Comparison of genome‐wide analysis techniques to DNA methylation analysis in human cancer

The common bisulfite-conversion-based techniques to analyze DNA methylation in human cancers

DNA methylation is an important molecular modification that plays a key role in the expression of cancer genes. Evaluation of epigenetic changes, hypomethylation and hypermethylation, in specific genes are applied for cancer diagnosis. Numerous studies have concentrated on describing DNA methylation patterns as biomarkers for cancer diagnosis monitoring and predicting response to cancer therapy. Various techniques for detecting DNA methylation status in cancers are based on sodium bisulfite treatment. According to the application of these methods in research and clinical studies, they have a number of advantages and disadvantages. The current review highlights sodium bisulfite treatment-based techniques, as well as, the advantages, drawbacks, and applications of these methods in the evaluation of human cancers.

Integrative analyses of multi-omics data constructing tumor microenvironment and immune-related molecular prognosis model in human colorectal cancer

The increasing prevalence and incidence of colorectal cancer (CRC), particularly in young adults, underscore the imperative to comprehend its fundamental mechanisms, discover novel diagnostic and prognostic markers, and enhance therapeutic strategies. Here, we integrated multi-omics data, including gene expression, somatic mutation data and DNA methylation data, to unravel the intricacies of tumor microenvironment (TME) in CRC and search for novel prognostic markers. By calculating the immune score for each patient from the expression profile, we delineated the differential immune cell fraction, constructed an immune-related multi-omics atlas, and identified molecular characteristics. The entire colorectal dataset (n = 343) was randomly divided into training (n = 249) and testing datasets (n = 94). We screened 144 immune-related genes, 6 mutant genes, and 38 methylation probes associated with overall survival (OS). These makers were then incorporated into a 10-gene prognostic model using Lasso and Cox regression in the training dataset, and the model's performance was evaluated in an independent validation dataset. The model exhibited satisfactory results (average concordance index [C-index] = 0.77), with the average 1-year, 3-year, and 5-year AUCs being 0.79, 0.76, and 0.76 in the training dataset and 0.74, 0.80, and 0.90 in the testing dataset. Furthermore, the prognostic model demonstrated applicability in guiding chemotherapy for CRC patients and exhibited a degree of pan-cancer utility in risk stratification. In conclusion, our integrated analysis of multi-omics data revealed immune-related genetic and epigenetic characteristics of the TME. We propose an integrative prognostic model that can stratify risk and guide chemotherapy for CRC patients. The generalizability of the model in risk stratification across different cancer types was validated in Pan-Cancer cohort.

Maternal exposure to E 551 during pregnancy leads to genome-wide DNA methylation changes and metabolic disorders in the livers of pregnant mice and their fetuses

The widespread use of nanoparticles in the food industry has raised concerns regarding their potential adverse effects on human health, particularly in vulnerable populations, including pregnant mothers and fetuses. However, studies evaluating the reproductive and developmental toxicity of food-grade nanomaterials are limited. This study investigated the potential risks of prenatal dietary exposure to food-grade silica nanoparticles (E 551) on maternal health and fetal growth using conventional toxicological and epigenetic methods. The results showed that prenatal exposure to a high-dose of E 551 induces fetal resorption. Moreover, E 551 significantly accumulates in maternal and fetal livers, triggering a hepatic inflammatory response. At the epigenetic level, global DNA methylation is markedly altered in the maternal and fetal livers. Genome-wide DNA methylation sequencing revealed affected mCG, mCHG, and mCHH methylation landscapes. Subsequent bioinformatic analysis of the differentially methylated genes suggests that E 551 poses a risk of inducing metabolic disorders in maternal and fetal livers. This is further evidenced by impaired glucose tolerance in pregnant mice and altered expression of key metabolism-related genes and proteins in maternal and fetal livers. Collectively, the results of this study highlighted the importance of epigenetics in characterizing the potential toxicity of maternal exposure to food-grade nanomaterials during pregnancy.

Portraying the dark side of endogenous IFN-λ for promoting cancer progression and immunoevasion in pan-cancer

BACKGROUND

IFN-λ has been shown to have a dual function in cancer, with its tumor-suppressive roles being well-established. However, the potential existence of a negative ''tumor-promoting'' effect of endogenous IFN-λ is still not fully understood.

METHODS

We conducted a comprehensive review and analysis of the perturbation of IFN-λ genes across various cancer types. Correlation coefficients were utilized to examine the relationship between endogenous IFN-λ expression and clinical factors, immune cell infiltration, tumor microenvironment, and response to immunotherapy. Genes working together with IFN-λ were obtained by constructing the correlation-based network related to IFN-λ and the gene interaction network in the KEGG pathway and IFN-λ-related genes obtained from the networks were integrated as candidate markers for the prognosis model. We then applied univariate and multivariate COX regression models to select cancer-specific independent prognostic markers associated with IFN-λ and to investigate risk factors for these genes by survival analysis. Additionally, computational methods were used to analyze the transcriptome, copy number variations, genetic mutations, and methylation of IFN-λ-related patient groups.

RESULT

Endogenous expression of IFN-λ has been linked to poor prognosis in cancer patients, with the genes IFN-λ2 and IFN-λ3 serving as independent prognostic markers. IFN-λ acts in conjunction with related genes such as STAT1, STAT2, and STAT3 to affect the JAK-STAT signaling pathway, which promotes tumor progression. Abnormalities in IFN-λ genes are associated with changes in immune checkpoints and immune cell infiltration, which in turn affects cancer- and immune-related pathways. While there is increased immune cell infiltration in patients with IFN-λ expression, this does not improve survival prognosis, as T-cell dysfunction and an inflammatory environment are also present. The amplification of IFNL2 and IFNL3 copy number variants drives specific endogenous expression of IFN-λ in patients, and those with this specific expression have been found to have more mutations in the TP53 gene and lower levels of DNA methylation.

CONCLUSION

Our study integrated multi-omics data to provide a comprehensive insight into the dark side of endogenous IFN-λ, providing a fundamental resource for further discovery and therapeutic exploration in cancer.

Detection of methyltransferase activity and inhibitor screening based on rGO-mediated silver enhancement signal amplification strategy

DNA methylation refers to the chemical modification process of obtaining a methyl group by the covalent bonding of a specific base in DNA sequence with S-adenosyl methionine (SAM) as a methyl donor under the catalysis of methyltransferase (MTase), which is related to the occurrence of multiple diseases. Therefore, the detection of MTase activity is of great significance for disease diagnosis and drug screening. Because reduced graphene oxide (rGO) has a unique planar structure and remarkable catalytic performance, it is not clear whether rGO can rapidly catalyze silver deposition as an effective way of signal amplification. However, in this study, we were pleasantly surprised to find that using H₂O₂ as a reducing agent, rGO can rapidly catalyze silver deposition, and its catalytic efficiency of silver deposition is significantly better than that of GO. Therefore, based on further verifying the mechanism of catalytic properties of rGO, we constructed a novel electrochemical biosensor (rGO/silver biosensor) for the detection of dam MTase activity, which has high selectivity and sensitivity to MTase in the range of 0.1 U/mL to 10.0 U/mL, and the detection limit is as low as 0.07 U/mL. Besides, this study also used Gentamicin and 5-Fluorouracil as inhibitor models, confirming that the biosensor has a good application prospect in the high-throughput screening of dam MTase inhibitors.

The roles of NOP56 in cancer and SCA36

NOP56 is a highly conserved nucleolar protein. Amplification of the intron GGCCTG hexanucleotide repeat sequence of the NOP56 gene results in spinal cerebellar ataxia type 36 (SCA36). NOP56 contains an N-terminal domain, a coiled-coil domain, and a C-terminal domain. Nucleolar protein NOP56 is significantly abnormally expressed in a number of malignant tumors, and its mechanism is different in different tumors, but its regulatory mechanism in most tumors has not been fully explored. NOP56 promotes tumorigenesis in some cancers and inhibits tumorigenesis in others. In addition, NOP56 is associated with methylation in some tumors, suggesting that NOP56 has the potential to become a tumor-specific marker. This review focuses on the structure, function, related signaling pathways, and role of NOP56 in the progression of various malignancies, and discusses the progression of NOP56 in neurodegenerative and other diseases.

Potential mechanisms and prognostic model of eRNAs-regulated genes in stomach adenocarcinoma

Gastric Carcinoma is the fourth leading cause of cancer deaths worldwide, in which stomach adenocarcinoma (STAD) is the most common histological type. A growing amount of evidence has suggested the importance of enhancer RNAs (eRNAs) in the cancer. However, the potential mechanism of eRNAs in STAD remains unclear. The eRNAs-regulated genes (eRRGs) were identified through four different enhancer resources. The differentially expressed eRRGs were obtained by ‘DESeq2’ R package. The prognosis prediction model was constructed by Cox and Lasso regression analysis. The ‘ChAMP’ R package and ‘maftools’ R package were used to investigate the multi-omics characters. In this study, combining the concept of contact domain, a total of 9014 eRRGs including 4926 PCGs and 4088 lncRNAs were identified and these eRRGs showed higher and more stable expression. Besides, the functions of these genes were mainly associated with tumor-related biological processes. Then, a prognostic prediction model was constructed and the AUC values of the 1-, 3- and 5-year survival prediction reached 0.76, 0.84 and 0.84, respectively, indicating that this model has a high accuracy. Finally, the difference between high-risk group and low-risk group were investigated using multi-omics data including gene expression, DNA methylation and somatic mutations. Our study provides significant clues for the elucidation of eRNAs in STAD and may help improve the overall survival for STAD patients.

Site-Specific Hypermethylation of SST 1stExon as a Biomarker for Predicting the Risk of Gastrointestinal Tract Cancers

Background

DNA methylation is an important epigenetic modification in tumorigenesis, and similar epigenetic regulation mechanisms have been found in the gastrointestinal tract (GIT) cancers. Somatostatin (SST) has been confirmed to be expressed throughout the GIT. This study aimed to simultaneously explore the relationships between the SST methylation and the risks of three GIT cancers (esophageal cancer (EC), gastric cancer (GC), and colorectal cancer (CRC)) and to evaluate its diagnostic value.

Methods

Differentially methylated regions (DMRs) of the SST gene, including TSS200, 1stExon, and the gene body, were identified in GIT cancers by The Cancer Genome Atlas (TCGA) database analysis. Further analyses were conducted in tissue samples of EC (n = 50), GC (n = 99), and CRC (n = 80). The SST methylation was detected by bisulfite-sequencing PCR (BSP), and the SST expression was detected by quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR).

Results

In GIT cancers, DMR-related CpG islands were mainly located in the 1stExon. The methylation status of the SST 1stExon in the tumor tissues was significantly higher than that in the adjacent noncancerous tissues, and the methylation rates of the specific CpG sites were correlated with clinical phenotypes. The average methylation rate (AMR) of the SST 1stExon was negatively correlated with the SST gene expression in GC and CRC (both P < 0.001). For the diagnosis of GIT cancers, the combined detection of methylation at CpG sites +18 and +129 showed the highest area under the curve (AUC 0.698), with a sensitivity of 59.3% and a specificity of 72.8%.

Conclusions

The site-specific hypermethylation of the SST 1stExon increases the risk of GIT cancers and might be a potential predictive marker for pan-GIT cancers.

Laboratory methods to decipher epigenetic signatures: a comparative review

Epigenetics refers to nucleotide sequence-independent events, and heritable changes, including DNA methylation and histone modification (as the two main processes), contributing to the phenotypic features of the cell. Both genetics and epigenetics contribute to determining the outcome of regulatory gene expression systems. Indeed, the flexibility of epigenetic effects and stability of genetic coding lead to gene regulation complexity in response signals. Since some epigenetic changes are significant in abnormalities such as cancers and neurodegenerative diseases, the initial changes, dynamic and reversible properties, and diagnostic potential of epigenomic phenomena are subject to epigenome-wide association studies (EWAS) for therapeutic aims. Based on recent studies, methodological developments are necessary to improve epigenetic research. As a result, several methods have been developed to explore epigenetic alterations at low, medium, and high scales, focusing on DNA methylation and histone modification detection. In this research field, bisulfite-, enzyme sensitivity- and antibody specificity-based techniques are used for DNA methylation, whereas histone modifications are gained based on antibody recognition. This review provides a mechanism-based understanding and comparative overview of the most common techniques for detecting the status of epigenetic effects, including DNA methylation and histone modifications, for applicable approaches from low- to high-throughput scales.

Prognostic signatures and potential pathogenesis of eRNAs-related genes in colon adenocarcinoma

Enhancer RNAs (eRNAs) are a subclass of long noncoding RNAs (lncRNAs) that have a wide effect in human tumors. However, the systematic analysis of potential functions of eRNAs-related genes (eRGs) in colon cancer (CC) remains unexplored. In this study, a total of 8231 eRGs including 6236 protein-coding genes and 1995 lncRNAs were identified in CC based on the multiple resources. These eRGs showed higher expression level and stability compared to other genes. What's more, the functions of these eRGs were closely related to cancer. Then a prognostic prediction model with 12 eRGs signatures were obtained for colon adenocarcinoma (COAD) patients. ROC curves showed the AUCs were 0.81, 0.77, and 0.78 for 1-, 3-, and 5-year survival prediction, respectively. And the prognostic model also manifested good performance in the validation datasets. Besides, the expression levels of two prognostic signatures, TMEM220 and LRRN2, were verified to be significantly lower in CC tissues than in adjacent noncancerous tissues (p < .05). Finally, the distinct molecular features were characterized between the high- and low-risk group through multiomics analysis including DNA mutation and methylation. Our results show eRGs signatures based prognostic model has high accuracy and may provide innovative biomarkers in COAD.

Characterization of METTL7B to Evaluate TME and Predict Prognosis by Integrative Analysis of Multi-Omics Data in Glioma

Glioma is the most common and aggressive type of primary brain malignant tumor with limited treatment approaches. Methyltransferase-like 7B (METTL7B) is associated with the pathogenesis of several diseases but is rarely studied in glioma. In this study, 1,493 glioma samples (data from our cohort, TCGA, and CGGA) expressing METTL7B were used to explore its prognostic value and mechanism in the immune microenvironment. Results showed that high expression of METTL7B is associated with poor prognosis and abundant immunosuppressive cells. Further, functional enrichment showed that METTL7B is involved in the negative regulation of immunity and carcinogenic signaling pathways. Moreover, a METTL7B-related prognostic signature constructed based on multi-omics showed a good prediction of the overall survival (OS) time of glioma patients. In conclusion, METTL7B is a potential prognostic biomarker. In addition, the prognostic prediction model constructed in this study can be used in clinical setups for the development of novel effective therapeutic strategies for glioma patients and improving overall survival.

Intracellular zinc-dependent TAS2R8 gene expression through CTCF activation

Taste-2 receptors (TAS2Rs), which belong to the G-protein coupled receptor (GPCR) family, are receptors for bitter taste perception. The aim of this study was to investigate whether zinc deficiency affects the expression of TAS2R genes. The promoter activity of the TAS2R7, TAS2R8, and TAS2R42 genes were determined in Ca9-22 oral squamous cell carcinoma cells cultured in the presence or absence of zinc. Luciferase reporter assays showed that zinc deprivation inhibited TAS2R8 promoter activity, but not the promoter activity of the other two genes. Treatment of the cells with N,N,N',N'-tetrakis(2-pyridinylmethyl)-1,2-ethanediamine (TPEN), an intracellular chelator of Zn²⁺, in the presence of 10% fetal bovine serum reduced TAS2R8 promoter activity. Truncation/deletion mutants of TAS2R8 promoter-luciferase constructs showed that the region from nucleotide -1152 to nucleotide -925 was critical for intracellular zinc dependency and contained a CCCTC-binding factor (CTCF) binding motif. A chromatin immunoprecipitation (ChiP) assay showed that CTCF bound specifically to this region, a binding abrogated by zinc deficiency, suggesting that CTCF plays a critical role in zinc-dependent bitter taste perception through TAS2R8.

A new thinking: extended application of genomic selection to screen multiomics data for development of novel hypoxia-immune biomarkers and target therapy of clear cell renal cell carcinoma

Increasing evidences show the clinical significance of the interaction between hypoxia and immune in clear cell renal cell carcinoma (ccRCC) microenvironment. However, reliable prognostic signatures based on a combination of hypoxia and immune have not been well established. Moreover, many studies have only used RNA-seq profiles to screen the prognosis feature of ccRCC. Presently, there is no comprehensive analysis of multiomics data to mine a better one. Thus, we try and get it. First, t-SNE and ssGSEA analysis were used to establish tumor subtypes related to hypoxia-immune, and we investigated the hypoxia-immune-related differences in three types of genetic or epigenetic characteristics (gene expression profiles, somatic mutation, and DNA methylation) by analyzing the multiomics data from The Cancer Genome Atlas (TCGA) portal. Additionally, a four-step strategy based on lasso regression and Cox regression was used to construct a satisfying prognostic model, with average 1-year, 3-year and 5-year areas under the curve (AUCs) equal to 0.806, 0.776 and 0.837. Comparing it with other nine known prognostic biomarkers and clinical prognostic scoring algorithms, the multiomics-based signature performs better. Then, we verified the gene expression differences in two external databases (ICGC and SYSU cohorts). Next, eight hub genes were singled out and seven hub genes were validated as prognostic genes in SYSU cohort. Furthermore, it was indicated high-risk patients have a better response for immunotherapy in immunophenoscore (IPS) analysis and TIDE algorithm. Meanwhile, estimated by GDSC and cMAP database, the high-risk patients showed sensitive responses to six chemotherapy drugs and six candidate small-molecule drugs. In summary, the signature can accurately predict the prognosis of ccRCC and may shed light on the development of novel hypoxia-immune biomarkers and target therapy of ccRCC.

The regulation mechanisms and the Lamarckian inheritance property of DNA methylation in animals

DNA methylation is a stable and heritable epigenetic mechanism, of which the main functions are stabilizing the transcription of genes and promoting genetic conservation. In animals, the direct molecular inducers of DNA methylation mainly include histone covalent modification and non-coding RNA, whereas the fundamental regulators of DNA methylation are genetic and environmental factors. As is well known, competition is present everywhere in life systems, and will finally strike a balance that is optimal for the animal's survival and reproduction. The same goes for the regulation of DNA methylation. Genetic and environmental factors, respectively, are responsible for the programmed and plasticity changes of DNA methylation, and keen competition exists between genetically influenced procedural remodeling and environmentally influenced plastic alteration. In this process, genetic and environmental factors collaboratively decide the methylation patterns of corresponding loci. DNA methylation alterations induced by environmental factors can be transgenerationally inherited, and exhibit the characteristic of Lamarckian inheritance. Further research on regulatory mechanisms and the environmental plasticity of DNA methylation will provide strong support for understanding the biological function and evolutionary effects of DNA methylation.

Current Advances in DNA Methylation Analysis Methods

DNA methylation is one of the epigenetic changes, which plays a major role in regulating gene expression and, thus, many biological processes and diseases. There are several methods for determining the methylation of DNA samples. However, selecting the most appropriate method for answering biological questions appears to be a challenging task. The primary methods in DNA methylation focused on identifying the state of methylation of the examined genes and determining the total amount of 5-methyl cytosine. The study of DNA methylation at a large scale of genomic levels became possible following the use of microarray hybridization technology. The new generation of sequencing platforms now allows the preparation of genomic maps of DNA methylation at the single-open level. This review includes the majority of methods available to date, introducing the most widely used methods, the bisulfite treatment, biological identification, and chemical cutting along with their advantages and disadvantages. The techniques are then scrutinized according to their robustness, high throughput capabilities, and cost.

Colorectal cancer screening and diagnosis: omics-based technologies for development of a non-invasive blood-based method

Introduction: Colorectal cancer (CRC) is one of the most important health problems in the Western world. In order to reduce the burden of the disease, two strategies are proposed: screening and prompt detection in symptomatic patients. Although diagnosis and prevention are mainly based on colonoscopy, fecal hemoglobin detection has been widely implemented as a noninvasive strategy. Various studies aiming to discover blood-based biomarkers have recently emerged.Areas covered: The burgeoning omics field provides diverse high-throughput approaches for CRC blood-based biomarker discovery. In this review, we appraise the most robust and commonly used technologies within the fields of genomics, transcriptomics, epigenomics, proteomics, and metabolomics, together with their targeted validation approaches. We summarize the transference process from the discovery phase until clinical translation. Finally, we review the best candidate biomarkers and their potential clinical applicability.Expert opinion: Some available biomarkers are promising, especially in the field of epigenomics: DNA methylation and microRNA. Transference requires the joint collaboration of basic researchers, intellectual property experts, technology transfer officers and clinicians. Blood-based biomarkers will be selected not only based on their diagnostic accuracy and cost but also on their reliability, applicability to clinical analysis laboratories and their acceptance by the population.

DNA methylation in Hepatoblastoma-a literature review

Hepatoblastoma (HB) is the most common malignant liver tumor in children. Abnormal activation of the Wnt/β-catenin signaling pathway plays an important role in the formation and development of HB. Genes in HB show a global hypomethylation change, accompanied by hypermethylation of specific tumor suppressor genes (TSGs). This article reviews the hypermethylation changes in several TSGs, such as RASSF1A, SOCS1, APC, HHIP, and P16, and analyzes the pathways and mechanisms of TSGs regulating gene expression. The role of the methylation-regulating enzymes DNA methyltransferases (DNMTs) and ten-eleven translocation (TET) family members enzymes in the methylation changes of HB was analyzed, and it was speculated that the occurrence of HB is partly due to the obstruction of liver differentiation in the early stage of differentiation. The origin cells may be incompletely differentiated hepatocytes remaining in the liver of children after birth. Therefore, further studying the role of methylation regulating enzymes in methylation changes in HB is a promising future research direction.

Multi-omics Data Analyses Construct TME and Identify the Immune-Related Prognosis Signatures in Human LUAD

Lung cancer has been the focus of attention for many researchers in recent years for the leading contribution to cancer-related death worldwide, in which lung adenocarcinoma (LUAD) is the most common histological type. However, the potential mechanism behind LUAD initiation and progression remains unclear. Aiming to dissect the tumor microenvironment of LUAD and to discover more informative prognosis signatures, we investigated the immune-related differences in three types of genetic or epigenetic characteristics (expression status, somatic mutation, and DNA methylation) and considered the potential roles that these alterations have in the immune response and both the immune-related metabolic and neural systems by analyzing the multi-omics data from The Cancer Genome Atlas (TCGA) portal. Additionally, a four-step strategy based on lasso regression and Cox regression was used to construct the prognostic prediction model. For the prognostic predictions on the independent test set, the performance of the trained models (average concordance index [C-index] = 0.839) is satisfied, with average 1-year, 3-year, and 5-year areas under the curve (AUCs) equal to 0.796, 0.786, and 0.777. Finally, the overall model was constructed based on all samples, which comprised 27 variables and achieved a high degree of accuracy on the 1-year (AUC = 0.861), 3-year (AUC = 0.850), and 5-year (AUC = 0.916) survival predictions.

A Hybrid Ensemble Approach for Identifying Robust Differentially Methylated Loci in Pan-Cancers

DNA methylation is a widely investigated epigenetic mark that plays a vital role in tumorigenesis. Advancements in high-throughput assays, such as the Infinium 450K platform, provide genome-scale DNA methylation landscapes in single-CpG locus resolution, and the identification of differentially methylated loci has become an insightful approach to deepen our understanding of cancers. However, the situation with extremely unbalanced numbers of samples and loci (approximately 1:1,000) makes it rather difficult to explore differential methylation between the sick and the normal. In this article, a hybrid approach based on ensemble feature selection for identifying differentially methylated loci (HyDML) was proposed by incorporating instance perturbation and multiple function models. Experiments on data from The Cancer Genome Atlas showed that HyDML not only achieved effective DML identification, but also outperformed the single-feature selection approach in terms of classification performance and the robustness of feature selection. The intensive analysis of the DML indicated that different types of cancers have mutual patterns, and the stable DML sharing in pan-cancers is of the great potential to be biomarkers, which may strengthen the confidence of domain experts to implement biological validations.

A model of pulldown alignments from SssI-treated DNA improves DNA methylation prediction

Background

Protein pulldown using Methyl-CpG binding domain (MBD) proteins followed by high-throughput sequencing is a common method to determine DNA methylation. Algorithms have been developed to estimate absolute methylation level from read coverage generated by affinity enrichment-based techniques, but the most accurate one for MBD-seq data requires additional data from an SssI-treated Control experiment.

Results

Using our previous characterizations of Methyl-CpG/MBD2 binding in the context of an MBD pulldown experiment, we build a model of expected MBD pulldown reads as drawn from SssI-treated DNA. We use the program BayMeth to evaluate the effectiveness of this model by substituting calculated SssI Control data for the observed SssI Control data. By comparing methylation predictions against those from an RRBS data set, we find that BayMeth run with our modeled SssI Control data performs better than BayMeth run with observed SssI Control data, on both 100 bp and 10 bp windows. Adapting the model to an external data set solely by changing the average fragment length, our calculated data still informs the BayMeth program to a similar level as observed data in predicting methylation state on a pulldown data set with matching WGBS estimates.

Conclusion

In both internal and external MBD pulldown data sets tested in this study, BayMeth used with our modeled pulldown coverage performs better than BayMeth run without the inclusion of any estimate of SssI Control pulldown, and is comparable to – and in some cases better than – using observed SssI Control data with the BayMeth program. Thus, our MBD pulldown alignment model can improve methylation predictions without the need to perform additional control experiments.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-3011-2) contains supplementary material, which is available to authorized users.

Next-generation sequencing approaches for the study of genome and epigenome toxicity induced by sulfur mustard

Sulfur mustard (SM) is an extensive nucleophilic and alkylating agent that targets different tissues. The genotoxic property of SM is the most threatening effect, because it is associated with detrimental inflammations and susceptibility to several kinds of cancer. Moreover, SM causes a wide variety of adverse effects on DNA which result in accumulation of DNA adducts, multiple mutations, aneuploidies, and epigenetic aberrations in the genome. However, these adverse effects are still not known well, possibly because no valid biomarkers have been developed for detecting them. The advent of next-generation sequencing (NGS) has provided opportunities for the characterization of these alterations with a higher level of molecular detail and cost-effectivity. The present review introduces NGS approaches for the detection of SM-induced DNA adducts, mutations, chromosomal structural variation, and epigenetic aberrations, and also comparing and contrasting them with regard to which might be most advantageous.

Liquid biomarkers in melanoma: detection and discovery

A vast array of tumor-derived genetic, proteomic and cellular components are constantly released into the circulation of cancer patients. These molecules including circulating tumor DNA and RNA, proteins, tumor and immune cells are emerging as convenient and accurate liquid biomarkers of cancer. Circulating cancer biomarkers provide invaluable information on cancer detection and diagnosis, prognosticate patient outcomes, and predict treatment response. In this era of effective molecular targeted treatments and immunotherapies, there is now an urgent need to implement use of these circulating biomarkers in the clinic to facilitate personalized therapy. In this review, we present recent findings in circulating melanoma biomarkers, examine the challenges and promise of evolving technologies used for liquid biomarker discovery, and discuss future directions and perspectives in melanoma biomarker research.

Genetic variation in CDH13 gene was associated with non-small cell lung cancer (NSCLC): A population-based case-control study

Cadherin 13 (CDH13, T-cadherin, H-cadherin) has been identified as an anti-oncogene in various cancers. Recent studies have reported that downregulation of H-cadherin in cancers is associated with CDH13 promoter hypermethylation, which could be affected by the single nucleotide polymorphisms (SNPs) near CpG sites in the CDH13 promoter. In the current study, we investigated and analyzed the association of seven SNPs (rs11646213, rs12596316, rs3865188, rs12444338, rs4783244, rs12051272 and rs7195409) with non-small cell lung cancer (NSCLC) using logistic regression analysis. SNPs rs11646213, rs12596316, rs3865188 and rs12444338 are located in the promoter region, rs4783244 and rs12051272 are located in intron 1, and rs7195409 is located in intron 7. A total of 454 patients with NSCLC were placed into a NSCLC group and 444 healthy controls were placed into a control group, all participants were recruited to genotype the SNPs using Taqman assay. Our results showed that the allelic frequencies of rs11646213 were significantly different between NSCLC and control groups (P = 0.006). In addition, the association analysis of these SNPs stratified into NSCLC pathologic stages I+II and III+IV showed that the allelic frequencies rs7195409 had a significant difference between NSCLC pathologic stages I+II and III+IV (P = 0.006). Our results indicated that the rs11646213 and rs7195409 in CDH13 could be associated with NSCLC or its pathologic stages in the Chinese Han population.