DNA Methylation Analysis Research Articles

Identification of colon cancer subtypes based on multi-omics data-construction of methylation markers for immunotherapy.

Being the most widely used biomarker for immunotherapy, the microsatellite status has limitations in identifying all patients who benefit in clinical practice. It is essential to identify additional biomarkers to guide immunotherapy. Aberrant DNA methylation is consistently associated with changes in the anti-tumor immune response, which can promote tumor progression. This study aims to explore immunotherapy biomarkers for colon cancers from the perspective of DNA methylation. The related data (RNA sequencing data and DNA methylation data) were obtained from The Cancer Genome Atlas (TCGA) and UCSC XENA database. Methylation-driven genes (MDGs) were identified through the Pearson correlation analysis. Unsupervised consensus clustering was conducted using these MDGs to identify distinct clusters of colon cancers. Subsequently, we evaluated the immune status and predicted the efficacy of immunotherapy by tumor immune dysfunction and exclusion (Tide) score. Finally, The Quantitative Differentially Methylated Regions (QDMR) software was used to identify the specific DNA methylation markers within particular clusters. A total of 282 MDGs were identified by integrating the DNA methylation and RNA-seq data. Consensus clustering using the K-means algorithm revealed that the optimal number of clusters was 4. It was revealed that the composition of the tumor immune microenvironment (TIME) in Cluster 1 was significantly different from others, and it exhibited a higher level of tumor mutation burdens (TMB) and stronger anti-tumor immune activity. Furthermore, we identified three specific hypermethylation genes that defined Cluster 1 (PCDH20, APCDD1, COCH). Receiver operating characteristic (ROC) curves demonstrated that these specific markers could effectively distinguish Cluster 1 from other clusters, with an AUC of 0.947 (95% CI 0.903-0.990). Finally, we selected clinical samples for immunohistochemical validation. In conclusion, through the analysis of DNA methylation, consensus clustering of colon cancer could effectively identify the cluster that benefit from immunotherapy along with specific methylation biomarkers.

Downregulation of Ambra1 by altered DNA methylation exacerbates dopaminergic neuron damage in a fenpropathrin-induced Parkinson-like mouse model

Fenpropathrin (Fen), a volatile pyrethroid insecticide, is used widely for agricultural applications and has been reported to increase the risk of Parkinson’s disease (PD). However, the molecular basis, underlying mechanisms, and pathophysiology of Fen-exposed Parkinsonism remain unknown. Recent studies have revealed epigenetic mechanisms underlying PD-related pathway regulation, including DNA methylation. Epigenetic mechanisms are potential targets for therapeutic intervention in neurodegenerative diseases. After whole-genome bisulfite sequencing (WGBS) of midbrain tissues from a Fen-exposed PD-like mouse model, we performed an association analysis of DNA methylation and gene expression. Then we successfully screened for the DNA methylation differential gene Ambra1, which is closely related to PD. The hypermethylation-low expression Ambra1 gene aggravated DA neuron damage in vitro and in vivo through the Ambra1/Parkin/LC3B-mediated mitophagy pathway. We administered 5-aza-2′-deoxycytidine (5-Aza-dC) to upregulate Ambra1 expression, thereby reducing Ambra1-mediated mitophagy and protecting DA neurons against Fen-induced damage. In conclusion, these findings elucidate the potential function of Ambra1 under the regulation of DNA methylation, suggesting that the inhibition of DNA methylation may alleviate Fen-exposed neuron damage.

Unclassifiable CNS tumors in DNA methylation-based classification: clinical challenges and prognostic impact.

DNA methylation analysis has become a powerful tool in neuropathology. Although DNA methylation-based classification usually shows high accuracy, certain samples cannot be classified and remain clinically challenging. We aimed to gain insight into these cases from a clinical perspective. To address, central nervous system (CNS) tumors were subjected to DNA methylation profiling and classified according to their calibrated score using the DKFZ brain tumor classifier (V11.4) as "≥ 0.84" (score ≥ 0.84), "0.3-0.84" (score 0.3-0.84), or "< 0.3" (score < 0.3). Histopathology, patient characteristics, DNA input amount, and tumor purity were correlated. Clinical outcome parameters were time to treatment decision, progression-free, and overall survival. In 1481 patients, the classifier identified 69 (4.6%) tumors with an unreliable score as "< 0.3". Younger age (P < 0.01) and lower tumor purity (P < 0.01) compromised accurate classification. A clinical impact was demonstrated as unclassifiable cases ("< 0.3") had a longer time to treatment decision (P < 0.0001). In a subset of glioblastomas, these cases experienced an increased time to adjuvant treatment start (P < 0.001) and unfavorable survival (P < 0.025). Although DNA methylation profiling adds an important contribution to CNS tumor diagnostics, clinicians should be aware of a potentially longer time to treatment initiation, especially in malignant brain tumors.

Epigenome-wide DNA methylation analysis of late-stage mild cognitive impairment.

Background: Patients with late-stage mild cognitive impairment (LMCI) have a higher risk of progression to Alzheimer's disease (AD) than those with early-stage mild cognitive impairment (EMCI). However, previous studies have often pooled EMCI and LMCI patients into a single MCI group, with limited independent investigation into the pathogenesis of LMCI. Methods: In this study, we employed whole-genome methylation association analysis to determine the differences in peripheral blood methylation profiles between 663 cognitive aging (CN) and 554 LMCI patients. Results: Our results revealed 2,333 differentially methylated probes (DMPs) and 85 differentially methylated regions (DMRs) specific to LMCI. The top hit methylation sites or regions were associated with genes such as SNED1, histone deacetylases coding gene HDACs, and HOX and ZNF gene family. The DNA methylations upregulated the expression of HDAC4, HDAC8, and HOX family genes HOXC5 and HOXC9, but they downregulated the expression of SNED1, ADCYAP1, and ZNF family genes ZNF415 and ZNF502. Gene Ontology (GO) and KEGG analysis showed that the genes associated with these methylation sites were predominantly related to the processes of addiction disorders, neurotransmission, and neurogenesis. Out of the 554 LMCI patients included in this study, 358 subjects (65%) had progressed to AD. Further association analysis between the LMCI subjects with a stable course (sLMCI) and those who progressed to AD (pLMCI) indicated that the methylation signal intensities of HDAC6, ZNF502, HOXC5, HOXC6, and HOXD8 were associated with increased susceptibility to AD. Protective effects against progression to AD were noticed when the methylation of SNED1 and ZNF727 appeared in LMCI patients. Conclusion: Our findings highlight a substantial number of LMCI-specific methylated biomarkers that differ from those identified in previous MCI case-control studies. These biomarkers have the potential to contribute to a better understanding of the pathogenesis of LMCI.

Diagnostic utility of genetic alterations in distinguishing IDH-wildtype glioblastoma from lower-grade gliomas: Insight from next-generation sequencing analysis of 479 cases.

The accurate diagnosis and classification of gliomas are essential for appropriate treatment planning and prognosis prediction. This study aimed to investigate the molecular diagnostics of IDH-wildtype diffuse astrocytic gliomas and identify potential genetic variants that could differentiate glioblastoma (GBM) from lower-grade gliomas when DNA methylation analysis is not feasible. In total, 479 H3-and IDH-wildtype diffuse astrocytic gliomas were included in this study. All the cases were diagnosed according to the 2021 World Health Organization (WHO) classification of central nervous system (CNS) tumors. Panel sequencing data were collected, and clinicopathological information was retrieved from medical records. Genetic alterations and histological findings were analyzed to determine their diagnostic utility and prognostic implications. Out of 479 cases, 439 (91.6%) were diagnosed with GBM, including 28 cases that were molecularly diagnosed as GBM. However, 40 (8.4%) cases could not be classified according to the 2021 WHO classification and were diagnosed as lower-grade diffuse astrocytic glioma, IDH-wildtype, not elsewhere classified (LGNEC). In addition to the three genetic alterations included in the diagnostic criteria of GBM, PTEN and EGFR mutations were found to be enriched in GBM. Patients harboring mTOR pathway mutations demonstrated a more favorable prognosis and often exhibited morphology resembling subependymal giant cell astrocytoma, along with a high tumor mutational burden. Among patients with mTOR pathway mutations, those lacking molecular diagnostic features of GBM exhibited outstanding survival outcomes, even in the presence of grade 4 histology. Integration of molecular features enhanced the diagnostic accuracy of IDH-wildtype gliomas. Some molecular alterations enriched in GBM offer valuable insights for molecular diagnosis and glioma classification. Furthermore, high-grade diffuse astrocytic gliomas featuring mTOR pathway mutations in the absence of molecular diagnostic features of GBM could represent more favorable tumor types distinct from GBM.

Estimation of Human Chronological Age from Buccal Swab Samples through a DNA Methylation Analysis Approach of a Five-Locus Multiple Regression Model.

Recent advancements in forensic genetics have facilitated the extraction of additional characteristics from unidentified samples. This study delves into the predictive potential of a five-gene (ELOVL2, FHL2, KLF14, C1orf132, and TRIM59) methylation rate analysis for human age estimation using buccal swabs collected from 60 Italian volunteers. The methylation levels of specific CpG sites in the five genes were analyzed through bisulfite conversion, single-base extension, and capillary electrophoresis. A multivariate linear regression model was crafted on the training set, then the test set was employed to validate the predictive model. The multivariate predictive model revealed a mean absolute deviation of 3.49 years in the test set of our sample. While limitations include a modest sample size, the study provides valuable insights into the potential of buccal swab-based age prediction, aiding in criminal investigations where accurate age determination is crucial. Our results also highlight that it is necessary to investigate the effectiveness of predictive models specific to biological tissues and individual populations, since models already proven effective for other populations or different tissues did not show the same effectiveness in our study.

Morphology-based molecular classification of spinal cord ependymomas using deep neural networks.

Based on DNA-methylation, ependymomas growing in the spinal cord comprise two major molecular types termed spinal (SP-EPN) and myxopapillary ependymomas (MPE(-A/B)), which differ with respect to their clinical features and prognosis. Due to the existing discrepancy between histomorphogical diagnoses and classification using methylation data, we asked whether deep neural networks can predict the DNA methylation class of spinal cord ependymomas from hematoxylin and eosin stained whole-slide images. Using explainable AI, we further aimed to prospectively improve the consistency of histology-based diagnoses with DNA methylation profiling by identifying and quantifying distinct morphological patterns of these molecular ependymoma types. We assembled a case series of 139 molecularly characterized spinal cord ependymomas (nMPE = 84, nSP-EPN = 55). Self-supervised and weakly-supervised neural networks were used for classification. We employed attention analysis and supervised machine-learning methods for the discovery and quantification of morphological features and their correlation to the diagnoses of experienced neuropathologists. Our best performing model predicted the DNA methylation class with 98% test accuracy and used self-supervised learning to outperform pretrained encoder-networks (86% test accuracy). In contrast, the diagnoses of neuropathologists matched the DNA methylation class in only 83% of cases. Domain-adaptation techniques improved model generalization to an external validation cohort by up to 22%. Statistically significant morphological features were identified per molecular type and quantitatively correlated to human diagnoses. The approach was extended to recently defined subtypes of myxopapillary ependymomas (MPE-(A/B), 80% test accuracy). In summary, we demonstrated the accurate prediction of the DNA methylation class of spinal cord ependymomas (SP-EPN, MPE(-A/B)) using hematoxylin and eosin stained whole-slide images. Our approach may prospectively serve as a supplementary resource for integrated diagnostics and may even help to establish a standardized, high-quality level of histology-based diagnostics across institutions-in particular in low-income countries, where expensive DNA-methylation analyses may not be readily available.

The underlying mechanisms of DNA methylation in high salt memory in hypertensive vascular disease

This study demonstrates the effect and DNA methylation-related mechanisms of a high-salt diet and salt memory-induced hypertension and vasculopathy. Thirty Sprague Dawley rats were randomly divided into a control (CON) group (n = 6) and a modeling group (n = 24). A 12% NaCl solution (1 mL/100 g) was intragastrically administered for 60 consecutive days for modeling. An increase in blood pressure up to 140 mmHg was considered successful modeling. Twelve of fifteen successfully modeled rats were randomly selected and divided into a High Salt Diet (HSD) group and a High Salt Memory (HSM) group (n = 6). Rats in HSD group were intragastrically administered a 12% NaCl solution, while rats in HSM group were administered a 3% NaCl solution twice a day for 30 days. At the end of the intervention, blood pressure and the serum levels of ET-1, NO, TNF-α and IL-1β were measured. RRBS-heavy sulfite sequencing technology was selected for DNA methylation analysis. The systolic blood pressure of rats in the HSD group and HSM group was significantly higher than that in the CON group. Compared with those in the CON group, the serum levels of ET-1 in the HSM group and the serum levels of NO in the HSD group and HSM group were significantly increased. The methylation level of the CON group was lower than that of the HSD group and the HSM group, and there was no significant difference between the HSD group and the HSM group. The methylation level of Myoz3 was downregulated in the HSD group and HSM group. The methylation level of Fgd3 were upregulated in HSD group and downregulated in the HSM group. The methylation levels of AC095693.1, Adamts3, PDGFA and PDGFRα were downregulated in the HSD group and upregulated in the HSM group. According to the GO database, the differentially methylated genes were significantly enriched in the coordination of cell function, genetic development, and RNA transcription. There were three main metabolic pathways that were enriched in the differentially expressed genes between the groups: the PI3K-Akt signaling pathway, MAPK signaling pathway, and Hippo signaling pathway. Excessive salt intake may cause hypertension and vascular damage, and this damage may continue after the reduction of salt intake. Therefore, salt memory phenomenon exists, and this memory effect may be correlated with the levels of DNA methylation.

Joint Analysis of Genome-wide DNA Methylation and Transcription Sequencing Identifies the Role of BAX Gene in Heat Stress-Induced-Sertoli Cells Apoptosis.

The problem of male infertility is a global health crisis and poses a serious threat to the well-being of families. Under heat stress (HS), the reduction of Sertoli cells (SCs) inhibits energy transport and nutrient supply to germ cells, leading to spermatogenesis failure. DNA methylation of genes is a central epigenetic regulatory mechanism in mammalian reproduction. However, it remains unclear how DNA methylation regulates gene expression in heat-stressed SCs. In this study, we investigated whether the decrease in SC levels during HS could be related to epigenetic DNA modifications. The cells exposed to HS showed changes in differential methylation cytosines and regions (DMCs/DMRs) and differential expression genes (DEGs), but not in global DNA methylations. One of the most important biological processes affected by HS is cell apoptosis induced by the intrinsic apoptotic signaling pathway (GO: 2,001,244, P < 0.05) by enrichment in the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The joint analysis showed that several gene expressions in RNA-seq and WGBS overlapped and the shortlisted genes BAX, HSPH1, HSF1B, and BAG were strongly correlated with stress response and apoptosis. Methylation-specific PCR (MSP) and flow cytometry (FCM) analyzes showed that reduced promoter methylation and enhanced gene expression of BAX with a consequence of apoptosis. The activity of BAX, as well as an increase in its expression, is likely to result in a reduction of SCs population which could further impair ATP supply and adversely affect membrane integrity. These findings provide novel insights into the molecular mechanisms through which stressors cause male reproductive dysfunction and a new molecular etiology of male infertility.

Thirteen-gene DNA methylation analysis of oral brushing samples: A potential surveillance tool for periodic monitoring of treated patients with oral cancer.

We evaluated the prognostic role of 13-gene DNA methylation analysis by oral brushing repeatedly performed during the follow-up of patients surgically treated for oral cancer. This is a nested case-control study including 61 patients for a total of 64 outcomes (2/61 patients experienced multiple relapses). Samples were collected at baseline (4-10 months after OSCC resection) and repeatedly every 4-10 months until relapse or death. DNA methylation scores were classified as persistently positive, persistently negative, or mixed. Twenty cases who had persistently positive scores and 30 cases with mixed scores had, respectively, an almost 42-fold (p < 0.001) and 32-fold (p = 0.006) higher likelihood of relapse, compared to 14 patients with persistently negative scores. The last score before reoccurrence was positive in 18/19 secondary events. The 13-gene DNA methylation analysis may be considered for the surveillance of patients treated for oral carcinoma.

ZSCAN25 methylation predicts seizures and severe alcohol withdrawal syndrome

ABSTRACT Currently, clinicians use their judgement and indices such as the Prediction of Alcohol Withdrawal Syndrome Scale (PAWSS) to determine whether patients are admitted to hospitals for consideration of withdrawal syndrome (AWS). However, only a fraction of those admitted will experience severe AWS. Previously, we and others have shown that epigenetic indices, such as the Alcohol T-Score (ATS), can quantify recent alcohol consumption. However, whether these or other alcohol biomarkers, such as carbohydrate deficient transferrin (CDT), could identify those at risk for severe AWS is unknown. To determine this, we first conducted genome-wide DNA methylation analyses of subjects entering and exiting alcohol treatment to identify loci whose methylation quickly reverted as a function of abstinence. We then tested whether methylation at a rapidly reverting locus, cg07375256, or other existing metrics including PAWSS scores, CDT levels, or ATS, could predict outcome in 125 subjects admitted for consideration of AWS. We found that PAWSS did not significantly predict severe AWS nor seizures. However, methylation at cg07375256 (ZSCAN25) and CDT strongly predicted severe AWS with ATS (p < 0.007) and cg07375256 (p < 6 × 10–5) methylation also predicting AWS associated seizures. We conclude that epigenetic methods can predict those likely to experience severe AWS and that the use of these or similar Precision Epigenetic approaches could better guide AWS management.

Roughage quality determines the production performance of post-weaned Hu sheep via altering ruminal fermentation, morphology, microbiota, and the global methylome landscape of the rumen wall

Roughage quality is a crucial factor influencing the growth performance and feeding cost of ruminants; however, a systematic investigation of the mechanisms underlying this is still lacking. In this study, we examined the growth performance, meat quality, ruminal fermentation parameters, rumen microbiome, and tissue methylomes of post-weaned Hu sheep fed low- or high-quality forage-based diets. Our results showed that sheep in the alfalfa hay (AG) and peanut vine (PG) groups exhibited better growth performance, slaughter performance, and meat quality than sheep in the wheat straw group (WG). The sheep in the AG possessed relatively higher contents of serum immunoglobins (IgA, IgG, and IgM) and lower contents of serum inflammation factors (TNF-α, IL-1β, IL-6, and IL-8) than those in the WG and the PG did. In addition, the levels of blood T lymphocytes (CD4+ and CD8+) and the CD4-to-CD8 ratio were significantly higher in the AG sheep than in the WG sheep and PG sheep. The concentration of ruminal NH3-N was highest in WG sheep, whereas the concentrations of individual and total short-chain fatty acids (SCFAs) were highest in the PG sheep. The length, width, and surface area of ruminal papillae were markedly different among the three groups, with the sheep in the PG being the most morphologically developed. The main ruminal microbes at the genus level include Prevotella 1, Rikenellaceae RC9 gut group, norank f F082, Ruminococcus 1, and Ruminococcus 2. The relative abundances of certain species are positively or negatively associated with fermentation parameters and growth index. For example, the fibrolytic bacteria Ruminococcaceae UGG-001 showed positive relationships with the concentration of SCFAs, except propionate. In addition, the relative abundances of fibrolytic bacteria (e.g., Ruminoccus 1) showed a negative relationship with starch-degrading bacteria (e.g., Prevotellaceae). The genome-wide DNA methylation analysis revealed that rumen tissues in the PG sheep and WG sheep occupied different global DNA methylomes. The genes with differentially methylated promoters were involved in known pathways (e.g., the FoxO signaling pathway) and the Gene Ontology (GO) terms (e.g., anatomical structure morphogenesis) pertaining to rumen development. Two candidate genes (ACADL and ENSOARG00020014533) with hyper- and hypo-methylated promoters were screened as potential regulators of rumen development. In conclusion, roughage quality determines sheep growth performance via directly influencing rumen fermentation and microbiome composition, and indirectly affecting rumen development at the epigenetic level.

Integrated Analysis of DNA Methylation and Gene Expression Profiles in a Rat Model of Osteoarthritis.

Osteoarthritis (OA) is common and affected by several factors, such as age, weight, sex, and genetics. The pathogenesis of OA remains unclear. Therefore, using a rat model of monosodium iodoacetate (MIA)-induced OA, we examined genomic-wide DNA methylation using methyl-seq and characterized the transcriptome using RNA-seq in the articular cartilage tissue from a negative control (NC) and MIA-induced rats. We identified 170 genes (100 hypomethylated and upregulated genes and 70 hypermethylated and downregulated genes) regulated by DNA methylation in OA. DNA methylation-regulated genes were enriched in functions related to focal adhesion, extracellular matrix (ECM)-receptor interaction and the PI3K-Akt and Hippo signaling pathways. Functions related to extracellular matrix organization, extracellular matrix proteoglycans, and collagen formation were involved in OA. A molecular and protein-protein network was constructed using methylated expression-correlated genes. Erk1/2 was a downstream target of OA-induced changes in DNA methylation and RNA expression. We found that the integrin subunit alpha 2 (ITGA2) gene is important in focal adhesion, alpha6-beta4 integrin signaling, and the inflammatory response pathway in OA. Overall, gene expression changes because DNA methylation influences OA pathogenesis. ITGA2, whose gene expression changes are regulated by DNA methylation during OA onset, is a candidate gene. Our findings provide insights into the epigenetic targets of OA processes in rats.

DNA methylation analysis to differentiate reference, breed, and parent-of-origin effects in the bovine pangenome era.

Most DNA methylation studies have used a single reference genome with little attention paid to the bias introduced due to the reference chosen. Reference genome artifacts and genetic variation, including single nucleotide polymorphisms (SNPs) and structural variants (SVs), can lead to differences in methylation sites (CpGs) between individuals of the same species. We analyzed whole-genome bisulfite sequencing data from the fetal liver of Angus (Bos taurus taurus), Brahman (Bos taurus indicus), and reciprocally crossed samples. Using reference genomes for each breed from the Bovine Pangenome Consortium, we investigated the influence of reference genome choice on the breed and parent-of-origin effects in methylome analyses. Our findings revealed that ∼75% of CpG sites were shared between Angus and Brahman, ∼5% were breed specific, and ∼20% were unresolved. We demonstrated up to ∼2% quantification bias in global methylation when an incorrect reference genome was used. Furthermore, we found that SNPs impacted CpGs 13 times more than other autosomal sites (P < $5 \times {10}^{ - 324}$) and SVs contained 1.18 times (P < $5 \times {10}^{ - 324}$) more CpGs than non-SVs. We found a poor overlap between differentially methylated regions (DMRs) and differentially expressed genes (DEGs) and suggest that DMRs may be impacting enhancers that target these DEGs. DMRs overlapped with imprinted genes, of which 1, DGAT1, which is important for fat metabolism and weight gain, was found in the breed-specific and sire-of-origin comparisons. This work demonstrates the need to consider reference genome effects to explore genetic and epigenetic differences accurately and identify DMRs involved in controlling certain genes.

Whole-Genome Bisulfite Sequencing Protocol for the Analysis of Genome-Wide DNA Methylation and Hydroxymethylation Patterns at Single-Nucleotide Resolution.

The analysis of genome-wide epigenomic alterations including DNA methylation and hydroxymethylation has become a subject of intensive research for many biological and clinical questions. DNA methylation analysis bears the particular promise to supplement or replace biochemical and imaging-based tests for the next generation of personalized medicine. Whole-genome bisulfite sequencing (WGBS) using next-generation sequencing technologies is currently considered the gold standard for a comprehensive and quantitative analysis of DNA methylation throughout the genome. However, bisulfite conversion does not allow distinguishing between cytosine methylation and hydroxymethylation requiring an additional chemical or enzymatic step to identify hydroxymethylated cytosines. Here, we provide a detailed protocol based on a commercial kit for the preparation of sequencing libraries for the comprehensive whole-genome analysis of DNA methylation and/or hydroxymethylation. The protocol is based on the construction of sequencing libraries from limited amounts of input DNA by ligation of methylated adaptors to the fragmented DNA prior to bisulfite conversion. For analyses requiring a quantitative distinction between 5-methylcytosine and 5-hydroxymethylcytosines levels, an oxidation step is included in the same workflow to perform oxidative bisulfite sequencing (OxBs-Seq). In this case, two sequencing libraries will be generated and sequenced: a classic methylome following bisulfite conversion and analyzing modified cytosines (not distinguishing between methylated and hydroxymethylated cytosines) and a methylome analyzing only methylated cytosines, respectively. Hydroxymethylation levels are deduced from the differences between the two reactions. We also provide a step-by-step description of the data analysis using publicly available bioinformatic tools. The described protocol has been successfully applied to different human and plant samples and yields robust and reproducible results.

Transcriptomics analysis reveals distinct mechanism of breast cancer stem cells regulation in mammospheres from MCF-7 and T47D cells

Luminal A breast cancer, constituting 70 % of breast cancer cases, presents a challenge due to the development of resistance and recurrence caused by breast cancer stem cells (BCSC). Luminal breast tumors are characterized by TP53 expression, a tumor suppressor gene involved in maintaining stem cell attributes in cancer. Although a previous study successfully developed mammospheres (MS) from MCF-7 (with wild-type TP53) and T47D (with mutant TP53) luminal breast cancer cells for BCSC enrichment, their transcriptomic profiles remain unclear. We aimed to elucidate the transcriptomic disparities between MS of MCF-7 and T47D cells using bioinformatics analyses of differentially expressed genes (DEGs), including the KEGG pathway, Gene Ontology (GO), drug-gene association, disease-gene association, Gene Set Enrichment Analysis (GSEA), DNA methylation analysis, correlation analysis of DEGs with immune cell infiltration, and association analysis of genes and small-molecule compounds via the Connectivity Map (CMap). Upregulated DEGs were enriched in metabolism-related KEGG pathways, whereas downregulated DEGs were enriched in the MAPK signaling pathway. Drug-gene association analysis revealed that both upregulated and downregulated DEGs were associated with fostamatinib. The KEGG pathway GSEA results indicated that the DEGs were enriched for oxidative phosphorylation, whereas the downregulated DEGs were negatively enriched for the p53 signaling pathway. Examination of DNA methylation revealed a noticeable disparity in the expression patterns of the PKM2, ERO1L, SLC6A6, EPAS1, APLP2, RPL10L, and NEDD4 genes when comparing cohorts with low- and high-risk breast cancer. Furthermore, a significant positive correlation was identified between SLC6A6 expression and macrophage presence, as well as MSN, and AKR1B1 expression and neutrophil and dentritic cell infiltration. CMap analysis unveiled SA-83851 as a potential candidate to counteract the effects of DEGs, specifically in cells harbouring mutant TP53. Further research, including in vitro and in vivo validations, is warranted to develop drugs targeting BCSCs.

Molecular characterization of gliomas and glioneuronal tumors amid Noonan syndrome: cancer predisposition examined.

In the setting of pediatric and adolescent young adult cancer, increased access to genomic profiling has enhanced the detection of genetic variation associated with cancer predisposition, including germline syndromic conditions. Noonan syndrome (NS) is associated with the germline RAS pathway activating alterations and increased risk of cancer. Herein, we describe our comprehensive molecular profiling approach, the association of NS with glioma and glioneuronal tumors, and the clinical and histopathologic characteristics associated with the disease. Within an institutional pediatric cancer cohort (n = 314), molecular profiling comprised of paired somatic disease-germline comparator exome analysis, RNA sequencing, and tumor classification by DNA methylation analysis was performed. Through the implementation of paired analysis, this study identified 4 of 314 (1.3%) individuals who harbored a germline PTPN11 variant associated with NS, of which 3 individuals were diagnosed with a glioma or glioneuronal tumor. Furthermore, we extend this study through collaboration with a peer institution to identify two additional individuals with NS and a glioma or glioneuronal tumor. Notably, in three of five (60%) individuals, paired genomic profiling led to a previously unrecognized diagnosis of Noonan syndrome despite an average age of cancer diagnosis of 16.8 years. The study of the disease-involved tissue identified signaling pathway dysregulation through somatic alteration of genes involved in cellular proliferation, survival, and differentiation. Comparative pathologic findings are presented to enable an in-depth examination of disease characteristics. This comprehensive analysis highlights the association of gliomas and glioneuronal tumors with RASopathies and the potential therapeutic challenges and importantly demonstrates the utility of genomic profiling for the identification of germline cancer predisposition.

Pan-cancer analysis confirms the prognostic and immunological effects of prostate tumor overexpressed-1 in human cancers.

Prostate tumor overexpressed-1 (PTOV1) is a conserved oncogenic adaptor protein associated with cancer progression and may be an independent prognostic marker for several malignancies. Consequently, using pan-cancer research to explore the significance of PTOV1 is valuable, and may reveal novel targets for cancer treatment. A comprehensive bioinformatics analysis of PTOV1 was performed. The qRT-PCR was utilized to confirm the aberrant PTOV1 expression in several cancer cell lines. We observed that PTOV1 mRNA expression was high in 18 cancer tissues and was thereafter associated with poor survival prognosis in a range of malignancies. The immune subtypes of 14 malignancies and the molecular subtypes of six malignancies were related to PTOV1. A substantial association between PTOV1 and immune checkpoint (ICP) genes was also observed. Tumor mutational burden (TMB), microsatellite instability (MSI), and DNA methylation analyses indicated that PTOV1 acts as a cancer-promoting agent in a series of tumors. In addition, an enrichment study of PTOV1 and related genes revealed that RNA splicing may be responsible for the involvement of PTOV1 in cancers. Lastly, we also verified that PTOV1 expression was elevated in bladder cancer, breast cancer, CESC, LIHC cell lines via qRT-PCR. Our bioinformatics research indicated that PTOV1 may be involved in tumor immunity. Furthermore, differentially expressed PTOV1 was found to be related to poor prognosis in cancers, and RNA splicing may be the specific mechanism for this effect. Therefore, PTOV1 mRNA and the corresponding protein may function as potential prognostic indicators and therapeutic targets in various cancers.

Combination Analysis of PCDHGA12 and CDO1 DNA Methylation in Bronchial Washing Fluid for Lung Cancer Diagnosis.

When suspicious lesions are observed on computer-tomography (CT), invasive tests are needed to confirm lung cancer. Compared with other procedures, bronchoscopy has fewer complications. However, the sensitivity of peripheral lesion through bronchoscopy including washing cytology is low. A new test with higher sensitivity through bronchoscopy is needed. In our previous study, DNA methylation of PCDHGA12 in bronchial washing cytology has a diagnostic value for lung cancer. In this study, combination of PCDHGA12 and CDO1 methylation obtained through bronchial washing cytology was evaluated as a diagnostic tool for lung cancer. A total of 187 patients who had suspicious lesions in CT were enrolled. PCDHGA12 methylation test, CDO1 methylation test, and cytological examination were performed using 3-plex LTE-qMSP test. Sixty-two patients were diagnosed with benign diseases and 125 patients were diagnosed with lung cancer. The sensitivity of PCDHGA12 was 74.4% and the specificity of PCDHGA12 was 91.9% respectively. CDO1 methylation test had a sensitivity of 57.6% and a specificity of 96.8%. The combination of both PCDHGA12 methylation test and CDO1 methylation test showed a sensitivity of 77.6% and a specificity of 90.3%. The sensitivity of lung cancer diagnosis was increased by combining both PCDHGA12 and CDO1 methylation tests. Checking DNA methylation of both PCDHGA12 and CDO1 genes using bronchial washing fluid can reduce the invasive procedure to diagnose lung cancer.

Poor control of oxidative stress index is associated with increased DNA methylation in retinopathy patients of a sample from babylonian population

Abstract Background: Retinopathy is one of almost insidious advanced neuron-vascular complications of diabetes, oneof the most common complications that lead to permanent visual impairment in the middle-aged population. Objectives: The study investigated the association between poor oxidative stress index and DNA methylation. Materials and Methods: The study included 120 participants, of whom 40 were healthy, 40 patients with retinopathy, and 40 non-retinopathy diabetes patients (type 2 diabetes mellitus (T2DM)). The total antioxidant, capacity (TAC) evaluated using Cupric ion reducing antioxidant capacity method. Reactive oxygen species (ROS) was measured using Erel method. Global DNA methylation has measured employing 5 mC% estimating using MethylFlash™ Methylated DNA Quantification Kit. Results: Current investigation indicated significant (P ≤ 0.05) accrue in TAC, ROSs, and oxidative stress index (OSI) in diabetic compared with controls. In addition, a significant (P ≤ 0.05) increase of ROSs and OSI were recorded in retinopathy compared with T2DM patients was reported. The analysis of global DNA methylation revealed that diabetic patients have a significantly (P ≤ 0.05) more 5 mC% as compared with healthy subjects. Also, the present study showed a significant rise in methylation in retinopathy compared as with T2DM patients. Regarding the correlation analysis, the current study conducted significantly (P &lt; 0.05) positive association between DNA methylation and each of the ROSs and OSI. Also, a significant positive correlation was reported between DNA methylation and ROSs and OSI in retinopathy and T2DM. Conclusion: Global DNA methylation has an increased level in patients and could be engaged with emergence and progress of retinopathy in diabetic with poor control of oxidative stress and increased ROSs.