for immunotherapy indicated that this risk classification could function as a practical roadmap for LGG treatment using immune-based therapies. Cellular experiments demonstrated that suppressing the crucial ABI3 gene in the predictive model significantly reduced the migratory and invasive abilities of both SHG44 and U251 cell lines while also triggering cytoskeletal retraction and increased cell pseudopodia.

Conclusion

The research suggests that the prognostic pattern relying on genes linked to disulfidptosis can provide valuable insights into the clinical outcomes, tumor characteristics, and immune alterations in patients with LGG. This could pave the way for early interventions and suggests that ABI3 might be a potential therapeutic target for disulfidptosis.

The interaction between ASF1B and TLK1 promotes the malignant progression of low-grade glioma

AIM

Low-grade glioma (LGG), which is the second most frequent adult brain malignancy, severely threatens patients' health and has a high recurrence rate. Histone H3/H4 chaperone anti-silencing function 1 B (ASF1B) has a tight association with the initiation and development of tumours. The expression and regulation mechanism of ASF1B in LGG were discussed.

METHODS

ASF1B expression in LGG patients as well as the association of ASF1B with overall survival and disease-free survival of LGG patients were predicted by GEPIA database. The independent prognostic value of ASF1B in LGG patients was investigated by TCGA database. RT-qPCR, together with western blot was applied for the assessment of ASF1B in LGG cell lines. After ASF1B expression was inhibited, CCK8 and colony formation assays judged cell proliferation. Flow cytometry analysis and TUNEL assay appraised cell cycle as well as apoptosis. Cell migratory and invasive capacities were measured by wound healing as well as Transwell assays. Western blot tested the expression of proliferation-, cycle-, apoptosis-, and metastasis-associated proteins. STRING and GeneMANIA database predicted the relationship between ASF1B and tousled-like kinase 1 (TLK1). ChIP assay testified the affinity of ASF1B with TLK1. Subsequently, TLK1 was overexpressed and ASF1B expression interfered, and the functional assays were executed.

RESULTS

ASF1B was discovered to be increased in LGG tissues and cells and indicates an unfavourable prognosis for LGG patients. ASF1B was not an independent prognostic factor for LGG. ASF1B deficiency obstructed the proliferation, cell cycle as well as metastasis of LGG cells, and induced cell death, which might be realized through the interaction with TLK1.

CONCLUSION

The interaction between ASF1B and TLK1 promoted the malignant progression of LGG.Key messagesTLK1 interacts with ASF1B.Interference with ASF1B inhibits the proliferative, invasive and migratory capabilities and induces the cycle arrest, along with the apoptosis of LGG cells.The interaction between ASF1B and TLK1 promotes the malignant progression of LGG.

Overcoming chemotherapy resistance in low-grade gliomas: A computational approach

Low-grade gliomas are primary brain tumors that arise from glial cells and are usually treated with temozolomide (TMZ) as a chemotherapeutic option. They are often incurable, but patients have a prolonged survival. One of the shortcomings of the treatment is that patients eventually develop drug resistance. Recent findings show that persisters, cells that enter a dormancy state to resist treatment, play an important role in the development of resistance to TMZ. In this study we constructed a mathematical model of low-grade glioma response to TMZ incorporating a persister population. The model was able to describe the volumetric longitudinal dynamics, observed in routine FLAIR 3D sequences, of low-grade glioma patients acquiring TMZ resistance. We used the model to explore different TMZ administration protocols, first on virtual clones of real patients and afterwards on virtual patients preserving the relationships between parameters of real patients. In silico clinical trials showed that resistance development was deferred by protocols in which individual doses are administered after rest periods, rather than the 28-days cycle standard protocol. This led to median survival gains in virtual patients of more than 15 months when using resting periods between two and three weeks and agreed with recent experimental observations in animal models. Additionally, we tested adaptive variations of these new protocols, what showed a potential reduction in toxicity, but no survival gain. Our computational results highlight the need of further clinical trials that could obtain better results from treatment with TMZ in low grade gliomas.

Precise Construction of Dual-Promising Anticancer Drugs Associated with Gold Nanomaterials on Glioma Cancer Cells

Multiple chemodrugs with nanotechnology have proven to be an effective cancer treatment technique. When taken combined, cabazitaxel (CTX) and cisplatin (PT) have more excellent cytotoxic effects than drugs used alone in the chemotherapy of several different cancers. However, several severe side effects are associated with using these chemotherapy drugs in cancer patients. Gold nanomaterials (AuNMs) are promising as drug carriers because of their small diameter, easy surface modifications, good biocompatibility, and strong cell penetration. This work aimed to determine the CTX and PT encapsulated with AuNMs against human glioma U87 cancer cells. The fabrication of the AuNMs achieved a negative surface charge, polydispersity index, and the mean sizes. The combined cytotoxic effect of CTX and PT bound to AuNMs was greater than that of either drug alone when tested on U87 cells. The half inhibitory concentration (IC50) values for free PT were 54.7 μg/mL (at 24 h) and 4.8 g μg/mL (at 72 h). Results acquired from the MTT assay show cell growth decreases time- and concentration-dependent AuNMs, free CTX, free PT, and AuNMs@CTX/PT-induced cytotoxicity and, ultimately, the cell death of U87 cells via apoptosis. The biochemical apoptosis staining techniques investigated the cells' morphological changes of the cells (acridine orange and ethidium bromide (AO-EB) and nuclear staining (DAPI) techniques). The AO-EB and nuclear staining results reveal that the NPs effectively killed cancer cells. Furthermore, the flow cytometry analysis examined the mode of cell death. Therefore, AuNMs@CTX/PT has excellent potential in the cancer therapy of different cancer cells.

Identification of disulfidptosis-related genes and immune infiltration in lower-grade glioma

Lower-grade glioma (LGG), a prevalent malignant tumor in the central nervous system, requires accurate prediction and treatment to prevent aggressive progression. We aimed to explore the role of disulfidptosis-related genes (DRGs) in LGG, a recently discovered form of programmed cell death characterized by abnormal disulfide accumulation. Leveraging public databases, we analyzed 532 LGG tumor tissues (The Cancer Genome Atlas), 1,157 normal samples (Genotype-Tissue Expression), and 21 LGG tumor samples with 8 paired normal samples (GSE16011). Our research uncovered intricate relationships between DRGs and crucial aspects of LGG, including gene expression, immune response, mutation, drug sensitivity, and functional enrichment. Notably, we identified significant heterogeneity among disulfidptosis sub-clusters and elucidated specific differential gene expression in LGG, with myeloid cell leukemia-1 (MCL1) as a key candidate. Machine learning techniques validated the relevance of MCL1, considering its expression patterns, prognostic value, diagnostic potential, and impact on immune infiltration. Our study offers opportunities and challenges to unravel potential mechanisms underlying LGG prognosis, paving the way for personalized cancer care and innovative immunotherapeutic strategies. By shedding light on DRGs, particularly MCL1, we enhance understanding and management of LGG.

PLEKHA4 is a novel prognostic biomarker that reshapes the tumor microenvironment in lower-grade glioma

Background

Lower-grade glioma (LGG) is a primary intracranial tumor that carry a high risk of malignant transformation and limited therapeutic options. Emerging evidence indicates that the tumor microenvironment (TME) is a superior predictor for tumor progression and therapy response. PLEKHA4 has been demonstrated to be a biomarker for LGG that correlate with immune infiltration. However, the fundamental mechanism by which PLEKHA4 contributes to LGG is still poorly understood.

Methods

Multiple bioinformatic tools, including Tumor Immune Estimation Resource (TIMER), Gene Expression Profiling Interactive Analysis (GEPIA2), Shiny Methylation Analysis Resource Tool (SMART), etc., were incorporated to analyze the PLEKHA4. ESTIMATE, ssGSEA, CIBERSORT, TIDE and CellMiner algorithms were employed to determine the association of PLEKHA4 with TME, immunotherapy response and drug sensitivities. Immunohistochemistry (IHC)-based tissue microarrays and M2 macrophage infiltration assay were conducted to verify their associations.

Results

PLEKHA4 expression was found to be dramatically upregulated and strongly associated with unfavorable overall survival (OS) and disease-specific survival (DSS) in LGG patients, as well as their poor clinicopathological characteristics. Cox regression analysis identified that PLEKHA4 was an independent prognostic factor. Methylation analysis revealed that DNA methylation correlates with PLEKHA4 expression and indicates a better outcome in LGG. Moreover, PLEKHA4 was remarkably correlated with immune responses and TME remodeling, as evidenced by its positive correlation with particular immune marker subsets and the putative infiltration of immune cells. Surprisingly, the proportion of M2 macrophages in TME was strikingly higher than others, inferring that PLEKHA4 may regulate the infiltration and polarization of M2 macrophages. Evidence provided by IHC-based tissue microarrays and M2 macrophage infiltration assay further validated our findings. Moreover, PLEKHA4 expression was found to be significantly correlated with chemokines, interleukins, and their receptors, further supporting the critical role of PLEKHA4 in reshaping the TME. Additionally, we found that PLEKHA4 expression was closely associated with drug sensitivities and immunotherapy responses, indicating that PLEKHA4 expression also had potential clinical significance in guiding immunotherapy and chemotherapy in LGG.

Conclusion

PLEKHA4 plays a pivotal role in reshaping the TME of LGG patients, and may serve as a potential predictor for LGG prognosis and therapy.

Genetically modified IL2 bone-marrow-derived myeloid cells reprogram the glioma immunosuppressive tumor microenvironment

Gliomas are one of the leading causes of cancer-related death in the adolescent and young adult (AYA) population. Two-thirds of AYA glioma patients are affected by low-grade gliomas (LGGs), but there are no specific treatments. Malignant progression is supported by the immunosuppressive stromal component of the tumor microenvironment (TME) exacerbated by M2 macrophages and a paucity of cytotoxic T cells. A single intravenous dose of engineered bone-marrow-derived myeloid cells that release interleukin-2 (GEMys-IL2) was used to treat mice with LGGs. Our results demonstrate that GEMys-IL2 crossed the blood-brain barrier, infiltrated the TME, and reprogrammed the immune cell composition and transcriptome. Moreover, GEMys-IL2 extended survival in an LGG immunocompetent mouse model. Here, we report the efficacy of an in vivo approach that demonstrates the potential for a cell-mediated innate immunotherapy designed to enhance the recruitment of activated effector T and natural killer cells within the glioma TME.

Pan-Cancer Identification of Prognostic-Associated Metabolic Pathways

Metabolic dysregulation has been reported involving in the clinical outcomes of multiple cancers. However, systematical identification of the impact of metabolic pathways on cancer prognosis is still lacking. Here, we performed a pan-cancer analysis of popular metabolic checkpoint genes and pathways with cancer prognosis by integrating information of clinical survival with gene expression and pathway activity in multiple cancer patients. By discarding the effects of age and sex, we revealed extensive and significant associations between the survival of cancer patients and the expression of metabolic checkpoint genes, as well as the activities of three primary metabolic pathways: amino acid metabolism, carbohydrate metabolism, lipid metabolism, and eight nonprimary metabolic pathways. Among multiple cancers, we found the survival of kidney renal clear cell carcinoma and low-grade glioma exhibit high metabolic dependence. Our work systematically assesses the impact of metabolic checkpoint genes and pathways on cancer prognosis, providing clues for further study of cancer diagnosis and therapy.

TRIB1 confers therapeutic resistance in GBM cells by activating the ERK and Akt pathways

GBM (Glioblastoma) is the most lethal CNS (Central nervous system) tumor in adults, which inevitably develops resistance to standard treatments leading to recurrence and mortality. TRIB1 is a serine/threonine pseudokinase which functions as a scaffold platform that initiates degradation of its substrates like C/EBPα through the ubiquitin proteasome system and also activates MEK and Akt signaling. We found that increased TRIB1 gene expression associated with worse overall survival of GBM patients across multiple cohorts. Importantly, overexpression of TRIB1 decreased RT/TMZ (radiation therapy/temozolomide)-induced apoptosis in patient derived GBM cell lines in vitro. TRIB1 directly bound to MEK and Akt and increased ERK and Akt phosphorylation/activation. We also found that TRIB1 protein expression was maximal during G2/M transition of cell cycle in GBM cells. Furthermore, TRIB1 bound directly to HDAC1 and p53. Importantly, mice bearing TRIB1 overexpressing tumors had worse overall survival. Collectively, these data suggest that TRIB1 induces resistance of GBM cells to RT/TMZ treatments by activating the cell proliferation and survival pathways thus providing an opportunity for developing new targeted therapeutics.

PSRC1 Regulated by DNA Methylation Is a Novel Target for LGG Immunotherapy

Proline and serine-rich coiled-coil 1 (PSRC1) has been reported to function as an oncogene in several cancers by regulating mitosis, while there are few reports on the role of PSRC1 in lower-grade glioma (LGG). Thus, this study collected 22 samples and 1126 samples from our institution and several databases, respectively, to explore the function of PSRC1 in LGG. First, the analysis of clinical characteristics showed that PSRC1 was always highly expressed in more malignant clinical characteristics of LGG, such as higher WHO grade, recurrence type, and IDH wild type. Second, the prognosis analysis revealed that the high expression of PSRC1 was an independent risk factor contributing to the shorter overall survival of LGG patients. Third, the analysis of DNA methylation showed that the expression of PSRC1 was associated with its 8 DNA methylation sites, overall negatively regulated by its DNA methylation level in LGG. Fourth, the analysis of immune correlation revealed that the expression of PSRC1 was positively correlated with the infiltration of 6 immune cells and the expression of 4 well-known immune checkpoints in LGG, respectively. Finally, co-expression analysis and KEGG analysis showed the 10 genes most related to PSRC1 and the signaling pathways involved by PSRC1 in LGG, respectively, such as MAPK signaling pathway and focal adhesion. In conclusion, this study identified the pathogenic role of PSRC1 in the pathological progression of LGG, expanding the molecular understanding of PSRC1, and provided a biomarker and potential immunotherapeutic target for the treatment of LGG.

DUSP10 is a novel immune-related biomarker connected with survival and cellular proliferation in lower-grade glioma

OBJECTIVE

The role of dual-specificity phosphatase 10 (DUSP10) has been investigated in several types of cancer. Nevertheless, the underlying function of DUSP10 in lower-grade glioma (LGG) remains undetermined.

METHODS

We entirely determined the expression features and prognostic significance of DUSP10 in numerous tumors by implementing a pan-cancer analysis. Adjacently, we thoroughly inspected the correlation between DUSP10 expression and clinicopathologic features, prognosis, biological processes, immune traits, gene variations, and treatment responses based on the expression features in LGG. In vitro studies were conducted to detect the underlying functions of DUSP10 in LGG.

RESULTS

Unconventionally boosted DUSP10 expression and higher DUSP10 expression correlated with poorer prognosis were discovered in various tumors, including LGG. Fortunately, DUSP10 expression was proven to be an independent prognostic indicator of patients with LGG. Additionally, DUSP10 expression was tightly linked to the immune modulation, gene mutations, and response to immunotherapy/chemotherapy in LGG patients. In vitro studies illustrated that the DUSP10 was abnormally increased and pivotal for cell proliferation in LGG.

CONCLUSIONS

Collectively, we verified that DUSP10 was an independent prognostic indicator and may become a novelty target of targeted therapy of LGG.

Focusing on scRNA-seq-Derived T Cell-Associated Genes to Identify Prognostic Signature and Immune Microenvironment Status in Low-Grade Glioma

Background

The clinical outcomes of low-grade glioma (LGG) are associated with T cell infiltration, but the specific contribution of heterogeneous T cell types remains unclear.

Method

To study the different functions of T cells in LGG, we mapped the single-cell RNA sequencing results of 10 LGG samples to obtain T cell marker genes. In addition, bulk RNA data of 975 LGG samples were collected for model construction. Algorithms such as TIMER, CIBERSORT, QUANTISEQ, MCPCOUTER, XCELL, and EPIC were used to depict the tumor microenvironment landscape. Subsequently, three immunotherapy cohorts, PRJEB23709, GSE78820, and IMvigor210, were used to explore the efficacy of immunotherapy.

Results

The Human Primary Cell Atlas was used as a reference dataset to identify each cell cluster; a total of 15 cell clusters were defined and cells in cluster 12 were defined as T cells. According to the distribution of T cell subsets (CD4+ T cell, CD8+ T cell, Naïve T cell, and Treg cell), we selected the differentially expressed genes. Among the CD4+ T cell subsets, we screened 3 T cell-related genes, and the rest were 28, 4, and 13, respectively. Subsequently, according to the T cell marker genes, we screened six genes for constructing the model, namely, RTN1, HERPUD1, MX1, SEC61G, HOPX, and CHI3L1. The ROC curve showed that the predictive ability of the prognostic model for 1, 3, and 5 years was 0.881, 0.817, and 0.749 in the TCGA cohort, respectively. In addition, we found that risk scores were positively correlated with immune infiltration and immune checkpoints. To this end, we obtained three immunotherapy cohorts to verify their predictive ability of immunotherapy effects and found that high-risk patients had better clinical effects of immunotherapy.

Conclusion

This single-cell RNA sequencing combined with bulk RNA sequencing may elucidate the composition of the tumor microenvironment and pave the way for the treatment of low-grade gliomas.

Supratotal Surgical Resection for Low-Grade Glioma: A Systematic Review

Low-grade gliomas (LGGs) are optimally treated with up-front maximal safe surgical resection, typically defined as maximizing the extent of tumor resection while minimizing neurologic risks of surgery. Supratotal resection of LGG may improve outcomes beyond gross total resection by removing tumor cells invading beyond the tumor border as defined on MRI. However, the evidence regarding supratotal resection of LGG, in terms of impact on clinical outcomes, such as overall survival and neurologic morbidities, remains unclear. Authors independently searched the PubMed, Medline, Ovid, CENTRAL (Cochrane Central Register of Controlled Trials), and Google Scholar databases for studies evaluating overall survival, time to progression, seizure outcomes, and postoperative neurologic and medical complications of supratotal resection/FLAIRectomy of WHO-defined LGGs. Papers in languages other than English, lacking full-text availability, evaluating supratotal resection of WHO-defined high-grade gliomas only, and nonhuman studies were excluded. After literature search, reference screening, and initial exclusions, 65 studies were screened for relevancy, of which 23 were evaluated via full-text review, and 10 were ultimately included in the final evidence review. Studies were evaluated for quality using the MINORS criteria. After data extraction, a total of 1301 LGG patients were included in the analysis, with 377 (29.0%) undergoing supratotal resection. The main measured outcomes were extent of resection, pre- and postoperative neurological deficits, seizure control, adjuvant treatment, neuropsychological outcomes, ability to return to work, progression-free survival, and overall survival. Overall, low- to moderate-quality evidence was supportive of aggressive, functional boundary-based resection of LGGs due to improvements in progression-free survival and seizure control. The published literature provides a moderate amount of low-quality evidence supporting supratotal surgical resection along functional boundaries for low-grade glioma. Among patients included in this analysis, the occurrence of postoperative neurological deficits was low, and nearly all patients recovered within 3 to 6 months after surgery. Notably, the surgical centers represented in this analysis have significant experience in glioma surgery in general, and supratotal resection specifically. In this setting, supratotal surgical resection along functional boundaries appears to be appropriate for both symptomatic and asymptomatic low-grade glioma patients. Larger clinical studies are needed to better define the role of supratotal resection in LGG.

Integrative Analysis of the Predictive Value of Perilipin Family on Clinical Significance, Prognosis and Immunotherapy of Glioma

Gliomas are common tumors of the central nervous system. The PLINs family is widely involved in the regulation of lipid metabolism and has been associated with the development and invasive metastasis of various malignancies. However, the biological role of the PLINs family in gliomas is still unclear. TIMER and UALCAN were used to assess PLINs mRNA expression in gliomas. “Survminer” and “Survival” were used to evaluate the connection between PLINs expression and glioma patients’ survival. cBioPortal was applied to assess PLINs’ genetic alterations in glioblastoma multiforme (GBM) and low-grade glioma (LGG). The correlation of PLINs expression with tumor immune cells was analyzed by TIMER. The expressions of PLIN1, PLIN4, and PLIN5 were decreased in GBM compared to normal tissues. However, PLIN2 and PLIN3 were significantly increased in GBM. Prognostic analysis showed that LGG patients with high PLIN1 expression had better overall survival (OS), and high expression of PLIN2/3/4/5 was associated with unfavorable OS. We further determined that the expression of PLINs members in gliomas was strongly related to tumor immune cells and immune checkpoint-associated genes. PLINS may be potential biomarkers for regulating the tumor microenvironment and predicting the efficacy of immunotherapy. In addition, we determined that PLIN1 may affect glioma patients’ therapeutic sensitivity to temozolomide. Our results demonstrated the biological significance and clinical values of PLINs in gliomas and provide a basis for future in-depth exploration of the specific mechanisms of each member of PLINs in gliomas.

Long non-coding RNA in glioma: novel genetic players in temozolomide resistance

Glioma is the most common primary malignant brain tumor in adults and accounts for approximately 80% of brain and central nervous system tumors. In 2021, the World Health Organization (WHO) published a new taxonomy for glioma based on its histological features and molecular alterations. Isocitrate dehydrogenase (IDH) catalyzes the decarboxylation of isocitrate, a critical metabolic reaction in energy generation in cells. Mutations in the IDH genes interrupt cell differentiation and serve as molecular biomarkers that can be used to classify gliomas. For example, the mutant IDH is widely detected in low-grade gliomas, whereas the wild type is in high-grade ones, including glioblastomas. Long non-coding RNAs (lncRNAs) are epigenetically involved in gene expression and contribute to glioma development. To investigate the potential use of lncRNAs as biomarkers, we examined lncRNA dysregulation dependent on the IDH mutation status. We found that several lncRNAs, namely, AL606760.2, H19, MALAT1, PVT1 and SBF2-AS1 may function as glioma risk factors, whereas AC068643.1, AC079228.1, DGCR5, FAM13A-AS1, HAR1A and WDFY3-AS2 may have protective effects. Notably, H19, MALAT1, PVT1, and SBF2-AS1 have been associated with temozolomide resistance in glioma patients. This review study suggests that targeting glioma-associated lncRNAs might aid the treatment of glioma.

Identification of an energy metabolism-related six-gene signature for distinguishing and forecasting the prognosis of low-grade gliomas

Background

Low-grade gliomas (LGG) account for 20-25% of all gliomas. In this study, we assessed whether metabolic status was correlated with clinical outcomes in LGG patients using data from The Cancer Genome Atlas (TCGA).

Methods

LGG patient data were collected from TCGA, and the Molecular Signature Database was used to extract gene sets related to energy metabolism. After performing a consensus-clustering algorithm, the LGG patients were divided into four clusters. We then compared the tumor prognosis, function, immune cell infiltration, checkpoint proteins, chemo-resistance, and cancer stem cells (CSC) between the two groups with the greatest prognostic difference. Using least absolute shrinkage and selection operator (LASSO) analysis, an energy metabolism-related signature was further developed.

Results

Energy metabolism-related signatures were applied to identify four clusters (C1, C2, C3, and C4) using a consensus-clustering algorithm. C1 LGG patients were more related to the synapse and had higher CSC scores, more chemo-resistance, and a better prognosis. C4 LGG was observed to have more immune-related pathways and better immunity. We then identified six energy metabolism-related genes (PYGL, HS3ST3B, NNMT, FMOD, CHST6, and B3GNT7) that can accurately predict LGG prognosis not only as a whole but also based on the independent predictions of each of these six genes.

Conclusions

The energy metabolism-related subtypes of LGG were identified, which were strongly related to the immune microenvironment, immune checkpoint proteins, CSCs, chemo-resistance, prognosis, and LGG advancement. A signature of genes involved in energy metabolism could help to distinguish and predict the prognosis of LGG patients, and a promising method to discover patients that may benefit from LGG therapy.

Signaling pathways in brain tumors and therapeutic interventions

Brain tumors, although rare, contribute to distinct mortality and morbidity at all ages. Although there are few therapeutic options for brain tumors, enhanced biological understanding and unexampled innovations in targeted therapies and immunotherapies have considerably improved patients' prognoses. Nonetheless, the reduced response rates and unavoidable drug resistance of currently available treatment approaches have become a barrier to further improvement in brain tumor (glioma, meningioma, CNS germ cell tumors, and CNS lymphoma) treatment. Previous literature data revealed that several different signaling pathways are dysregulated in brain tumor. Importantly, a better understanding of targeting signaling pathways that influences malignant behavior of brain tumor cells might open the way for the development of novel targeted therapies. Thus, there is an urgent need for a more comprehensive understanding of the pathogenesis of these brain tumors, which might result in greater progress in therapeutic approaches. This paper began with a brief description of the epidemiology, incidence, risk factors, as well as survival of brain tumors. Next, the major signaling pathways underlying these brain tumors' pathogenesis and current progress in therapies, including clinical trials, targeted therapies, immunotherapies, and system therapies, have been systemically reviewed and discussed. Finally, future perspective and challenges of development of novel therapeutic strategies in brain tumor were emphasized.

Epidemiology and risk stratification of low-grade gliomas in the United States, 2004-2019: A competing-risk regression model for survival analysis

Background

Understanding the epidemiology and prognostic factors of low-grade gliomas (LGGs) can help estimate the public health impact and optimize risk stratification and treatment strategies.

Methods

3 337 patients diagnosed with LGGs were collected from the Surveillance, Epidemiology, and End Results (SEER) dataset, 2004-2019. The incidence trends of LGGs were analyzed by patient demographics (sex, age, race, and ethnicity). In addition, a competing risk regression model was used to explore the prognostic factors of LGGs by patient demographics, tumor characteristics (histological subtypes, invasiveness, and size), treatment modality, and molecular markers (IDH mutation and 1p/19q codeletion).

Results

LGGs occurred more frequently in male, non-Hispanic, and White populations. The incidence rate of mixed gliomas was stable from 2004 to 2013 and decreased dramatically to nearly zero until 2019. The risk of death increased 1.99 times for every 20-year increase in patient age, and 60 years is a predictive cut-off age for risk stratification of LGGs. Male patients showed poorer LGG-specific survival. Among the different subtypes, astrocytoma has the worst prognosis, followed by mixed glioma and oligodendroglioma. Tumors with larger size (≥5 cm) and invasive behavior tended to have poorer survival. Patients who underwent gross total resection had better survival rates than those who underwent subtotal resection. Among the different treatment modalities, surgery alone had the best survival, followed by surgery + radiotherapy + chemotherapy, but chemotherapy alone had a higher death risk than no treatment. Furthermore, age, invasiveness, and molecular markers were the most robust prognostic factors.

Conclusion

This study reviewed the incidence trends and identified several prognostic factors that help clinicians identify high-risk patients and determine the need for postoperative treatment according to guidelines.

DNALI1 is a prognosis-related biomarker and correlates with immune infiltrates in low grade glioma

BACKGROUND

Dynein axonemal light intermediate chain 1 (DNALI1) is a component of axonemal dyneins and its role in cancer progression is not known.

OBJECTIVE

The influence of DNALI1 expression on the prognosis of low-grade gliomas (LGG) and the possible mechanisms of DNALI1 in promoting the progression of LGG was investigated by applying multiple bioinformatics analyses using datasets from TCGA, GTEx, CPTAC, and CGGA.

METHODS

The expression of DNALI1 in different tumor tissues including LGG was investigated. GO functional annotation, KEGG pathway analysis, and GSEA enrichment analysis were performed. The correlation between DNALI1 and prognosis, tumor microenvironment (TME) and immune checkpoints in LGG were assessed.

RESULTS

DNALI1 is mainly expressed in malignant cells in the TME of LGG and positively correlated with the development of LGG. DNALI1 expression is negatively correlated with isocitrate dehydrogenase (IDH) mutations and 1p/19q co-deletion. High DNALI1 expression is associated with poor prognosis in LGG. DNALI1 may promote LGG progression through multiple immune-related pathways. The expression of DNALI1 is positively correlated with the infiltration of certain types of immune cells and the expression of some immune checkpoints.

CONCLUSIONS

DNALI1 is a potential prognostic marker for LGG, and high expression of DNALI1 may play an important role in maintaining the immunosuppressive microenvironment of LGG.

Pan-Cancer Study of the Prognosistic Value of Selenium Phosphate Synthase 1

Objective: This study sought to determine the mean prognostic usefulness of seleniumphosphate synthase (SEPHS1) by investigating its expression in 33 human malignancies and its relationship to tumor immunity.Methods: The expression of selenophosphate synthase 1 (SEPHS1) in 33 human malignant tumors was examined using the Genotype-Tissue Expression (GTEx), Cancer Genome Atlas (TCGA), and TIMER databases. Furthermore, the TCGA cohort was used to investigate relationships between SEPHS1 and immunological checkpoint genes (ICGs), tumor mutation burden (TMB), microsatellite instability (MSI), and DNA mismatch repair genes (MMRs). To establish independent risk factors and calculate survival probabilities for liver hepatocellular carcinoma (LIHC) and brain lower-grade glioma (LGG), Cox regression models and Kaplan-Meier curves were utilized. Eventually, the Genomics of Cancer Drug Sensitivity (GDSC) database was used to evaluate the drug sensitivity in LGG and LIHC patients with high SEPHS1 expression.Results: Overall, in numerous tumor tissues, SEPHS1 was highly expressed, and it significantly linked with the prognosis of LGG, ACC, and LIHC (P < .05). Furthermore, in numerous cancers, SEPHS1 expression was linked to tumor-infiltrating immune cells (TIICs), TMB, MSI, and MMRs. According to univariate and multivariate Cox analyses, SEPHS1 expression was significant for patients with LGG and LIHC.Conclusion: High SEPHS1 expression has a better prognosis for LGG, while low SEPHS1 expression has a better prognosis for LIHC. Chemotherapy was advised for LGG patients, particularly for those with high SEPHS1 expression because it can predict how responsive patients will be to 5-Fluorouracil and Temozolomide. This interaction between SEPHS1 and chemoradiotherapy has a positive clinical impact and may be used as evidence for chemotherapy for LGG and LIHC patients.

robustica: customizable robust independent component analysis

BACKGROUND

Independent Component Analysis (ICA) allows the dissection of omic datasets into modules that help to interpret global molecular signatures. The inherent randomness of this algorithm can be overcome by clustering many iterations of ICA together to obtain robust components. Existing algorithms for robust ICA are dependent on the choice of clustering method and on computing a potentially biased and large Pearson distance matrix.

RESULTS

We present robustica, a Python-based package to compute robust independent components with a fully customizable clustering algorithm and distance metric. Here, we exploited its customizability to revisit and optimize robust ICA systematically. Of the 6 popular clustering algorithms considered, DBSCAN performed the best at clustering independent components across ICA iterations. To enable using Euclidean distances, we created a subroutine that infers and corrects the components' signs across ICA iterations. Our subroutine increased the resolution, robustness, and computational efficiency of the algorithm. Finally, we show the applicability of robustica by dissecting over 500 tumor samples from low-grade glioma (LGG) patients, where we define two new gene expression modules with key modulators of tumor progression upon IDH1 and TP53 mutagenesis.

CONCLUSION

robustica brings precise, efficient, and customizable robust ICA into the Python toolbox. Through its customizability, we explored how different clustering algorithms and distance metrics can further optimize robust ICA. Then, we showcased how robustica can be used to discover gene modules associated with combinations of features of biological interest. Taken together, given the broad applicability of ICA for omic data analysis, we envision robustica will facilitate the seamless computation and integration of robust independent components in large pipelines.

Magnetic Resonance-Guided Laser Interstitial Thermal Therapy for Management of Low-Grade Gliomas and Radiation Necrosis: A Single-Institution Case Series

BACKGROUND

Laser interstitial thermal therapy (LITT) has emerged as a minimally invasive treatment modality for ablation of low-grade glioma (LGG) and radiation necrosis (RN).

OBJECTIVE

To evaluate the efficacy, safety, and survival outcomes of patients with radiographically presumed recurrent or newly diagnosed LGG and RN treated with LITT.

METHODS

The neuro-oncological database of a quaternary center was reviewed for all patients who underwent LITT for management of LGG between 1 January 2013 and 31 December 2020. Clinical data including demographics, lesion characteristics, and clinical and radiographic outcomes were collected. Kaplan-Meier analyses comprised overall survival (OS) and progression-free survival (PFS).

RESULTS

Nine patients (7 men, 2 women; mean [SD] age 50 [16] years) were included. Patients underwent LITT at a mean (SD) of 11.6 (8.5) years after diagnosis. Two (22%) patients had new lesions on radiographic imaging without prior treatment. In the other 7 patients, all (78%) had surgical resection, 6 (67%) had intensity-modulated radiation therapy and chemotherapy, respectively, and 4 (44%) had stereotactic radiosurgery. Two (22%) patients had lesions that were wild-type IDH1 status. Volumetric assessment of preoperative T1-weighted contrast-enhancing and T2-weighted fluid-attenuated inversion recovery (FLAIR) sequences yielded mean (SD) lesion volumes of 4.1 (6.5) cm³ and 26.7 (27.9) cm³, respectively. Three (33%) patients had evidence of radiographic progression after LITT. The pooled median (IQR) PFS for the cohort was 52 (56) months, median (IQR) OS after diagnosis was 183 (72) months, and median (IQR) OS after LITT was 52 (60) months. At the time of the study, 2 (22%) patients were deceased.

CONCLUSIONS

LITT is a safe and effective treatment option for management of LGG and RN, however, there may be increased risk of permanent complications with treatment of deep-seated subcortical lesions.

Cuproptosis-related gene signature stratifies lower-grade glioma patients and predicts immune characteristics

Cuproptosis is the most recently discovered type of regulated cell death and is mediated by copper ions. Studies show that cuproptosis plays a significant role in cancer development and progression. Lower-grade gliomas (LGGs) are slow-growing brain tumors. The majority of LGGs progress to high-grade glioma, which makes it difficult to predict the prognosis. However, the prognostic value of cuproptosis-related genes (CRGs) in LGG needs to be further explored. mRNA expression profiles and clinical data of LGG patients were collected from public sources for this study. Univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) Cox regression model were used to build a multigene signature that could divide patients into different risk groups. The differences in clinical pathological characteristics, immune infiltration characteristics, and mutation status were evaluated in risk subgroups. In addition, drug sensitivity and immune checkpoint scores were estimated in risk subgroups to provide LGG patients with precision medication. We found that all CRGs were differentially expressed in LGG and normal tissues. Patients were divided into high- and low-risk groups based on the risk score of the CRG signature. Patients in the high-risk group had a considerably lower overall survival rate than those in the low-risk group. According to functional analysis, pathways related to the immune system were enriched, and the immune state differed across the two risk groups. Immune characteristic analysis showed that the immune cell proportion and immune scores were different in the different groups. High-risk group was characterized by low sensitivity to chemotherapy but high sensitivity to immune checkpoint inhibitors. The current study revealed that the novel CRG signature was related to the prognosis, clinicopathological features, immune characteristics, and treatment perference of LGG.

A novel model based on necroptosis-related genes for predicting immune status and prognosis in glioma

Background

Glioma is a highly aggressive brain cancer with a poor prognosis. Necroptosis is a form of programmed cell death occurring during tumor development and in immune microenvironments. The prognostic value of necroptosis in glioma is unclear. This study aimed to develop a prognostic glioma model based on necroptosis.

Methods

A necroptosis-related risk model was constructed by Cox regression analysis based on The Cancer Genome Atlas (TCGA) training set, validated in two Chinese Glioma Genome Atlas (CGGA) validation sets. We explored the differences in immune infiltration and immune checkpoint genes between low and high risk groups and constructed a nomogram. Moreover, we compiled a third validation cohort including 43 glioma patients. The expression of necroptosis-related genes was verified in matched tissues using immunochemical staining in the third cohort, and we analyzed their relationship to clinicopathological features.

Results

Three necroptosis-related differentially expressed genes (EZH2, LEF1, and CASP1) were selected to construct the prognostic model. Glioma patients with a high risk score in the TCGA and CGGA cohorts had significantly shorter overall survival. The necroptosis-related risk model and nomogram exhibited good predictive performance in the TCGA training set and the CGGA validation sets. Furthermore, patients in the high risk group had higher immune infiltration status and higher expression of immune checkpoint genes, which was positively correlated with poorer outcomes. In the third validation cohort, the expression levels of the three proteins encoded by EZH2, LEF1, and CASP1 in glioma tissues were significantly higher than those from paracancerous tissues. They were also closely associated with disease severity and prognosis.

Conclusions

Our necroptosis-related risk model can be used to predict the prognosis of glioma patients and improve prognostic accuracy, which may provide potential therapeutic targets and a theoretical basis for treatment.

Prognostic Factors of Low-Grade Gliomas in Adults

Adult low-grade gliomas are a rare and aggressive pathology of the central nervous system. Some of their characteristics contribute to the patient's life expectancy and to their management. This study aimed to characterize and identify the main prognostic factors of low-grade gliomas. The six-year retrospective study statistically analyzed the demographic, imaging, and morphogenetic characteristics of the patient group through appropriate parameters. Immunohistochemical tests were performed: IDH1, Ki-67, p53, and Nestin, as well as FISH tests on the CDKN2A gene and 1p/19q codeletion. The pathology was prevalent in females, with patients having an average age of 56.31 years. The average tumor volume was 41.61 cm³, producing a midline shift with an average of 7.5 mm. Its displacement had a negative impact on survival. The presence of a residual tumor resulted in decreased survival and is an independent risk factor for mortality. Positivity for p53 identified a low survival rate. CDKN2A mutations were an independent risk factor for mortality. We identified that a negative prognosis is influenced by the association of epilepsy with headache, tumor volume, and immunoreactivity to IDH1 and p53. Independent factors associated with mortality were midline shift, presence of tumor residue, and CDKN2A gene deletions and amplifications.

T2-Fluid-Attenuated Inversion Recovery (FLAIR) Mismatch as a Novel Specific MRI Marker for Adult Low-Grade Glioma (LGG): A Case Report

Astrocytic tumors are primary central nervous system tumors. They are the most common tumors arising from glial cells. In the new WHO classification 2021, adult-type diffuse astrocytic gliomas subdivide into isocitrate dehydrogenase (IDH)-mutant astrocytoma, IDH-mutant and 1p/19q-codeleted oligodendroglioma, and IDH-wildtype glioblastoma. The T2-fluid-attenuated inversion recovery (FLAIR) mismatch sign describes the MRI appearance of IDH-mutant astrocytoma, it is considered a highly specific radiogenomic signature for diffuse astrocytoma, as opposed to other lower-grade. MRI is the first and most accurate diagnostic tool for low-grade gliomas (LGGs). It is particularly helpful in distinguishing a diffuse astrocytoma from an oligodendroglioma that will not demonstrate T2-FLAIR mismatch. The tumor displays a hyperintense signal on T2-weighted images and a hypointense signal on T2-weighted FLAIR images, which distinguishes it from other types of diffuse gliomas. We report a case of a 29-year-old female patient who was diagnosed with IDH-mutant 1p/19q-non-codeleted diffuse astrocytoma based on MRI T-2 FLAIR mismatch sign, which is confirmed by the molecular analysis in the pathology lab. Our aim of this report is to confirm the power of the MRI findings in the diagnosis of glioma genotypes and to assess neurosurgeons in the preoperative surgical planning.

Machine learning identification of cuproptosis and necroptosis-associated molecular subtypes to aid in prognosis assessment and immunotherapy response prediction in low-grade glioma

Both cuproptosis and necroptosis are typical cell death processes that serve essential regulatory roles in the onset and progression of malignancies, including low-grade glioma (LGG). Nonetheless, there remains a paucity of research on cuproptosis and necroptosis-related gene (CNRG) prognostic signature in patients with LGG. We acquired patient data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) and captured CNRGs from the well-recognized literature. Firstly, we comprehensively summarized the pan-cancer landscape of CNRGs from the perspective of expression traits, prognostic values, mutation profiles, and pathway regulation. Then, we devised a technique for predicting the clinical efficacy of immunotherapy for LGG patients. Non-negative matrix factorization (NMF) defined by CNRGs with prognostic values was performed to generate molecular subtypes (i.e., C1 and C2). C1 subtype is characterized by poor prognosis in terms of disease-specific survival (DSS), progression-free survival (PFS), and overall survival (OS), more patients with G3 and tumour recurrence, high abundance of immunocyte infiltration, high expression of immune checkpoints, and poor response to immunotherapy. LASSO-SVM-random Forest analysis was performed to aid in developing a novel and robust CNRG-based prognostic signature. LGG patients in the TCGA and GEO databases were categorized into the training and test cohorts, respectively. A five-gene signature, including SQSTM1, ZBP1, PLK1, CFLAR, and FADD, for predicting OS of LGG patients was constructed and its predictive reliability was confirmed in both training and test cohorts. In both the training and the test datasets (cohorts), higher risk scores were linked to a lower OS rate. The time-dependent ROC curve proved that the risk score had outstanding prediction efficiency for LGG patients in the training and test cohorts. Univariate and multivariate Cox regression analyses showed the CNRG-based prognostic signature independently functioned as a risk factor for OS in LGG patients. Furthermore, we developed a highly reliable nomogram to facilitate the clinical practice of the CNRG-based prognostic signature (AUC > 0.9). Collectively, our results gave a promising understanding of cuproptosis and necroptosis in LGG, as well as a tailored prediction tool for prognosis and immunotherapeutic responses in patients.

Glycosylation modification patterns reveal distinct tumor metabolism and immune microenvironment landscape in lower-grade gliomas

Glycosylation alterations, a key driver throughout tumorigenesis and tumor progression, could regulate the microenvironment and immune response as well as lead to harmful metabolism and cell signaling. In this study, we first comprehensively evaluated the glycosylation modification patterns of LGGs based on glycosyltransferase family genes and systematically integrated these modification patterns with tumor metabolism and immune microenvironment characteristics. Glycosylation score was also developed to quantify glycosylation modification patterns of individuals. As a result, two glycosylation modification patterns were identified, with distinct prognosis, metabolism, and immune microenvironment features. The glycosylation subtype A and cluster A were characterized by higher carbohydrates and amino acid metabolism activity, higher levels of infiltrating cells, and poor prognosis, whereas an opposite modification pattern was observed in glycosylation subtype B and cluster B. In addition, a high glycosylation score is closer to a microenvironment characterized by chronic inflammation, immunosuppression, and tumor promotion. Following analysis and validation, the glycosylation score was a reliable and independent prognostic index. More importantly, the glycosylation score influenced the response to immunotherapy, chemotherapy, or targeted therapy, which provided a novel insight into promoting personalized therapy in the future and may contribute to developing novel therapeutic drugs or exploring promising drug combination therapy strategies.

Identification of Gender- and Subtype-Specific Gene Expression Associated with Patient Survival in Low-Grade and Anaplastic Glioma in Connection with Steroid Signaling

Simple Summary

Gliomas are primary brain tumors that are initially slow growing but progress to be more aggressive and, ultimately, fatal within a few years. They are more common in men than in women, suggesting a protective role for female hormones. By analyzing patient data collected in the public TGCA-LGG database, we have demonstrated a link between the expression level of key steroid biosynthesis enzymes or hormone receptors with patient survival, in ways that are dependent on gender and molecular subtype. We also determined the genes which expression associated with these actors of steroid signaling and the functions they perform, to decipher the mechanisms underlying gender-dependent differences. Together, these results establish, for the first time, the involvement of hormones in low-grade and anaplastic gliomas and provide clues for refining their classification and, thus, facilitating more personalized management of patients.

Abstract

Low-grade gliomas are rare primary brain tumors, which fatally evolve to anaplastic gliomas. The current treatment combines surgery, chemotherapy, and radiotherapy. If gender differences in the natural history of the disease were widely described, their underlying mechanisms remain to be determined for the identification of reliable markers of disease progression. We mined the transcriptomic and clinical data from the TCGA-LGG and CGGA databases to identify male-over-female differentially expressed genes and selected those associated with patient survival using univariate analysis, depending on molecular characteristics (IDH wild-type/mutated; 1p/19q codeleted/not) and grade. Then, the link between the expression levels (low or high) of the steroid biosynthesis enzyme or receptors of interest and survival was studied using the log-rank test. Finally, a functional analysis of gender-specific correlated genes was performed. HOX-related genes appeared to be differentially expressed between males and females in both grades, suggesting that a glioma could originate in perturbation of developmental signals. Moreover, aromatase, androgen, and estrogen receptor expressions were associated with patient survival and were mainly related to angiogenesis or immune response. Therefore, consideration of the tight control of steroid hormone production and signaling seems crucial for the understanding of glioma pathogenesis and emergence of future targeted therapies.

Machine learning-based identification of tumor-infiltrating immune cell-associated lncRNAs for improving outcomes and immunotherapy responses in patients with low-grade glioma

Rationale: Accumulating evidence demonstrated that long noncoding RNAs (lncRNAs) involved in the regulation of the immune system and displayed a cell-type-specific pattern in immune cell subsets. Given the vital role of tumor-infiltrating lymphocytes in effective immunotherapy, we explored the tumor-infiltrating immune cell-associated lncRNA (TIIClncRNA) in low-grade glioma (LGG), which has never been uncovered yet.

Methods: This study utilized a novel computational framework and 10 machine learning algorithms (101 combinations) to screen out TIIClncRNAs by integratively analyzing the sequencing data of purified immune cells, LGG cell lines, and bulk LGG tissues.

Results: The established TIIClnc signature based on the 16 most potent TIIClncRNAs could predict outcomes in public datasets and the Xiangya in-house dataset with decent efficiency and showed better performance when compared with 95 published signatures. The TIIClnc signature was strongly correlated to immune characteristics, including microsatellite instability, tumor mutation burden, and interferon γ, and exhibited a more active immunologic process. Furthermore, the TIIClnc signature predicted superior immunotherapy response in multiple datasets across cancer types. Notably, the positive correlation between the TIIClnc signature and CD8, PD-1, and PD-L1 was verified in the Xiangya in-house dataset.

Conclusions: The TIIClnc signature enabled a more precise selection of the LGG population who were potential beneficiaries of immunotherapy.

Current Considerations in the Treatment of Grade 3 Gliomas

OPINION STATEMENT

Treatment recommendations for grade 3 gliomas are guided by their histopathologic and molecular phenotype. In the 2021 WHO classification, these tumors are categorized into two types, grade 3 IDH mutant (IDHmt), 1p/19q codeleted oligodendroglioma and IDH mutant astrocytoma. Treatment consists of maximal safe surgery, followed by radiation therapy (RT) and alkylating agent-based chemotherapy. Based on the updated CATNON result, RT followed by temozolomide improves outcome in patients with non-codeleted grade 3 IDHmt astrocytoma. In patients with IDHmt, codeleted oligodendroglioma, the addition of procarbazine, CCNU, and vincristine regimen is the recommended treatment, based on large randomized controlled trials. These current treatments prolong the overall survival to up to 10 years in patients with grade 3 IDHmt astrocytoma and 14 years in grade 3 IDHmt codeleted oligodendroglioma. Treatment options at recurrence include re-resection, re-irradiation, and other cytotoxic chemotherapy; however, these are of limited benefit. Novel agents targeting IDH mutation and its metabolic effects are currently under investigation to improve the outcome of these patients.

MGMT and Whole-Genome DNA Methylation Impacts on Diagnosis, Prognosis and Therapy of Glioblastoma Multiforme

Epigenetic changes in DNA methylation contribute to the development of many diseases, including cancer. In glioblastoma multiforme, the most prevalent primary brain cancer and an incurable tumor with a median survival time of 15 months, a single epigenetic modification, the methylation of the O⁶-Methylguanine-DNA Methyltransferase (MGMT) gene, is a valid biomarker for predicting response to therapy with alkylating agents and also, independently, prognosis. More recently, the progress from single gene to whole-genome analysis of DNA methylation has allowed a better subclassification of glioblastomas. Here, we review the clinically relevant information that can be obtained by studying MGMT gene and whole-genome DNA methylation changes in glioblastomas, also highlighting benefits, including those of liquid biopsy, and pitfalls of the different detection methods. Finally, we discuss how changes in DNA methylation, especially in glioblastomas bearing mutations in the Isocitrate Dehydrogenase (IDH) 1 and 2 genes, can be exploited as targets for tailoring therapy.

Identification and Validation of a Gene Signature for Lower-Grade Gliomas Based on Pyroptosis-Related Genes to Predict Survival and Response to Immune Checkpoint Inhibitors

Pyroptosis plays a critical role in the immune response to immune checkpoint inhibitors (ICIs) by mediating the tumor immune microenvironment. However, the impact of pyroptosis-related biomarkers on the prognosis and efficacy of ICIs in patients with lower-grade gliomas (LGGs) is unclear. An unsupervised clustering analysis identified pyroptosis-related subtypes (PRSs) based on the expression profile of 47 pyroptosis-related genes in The Cancer Genome Atlas-LGG cohort. A PRS gene signature was established using univariate Cox regression, random survival forest, least absolute shrinkage and selection operator, and stepwise multivariable Cox regression analyses. The predictive power of this signature was validated in the Chinese Glioma Genome Atlas database. We also investigated the differences between high- and low-risk groups in terms of the tumor immune microenvironment, tumor mutation, and response to target therapy and ICIs. The PRS gene signature comprised eight PRS genes, which independently predicted the prognosis of LGG patients. High-risk patients had a worse overall survival than did the low-risk patients. The high-risk group also displayed a higher proportion of M1 macrophages and CD8⁺ T cells and higher immune scores, tumor mutational burden, immunophenoscore, IMmuno-PREdictive Score, MHC I association immune score, and T cell-inflamed gene expression profile scores, but lower suppressor cells scores, and were more suitable candidates for ICI treatment. Higher risk scores were more frequent in patients who responded to ICIs using data from the ImmuCellAI website. The presently established PRS gene signature can be validated in melanoma patients treated with real ICI treatment. This signature is valuable in predicting prognosis and ICI treatment of LGG patients, pending further prospective verification.

Abundant expression of ferroptosis-related SAT1 is related to unfavorable outcome and immune cell infiltration in low-grade glioma

Background

Low-grade glioma (LGG) is susceptible to ferroptosis, which is involved in TMZ resistance. Ferroptosis induction can enhance the sensitivity to TMZ and synergistically kill glioma cells. T cell-promoted tumor ferroptosis is a vital anti-tumor mechanism of immune checkpoint inhibitors. The SAT1 activation is closely related to ferroptosis upon ROS induction due to the upregulation of arachidonate 15-lipoxygenase (ALOX15) expression.

Methods

The expression of SAT1 in pan-cancer and corresponding normal tissue from the TCGA data portal was primarily explored. The landscape of SAT1 and immune cell infiltration and their corresponding gene marker sets in different tissues were further explored. Additionally, we evaluated the relationships between SAT1 and the clinicopathologic parameters of LGG, and the disease-specific survival (DSS), progression-free interval (PFI), and overall survival (OS) were also assessed using KM survival curves and multivariate analysis in LGG. Meanwhile, the Gene Set Enrichment Analysis (GSEA) was also implemented to determine the potential effect of the SAT1 gene in LGG. Furthermore, the predictive power of SAT1 was validated using an independent LGG cohort from the Chinese Glioma Genome Atlas (CGGA) data.

Results

In general, the expression of SAT1 is different between most tumors and their adjacent normal tissues. The results demonstrated that SAT1 expression is positively associated with TMB in LGG, BRCA, and THYM. The results displayed that the expression level of SAT1 is obviously correlated with the level of infiltrating macrophages and CD8 + T cells, and the levels of most immune gene sets were associated with the SAT1 expression in LGG. Interestingly, univariate and multivariate models significantly indicated that the OS and PFI of patients with LGG with high SAT1 levels were poorer than those with low SAT1 expression in the TCGA LGG cohort. GSEA showed that SAT1 was involved in immune regulation and multiple signaling pathways. Finally, our analysis demonstrated that SAT1 was closely associated with IDH mutation, 1p19q codeletion, chemoradiotherapy resistance and disease recurrence.

Conclusions

Abundant expression of SAT1 was related to poor disease prognosis and abundant immune cell infiltration in LGG.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09313-w.

Duchenne muscular dystrophy gene expression is an independent prognostic marker for IDH mutant low-grade glioma

Alterations in the expression of the Duchenne muscular dystrophy (DMD) gene have been associated with the development, progression and survival outcomes of numerous cancers including tumours of the central nervous system. We undertook a detailed bioinformatic analysis of low-grade glioma (LGG) bulk RNAseq data to characterise the association between DMD expression and LGG survival outcomes. High DMD expression was significantly associated with poor survival in LGG with a difference in median overall survival between high and low DMD groups of over 7 years (P = < 0.0001). In a multivariate model, DMD expression remained significant (P = 0.02) and was an independent prognostic marker for LGG. The effect of DMD expression on overall survival was only apparent in isocitrate dehydrogenase (IDH) mutant cases where non-1p/19q co-deleted LGG patients could be further stratified into high/low DMD groups. Patients in the high DMD group had a median overall survival time almost halve that of the low DMD group. The expression of the individual DMD gene products Dp71, Dp71ab and Dp427m were also significantly associated with overall survival in LGG which have differential biological effects relevant to the pathogenesis of LGG. Differential gene expression and pathway analysis identifies dysregulated biological processes relating to ribosome biogenesis, synaptic signalling, neurodevelopment, morphogenesis and immune pathways. Genes spanning almost the entirety of chromosome 1p are upregulated in patients with high overall DMD, Dp71 and Dp427m expression which worsens survival outcomes for these patients. We confirmed dystrophin protein is variably expressed in LGG tumour tissue by immunohistochemistry and, overall, demonstrate that DMD expression has potential utility as an independent prognostic marker which can further stratify IDH mutant LGG to identify those at risk of poor survival. This knowledge may improve risk stratification and management of LGG.

RFC2: a prognosis biomarker correlated with the immune signature in diffuse lower-grade gliomas

Diffuse lower-grade gliomas (LGG) represent the highly heterogeneous and infiltrative neoplasms in the central nervous system (CNS). Replication factor C 2 (RFC2) is a subunit of the RFC complex that modulates DNA replication and repair. However, the prognosis value of RFC2 and its association with the immune signature of tumor microenvironment (TME) in LGG remains unknown. Based on Oncomine, TCGA, GTEx, TIMER, GEPIA, and HPA databases, we evaluated RFC2 expression levels and its clinical prognostic value in LGG and other cancers. Then we analyzed the correlations between RFC2 expression and tumor mutation burden (TMB), tumor microsatellite instability (MSI), and mismatch repair (MMR) genes across cancers. And CIBERSORT and ESTIMATE algorithms were conducted to estimate the association of RFC2 with immune cell infiltration of LGG. Additionally, we performed the functional enrichment analyses of RFC2 in LGG. Then functional experiments were employed to further validate the oncogenic role of RFC2 in LGG. Our results showed that RFC2 was widely highly expressed in most types of cancer. And its expression was closely related to the clinicopathological features and prognosis in LGG and other cancer types. RFC2 levels were also correlated with TMB and MSI across various cancers. Furthermore, RFC2 was positively associated with the infiltration levels of immune cells and immune checkpoint genes in LGG. Additionally, in vitro experiments revealed that RFC2 played an oncogenic role in LGG progression. In conclusion, our findings revealed that RFC2 could serve as a reliable biomarker to predict the prognosis and immune signature for LGG.

Functions of RNF Family in the Tumor Microenvironment and Drugs Prediction in Grade II/III Gliomas

Increasing evidence has demonstrated that RING finger (RNF) proteins played a vital role in cellular and physiological processes and various diseases. However, the function of RNF proteins in low-grade glioma (LGG) remains unknown. In this study, 138 RNF family members revealed their role in LGG. The TCGA database was used as the training cohort; two CGGA databases and GSE108474 were selected as external validation cohorts. Patients were grouped into cluster 1 and cluster 2, both in the training and validation cohorts, using consensus clustering analysis. The prognosis of patients in cluster 1 is significantly better than that in cluster 2. Meanwhile, biofunction prediction was further introduced to explore the potential mechanisms that led to differences in survival outcomes. Patients in Cluster 2 showed more complicated immunocytes infiltration and highly immunosuppressive features than cluster 1. Enrichment pathways such as negative regulation of mast cell activation, DNA replication, mismatch repair, Th17 cell differentiation, antigen processing and presentation, dendritic cell antigen processing and presentation, dendritic cell differentiation were also enriched in cluster 2 patients. For the last, the main contributors were distinguished by employing a machine learning algorithm. A lot of targeted and small molecule drugs that are sensitive to patients in cluster 2 were predicted. Importantly, we discovered TRIM8, DTX2, and TRAF5 as the most vital contributors from the RNF family, which were related to immune infiltration in LGG tumor immune landscape. In this study, we demonstrated the predicted role of RNF proteins in LGG. In addition, we found out three markers among RNF proteins that are closely related to the immune aspects of LGG, which might serve as novel therapeutic targets for immunotherapy in the future.

Glioma targeted therapy: insight into future of molecular approaches

Gliomas are the common type of brain tumors originating from glial cells. Epidemiologically, gliomas occur among all ages, more often seen in adults, which males are more susceptible than females. According to the fifth edition of the WHO Classification of Tumors of the Central Nervous System (WHO CNS5), standard of care and prognosis of gliomas can be dramatically different. Generally, circumscribed gliomas are usually benign and recommended to early complete resection, with chemotherapy if necessary. Diffuse gliomas and other high-grade gliomas according to their molecule subtype are slightly intractable, with necessity of chemotherapy. However, for glioblastoma, feasible resection followed by radiotherapy plus temozolomide chemotherapy define the current standard of care. Here, we discuss novel feasible or potential targets for treatment of gliomas, especially IDH-wild type glioblastoma. Classic targets such as the p53 and retinoblastoma (RB) pathway and epidermal growth factor receptor (EGFR) gene alteration have met failure due to complex regulatory network. There is ever-increasing interest in immunotherapy (immune checkpoint molecule, tumor associated macrophage, dendritic cell vaccine, CAR-T), tumor microenvironment, and combination of several efficacious methods. With many targeted therapy options emerging, biomarkers guiding the prescription of a particular targeted therapy are also attractive. More pre-clinical and clinical trials are urgently needed to explore and evaluate the feasibility of targeted therapy with the corresponding biomarkers for effective personalized treatment options.

Phospholipase Cγ1 (PLCG1) overexpression is associated with tumor growth and poor survival in IDH wild-type lower-grade gliomas in adult patients

Gliomas are the most common and recalcitrant intracranial tumors, approximately a quarter of which are classified as lower-grade gliomas (WHO II-III). Although the prognosis of lower-grade gliomas (LGGs) is significantly better than that of higher-grade gliomas, as a highly heterogeneous tumor type, the prognosis of LGGs varies greatly based on the molecular diagnosis. IDH wild-type used to be regarded as a dismal prognostic biomarker in LGGs; however, several studies revealed that IDH wild-type LGGs might not always be equivalent to glioblastoma (WHO IV). Hence, we hypothesize that underlying biological events in LGGs can result in different prognosis. In our study, transcriptome profiling was performed in 24 samples of LGG, and the results showed that the expression of phospholipase Cγ1 (PLCG1) was significantly correlated with IDH1/2 status and patients' clinical outcome. Furthermore, the cancer genome atlas (TCGA) and the Chinese glioma genome atlas (CGGA) databases verified that elevated PLCG1 expression was associated with tumor progression and poor survival in LGG patients. Moreover, PLCG1-targeted siRNA dramatically affected the growth, migration and invasiveness of IDH wild-type LGG cell lines. In in vitro and in vivo experiments, the PLC-targeted drug significantly suppressed the tumor growth of IDH wild-type LGG cell lines in vitro and tumors in mouse models. Taken together, our results demonstrated that higher PLCG1 expression was associated with tumor growth and worse prognosis in IDH wild-type LGGs and PLCG1 could serve as a potential therapeutic target for IDH wild-type LGG patients.

Diagnostic performance of edited 2HG MR spectroscopy of central glioma in the clinical environment

OBJECTIVE

Oncometabolite D-2-hydroxyglutarate (2HG) is pooled in isocitrate dehydrogenase (IDH)-mutant glioma cells. Detecting 2HG by MR spectroscopy (MRS) has been proven viable in the last decade but has not entirely found its way into the clinical routine. This study aimed to explore the adoption of 2HG MRS while acknowledging factors that influence its performance in the clinical environment.

METHODS

Thirty-nine MR spectra were acquired and reported prospectively in patients with suspected glioma using a 3 T system with Mescher-Garwood point-resolved spectroscopy (MEGA-PRESS) sequence utilizing averaged free induction decay (FID) signals. Postprocessing and evaluation of spectra were performed with jMRUI and LCModel. 2HG concentration estimates, 2HG/Cr ratio, together with quality measures, including Cramér-Rao lower bounds (CRLBs), full-width at half-maximum (FWHM) values, and signal-to-noise ratio (SNR) were calculated using LCModel. Immunohistochemistry and genomic analysis results used as a ground truth were available for 15 patients.

RESULTS

The threshold for test positivity was set according to the ROC curve at 1 mM. Calculated sensitivity was 57.14% (95% CI 0.20-0.88), specificity 87.5% (95% CI 0.46-0.99), positive predictive value 80%, and negative predictive value 70%. Overall diagnostic accuracy was 73.33% (95% CI 0.45-0.92). The 2HG/Cr ratio with the cutoff value 0.085 significantly improved sensitivity and overall diagnostic accuracy [85.71%, 95% CI 0.42-1.00 and 86.67%, (95% CI 0.60-0.98), respectively].

CONCLUSION

Multiple factors compromising spectral quality in the clinical adoption of edited 2HG MRS resulted in diminished sensitivity but clinically acceptable specificity. Furthermore, the 2HG/Cr ratio performs better than the sole 2HG concentration estimate in the pre-operative setting.

Effects of ESCO2 or its methylation on the prognosis, clinical characteristics, immune microenvironment, and pathogenesis of low-grade glioma

The establishment of sister chromatid cohesion N-acetyltransferase 2 (ESCO2) has an important regulatory effect on cell proliferation and division, which is closely related to the malignant process of glioma cells. Therefore, this study attempts to provide a target for biologically targeted therapy for low-grade glioma (LGG) by demonstrating the regulatory effect of ESCO2 during the pathological process of LGG. First, the 1064 samples of LGG transcriptomic data and corresponding clinicopathological information obtained from various databases were included in the study. Second, the chi-squared test showed that the expression of ESCO2 was associated with the malignant characteristics of LGG (recurrence and grade), and Kaplan Meier and multivariate analysis suggested that ESCO2 was an independent risk factor, resulting in a significant reduction in the overall duration of survival of patients. Third, co-expression analysis showed that the level of mRNA expression of ESCO2 was negatively regulated by multiple methylation sites (cg04108328, cg12564175, and cg26534677), and the hypermethylation status of cg12564175 could prolong the overall survival of patients. Fourth, the Tumor Immune Estimation Resource (TIMER) database shows that ESCO2 can have a positive regulatory relationship with six different immune cells, such as CD8 + T cells and macrophages, and a positive expression relationship with PD-1 and PD-L1. Finally, Gene Set Enrichment Analysis (GSEA) showed that ESCO2 may play a carcinogenic role by affecting cell replication and DNA repair. In summary, this study confirmed the carcinogenic effect of ESCO2 on LGG for the first time. It is speculated that both the mRNA of ESCO2 and its methylation site (cg12564175) can be useful biological targets for molecular targeted therapy of LGG.

The Clinical Significance and Transcription Regulation of a DNA Damage Repair Gene, SMC4, in Low-Grade Glioma via Integrated Bioinformatic Analysis

Glioma is the most common type of malignant tumor in the central nervous system with an unfavorable prognosis and limited treatment. In this study, we are devoted to addressing the prognostic value of DNA damage repair-related genes in low-grade glioma (LGG). We plotted the landscape of DNA damage repair (DDR)-related genes and identified SMC4 as an independent prognostic marker with integrated bioinformatics analysis, which is overexpressed in different histologic subtypes of glioma. We observed that SMC4 expression is elevated in recurrent LGG patients or those with advanced histologic staging. SMC4 depletion inhibits proliferation and induces increased replication damage in LGG cells. Lastly, we predicted and validated the transcription modulation of SMC4 by a transcription factor, MYB, at the -976bp~ -837bp of the SMC4 promoter region in LGG cells. Together, our study identified SMC4 as a potential prognostic biomarker for LGG patients, which functions to promote cell proliferation by repairing replication damage and the expression of SMC4 could be transcriptionally regulated by MYB.