Identification of regulatory role of DNA methylation in colon cancer gene expression via systematic bioinformatics analysis

Promoter hypermethylation of neural-related genes is compatible with stemness in solid cancers

BACKGROUND

DNA hypermethylation is an epigenetic feature that modulates gene expression, and its deregulation is observed in cancer. Previously, we identified a neural-related DNA hypermethylation fingerprint in colon cancer, where most of the top hypermethylated and downregulated genes have known functions in the nervous system. To evaluate the presence of this signature and its relevance to carcinogenesis in general, we considered 16 solid cancer types available in The Cancer Genome Atlas (TCGA).

RESULTS

All tested cancers showed significant enrichment for neural-related genes amongst hypermethylated genes. This signature was already present in two premalignant tissue types and could not be explained by potential confounders such as bivalency status or tumor purity. Further characterization of the neural-related DNA hypermethylation signature in colon cancer showed particular enrichment for genes that are overexpressed during neural differentiation. Lastly, an analysis of upstream regulators identified RE1-Silencing Transcription factor (REST) as a potential mediator of this DNA methylation signature.

CONCLUSION

Our study confirms the presence of a neural-related DNA hypermethylation fingerprint in various cancers, of genes linked to neural differentiation, and points to REST as a possible regulator of this mechanism. We propose that this fingerprint indicates an involvement of DNA hypermethylation in the preservation of neural stemness in cancer cells.

Nerves in gastrointestinal cancer: from mechanism to modulations

Maintenance of gastrointestinal health is challenging as it requires balancing multifaceted processes within the highly complex and dynamic ecosystem of the gastrointestinal tract. Disturbances within this vibrant environment can have detrimental consequences, including the onset of gastrointestinal cancers. Globally, gastrointestinal cancers account for ~19% of all cancer cases and ~22.5% of all cancer-related deaths. Developing new ways to more readily detect and more efficiently target these malignancies are urgently needed. Whereas members of the tumour microenvironment, such as immune cells and fibroblasts, have already been in the spotlight as key players of cancer initiation and progression, the importance of the nervous system in gastrointestinal cancers has only been highlighted in the past few years. Although extrinsic innervations modulate gastrointestinal cancers, cells and signals from the gut's intrinsic innervation also have the ability to do so. Here, we shed light on this thriving field and discuss neural influences during gastrointestinal carcinogenesis. We focus on the interactions between neurons and components of the gastrointestinal tract and tumour microenvironment, on the neural signalling pathways involved, and how these factors affect the cancer hallmarks, and discuss the neural signatures in gastrointestinal cancers. Finally, we highlight neural-related therapies that have potential for the management of gastrointestinal cancers.

Identification of Epigenetically Modified Hub Genes and Altered Pathways Associated With Retinoblastoma

Retinoblastoma (Rb) is the most common childhood malignancy initiated by biallelic mutation in RB1 gene and driven by various epigenetic events including DNA methylation and microRNA dysregulation. Hence, understanding the key genes that are critically modulated by epigenetic modifications in RB1^−/− cells is very important to identify prominent biomarkers and therapeutic targets of Rb. In this study, we for the first time have integrated various Rb microarray NCBI-GEO datasets including DNA Methylation (GSE57362), miRNA (GSE7072) and mRNA (GSE110811) to comprehensively investigate the epigenetic consequences of RB loss in retinoblastoma tumors and identify genes with the potential to serve as early diagnostic markers and therapeutic targets for Rb. Interestingly, the GEO2R and co-expression network analysis have identified three genes namely E2F3, ESR1, and UNC5D that are significantly deregulated by modified DNA methylation, mRNA and microRNA expression in Rb tumors. Due to their recognition in all epigenetic, transcriptomic, and miRNA datasets, we have termed these genes as “common genes”. The results of our integrative bioinformatics analysis were validated in vitro by studying the gene and protein expression of these common genes in Y79, WERI-Rb-1, Rb cell lines and non-tumorigenic retinal pigment epithelial cell line (hTERT-RPE). The expression of E2F3 and UNC5D were up-regulated and that of ESR1 was down-regulated in Rb tumor cells when compared to that in non-tumorigenic hTERT-RPE cells. More importantly, UNC5D, a potent tumor suppressor gene in most cancers is significantly up-regulated in Y79 and Weri Rb1 cells, which, in turn, questions its anti-cancer properties. Together, our study shows that E2F3, ESR1, and UNC5D may be crucially involved in Rb tumorigenesis and possess the potential to act as early diagnostic biomarkers and therapeutic targets of Rb.

GNAO1 as a Novel Predictive Biomarker for Late Relapse in Hepatocellular Carcinoma

GNAO1, the alpha O1 subunit of G protein, was reported to be significantly downregulated in hepatocellular carcinoma (HCC), as well as being implicated in a variety of intracellular biological events; findings suggest that it may act as a tumor suppressor. Our goal was to further explore the expression of GNAO1 in HCC patients and its potential clinical significance. Oncomine and Kaplan–Meier plotter databases were used to assess the mRNA expression of GNAO1 in HCC tissues and patient survival time. Subsequently, immunohistochemistry (IHC) was used to measure GNAO1 protein level in tissue from 79 cases of HCC and paired adjacent tissues. The Kaplan–Meier survival analysis, Cox regression model, and prognostic nomogram were used to evaluate the prognostic role of GNAO1 in HCC. Results demonstrated that mRNA and protein expressions of GNAO1 were both lower in HCC tissues than in adjacent tissues (all p < 0.01). HCC patients with high expression of GNAO1 had better relapse-free survival (RFS) than those with low GNAO1 expression (all p < 0.05). A high expression of GNAO1, meanwhile, functioned as a good predictor of late relapse for HCC (p < 0.05). The nomogram consisting of GNAO1 expression and the tumor-node-metastasis (TNM) model presented good ability in predicting the 3-year relapse for HCC (C-index = 0.614). In conclusion, GNAO1 was a reliable biomarker of relapse prediction for HCC.

Experiments from unfinished Registered Reports in the Reproducibility Project: Cancer Biology

As part of the Reproducibility Project: Cancer Biology, we published Registered Reports that described how we intended to replicate selected experiments from 29 high-impact preclinical cancer biology papers published between 2010 and 2012. Replication experiments were completed and Replication Studies reporting the results were submitted for 18 papers, of which 17 were accepted and published by eLife with the rejected paper posted as a preprint. Here, we report the status and outcomes obtained for the remaining 11 papers. Four papers initiated experimental work but were stopped without any experimental outcomes. Two papers resulted in incomplete outcomes due to unanticipated challenges when conducting the experiments. For the remaining five papers only some of the experiments were completed with the other experiments incomplete due to mundane technical or unanticipated methodological challenges. The experiments from these papers, along with the other experiments attempted as part of the Reproducibility Project: Cancer Biology, provides evidence about the challenges of repeating preclinical cancer biology experiments and the replicability of the completed experiments.

Screening for Colorectal Cancer Leading into a New Decade: The "Roaring '20s" for Epigenetic Biomarkers?

Colorectal cancer (CRC) has an important bearing (top five) on cancer incidence and mortality in the world. The etiology of sporadic CRC is related to the accumulation of genetic and epigenetic alterations that result in the appearance of cancer hallmarks such as abnormal proliferation, evasion of immune destruction, resistance to apoptosis, replicative immortality, and others, contributing to cancer promotion, invasion, and metastasis. It is estimated that, each year, at least four million people are diagnosed with CRC in the world. Depending on CRC staging at diagnosis, many of these patients die, as CRC is in the top four causes of cancer death in the world. New and improved screening tests for CRC are needed to detect the disease at an early stage and adopt patient management strategies to decrease the death toll. The three pillars of CRC screening are endoscopy, radiological imaging, and molecular assays. Endoscopic procedures comprise traditional colonoscopy, and more recently, capsule-based endoscopy. The main imaging modality remains Computed Tomography (CT) of the colon. Molecular approaches continue to grow in the diversity of biomarkers and the sophistication of the technologies deployed to detect them. What started with simple fecal occult blood tests has expanded to an armamentarium, including mutation detection and identification of aberrant epigenetic signatures known to be oncogenic. Biomarker-based screening methods have critical advantages and are likely to eclipse the classical modalities of imaging and endoscopy in the future. For example, imaging methods are costly and require highly specialized medical personnel. In the case of endoscopy, their invasiveness limits compliance from large swaths of the population, especially those with average CRC risk. Beyond mere discomfort and fear, there are legitimate iatrogenic concerns associated with endoscopy. The risks of perforation and infection make endoscopy best suited for a confirmatory role in cases where there are positive results from other diagnostic tests. Biomarker-based screening methods are largely non-invasive and are growing in scope. Epigenetic biomarkers, in particular, can be detected in feces and blood, are less invasive to the average-risk patient, detect early-stage CRC, and have a demonstrably superior patient follow-up. Given the heterogeneity of CRC as it evolves, optimal screening may require a battery of blood and stool tests, where each can leverage different pathways perturbed during carcinogenesis. What follows is a comprehensive, systematic review of the literature pertaining to the screening and diagnostic protocols used in CRC. Relevant articles were retrieved from the PubMed database using keywords including: "Screening", "Diagnosis", and "Biomarkers for CRC". American and European clinical trials in progress were included as well.

The PPARα and PPARγ Epigenetic Landscape in Cancer and Immune and Metabolic Disorders

Peroxisome proliferator-activated receptors (PPARs) are ligand-modulated nuclear receptors that play pivotal roles in nutrient sensing, metabolism, and lipid-related processes. Correct control of their target genes requires tight regulation of the expression of different PPAR isoforms in each tissue, and the dysregulation of PPAR-dependent transcriptional programs is linked to disorders, such as metabolic and immune diseases or cancer. Several PPAR regulators and PPAR-regulated factors are epigenetic effectors, including non-coding RNAs, epigenetic enzymes, histone modifiers, and DNA methyltransferases. In this review, we examine advances in PPARα and PPARγ-related epigenetic regulation in metabolic disorders, including obesity and diabetes, immune disorders, such as sclerosis and lupus, and a variety of cancers, providing new insights into the possible therapeutic exploitation of PPAR epigenetic modulation.

Integrated bioinformatics identifies the dysregulation induced by aberrant gene methylation in colorectal carcinoma

Colorectal carcinoma (CRC) is one of the most common cancers, and is associated with a poor clinical outcome. The key genes and potential prognostic markers in colorectal carcinoma remain to be identified and explored for clinical application. DNA expression/methylation profiles were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed/methylated genes (DEGs and DEMs). A total of 255 genes and 372 genes were identified as being up-regulated and down-regulated, respectively, in GSE113513, GSE81558, and GSE89076. There were a total of 3350 hypermethylated genes and 443 hypomethylated genes identified in GSE48684. Twenty genes were found to be hypermethylated as well as down-regulated, and a functional enrichment analysis revealed that these genes were mainly involved in cancer-related pathways. Among these 20 genes, GPM6A, HAND2 and C2orf40 were related to poor outcomes in cancer patients based on a survival analysis. Concurrent decreases of GPM6A, HAND2 and C2orf40 protein expression were observed in highly-differentiated colorectal carcinoma tissues, and higher expression levels were found in undifferentiated or minimally-differentiated colorectal carcinoma tissues. In conclusion, 20 genes were found to be downregulated and hypermethylated in CRC, among which GPM6A, HAND2 and C2orf40 were explored for their potential prognostic value.

Identification of DNA methylation markers for early detection of CRC indicates a role for nervous system-related genes in CRC

Purpose

Colonoscopy and the fecal immunochemical test (FIT) are currently the most widely used screening modalities for colorectal cancer (CRC), however, both with their own limitations. Here we aim to identify and validate stool-based DNA methylation markers for the early detection of CRC and investigate the biological pathways prone to DNA methylation.

Methods

DNA methylation marker discovery was performed using The Cancer Genome Atlas (TCGA) colon adenocarcinoma data set consisting of normal and primary colon adenocarcinoma tissue. The performance of the five best candidate markers and a previously identified marker, NDRG4, was evaluated on tissues and whole stool samples of healthy subjects and CRC patients using quantitative MSP assays. The results were compared and combined with FIT data. Finally, pathway and gene ontology enrichment analyses were performed using ToppFun, GOrilla and clusterProfiler.

Results

GDNF, HAND2, SLC35F3, SNAP91 and SORCS1 were ranked as the best performing markers. Gene combinations of all five markers, NDRG4 and FIT were evaluated to establish the biomarker panel with the highest diagnostic potential, resulting in the identification of GDNF/SNAP91/NDRG4/FIT as the best performing marker panel. Pathway and gene ontology enrichment analyses revealed that genes associated with the nervous system were enriched in the set of best performing CRC-specific biomarkers.

Conclusion

In silico discovery analysis using TCGA-derived data yielded a novel DNA-methylation-based assay for the early detection of CRC, potentially improving current screening modalities. Additionally, nervous system-related pathways were enriched in the identified genes, indicating an epigenetic regulation of neuronal genes in CRC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-021-01067-9.

Two immune-enhanced molecular subtypes differ in inflammation, immune checkpoints, mutations, and prognostic outcome in stage I-II colonic carcinoma

The purpose of this paper is to investigate the immune function of the tumor microenvironment and its clinical correlation with colonic carcinoma. Immune genes were downloaded from the The Cancer Genome Atlas database. Five subtypes are obtained by cluster screening based on immune gene expression data. The C3 and C4 subtypes show stronger immune activity. In addition, the C4 subtype has the largest number of gene mutations and the worst prognosis. Most of the immune signatures are upregulated in the C4 subtype, while most of the immune infiltration-related cells are upregulated in the C3 and C4 subtypes. The different immune microenvironments between these subtypes may provide new ideas for immunotherapy strategies in colon carcinoma.

Identification of Monotonically Differentially Expressed Genes across Pathologic Stages for Cancers

Given the fact that cancer is a multistage progression process resulting from genetic sequence mutations, the genes whose expression values increase or decrease monotonically across pathologic stages are potentially involved in tumor progression. This may provide insightful clues about how human cancers advance, thereby facilitating more personalized treatments. By replacing the expression values of genes with their GeneRanks, we propose a procedure capable of identifying monotonically differentially expressed genes (MEGs) as the disease advances. Using three real-world gene expression data that cover three distinct cancer types-colon, esophageal, and lung cancers-the proposed procedure has demonstrated excellent performance in detecting the potential MEGs. To conclude, the proposed procedure can detect MEGs across pathologic stages of cancers very efficiently and is thus highly recommended.

Epigenetic Clock: DNA Methylation in Aging

Aging, which is accompanied by decreased organ function and increased disease incidence, limits human lifespan and has attracted investigators for thousands of years. In recent decades, with the rapid development of biology, scientists have shown that epigenetic modifications, especially DNA methylation, are key regulators involved in this process. Regular fluctuations in global DNA methylation levels have been shown to accurately estimate biological age and disease prognosis. In this review, we discuss recent findings regarding the relationship between variations in DNA methylation level patterns and aging. In addition, we introduce the known mechanisms by which DNA methylation regulators affect aging and related diseases. As more studies uncover the mechanisms by which DNA methylation regulates aging, antiaging interventions and treatments for related diseases may be developed that enable human life extension.

Construction of a CXC Chemokine-Based Prediction Model for the Prognosis of Colon Cancer

Colon cancer is the third most common cancer, with a high incidence and mortality. Construction of a specific and sensitive prediction model for prognosis is urgently needed. In this study, profiles of patients with colon cancer with clinical and gene expression data were downloaded from Gene Expression Omnibus and The Cancer Genome Atlas (TCGA). CXC chemokines in patients with colon cancer were investigated by differential expression gene analysis, overall survival analysis, receiver operating characteristic analysis, gene set enrichment analysis (GSEA), and weighted gene coexpression network analysis. CXCL1, CXCL2, CXCL3, and CXCL11 were upregulated in patients with colon cancer and significantly correlated with prognosis. The area under curve (AUC) of the multigene forecast model of CXCL1, CXCL11, CXCL2, and CXCL3 was 0.705 in the GSE41258 dataset and 0.624 in TCGA. The prediction model was constructed using the risk score of the multigene model and three clinicopathological risk factors and exhibited 92.6% and 91.8% accuracy in predicting 3-year and 5-year overall survival of patients with colon cancer, respectively. In addition, by GSEA, expression of CXCL1, CXCL11, CXCL2, and CXCL3 was correlated with several signaling pathways, including NOD-like receptor, oxidative phosphorylation, mTORC1, interferon-gamma response, and IL6/JAK/STAT3 pathways. Patients with colon cancer will benefit from this prediction model for prognosis, and this will pave the way to improve the survival rate and optimize treatment for colon cancer.

Identification of hub methylated-CpG sites and associated genes in oral squamous cell carcinoma

To improve personalized diagnosis and prognosis for oral squamous cell carcinoma (OSCC) by identification of hub methylated‐CpG sites and associated genes, weighted gene comethylation network analysis (WGCNA) was performed to examine and identify hub modules and CpG sites correlated with OSCC. Here, WGCNA modeling yielded blue and brown comethylation modules that were significantly associated with OSCC status. Following screening of the differentially expressed genes (DEGs) from gene expression microarrays and differentially methylated‐CpG sites (DCGs), integrated multiomics analysis of the DEGs, DCGs, and hub CpG sites from the modules was performed to investigate their correlations. Expression levels of 16 CpG sites‐associated genes were negatively correlated with methylation patterns of promoter. Moreover, Kaplan‐Meier survival analysis of the hub CpG sites and associated genes was carried out using 2 public databases, MethSurv and GEPIA. Only 5 genes, ACTA1, ACTN2, OSR1, SYNGR1, and ZNF677, had significant overall survival using GEPIA. Hypermethylated‐CpG sites ACTN2‐cg21376883 and OSR1‐cg06509239 were found to be associated with poor survival by MethSurv. Methylation status of specific site and expression levels of associated genes were determined using clinical samples by quantitative methylation‐specific PCR and real‐time PCR. Pearson's correlation analysis showed that methylation levels of cg06509239 and cg18335068 were negatively related to OSR1 and ZNF677 expression levels, respectively. Our classification schema using multiomics analysis represents a screening framework for identification of hub CpG sites and associated genes.

Comprehensive analysis identifying aberrant DNA methylation in rectal mucosa from ulcerative colitis patients with neoplasia

Background

There are no biomarkers to facilitate the identification of patients with ulcerative colitis (UC) who are at high risk for developing colorectal cancer (CRC). In our current study, we used rectal tissues from UC patients to identify aberrant DNA methylations and evaluated whether they could be used to identify UC patients with coexisting colorectal neoplasia.

Results

Using a training set, we identified 484 differentially methylated regions (DMRs) with absolute delta beta-values > 0.1 in rectal mucosa by using the ChAMP algorithm. Next, pathway enrichment analysis was performed using 484 DMRs to select coordinately methylated DMRs, resulting in the selection of 187 aberrant DMRs in rectal tissues from UC-CRC. Then, the Elastic Net classification algorithm was performed to narrow down optimal aberrant DMRs, and we finally selected 11 DMRs as biomarkers for identification of UC-CRC patients. The 11 chosen DMRs could discriminate UC patients with or without CRC in a training set (area under the curve, 0.96) and the validation set (area under the curve, 0.81).

Conclusions

In conclusion, we identified 11 DMRs that could identify UC patients with CRC complications. Prospective studies should further confirm the validity of these biomarkers.

Methods

We performed genome-wide DNA methylation profiles in rectal mucosal tissues (n = 48) from 24 UC-CRC and 24 UC patients in a training set. Next, we performed comprehensive DNA methylation analysis using rectal mucosal tissues (n = 16) from 8 UC-CRC and 8 UC patients for validation.