Genome-scale analysis of DNA methylation in colorectal cancer using Infinium HumanMethylation450 BeadChips

Understanding the role of DNA methylation in colorectal cancer: Mechanisms, detection, and clinical significance

Colorectal cancer (CRC) is one of the deadliest malignancies worldwide, ranking third in incidence and second in mortality. Remarkably, early stage localized CRC has a 5-year survival rate of over 90%; in stark contrast, the corresponding 5-year survival rate for metastatic CRC (mCRC) is only 14%. Compounding this problem is the staggering lack of effective therapeutic strategies. Beyond genetic mutations, which have been identified as critical instigators of CRC initiation and progression, the importance of epigenetic modifications, particularly DNA methylation (DNAm), cannot be underestimated, given that DNAm can be used for diagnosis, treatment monitoring and prognostic evaluation. This review addresses the intricate mechanisms governing aberrant DNAm in CRC and its profound impact on critical oncogenic pathways. In addition, a comprehensive review of the various techniques used to detect DNAm alterations in CRC is provided, along with an exploration of the clinical utility of cancer-specific DNAm alterations.

Advances in cancer DNA methylation analysis with methPLIER: use of non-negative matrix factorization and knowledge-based constraints to enhance biological interpretability

DNA methylation is an epigenetic modification that results in dynamic changes during ontogenesis and cell differentiation. DNA methylation patterns regulate gene expression and have been widely researched. While tools for DNA methylation analysis have been developed, most of them have focused on intergroup comparative analysis within a dataset; therefore, it is difficult to conduct cross-dataset studies, such as rare disease studies or cross-institutional studies. This study describes a novel method for DNA methylation analysis, namely, methPLIER, which enables interdataset comparative analyses. methPLIER combines Pathway Level Information Extractor (PLIER), which is a non-negative matrix factorization (NMF) method, with regularization by a knowledge matrix and transfer learning. methPLIER can be used to perform intersample and interdataset comparative analysis based on latent feature matrices, which are obtained via matrix factorization of large-scale data, and factor-loading matrices, which are obtained through matrix factorization of the data to be analyzed. We used methPLIER to analyze a lung cancer dataset and confirmed that the data decomposition reflected sample characteristics for recurrence-free survival. Moreover, methPLIER can analyze data obtained via different preprocessing methods, thereby reducing distributional bias among datasets due to preprocessing. Furthermore, methPLIER can be employed for comparative analyses of methylation data obtained from different platforms, thereby reducing bias in data distribution due to platform differences. methPLIER is expected to facilitate cross-sectional DNA methylation data analysis and enhance DNA methylation data resources.

Early results of the integrative epigenomic-transcriptomic landscape of colorectal adenoma and cancer

BACKGROUND

Aberrant methylation is common during the initiation and progression of colorectal cancer (CRC), and detecting these changes that occur during early adenoma (ADE) formation and CRC progression has clinical value.

AIM

To identify potential DNA methylation markers specific to ADE and CRC.

METHODS

Here, we performed SeqCap targeted bisulfite sequencing and RNA-seq analysis of colorectal ADE and CRC samples to profile the epigenomic-transcriptomic landscape.

RESULTS

Comparing 22 CRC and 25 ADE samples, global methylation was higher in the former, but both showed similar methylation patterns regarding differentially methylated gene positions, chromatin signatures, and repeated elements. High-grade CRC tended to exhibit elevated methylation levels in gene promoter regions compared to those in low-grade CRC. Combined with RNA-seq gene expression data, we identified 14 methylation-regulated differentially expressed genes, of which only AGTR1 and NECAB1 methylation had prognostic significance.

CONCLUSION

Our results suggest that genome-wide alterations in DNA methylation occur during the early stages of CRC and demonstrate the methylation signatures associated with colorectal ADEs and CRC, suggesting prognostic biomarkers for CRC.

Multimodal epigenetic sequencing analysis (MESA) of cell-free DNA for non-invasive colorectal cancer detection

BACKGROUND

Detecting human cancers through cell-free DNA (cfDNA) in blood is a sensitive and non-invasive option. However, capturing multiple forms of epigenetic information remains a technical and financial challenge.

METHODS

To address this, we developed multimodal epigenetic sequencing analysis (MESA), a flexible and sensitive approach to capturing and integrating a diverse range of epigenetic features in cfDNA using a single experimental assay, i.e., non-disruptive bisulfite-free methylation sequencing, such as Enzymatic Methyl-seq. MESA enables simultaneous inference of four epigenetic modalities: cfDNA methylation, nucleosome occupancy, nucleosome fuzziness, and windowed protection score for regions surrounding gene promoters and polyadenylation sites.

RESULTS

When applied to 690 cfDNA samples from 3 colorectal cancer clinical cohorts, MESA's novel modalities, which include nucleosome fuzziness, and genomic features, including polyadenylation sites, improve cancer detection beyond the traditional epigenetic markers of promoter DNA methylation.

CONCLUSIONS

Together, MESA stands as a major advancement in the field by utilizing comprehensive and complementary epigenetic profiles of cfDNA for effective non-invasive cancer detection.

Analyzing aberrant DNA methylation in colorectal cancer uncovered intangible heterogeneity of gene effects in the survival time of patients

Colorectal cancer (CRC) involves epigenetic alterations. Irregular gene-methylation alteration causes and advances CRC tumor growth. Detecting differentially methylated genes (DMGs) in CRC and patient survival time paves the way to early cancer detection and prognosis. However, CRC data including survival times are heterogeneous. Almost all studies tend to ignore the heterogeneity of DMG effects on survival. To this end, we utilized a sparse estimation method in the finite mixture of accelerated failure time (AFT) regression models to capture such heterogeneity. We analyzed a dataset of CRC and normal colon tissues and identified 3406 DMGs. Analysis of overlapped DMGs with several Gene Expression Omnibus datasets led to 917 hypo- and 654 hyper-methylated DMGs. CRC pathways were revealed via gene ontology enrichment. Hub genes were selected based on Protein-Protein-Interaction network including SEMA7A, GATA4, LHX2, SOST, and CTLA4, regulating the Wnt signaling pathway. The relationship between identified DMGs/hub genes and patient survival time uncovered a two-component mixture of AFT regression model. The genes NMNAT2, ZFP42, NPAS2, MYLK3, NUDT13, KIRREL3, and FKBP6 and hub genes SOST, NFATC1, and TLE4 were associated with survival time in the most aggressive form of the disease that can serve as potential diagnostic targets for early CRC detection.

Screening and identifying of biomarkers in early colorectal cancer and adenoma based on genome-wide methylation profiles

BACKGROUND

Colorectal cancer is one of the most common malignant tumors worldwide with high morbidity and mortality. This study aimed to identify different methylation sites as new methylation markers in CRC and colorectal adenoma through tissue detection.

METHODS

DNA extraction and bisulfite modification as well as Infinium 450K methylation microarray detection were performed in 46 samples of sporadic colorectal cancer tissue, nine samples of colorectal adenoma, and 20 normal samples, and bioinformatic analysis was conducted involving genes enrichments of GO and KEGG. Pyrosequencing methylation detection was further performed in 68 sporadic colorectal cancer tissues, 31 samples of colorectal adenoma, and 49 normal colorectal mucosae adjacent to carcinoma to investigate the differentially methylated genes obtained from methylation microarray.

RESULTS

There were 65,535 differential methylation marker probes, among which 25,464 were hypermethylated markers and 40,071 were hypomethylated markers in the adenoma compared with the normal group, and 395,571 were differentially methylated markers in patients with sporadic colorectal cancer compared with the normal group, including 21,710 hypermethylated markers and 17,861 hypomethylated markers. Five hypermethylated genes including ZNF471, SND1, SPOCK1, FBLIM1, and OTX1 were detected and confirmed in 68 cases of colorectal cancer, 31 cases of adenoma, and 49 cases of normal control group.

CONCLUSIONS

Hypermethylated genes of ZNF471, SND1, SPOCK1, FBLIM1, and OTX1 were obtained from methylation chip detection and further confirm analysis in colorectal cancer and adenoma compared with normal tissue, which may be promising diagnostic markers of colorectal cancer and colorectal adenoma.

Combined detection of SDC2/ADHFE1/PPP2R5C methylation in stool DNA for colorectal cancer screening

BACKGROUND

Colorectal cancer (CRC) is a disease of global concern, and its increasing incidence suggests the need for early and accurate diagnosis. The aim of this study was to investigate the value of combined detection of SDC2, ADHFE1 and PPP2R5C gene methylation in stool samples for early CRC screening.

METHODS

Stool samples from patients with CRC (n = 105), advanced adenoma (AA) (n = 54), non-advanced adenoma (NA) (n = 57), hyperplastic or other polyps (HOP) (n = 47) or no evidence of disease (NED) (n = 100) were collected from September 2021 to September 2022. The methylation levels of SDC2, ADHFE1 and PPP2R5C were quantified by quantitative methylation-specific polymerase chain reaction (qMSP), and faecal immunochemical testing (FIT) was performed. The diagnostic value was assessed using reporter operating characteristic (ROC) curve analysis.

RESULTS

The sensitivity of combined detection of SDC2/ADHFE1/PPP2R5C methylation in predicting CRC (0-IV) was 84.8%, the specificity was 98.0%, and the AUC was 0.930 (95% CI 0.889-0.970). Compared to FIT and serum tumour biomarkers, it showed better diagnostic performance for different stages of CRC.

CONCLUSION

The results of this study verified that the methylation levels of SDC2, ADHFE1 and PPP2R5C in stool DNA were significantly increased in CRC patients. Combined detection of SDC2/ADHFE1/PPP2R5C methylation is a potential non-invasive diagnostic method for CRC and precancerous lesion screening.

CLINICAL TRIAL REGISTRATION

Chinese Clinical Trials Registry, ChiCTR2100046662, registered on 26 May 2021, prospective registration.

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.

CpG Site-Based Signature Predicts Survival of Colorectal Cancer

BACKGROUND

A critical unmet medical need in clinical management of colorectal cancer (CRC) pivots around lack of noninvasive and or minimally invasive techniques for early diagnosis and prognostic prediction of clinical outcomes. Because DNA methylation can capture the regulatory landscape of tumors and can be measured in body fluids, it provides unparalleled opportunities for the discovery of early diagnostic and prognostics markers predictive of clinical outcomes. Here we investigated use of DNA methylation for the discovery of potential clinically actionable diagnostic and prognostic markers for predicting survival in CRC.

METHODS

We analyzed DNA methylation patterns between tumor and control samples to discover signatures of CpG sites and genes associated with CRC and predictive of survival. We conducted functional analysis to identify molecular networks and signaling pathways driving clinical outcomes.

RESULTS

We discovered a signature of aberrantly methylated genes associated with CRC and a signature of thirteen (13) CpG sites predictive of survival. We discovered molecular networks and signaling pathways enriched for CpG sites likely to drive clinical outcomes.

CONCLUSIONS

The investigation revealed that CpG sites can predict survival in CRC and that DNA methylation can capture the regulatory state of tumors through aberrantly methylated molecular networks and signaling pathways.

Promoter Methylation of QKI as a Potential Specific Biomarker for Early Detection of Colorectal Cancer

Early and specific detection of cancer provides an opportunity for appropriate treatment. Although studies have suggested that QKI is a tumor suppressor gene, no studies have evaluated the diagnostic utility of QKI methylation in colorectal cancer (CRC). Here, we evaluated the methylation status of QKI by integrating the methylation data of tissues and cell lines of multiple cancer types. The diagnostic performance of QKI was analyzed in the discovery dataset from the TCGA CRC 450K array (n = 440) and tested in the test sets (n = 845) from the GEO. The methylation level of QKI was further validated in our independent dataset (n = 388) using targeted bisulfite sequencing. All detected CpG sites in the QKI promoter showed CRC-specific hypermethylation in 31 types of tumor tissues. In the discovery dataset, six consecutive CpG sites achieved high diagnostic performances, with AUCs ranging from 0.821 to 0.930. In the test set, a region (chr6: 163,834,452–163,834,924) including four consecutive CpG sites had robust diagnostic ability in distinguishing CRC and adenoma from normal samples. In the validation dataset, similar robust results were observed in both early- and advanced-stage CRC patients. In addition, QKI exhibited hypermethylation in the cfDNA of patients with CRC (n = 14). Collectively, the QKI promoter is a CRC-specific methylation biomarker and holds great promise for improving the diagnosis using minimally invasive biopsy.

MicroRNA Methylome Signature and Their Functional Roles in Colorectal Cancer Diagnosis, Prognosis, and Chemoresistance

Colorectal cancer (CRC) is one of the leading causes of cancer-related deaths worldwide. Despite significant advances in the diagnostic services and patient care, several gaps remain to be addressed, from early detection, to identifying prognostic variables, effective treatment for the metastatic disease, and the implementation of tailored treatment strategies. MicroRNAs, the short non-coding RNA species, are deregulated in CRC and play a significant role in the occurrence and progression. Nevertheless, microRNA research has historically been based on expression levels to determine its biological significance. The exact mechanism underpinning microRNA deregulation in cancer has yet to be elucidated, but several studies have demonstrated that epigenetic mechanisms play important roles in the regulation of microRNA expression, particularly DNA methylation. However, the methylation profiles of microRNAs remain unknown in CRC patients. Methylation is the next major paradigm shift in cancer detection since large-scale epigenetic alterations are potentially better in identifying and classifying cancers at an earlier stage than somatic mutations. This review aims to provide insight into the current state of understanding of microRNA methylation in CRC. The new knowledge from this study can be utilized for personalized health diagnostics, disease prediction, and monitoring of treatment.

Diagnostic classification of cancers using DNA methylation of paracancerous tissues

The potential role of DNA methylation from paracancerous tissues in cancer diagnosis has not been explored until now. In this study, we built classification models using well-known machine learning models based on DNA methylation profiles of paracancerous tissues. We evaluated our methods on nine cancer datasets collected from The Cancer Genome Atlas (TCGA) and utilized fivefold cross-validation to assess the performance of models. Additionally, we performed gene ontology (GO) enrichment analysis on the basis of the significant CpG sites selected by feature importance scores of XGBoost model, aiming to identify biological pathways involved in cancer progression. We also exploited the XGBoost algorithm to classify cancer types using DNA methylation profiles of paracancerous tissues in external validation datasets. Comparative experiments suggested that XGBoost achieved better predictive performance than the other four machine learning methods in predicting cancer stage. GO enrichment analysis revealed key pathways involved, highlighting the importance of paracancerous tissues in cancer progression. Furthermore, XGBoost model can accurately classify nine different cancers from TCGA, and the feature sets selected by XGBoost can also effectively predict seven cancer types on independent GEO datasets. This study provided new insights into cancer diagnosis from an epigenetic perspective and may facilitate the development of personalized diagnosis and treatment strategies.

Hypermethylation of TMEM240 predicts poor hormone therapy response and disease progression in breast cancer

Background

Approximately 25% of patients with early-stage breast cancer experience cancer progression throughout the disease course. Alterations in TMEM240 in breast cancer were identified and investigated to monitor treatment response and disease progression.

Methods

Circulating methylated TMEM240 in the plasma of breast cancer patients was used to monitor treatment response and disease progression. The Cancer Genome Atlas (TCGA) data in Western countries and Illumina methylation arrays in Taiwanese breast cancer patients were used to identify novel hypermethylated CpG sites and genes related to poor hormone therapy response. Quantitative methylation-specific PCR (QMSP), real-time reverse transcription PCR, and immunohistochemical analyses were performed to measure DNA methylation and mRNA and protein expression levels in 394 samples from Taiwanese and Korean breast cancer patients. TMEM240 gene manipulation, viability, migration assays, RNA-seq, and MetaCore were performed to determine its biological functions and relationship to hormone drug treatment response in breast cancer cells.

Results

Aberrant methylated TMEM240 was identified in breast cancer patients with poor hormone therapy response using genome-wide methylation analysis in the Taiwan and TCGA breast cancer cohorts. A cell model showed that TMEM240, which is localized to the cell membrane and cytoplasm, represses breast cancer cell proliferation and migration and regulates the expression levels of enzymes involved in estrone and estradiol metabolism. TMEM240 protein expression was observed in normal breast tissues but was not detected in 88.2% (67/76) of breast tumors and in 90.0% (9/10) of metastatic tumors from breast cancer patients. QMSP revealed that in 54.5% (55/101) of Taiwanese breast cancer patients, the methylation level of TMEM240 was at least twofold higher in tumor tissues than in matched normal breast tissues. Patients with hypermethylation of TMEM240 had poor 10-year overall survival (p = 0.003) and poor treatment response, especially hormone therapy response (p < 0.001). Circulating methylated TMEM240 dramatically and gradually decreased and then diminished in patients without disease progression, whereas it returned and its levels in plasma rose again in patients with disease progression. Prediction of disease progression based on circulating methylated TMEM240 was found to have 87.5% sensitivity, 93.1% specificity, and 90.2% accuracy.

Conclusions

Hypermethylation of TMEM240 is a potential biomarker for treatment response and disease progression monitoring in breast cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s10020-022-00474-9.

Genome-wide methylation profiling of early colorectal cancer using an Illumina Infinium Methylation EPIC BeadChip

BACKGROUND

DNA methylation is a part of epigenetic modification, that is closely related to the growth and development of colorectal cancer (CRC). Specific methylated genes and methylated diagnostic models of tumors have become current research focuses. The methylation status of circulating DNA in plasma might serve as a potential biomarker for CRC.

AIM

To investigate genome-wide methylation pattern in early CRC using the Illumina Infinium Human Methylation 850K BeadChip.

METHODS

The 850K Methylation BeadChip was used to analyze the genome-wide methylation status of early CRC patients (n = 5) and colorectal adenoma patients (n = 5). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analyses were performed on the selected differentially methylated sites to further discover candidate methylation biomarkers in plasma.

RESULTS

A total of 1865 methylated CpG sites with significant differences were detected, including 676 hypermethylated sites and 1189 hypomethylated sites. The distribution of these sites covered from the 1^st to 22^nd chromosomes and are mainly distributed on the gene body and gene promoter region. GO and KEGG enrichment analysis showed that the functions of these genes were related to biological regulation, molecular binding, transcription factor activity and signal transduction pathway.

CONCLUSION

The study demonstrated that the Illumina Infinium Human Methylation 850K BeadChip can be used to investigate genome-wide methylation status of plasma DNA in early CRC and colorectal adenoma patients.

DNA methylation-based diagnostic, prognostic, and predictive biomarkers in colorectal cancer

DNA methylation is an epigenetic mechanism regulating gene expression. Changes in DNA methylation were suggested to be useful biomarkers for diagnosis, and for the determination of prognosis and treatment response. Here, we provide an overview of methylation-based biomarkers in colorectal cancer. First, we start with the two methylation-based diagnostic biomarkers already approved for colorectal cancer, SEPT9 and the combination of NDRG4 and BMP3. Then, we provide a list-based overview of new biomarker candidates depending on the sample source including plasma, stool, urine, and surgically removed tumor tissues. The most often identified markers like SDC2, VIM, APC, MGMT, SFRP1, SFRP2, and NDRG4 have distinct functions previously linked to tumor progression. Although numerous studies have identified tumor-specific methylation changes, most of these alterations were observed in a single study only. The lack of validation in independent samples means low reproducibility and is a major limitation. The genome-wide determination of methylation status (methylome) can provide data to solve these issues. In the third section of the review, methylome studies focusing on different aspects related to CRC, including precancerous lesions, CRC-specific changes, molecular subtypes, aging, and chemotherapy response are summarized. Notably, techniques simultaneously analyzing a large set of regions can also uncover epigenetic regulation of genes which have not yet been associated with tumorigenesis previously. A remaining constraint of studies published to date is the low patient number utilized in these preventing the identification of clinically valuable biomarker candidates. Either future large-scale studies or the integration of already available methylome-level data will be necessary to uncover biomarkers sufficiently robust for clinical application.

Epigenome-Wide DNA Methylation Profiling in Colorectal Cancer and Normal Adjacent Colon Using Infinium Human Methylation 450K

The aims were to profile the DNA methylation in colorectal cancer (CRC) and to explore cancer-specific methylation biomarkers. Fifty-four pairs of CRCs and the adjacent normal tissues were subjected to Infinium Human Methylation 450K assay and analysed using ChAMP R package. A total of 26,093 differentially methylated probes were identified, which represent 6156 genes; 650 probes were hypermethylated, and 25,443 were hypomethylated. Hypermethylated sites were common in CpG islands, while hypomethylated sites were in open sea. Most of the hypermethylated genes were associated with pathways in cancer, while the hypomethylated genes were involved in the PI3K-AKT signalling pathway. Among the identified differentially methylated probes, we found evidence of four potential probes in CRCs versus adjacent normal; HOXA2 cg06786372, OPLAH cg17301223, cg15638338, and TRIM31 cg02583465 that could serve as a new biomarker in CRC since these probes were aberrantly methylated in CRC as well as involved in the progression of CRC. Furthermore, we revealed the potential of promoter methylation ADHFE1 cg18065361 in differentiating the CRC from normal colonic tissue from the integrated analysis. In conclusion, aberrant DNA methylation is significantly involved in CRC pathogenesis and is associated with gene silencing. This study reports several potential important methylated genes in CRC and, therefore, merit further validation as novel candidate biomarker genes in CRC.

Genome-wide DNA methylation profiling and identification of potential pan-cancer and tumor-specific biomarkers

DNA methylation alterations have already been linked to cancer, and their usefulness for therapy and diagnosis has encouraged research into the human epigenome. Several biomarker studies have focused on identifying cancer types individually, yet common cancer and multi-cancer markers are still underexplored. We used The Cancer Genome Atlas (TCGA) to investigate genome-wide methylation profiles of 14 different cancer types and developed a three-step computational approach to select candidate biomarker CpG sites. In total, 1,991 pan-cancer and between 75 and 1,803 cancer-specific differentially methylated CpG sites were discovered. Differentially methylated blocks and regions were also discovered for the first time on such a large-scale. Through a three-step computational approach, a combination of four pan-cancer CpG markers was identified from these sites and externally validated (AUC = 0.90), maintaining comparable performance across tumor stages. Additionally, 20 tumor-specific CpG markers were identified and made up the final type-specific prediction model, which could accurately differentiate tumor types (AUC = 0.87-0.99). Our study highlights the power of the methylome as a rich source of cancer biomarkers, and the signatures we identified provide a new resource for understanding cancer mechanisms on the wider genomic scale with strong applicability in the context of new minimally invasive cancer detection assays.

Culture-Associated DNA Methylation Changes Impact on Cellular Function of Human Intestinal Organoids

BACKGROUND & AIMS

Human intestinal epithelial organoids (IEOs) are a powerful tool to model major aspects of intestinal development, health, and diseases because patient-derived cultures retain many features found in vivo. A necessary aspect of the organoid model is the requirement to expand cultures in vitro through several rounds of passaging. This is of concern because the passaging of cells has been shown to affect cell morphology, ploidy, and function.

METHODS

Here, we analyzed 173 human IEO lines derived from the small and large bowel and examined the effect of culture duration on DNA methylation (DNAm). Furthermore, we tested the potential impact of DNAm changes on gene expression and cellular function.

RESULTS

Our analyses show a reproducible effect of culture duration on DNAm in a large discovery cohort as well as 2 publicly available validation cohorts generated in different laboratories. Although methylation changes were seen in only approximately 8% of tested cytosine-phosphate-guanine dinucleotides (CpGs) and global cellular function remained stable, a subset of methylation changes correlated with altered gene expression at baseline as well as in response to inflammatory cytokine exposure and withdrawal of Wnt agonists. Importantly, epigenetic changes were found to be enriched in genomic regions associated with colonic cancer and distant to the site of replication, indicating similarities to malignant transformation.

CONCLUSIONS

Our study shows distinct culture-associated epigenetic changes in mucosa-derived human IEOs, some of which appear to impact gene transcriptomic and cellular function. These findings highlight the need for future studies in this area and the importance of considering passage number as a potentially confounding factor.

DNA methylation variation along the cancer epigenome and the identification of novel epigenetic driver events

While large-scale studies applying various statistical approaches have identified hundreds of mutated driver genes across various cancer types, the contribution of epigenetic changes to cancer remains more enigmatic. This is partly due to the fact that certain regions of the cancer genome, due to their genomic and epigenomic properties, are more prone to dysregulated DNA methylation than others. Thus, it has been difficult to distinguish which promoter methylation changes are really driving carcinogenesis from those that are mostly just a reflection of their genomic location. By developing a novel method that corrects for epigenetic covariates, we reveal a small, concise set of potential epigenetic driver events. Interestingly, those changes suggest different modes of epigenetic carcinogenesis: first, we observe recurrent inactivation of known cancer genes across tumour types suggesting a higher convergence on common tumour suppressor pathways than previously anticipated. Second, in prostate cancer, a cancer type with few recurrently mutated genes, we demonstrate how the epigenome primes tumours towards higher tolerance of other aberrations.

Colon Cancer-Related Genes Identification and Function Study Based on Single-Cell Multi-Omics Integration

Transcriptomes and DNA methylation of colon cancer at the single-cell level are used to identify marker genes and improve diagnoses and therapies. Seven colon cancer subtypes are recognized based on the single-cell RNA sequence, and the differentially expressed genes regulated by dysregulated methylation are identified as marker genes for different types of colon cancer. Compared with normal colon cells, marker genes of different types show very obvious specificity, especially upregulated genes in tumors. Functional enrichment analysis for marker genes indicates a possible relation between colon cancer and nervous system disease, moreover, the weak immune system is verified in colon cancer. The heightened expression of markers and the reduction of methylation in colon cancer promote tumor development in an extensive mechanism so that there is no biological process that can be enriched in different types.

Integrative Analysis of DNA Methylation and Gene Expression Profiles Identifies Colorectal Cancer-Related Diagnostic Biomarkers

Background: Colorectal cancer (CRC) is a common human malignancy worldwide. The prognosis of patients is largely frustrated by delayed diagnosis or misdiagnosis. DNA methylation alterations have been previously proved to be involved in CRC carcinogenesis.

Methods: In this study, we proposed to identify CRC-related diagnostic biomarkers by analyzing DNA methylation and gene expression profiles. TCGA-COAD datasets downloaded from the Cancer Genome Atlas (TCGA) were used as the training set to screen differential expression genes (DEGs) and methylation CpG sites (dmCpGs) in CRC samples. A logistic regression model was constructed based on hyper-methylated CpG sites which were located in downregulated genes for CRC diagnosis. Another two independent datasets from the Gene Expression Omnibus (GEO) were used as a testing set to evaluate the performance of the model in CRC diagnosis.

Results: We found that CpG island methylator phenotype (CIMP) was a potential signature of poor prognosis by dividing CRC samples into CIMP and noCIMP groups based on a set of CpG sites with methylation standard deviation (sd) > 0.2 among CRC samples and low methylation levels (mean β < 0.05) in adjacent samples. Hyper-methylated CpGs tended to be more closed to CpG island (CGI) and transcription start site (TSS) relative to hypo-methylated CpGs (p-value < 0.05, Fisher exact test). A logistic regression model was finally constructed based on two hyper-methylated CpGs, which had an area under receiver operating characteristic curve of 0.98 in the training set, and 0.85 and 0.95 in the two independent testing sets.

Conclusions: In conclusion, our study identified promising DNA methylation biomarkers for CRC diagnosis.

Aberrantly methylated-differentially genes and pathways among Iranian patients with colorectal cancer

Background

Methylation plays an important role in colorectal cancer (CRC) pathogenesis. The goal of this study was to identify aberrantly differentially methylated genes (DMGs) and pathways through bioinformatics analysis among Iranian CRC patients using Methylation Next Generation Sequencing.

Methods

This study has integrated results of SureSelectXT Methyl-Seq Target with the potential key candidate genes and pathways in CRC. Six CRC and six samples of normal colon were integrated and deeply analyzed. In addition to this gene methylation profiling, several other gene methylation profiling datasets were obtained from Gene Expression Omnibus (GEO) and TCGA datasets. DMGs were sorted and candidate genes and enrichment pathways were analyzed. DMGs-associated protein–protein interaction network (PPI) was constructed based on the STRING online database.

Results

Totally, 320 genes were detected as common genes between our patients and selected GEO and TCGA datasets from the Agilent SureSelect analysis with selecting criteria of p-value < 0.05 and FC ≥ 1.5. DMGs were identified from hyper-DMGs PPI network complex and 10 KEGG pathways were identified. The most important modules were extracted from MCODE, as most of the corresponding genes were involved in cellular process and protein binding.

Conclusions

Hub genes including WNT2, SFRP2, ZNF726 and BMP2 were suggested as potentially diagnostic and therapeutic targets for CRC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02053-0.

A methylation-driven gene panel predicts survival in patients with colon cancer

The accumulation of various genetic and epigenetic changes in colonic epithelial cells has been identified as one of the fundamental processes that drive the initiation and progression of colorectal cancer (CRC). This study aimed to explore functional genes regulated by DNA methylation and their potential utilization as biomarkers for the prediction of CRC prognoses. Methylation‐driven genes (MDGs) were explored by applying the integrative analysis tool (methylmix) to The Cancer Genome Atlas CRC project. The prognostic MDG panel was identified by combining the Cox regression model with the least absolute shrinkage and selection operator regularization. Gene set enrichment analysis was used to determine the pathways associated with the six‐MDG panel. Cluster of differentiation 40 (CD40) expression and methylation in CRC samples were validated by using additional datasets from the Gene Expression Omnibus. Methylation‐specific PCR and bisulfite sequencing were used to confirm DNA methylation in CRC cell lines. A prognostic MDG panel consisting of six gene members was identified: TMEM88, HOXB2, FGD1, TOGARAM1, ARHGDIB and CD40. The high‐risk phenotype classified by the six‐MDG panel was associated with cancer‐related biological processes, including invasion and metastasis, angiogenesis and the tumor immune microenvironment. The prognostic value of the six‐MDG panel was found to be independent of tumor node metastasis stage and, in combination with tumor node metastasis stage and age, could help improve survival prediction. In addition, the expression of CD40 was confirmed to be regulated by promoter region methylation in CRC samples and cell lines. The proposed six‐MDG panel represents a promising signature for estimating the prognosis of patients with CRC.

ADHFE1 is a correlative factor of patient survival in cancer

Alcohol dehydrogenase iron containing 1 (ADHFE1) encodes a hydroxyacid-oxoacid transhydrogenase participating in multiple biological processes. The role of ADHFE1 in cancer has not been fully uncovered. Herein, we performed data analysis to investigate the expression of ADHFE1 and the underlying regulatory mechanisms, its relationship with cancer patients’ survival, and the relevant pathways in cancer. A range of recognized, web-available databases and bioinformatics tools were used in this in silico study. We found that ADHFE1 was frequently downregulated and hypermethylated in various cancer cell lines and tissue samples. High expression of ADHFE1 was positively associated with favorable patient prognosis in breast, colon, and gastric cancers. Pathway analysis revealed its potential role in cancer-related biological processes, including energy metabolism, DNA replication, and cell cycle regulation. AHDFE1 mRNA expression and DNA methylation can potentially be used as diagnostic markers in cancer and might be of great value in predicting the survival of patients with cancer.

Methylated biomarkers for breast cancer identified through public database analysis and plasma target capture sequencing

Background

Aberrant methylation is common during the early stage of cancer development. This study was designed to investigate DNA methylation as biomarker for breast cancer.

Methods

Public database analysis and methylation-specific whole-gene sequencing were conducted to identify methylated biomarkers that would enable early non-invasive diagnosis of breast cancer. Firstly, the data was obtained from the TCGA Database and the Blueprint Epigenome Database. Secondly, methylation-specific whole-gene sequencing was conducted in 10 female patients with early-stage breast cancer and 10 healthy female volunteers from Nanfang Hospital of Southern Medical University between March 2018 and July 2018. Thirdly, the R language was used for data analysis, and KEGG and DAVID online tool was used for annotations.

Results

We found that methylation levels at 13 cytosine-phosphate-guanine (CpG) sites (cg04066177, cg04281344, cg05995576, cg06221609, cg08642731, cg11388802, cg12665414, cg14557216, cg19404723, cg19457909, cg24570211, cg25818763, and cg26215982) in the malignant tissue DNA were highly comparable to those of circulating cell-free DNA (cfDNA) of breast cancer patients, but were significantly different from those of normal tissue DNA, cfDNA of healthy women, and leukocyte DNA. In addition, three CpG sites (cg04281344, cg24570211, and cg26215982) were confirmed in clinical research, which showed that the sensitivity and specificity of these CpGs as biomarkers for breast cancer were 69.4–83.7% and 85.7–88.6%, respectively.

Conclusions

New biomarkers were identified and confirmed for breast cancer by comparing the methylation of tumour tissues, leukocytes, and non-plasma DNA.

Colon cancer-specific diagnostic and prognostic biomarkers based on genome-wide abnormal DNA methylation

Abnormal DNA methylation is a major early contributor to colon cancer (COAD) development. We conducted a cohort-based systematic investigation of genome-wide DNA methylation using 299 COAD and 38 normal tissue samples from TCGA. Through conditional screening and machine learning with a training cohort, we identified one hypomethylated and nine hypermethylated differentially methylated CpG sites as potential diagnostic biomarkers, and used them to construct a COAD-specific diagnostic model. Unlike previous models, our model precisely distinguished COAD from nine other cancer types (e.g., breast cancer and liver cancer; error rate ≤ 0.05) and from normal tissues in the training cohort (AUC = 1). The diagnostic model was verified using a validation cohort from The Cancer Genome Atlas (AUC = 1) and five independent cohorts from the Gene Expression Omnibus (AUC ≥ 0.951). Using Cox regression analyses, we established a prognostic model based on six CpG sites in the training cohort, and verified the model in the validation cohort. The prognostic model sensitively predicted patients’ survival (p ≤ 0.00011, AUC ≥ 0.792) independently of important clinicopathological characteristics of COAD (e.g., gender and age). Thus, our DNA methylation analysis provided precise biomarkers and models for the early diagnosis and prognostic evaluation of COAD.

SCTR hypermethylation is a diagnostic biomarker in colorectal cancer

Diagnostic markers for both colorectal cancer (CRC) and its precursor lesions are lacking. Although aberrant methylation of the secretin receptor (SCTR) gene was observed in CRC, the diagnostic performance has not been evaluated. Therefore, this study aimed to assess and verify the diagnostic value of SCTR methylation of CRC and its precursor lesions through integrating the largest methylation data. The diagnostic performance of SCTR methylation was analyzed in the discovery set from The Cancer Genome Atlas (TCGA) CRC methylation data (N = 440), and verified in a large-scale test set (N = 938) from the Gene Expression Omnibus (GEO). Targeted bisulfite sequencing analysis was developed and applied to detect the methylation status of SCTR in our independent validation set (N = 374). Our findings revealed that the SCTR gene was frequently hypermethylated at its CpG islands in CRC. In the TCGA discovery set, the diagnostic score was constructed using 4 CpG sites (cg01013590, cg20505223, cg07176264, and cg26009192) and achieved high diagnostic performance (area under the ROC curve [AUC] = 0.964). In the GEO test set, the diagnostic score had robust diagnostic ability to distinguish CRC (AUC = 0.948) and its precursor lesions (AUC = 0.954) from normal samples. Moreover, hypermethylation of the SCTR gene was also found in cell-free DNA samples collected from CRC patients, but not in those from healthy controls. In the validation set, consistent results were observed using the targeted bisulfite sequencing array. Our study highlights that hypermethylation at CpG islands of the SCTR gene is a potential diagnostic biomarker in CRCs and its precursor lesions.

FANCF hypomethylation is associated with colorectal cancer in Han Chinese

BACKGROUND/AIMS

Fanconi anemia complement group F (FANCF) is known to be involved in DNA repair, and the overexpression of FANCF protein leads to cell proliferation and ultimately to cancer. The purpose of this study was to assess whether FANCF methylation was associated with colorectal cancer (CRC).

MATERIALS AND METHODS

A case-control experiment was conducted to study the association between FANCF methylation and CRC. We used quantitative methylation-specific PCR to measure the FANCF promoter methylation, and the percentage of methylation reference (PMR) to quantify the FANCF promoter methylation level. To investigate the effect of the selected FANCF fragment on gene expression regulation, we also performed a dual-luciferase reporter gene assay.

RESULTS

The results indicated that FANCF methylation in CRC tumor tissues was significantly lower than that in the nontumor tissues (median PMR: 44.86% vs. 65.77%, p=0.00001). Analysis of receiver-operating characteristic curves showed that FANCF hypomethylation had a diagnostic value for CRC (area under curve [AUC]: 0.670, sensitivity: 55.8%, specificity: 71.7%, p=0.00001). The dual-luciferase reporter assay showed that the FANCF fragment upregulated gene expression (fold change: 1.93, p=0.002).

CONCLUSION

Research demonstrates for the first time that FANCF hypomethylation is significantly associated with CRC risk. FANCF hypomethylation may ultimately increase the risk of CRC by upregulating the expression of FANCF.

Identification and prognostic value of metabolism-related genes in gastric cancer

Gastric cancer (GC) is one of the most commonly occurring cancers, and metabolism-related genes (MRGs) are associated with its development. Transcriptome data and the relevant clinical data were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases, and we identified 194 MRGs differentially expressed between GC and adjacent nontumor tissues. Through univariate Cox and lasso regression analyses we identified 13 potential prognostic differentially expressed MRGs (PDEMRGs). These PDEMRGs (CKMT2, ME1, GSTA2, ASAH1, GGT5, RDH12, NNMT, POLR1A, ACYP1, GLA, OPLAH, DCK, and POLD3) were used to build a Cox regression risk model to predict the prognosis of GC patients. Further univariate and multivariate Cox regression analyses showed that this model could serve as an independent prognostic parameter. Gene Set Enrichment Analysis showed significant enrichment pathways that could potentially contribute to pathogenesis. This model also revealed the probability of genetic alterations of PDEMRGs. We have thus identified a valuable metabolic model for predicting the prognosis of GC patients. The PDEMRGs in this model reflect the dysregulated metabolic microenvironment of GC and provide useful noninvasive biomarkers.

DNA methylation events in transcription factors and gene expression changes in colon cancer

Aim: Gain insight about the role of DNA methylation in the malignant growth of colon cancer. Patients & methods: Methylation and gene expression from 90 adjacent-tumor paired tissues and 48 healthy tissues were analyzed. Tumor genes whose change in expression was explained by changes in methylation were identified using linear models adjusted for tumor stromal content. Results: No differences in methylation were found between adjacent and healthy tissues, but clear differences were found between adjacent and tumor samples. We identified hypermethylated CpG islands located in promoter regions that drive differential gene expression of transcription factors and their target genes. Conclusion: Changes in methylation of a few genes provoke important changes in gene expression, by expanding the signal through transcription activation/repression.

PDX1 DNA Methylation Distinguishes Two Subtypes of Pancreatic Neuroendocrine Neoplasms with a Different Prognosis

DNA methylation is a crucial epigenetic mechanism for gene expression regulation and cell differentiation. Furthermore, it was found to play a major role in multiple pathological processes, including cancer. In pancreatic neuroendocrine neoplasms (PNENs), epigenetic deregulation is also considered to be of significance, as the most frequently mutated genes have an important function in epigenetic regulation. However, the exact changes in DNA methylation between PNENs and the endocrine cells of the pancreas, their likely cell-of-origin, remain largely unknown. Recently, two subtypes of PNENs have been described which were linked to cell-of-origin and have a different prognosis. A difference in the expression of the transcription factor PDX1 was one of the key molecular differences. In this study, we performed an exploratory genome-wide DNA methylation analysis using Infinium Methylation EPIC arrays (Illumina) on 26 PNENs and pancreatic islets of five healthy donors. In addition, the methylation profile of the PDX1 region was used to perform subtyping in a global cohort of 83 PNEN, 2 healthy alpha cell and 3 healthy beta cell samples. In our exploratory analysis, we identified 26,759 differentially methylated CpGs and 79 differentially methylated regions. The gene set enrichment analysis highlighted several interesting pathways targeted by altered DNA methylation, including MAPK, platelet-related and immune system-related pathways. Using the PDX1 methylation in 83 PNEN, 2 healthy alpha cell and 3 healthy beta cell samples, two subtypes were identified, subtypes A and B, which were similar to alpha and beta cells, respectively. These subtypes had different clinicopathological characteristics, a different pattern of chromosomal alterations and a different prognosis, with subtype A having a significantly worse prognosis compared with subtype B (HR 0.22 [95% CI: 0.051–0.95], p = 0.043). Hence, this study demonstrates that several cancer-related pathways are differently methylated between PNENs and normal islet cells. In addition, we validated the use of the PDX1 methylation status for the subtyping of PNENs and its prognostic importance.

High-Yield Methylation Markers for Stool-Based Detection of Colorectal Cancer

BACKGROUND

Many methylation markers associated with colorectal cancer have been reported, but few of them are actually used in clinical practice.

AIMS

This study was designed to identify promising methylation markers for stool-based detection of colorectal cancer.

METHODS

We first tested 324 reported methylated genes in colorectal cancer cell lines. A total of 111 heavily methylated genes were selected for further evaluation with a pilot set of colorectal cancer and adjacent normal tissues. Ten high-yield methylated markers were further studied in 319 tissue samples. Eventually, the four best markers, namely methylated COL4A1, COL4A2, TLX2, and ITGA4, were validated in 240 stool samples. Methylation-specific PCR (MSP) and real-time MSP (qMSP) were employed for methylation detection.

RESULTS

After hierarchical selection, ten differentially methylated genes demonstrated high sensitivity and specificity for the detection of colorectal cancer in tissue. When validated in stool samples, the four with the best performance-COL4A1, COL4A2, TLX2, and ITGA4-were able to detect 82.5-92.5% of colorectal cancers and 41.6-58.4% of adenomas (≥ 1 cm) with specificity of 88.0-96.4%. The best combination, COL4A2 and TLX2, detected 91.3% of CRCs and 51.9% of advanced adenomas in stool with 97.6% specificity.

CONCLUSIONS

Methylated COL4A1, COL4A2, TLX2, and ITGA4 demonstrated high accuracy for the detection of colorectal neoplasms in stool. They are potentially valuable markers for the detection of colorectal cancer.

DNMIVD: DNA methylation interactive visualization database

Aberrant DNA methylation plays an important role in cancer progression. However, no resource has been available that comprehensively provides DNA methylation-based diagnostic and prognostic models, expression–methylation quantitative trait loci (emQTL), pathway activity-methylation quantitative trait loci (pathway-meQTL), differentially variable and differentially methylated CpGs, and survival analysis, as well as functional epigenetic modules for different cancers. These provide valuable information for researchers to explore DNA methylation profiles from different aspects in cancer. To this end, we constructed a user-friendly database named DNA Methylation Interactive Visualization Database (DNMIVD), which comprehensively provides the following important resources: (i) diagnostic and prognostic models based on DNA methylation for multiple cancer types of The Cancer Genome Atlas (TCGA); (ii) meQTL, emQTL and pathway-meQTL for diverse cancers; (iii) Functional Epigenetic Modules (FEM) constructed from Protein-Protein Interactions (PPI) and Co-Occurrence and Mutual Exclusive (COME) network by integrating DNA methylation and gene expression data of TCGA cancers; (iv) differentially variable and differentially methylated CpGs and differentially methylated genes as well as related enhancer information; (v) correlations between methylation of gene promoter and corresponding gene expression and (vi) patient survival-associated CpGs and genes with different endpoints. DNMIVD is freely available at http://www.unimd.org/dnmivd/. We believe that DNMIVD can facilitate research of diverse cancers.

Hypermethylation and decreased expression of TMEM240 are potential early-onset biomarkers for colorectal cancer detection, poor prognosis, and early recurrence prediction

BACKGROUND

Gene silencing by aberrant DNA methylation of promoter regions remains the most dominant phenomenon occurring during tumorigenesis. Improving the early diagnosis, prognosis, and recurrence prediction of colorectal cancer using noninvasive aberrant DNA methylation biomarkers has encouraging potential. The aim of this study is to characterize the DNA methylation of the promoter region of TMEM240, as well as gene expression and its effect on cell biological functions and its applications in early detection and outcome prediction.

RESULTS

Highly methylated CpG sites were identified in the TMEM240 gene by Illumina methylation 450K arrays in 26 Taiwanese patient paired samples and 38 paired samples from The Cancer Genome Atlas (TCGA) colorectal cancer dataset. Transient transfection and knockdown of TMEM240 were performed to demonstrate the role of TMEM240 in colorectal cancer cells. The data showed that TMEM240 could lead to G1 cell cycle arrest, repress cancer cell proliferation, and inhibit cancer cell migration. The quantitative methylation-specific real-time polymerase chain reaction (PCR) results revealed that 87.8% (480 of 547) of the colorectal cancer tumors had hypermethylated TMEM240, and this was also found in benign tubular adenomas (55.6%). Circulating cell-free methylated TMEM240 was detected in 13 of 25 (52.0%) Taiwanese colorectal cancer patients but in fewer (28.6%) healthy controls. In 72.0% (85/118) of tissue samples, TMEM240 mRNA expression was lower in Taiwanese CRC tumor tissues than in normal colorectal tissues according to real-time reverse transcription PCR results, and this was also found in benign tubular adenomas (44.4%). The TMEM240 protein was analyzed in South Korean and Chinese CRC patient samples using immunohistochemistry. The results exhibited low protein expression in 91.7% (100/109) of tumors and 75.0% (24/32) of metastatic tumors but exhibited high expression in 75.0% (6/8) of normal colon tissues. Multivariate Cox proportional hazards regression analysis found that mRNA expression of TMEM240 was significantly associated with overall, cancer-specific, and recurrence-free survival (p = 0.012, 0.007, and 0.022, respectively).

CONCLUSIONS

Alterations in TMEM240 are commonly found in Western and Asian populations and can potentially be used for early prediction and as poor prognosis and early-recurrence biomarkers in colorectal cancer.

Genome-Wide Open Chromatin Methylome Profiles in Colorectal Cancer

The methylome of open chromatins was investigated in colorectal cancer (CRC) to explore cancer-specific methylation and potential biomarkers. Epigenome-wide methylome of open chromatins was studied in colorectal cancer tissues using the Infinium DNA MethylationEPIC assay. Differentially methylated regions were identified using the ChAMP Bioconductor. Our stringent analysis led to the discovery of 2187 significant differentially methylated open chromatins in CRCs. More hypomethylated probes were observed and the trend was similar across all chromosomes. The majority of hyper- and hypomethylated probes in open chromatin were in chromosome 1. Our unsupervised hierarchical clustering analysis showed that 40 significant differentially methylated open chromatins were able to segregate CRC from normal colonic tissues. Receiver operating characteristic analyses from the top 40 probes revealed several significant, highly discriminative, specific and sensitive probes such as OPLAH cg26256223, EYA4 cg01328892, and CCNA1 cg11513637, among others. OPLAH cg26256223 hypermethylation is associated with reduced gene expression in the CRC. This study reports many open chromatin loci with novel differential methylation statuses, some of which with the potential as candidate markers for diagnostic purposes.

Enhanced CXCR4 Expression Associates with Increased Gene Body 5-Hydroxymethylcytosine Modification but not Decreased Promoter Methylation in Colorectal Cancer

In colorectal cancer (CRC), upregulation of the C-X-C motif chemokine receptor 4 (CXCR4) is correlated with metastasis and poor prognosis, highlighting the need to further elucidate CXCR4’s regulation in CRC. For the first time, DNA methylation and 5-hydroxymethylcytosine aberrations were investigated to better understand the epigenetic regulation of CXCR4 in CRC. CXCR4 expression levels were measured using qPCR and immunoblotting in normal colon tissues, primary colon cancer tissues and CRC cell lines. Publicly available RNA-seq and methylation data from The Cancer Genome Atlas (TCGA) were extracted from tumors from CRC patients. The DNA methylation status spanning CXCR4 gene was evaluated using combined bisulfite restriction analysis (COBRA). The methylation status in the CXCR4 gene body was analyzed using previously performed nano-hmC-seal data from colon cancers and adjacent normal colonic mucosa. CXCR4 expression levels were significantly increased in tumor stromal cells and in tumor colonocytes, compared to matched cell types from adjacent normal-appearing mucosa. CXCR4 promoter methylation was detected in a minority of colorectal tumors in the TCGA. The CpG island of the CXCR4 promoter showed increased methylation in three of four CRC cell lines. CXCR4 protein expression differences were also notable between microsatellite stable (MSS) and microsatellite instable (MSI) tumor cell lines. While differential methylation was not detected in CXCR4, enrichment of 5-hydroxymethylcytosine (5hmC) in CXCR4 gene bodies in CRC was observed compared to adjacent mucosa.

Genome-wide analysis of DNA methylation identifies two CpG sites for the early screening of colorectal cancer

Aim: To identify a panel of DNA methylation markers for the early diagnosis of colorectal cancer (CRC). Materials & methods: Using public omics data and our pyrosequencing data, we developed and validated a global methylation model and a CpG-methylation-based model for CRC screening. Results: Both of the models yielded high sensitivity and specificity for distinguishing CRC and its precursors (colorectal adenoma and colorectal laterally spreading tumor) from normal controls in eight independent datasets and our newly collected samples. More importantly, the two-CpG-based model showed high specificity in excluding inflammatory bowel diseases and other 13 cancer types. Conclusion: A diagnostic model based on two CpGs (cg09239744 and cg12587766) may be a powerful tool for CRC screening.

MeinteR: A framework to prioritize DNA methylation aberrations based on conformational and cis-regulatory element enrichment

DNA methylation studies have been reformed with the advent of single-base resolution arrays and bisulfite sequencing methods, enabling deeper investigation of methylation-mediated mechanisms. In addition to these advancements, numerous bioinformatics tools address important computational challenges, covering DNA methylation calling up to multi-modal interpretative analyses. However, contrary to the analytical frameworks that detect driver mutational signatures, the identification of putatively actionable epigenetic events remains an unmet need. The present work describes a novel computational framework, called MeinteR, that prioritizes critical DNA methylation events based on the following hypothesis: critical aberrations of DNA methylation more likely occur on a genomic substrate that is enriched in cis-acting regulatory elements with distinct structural characteristics, rather than in genomic “deserts”. In this context, the framework incorporates functional cis-elements, e.g. transcription factor binding sites, tentative splice sites, as well as conformational features, such as G-quadruplexes and palindromes, to identify critical epigenetic aberrations with potential implications on transcriptional regulation. The evaluation on multiple, public cancer datasets revealed significant associations between the highest-ranking loci with gene expression and known driver genes, enabling for the first time the computational identification of high impact epigenetic changes based on high-throughput DNA methylation data.

Genome-wide methylation and expression profiling identify methylation-associated genes in colorectal cancer

Aim: To identify methylation-associated genes in the carcinogenesis of colorectal cancer (CRC). Materials & methods: Genome-wide patterns of DNA methylation and gene expression in CRC tissues and adjacent normal tissues were determined and further validated in The Cancer Genome Atlas data and Chinese CRC patients, respectively. Gene overexpression and knockdown cells were constructed to investigate their biological roles in CRC. Results: After validations, hypermethylation of eight genes were found to be correlated with their reduced transcription, and hypomethyaltion of three genes were associated with their upregulation. CADM3, CNRIP1, GRHL2, GRIA4, GSTM2 and NRXN1 were associated with the overall survival of CRC patients. CNRIP1 and GSTM2 were mainly responsible for the proliferation in CRC cells. Conclusion: A total of 11 genes may be promising biomarkers for CRC.

Epigenomic dysregulation-mediated alterations of key biological pathways and tumor immune evasion are hallmarks of gingivo-buccal oral cancer

BACKGROUND

Gingivo-buccal oral squamous cell carcinoma (OSCC-GB) is the most common cancer among men in India and is associated with high mortality. Although OSCC-GB is known to be quite different from tongue cancer in its genomic presentation and its clinical behavior, it is treated identically as tongue cancer. Predictive markers of prognosis and therapy that are specific to OSCC-GB are, therefore, required. Although genomic drivers of OSCC-GB have been identified by whole exome and whole genome sequencing, no epigenome-wide study has been conducted in OSCC-GB; our study has filled this gap, and has discovered and validated epigenomic hallmarks of gingivobuccal oral cancer.

METHODS

We have carried out integrative analysis of epigenomic (n = 87) and transcriptomic (n = 72) profiles of paired tumor-normal tissues collected from OSCC-GB patients from India. Genome-wide DNA methylation assays and RNA-sequencing were performed on high-throughput platforms (Illumina) using a half-sample of randomly selected patients to discover significantly differentially methylated probes (DMPs), which were validated on the remaining half-sample of patients.

RESULTS

About 200 genes showed significant inverse correlation between promoter methylation and expression, of which the most significant genes included genes that act as transcription factors and genes associated with other cancer types. Novel findings of this study include identification of (a) potential immunosuppressive effect in OSCC-GB due to significant promoter hypomethylation driven upregulation of CD274 and CD80, (b) significant dysregulation by epigenetic modification of DNMT3B (upregulation) and TET1 (downregulation); and (c) known drugs that can reverse the direction of dysregulation of gene expression caused by promoter methylation.

CONCLUSIONS

In OSCC-GB patients, there are significant alterations in expression of key genes that (a) regulate normal cell division by maintenance of balanced DNA methylation and transcription process, (b) maintain normal physiological signaling (PPAR, B cell receptor) and metabolism (arachidonic acid) pathways, and (c) provide immune protection against antigens, including tumor cells. These findings indicate novel therapeutic targets, including immunotherapeutic, for treatment of OSCC-GB.

Cell-of-Origin DNA Methylation Signatures Are Maintained during Colorectal Carcinogenesis

Colorectal adenomas are precursor lesions of colorectal cancers and represent clonal amplifications of single cells from colonic crypts. DNA methylation patterns specify cell-type identity during cellular differentiation and, therefore, provide opportunities for the molecular analysis of tumors. We have now analyzed DNA methylation patterns in colorectal adenomas and identified three biologically defined subclasses that describe different intestinal crypt differentiation stages. Importantly, colorectal carcinomas could be classified into the same methylation subtypes, reflecting their shared cell types of origin with adenomas. Further data analysis also revealed significantly reduced overall survival for one of the subtypes. Our results provide a concept for understanding the methylation patterns observed in colorectal cancer and provide opportunities for tumor subclassification and patient stratification.

Hypermethylation Of ADHFE1 Promotes The Proliferation Of Colorectal Cancer Cell Via Modulating Cell Cycle Progression

Background

Colorectal cancer (CRC) is one of the most common malignancies worldwide. Studies have demonstrated that epigenetic modifications play essential roles in the development of CRC. ADHFE1 is a differentially expressed gene that has been reported to be hypermethylated in CRC. However, the role and mechanism of ADHFE1 in the proliferation of CRC remain unclear.

Materials and methods

ADHFE1 expression was analyzed in CRC tissues by IHC and qRT-PCR, and the relationship between ADHFE1 expression and the clinicopathological parameters was analyzed. Cell proliferation were assessed by the in vitro and in vivo experimental models. GSEA assay was performed to explore the mechanism of ADHFE1 in the proliferation of CRC. Flow cytometry and Western blot were used to detect the activation of the cell cycle signaling. Bisulfite genomic sequence (BSP) assay was used to test the methylation degree of ADHFE1 gene promoter in CRC tissues.

Results

Here, we verified that ADHFE1 was down-regulated and hypermethylated in CRC tissues. The down-regulation of ADHFE1 was correlated with poor differentiation and advanced TNM stage of CRC patients. And ADHFE1 expression restored when the CRC cell line SW620 was treated with the demethylating agent 5-Aza-CdR. Overexpression of ADHFE1 inhibited the proliferation of CRC, while ADHFE1 knockdown promoted the proliferation of CRC cells in vitro and in vivo. Moreover, ADHFE1 overexpression could induce a significant G1-S cell cycle arrest in CRC cells and vice versa.

Conclusion

Hypermethylation of ADHFE1 might promote cell proliferation by modulating cell cycle progression in CRC, potentially providing a new therapeutic target for CRC patients.

A prognostic CpG score derived from epigenome-wide profiling of tumor tissue was independently associated with colorectal cancer survival

Background

Results of previous studies on the association of the CpG island methylator phenotype (CIMP) with colorectal cancer (CRC) prognosis were inconsistent and mostly based on different CIMP definitions. The current study aimed to comprehensively investigate the associations between DNA methylation on genes previously used to define CIMP status with CRC survival.

Results

Patients with CRC followed up for a median of 5.2 years were divided into a study cohort (n = 568) and a validation cohort (n = 308). DNA methylation was measured in tumor tissue using the Illumina Infinium HumanMethylation450 BeadChip and restricted to 43 genes used to define CIMP status in previous studies. Cox proportional hazard regression models were used to estimate adjusted hazard ratios (HR) and 95% confidence intervals (CI) of survival after CRC, including adjustment for tumor stage, microsatellite instability, and BRAF mutation status. In the study cohort, ten CpG sites were identified to be associated with CRC survival. Seven of these ten CpG sites were also associated with CRC survival in the validation cohort and were used to construct a prognostic score. CRC patients with a prognostic score of the lowest methylation level showed poorer disease-specific survival compared with patients with the highest methylation level in both the study cohort and the validation cohort (HR = 3.11 and 95% CI = 1.97–4.91, and HR = 3.06 and 95% CI = 1.71–5.45, respectively).

Conclusions

A CpG panel consisting of seven CpG sites was found to be strongly associated with CRC survival, independent from important clinical factors and mutations associated with CIMP. Further studies are required to confirm these findings.

Electronic supplementary material

The online version of this article (10.1186/s13148-019-0703-4) contains supplementary material, which is available to authorized users.

Identification of differentially expressed genes regulated by methylation in colon cancer based on bioinformatics analysis

BACKGROUND

DNA methylation, acknowledged as a key modification in the field of epigenetics, regulates gene expression at the transcriptional level. Aberrant methylation in DNA regulatory regions could upregulate oncogenes and downregulate tumor suppressor genes without changing the sequences. However, studies of methylation in the control of gene expression are still inadequate. In the present research, we performed bioinformatics analysis to clarify the function of methylation and supply candidate methylation-related biomarkers and drivers for colon cancer.

AIM

To identify and analyze methylation-regulated differentially expressed genes (MeDEGs) in colon cancer by bioinformatics analysis.

METHODS

We downloaded RNA expression profiles, Illumina Human Methylation 450K BeadChip data, and clinical data of colon cancer from The Cancer Genome Atlas project. MeDEGs were identified by analyzing the gene expression and methylation levels using the edgeR and limma package in R software. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed in the DAVID database and KEGG Orthology-Based Annotation System 3.0, respectively. We then conducted Kaplan–Meier survival analysis to explore the relationship between methylation and expression and prognosis. Gene set enrichment analysis (GSEA) and investigation of protein-protein interactions (PPI) were performed to clarify the function of prognosis-related genes.

RESULTS

A total of 5 up-regulated and 81 down-regulated genes were identified as MeDEGs. GO and KEGG pathway analyses indicated that MeDEGs were enriched in multiple cancer-related terms. Furthermore, Kaplan–Meier survival analysis showed that the prognosis was negatively associated with the methylation status of glial cell-derived neurotrophic factor (GDNF) and reelin (RELN). In PPI networks, GDNF and RELN interact with neural cell adhesion molecule 1. Besides, GDNF can interact with GDNF family receptor alpha (GFRA1), GFRA2, GFRA3, and RET. RELN can interact with RAFAH1B1, disabled homolog 1, very low-density lipoprotein receptor, lipoprotein receptor-related protein 8, and NMDA 2B. Based on GSEA, hypermethylation of GDNF and RELN were both significantly associated with pathways including “RNA degradation,” “ribosome,” “mismatch repair,” “cell cycle” and “base excision repair.”

CONCLUSION

Aberrant DNA methylation plays an important role in colon cancer progression. MeDEGs that are associated with the overall survival of patients may be potential targets in tumor diagnosis and treatment.

Epigenetic silencing of TGFBI confers resistance to trastuzumab in human breast cancer

Background

Acquired resistance to trastuzumab is a major clinical problem in the treatment of HER2-positive (HER2+) breast cancer patients. The selection of trastuzumab-resistant patients is a great challenge of precision oncology. The aim of this study was to identify novel epigenetic biomarkers associated to trastuzumab resistance in HER2+ BC patients.

Methods

We performed a genome-wide DNA methylation (450K array) and a transcriptomic analysis (RNA-Seq) comparing trastuzumab-sensitive (SK) and trastuzumab-resistant (SKTR) HER2+ human breast cancer cell models. The methylation and expression levels of candidate genes were validated by bisulfite pyrosequencing and qRT-PCR, respectively. Functional assays were conducted in the SK and SKTR models by gene silencing and overexpression. Methylation analysis in 24 HER2+ human BC samples with complete response or non-response to trastuzumab-based treatment was conducted by bisulfite pyrosequencing.

Results

Epigenomic and transcriptomic analysis revealed the consistent hypermethylation and downregulation of TGFBI, CXCL2, and SLC38A1 genes in association with trastuzumab resistance. The DNA methylation and expression levels of these genes were validated in both sensitive and resistant models analyzed. Of the genes, TGFBI presented the highest hypermethylation-associated silencing both at the transcriptional and protein level. Ectopic expression of TGFBI in the SKTR model suggest an increased sensitivity to trastuzumab treatment. In primary tumors, TGFBI hypermethylation was significantly associated with trastuzumab resistance in HER2+ breast cancer patients.

Conclusions

Our results suggest for the first time an association between the epigenetic silencing of TGFBI by DNA methylation and trastuzumab resistance in HER2+ cell models. These results provide the basis for further clinical studies to validate the hypermethylation of TGFBI promoter as a biomarker of trastuzumab resistance in HER2+ breast cancer patients.

Electronic supplementary material

The online version of this article (10.1186/s13058-019-1160-x) contains supplementary material, which is available to authorized users.

DNA methylation changes that precede onset of dysplasia in advanced sessile serrated adenomas

Background

Sessile serrated adenomas (SSAs) are common polyps which give rise to 20–30% of colorectal cancer (CRC). SSAs display clinicopathologic features which present challenges in surveillance, including overrepresentation in young patients, proclivity for the proximal colon and rarity of histologic dysplasia (referred to then as SSAs with dysplasia, SSADs). Once dysplasia develops, there is rapid progression to CRC, even at a small size. There is therefore a clinical need to separate the “advanced” SSAs at high risk of progression to SSAD and cancer from ordinary SSAs. Since SSAs are known to accumulate methylation over time prior to the development of dysplasia, SSAD backgrounds (the remnant SSA present within an SSAD) likely harbour additional methylation events compared with ordinary SSAs. We therefore performed MethyLight and comprehensive methylation array (Illumina MethylationEPIC) on 40 SSAD backgrounds and 40 matched ordinary SSAs, and compared the methylation results with CRC methylation, CRC expression and immunohistochemical data.

Results

SSAD backgrounds demonstrated significant hypermethylation of CpG islands compared with ordinary SSAs, and the proportion of hypermethylated probes decreased progressively in the shore, shelf and open sea regions. Hypomethylation occurred in concert with hypermethylation, which showed a reverse pattern, increasing progressively away from the island regions. These methylation changes were also identified in BRAF-mutant hypermethylated CRCs. When compared with CRC expression data, SV2B, MLH1/EPM2AIP1, C16orf62, RCOR3, BAIAP3, OGDHL, HDHD3 and ATP1B2 demonstrated both promoter hypermethylation and decreased expression. Although SSAD backgrounds were histologically indistinguishable from ordinary SSAs, MLH1 methylation was detectable via MethyLight in 62.9% of SSAD backgrounds, and focal immunohistochemical MLH1 loss was seen in 52.5% of SSAD backgrounds.

Conclusions

Significant hyper- and hypomethylation events occur during SSA progression well before the development of histologically identifiable changes. Methylation is a heterogeneous process within individual SSAs, as typified by MLH1, where both MLH1 methylation and focal immunohistochemical MLH1 loss can be seen in the absence of dysplasia. This heterogeneity is likely a generalised phenomenon and should be taken into account in future methylation-based studies and the development of clinical methylation panels.

Electronic supplementary material

The online version of this article (10.1186/s13148-019-0691-4) contains supplementary material, which is available to authorized users.

Study of Promoter Methylation Patterns of HOXA2, HOXA5, and HOXA6 and Its Clinicopathological Characteristics in Colorectal Cancer

Research on DNA methylation offers great potential for the identification of biomarkers that can be applied for accurately assessing an individual's risk for cancer. In this article, we try to find the ideal epigenetic genes involved in colorectal cancer (CRC) based on a CRC database and our CRC cohort. The top 20 genes with an extremely high frequency of hypermethylation in CRC were identified in the latest database. Remarkably, 3 HOXA genes were included in this list and ranked at the top. The percentage of methylation in the HOXA5, HOXA2, and HOXA6 genes in CRC were up to 67.62, 58.36, and 31.32%, respectively, and ranked first in CRC among all human tumor tissues. Paired colorectal tumor samples and adjacent non-tumor colorectal tissue samples and four CRC cell lines were selected for MethylTarget™ assays. The results demonstrated that CRC tissues and cells had a stronger methylation status around the 3 HOXA gene promoter regions compared with adjacent non-tumor colonic tissue samples. The Receiver operator characteristic curve (ROC) curves for HOXA genes show excellent diagnostic ability in distinguishing tissue from healthy individuals and CRC patients, especially for Stage I patients (AUC = 0.9979 in HOXA2, 0.9309 in HOXA5, and 0.8025 in HOXA6). An association analysis between the methylation pattern of HOXA genes and clinical indicators was performed and found that HOXA2 methylation was significantly associated with age, N, stage, M, lymphovascular invasion, perineural invasion, lymph node number. HOXA5 methylation was associated with age, T, M, stage, and tumor status, and HOXA6 methylation was associated with age and KRAS mutation. Notably, we found that the highest methylation of HOXA5 and HOXA2 occurs in the early stages of colorectal cancer tissues such as stage I, N0, MO, and non-invasive tissues. The methylation levels declined as tumors progressed. However, methylation level at any stage of the tumor was still significantly higher than in normal tissues (p < 0.0001). The mRNA of the 3 HOXA genes was downregulated in early tumor stages due to hypermethylation of CpG islands adjacent to the promoters of the genes. In addition, hypermethylation of HOXA5 and HOXA6 mainly occurred in patients < 60 years old and with MSI-L, MSS, CIMP.L and non-CIMP tumors. Together, this suggests that epigenetic silencing of 3 adjacent HOXA genes may be an important event in the progression of colorectal cancer.

Methylation analysis of Gasdermin E shows great promise as a biomarker for colorectal cancer

In addition to its implication in hereditary hearing loss, the Gasdermin E (GSDME) gene is also a tumor suppressor involved in cancer progression through programmed cell death. GSDME epigenetic silencing through methylation has been shown in some cancer types, but studies are yet to fully explore its diagnostic/prognostic potential in colorectal cancer on a large-scale. We used public data from The Cancer Genome Atlas (TCGA) to investigate differences in GSDME methylation and expression between colorectal cancer and normal colorectal tissue, and between left- and right-sided colorectal cancers in 432 samples. We also explored GSDME's diagnostic capacity as a biomarker for colorectal cancer. We observed differential methylation in all 22 GSDME CpGs between tumor and normal tissues, and in 18 CpGs between the left- and right-sided groups. In the cancer tissue, putative promoter probes were hypermethylated and gene body probes were hypomethylated, while this pattern was inversed in normal tissues. Both putative promoter and gene body CpGs correlated well together but formed distinct methylation patterns with the putative promoter exhibiting the most pronounced methylation differences between tumor and normal tissues. Clinicopathological parameters, excluding age, did not show any effect on CpG methylation. Although the methylation of 5 distinct probes was a good predictor of gene expression, we could not identify an association between GSDME methylation and expression in general. Survival analysis showed no association between GSDME methylation and expression on 5-year patient survival. Through logistic regression, we identified a combination of 2 CpGs, that can discriminate between cancer and normal tissue with high accuracy (AUC = 0.95) irrespective of age and tumor stage. We also validated our model in 3 external methylation datasets, from the Gene Expression Omnibus database, and similar results were reached. Our results suggest that GSDME is a promising biomarker for the detection of colorectal cancer.

DNA methylation of shelf, shore and open sea CpG positions distinguish high microsatellite instability from low or stable microsatellite status colon cancer stem cells

Aim: To investigate the genome-wide methylation of genetically characterized colorectal cancer stem cell (CR-CSC) lines. Materials & methods: Eight CR-CSC lines were isolated from primary colorectal cancer (CRC) tissues, cultured and characterized for aneuploidy, mutational status of CRC-related genes and microsatellite instability (MSI). Genome-wide DNA methylation was assessed by MethylationEPIC microarray. Results: We describe a distinctive methylation pattern that is maintained following in vivo passages in immune-compromised mice. We identified an epigenetic CR-CSC signature associated with MSI. We noticed that the preponderance of the differentially methylated positions do not reside at CpG islands, but spread to shelf and open sea regions. Conclusion: Given that CRCs with MSI-high status have a lower metastatic potential, the identification of a MSI-related methylation signature could provide new insights and possible targets into metastatic CRC.

Genes CEP55, FOXD3, FOXF2, GNAO1, GRIA4, and KCNA5 as potential diagnostic biomarkers in colorectal cancer

Background

Colorectal cancer (CRC) is one of the leading causes of death by cancer worldwide and in need of novel potential diagnostic biomarkers for early discovery.

Methods

We conducted a two-step study. We first employed bioinformatics on data from The Cancer Genome Atlas to obtain potential biomarkers and then experimentally validated some of them on our clinical samples. Our aim was to find a methylation alteration common to all clusters, with the potential of becoming a diagnostic biomarker in CRC.

Results

Unsupervised clustering of methylation data resulted in four clusters, none of which had a known common genetic or epigenetic event, such as mutations or methylation. The intersect among clusters and regulatory regions resulted in 590 aberrantly methylated probes, belonging to 198 differentially expressed genes. After performing pathway and functional analysis on differentially expressed genes, we selected six genes: CEP55, FOXD3, FOXF2, GNAO1, GRIA4 and KCNA5, for further experimental validation on our own clinical samples. In silico analysis demonstrated that CEP55 was hypomethylated in 98.7% and up-regulated in 95.0% of samples. Genes FOXD3, FOXF2, GNAO1, GRIA4 and KCNA5 were hypermethylated in 97.9, 81.1, 80.3, 98.4 and 94.0%, and down-regulated in 98.3, 98.9, 98.1, 98.1 and 98.6% of samples, respectively. Our experimental data show CEP55 was hypomethylated in 97.3% of samples and down-regulated in all samples, while FOXD3, FOXF2, GNAO1, GRIA4 and KCNA5 were hypermethylated in 100.0, 90.2, 100.0, 99.1 and 100.0%, and down-regulated in 68.0, 76.0, 96.0, 95.2 and 84.0% of samples, respectively. Results of in silico and our experimental analyses showed that more than 97% of samples had at least four methylation markers altered.

Conclusions

Using bioinformatics followed by experimental validation, we identified a set of six genes that were differentially expressed in CRC compared to normal mucosa and whose expression seems to be methylation dependent. Moreover, all of these six genes were common in all methylation clusters and mutation statuses of CRC and as such are believed to be an early event in human CRC carcinogenesis and to represent potential CRC biomarkers.

Electronic supplementary material

The online version of this article (10.1186/s12920-019-0501-z) contains supplementary material, which is available to authorized users.