Microarray-based molecular margin methylation pattern analysis in colorectal carcinoma

Relationship Between Human mutL Homolog 1 (hMLH1) Hypermethylation and Colorectal Cancer: A Meta-Analysis

Background

Hypermethylation of CpG islands in gene promoter regions is an important mechanism of gene inactivation in cancers. Promoter hypermethylation of human mutL homolog 1 (hMLH1) has been implicated in a subset of colorectal cancers that show microsatellite instability (MSI), while the connection of the epigenetic inactivation of hMLH1 in colorectal cancers remains unknown. The aim of this study was to evaluate the relationship between the promoter hypermethylation of hMLH1 and colorectal cancers by performing a meta-analysis.

Material/Methods

Eligible studies were identified through searching PubMed, Cochrane Library, Web of Science, and Google Scholar databases. R Software including meta packages was used to calculate the pooled and odds ratios (ORs) with corresponding confidence intervals (CIs). Funnel plots were also performed to evaluate publication bias.

Results

This meta-analysis obtained 45 articles, including 4096 colorectal cancer patients, and identified a significant association between hMLH1 hypermethylation and colorectal cancer risk using the fixed-effects model (OR=8.3820; 95% CI, 6.9202~10.1527; z=21.7431; P<0.0001) and random effects model pooled (OR=10.0963; 95% CI, 6.1919~16.4626; z=9.2688; P<0.0001). The significant relationship was found in subgroup analyses.

Conclusions

The results of this meta-analysis show a significant association between hMLH1 hypermethylation and colorectal cancer risk.

Analysis of the DNA methylation level of cancer-related genes in colorectal cancer and the surrounding normal mucosa

Background

Two molecular pathways promote the development of colorectal cancer (CRC). One is termed “microsatellite stable” (MSS) whereas the other is characterized by “microsatellite instability” (MSI or MIN). In addition, the CpG island methylation phenotype is known to be an important alteration as a third molecular type. Thus, DNA methylation is thought to provide potential biomarkers for assessment of cancer risk in normal mucosa. In addition, it is also known that colonic location is an important parameter in the development of CRC.

Methods

We examined the surrounding normal mucosa in three parts of the colon. Next, we quantified DNA methylation levels of SFRP1, SFRP2, SFRP5, DKK2, DKK3, mir34b/c, RASSF1A, IGFBP7, CDKN2A, and MLH1 in isolated cancerous glands and crypts of normal colorectal mucosa adjacent to CRCs using a pyrosequencer.

Results

DNA methylation levels of SFRP1, SFRP2, DKK2, and mir34b/c were significantly higher in CRCs with an MSS phenotype than in those with an MSI phenotype. The average level of methylation in normal crypts did not decrease with the distance from the tumor, irrespective of microsatellite status or the tumor location. DNA methylation levels in SFRP1 and SFRP2 genes in normal crypts were significantly higher in left-side than right-side CRC with an MSS phenotype. Finally, the genes were classified into three types based on the methylation frequencies in normal crypts, including type I (SFRP1 and SFRP2I), type II (DKK2 and mir34b/c), and type III (others).

Conclusions

Our results showed that DNA methylation of SFRP1 and SFRP2 might be useful to predict cancer risk of surrounding normal mucosa. In addition, a field effect may be present in CRC, affecting both adjacent and non-adjacent normal mucosa.

Electronic supplementary material

The online version of this article (doi:10.1186/s13148-017-0352-4) contains supplementary material, which is available to authorized users.

The topography of DNA methylation in the non-neoplastic colonic mucosa surrounding colorectal cancers

The degree of gene hypermethylation in non-neoplastic colonic mucosa (NNCM) is a potentially important event in the development of colorectal cancer (CRC), particularly for the subgroup with a CpG island methylator phenotype (CIMP). In this study, we aimed to use an unbiased and high-throughput approach to evaluate the topography of DNA methylation in the non-neoplastic colonic mucosa (NNCM) surrounding colorectal cancer (CRC). A total of 61 tissue samples comprising 53 NNCM and 8 tumor samples were obtained from hemicolectomy specimens of two CRC patients (Cases 1 and 2). NNCM was stripped from the underlying colonic wall and samples taken at varying distances from the tumor. The level of DNA methylation in NNCM and tumor tissues was assessed at 1,505 CpG sites in 807 cancer-related genes using Illumina GoldenGate® methylation arrays. Case 1 tumor showed significantly higher levels of methylation compared to surrounding NNCM samples (P < 0.001). The average level of methylation in NNCM decreased with increasing distance from the tumor (r = -0.418; P = 0.017), however this was not continuous and "patches" with higher levels of methylation were observed. Case 2 tumor was less methylated than Case 1 tumor (average β-value 0.181 vs. 0.415) and no significant difference in the level of methylation was observed in comparison to the surrounding NNCM. No evidence was found for a diminishing gradient of methylation in the NNCM surrounding CRC with a high level of methylation. Further work is required to determine whether CIMP+ CRC develop from within "patches" of NCCM that display high levels of methylation.

A simple colorimetric detection of DNA methylation

In this work, we describe a simple colorimetric method to detect DNA methylation. Adenomatous polyposis coli (APC) with a small CpG region containing methylated cytosine (methylated APC) was synthesized and tested. Methylated APC was first captured and enriched by anti-5-methylcytosine monoclonal antibody conjugated magnetic microspheres (MMPs). Then a probe partly complementary to the APC sequence was added, resulting in the formation of DNA duplexes. The microsphere-captured probe was then released by heat denaturation and added into unmodified gold nanoparticle (AuNP) solution. Colorimetric detection was performed by salt-induced aggregation. The limit of detection is 80 fmol. Semi-quantitative analysis was done with a UV/Vis spectrophotometer by recording the absorbance of AuNP solution at 520 nm. Thus, this method provides a simple, rapid and quantitative tool for DNA methylation detection.

Biomarker-based selection of therapy for colorectal cancer

Colorectal cancer (CRC) has been re-classified based on molecular analyses of various genes and proteins capable of separating morphologic types of tumors into molecular categories. The diagnosis and management of CRC has evolved with the discovery and validation of a wide variety of biomarkers designed to facilitate a personalized approach for the treatment of the disease. In addition, a number of new prognostic and predictive individual genes and proteins have been discovered that are designed to reflect the sensitivity and/or resistance of CRC to existing therapies. Multigene predictors have also been developed to predict the risk of relapse for intermediate-stage CRC after completion of surgical resection. Finally, a number of biomarkers have been proposed as specific predictors of chemotherapy and radiotherapy response and, in some instances, drug toxicity. In this article, a series of novel biomarkers are considered and compared with standard-of-care markers for their potential use as pharmacogenomic and pharmacogenetic predictors of disease outcome.

Distinct epigenetic domains separated by a CTCF bound insulator between the tandem genes, BLU and RASSF1A

Background

Tumor suppressor gene (TSG) RASSF1A and candidate TSG BLU are two tandem head-to-tail genes located at 3p21.3. We hypothesized that there may be a concordance on their gene expression and promoter methylation status. If not, then there may be an insulator located between RASSF1A and BLU genes that provides a barrier activity.

Methodology/Principal Findings

We first identified potential transcriptionally important CpG sites using the methylation-specific oligonucleotide array in relation to mRNA expression of RASSF1A and BLU genes in primary lung tumors. We demonstrated that E2F1 bound to the potential transcriptionally important CpG sites in RASSF1A gene of a normal lung cell line expressing RASSF1A transcripts, whereas loss of E2F1 binding to RASSF1A in A549 cancer cell line was the result of DNA methylation. Both RASSF1A and BLU genes had their own potential transcriptionally important CpG regions. However, there was no correlation of methylation status between RASSF1A and BLU. Using gel shift assay and chromatin immunoprecipitation-PCR (ChIP-PCR), we found that CCCTC-binding factor (CTCF) bound to insulator sequences located between these two genes. Bisulfite sequencing and ChIP-PCR revealed distinct methylation and chromatin boundaries separated by the CTCF binding domains in normal cells, whereas such distinct epigenetic domains were not observed in cancer cells. Note that demethylation reagent and histone deacetylase inhibitor treatments led to CTCF binding and recovery of barrier effect for RASSF1A and BLU genes in cancer cells.

Conclusions/Significance

Our study dissects the potential transcriptionally important CpG sites for RASSF1A and BLU genes at the sequence level and demonstrates that CTCF binding to the insulator of BLU gene provides a barrier activity within separate epigenetic domains of the juxtaposed BLU and RASSF1A loci in the 3p21.3 gene cluster region.

Biomarker-based prediction of response to therapy for colorectal cancer: current perspective

The diagnosis and management of colorectal cancer (CRC) has been impacted by the discovery and validation of a wide variety of biomarkers designed to facilitate a personalized approach for the treatment of the disease. Recently, CRC has been reclassified based on molecular analyses of various genes and proteins capable of separating morphologic types of tumors into molecular categories. At the same time, a number of new prognostic and predictive single genes and proteins have been discovered that are designed to reflect sensitivity and/or resistance to existing therapies. Multigene predictors have also been developed to predict the risk of relapse for intermediate-stage CRC after completion of surgical extirpation. More recently, a number of biomarkers tested by a variety of methods have been proposed as specific predictors of chemotherapy and radiotherapy response. Other markers have been successfully used to predict toxic effects of standard therapies. In this review, a series of novel biomarkers are considered and compared with standard-of-care markers for their potential use as pharmacogenomic and pharmacogenetic predictors of disease outcome.

The application of next generation sequencing in DNA methylation analysis

DNA methylation is a major form of epigenetic modification and plays essential roles in physiology and disease processes. In the human genome, about 80% of cytosines in the 56 million CpG sites are methylated to 5-methylcytosines. The methylation pattern of DNA is highly variable among cells types and developmental stages and influenced by disease processes and genetic factors, which brings considerable theoretical and technological challenges for its comprehensive mapping. Recently various high-throughput approaches based on bisulfite conversion combined with next generation sequencing have been developed and applied for the genome wide analysis of DNA methylation. These methods provide single base pair resolution, quantitative DNA methylation data with genome wide coverage. We review these methods here and discuss some technical points of special interest like the sequence depth necessary to reach conclusions, the identification of clonal DNA amplification after bisulfite conversion and the detection of non-CpG methylation. Future application of these methods will greatly facilitate the profiling of the DNA methylation in the genomes of different species, individuals and cell types under healthy and disease states.

Emerging methods for analysis of the cancer methylome

CpG island hypermethylation plays a key role in the silencing of cancer-related genes. In recent years, some new and effective methods have been developed for high-throughput analysis of DNA methylation, and have provided DNA methylation markers as powerful tools for the development of innovative diagnostic and therapeutic strategies in cancer. In this review, we describe various current and emerging technologies for studying the DNA methylation profile in cancer including: the isoschizomers and gel-based methylation analysis, the microarray-based methylation analysis and the sequencing-based methylation analysis. All of these techniques have advantages and disadvantages, such as sensitivity, specificity, analysis scale and cost. In the coming years, newer platforms of low cost, high-throughput and greater expediency, and speed for cancer methylome analysis will be developed.

The value of diffusion-weighted imaging in assessing the ADC changes of tissues adjacent to breast carcinoma

Background

To define a threshold value of apparent diffusion coefficient (ADC) with which malignant breast lesions can be distinguished from benign lesions, and to evaluate the ADC change of peri-tumor tissue in breast carcinoma by echo planar-diffusion weighted imaging (EPI-DWI).

Methods

57 breast lesions were scanned by routine MRI and EPI-DWI. The ADC values were compared between malignant and benign lesions. The sensitivity and specificity of EPI-DWI and the threshold ADC value were evaluated by Receiver Operating Characteristic curve (ROC). The ADC values of malignant lesion and layered peri-tumor tissues (from innermost layer 1 to outermost layer 4 with 5 mm every layer) in different directions were compared and the ADC values among different layers were compared.

Results

The ADC value of 35 malignant lesions was statistically lower than that of 22 benign lesions (P < 0.05). In ROC curve, the threshold value was 1.24 +/- 0.25*10E-3 mm²/s (b = 500) or 1.20 +/- 0.25*10E-3 mm²/s (b = 1000). The ADC value of malignant lesions was statistically lower than that of peri-tumor tissues in different directions (P < 0.05). For peri-tumor tissues, the ADC values increased gradually from layer 1 to layer 4 and there was a significant difference between the ADC values of layer 1 and layer 2 (P < 0.05); while from layer 2 outwards, there was no statistical difference among different layers.

Conclusion

ADC value was a sensitive and specific parameter that could help to differentiate benign and malignant breast lesions. ADC changes in tissues adjacent to breast carcinoma could be detected by EPI-DWI, which made EPI-DWI a promising method for helping to determine surgical scope of breast carcinoma.

Profiling CpG island field methylation in both morphologically normal and neoplastic human colonic mucosa

Aberrant CpG island (CGI) methylation occurs early in colorectal neoplasia. Quantitative methylation-specific PCR profiling applied to biopsies was used to quantify low levels of CGI methylation of 18 genes in the morphologically normal colonic mucosa of neoplasia-free subjects, adenomatous polyp patients, cancer patients and their tumours. Multivariate statistical analyses distinguished tumour from mucosa with a sensitivity of 78.9% and a specificity of 100% (P=3 x 10(-7)). In morphologically normal mucosa, age-dependent CGI methylation was observed for APC, AXIN2, DKK1, HPP1, N33, p16, SFRP1, SFRP2 and SFRP4 genes, and significant differences in CGI methylation levels were detected between groups. Multinomial logistic regression models based on the CGI methylation profiles from normal mucosa correctly identified 78.9% of cancer patients and 87.9% of non-cancer (neoplasia-free+polyp) patients (P=4.93 x 10(-7)) using APC, HPP1, p16, SFRP4, WIF1 and ESR1 methylation as the most informative variables. Similarly, CGI methylation of SFRP4, SFRP5 and WIF1 correctly identified 61.5% of polyp patients and 78.9% of neoplasia-free subjects (P=0.0167). The apparently normal mucosal field of patients presenting with neoplasia has evidently undergone significant epigenetic modification. Methylation of the genes selected by the models may play a role in the earliest stages of the development of colorectal neoplasia.

DNA microarrays: a powerful genomic tool for biomedical and clinical research

Among the many benefits of the Human Genome Project are new and powerful tools such as the genome-wide hybridization devices referred to as microarrays. Initially designed to measure gene transcriptional levels, microarray technologies are now used for comparing other genome features among individuals and their tissues and cells. Results provide valuable information on disease subcategories, disease prognosis, and treatment outcome. Likewise, they reveal differences in genetic makeup, regulatory mechanisms, and subtle variations and move us closer to the era of personalized medicine. To understand this powerful tool, its versatility, and how dramatically it is changing the molecular approach to biomedical and clinical research, this review describes the technology, its applications, a didactic step-by-step review of a typical microarray protocol, and a real experiment. Finally, it calls the attention of the medical community to the importance of integrating multidisciplinary teams to take advantage of this technology and its expanding applications that, in a slide, reveals our genetic inheritance and destiny.