DNA methylation in cancer: too much, but also too little

Comparison of the classifiers based on mRNA, microRNA and lncRNA expression and DNA methylation profiles for the tumor origin detection

Background

Tumor tissue origin detection is of great importance in determining the appropriate course of treatment for cancer patients. Classifiers based on gene expression and DNA methylation profiles have been confirmed to be feasible and reliable to predict the tumor primary. However, few works have been performed to compare the performance of these classifiers based on different profiles.

Methods

Using gene expression and DNA methylation profiles from The Cancer Genome Atlas (TCGA) project, eight machine learning methods were employed for the tumor tissue origin detection. We then evaluated the predictive performance using DNA methylation, mRNA, microRNA (miRNA) and long non-coding RNA (lncRNA) expression profiles in a comparative manner. A statistical method was introduced to select the most informative CpG sites.

Results

We found that LASSO is the most predictive models based on various profiles. Further analyses indicated that the results derived from DNA methylation (overall accuracy: 97.77%) are better than those derived from mRNA expression (overall accuracy: 88.01%), microRNA expression (overall accuracy: 91.03%) and lncRNA expression (overall accuracy: 95.7%). It has been suggested that we can achieve an overall accuracy >90% using only 1,000 methylated CpG sites for prediction.

Conclusion

In this work, we comprehensively evaluated the performance of classifiers based on different profiles for the tumor origin detection. Our findings demonstrated the effectiveness of DNA methylation as biomarker for tracing tumor tissue origin using LASSO and neural network.

Overexpression of Hypermethylated Homeobox A11 (HOXA11) Inhibits Tumor Cell Growth and Induces Apoptosis in Cervical Cancer

This study aimed to elucidate the potential of Homeobox A11 (HOXA11) as a therapeutic target and a diagnostic methylation marker for cervical cancer. Gene expression analysis using cDNA microarray in cervical cancer cell lines revealed significantly reduced expression of the HOXA11 gene. Subsequent investigation of HOXA11 promoter methylation in samples from normal individuals and invasive cervical cancer patients showed over 53.2% higher methylation in cancer scrapes compared to normal scrapes. Furthermore, overexpression of HOXA11, which is downregulated in cervical cancer, strongly suppressed cell growth in cervical cancer cell lines, HeLa and HT3. Additionally, we performed transferase dUTP nick end labeling assay and confirmed that the inhibition of cervical cancer cell proliferation occurred via apoptosis. Mechanistically, overexpression of HOXA11 led to mitochondrial apoptosis characterized by PARP cleavage due to increased c-Myc and enhanced cytochrome C secretion into the cytoplasm. These findings suggest that HOXA11 could potentially serve as a methylation marker for diagnosing cervical cancer and as a novel therapeutic target for its treatment.

Promoter hypermethylation as a novel regulator of ANO1 expression and function in prostate cancer bone metastasis

Despite growing evidence implicating the calcium-activated chloride channel anoctamin1 (ANO1) in cancer metastasis, its direct impact on the metastatic potential of prostate cancer and the possible significance of epigenetic alteration in this process are not fully understood. Here, we show that ANO1 is minimally expressed in LNCap and DU145 prostate cancer cell lines with low metastatic potential but overexpressed in high metastatic PC3 prostate cancer cell line. The treatment of LNCap and DU145 cells with DNMT inhibitor 5-aza-2'-deoxycytidine (5-Aza-CdR) potentiates ANO1 expression, suggesting that DNA methylation is one of the mechanisms controlling ANO1 expression. Consistent with this notion, hypermethylation was detected at the CpG island of ANO1 promoter region in LNCap and DU145 cells, and 5-Aza-CdR treatment resulted in a drastic demethylation at promoter CpG methylation sites. Upon 5-Aza-CdR treatment, metastatic indexes, such as cell motility, invasion, and metastasis-related gene expression, were significantly altered in LNCap and DU145 cells. These 5-Aza-CdR-induced metastatic hallmarks were, however, almost completely ablated by stable knockdown of ANO1. These in vitro discoveries were further supported by our in vivo observation that ANO1 expression in xenograft mouse models enhances the metastatic dissemination of prostate cancer cells into tibial bone and the development of osteolytic lesions. Collectively, our results help elucidate the critical role of ANO1 expression in prostate cancer bone metastases, which is epigenetically modulated by promoter CpG methylation.

Unveiling Alterations of Epigenetic Modifications and Chromatin Architecture Leading to Lipid Metabolic Reprogramming during the Evolutionary Trastuzumab Adaptation of HER2-Positive Breast Cancer

Secondary trastuzumab resistance represents an evolutionary adaptation of HER2-positive breast cancer during anti-HER2 treatment. Most current studies have tended to prioritize HER2 and its associated signaling pathways, often overlooking broader but seemingly less relevant cellular processes, along with their associated genetic and epigenetic mechanisms. Here, transcriptome data is not only characterized but also examined epigenomic and 3D genome architecture information in both trastuzumab-sensitive and secondary-resistant breast cancer cells. The findings reveal that the global metabolic reprogramming associated with trastuzumab resistance may stem from genome-wide alterations in both histone modifications and chromatin structure. Specifically, the transcriptional activities of key genes involved in lipid metabolism appear to be regulated by variant promoter H3K27me3 and H3K4me3 modifications, as well as promoter-enhancer interactions. These discoveries offer valuable insights into how cancer cells adapt to anti-tumor drugs and have the potential to impact future diagnostic and treatment strategies.

Effects of folate deficiency and sex on carcinogenesis in a mouse model of oral cancer

OBJECTIVES

To investigate the effects of dietary folate and sex on histopathology of oral squamous cell carcinoma in mice.

MATERIALS AND METHODS

Mice (C57Bl/6, 30/sex) were fed either a deficient folate or sufficient folate diet. Vehicle or 4-nitroquinoline1-oxide (50 μg/mL) in vehicle were administered in drinking water for 20 weeks, followed by 6 weeks of regular drinking water. Oral lesions were observed weekly. Tongues were studied for histopathologic changes. Immunohistochemical techniques were used to measure cell proliferation (Ki67+), and to quantify expression of folate receptor, reduced folate carrier, and proton-coupled folate transporter. T cells, macrophages, and neutrophils were counted and normalized to area.

RESULTS

All 4NQO-treated mice developed oral tumors. Dietary folate level did not affect tumor burden. More tumors were observed on the ventral aspect of the tongue than in other locations within the oral cavity. 4-nitroquinoline-1-oxide-treated mice displayed 27%-46% significantly lower expression of all three folate transport proteins; diet and sex had no effect on folate transporter expression. T-cell and neutrophil infiltration in tongues were 9.1-fold and 18.1-fold increased in the 4-nitroquinoline-1-oxide-treated mouse tongues than in controls.

CONCLUSION

Treatment with 4NQO was the primary factor in determining cancer development, decreased folate transport expression, and lymphoid cell infiltration.

Conserved methylation signatures associate with the tumor immune microenvironment and immunotherapy response

BACKGROUND

Aberrant DNA methylation is a major characteristic of cancer genomes. It remains unclear which biological processes determine epigenetic reprogramming and how these processes influence the variants in the cancer methylome, which can further impact cancer phenotypes.

METHODS

We performed pairwise permutations of 381,900 loci in 569 paired DNA methylation profiles of cancer tissue and matched normal tissue from The Cancer Genome Atlas (TCGA) and defined conserved differentially methylated positions (DMPs) based on the resulting null distribution. Then, we derived independent methylation signatures from 2,465 cancer-only methylation profiles from the TCGA and 241 cell line-based methylation profiles from the Genomics of Drug Sensitivity in Cancer (GDSC) cohort using nonnegative matrix factorization (NMF). We correlated DNA methylation signatures with various clinical and biological features, including age, survival, cancer stage, tumor immune microenvironment factors, and immunotherapy response. We inferred the determinant genes of these methylation signatures by integrating genomic and transcriptomic data and evaluated the impact of these signatures on cancer phenotypes in independent bulk and single-cell RNA/methylome cohorts.

RESULTS

We identified 7,364 differentially methylated positions (2,969 Hyper-DMPs and 4,395 Hypo-DMPs) in nine cancer types from the TCGA. We subsequently retrieved three highly conserved, independent methylation signatures (Hyper-MS1, Hypo-MS1, and Hypo-MS4) from cancer tissues and cell lines based on these Hyper and Hypo-DMPs. Our data suggested that Hypo-MS4 activity predicts poor survival and is associated with immunotherapy response and distant tumor metastasis, and Hypo-MS4 activity is related to TP53 mutation and FOXA1 binding specificity. In addition, we demonstrated a correlation between the activities of Hypo-MS4 in cancer cells and the fractions of regulatory CD4 + T cells with the expression levels of immunological genes in the tumor immune microenvironment.

CONCLUSIONS

Our findings demonstrated that the methylation signatures of distinct biological processes are associated with immune activity in the cancer microenvironment and predict immunotherapy response.

Epigenetic programming of host lipid metabolism associates with resistance to TST/IGRA conversion after exposure to Mycobacterium tuberculosis

Mycobacterium tuberculosis (Mtb) exposure leads to a range of outcomes including clearance, latent TB infection (LTBI), and pulmonary tuberculosis (TB). Some heavily exposed individuals resist tuberculin skin test (TST) and interferon gamma release assay (IGRA) conversion (RSTR), which suggests that they employ IFNγ-independent mechanisms of Mtb control. Here, we compare monocyte epigenetic profiles of RSTR and LTBI from a Ugandan household contact cohort. Chromatin accessibility did not differ between uninfected RSTR and LTBI monocytes. In contrast, methylation significantly differed at 174 CpG sites and across 63 genomic regions. Consistent with previous transcriptional findings in this cohort, differential methylation was enriched in lipid and cholesterol associated pathways including in the genes APOC3, KCNQ1, and PLA2G3. In addition, methylation was enriched in Hippo signaling, which is associated with cholesterol homeostasis and includes CIT and SHANK2. Lipid export and Hippo signaling pathways were also associated with gene expression in response to Mtb in RSTR as well as IFN stimulation in monocyte-derived macrophages (MDMs) from an independent healthy donor cohort. Moreover, serum-derived HDL from RSTR had elevated ABCA1-mediated cholesterol efflux capacity (CEC) compared to LTBI. Our findings suggest that resistance to TST/IGRA conversion is linked to regulation of lipid accumulation in monocytes, which could facilitate early Mtb clearance among RSTR subjects through IFNγ-independent mechanisms.

Reconstruction of cell-specific models capturing the influence of metabolism on DNA methylation in cancer

The imbalance of epigenetic regulatory mechanisms such as DNA methylation, which can promote aberrant gene expression profiles without affecting the DNA sequence, may cause the deregulation of signaling, regulatory, and metabolic processes, contributing to a cancerous phenotype. Since some metabolites are substrates and cofactors of epigenetic regulators, their availability can be affected by characteristic cancer cell metabolic shifts, feeding cancer onset and progression through epigenetic deregulation. Hence, there is a need to study the influence of cancer metabolic reprogramming in DNA methylation to design new effective treatments. In this study, a generic Genome-Scale Metabolic Model (GSMM) of a human cell, integrating DNA methylation or demethylation reactions, was obtained and used for the reconstruction of Genome-Scale Metabolic Models enhanced with Enzymatic Constraints using Kinetic and Omics data (GECKOs) of 31 cancer cell lines. Furthermore, cell-line-specific DNA methylation levels were included in the models, as coefficients of a DNA composition pseudo-reaction, to depict the influence of metabolism over global DNA methylation in each of the cancer cell lines. Flux simulations demonstrated the ability of these models to provide simulated fluxes of exchange reactions similar to the equivalent experimentally measured uptake/secretion rates and to make good functional predictions. In addition, simulations found metabolic pathways, reactions and enzymes directly or inversely associated with the gene promoter methylation. Two potential candidates for targeted cancer epigenetic therapy were identified.

Regucalcin downregulation in human cancer

Regucalcin is a unique calcium-binding protein first discovered in rat liver in 1978. Regucalcin has multiple functions as an inhibitor of various cellular signaling pathways that regulate cell activity. The expression of the regucalcin gene can be altered by various physiological and pathological factors such as diet (nutrients), hormones, diabetes, alcohol and drugs. Several transcription factors have been identified on the regucalcin gene, including AP-1, NF1-A1, RGPR-p117, β-catenin, NF-κB, STAT3 and hypoxia-inducible factor-1α (HIF-1α). Notably, regucalcin plays an important role in the development of several cancers by controlling cell growth. Clinically, many studies have reported that the expression of the regucalcin gene is downregulated in various human cancers. In addition, higher expression of regucalcin in tumor tissue has been associated with longer patient survival, suggesting that regucalcin may act as a potential suppressor of various types of human cancer. Regucalcin may offer a novel therapeutic strategy and diagnostic tool for cancer treatment. However, the underlying mechanism by which regucalcin expression is reduced in human cancer is still unclear. A deeper understanding of regucalcin reduction and function in cancer is needed to discover potential resistance mechanisms and biomarkers, and to improve regucalcin-targeting agents. We review recent findings on regucalcin gene expression in cancer. We discuss the possible mechanisms by which regucalcin expression is downregulated in cancer cells to facilitate understanding of how regucalcin regulates cell growth function. This mini-review may lead to better therapeutic targets with regucalcin.

A signal processing and deep learning framework for methylation detection using Oxford Nanopore sequencing

Oxford Nanopore sequencing can detect DNA methylations from ionic current signal of single molecules, offering a unique advantage over conventional methods. Additionally, adaptive sampling, a software-controlled enrichment method for targeted sequencing, allows reduced representation methylation sequencing that can be applied to CpG islands or imprinted regions. Here we present DeepMod2, a comprehensive deep-learning framework for methylation detection using ionic current signal from Nanopore sequencing. DeepMod2 implements both a bidirectional long short-term memory (BiLSTM) model and a Transformer model and can analyze POD5 and FAST5 signal files generated on R9 and R10 flowcells. Additionally, DeepMod2 can run efficiently on central processing unit (CPU) through model pruning and can infer epihaplotypes or haplotype-specific methylation calls from phased reads. We use multiple publicly available and newly generated datasets to evaluate the performance of DeepMod2 under varying scenarios. DeepMod2 has comparable performance to Guppy and Dorado, which are the current state-of-the-art methods from Oxford Nanopore Technologies that remain closed-source. Moreover, we show a high correlation (r = 0.96) between reduced representation and whole-genome Nanopore sequencing. In summary, DeepMod2 is an open-source tool that enables fast and accurate DNA methylation detection from whole-genome or adaptive sequencing data on a diverse range of flowcell types.

Epigenetic alterations fuel brain metastasis via regulating inflammatory cascade

Brain metastasis (BrM) is a major threat to the survival of melanoma, breast, and lung cancer patients. Circulating tumor cells (CTCs) cross the blood-brain barrier (BBB) and sustain in the brain microenvironment. Genetic mutations and epigenetic modifications have been found to be critical in controlling key aspects of cancer metastasis. Metastasizing cells confront inflammation and gradually adapt in the unique brain microenvironment. Currently, it is one of the major areas that has gained momentum. Researchers are interested in the factors that modulate neuroinflammation during BrM. We review here various epigenetic factors and mechanisms modulating neuroinflammation and how this helps CTCs to adapt and survive in the brain microenvironment. Since epigenetic changes could be modulated by targeting enzymes such as histone/DNA methyltransferase, deacetylases, acetyltransferases, and demethylases, we also summarize our current understanding of potential drugs targeting various aspects of epigenetic regulation in BrM.

Nanopore-based DNA long-read sequencing analysis of the aged human brain

Aging disrupts cellular processes such as DNA repair and epigenetic control, leading to a gradual buildup of genomic alterations that can have detrimental effects in post-mitotic cells. Genomic alterations in regions of the genome that are rich in repetitive sequences, often termed "dark loci," are difficult to resolve using traditional sequencing approaches. New long-read technologies offer promising avenues for exploration of previously inaccessible regions of the genome. Using nanopore-based long-read whole-genome sequencing of DNA extracted from aged 18 human brains, we identify previously unreported structural variants and methylation patterns within repetitive DNA, focusing on transposable elements ("jumping genes") as crucial sources of variation, particularly in dark loci. Our analyses reveal potential somatic insertion variants and provides DNA methylation frequencies for many retrotransposon families. We further demonstrate the utility of this technology for the study of these challenging genomic regions in brains affected by Alzheimer's disease and identify significant differences in DNA methylation in pathologically normal brains versus those affected by Alzheimer's disease. Highlighting the power of this approach, we discover specific polymorphic retrotransposons with altered DNA methylation patterns. These retrotransposon loci have the potential to contribute to pathology, warranting further investigation in Alzheimer's disease research. Taken together, our study provides the first long-read DNA sequencing-based analysis of retrotransposon sequences, structural variants, and DNA methylation in the aging brain affected with Alzheimer's disease neuropathology.

Large-Scale Machine Learning Analysis Reveals DNA Methylation and Gene Expression Response Signatures for Gemcitabine-Treated Pancreatic Cancer

Background: Gemcitabine is a first-line chemotherapy for pancreatic adenocarcinoma (PAAD), but many PAAD patients do not respond to gemcitabine-containing treatments. Being able to predict such nonresponders would hence permit the undelayed administration of more promising treatments while sparing gemcitabine life-threatening side effects for those patients. Unfortunately, the few predictors of PAAD patient response to this drug are weak, none of them exploiting yet the power of machine learning (ML). Methods: Here, we applied ML to predict the response of PAAD patients to gemcitabine from the molecular profiles of their tumors. More concretely, we collected diverse molecular profiles of PAAD patient tumors along with the corresponding clinical data (gemcitabine responses and clinical features) from the Genomic Data Commons resource. From systematically combining 8 tumor profiles with 16 classification algorithms, each of the resulting 128 ML models was evaluated by multiple 10-fold cross-validations. Results: Only 7 of these 128 models were predictive, which underlines the importance of carrying out such a large-scale analysis to avoid missing the most predictive models. These were here random forest using 4 selected mRNAs [0.44 Matthews correlation coefficient (MCC), 0.785 receiver operating characteristic-area under the curve (ROC-AUC)] and XGBoost combining 12 DNA methylation probes (0.32 MCC, 0.697 ROC-AUC). By contrast, the hENT1 marker obtained much worse random-level performance (practically 0 MCC, 0.5 ROC-AUC). Despite not being trained to predict prognosis (overall and progression-free survival), these ML models were also able to anticipate this patient outcome. Conclusions: We release these promising ML models so that they can be evaluated prospectively on other gemcitabine-treated PAAD patients.

Colorectal cancer with low SLC35A3 is associated with immune infiltrates and poor prognosis

The expression level of SLC35A3 is associated with the prognosis of many cancers, but its role in colorectal cancer (CRC) is unclear. The purpose of our study was to elucidate the role of SLC35A3 in CRC. The expression levels of SLC35A3 in CRC were evaluated through tumor immune resource assessment (TIMER), The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), International Cancer Genome Consortium (ICGC), Human Protein Atlas (HPA), qRT-PCR, and immunohistochemical evaluation. TCGA, GEO, and ICGC databases were used to analyze the diagnostic and prognostic value of SLC35A3 in CRC. A overall survival (OS) model was constructed and validated based on the expression level of SLC35A3 and multivariable analysis results. The cBioPortal tool was used to analyze SLC35A3 mutation in CRC. The UALCAN tool was used to analyze the promoter methylation level of SLC35A3 in colorectal cancer. In addition, the role of SLC35A3 in CRC was determined through GO analysis, KEGG analysis, gene set enrichment analysis (GSEA), immune infiltration analysis, and immune checkpoint correlation analysis. In vitro experiments validated the function of SLC35A3 in colorectal cancer cells. Compared with adjacent normal tissues and colonic epithelial cells, the expression of SLC35A3 was decreased in CRC tissues and CRC cell lines. Low expression of SLC35A3 was associated with N stage, pathological stage, and lymphatic infiltration, and it was unfavorable for OS, disease-specific survival (DSS), recurrence-free survival (RFS), and post-progression survival (PPS). According to the Receiver Operating Characteristic (ROC) analysis, SLC35A3 is a potential important diagnostic biomarker for CRC patients. The nomograph based on the expression level of SLC35A3 showed a better predictive model for OS than single prognostic factors and TNM staging. SLC35A3 has multiple types of mutations in CRC, and its promoter methylation level is significantly decreased. GO and KEGG analysis indicated that SLC35A3 may be involved in transmembrane transport protein activity, cell communication, and interaction with neurotransmitter receptors. GSEA revealed that SLC35A3 may be involved in energy metabolism, DNA repair, and cancer pathways. In addition, SLC35A3 was closely related to immune cell infiltration and immune checkpoint expression. Immunohistochemistry confirmed the positive correlation between SLC35A3 and helper T cell infiltration. In vitro experiments showed that overexpression of SLC35A3 inhibited the proliferation and invasion capability of colorectal cancer cells and promoted apoptosis. The results of this study indicate that decreased expression of SLC35A3 is closely associated with poor prognosis and immune cell infiltration in colorectal cancer, and it can serve as a promising independent prognostic biomarker and potential therapeutic target.

Deep learning-based age estimation from chest CT scans

PURPOSE

Medical imaging can be used to estimate a patient's biological age, which may provide complementary information to clinicians compared to chronological age. In this study, we aimed to develop a method to estimate a patient's age based on their chest CT scan. Additionally, we investigated whether chest CT estimated age is a more accurate predictor of lung cancer risk compared to chronological age.

METHODS

To develop our age prediction model, we utilized composite CT images and Inception-ResNet-v2. The model was trained, validated, and tested on 13,824 chest CT scans from the National Lung Screening Trial, with 91% for training, 5% for validation, and 4% for testing. Additionally, we independently tested the model on 1849 CT scans collected locally. To assess chest CT estimated age as a risk factor for lung cancer, we computed the relative lung cancer risk between two groups. Group 1 consisted of individuals assigned a CT age older than their chronological age, while Group 2 comprised those assigned a CT age younger than their chronological age.

RESULTS

Our analysis revealed a mean absolute error of 1.84 years and a Pearson's correlation coefficient of 0.97 for our local data when comparing chronological age with the estimated CT age. The model showed the most activation in the area associated with the lungs during age estimation. The relative risk for lung cancer was 1.82 (95% confidence interval, 1.65-2.02) for individuals assigned a CT age older than their chronological age compared to those assigned a CT age younger than their chronological age.

CONCLUSION

Findings suggest that chest CT age captures some aspects of biological aging and may be a more accurate predictor of lung cancer risk than chronological age. Future studies with larger and more diverse patients are required for the generalization of the interpretations.

Blood-based DNA methylation in advanced Nasopharyngeal Carcinoma exhibited distinct CpG methylation signature

The TNM staging system is currently used to detect cancer stages. Regardless, a small proportion of cancer patients recur even after therapy, suggesting more specific molecular tools are required to justify the stage-specific detection and prompt cancer diagnosis. Thus, we aimed to explore the blood-based DNA methylation signature of metastatic nasopharyngeal carcinoma (NPC) to establish a holistic methylation biomarker panel. For the identification of methylation signature, the EPIC BeadChip-based array was performed. Comparative analysis for identifying unique probes, validation, and functional studies was investigated by analyzing GEO and TCGA datasets. We observed 4093 differentially methylated probes (DMPs), 1232 hydroxymethylated probes, and 25 CpG islands. Gene expression study revealed both upregulated and downregulated genes. Correlation analysis suggested a positive (with a positive r, p ≤ 0.05) and negative (with a negative r, p ≤ 0.05) association with different cancers. TFBS analysis exhibited the binding site for many TFs. Furthermore, gene enrichment analysis indicated the involvement of those identified genes in biological pathways. However, blood-based DNA methylation data uncovered a distinct DNA methylation pattern, which might have an additive role in NPC progression by altering the TFs binding. Moreover, based on tissue-specificity, a variation of correlation between methylation and gene expression was noted in different cancers.

Targeting epigenetic deregulations for the management of esophageal carcinoma: recent advances and emerging approaches

Ranking from seventh in incidence to sixth in mortality, esophageal carcinoma is considered a severe malignancy of food pipe. Later-stage diagnosis, drug resistance, and a high mortality rate contribute to its lethality. Esophageal squamous cell carcinoma and esophageal adenocarcinoma are the two main histological subtypes of esophageal carcinoma, with squamous cell carcinoma alone accounting for more than eighty percent of its cases. While genetic anomalies are well known in esophageal cancer, accountability of epigenetic deregulations is also being explored for the recent two decades. DNA methylation, histone modifications, and functional non-coding RNAs are the crucial epigenetic players involved in the modulation of different malignancies, including esophageal carcinoma. Targeting these epigenetic aberrations will provide new insights into the development of biomarker tools for risk stratification, early diagnosis, and effective therapeutic intervention. This review discusses different epigenetic alterations, emphasizing the most significant developments in esophageal cancer epigenetics and their potential implication for the detection, prognosis, and treatment of esophageal carcinoma. Further, the preclinical and clinical status of various epigenetic drugs has also been reviewed.

Towards system genetics analysis of head and neck squamous cell carcinoma using the mouse model, cellular platform, and clinical human data

Head and neck squamous cell cancer (HNSCC) is a leading global malignancy. Every year, More than 830 000 people are diagnosed with HNSCC globally, with more than 430 000 fatalities. HNSCC is a deadly diverse malignancy with many tumor locations and biological characteristics. It originates from the squamous epithelium of the oral cavity, oropharynx, nasopharynx, larynx, and hypopharynx. The most frequently impacted regions are the tongue and larynx. Previous investigations have demonstrated the critical role of host genetic susceptibility in the progression of HNSCC. Despite the advances in our knowledge, the improved survival rate of HNSCC patients over the last 40 years has been limited. Failure to identify the molecular origins of development of HNSCC and the genetic basis of the disease and its biological heterogeneity impedes the development of new therapeutic methods. These results indicate a need to identify more genetic factors underlying this complex disease, which can be better used in early detection and prevention strategies. The lack of reliable animal models to investigate the underlying molecular processes is one of the most significant barriers to understanding HNSCC tumors. In this report, we explore and discuss potential research prospects utilizing the Collaborative Cross mouse model and crossing it to mice carrying single or double knockout genes (e.g. Smad4 and P53 genes) to identify genetic factors affecting the development of this complex disease using genome-wide association studies, epigenetics, microRNA, long noncoding RNA, lncRNA, histone modifications, methylation, phosphorylation, and proteomics.

Methylation of hypoxia-inducible factor 3 subunit alpha contributes to poor prognosis in lung adenocarcinoma

Hypoxia-inducible factor 3 subunit alpha (HIF3A) has been implicated in various types of cancers, while its precise role in the lung adenocarcinoma remains unclear. Our study aimed to investigate the roles of HIF3A in lung adenocarcinoma and its regulation by DNA methylation. We utilized bioinformatic tools, including UALCAN and KMPlot, to analyze the relationship between HIF3A expression, DNA methylation, and patient survival rate in lung adenocarcinoma. We also used siRNA-mediated knockdown of HIF3A and DNA-methyltransferase 1 (DNMT1), as well as the treatment of DNA methylation inhibitor 5-Azacytidine, in A549 and H1299 lung adenocarcinoma cell lines. qPCR, MTT, and cell counting assays were performed to evaluate the mRNA expression and cell viability. The bioinformatic analysis revealed that HIF3A expression was downregulated and its methylation was upregulated in lung tumor tissues. Additionally, Kaplan-Meier analysis indicated a correlation between low HIF3A expression and patient poor survival rate. We found that DNMT1 regulated HIF3A methylation. Knockdown of HIF3A promoted cancer cell proliferation. These data suggest that downregulation of HIF3A promotes tumor cell proliferation, and support that HIF3A methylation may serve as a prognostic factor for lung adenocarcinoma.

Epigenetic and transcriptional regulation of the human angiotensinogen gene by high salt

Hypertension is caused by a combination of genetic and environmental factors. Angiotensinogen (AGT) is a component of RAAS, that regulates blood pressure. The human angiotensinogen (hAGT) gene has -6A/-6G polymorphism and -6A variant is associated with human hypertension. In this study, we have investigated the epigenetic regulation of the hAGT. To understand transcriptional regulation of the hAGT, we have made transgenic animals containing -6A. We show that HS affects DNA methylation and modulates transcriptional regulation of this gene in liver and kidney. High salt (HS) increases hAGT gene expression in -6A TG mice. We have observed that the number of CpG sites in the hAGT promoter is decreased after HS treatment. In the liver, seven CpG sites are methylated whereas after HS treatment, only three CpG sites remain methylated. In the kidney, five CpG sites are methylated, whereas after HS treatment, only three CpG sites remain methylated. These results suggest that HS promotes DNA demethylation and increasing AGT gene expression. RT-PCR and immunoblot analysis show that hAGT gene expression is increased by HS. Chip assay has shown that transcription factors bind strongly after HS treatment. RNA-Seq identified differentially expressed genes, novel target genes associated with hypertension, top canonical pathways, upstream regulators. One of the plausible mechanisms for HS induced up-regulation of the hAGT gene is through IL-6/JAK/STAT3/AGT axis.

Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization

Despite their promise, circulating tumor DNA (ctDNA)-based assays for multi-cancer early detection face challenges in test performance, due mostly to the limited abundance of ctDNA and its inherent variability. To address these challenges, published assays to date demanded a very high-depth sequencing, resulting in an elevated price of test. Herein, we developed a multimodal assay called SPOT-MAS (screening for the presence of tumor by methylation and size) to simultaneously profile methylomics, fragmentomics, copy number, and end motifs in a single workflow using targeted and shallow genome-wide sequencing (~0.55×) of cell-free DNA. We applied SPOT-MAS to 738 non-metastatic patients with breast, colorectal, gastric, lung, and liver cancer, and 1550 healthy controls. We then employed machine learning to extract multiple cancer and tissue-specific signatures for detecting and locating cancer. SPOT-MAS successfully detected the five cancer types with a sensitivity of 72.4% at 97.0% specificity. The sensitivities for detecting early-stage cancers were 73.9% and 62.3% for stages I and II, respectively, increasing to 88.3% for non-metastatic stage IIIA. For tumor-of-origin, our assay achieved an accuracy of 0.7. Our study demonstrates comparable performance to other ctDNA-based assays while requiring significantly lower sequencing depth, making it economically feasible for population-wide screening.

Significant increase of high-risk chromosome 1q gain and 6q loss at recurrence in posterior fossa group A ependymoma: A multicenter study

BACKGROUND

Ependymoma (EPN) posterior fossa group A (PFA) has the highest rate of recurrence and the worst prognosis of all EPN molecular groups. At relapse, it is typically incurable even with re-resection and re-irradiation. The biology of recurrent PFA remains largely unknown; however, the increasing use of surgery at first recurrence has now provided access to clinical samples to facilitate a better understanding of this.

METHODS

In this large longitudinal international multicenter study, we examined matched samples of primary and recurrent disease from PFA patients to investigate the biology of recurrence.

RESULTS

DNA methylome derived copy number variants (CNVs) revealed large-scale chromosome gains and losses at recurrence in PFA. CNV changes were dominated by chromosome 1q gain and/or 6q loss, both previously identified as high-risk factors in PFA, which were present in 23% at presentation but increased to 61% at first recurrence. Multivariate survival analyses of this cohort showed that cases with 1q gain or 6q loss at first recurrence were significantly more likely to recur again. Predisposition to 1q+/6q- CNV changes at recurrence correlated with hypomethylation of heterochromatin-associated DNA at presentation. Cellular and molecular analyses revealed that 1q+/6q- PFA had significantly higher proportions of proliferative neuroepithelial undifferentiated progenitors and decreased differentiated neoplastic subpopulations.

CONCLUSIONS

This study provides clinically and preclinically actionable insights into the biology of PFA recurrence. The hypomethylation predisposition signature in PFA is a potential risk-classifier for trial stratification. We show that the cellular heterogeneity of PFAs evolves largely because of genetic evolution of neoplastic cells.

Predicting regional somatic mutation rates using DNA motifs

How the locus-specificity of epigenetic modifications is regulated remains an unanswered question. A contributing mechanism is that epigenetic enzymes are recruited to specific loci by DNA binding factors recognizing particular sequence motifs (referred to as epi-motifs). Using these motifs to predict biological outputs depending on local epigenetic state such as somatic mutation rates would confirm their functionality. Here, we used DNA motifs including known TF motifs and epi-motifs as a surrogate of epigenetic signals to predict somatic mutation rates in 13 cancers at an average 23kbp resolution. We implemented an interpretable neural network model, called contextual regression, to successfully learn the universal relationship between mutations and DNA motifs, and uncovered motifs that are most impactful on the regional mutation rates such as TP53 and epi-motifs associated with H3K9me3. Furthermore, we identified genomic regions with significantly higher mutation rates than the expected values in each individual tumor and demonstrated that such cancer-related regions can accurately predict cancer types. Interestingly, we found that the same mutation signatures often have different contributions to cancer-related and cancer-independent regions, and we also identified the motifs with the most contribution to each mutation signature.

Pan-cancer analysis: SPAG5 is an immunological and prognostic biomarker for multiple cancers

Sperm-associated antigen 5 (SPAG5) is a mitotic spindle protein that regulates the separation of sister chromatids into daughter cells. Recent studies have discovered its overexpression in various cancers, suggesting its oncogenic characteristics and functions. However, a comprehensive analysis of SPAG5 regarding its diagnostic, prognostic, and immune-related effects across different cancer types is lacking. In this study, we employed bioinformatics methods and integrated multiple public databases to explore the potential oncogenic role of SPAG5. We analyzed its expression, prognosis, related chemicals, enriched pathways, immune infiltration, and its impact on different tumor genetic alterations. The results revealed that SPAG5 is highly expressed in most cancers and significantly correlates with poor patient prognosis. Additionally, SPAG5 expression showed potential for early cancer diagnosis in 15 different cancer types. In terms of tumor immunity, high expression of SPAG5 was associated with an immunosuppressive tumor microenvironment and immune therapy efficacy indicators. SPAG5 expression exhibited a negative correlation with most immune cell infiltrates but demonstrated a significant positive correlation with Th2 cells and MDSC cells. Multicolor fluorescence immunohistochemistry demonstrated that SPAG5 activates immune cell populations within tumors, indicating its significant role in the tumor microenvironment. Enrichment analysis indicated that SPAG5-related genes are mainly involved in cell cycle, cellular senescence, P53 signaling pathway, and FoxO signaling pathway. Furthermore, we confirmed the high expression of SPAG5 in cancer cells and observed that its knockdown upregulated the expression of the p53 protein. In conclusion, SPAG5 holds value as a diagnostic, prognostic, and immune biomarker in various cancers and may provide a novel target for tumor immunotherapy.

capTEs enables locus-specific dissection of transcriptional outputs from reference and nonreference transposable elements

Transposable elements (TEs) serve as both insertional mutagens and regulatory elements in cells, and their aberrant activity is increasingly being revealed to contribute to diseases and cancers. However, measuring the transcriptional consequences of nonreference and young TEs at individual loci remains challenging with current methods, primarily due to technical limitations, including short read lengths generated and insufficient coverage in target regions. Here, we introduce a long-read targeted RNA sequencing method, Cas9-assisted profiling TE expression sequencing (capTEs), for quantitative analysis of transcriptional outputs for individual TEs, including transcribed nonreference insertions, noncanonical transcripts from various transcription patterns and their correlations with expression changes in related genes. This method selectively identified TE-containing transcripts and outputted data with up to 90% TE reads, maintaining a comparable data yield to whole-transcriptome sequencing. We applied capTEs to human cancer cells and found that internal and inserted Alu elements may employ distinct regulatory mechanisms to upregulate gene expression. We expect that capTEs will be a critical tool for advancing our understanding of the biological functions of individual TEs at the locus level, revealing their roles as both mutagens and regulators in biological and pathogenic processes.

Tuning Methylation-Dependent Silencing Dynamics by Synthetic Modulation of CpG Density

Methylation of cytosines in CG dinucleotides (CpGs) within promoters has been shown to lead to gene silencing in mammals in natural contexts. Recently, engineered recruitment of methyltransferases (DNMTs) at specific loci was shown to be sufficient to silence synthetic and endogenous gene expression through this mechanism. A critical parameter for DNA methylation-based silencing is the distribution of CpGs within the target promoter. However, how the number or density of CpGs in the target promoter affects the dynamics of silencing by DNMT recruitment has remained unclear. Here, we constructed a library of promoters with systematically varying CpG content, and analyzed the rate of silencing in response to recruitment of DNMT. We observed a tight correlation between silencing rate and CpG content. Further, methylation-specific analysis revealed a constant accumulation rate of methylation at the promoter after DNMT recruitment. We identified a single CpG site between TATA box and transcription start site (TSS) that accounted for a substantial part of the difference in silencing rates between promoters with differing CpG content, indicating that certain residues play disproportionate roles in controlling silencing. Together, these results provide a library of promoters for synthetic epigenetic and gene regulation applications, as well as insights into the regulatory link between CpG content and silencing rate.

DNA methylation profiling to determine the primary sites of metastatic cancers using formalin-fixed paraffin-embedded tissues

Identifying the primary site of metastatic cancer is critical to guiding the subsequent treatment. Approximately 3-9% of metastatic patients are diagnosed with cancer of unknown primary sites (CUP) even after a comprehensive diagnostic workup. However, a widely accepted molecular test is still not available. Here, we report a method that applies formalin-fixed, paraffin-embedded tissues to construct reduced representation bisulfite sequencing libraries (FFPE-RRBS). We then generate and systematically evaluate 28 molecular classifiers, built on four DNA methylation scoring methods and seven machine learning approaches, using the RRBS library dataset of 498 fresh-frozen tumor tissues from primary cancer patients. Among these classifiers, the beta value-based linear support vector (BELIVE) performs the best, achieving overall accuracies of 81-93% for identifying the primary sites in 215 metastatic patients using top-k predictions (k = 1, 2, 3). Coincidentally, BELIVE also successfully predicts the tissue of origin in 81-93% of CUP patients (n = 68).

Integrative multi-omic cancer profiling reveals DNA methylation patterns associated with therapeutic vulnerability and cell-of-origin

DNA methylation plays a critical role in establishing and maintaining cellular identity. However, it is frequently dysregulated during tumor development and is closely intertwined with other genetic alterations. Here, we leveraged multi-omic profiling of 687 tumors and matched non-involved adjacent tissues from the kidney, brain, pancreas, lung, head and neck, and endometrium to identify aberrant methylation associated with RNA and protein abundance changes and build a Pan-Cancer catalog. We uncovered lineage-specific epigenetic drivers including hypomethylated FGFR2 in endometrial cancer. We showed that hypermethylated STAT5A is associated with pervasive regulon downregulation and immune cell depletion, suggesting that epigenetic regulation of STAT5A expression constitutes a molecular switch for immunosuppression in squamous tumors. We further demonstrated that methylation subtype-enrichment information can explain cell-of-origin, intra-tumor heterogeneity, and tumor phenotypes. Overall, we identified cis-acting DNA methylation events that drive transcriptional and translational changes, shedding light on the tumor's epigenetic landscape and the role of its cell-of-origin.

Genome-Wide DNA Methylation and Gene Expression in Patients with Indolent Systemic Mastocytosis

Mastocytosis is a clinically heterogenous, usually acquired disease of the mast cells with a survival time that depends on the time of onset. It ranges from skin-limited to systemic disease, including indolent and more aggressive variants. The presence of the oncogenic KIT p. D816V gene somatic mutation is a crucial element in the pathogenesis. However, further epigenetic regulation may also affect the expression of genes that are relevant to the pathology. Epigenetic alterations are responsible for regulating the expression of genes that do not modify the DNA sequence. In general, it is accepted that DNA methylation inhibits the binding of transcription factors, thereby down-regulating gene expression. However, so far, little is known about the epigenetic factors leading to the clinical onset of mastocytosis. Therefore, it is essential to identify possible epigenetic predictors, indicators of disease progression, and their link to the clinical picture to establish appropriate management and a therapeutic strategy. The aim of this study was to analyze genome-wide methylation profiles to identify differentially methylated regions (DMRs) in patients with mastocytosis compared to healthy individuals, as well as the genes located in those regulatory regions. Genome-wide DNA methylation profiling was performed in peripheral blood collected from 80 adult patients with indolent systemic mastocytosis (ISM), the most prevalent subvariant of mastocytosis, and 40 healthy adult volunteers. A total of 117 DNA samples met the criteria for the bisulfide conversion step and microarray analysis. Genome-wide DNA methylation analysis was performed using a MethylationEPIC BeadChip kit. Further analysis was focused on the genomic regions rather than individual CpG sites. Co-methylated regions (CMRs) were assigned via the CoMeBack method. To identify DMRs between the groups, a linear regression model with age as the covariate on CMRs was performed using Limma. Using the available data for cases only, an association analysis was performed between methylation status and tryptase levels, as well as the context of allergy, and anaphylaxis. KEGG pathway mapping was used to identify genes differentially expressed in anaphylaxis. Based on the DNA methylation results, the expression of 18 genes was then analyzed via real-time PCR in 20 patients with mastocytosis and 20 healthy adults. A comparison of the genome-wide DNA methylation profile between the mastocytosis patients and healthy controls revealed significant differences in the methylation levels of 85 selected CMRs. Among those, the most intriguing CMRs are 31 genes located within the regulatory regions. In addition, among the 10 CMRs located in the promoter regions, 4 and 6 regions were found to be either hypo- or hypermethylated, respectively. Importantly, three oncogenes-FOXQ1, TWIST1, and ERG-were identified as differentially methylated in mastocytosis patients, for the first time. Functional annotation revealed the most important biological processes in which the differentially methylated genes were involved as transcription, multicellular development, and signal transduction. The biological process related to histone H2A monoubiquitination (GO:0035518) was found to be enriched in association with higher tryptase levels, which may be associated with more aberrant mast cells and, therefore, more atypical mast cell disease. The signal in the BAIAP2 gene was detected in the context of anaphylaxis, but no significant differential methylation was found in the context of allergy. Furthermore, increased expression of genes encoding integral membrane components (GRM2 and KRTCAP3) was found in mastocytosis patients. This study confirms that patients with mastocytosis differ significantly in terms of methylation levels in selected CMRs of genes involved in specific molecular processes. The results of gene expression profiling indicate the increased expression of genes belonging to the integral component of the membrane in mastocytosis patients (GRM2 and KRTCAP3). Further work is warranted, especially in relation to the disease subvariants, to identify links between the methylation status and the symptoms and novel therapeutic targets.

Hyperhomocysteinaemia Promotes Doxorubicin-Induced Cardiotoxicity in Mice

Doxorubicin, a widely used chemotherapeutic drug in clinical oncology, causes a series of cardiac side effects referred to as doxorubicin-induced cardiotoxicity. Hyperhomocysteinaemia is an independent risk factor for multiple cardiovascular diseases. However, whether hyperhomocysteinaemia contributes to doxorubicin-induced cardiotoxicity is currently unknown. In this study, we explored the pathogenic effects of hyperhomocysteinaemia induced by dietary methionine supplementation (2% wt/wt in rodent chow) in a mouse model of doxorubicin-induced cardiotoxicity. Our data showed that methionine supplementation doubled serum homocysteine levels, inducing mild hyperhomocysteinaemia. Doxorubicin at a cumulative dosage of 25 mg/kg body weight led to significant weight loss and severe cardiac dysfunction, which were further exacerbated by methionine-induced mild hyperhomocysteinaemia. Doxorubicin-induced cardiac atrophy, cytoplasmic vacuolisation, myofibrillar disarray and loss, as well as cardiac fibrosis, were also exacerbated by methionine-induced mild hyperhomocysteinaemia. Additional folic acid supplementation (0.006% wt/wt) prevented methionine-induced hyperhomocysteinaemia and inhibited hyperhomocysteinaemia-aggravated cardiac dysfunction and cardiomyopathy. In particular, hyperhomocysteinaemia increased both serum and cardiac oxidative stress, which could all be inhibited by folic acid supplementation. Therefore, we demonstrated for the first time that hyperhomocysteinaemia could exacerbate doxorubicin-induced cardiotoxicity in mice, and the pathogenic effects of hyperhomocysteinaemia might at least partially correlate with increased oxidative stress and could be prevented by folic acid supplementation. Our study provides preliminary experimental evidence for the assessment of hyperhomocysteinaemia as a potential risk factor for chemotherapy-induced cardiotoxicity in cancer patients.

Downregulation of DNA methylation enhances differentiation of THP-1 cells and induces M1 polarization of differentiated macrophages

DNA methylation is an epigenetic modification that regulates gene expression and plays an essential role in hematopoiesis. UHRF1 and DNMT1 are both crucial for regulating genome-wide maintenance of DNA methylation. Specifically, it is well known that hypermethylation is crucial characteristic of acute myeloid leukemia (AML). However, the mechanism underlying how DNA methylation regulates the differentiation of AML cells, including THP-1 is not fully elucidated. In this study, we report that UHRF1 or DNMT1 depletion enhances the phorbol-12-myristate-13-acetate (PMA)-induced differentiation of THP-1 cells. Transcriptome analysis and genome-wide methylation array results showed that depleting UHRF1 or DNMT1 induced changes that made THP-1 cells highly sensitive to PMA. Furthermore, knockdown of UHRF1 or DNMT1 impeded solid tumor formation in xenograft mouse model. These findings suggest that UHRF1 and DNMT1 play a pivotal role in regulating differentiation and proliferation of THP-1 cells and targeting these proteins may improve the efficiency of differentiation therapy in AML patients.

Identification of potential DNA methylation biomarkers related to diagnosis in patients with bladder cancer through integrated bioinformatic analysis

BACKGROUND

Bladder cancer (BLCA) is one of the most common malignancies among tumors worldwide. There are no validated biomarkers to facilitate such treatment diagnosis. DNA methylation modification plays important roles in epigenetics. Identifying methylated differentially expressed genes is a common method for the discovery of biomarkers.

METHODS

Bladder cancer data were obtained from Gene Expression Omnibus (GEO), including the gene expression microarrays GSE37817( 18 patients and 3 normal ), GSE52519 (9 patients and 3 normal) and the gene methylation microarray GSE37816 (18 patients and 3 normal). Aberrantly expressed genes were obtained by GEO2R. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were analyzed using the DAVID database and KOBAS. Protein-protein interactions (PPIs) and hub gene networks were constructed by STRING and Cytoscape software. The validation of the results which was confirmed through four online platforms, including Gene Expression Profiling Interactive Analysis (GEPIA), Gene Set Cancer Analysis (GSCA), cBioProtal and MEXPRESS.

RESULTS

In total, 253 and 298 upregulated genes and 674 and 454 downregulated genes were identified for GSE37817 and GSE52519, respectively. For the GSE37816 dataset, hypermethylated and hypomethylated genes involving 778 and 3420 genes, respectively, were observed. Seventeen hypermethylated and low expression genes were enriched in biological processes associated with different organ development and morphogenesis. For molecular function, these genes showed enrichment in extracellular matrix structural constituents. Pathway enrichment showed drug metabolic enzymes and several amino acids metabolism, PI3K-Akt, Hedgehog signaling pathway. The top 3 hub genes screened by Cytoscape software were EFEMP1, SPARCL1 and ABCA8. The research results were verified using the GEPIA, GSCA, cBioProtal and EXPRESS databases, and the hub hypermethylated low expression genes were validated.

CONCLUSION

This study screened possible aberrantly methylated expression hub genes in BLCA by integrated bioinformatics analysis. The results may provide possible methylation-based biomarkers for the precise diagnosis and treatment of BLCA in the future.

Epigenome-wide methylation analysis of colorectal carcinoma, adenoma and normal tissue reveals novel biomarkers addressing unmet clinical needs

BACKGROUND

Biomarker discovery in colorectal cancer has mostly focused on methylation patterns in normal and colorectal tumor tissue, but adenomas remain understudied. Therefore, we performed the first epigenome-wide study to profile methylation of all three tissue types combined and to identify discriminatory biomarkers.

RESULTS

Public methylation array data (Illumina EPIC and 450K) were collected from a total of 1 892 colorectal samples. Pairwise differential methylation analyses between tissue types were performed for both array types to "double evidence" differentially methylated probes (DE DMPs). Subsequently, the identified DMPs were filtered on methylation level and used to build a binary logistic regression prediction model. Focusing on the clinically most interesting group (adenoma vs carcinoma), we identified 13 DE DMPs that could effectively discriminate between them (AUC = 0.996). We validated this model in an in-house experimental methylation dataset of 13 adenomas and 9 carcinomas. It reached a sensitivity and specificity of 96% and 95%, respectively, with an overall accuracy of 96%. Our findings raise the possibility that the 13 DE DMPs identified in this study can be used as molecular biomarkers in the clinic.

CONCLUSIONS

Our analyses show that methylation biomarkers have the potential to discriminate between normal, precursor and carcinoma tissues of the colorectum. More importantly, we highlight the power of the methylome as a source of markers for discriminating between colorectal adenomas and carcinomas, which currently remains an unmet clinical need.

Normal gastric tissue Helicobacter pylori infection is associated with epigenetic age acceleration, increased mitotic tick rate, tissue cell composition, and Natural Killer cell methylation alterations

Background

Gastric adenocarcinomas are a leading cause of global mortality, associated with chronic infection with Helicobacter pylori. The mechanisms by which infection with H. pylori contributes to carcinogenesis are not well understood. Recent studies from subjects with and without gastric cancer have identified significant DNA methylation alterations in normal gastric mucosa associated with H. pylori infection and gastric cancer risk. Here we further investigated DNA methylation alterations in normal gastric mucosa in gastric cancer cases (n = 42) and control subjects (n = 42) with H. pylori infection data. We assessed tissue cell type composition, DNA methylation alterations within cell populations, epigenetic aging, and repetitive element methylation.

Results

In normal gastric mucosa of both gastric cancer cases and control subjects, we observed increased epigenetic age acceleration associated with H. pylori infection. We also observed an increased mitotic tick rate associated with H. pylori infection in both gastric cancer cases and controls. Significant differences in immune cell populations associated with H. pylori infection in normal tissue from cancer cases and controls were identified using DNA methylation cell type deconvolution. We also found natural killer cell-specific methylation alterations in normal mucosa from gastric cancer patients with H. pylori infection.

Conclusions

Our findings from normal gastric mucosa provide insight into underlying cellular composition and epigenetic aspects of H. pylori associated gastric cancer etiology.

Occurrence of L1M Elements in Chromosomal Rearrangements Associated to Chronic Myeloid Leukemia (CML): Insights from Patient-Specific Breakpoints Characterization

Chronic myeloid leukemia (CML) is a rare myeloproliferative disorder caused by the reciprocal translocation t(9;22)(q34;q11) in hematopoietic stem cells (HSCs). This chromosomal translocation results in the formation of an extra-short chromosome 22, called a Philadelphia chromosome (Ph), containing the BCR-ABL1 fusion gene responsible for the expression of a constitutively active tyrosine kinase that causes uncontrolled growth and replication of leukemic cells. Mechanisms behind the formation of this chromosomal rearrangement are not well known, even if, as observed in tumors, repetitive DNA may be involved as core elements in chromosomal rearrangements. We have participated in the explorative investigations of the PhilosoPhi34 study to evaluate residual Ph+ cells in patients with negative FISH analysis on CD34+/lin- cells with gDNA qPCR. Using targeted next-generation deep sequencing strategies, we analyzed the genomic region around the t(9;22) translocations of 82 CML patients and one CML cell line and assessed the relevance of interspersed repeat elements at breakpoints (BP). We found a statistically higher presence of LINE elements, in particular belonging to the subfamily L1M, in BP cluster regions of both chromosome 22 and 9 compared to the whole human genome. These data suggest that L1M elements could be potential drivers of t(9;22) translocation leading to the generation of the BCR-ABL1 chimeric gene and the expression of the active BCR-ABL1-controlled tyrosine kinase chimeric protein responsible for CML.

The transposable element-derived transcript of LIN28B has a placental origin and is not specific to tumours

Transposable elements (TEs) are genetic elements that have evolved as crucial regulators of human development and cancer, functioning as both genes and regulatory elements. When TEs become dysregulated in cancer cells, they can serve as alternate promoters to activate oncogenes, a process known as onco-exaptation. This study aimed to explore the expression and epigenetic regulation of onco-exaptation events in early human developmental tissues. We discovered co-expression of some TEs and oncogenes in human embryonic stem cells and first trimester and term placental tissues. Previous studies identified onco-exaptation events in various cancer types, including an AluJb SINE element-LIN28B interaction in lung cancer cells, and showed that the TE-derived LIN28B transcript is associated with poor patient prognosis in hepatocellular carcinoma. This study further characterized the AluJb-LIN28B transcript and confirmed that its expression is restricted to the placenta. Targeted DNA methylation analysis revealed differential methylation of the two LIN28B promoters between placenta and healthy somatic tissues, indicating that some TE-oncogene interactions are not cancer-specific but arise from the epigenetic reactivation of developmental TE-derived regulatory events. In conclusion, our findings provide evidence that some TE-oncogene interactions are not limited to cancer and may originate from the epigenetic reactivation of TE-derived regulatory events that are involved in early development. These insights broaden our understanding of the role of TEs in gene regulation and suggest the potential importance of targeting TEs in cancer therapy beyond their conventional use as cancer-specific markers.

Tuning methylation-dependent silencing dynamics by synthetic modulation of CpG density

Methylation of cytosines in CG dinucleotides (CpGs) within promoters has been shown to lead to gene silencing in mammals in natural contexts. Recently, engineered recruitment of methyltransferases (DNMTs) at specific loci was shown to be sufficient to silence synthetic and endogenous gene expression through this mechanism. A critical parameter for DNA methylation-based silencing is the distribution of CpGs within the target promoter. However, how the number or density of CpGs in the target promoter affects the dynamics of silencing by DNMT recruitment has remained unclear. Here we constructed a library of promoters with systematically varying CpG content, and analyzed the rate of silencing in response to recruitment of DNMT. We observed a tight correlation between silencing rate and CpG content. Further, methylation-specific analysis revealed a constant accumulation rate of methylation at the promoter after DNMT recruitment. We identified a single CpG site between TATA box and transcription start site (TSS) that accounted for a substantial part of the difference in silencing rates between promoters with differing CpG content, indicating that certain residues play disproportionate roles in controlling silencing. Together, these results provide a library of promoters for synthetic epigenetic and gene regulation applications, as well as insights into the regulatory link between CpG content and silencing rate.

Multimodal analysis of genome-wide methylation, copy number aberrations, and end motif signatures enhances detection of early-stage breast cancer

Introduction

Breast cancer causes the most cancer-related death in women and is the costliest cancer in the US regarding medical service and prescription drug expenses. Breast cancer screening is recommended by health authorities in the US, but current screening efforts are often compromised by high false positive rates. Liquid biopsy based on circulating tumor DNA (ctDNA) has emerged as a potential approach to screen for cancer. However, the detection of breast cancer, particularly in early stages, is challenging due to the low amount of ctDNA and heterogeneity of molecular subtypes.

Methods

Here, we employed a multimodal approach, namely Screen for the Presence of Tumor by DNA Methylation and Size (SPOT-MAS), to simultaneously analyze multiple signatures of cell free DNA (cfDNA) in plasma samples of 239 nonmetastatic breast cancer patients and 278 healthy subjects.

Results

We identified distinct profiles of genome-wide methylation changes (GWM), copy number alterations (CNA), and 4-nucleotide oligomer (4-mer) end motifs (EM) in cfDNA of breast cancer patients. We further used all three signatures to construct a multi-featured machine learning model and showed that the combination model outperformed base models built from individual features, achieving an AUC of 0.91 (95% CI: 0.87-0.95), a sensitivity of 65% at 96% specificity.

Discussion

Our findings showed that a multimodal liquid biopsy assay based on analysis of cfDNA methylation, CNA and EM could enhance the accuracy for the detection of early- stage breast cancer.

The pan-cancer analysis of the oncogenic role of FAM72A as a BRCA prognostic biomarker and immunotherapeutic target

In this study, we first comprehensively investigated the expression profile, mutation status, and survival analysis of FAM72A as well as the correlation between FAM72A and DNA damage repair, methylation, and cell stemness analysis using bioinformatics techniques. In addition, we also analyzed the relationship between FAM72A and immune cell infiltration and pathway enrichment. The role of FAM72A in breast cancer (BC) was so conspicuous that we analyzed the prognostic significance and clinicopathological parameter's relevance of FAM72A in BC. We also validated biological functions by applying in vitro experiments. FAM72A was highly expressed in 26 types of a total of 31 cancers, while it expressed low levels in only five cancers. FAM72A expression was relative to clinical stages in nine cancers and has a significant difference in disease-free survival among 31 kinds of cancers. In addition, FAM72A has negatively correlated with cancer-associated fibroblast and endothelial cells in BC but positively correlated with follicular helper T cells. Univariate and multivariate cox regression analyses identified T, N, M, age, and FAM72A expression as independent influences on BC prognosis, so we created a nomogram to predict patient survival benefits. In in vitro experiments, we verified that downregulation of FAM72A not only inhibited cell proliferation, colony formation, cell migration, cell invasion, and G2/M cell cycle transition but also promoted apoptosis of breast invasive carcinoma cells. Our study discovered FAM72A as a clinically meaningful biomarker for prognostic predicting and a guiding target for immune treatment in BC.

Epigenetic Signatures in Hypertension

Clear epigenetic signatures were found in hypertensive and pre-hypertensive patients using DNA methylation data and neural networks in a classification algorithm. It is shown how by selecting an appropriate subset of CpGs it is possible to achieve a mean accuracy classification of 86% for distinguishing control and hypertensive (and pre-hypertensive) patients using only 2239 CpGs. Furthermore, it is also possible to obtain a statistically comparable model achieving an 83% mean accuracy using only 22 CpGs. Both of these approaches represent a substantial improvement over using the entire amount of available CpGs, which resulted in the neural network not generating accurate classifications. An optimization approach is followed to select the CpGs to be used as the base for a model distinguishing between hypertensive and pre-hypertensive individuals. It is shown that it is possible to find methylation signatures using machine learning techniques, which can be applied to distinguish between control (healthy) individuals, pre-hypertensive individuals and hypertensive individuals, illustrating an associated epigenetic impact. Identifying epigenetic signatures might lead to more targeted treatments for patients in the future.

Epigenetic Alterations from Barrett's Esophagus to Esophageal Adenocarcinoma

Barrett's esophagus (BE) is a disease entity that is a sequela of chronic gastroesophageal reflux disease that may result in esophageal adenocarcinoma (EAC) due to columnar epithelial dysplasia. The histological degree of dysplasia is the sole biomarker frequently utilized by clinicians. However, the cost of endoscopy and the fact that the degree of dysplasia does not progress in many patients with BE diminish the effectiveness of histological grading as a perfect biomarker. Multiple or more quantitative biomarkers are required by clinicians since early diagnosis is crucial in esophageal adenocancers, which have a high mortality rate. The presence of epigenetic factors in the early stages of this neoplastic transformation holds promise as a predictive biomarker. In this review, current studies on DNA methylations, histone modifications, and noncoding RNAs (miRNAs) that have been discovered during the progression from BE dysplasia to EAC were collated.

Analysis of endometrial carcinoma TCGA reveals differences in DNA methylation in tumors from Black and White women

OBJECTIVE

Racial disparities exist in cancer patients both in incidence and death rates. In endometrial cancer, Black patients are reported to have higher incidence of aggressive endometrial cancer subtypes and higher death rates than White women. To date, diagnostic and prognostic biomarkers associated with race-specific methylation driven genes have yet to be identified. The objective of this study was to explore DNA methylation patterns in endometrial tumor samples from White and Black women.

METHODS

Differentially methylated CpGs (DMCs) and differentially methylated regions (DMRs) were identified in White tumor samples compared to Black tumor samples using Endometrial Carcinoma (EC) methylation and clinical data from The Cancer Genome Atlas (TCGA). Survival analysis was performed using survival R package and results were visualized using Kaplan-Meier plots. To access the correlation between changes in methylation and gene expression, we downloaded raw RNA-sequencing by Expectation-Maximization (RSEM) counts data from The Cancer Genome Atlas (TCGA) using TCGABiolinks package (v2.18.0).

RESULTS

Our analysis revealed 704 differentially methylated CpGs in tumors from Black and White women. These differentially methylated genes showed strong negative correlation with gene expression and statistically significant enrichment in regulatory regions such as DNase I hypersensitivity sites (DHSs) and transcription factor binding sites (TFBSs). Increased variability in methylation occurred in genes such as the insulin signaling pathway in Black tumor samples.

CONCLUSION

By using two independent statistical method based on means (DMR, DMCs) and variances (DVCs) on the endometrial carcinoma TCGA data, we showed that endometrial tumors from Black women are hypomethylated and more hypervariable than tumors from White women. In-depth investigation of these methylation driven markers can aid in successful management of endometrial cancer disparities and improved overall survival in Black and White populations.

Global DNA methylation and increased DNMT3A expression in multiple myeloma patients

AIMS

The aim of this study was to compare the expression profile of selected DNA methyltransferases and global DNA methylation status in patients with different phases of multiple myeloma (MM) . For the analysis, different cellular populations including unsorted myeloma cells and a set of plasma cells purified by relevant antibodies were used. Consequently, laboratory data were compared to patients' clinical data.

PATIENTS AND METHODS

For the analysis, unsorted bone marrow cell population of 44 MM patients (30 newly diagnosed, 9 relapsed and 5 patients in remission) and a set of 8 patients' samples of sorted plasma cells were used. We used commercially available RNA isolated from BM of 3 healthy individuals as control samples. Expression analysis of three DNA methyltransferases - DNMT1, DNMT3A, and DNMT3B was performed by quantitative RT-PCR and the patient global DNA methylation profiles were detected by colorimetric assay.

RESULTS

Unchanged DNMT1 expression was detected in the selected cohort of patients. Normalized DNMT3A gene expression was globally higher in comparison with controls in unsorted and sorted cell populations. Low (0.08-1.81%) global DNA methylation status in unsorted samples of multiple myeloma patients did not correlate either with expression profiles of monitored DNA methyltransferases or with the stages of MM based on Durie-Salmon and International Staging System.

CONCLUSION

This is the first comparative study between DNA methyltransferases expression profiles and global DNA methylation status in different phases of multiple myeloma patients. No significant correlation between the level of global methylation and the clinical stage of the unsorted cell population of patients with multiple myeloma was registered. Overexpression of the DNMT3A gene occurred in both sorted and unsorted cell populations of patients with multiple myeloma. This fact highlights the DNMT3A as a potential marker of multiple myeloma tumor progression. Moreover, we demonstrated comparable results in the expression of DNA methyltransferases in both sorted and unsorted cell populations. This is a promising result from the methodical point of view because when compared to samples of unsorted multiple myeloma cells, samples of sorted cells bring reduction of the number of possible analyses performed.

Psoriatic Resolved Skin Epidermal Keratinocytes Retain Disease-Residual Transcriptomic and Epigenomic Profiles

The disease-residual transcriptomic profile (DRTP) within psoriatic healed/resolved skin and epidermal tissue-resident memory T (TRM) cells have been proposed to be crucial for the recurrence of old lesions. However, it is unclear whether epidermal keratinocytes are involved in disease recurrence. There is increasing evidence regarding the importance of epigenetic mechanisms in the pathogenesis of psoriasis. Nonetheless, the epigenetic changes that contribute to the recurrence of psoriasis remain unknown. The aim of this study was to elucidate the role of keratinocytes in psoriasis relapse. The epigenetic marks 5-methylcytosine (5-mC) and 5-hydroxymethylcytosine (5-hmC) were visualized using immunofluorescence staining, and RNA sequencing was performed on paired never-lesional and resolved epidermal and dermal compartments of skin from psoriasis patients. We observed diminished 5-mC and 5-hmC amounts and decreased mRNA expression of the ten-eleven translocation (TET) 3 enzyme in the resolved epidermis. SAMHD1, C10orf99, and AKR1B10: the highly dysregulated genes in resolved epidermis are known to be associated with pathogenesis of psoriasis, and the DRTP was enriched in WNT, TNF, and mTOR signaling pathways. Our results suggest that epigenetic changes detected in epidermal keratinocytes of resolved skin may be responsible for the DRTP in the same regions. Thus, the DRTP of keratinocytes may contribute to site-specific local relapse.

Fucosyltransferases Regulated by Fusobacterium Nucleatum and Act as Novel Biomarkers in Colon Adenocarcinoma

Purpose

Colon adenocarcinoma (COAD) is one of the leading causes of cancer-associated mortality worldwide. Fucosyltransferases (FUTs) are associated with numerous cancers. We aimed to investigate the functions of FUTs in COAD.

Patients and Methods

Transcriptomic and clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were used to analyze the expression and clinical relevance of FUTs in COAD. Real Time Quantitative PCR (RT-qPCR), Western blot, immunohistochemistry and ELISA were used to detect the relative RNA and protein expression levels. Colitis-associated cancer mice treated with Fusobacterium nucleatum were used to illustrate the effects of Fusobacterium nucleatum on FUTs and COAD. Luciferase reporting assay was used to investigate the binding of miRNA to mRNA.

Results

TCGA and GEO datasets showed abnormal expression of FUTs in COAD at transcript level. RT-qPCR, Western blot and immunohistochemistry showed increased expression of FUT1, POFUT1 and POFUT2 in COAD. COAD patients with a high expression of FUT1, FUT11, FUT13 (POFUT2) had a worse prognosis, while patients with a high expression of FUT2, FUT3, FUT6 had a better prognosis. FUT1 and POFUT2 could independently predict the prognosis of COAD patients. Functional analysis by CancerSEA database showed that FUT3, FUT6, FUT8, FUT12 (POFUT1) and FUT13 are associated with differentiation, apoptosis, invasion, quiescence, and hypoxia. FUTs are associated with the tumor microenvironment of COAD. FUT1 regulated by miR-939-3p inhibit the expression of MUC2. Fusobacterium nucleatum may affect the expression of FUTs by affecting their transcription factors and miRNA levels. Moreover, Fusobacterium nucleatum promotes COAD progression through the miR-939-3p/FUT1/MUC2 axis.

Conclusion

Fucosyltransferases play an important role and may be the mediator of Fusobacterium nucleatum promoting COAD progression.

The histone acetyltransferase KAT6A is recruited to unmethylated CpG islands via a DNA binding winged helix domain

The lysine acetyltransferase KAT6A (MOZ, MYST3) belongs to the MYST family of chromatin regulators, facilitating histone acetylation. Dysregulation of KAT6A has been implicated in developmental syndromes and the onset of acute myeloid leukemia (AML). Previous work suggests that KAT6A is recruited to its genomic targets by a combinatorial function of histone binding PHD fingers, transcription factors and chromatin binding interaction partners. Here, we demonstrate that a winged helix (WH) domain at the very N-terminus of KAT6A specifically interacts with unmethylated CpG motifs. This DNA binding function leads to the association of KAT6A with unmethylated CpG islands (CGIs) genome-wide. Mutation of the essential amino acids for DNA binding completely abrogates the enrichment of KAT6A at CGIs. In contrast, deletion of a second WH domain or the histone tail binding PHD fingers only subtly influences the binding of KAT6A to CGIs. Overexpression of a KAT6A WH1 mutant has a dominant negative effect on H3K9 histone acetylation, which is comparable to the effects upon overexpression of a KAT6A HAT domain mutant. Taken together, our work revealed a previously unrecognized chromatin recruitment mechanism of KAT6A, offering a new perspective on the role of KAT6A in gene regulation and human diseases.

Crosstalk between G-quadruplex and ROS

The excessive production of reactive oxygen species (ROS) can lead to single nucleic acid base damage, DNA strand breakage, inter- and intra-strand cross-linking of nucleic acids, and protein-DNA cross-linking involved in the pathogenesis of cancer, neurodegenerative diseases, and aging. G-quadruplex (G4) is a stacked nucleic acid structure that is ubiquitous across regulatory regions of multiple genes. Abnormal formation and destruction of G4s due to multiple factors, including cations, helicases, transcription factors (TFs), G4-binding proteins, and epigenetic modifications, affect gene replication, transcription, translation, and epigenetic regulation. Due to the lower redox potential of G-rich sequences and unique structural characteristics, G4s are highly susceptible to oxidative damage. Additionally, the formation, stability, and biological regulatory role of G4s are affected by ROS. G4s are involved in regulating gene transcription, translation, and telomere length maintenance, and are therefore key players in age-related degeneration. Furthermore, G4s also mediate the antioxidant process by forming stress granules and activating Nrf2, which is suggestive of their involvement in developing ROS-related diseases. In this review, we have summarized the crosstalk between ROS and G4s, and the possible regulatory mechanisms through which G4s play roles in aging and age-related diseases.

Brain Invasion and Trends in Molecular Research on Meningioma

Meningiomas are the most common primary brain tumors in adults. The treatment of non-benign meningiomas remains a challenging task, and after the publication of the 2021 World Health Organization classification, the importance of molecular biological classification is emerging. In this article, we introduce the mechanisms of brain invasion in atypical meningioma and review the genetic factors involved along with epigenetic regulation. First, it is important to understand the three major steps for brain invasion of meningeal cells: 1) degradation of extracellular matrix by proteases, 2) promotion of tumor cell migration to resident cells by adhesion molecules, and 3) neovascularization and supporting cells by growth factors. Second, the genomic landscape of meningiomas should be analyzed by major categories, such as germline mutations in NF2 and somatic mutations in non-NF2 genes (TRAF7, KLF4, AKT1, SMO, and POLR2A). Finally, epigenetic alterations in meningiomas are being studied, with a focus on DNA methylation, histone modification, and RNA interference. Increasing knowledge of the molecular landscape of meningiomas has allowed the identification of prognostic and predictive markers that can guide therapeutic decision-making processes and the timing of follow-up.

Global and promoter specific hypermethylation of tumor suppressor genes P16, SOCS1, and SHP1 in oral squamous cell carcinoma and oral submucous fibrosis

ABSTRACTS

Aberrant methylation pattern leads to altered gene expression, that is, involved in the transformation of various cancers, including oral squamous cell carcinoma (OSCC). In the present study, an attempt has been made to examine the association of global and promoter-specific methylation of tumor suppressor genes in patients with OSCC and oral submucous fibrosis (OSMF). Promoter-specific methylation of tumor suppressor genes P16, SOCS1, and SHP1 had been studied earlier for their aberrant methylation patterns in other cancers; however, these studies were mainly conducted in-vitro or in animal models, and as such, only a few studies are available on human samples. In the present study evaluation of promoter-specific methylation of genes P16, SOCS1, and SHP1 in 76 patients' blood and tissue samples was done and compared with methylation of 35 healthy control samples using qPCR. Further, these samples were analyzed for global methylation patterns using ELISA. The results have shown a significant decreasing trend of promoter methylation (OSCC > OSMF > Controls); the methylation indices (MI) were significantly higher in OSCC than in the controls. The median MI of three genes for OSCC were P16MI (0.96), SHP1MI (0.79), and SOCS1 (0.80). Similarly, median MIs for OSMF were P16MI (0.18), SHP1 MI (0.19), and SOCS1 MI (0.5) against controls with MI (0) for each of the three genes. The global methylation %mC values were 1.9, 0.5, and 0.1, respectively. The values of MI and %mC were found to correlate with various risk factors such as tobacco, smoking, and alcohol consumption, which are positively involved in OSMF pathogenesis followed by oral cancer progression. Further, the methylation trend in tissue was reflected in blood samples, proving a window for methylation load to be used as a lesser invasive biomarker. The sensitivity and specificity of methylation load were also found reasonable. Therefore, the current study suggests that there may be a role of global and promoter-specific methylation load in the transition of OSMF to OSCC.