Impact of sample heterogeneity on methylation analysis

Quantitative analysis of p16 methylation in Barrett's carcinogenesis

p16 hypermethylation in Barrett's carcinogenesis has been evaluated in studies which did not take into account sample heterogeneity and yielded qualitative (methylated/unmethylated) instead of accurate quantitative (percentage of CpG methylation) data. We aimed to measure the degree of p16 methylation in pure samples representing all the steps of Barrett's tumorogenesis and to evaluate the influence of sample heterogeneity in methylation analysis.

METHODS

77 paraffin-embedded human esophageal samples were analyzed. Histological grading was established by two pathologists in: negative for dysplasia, indefinite for dysplasia, low-grade dysplasia, high-grade dysplasia and adenocarcinoma. Areas of interest were selected by laser-capture microdissection. p16 methylation was quantified by pyrosequencing. An adjacent section of the whole sample was also analyzed to compare methylation data.

RESULTS

After microdissection, we obtained 15 samples of squamous epithelium, 36 non-dysplastic Barrett's esophagus, 3 indefinite for dysplasia, 24 low-grade dysplasia, 4 high-grade dysplasia and 12 adenocarcinoma. Squamous epithelium showed the lowest methylation rates: 6% (IQR 5-11) vs. 11%(7-39.50) in negative/indefinite for dysplasia, p<0.01; 10.60%(6-24) in low-grade dysplasia, p<0.05; and 44.50%(9-66.75) in high-grade dysplasia/adenocarcinoma, p<0.01. This latter group also exhibited higher methylation rates than Barrett's epithelium with and without low-grade dysplasia (p<0.05). p16 methylation rates of microdissected and non-microdissected samples did not correlate unless the considered histological alteration comprised >71% of the sample.

CONCLUSIONS

p16 methylation is an early event in Barrett's carcinogenesis which increases with the severity of histological alteration. p16 methylation rates are profoundly influenced by sample heterogeneity, so selection of samples is crucial in order to detect differences.

Human trophoblasts are primarily distinguished from somatic cells by differences in the pattern rather than the degree of global CpG methylation

The placenta is a fetal exchange organ connecting mother and baby that facilitates fetal growth in utero. DNA methylation is thought to impact placental development and function. Global DNA methylation studies using human placental lysates suggest that the placenta is uniquely hypomethylated compared to somatic tissue lysates, and this hypomethylation is thought to be important in conserving the unique placental gene expression patterns required for successful function. In the placental field, methylation has frequently been examined in tissue lysates, which contain mixed cell types that can confound results. To better understand how DNA methylation influences placentation, DNA from isolated first trimester trophoblast populations underwent reduced representation bisulfite sequencing and was compared to publicly available data of blastocyst-derived and somatic cell populations. First, this revealed that, unlike murine blastocysts, human trophectoderm and inner cell mass samples did not have significantly different levels of global methylation. Second, our work suggests that differences in global CpG methylation between trophoblasts and somatic cells are much smaller than previously reported. Rather, our findings suggest that different patterns of CpG methylation may be more important in epigenetically distinguishing the placenta from somatic cell populations, and these patterns of methylation may contribute to successful placental/trophoblast function.

Summary: The placenta may not be as uniquely hypomethylated as previously reported, rather differences in the pattern of CpG methylation are what make it epigenetically distinct.

ZNF695 methylation predicts a response of esophageal squamous cell carcinoma to definitive chemoradiotherapy

PURPOSE

Definitive chemoradiotherapy (dCRT) is one of the standard treatments for esophageal squamous cell carcinoma. Patients with a response to dCRT have a better prognosis than those resistant to dCRT while survival benefits for patients with residual tumors are limited. Nevertheless, few molecular markers to predict the response to dCRT are currently available. Here, we aimed to establish a DNA methylation marker to predict the response to dCRT.

METHODS

A total of 104 patients were divided into screening (n = 43) and validation (n = 61) sets. A genome-wide DNA methylation analysis was performed using an Infinium HumanMethylation450 BeadChip array. Methylation levels were measured by quantitative methylation-specific PCR and normalized by the fraction of cancer cells in a sample.

RESULTS

The genome-wide methylation analysis of seven responders and eight non-responders identified 18 genomic regions specifically (un)methylated in the responders. Among these, methylation of the promoter CpG island of ZNF695 was significantly associated with the response to dCRT in the screening set (P = 0.004), and a cutoff value was determined. In the validation set, the association was successfully validated (P = 0.021), and a high specificity (90 %) for the prediction of responders was obtained using the prefixed cutoff value. In addition, a multivariate analysis showed that ZNF695 methylation was an independent predictive factor for the response to dCRT (OR 7.55, 95 % CI 2.12-26.9, P = 0.002).

CONCLUSION

ZNF695 methylation was significantly associated with the response to dCRT and is a promising predictive marker for the response to dCRT.

DNA methylation biomarkers: cancer and beyond

Biomarkers are naturally-occurring characteristics by which a particular pathological process or disease can be identified or monitored. They can reflect past environmental exposures, predict disease onset or course, or determine a patient's response to therapy. Epigenetic changes are such characteristics, with most epigenetic biomarkers discovered to date based on the epigenetic mark of DNA methylation. Many tissue types are suitable for the discovery of DNA methylation biomarkers including cell-based samples such as blood and tumor material and cell-free DNA samples such as plasma. DNA methylation biomarkers with diagnostic, prognostic and predictive power are already in clinical trials or in a clinical setting for cancer. Outside cancer, strong evidence that complex disease originates in early life is opening up exciting new avenues for the detection of DNA methylation biomarkers for adverse early life environment and for estimation of future disease risk. However, there are a number of limitations to overcome before such biomarkers reach the clinic. Nevertheless, DNA methylation biomarkers have great potential to contribute to personalized medicine throughout life. We review the current state of play for DNA methylation biomarkers, discuss the barriers that must be crossed on the way to implementation in a clinical setting, and predict their future use for human disease.

DNA methylation subgroups and the CpG island methylator phenotype in gastric cancer: a comprehensive profiling approach

BACKGROUND

Methylation-induced silencing of promoter CpG islands in tumor suppressor genes plays an important role in human carcinogenesis. In colorectal cancer, the CpG island methylator phenotype (CIMP) is defined as widespread and elevated levels of DNA methylation and CIMP+ tumors have distinctive clinicopathological and molecular features. In contrast, the existence of a comparable CIMP subtype in gastric cancer (GC) has not been clearly established. To further investigate this issue, in the present study we performed comprehensive DNA methylation profiling of a well-characterised series of primary GC.

METHODS

The methylation status of 1,421 autosomal CpG sites located within 768 cancer-related genes was investigated using the Illumina GoldenGate Methylation Panel I assay on DNA extracted from 60 gastric tumors and matched tumor-adjacent gastric tissue pairs. Methylation data was analysed using a recursively partitioned mixture model and investigated for associations with clinicopathological and molecular features including age, Helicobacter pylori status, tumor site, patient survival, microsatellite instability and BRAF and KRAS mutations.

RESULTS

A total of 147 genes were differentially methylated between tumor and matched tumor-adjacent gastric tissue, with HOXA5 and hedgehog signalling being the top-ranked gene and signalling pathway, respectively. Unsupervised clustering of methylation data revealed the existence of 6 subgroups under two main clusters, referred to as L (low methylation; 28% of cases) and H (high methylation; 72%). Female patients were over-represented in the H tumor group compared to L group (36% vs 6%; P = 0.024), however no other significant differences in clinicopathological or molecular features were apparent. CpG sites that were hypermethylated in group H were more frequently located in CpG islands and marked for polycomb occupancy.

CONCLUSIONS

High-throughput methylation analysis implicates genes involved in embryonic development and hedgehog signaling in gastric tumorigenesis. GC is comprised of two major methylation subtypes, with the highly methylated group showing some features consistent with a CpG island methylator phenotype.

Challenges and Pitfalls in the Introduction of Pharmacogenetics for Cancer

There have been several success stories in the field of pharmacogenetics in recent years, including the analysis of HER2 amplification for trastuzumab selection in breast cancer and VKORC1 genotyping for warfarin dosing in thrombosis. Encouraging results from these studies suggest that genetic factors may indeed be important determinants of drug response and toxicity for at least some drugs. However, to apply pharmacogenetics appropriately, a thorough understanding of the scope and limitations of this field is required. The challenges include an appreciation of biological variability, logistical issues pertaining to the proper management of information, the need for robust methods and adequate sample quality with well-designed workflows. At the same time, the economics of pharmacogenetic testing from the perspective of clinicians, patients, governments, insurance companies and pharmaceutical companies will play an important role in determining its future use. Ethical considerations such as informed consent and patient privacy, as well as the role of regulatory bodies in addressing these issues, must be fully understood. Only once these issues are properly dealt with can the full benefits of pharmacogenetics begin to be realised. Key words: Biomarkers, Diagnostics, Personalised medicine, Pharmacogenomics, Translational medicine