Association between MGMT Enhancer Methylation and MGMT Promoter Methylation, MGMT Protein Expression, and Overall Survival in Glioblastoma

Study on the mechanism of action of the active ingredient of Calculus Bovis in the treatment of sepsis by integrating single-cell sequencing and machine learning

BACKGROUND

Sepsis, a complex inflammatory condition with high mortality rates, lacks effective treatments. This study explores the therapeutic mechanisms of Calculus Bovis in sepsis using network pharmacology and RNA sequencing.

METHODS

Sepsis data from the China National GeneBank Database were analyzed for differentially expressed genes (FC ≥ 2, FDR < 0.05). Active components of Calculus Bovis were identified via the HERB and BATMAN-TCM databases, with target interactions assessed through protein-protein interaction (PPI) networks. GO and KEGG analyses identified pathway enrichments (P ≤ .01). Survival analysis using the GSE65682 database evaluated prognosis-related genes (P < .05). Four machine learning models (XGBoost, SVM, Decision Tree, KNN) were constructed to assess diagnostic potential, with AUC values evaluating accuracy. Immunofluorescence and single-cell RNA sequencing localized key genes, while molecular docking and molecular dynamics simulations (MD) assessed binding affinities and stability of Calculus Bovis compounds with target proteins.

RESULTS

We identified 593 targets for Calculus Bovis and 4329 sepsis-related genes, with 149 overlapping. Key genes ADAM17, CASP1, CD81, and MGMT were linked to improved prognosis (P < .05) and involved in inflammatory responses and pyroptosis (P ≤ .01). The XGBoost model achieved high diagnostic accuracy (AUC: training = 1.000, test = 0.964). Molecular docking showed strong binding (energy < -6.0 kcal/mol), and MD indicated stable interactions, particularly with ADAM17 and CD81.

CONCLUSION

This study highlights the potential of Calculus Bovis in sepsis treatment, identifying key genes as therapeutic targets.

Association of Intergenic and Intragenic MGMT Enhancer Methylation with MGMT Promoter Methylation, MGMT Protein Expression and Clinical and Demographic Parameters in Glioblastoma

The methylation status of the MGMT gene promoter is recognized as a key predictive biomarker for glioblastoma patients, influencing treatment decisions and outcomes. Emerging evidence suggests that enhancer methylation may also play a role in gene regulation and is associated with various clinical parameters, genetic variants, and demographic factors. This study aimed to assess DNA methylation levels in intergenic and intragenic MGMT enhancers to investigate their relationship with MGMT promoter methylation, MGMT protein expression, and clinical and demographic characteristics in glioblastoma. We developed 18 pyrosequencing assays to analyze 54 CpGs, including 34 in intergenic and 20 in intragenic enhancers. The assays were applied to tumor cells derived from 38 glioma patients. Intragenic enhancer CpGs showed significantly higher methylation than intergenic enhancer CpGs. Intragenic enhancer methylation showed a strong negative correlation with MGMT promoter methylation. For several CpGs in intragenic enhancers, an inverse L-shaped relationship between methylation levels and MGMT expression was observed. We identified distinct associations between enhancer methylation and clinical and demographic parameters. Intergenic enhancer methylation was primarily linked to the TERT SNP rs2853669 genotype, Ki-67 expression, age, and sex, whereas intragenic enhancer methylation was associated with MGMT promoter methylation, MGMT expression, overall survival, and progression-free survival. Further studies with larger patient cohorts are needed to validate the clinical relevance of intergenic and intragenic MGMT enhancer methylation in glioblastoma.

Contrast-enhanced ultrasound can differentiate the level of glioma infiltration and correlate it with biological behavior: a study based on local pathology

PURPOSE

The objective of this study is to assess the diagnostic efficacy of contrast-enhanced ultrasound (CEUS) in determining the level of glioma infiltration and to investigate its correlation with pathological markers.

METHODS

A prospective study involving 16 adult glioma patients was conducted. Preoperative US-(Magnetic Resonance)MR fusion imaging was utilized for tumor infiltration localization, while CEUS was employed to assess hemodynamic alterations. Parameters such as peak intensity (PI), rise time (RT), time to peak (TTP), and area under the curve (AUC) were measured. Utilizing contralateral normal brain tissue as the reference standard. The Kruskal-Wallis H-test was conducted to compare CEUS and pathological parameters (significance level, p < 0.05; bonferroni correction) among tumor margins, infiltration zones, and normal tissues, as well as between low-grade glioma (LGG) and high-grade glioma (HGG) within the infiltration zone, based on whole slide pathological images analysis. Spearman correlation analysis was employed to determine the correlation coefficient between hemodynamics and pathology. Receiver operating characteristic (ROC) curves were drawn to evaluate the performance of CEUS in tumor classification.

RESULTS

From tumor margin to normal tissue, PI, AUC, Ki67, EGFR, and 1p/19q showed a significant decreasing trend, while TTP, IDH-1, and MGMT gradually increased. RT was lower at the tumor margin but did not show statistically significant differences. In the infiltration zones, there was a significant increase in parameters such as PI, normalized PI (Nor_PI), AUC, and Ki67 from LGG to HGG, while RT, Nor_RT, TTP, Nor_TTP, IDH-1, and MGMT significantly decreased. Nor_AUC and EGFR increased but were not significant, and 1p/19q decreased but was not significant. RT and Nor_TTP were independent risk factors for distinguishing between LGG and HGG in the infiltration zone, with a combined diagnostic efficacy ROC of 0.891. The sensitivity reached 96.64% and the specificity reached 82.35%. There was a significant correlation between hemodynamic indicators and pathological indicators. CEUS can effectively differentiate levels of infiltration zones, which correlates with their biological behavior, with RT + Nor_TTP showing particularly highest diagnostic efficacy.

CONCLUSION

These findings contribute to improving the accuracy of diagnosing infiltration zones and provide essential biological insights for subsequent treatments.

Nanotechnology as a new strategy for the diagnosis and treatment of gliomas

Glioma is the most common malignant tumor of the central nervous system (CNS), and is characterized by high aggressiveness and a high recurrence rate. Currently, the main treatments for gliomas include surgical resection, temozolomide chemotherapy and radiotherapy. However, the prognosis of glioma patients after active standardized treatment is still poor, especially for glioblastoma (GBM); the median survival is still only 14.6 months, and the 5-year survival rate is only 4-5%. The current challenges in glioma treatment include difficulty in complete surgical resection, poor blood‒brain barrier (BBB) drug permeability, therapeutic resistance, and difficulty in tumor-specific targeting. In recent years, the rapid development of nanotechnology has provided new directions for diagnosing and treating gliomas. Nanoparticles (NPs) are characterized by excellent surface tunability, precise targeting, excellent biocompatibility, and high safety. In addition, NPs can be used for gene therapy, photodynamic therapy, and antiangiogenic therapy and can be combined with biomaterials for thermotherapy. In recent decades, breakthroughs in diagnosing and treating gliomas have been made with various functional NPs, and NPs are expected to become a new strategy for glioma diagnosis and treatment. In this paper, we review the main obstacles in the treatment of glioma and discuss the potential and challenges of the latest nanotechnology in the diagnosis and treatment of glioma.

Temperature-Wise Calibration Increases the Accuracy of DNA Methylation Levels Determined by High-Resolution Melting (HRM)

High-resolution melting (HRM) is a cost-efficient tool for targeted DNA methylation analysis. HRM yields the average methylation status across all CpGs in PCR products. Moreover, it provides information on the methylation pattern, e.g., the occurrence of monoallelic methylation. HRM assays have to be calibrated by analyzing DNA methylation standards of known methylation status and mixtures thereof. In general, DNA methylation levels determined by the classical calibration approach, including the whole temperature range in between normalization intervals, are in good agreement with the mean of the DNA methylation status of individual CpGs determined by pyrosequencing (PSQ), the gold standard of targeted DNA methylation analysis. However, the classical calibration approach leads to highly inaccurate results for samples with heterogeneous DNA methylation since they result in more complex melt curves, differing in their shape compared to those of DNA standards and mixtures thereof. Here, we present a novel calibration approach, i.e., temperature-wise calibration. By temperature-wise calibration, methylation profiles over temperature are obtained, which help in finding the optimal calibration range and thus increase the accuracy of HRM data, particularly for heterogeneous DNA methylation. For explaining the principle and demonstrating the potential of the novel calibration approach, we selected the promoter and two enhancers of MGMT, a gene encoding the repair protein MGMT.

A systematic review of high impact CpG sites and regions for MGMT methylation in glioblastoma [A systematic review of MGMT methylation in GBM]

BACKGROUND

MGMT (O 6 -methylguanine-DNA methyltransferase) promoter methylation is a commonly assessed prognostic marker in glioblastoma (GBM). Epigenetic silencing of the MGMT gene by promoter methylation is associated with greater overall and progression free survival with alkylating agent regimens. To date, there is marked heterogeneity in how MGMT promoter methylation is tested and which CpG sites are interrogated.

METHODS

To further elucidate which MGMT promoter CpG sites are of greatest interest, we performed comprehensive searches in PubMed, Web of Science, and Embase and reviewed 2,925 article abstracts. We followed the GRADE scoring system to assess risk of bias and the quality of the studies we included.

RESULTS

We included articles on adult glioblastoma that examined significant sites or regions within MGMT promoter for the outcomes: overall survival, progression free survival, and/or MGMT expression. We excluded systemic reviews and articles on lower grade glioma. fifteen articles met inclusion criteria with variable overlap in laboratory and statistical methods employed, as well as CpG sites interrogated. Pyrosequencing or BeadChip arrays were the most popular methods utilized, and CpG sites between CpG's 70-90 were most frequently investigated. Overall, there was moderate concordance between the CpG sites that the studies reported to be highly predictive of prognosis. Combinations or means of sites between CpG's 73-89 were associated with improved OS and PFS. Six studies identified CpG sites associated with prognosis that were closer to the transcription start site: CpG's 8, 19, 22, 25, 27, 32,38, and CpG sites 21-37, as well as low methylation level of the enhancer regions.

CONCLUSION

The following systematic review details a comprehensive investigation of the current literature and highlights several potential key CpG sites that demonstrate significant association with OS, PFS, and MGMT expression. However, the relationship between extent of MGMT promoter methylation and survival may be non-linear and could be influenced by potential CpG hotspots, the extent of methylation at each CpG site, and MGMT enhancer methylation status. There were several limitations within the studies such as smaller sample sizes, variance between methylation testing methods, and differences in the various statistical methods to test for association to outcome. Further studies of high impact CpG sites in MGMT methylation is warranted.

Epigenetic modification and characterization of the MGMT promoter region using CRISPRoff in glioblastoma cells

The methylation status of the O6-methylguanine DNA methyltransferase (MGMT) promoter region is a critical predictor of response to alkylating agents in glioblastoma. However, current approaches to study the MGMT status focus on analyzing models with non-identical backgrounds. Here, we present an epigenetic editing approach using CRISPRoff to introduce site-specific CpG methylation in the MGMT promoter region of glioma cell lines. Sanger sequencing revealed successful introduction of methylation, effectively generating differently methylated glioma cell lines with an isogenic background. The introduced methylation resulted in reduced MGMT mRNA and protein levels. Furthermore, the cell lines with MGMT promoter region methylation exhibited increased sensitivity to temozolomide, consistent with the impact of methylation on treatment outcomes in patients with glioblastoma. This precise epigenome-editing approach provides valuable insights into the functional relevance of MGMT promoter regional methylation and its potential for prognostic and predictive assessments, as well as epigenetic-targeted therapies.

Association of MGMT Promoter and Enhancer Methylation with Genetic Variants, Clinical Parameters, and Demographic Characteristics in Glioblastoma

The response of glioblastoma (GBM) patients to the alkylating agent temozolomide (TMZ) vitally depends on the expression level of the repair protein O6-methylguanine-DNA methyltransferase (MGMT). Since MGMT is strongly regulated by promoter methylation, the methylation status of the MGMT promoter has emerged as a prognostic and predictive biomarker for GBM patients. By determining the methylation levels of the four enhancers located within or close to the MGMT gene, we recently found that enhancer methylation contributes to MGMT regulation. In this study, we investigated if methylation of the four enhancers is associated with SNP rs16906252, TERT promoter mutations C228T and C250T, TERT SNP rs2853669, proliferation index Ki-67, overall survival (OS), age, and sex of the patients. In general, associations with genetic variants, clinical parameters, and demographic characteristics were caused by a complex interplay of multiple CpGs in the MGMT promoter and of multiple CpGs in enhancer regions. The observed associations for intragenic enhancer 4, located in intron 2 of MGMT, differed from associations observed for the three intergenic enhancers. Some findings were restricted to subgroups of samples with either methylated or unmethylated MGMT promoters, underpinning the relevance of the MGMT promoter status in GBMs.

[Total DNA methylation profile in assessing the MGMT gene promoter status in malignant gliomas]

Methylation of the O-6-methylguanine-DNA methyltransferase (MGMT) gene promoter is currently the most important prognostic biomarker in therapy of IDH-wild-type glioblastoma. One can obtain information about this methylation from total DNA methylation profile.

OBJECTIVE

To analyze the DNA methylation signal intensity in the MGMT gene in samples of malignant gliomas and identify the most significant genomic positions for calculating the MGMT gene promoter status for further improvement of diagnostics and prediction of therapeutic options in patients with malignant gliomas.

MATERIAL AND METHODS

The study is based on 43 samples (frozen tissue or paraffin blocks) from patients with malignant gliomas. Tumor DNA samples were prepared using the Illumina Infinium MethylationEPIC BeadChip Kit and the Illumina Next-Seq 550 Sequencing System platform. DNA methylation profiles were analyzed using computational algorithms in the R language, specialized libraries minfi and mgmtstp27, as well as basic statistical functions in the Rstudio environment.

RESULTS

We established the MGMT gene promoter status in 43 samples of malignant gliomas considering total DNA methylation profile. In 24 samples (55%), the MGMT gene promoter was methylated. We compared methylation signal in certain CpG islands in groups with methylated and unmethylated MGMT gene promoters and identified the most significant positions for further improvement of data analysis algorithm.

CONCLUSION

These data demonstrate the possibilities and prospects for further improvement of algorithm for analysis of the MGMT gene promoter status based on total DNA methylation profile in patients with malignant gliomas as an alternative to methyl-specific PCR. Our results are consistent with data of other neuro-oncology researchers. Indeed, computational methods like MGMT-STP27 are quite powerful and can be used in scientific and clinical practice to assess prognosis and make decisions about chemotherapy with alkylating agents.