New Methylation Biomarker Panel for Early Diagnosis of Dysplasia or Cancer in High-Risk Inflammatory Bowel Disease Patients

Microbiota composition and its impact on DNA methylation in colorectal cancer

Colorectal cancer is a complex disease resulting from the interaction of genetics, epigenetics, and environmental factors. DNA methylation is frequently found in tumor suppressor genes to promote cancer development. Several factors are associated with changes in the DNA methylation pattern, and recently, the gastrointestinal microbiota could be associated with this epigenetic change. The predominant phyla in gut microbiota are Firmicutes and Bacteroidetes; however, an enrichment of Bacteroides fragilis, Fusobacterium nucleatum, and Streptococcus bovis, among others, has been reported in colorectal cancer, although the composition could be influenced by several factors, including diet, age, sex, and cancer stage. Fusobacterium nucleatum, a gram-negative anaerobic bacillus, is mainly associated with colorectal cancer patients positive for the CpG island methylator phenotype, although hypermethylation in genes such as MLH1, CDKN2A, MTSS1, RBM38, PKD1, PTPRT, and EYA4 has also been described. Moreover, Hungatella hathewayi, a gram-positive, rod-shaped bacterium, is related to hypermethylation in SOX11, THBD, SFRP2, GATA5, ESR1, EYA4, CDX2, and APC genes. The underlying epigenetic mechanism is unclear, although it could be implicated in the regulation of DNA methyltransferases, enzymes that catalyze the transfer of a methyl group on cytosine of CpG sites. Since DNA methylation is a reversible event, changes in gut microbiota could modulate the gene expression through DNA methylation and improve the colorectal cancer prognosis.

The value of 7 peripheral blood serum ratios in diagnosis and prediction of disease activity of patients within inflammatory bowel disease individuals

Objective

In recent years, a number of studies have suggested that inflammation-based biomarkers can be applied in the diagnostics and prognostic testing of disease. However, the association between these ratios and inflammatory bowel disease (IBD) remains unclear. We aimed to investigate the role of these inflammation-based ratios in patients with IBD.

Methods

Retrospective analysis of 362 patients with IBD and 100 healthy individuals from January 2016 and December 2021. The receiver operating characteristic curve and logistic regression analysis was applied to explore the diagnostic and predictive performance of the seven ratio markers [neutrophil- to-albumin ratio (NAR), neutrophil-to-pre-albumin ratio (NPAR), albumin-to-alkaline-phosphatase ratio (AAPR), albumin-to-globulin ratio (AGR), albumin-to-fibrinogen ratio (AFR), fibrinogen-to-pre-albumin ratio (FPR), and Prognostic Nutritional Index (PNI)] regarding to disease activity in IBD individuals.

Results

Compared with healthy controls, patients with Crohn's disease (CD) or ulcerative colitis (UC) exhibited higher levels of NAR, NPAR, FPR (P < 0.001), lower levels of AAPR, and PNI (P < 0.001). Multivariate logistic regression showed that the level of NPAR (OR = 1.12, 95%CI: 1.02-1.23, P = 0.016) and AGR (OR = 1.01, 95%CI: 1.01-1.12, P < 0.001) was an independent risk factor of IBD. Then, we found the level of NPAR (OR = 1.10, 95%CI: 1.01-1.20, P = 0.02) and PNI (OR = 0.83, 95%CI: 0.71-0.96, P = 0.01) was independently associated with disease activity. Besides, a positive association was observed between the level of NPAR and two clinical scores [Harvey Bradshaw index (HBI) in patients with CD, Mayo score in patients with UC]. Finally, the level of NPAR (P = 0.002) and PNI (P = 0.003) showed a significant difference in the IBD-associated neoplasia group and IBD without neoplasia group.

Conclusion

Our data first suggests NPAR as a putative biomarker for diagnosing and predicting disease activity in patients with IBD. Investigations involving a larger number of IBD individuals are necessary to validate its use as an easily obtained peripheral blood biomarker of IBD.

Ubiquitin-specific proteases in inflammatory bowel disease-related signalling pathway regulation

The exact pathogenesis of inflammatory bowel disease (IBD), a chronic gastrointestinal inflammatory disease comprising Crohn’s disease and ulcerative colitis, remains unclear. Studies on ubiquitination, which regulates the degradation of inflammation signalling pathway molecules, and deubiquitination have provided novel insights. Targeting the ubiquitin-specific protease (USP) family of deubiquitinases elucidates IBD signalling pathway mechanisms and possibly, IBD therapeutic solutions. Here, we characterised USPs as chief regulators of pro-inflammatory signalling pathways, including nuclear factor-κB and transforming growth factor-β; analysed the relationship between USPs and IBD pathogenesis in terms of genetic susceptibility, intestinal epithelial barrier, immunity, and gut microbiota; and discussed future research prospects.

New Insights Into the Epigenetic Regulation of Inflammatory Bowel Disease

Inflammatory bowel disease (IBD) is a chronic inflammatory disease of the colonic mucosa. Environmental factors, genetics, intestinal microbiota, and the immune system are all involved in the pathophysiology of IBD. Lately, accumulating evidence has shown that abnormal epigenetic changes in DNA methylation, histone markers, and non-coding RNA expression greatly contribute to the development of the entire disease. Epigenetics regulates many functions, such as maintaining the homeostasis of the intestinal epithelium and regulating the immune system of the immune cells. In the present study, we systematically summarized the latest advances in epigenetic modification of IBD and how epigenetics reveals new mechanisms of IBD. Our present review provided new insights into the pathophysiology of IBD. Moreover, exploring the patterns of DNA methylation and histone modification through epigenetics can not only be used as biomarkers of IBD but also as a new target for therapeutic intervention in IBD patients.

Follow-Up Study Confirms the Presence of Gastric Cancer DNA Methylation Hallmarks in High-Risk Precursor Lesions

To adopt prevention strategies in gastric cancer, it is imperative to develop robust biomarkers with acceptable costs and feasibility in clinical practice to stratified populations according to risk scores. With this aim, we applied an unbiased genome-wide CpG methylation approach to a discovery cohort composed of gastric cancer (n = 24), and non-malignant precursor lesions (n = 64). Then, candidate-methylation approaches were performed in a validation cohort of precursor lesions obtained from an observational longitudinal study (n = 264), with a 12-year follow-up to identify repression or progression cases. H. pylori stratification and histology were considered to determine their influence on the methylation dynamics. As a result, we ascertained that intestinal metaplasia partially recapitulates patterns of aberrant methylation of intestinal type of gastric cancer, independently of the H. pylori status. Two epigenetically regulated genes in cancer, RPRM and ZNF793, consistently showed increased methylation in intestinal metaplasia with respect to earlier precursor lesions. In summary, our result supports the need to investigate the practical utilities of the quantification of DNA methylation in candidate genes as a marker for disease progression. In addition, the H. pylori-dependent methylation in intestinal metaplasia suggests that pharmacological treatments aimed at H. pylori eradication in the late stages of precursor lesions do not prevent epigenome reprogramming toward a cancer signature.

Rapid screening of UPB1 gene variations by high resolution melting curve analysis

The present study aimed to analyze gene mutations in patients with β-ureidopropinoase deficiency and establish a rapid detection method for β-ureidopropinoase (UPB1) pathogenic variations by high resolution melting (HRM) analysis. DNA samples with known UPB1 mutations in three patients with β-ureidopropinoase deficiency were utilized to establish a rapid detection method for UPB1 pathogenic variations by HRM analysis. Further rapid screening was performed on two patients diagnosed with β-ureidopropinoase deficiency and 50 healthy control individuals. The results showed that all known UPB1 gene mutations can be analyzed by a specially designed HRM assay. Each mutation has specific HRM profiles which could be used in rapid screening. The HRM method could correctly identify all genetic mutations in two children with β-ureidopropinoase deficiency. In addition, the HRM assay also recognized four unknown mutations. To conclude, the results support future studies of applying HRM analysis as a diagnostic approach for β-ureidopropinoase deficiency and a rapid screening method for UPB1 mutation carriers.

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.

Reference-free deconvolution, visualization and interpretation of complex DNA methylation data using DecompPipeline, MeDeCom and FactorViz

DNA methylation profiling offers unique insights into human development and diseases. Often the analysis of complex tissues and cell mixtures is the only feasible option to study methylation changes across large patient cohorts. Since DNA methylomes are highly cell type specific, deconvolution methods can be used to recover cell type-specific information in the form of latent methylation components (LMCs) from such 'bulk' samples. Reference-free deconvolution methods retrieve these components without the need for DNA methylation profiles of purified cell types. Currently no integrated and guided procedure is available for data preparation and subsequent interpretation of deconvolution results. Here, we describe a three-stage protocol for reference-free deconvolution of DNA methylation data comprising: (i) data preprocessing, confounder adjustment using independent component analysis (ICA) and feature selection using DecompPipeline, (ii) deconvolution with multiple parameters using MeDeCom, RefFreeCellMix or EDec and (iii) guided biological inference and validation of deconvolution results with the R/Shiny graphical user interface FactorViz. Our protocol simplifies the analysis and guides the initial interpretation of DNA methylation data derived from complex samples. The harmonized approach is particularly useful to dissect and evaluate cell heterogeneity in complex systems such as tumors. We apply the protocol to lung cancer methylomes from The Cancer Genome Atlas (TCGA) and show that our approach identifies the proportions of stromal cells and tumor-infiltrating immune cells, as well as associations of the detected components with clinical parameters. The protocol takes slightly >3 d to complete and requires basic R skills.

Novel methylation gene panel in adjacent normal tissues predicts poor prognosis of colorectal cancer in Taiwan

BACKGROUND

It is evident that current clinical criteria are suboptimal to accurately estimate patient prognosis. Studies have identified epigenetic aberrant changes as novel prognostic factors for colorectal cancer (CRC).

AIM

To estimate whether a methylation gene panel in different clinical stages can reflect a different prognosis.

METHODS

We enrolled 120 CRC patients from Tri-Service General Hospital in Taiwan and used the candidate gene approach to select six genes involved in carcinogenesis pathways. Patients were divided into two groups based on the methylation status of the six evaluated genes, namely, the < 3 aberrancy group and ≥ 3 aberrancy group. Various tumor stages were divided into two subgroups (local and advanced stages) on the basis of the pathological type of the following tissues: Tumor and adjacent normal tissues (matched normal). We assessed DNA methylation in tumors and adjacent normal tissues from CRC patients and analyzed the association between DNA methylation with different cancer stages and the prognostic outcome including time to progression (TTP) and overall survival.

RESULTS

We observed a significantly increasing trend of hazard ratio as the number of hypermethylated genes increased both in normal tissue and tumor tissue. The 5-year TTP survival curves showed a significant difference between the ≥ 3 aberrancy group and the < 3 aberrancy group. Compared with the < 3 aberrancy group, a significantly shorter TTP was observed in the ≥ 3 aberrancy group. We further analyzed the interaction between CRC prognosis and different cancer stages (local and advanced) according to the methylation status of the selected genes in both types of tissues. There was a significantly shorter 5-year TTP for tumors at advanced stages with the promoter methylation status of selected genes than for those with local stages. We found an interaction between cancer stages and the promoter methylation status of selected genes in both types of tissues.

CONCLUSION

Our data provide a significant association between the methylation markers in normal tissues with advanced stage and prognosis of CRC. We recommend using these novel markers to assist in clinical decision-making.

Analysis of Genes Involved in Ulcerative Colitis Activity and Tumorigenesis Through Systematic Mining of Gene Co-expression Networks

Ulcerative colitis (UC) is an idiopathic, chronic inflammatory disorder of the colon, characterized by continuous mucosal inflammation. Recently, some studies have considered it as part of an inflammatory bowel disease-based global network. Herein, with the aim of identifying the underlying potential genetic mechanisms involved in the development of UC, multiple algorithms for weighted correlation network analysis (WGCNA), principal component analysis (PCA), and linear models for microarray data algorithm (LIMMA) were used to identify the hub genes. The map of platelet activation, ligand-receptor interaction, calcium signaling pathway, and cAMP signaling pathway showed significant links with UC development, and the hub genes CCR7, CXCL10, CXCL9, IDO1, MMP9, and VCAM1, which are associated with immune dysregulation and tumorigenesis in biological function, were found by multiple powerful bioinformatics methods. Analysis of The Cancer Genome Atlas (TCGA) also showed that the low expression of CCR7, CXCL10, CXCL9, and MMP9 may be correlated with a poor prognosis of overall survival (OS) in colorectal cancer (CRC) patients (all p < 0.05), while no significance detected in both of IDO1 and VCAM1. In addition, low expression of CCR7, CXCL10, CXCL9, MMP9, and IDO1 may be associated with a poor prognosis in recurrence free survival (RFS) time (all p < 0.05), but no significant difference was identified in VCAM1. Moreover, the NFKB1, FLI1, and STAT1 with the highest enrichment score were detected as the master regulators of hub genes. In summary, these results indicated the central role of the hub genes of CCR7, CXCL10, CXCL9, IDO1, VCAM1, and MMP9, in response to UC progression, as well as the development of UC to CRC, thus shedding light on the molecular mechanisms involved and assisting with drug target validation.