PAX2 is regulated by estrogen/progesterone through promoter methylation in endometrioid adenocarcinoma and has an important role in carcinogenesis via the AKT/mTOR signaling pathway.

Endometrioid adenocarcinoma (EEC) is one of the most common cancers of the female reproductive system. In recent years, much emphasis has been placed on early diagnosis and treatment. PAX2 (Paired box 2) inactivation is reportedly an important biomarker for endometrioid intraepithelial neoplasia (EIN) and EEC. However, the role of PAX2 in EEC carcinogenesis remains unclear. PAX2 expression and associated clinical characteristics were analyzed via The Cancer Genome Atlas, Gene Expression Omnibus, and Cancer Cell Line Encyclopedia databases and clinical paired EIN/EEC tissue samples. Bioinformatic analysis was conducted to identify the putative molecular function and mechanism of PAX2. Cell proliferation, colony formation, cell migration, and invasion assays in vitro, and mouse xenograft models were utilized to study the biological functions of PAX2 in vivo. Pyrosequencing and the demethylating drug 5-Aza-dc were used to verify promoter methylation in clinical tissues and cell lines, respectively. The mechanism underlying the regulatory effect of estrogen (E2) and progesterone (P4) on PAX2 expression was investigated by receptor block assay and double luciferase reporter assay. PAX2 expression was found to be significantly downregulated in EIN and EEC tissues, its overexpression inhibited EEC cell malignant behaviors in vivo and in vitro and inhibited the AKT/mTOR signaling pathway. PAX2 inactivation in EEC was related to promoter methylation, and its expression was regulated by E2 and P4 through their receptors via promoter methylation. Our findings elucidated the expression and function of PAX2 in EEC and have provided hitherto undocumented evidence of the underlying molecular mechanisms. PAX2 expression is suppressed by estrogen prompting its methylation through estrogen receptor. Furthermore, PAX2 regulates the AKT/mTOR signaling pathway to influence EEC progression. © 2024 The Pathological Society of Great Britain and Ireland.

Clinical features and impact of p53 status on sporadic mismatch repair deficiency and Lynch syndrome in uterine cancer.

The clinical features of sporadic mismatch repair deficiency (MMRd) and Lynch syndrome (LS) in Japanese patients with endometrial cancer (EC) were examined by evaluating the prevalence and prognostic factors of LS and sporadic MMRd in patients with EC. Targeted sequencing of five LS susceptibility genes (MLH1, MSH2, MSH6, PMS2, and EPCAM) was carried out in 443 patients with EC who were pathologically diagnosed with EC at the National Cancer Center Hospital between 2011 and 2018. Pathogenic variants in these genes were detected in 16 patients (3.7%). Immunohistochemistry for MMR proteins was undertaken in 337 of the 433 (77.9%) EC patients, and 91 patients (27.0%) showed absent expression of at least one MMR protein. The 13 cases of LS with MMR protein loss (93.8%) showed a favorable prognosis with a 5-year overall survival (OS) rate of 100%, although there was no statistically significant difference between this group and the sporadic MMRd group (p = 0.27). In the MMRd without LS group, the 5-year OS rate was significantly worse in seven patients with an aberrant p53 expression pattern than in those with p53 WT (53.6% vs. 93.9%, log-rank test; p = 0.0016). These results suggest that p53 abnormalities and pathogenic germline variants in MMR genes could be potential biomarkers for the molecular classification of EC with MMRd.

Identification of epigenetic silencing of the SFRP2 gene in colorectal cancer as a clinical biomarker and molecular significance.

BACKGROUND: Several studies have suggested secreted frizzled-related protein 2 (SFRP2) gene as a potential clinical biomarker in colorectal cancer (CRC). However, its diagnostic role remains unclear. In this study, we aimed to investigate the significance of SFRP2 methylation levels in a large cohort of biological specimens (including blood, adipose and colonic tissues) from patients with CRC, thereby potentially identifying new biomarker utility. METHODS: We examined the expression (by qPCR) and methylation status (by 450 K DNA array and DNA pyrosequencing) of the SFRP2 gene in healthy participants (N = 110, aged as 53.7 (14.2), 48/62 males/females) and patients with CRC (N = 85, aged 67.7 (10.5), 61/24 males/females), across different biological tissues, and assessing its potential as a biomarker for CRC. Additionally, we investigated the effect of recombinant human SFRP2 (rhSFRP2) as a therapeutic target, on cell proliferation, migration, and the expression of key genes related to carcinogenesis and the Wnt pathway. RESULTS: Our findings revealed that SFRP2 promoter methylation in whole blood could predict cancer stage (I + II vs. III + IV) (AUC = 0.653), lymph node invasion (AUC = 0.692), and CRC recurrence (AUC = 0.699) in patients with CRC (all with p < 0.05). Furthermore, we observed a global hypomethylation of SFRP2 in tumors compared to the adjacent area (p < 0.001). This observation was validated in the TCGA-COAD and TCGA-READ cohorts, demonstrating overall hypermethylation (both with p < 0.001) and low expression (p < 0.001), as shown in publicly available scRNA-Seq data. Notably, neoadjuvant-treated CRC patients exhibited lower SFRP2 methylation levels compared to untreated patients (p < 0.05) and low promoter SFRP2 methylation in untreated patients was associated with poor overall survival (p < 0.05), when compared to high methylation. Finally, treatment with 5 µg of rhSFRP2 treatment in CRC cells (HCT116 cells) inhibited cell proliferation (p < 0.001) and migration (p < 0.05), and downregulated the expression of AXIN2 (p < 0.01), a gene involved in Wnt signaling pathway. CONCLUSIONS: These findings establish promoter methylation of the SFRP2 gene as a prognostic candidate in CRC when assessed in blood, and as a therapeutic prognostic candidate in tumors, potentially valuable in clinical practice. SFRP2 also emerges as a therapeutic option, providing new clinical and therapeutical avenues.

Accurate and comprehensive evaluation of O6-methylguanine-DNA methyltransferase promoter methylation by nanopore sequencing.

AIMS: The methylation status of the O6-methylguanine-DNA methyltransferase (MGMT) promoter region is essential in evaluating the prognosis and predicting the drug response in patients with glioblastoma. In this study, we evaluated the utility of using nanopore long-read sequencing as a method for assessing methylation levels throughout the MGMT CpG-island, compared its performance to established techniques and demonstrated its clinical applicability. METHODS: We analysed 165 samples from CNS tumours, focusing on the MGMT CpG-island using nanopore sequencing. Oxford Nanopore Technologies (ONT) MinION and PromethION flow cells were employed for single sample or barcoded assays, guided by a CRISPR/Cas9 protocol, adaptive sampling or as part of a whole genome sequencing assay. Methylation data obtained through nanopore sequencing were compared to results obtained via pyrosequencing and methylation bead arrays. Hierarchical clustering was applied to nanopore sequencing data for patient stratification. RESULTS: Nanopore sequencing displayed a strong correlation (R2 = 0.91) with pyrosequencing results for the four CpGs of MGMT analysed by both methods. The MGMT-STP27 algorithm's classification was effectively reproduced using nanopore data. Unsupervised hierarchical clustering revealed distinct patterns in methylated and unmethylated samples, providing comparable survival prediction capabilities. Nanopore sequencing yielded high-confidence results in a rapid timeframe, typically within hours of sequencing, and extended the analysis to all 98 CpGs of the MGMT CpG-island. CONCLUSIONS: This study presents nanopore sequencing as a valid and efficient method for determining MGMT promotor methylation status. It offers a comprehensive view of the MGMT promoter methylation landscape, which enables the identification of potentially clinically relevant subgroups of patients. Further exploration of the clinical implications of patient stratification using nanopore sequencing of MGMT is warranted.

Association of APP gene polymorphisms and promoter methylation with essential hypertension in Guizhou: a case-control study.

BACKGROUND: Single-nucleotide polymorphisms (SNPs) and DNA methylation are crucial regulators of essential hypertension (EH). Amyloid precursor protein (APP) mutations are implicated in hypertension development. Nonetheless, studies on the association of APP gene polymorphism and promoter methylation with hypertension are limited. Therefore, this case-control aims to evaluate the genetic association of APP gene polymorphism and promoter methylation with EH in Guizhou populations. OBJECTIVE AND METHODS: We conducted a case-control study on 343 EH patients and 335 healthy controls (including Miao, Buyi, and Han populations) in the Guizhou province of China to analyze 11 single-nucleotide polymorphisms (rs2040273, rs63750921, rs2211772, rs2830077, rs467021, rs368196, rs466433, rs364048, rs364051, rs438031, rs463946) in the APP gene via MassARRAY SNP. The MassARRAY EpiTYPER was employed to detect the methylation levels of the promoters. RESULTS: In the Han population, the rs2211772 genotype distribution was significantly different between disease and control groups (χ2 = 6.343, P = 0.039). The CC genotype reduced the risk of hypertension compared to the TT or TC genotype (OR 0.105, 95%CI 0.012-0.914, P = 0.041). For rs2040273 in the Miao population, AG or GG genotype reduced the hypertension risk compared with the AA genotype (OR 0.533, 95%CI 0.294-0.965, P = 0.038). Haplotype TCC (rs364051-rs438031-rs463946) increased the risk of EH in Guizhou (OR 1.427, 95%CI 1.020-1.996, P = 0.037). Each 1% increase in CpG_19 (- 613 bp) methylation level was associated with a 4.1% increase in hypertension risk (OR 1.041, 95%CI 1.002-1.081, P = 0.039). Each 1% increase in CpG_1 (- 296 bp) methylation level was associated with an 8% decrease in hypertension risk in women (OR 0.920, 95%CI 0.860-0.984, P = 0.015). CpG_19 significantly correlated with systolic blood pressure (r = 0.2, P = 0.03). The methylation levels of CpG_19 in hypertensive patients with rs466433, rs364048, and rs364051 minor alleles were lower than that with wild-type alleles (P < 0.05). Moreover, rs467021 and rs364051 showed strong synergistic interaction with EH (χ2 = 7.633, P = 0.006). CpG_11, CpG_19, and rs364051 showed weak synergistic interaction with EH (χ2 = 19.874, P < 0.001). CONCLUSION: In summary, rs2211772 polymorphism and promoter methylation level of APP gene may be linked to EH in Guizhou populations. Our findings will provide novel insights for genetic research of hypertension and Alzheimer's disease.

Epigenetically dysregulated NOTCH-Delta-HES signaling cascade can serve as a subtype classifier for acute lymphoblastic leukemia.

The NOTCH-Delta-HES signaling cascade is regarded as a double-edged sword owing to its dual tumor-suppressor and oncogenic roles, in different cellular environments. In the T-cells, it supports leukemogenesis by promoting differentiation while in B-cells, it controls leukemogenesis by inhibiting early differentiation/inducing growth arrest in the lead to apoptosis. The present study was undertaken to assess if this bi-faceted behavior of NOTCH family can be exploited as a diagnostic biomarker or subtype classifier of acute lymphoblastic leukemia (ALL). In this pursuit, expression of seven NOTCH cascade genes was analyzed in bone marrow (BM) biopsy and blood plasma (BP) of pediatric ALL patients using quantitative PCR (qPCR). Further, promoter DNA methylation status of the differentially expressed genes (DEGs) was assessed by methylation-specific qMSP and validated through bisulphite amplicon sequencing. Whereas hypermethylation of JAG1, DLL1, and HES-2, HES-4, and HES-5 was observed in all patients, NOTCH3 was found hypermethylated specifically in Pre-B ALL cases while DLL4 in Pre-T ALL cases. Aberrant DNA methylation strongly correlated with downregulated gene expression, which restored at complete remission stage as observed in "follow-up/post-treatment" subjects. The subtype-specific ROC curve analysis and Kaplan-Meier survival analysis predicted a clinically applicable diagnostic and prognostic potential of the panel. Moreover, the logistic regression model (Pre-B vs Pre-T ALL) was found to be the best-fitted model (McFadden's R2 = 0.28, F1 measure = 0.99). Whether analyzed in BM-aspirates or blood plasma, the NOTCH epigenetic signatures displayed comparable results (p < 0.001), advocating the potential of NOTCH-Delta-HES cascade, as a subtype classifier, in minimally invasive diagnosis of ALL.

Exploring MGMT methylation-driven structural connectivity changes in insular gliomas: a tractography and graph theoretical analysis.

OBJECTIVES: This study aims to explore the relationship between the methylation levels of the O-6-methylguanine-DNA methyltransferase (MGMT) promoter and the structural connectivity in insular gliomas across hemispheres. METHODS: We analyzed 32 left and 29 right insular glioma cases and 50 healthy controls, using differential tractography, correlational tractography, and graph theoretical analysis to investigate the correlation between structural connectivity and the methylation level. RESULTS: The differential tractography results revealed that in left insular glioma, the volume of affected inferior fronto-occipital fasciculus (IFOF, p = 0.019) significantly correlated with methylation levels. Correlational tractography results showed that the quantitative anisotropy (QA) value of peritumoral fiber tracts also exhibited a significant correlation with methylation levels (FDR < 0.05). On the other hand, in right insular glioma, anterior internal part of the reticular tract, IFOF, and thalamic radiation showed a significant correlation with methylation levels but at a different correlation direction from the left side (FDR < 0.05). The graph theoretical analysis showed that in the left insular gliomas, only the radius of graph was significantly lower in methylated MGMT group than unmethylated group (p = 0.047). No significant correlations between global properties and methylation levels were observed in insular gliomas on both sides. CONCLUSION: Our findings highlight a significant, hemisphere-specific correlation between MGMT promoter methylation and structural connectivity in insular gliomas. This study provides new insights into the genetic influence on glioma pathology, which could inform targeted therapeutic strategies.

Predominance of MGMT promoter methylation among Pakistani glioblastoma patients.

BACKGROUND: Glioblastoma multiforme (GBM), the most prevalent subgroup of neuroepithelial tumors, is characterized by dismal overall survival (OS). Several studies have linked O6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation to OS in GBM patients. However, MGMT methylation frequencies vary geographically and across ethnicities, with limited data for South Asian populations, including Pakistan. This study aimed to analyze MGMT promoter methylation in Pakistani GBM patients. METHODS: Consecutive primary GBM patients diagnosed ≥ 18 years-of-age, with no prior chemotherapy or radiotherapy history, were retrospectively selected. DNA was isolated from formalin-fixed-paraffin-embedded tissues. MGMT promoter methylation was analyzed using methylation-specific PCR. Clinical, pathological, and treatment data were assessed using Fisher's exact/Chi-squared tests. OS was calculated using Kaplan-Meier analysis in SPSS 27.0.1. RESULTS: The study included 48 GBM patients, comprising 38 (79.2%) males and 10 (20.8%) females. The median diagnosis age was 49.5 years (range 18-70). MGMT methylation was observed in 87.5% (42/48) of all cases. Patients with MGMT methylation undergoing radiotherapy or radiotherapy plus chemotherapy exhibited significantly improved median OS of 7.2 months (95% CI, 3.7-10.7; P < 0.001) and 16.9 months (95% CI, 15.9-17.9; P < 0.001), respectively, compared to those undergoing surgical resection only (OS: 2.2 months, 95% CI, 0.8-3.6). CONCLUSION: This is the first comprehensive study highlighting a predominance of MGMT methylation in Pakistani GBM patients. Furthermore, our findings underscore the association of MGMT methylation with improved OS across diverse treatment modalities. Larger studies are imperative to validate our findings for better management of Pakistani GBM patients.

CDKN2A promoter methylation enhances self-renewal of glioblastoma stem cells and confers resistance to carmustine.

BACKGROUND: Glioblastoma, a highly aggressive form of brain cancer, poses significant challenges due to its resistance to therapy and high recurrence rates. This study aimed to investigate the expression and functional implications of CDKN2A, a key tumor suppressor gene, in glioblastoma cells, building upon the existing background of knowledge in this field. METHOD: Quantitative reverse transcription PCR (qRT-PCR) analysis was performed to evaluate CDKN2A expression in U87 glioblastoma cells compared to normal human astrocytes (NHA). CDKN2A expression levels were manipulated using small interfering RNA (siRNA) and CDKN2A overexpression vector. Cell viability assays and carmustine sensitivity tests were conducted to assess the impact of CDKN2A modulation on glioblastoma cell viability and drug response. Sphere formation assays and western blot analysis were performed to investigate the role of CDKN2A in glioblastoma stem cell (GSC) self-renewal and pluripotency marker expression. Additionally, methylation-specific PCR (MSP) assays and demethylation treatment were employed to elucidate the mechanism of CDKN2A downregulation in U87 cells. RESULT: CDKN2A expression was significantly reduced in glioblastoma cells compared to NHA. CDKN2A overexpression resulted in decreased cell viability and enhanced sensitivity to carmustine treatment. CDKN2A inhibition promoted self-renewal capacity and increased pluripotency marker expression in U87 cells. CDKN2A upregulation led to elevated protein levels of p16INK4a, p14ARF, P53, and P21, which are involved in cell cycle regulation. CDKN2A downregulation in U87 cells was associated with high promoter methylation, which was reversed by treatment with a demethylating agent. CONCLUSION: Our findings demonstrate that CDKN2A downregulation in glioblastoma cells is associated with decreased cell viability, enhanced drug resistance, increased self-renewal capacity, and altered expression of pluripotency markers. The observed CDKN2A expression changes are mediated by promoter methylation. These results highlight the potential role of CDKN2A as a therapeutic target and prognostic marker in glioblastoma.

A noninvasive method for predicting clinically significant prostate cancer using magnetic resonance imaging combined with PRKY promoter methylation level: a machine learning study.

BACKGROUND: Traditional process for clinically significant prostate cancer (csPCA) diagnosis relies on invasive biopsy and may bring pain and complications. Radiomic features of magnetic resonance imaging MRI and methylation of the PRKY promoter were found to be associated with prostate cancer. METHODS: Fifty-four Patients who underwent prostate biopsy or photoselective vaporization of the prostate (PVP) from 2022 to 2023 were selected for this study, and their clinical data, blood samples and MRI images were obtained before the operation. Methylation level of two PRKY promoter sites, cg05618150 and cg05163709, were tested through bisulfite sequencing PCR (BSP). The PI-RADS score of each patient was estimated and the region of interest (ROI) was delineated by 2 experienced radiologists. After being extracted by a plug-in of 3D-slicer, radiomic features were selected through LASSCO regression and t-test. Selected radiomic features, methylation levels and clinical data were used for model construction through the random forest (RF) algorithm, and the predictive efficiency was analyzed by the area under the receiver operation characteristic (ROC) curve (AUC). RESULTS: Methylation level of the site, cg05618150, was observed to be associated with prostate cancer, for which the AUC was 0.74. The AUC of T2WI in csPCA prediction was 0.84, which was higher than that of the apparent diffusion coefficient ADC (AUC = 0.81). The model combined with T2WI and clinical data reached an AUC of 0.94. The AUC of the T2WI-clinic-methylation-combined model was 0.97, which was greater than that of the model combined with the PI-RADS score, clinical data and PRKY promoter methylation levels (AUC = 0.86). CONCLUSIONS: The model combining with radiomic features, clinical data and PRKY promoter methylation levels based on machine learning had high predictive efficiency in csPCA diagnosis.

O6 -methylguanine methyltransferase promoter methylation status of glioblastoma cell line clonal population.

Glioblastoma (GBM) remains a treatment-resistant malignant brain tumor in large part because of its genetic heterogeneity and epigenetic plasticity. In this study, we investigated the epigenetic heterogeneity of GBM by evaluating the methylation status of the O6 -methylguanine methyltransferase (MGMT) promoter in individual clones of a single cell derived from GBM cell lines. The U251 and U373 GBM cell lines, from the Brain Tumour Research Centre of the Montreal Neurological Institute, were used for the experiments. To evaluate the methylation status of the MGMT promoter, pyrosequencing and methylation-specific PCR (MSP) were used. Moreover, mRNA and protein expression levels of MGMT in the individual GBM clones were evaluated. The HeLa cell line, which hyper-expresses MGMT, was used as control. A total of 12 U251 and 12 U373 clones were isolated. The methylation status of 83 of 97 CpG sites in the MGMT promoter were evaluated by pyrosequencing, and 11 methylated CpG sites and 13 unmethylated CpG sites were evaluated by MSP. The methylation status by pyrosequencing was relatively high at CpG sites 3-8, 20-35, and 7-83, in both the U251 and U373 clones. Neither MGMT mRNA nor protein was detected in any clone. These findings demonstrate tumor heterogeneity among individual clones derived from a single GBM cell. MGMT expression may be regulated, not only by methylation of the MGMT promoter but by other factors as well. Further studies are needed to clarify the mechanisms underlying the epigenetic heterogeneity and plasticity of GBM.

Role of Epigenetics for the Efficacy of Cisplatin.

The clinical utility of the chemotherapeutic agent cisplatin is restricted by cancer drug resistance, which is either intrinsic to the tumor or acquired during therapy. Epigenetics is increasingly recognized as a factor contributing to cisplatin resistance and hence influences drug efficacy and clinical outcomes. In particular, epigenetics regulates gene expression without changing the DNA sequence. Common types of epigenetic modifications linked to chemoresistance are DNA methylation, histone modification, and non-coding RNAs. This review provides an overview of the current findings of various epigenetic modifications related to cisplatin efficacy in cell lines in vitro and in clinical tumor samples. Furthermore, it discusses whether epigenetic alterations might be used as predictors of the platinum agent response in order to prevent avoidable side effects in patients with resistant malignancies. In addition, epigenetic targeting therapies are described as a possible strategy to render cancer cells more susceptible to platinum drugs.

Contribution of constitutional BRCA1 promoter methylation to early-onset and familial breast cancer patients from Pakistan.

PURPOSE: Constitutional BRCA1 promoter methylation has been identified as a potential risk factor for breast cancer (BC) in the Caucasian population. However, this data is lacking for BC patients of Asian origin. Therefore, we assessed the contribution of constitutional BRCA1 promoter methylation in Pakistani BC patients. METHODS: A total of 385 BRCA1/2-negative index BC patients (197 early-onset BC (≤ 30 years), 152 familial BC, 17 familial BC and ovarian cancer, 19 male BC) and 107 healthy controls were screened for the constitutional BRCA1 promoter methylation by methylation-sensitive high-resolution melting assay. Overall, 131 patients displayed triple-negative BC (TNBC) and 254 non-TNBC phenotypes. The prevalence of BRCA1 promoter methylation was calculated based on clinicopathological characteristics using univariable and multivariable logistic regression models. RESULTS: Constitutional BRCA1 promoter methylation was identified in 19.5% (75/385) of BC patients and 13.1% (14/107) of controls. The frequency of methylation was higher in early-onset BC (23.4% vs. 13.1%, P = 0.035) and TNBC patients (29.0% vs. 13.1%, P = 0.004) compared to controls. Methylation was also more prevalent in patients with high-grade than low-grade tumors (21.7% vs. 12.2%, P = 0.034) and progesterone receptor (PR)-negative than PR-positive tumors (26.0% vs. 13.9%, P = 0.004). Constitutional BRCA1 promoter methylation remained independently associated with TNBC phenotype (odds ratio 1.99; 95% CI 1.12-3.54; P = 0.02) after adjusting for BC diagnosis age, tumor grade, ER, and PR status. CONCLUSION: Constitutional BRCA1 promoter methylation is associated with TNBC and can serve as a non-invasive blood-based biomarker for Pakistani TNBC patients.

Non-coding RNA-mediated endothelial-to-mesenchymal transition in human diabetic cardiomyopathy, potential regulation by DNA methylation.

AIMS: Diabetic cardiomyopathy (DCM) is a major complication of diabetes and a risk factor for cardiovascular disease. Endothelial dysfunction is central to DCM, and endothelial-to-mesenchymal transition (EndMT) is a key form of endothelial dysfunction in diabetes. EndMT in DCM has been well-studied in model systems and has been found to be epigenetically regulated by non-coding RNAs (ncRNAs). However, EndMT in DCM and its associated epigenetic changes need further characterization in human patients. It is also not known if ncRNAs are affected by changes in DNA methylation in DCM. This study aims to confirm in human hearts, the findings from animal and cell studies, and potentially provide novel insight into interactions between DNA methylation and ncRNAs in EndMT in DCM. METHODS AND RESULTS: Heart tissues were collected from autopsy patients, fixed in formalin, and embedded in paraffin. Thin sections from paraffin-embedded tissues were used for histology and immunofluorescence analyses, where we confirmed that diabetic patients showed increased cardiac fibrosis that EndMT had occurred. Tissue curls from the paraffin-embedded tissues were used for RT-qPCR and methylation analyses. RT-qPCR quantitatively showed that EndMT occurs in the hearts of diabetics, and that EndMT in human hearts corresponded to changes in key ncRNAs. Methylation analysis showed that some of the EndMT-related ncRNAs were regulated by DNA promoter methylation, while others may be regulated through different epigenetic mechanisms. CONCLUSIONS: We show that EndMT is a relevant pathological process in human hearts during DCM, and that its occurrence coincides with changes in relevant ncRNAs. We further find that interplay between DNA methylation and certain ncRNAs involved in the regulation of EndMT may contribute to the observed changes in ncRNA expression. These findings reinforce the role of EndMT in patients afflicted with DCM and underscore the complexities and importance of the interactions between different facets of epigenetic regulation.

Significance of O6-methyl guanine methyltransferase promoter methylation in high grade glioma patients: optimal cutoff point, CpG locus, and genetic assay.

PURPOSE: To evaluate O6-methyl guanine methyltransferase (MGMT) promoter methylation status in high grade glioma patients and to identify the best cutoff point as well as the most predictive CpG loci for patients survival. METHOD: Consecutive high grade glioma patients treated with surgical gross total resection followed by concomitant radiochemotherapy and adjuvant chemotherapy were included in this retrospective observational study. Methylation status of MGMT promoter CpG island of resected tumor tissue were evaluated using next generation sequencing assay. The outcomes were grouped as CpG 70-78, CpG 79-83, CpG 84-87, CpG 70-87, and whole promoter. Quantitative analyses were dichotomized as methylated or unmethylated based on the cutoff points set to %10, and methylation was further graded as <%10 unmethylated, %10-30 low-methylated, and %30-100 high-methylated. RESULTS: Total of 95 patients with the mean age of 51.50 ± 12.36 years were included in the study. Overall survival (OS) and progression free survival (PFS) were 14.53 ± 1.92 (95% CI 10.77-18.30) and 10.90 ± 2.05 (95% CI 6.89-14.92) months, respectively. MGMT promoter was methylated in 38.2% of cases and high-methylated in 10.5% of cases. Methylation status of MGMT promoter was recognized as a very powerful predictor of OS and PFS. In particular, high-methylation of CpG 79-83 and CpG 84-87 islands at promoter region were strongly associated with better survival outcomes (p < 0.05). CONCLUSION: Our outcomes support the prognostic value of MGMT promoter methylation in patients with high grade glioma. Sequencing of whole promoter CpG islands demonstrated that methylation of particular CpG sites might predict clinical outcomes more precisely.

Brain Tumor Radiogenomic Classification of O6-Methylguanine-DNA Methyltransferase Promoter Methylation in Malignant Gliomas-Based Transfer Learning.

Artificial Intelligence (AI) is the subject of a challenge and attention in the field of oncology and raises many promises for preventive diagnosis, but also fears, some of which are based on highly speculative visions for the classification and detection of tumors. A brain tumor that is malignant is a life-threatening disorder. Glioblastoma is the most prevalent kind of adult brain cancer and the 1 with the poorest prognosis, with a median survival time of less than a year. The presence of O6 -methylguanine-DNA methyltransferase (MGMT) promoter methylation, a particular genetic sequence seen in tumors, has been proven to be a positive prognostic indicator and a significant predictor of recurrence.This strong revival of interest in AI is modeled in particular to major technological advances which have significantly increased the performance of the predicted model for medical decision support. Establishing reliable forecasts remains a significant challenge for electronic health records (EHRs). By enhancing clinical practice, precision medicine promises to improve healthcare delivery. The goal is to produce improved prognosis, diagnosis, and therapy through evidence-based sub stratification of patients, transforming established clinical pathways to optimize care for each patient's individual requirements. The abundance of today's healthcare data, dubbed "big data," provides great resources for new knowledge discovery, potentially advancing precision treatment. The latter necessitates multidisciplinary initiatives that will use the knowledge, skills, and medical data of newly established organizations with diverse backgrounds and expertise.The aim of this paper is to use magnetic resonance imaging (MRI) images to train and evaluate your model to detect the presence of MGMT promoter methylation in this competition to predict the genetic subtype of glioblastoma based transfer learning. Our objective is to emphasize the basic problems in the developing disciplines of radiomics and radiogenomics, as well as to illustrate the computational challenges from the perspective of big data analytics.

Global and Regional DNA methylation silencing of PPARγ Associated with Glioblastoma Multiforme Pathogenesis.

BACKGROUND: The relationship between peroxisome proliferator-activated receptor gamma (PPARγ) expression level and epigenetic modifications occurring in glioblastoma multiforme (GBM) pathogenesis is largely unknown. Herein, we examine the association of PPARγ expression with its promoter and genomic global DNA methylation status, as well as DNA methyltransferases (DNMTs) gene expression in GBM patients. METHODS: We examined the patterns of promoter methylation and PPARγ expression in 26 GBM tissues and 13 adjacent non-tumor tissues by methylation-specific PCR (MSP), real-time PCR, and ELISA, respectively. Also, we examined the genomic global 5-methyl cytosine levels and DNMTs gene expression using ELISA and real-time PCR methods, respectively. RESULTS: We found that hypermethylation on a specific region of the PPARγ promoter is significantly associated with the downregulation of the PPARγ gene and protein level in GBM patients. Interestingly, the amount of 5-methyl cytosine level was significantly reduced in GBM patients and positively correlated with PPARγ protein expression. Furthermore, the expression level of DNMT1, DNMT3A, and 3B were upregulated in GBM patients and the average expression level of all three DNMTs was positively correlated with tumor area. Also, we found that tumors from cortical regions exhibited a higher global DNA hypomethylation and PPARγ hypermethylation was related to the increase in GBM risk. CONCLUSION: Our study demonstrated that global DNA methylation and PPARγ epigenetic silencing is associated with the GBM risk. Our data provide a novel molecular mechanistic insight into epigenetic silencing of PPARγ in GBM patients that may be relevant as a key tumor marker for GBM pathogenesis.

BRCA1 promoter methylation & its immunohistochemical correlation in sporadic breast cancer.

Background & objectives: Studies have shown that apart from hereditary breast carcinomas, breast cancer susceptibility gene 1 (BRCA1) mutations conferring to its loss are seen in sporadic breast carcinomas (SBC) as well. The aim of the present study was to assess BRCA1 methylation in females presenting at King George's Medical University, Lucknow, with SBC by both immunohistochemistry (IHC) and methylation PCR with respect to hormonal profile and various morphological prognostic parameters. The primary objective was to look for the association between BRCA1 protein expression and DNA promoter methylation. Methods: 81 mastectomy specimens from SBC of invasive breast carcinoma (no special type) were included in this study. After a detailed morphological assessment, formalin fixed paraffin embedded tissue from a representative tumour area was selected for BRCA1 IHC by heat-mediated antigen retrieval under high pH and DNA extraction and further bisulphate treatment. BRCA1 was studied for methylation by methylated and unmethylated PCR-specific primers. Results: BRCA1 promoter methylation was present in 42/81 (51.9%) participants, with significant BRCA1 protein loss (72.7%; P=0.002). A significant association between BRCA1 loss and hormonal profile was found (P=0.001); maximum in triple negative breast carcinoma (TNBC) (72%; 18/25). Most of the TNBC also harboured methylation (68%). Although not significant grade II and III tumours, lymph vascular invasion, ductal carcinoma in situ, and nodal metastasis (≥3) were seen in a higher percentage in methylated tumours. Mortality in SBC was significantly associated with BRCA1 loss (30.3%; P=0.024). Interpretation & conclusions: Study results highlight the concept of "BRCAness" in SBC as well. Hence, we can confer that identification of BRCA1 loss in SBC can make it a perfect candidate for poly ADP-ribose polymerase inhibitors or cisplatin-based therapy like hereditary ones.

Metabolomic differentiation of tumor core versus edge in glioma.

OBJECTIVE: Gliomas exhibit high intratumor and interpatient heterogeneity. Recently, it has been shown that the microenvironment and phenotype differ significantly between the glioma core (inner) and edge (infiltrating) regions. This proof-of-concept study differentiates metabolic signatures associated with these regions, with the potential for prognosis and targeted therapy that could improve surgical outcomes. METHODS: Paired glioma core and infiltrating edge samples were obtained from 27 patients after craniotomy. Liquid-liquid metabolite extraction was performed on the samples and metabolomic data were obtained via 2D liquid chromatography-mass spectrometry/mass spectrometry. To gauge the potential of metabolomics to identify clinically relevant predictors of survival from tumor core versus edge tissues, a boosted generalized linear machine learning model was used to predict metabolomic profiles associated with O6-methylguanine DNA methyltransferase (MGMT) promoter methylation. RESULTS: A panel of 66 (of 168) metabolites was found to significantly differ between glioma core and edge regions (p ≤ 0.05). Top metabolites with significantly different relative abundances included DL-alanine, creatine, cystathionine, nicotinamide, and D-pantothenic acid. Significant metabolic pathways identified by quantitative enrichment analysis included glycerophospholipid metabolism; butanoate metabolism; cysteine and methionine metabolism; glycine, serine, alanine, and threonine metabolism; purine metabolism; nicotinate and nicotinamide metabolism; and pantothenate and coenzyme A biosynthesis. The machine learning model using 4 key metabolites each within core and edge tissue specimens predicted MGMT promoter methylation status, with AUROCEdge = 0.960 and AUROCCore = 0.941. Top metabolites associated with MGMT status in the core samples included hydroxyhexanoycarnitine, spermine, succinic anhydride, and pantothenic acid, and in the edge samples metabolites included 5-cytidine monophosphate, pantothenic acid, itaconic acid, and uridine. CONCLUSIONS: Key metabolic differences are identified between core and edge tissue in glioma and, furthermore, demonstrate the potential for machine learning to provide insight into potential prognostic and therapeutic targets.

Development of A Radiomic Model for MGMT Promoter Methylation Detection in Glioblastoma Using Conventional MRI.

The methylation of the O6-methylguanine-DNA methyltransferase (MGMT) promoter is a molecular marker associated with a better response to chemotherapy in patients with glioblastoma (GB). Standard pre-operative magnetic resonance imaging (MRI) analysis is not adequate to detect MGMT promoter methylation. This study aims to evaluate whether the radiomic features extracted from multiple tumor subregions using multiparametric MRI can predict MGMT promoter methylation status in GB patients. This retrospective single-institution study included a cohort of 277 GB patients whose 3D post-contrast T1-weighted images and 3D fluid-attenuated inversion recovery (FLAIR) images were acquired using two MRI scanners. Three separate regions of interest (ROIs) showing tumor enhancement, necrosis, and FLAIR hyperintensities were manually segmented for each patient. Two machine learning algorithms (support vector machine (SVM) and random forest) were built for MGMT promoter methylation prediction from a training cohort (196 patients) and tested on a separate validation cohort (81 patients), based on a set of automatically selected radiomic features, with and without demographic variables (i.e., patients' age and sex). In the training set, SVM based on the selected radiomic features of the three separate ROIs achieved the best performances, with an average of 83.0% (standard deviation: 5.7%) for accuracy and 0.894 (0.056) for the area under the curve (AUC) computed through cross-validation. In the test set, all classification performances dropped: the best was obtained by SVM based on the selected features extracted from the whole tumor lesion constructed by merging the three ROIs, with 64.2% (95% confidence interval: 52.8-74.6%) accuracy and 0.572 (0.439-0.705) for AUC. The performances did not change when the patients' age and sex were included with the radiomic features into the models. Our study confirms the presence of a subtle association between imaging characteristics and MGMT promoter methylation status. However, further verification of the strength of this association is needed, as the low diagnostic performance obtained in this validation cohort is not sufficiently robust to allow clinically meaningful predictions.