Quantification of DNA methylation independent of sodium bisulfite conversion using methylation-sensitive restriction enzymes and digital PCR

Implementation of a MSRE ddPCR method for the detection of methylated WIF1 and NPY genes in colorectal cancer patients

BACKGROUND

Colorectal cancer is a worldwide leading cause of death accounting for high-rate mortality. Mutations in the epidermal growth factor receptor and RAS/MAPK pathways, as well as altered methylation genes profiles, have been described as molecular mechanisms promoting and sustaining tumour development and progression. Aberrant methylation is a well-known epigenetic mechanism involved in gene regulation; particularly several genes were reported as hypermethylated in CRC. Recently, it was shown that epigenetic alterations in genes such as neuropeptide y, proenkephalin and Wnt inhibitory factor 1 can be used as promising disease biomarkers. Almost all methods developed for the DNA methylation analysis combined next generation sequencing, conventional qRT-PCR or ddPCR with the prior DNA modification with sodium bisulfite.

METHODS AND RESULTS

We implemented a ddPCR method to assess the methylation status of Wnt inhibitory factor 1 and neuropeptide y using the methylation sensitive restriction enzyme approach that does not impact on DNA quality and guarantees the discrimination of DNA methylation independent of bisulfite conversion.

CONCLUSIONS

We showed that this method is robust and sensitive also allowing the monitoring of CRC disease progression when applied to circulating free DNA samples from liquid biopsies, proving to be a fast and easy to implement assay to be used for the monitoring of the methylation pattern of clinically relevant target genes.

Methylation‑sensitive restriction enzyme‑droplet digital PCR assay for the one‑step highly sensitive analysis of DNA methylation hotspots

DNA methylation is an epigenetic modification that plays a key role in several cellular processes mediating the fine regulation of gene expression. Aberrant DNA methylation is observed in a wide range of pathologies, including cancer. Since these DNA modifications are transferred to the cell progenies and are stable over the time, the analysis of DNA methylation status has been proposed for diagnostic and prognostic purposes in cancer. Currently, DNA bisulfite conversion is the gold standard method for the high‑throughput analysis of DNA methylation alterations. However, bisulfite treatment induces DNA fragmentation affecting its quality for the downstream analyses. In this field, it is mandatory to identify novel methods to overcome the limits of conventional approaches. In the present study, the Methylation‑Sensitive Restriction Enzyme‑droplet digital PCR (MSRE‑ddPCR) assay was developed as a novel sensitive method for the analysis of DNA methylation of short genomic regions, combining the MSRE assay with the high‑sensitivity ddPCR and using an exogenous methylation sequence as control. Setup and validation experiments were performed analyzing a methylation hotspot of the Solute Carrier Family 22 Member 17 in DNA samples derived from melanoma cell lines as well as from tissues and serum samples obtained from patients with melanoma and healthy controls. Compared with the standard MSRE approaches, the MSRE‑ddPCR assay is more appropriate for the analysis of DNA methylation (methDNA) in samples with low amounts of DNA (up to 0.651 ng) showing a greater sensitivity. These findings suggested the potential clinical application of MSRE‑ddPCR paving the way to the analysis of other methDNA hotspots in different tumors.

Mini-review of DNA Methylation Detection Techniques and Their Potential Applications in Disease Diagnosis, Prognosis, and Treatment

DNA methylation is the dominant epigenetic mechanism for regulating gene expression in mammals, playing crucial roles in development, differentiation, and tissue homeostasis. Aberrations in DNA methylation are closely associated with the potential onset of various diseases. Consequently, numerous DNA methylation detection techniques have been successively developed. These methods not only facilitate the exploration of disease mechanisms but also hold significant promise for the development of diagnostic and prognostic strategies. In this Perspective, we present a comprehensive overview of commonly employed DNA methylation detection techniques as well as biosensing based on their underlying analytical techniques. For its medical applications, we begin by examining the pathogenesis of different diseases and then proceed to discuss how relevant technologies are applied in the context of these specific medical conditions. Additionally, we briefly discuss the current limitations of these techniques and highlight future challenges in advancing methylation detection and analysis methodologies.

Investigating FGFR2 gene as a blood-based epigenetic biomarker in gastric cancer

BACKGROUND

Gastric adenocarcinoma is a prevalent form of cancer that often remains undetected in its early stages due to the lack of specific symptoms. This delayed diagnosis leads to poor clinical outcomes, underscoring the need for an effective and non-invasive method for early detection. Recent advances in cancer epigenetics have led to the identification of biomarkers that have the potential to revolutionize the early detection and monitoring of this disease. One such promising biomarker is the methylation of the FGFR2 promoter. This study aims to measure the methylation levels of a specific CpG site in the FGFR2 promoter gene in DNA extracted from blood leukocytes from patients with intestinal metaplasia, gastric cancer, and healthy control.

MATERIAL AND METHODS

The CpG site of the FGFR2 gene promoter was identified in its control region. Methylation alteration of the selected FGFR2 CpG site was determined through the (methylation-sensitive restriction enzyme) MSRE-qPCR. Genomic DNA was extracted from one hundred twenty-five participants.

RESULTS

The normal group had mean methylation levels of 93.23 ± 4.929%, while the IM group had a level of 69.85 ± 27.15%. In GC patients, the levels varied, with 25.96 ± 18.98% in the intestinal type and 28.30 ± 16.07% in the diffuse type. The methylation levels in the IM and GC patients were significantly lower than those in the normal control group. However, no significant difference was observed between the methylation status of the intestinal type of GC and the diffuse type. The Receiver operating characteristic (ROC) curve analysis showed that FGFR2 CpG methylation levels in GC patients compared to normal controls had a high sensitivity of 100% and specificity of 100%, with a cut-off of < 74.25%; when GC patients were compared to IM patients, the sensitivity was 85%, and the specificity was 80%, with a cut-off < 44.45%.

CONCLUSIONS

The potential of the FGFR2 methylation status as a non-invasive biomarker lies in its ability to be detected in blood leukocytes, which makes it a promising tool for the early detection of intestinal metaplasia and gastric cancer. This could significantly improve the detection and management of these gastric conditions.

Density Control over MBD2 Receptor-Coated Surfaces Provides Superselective Binding of Hypermethylated DNA

Using the biomarker hypermethylated DNA (hmDNA) for cancer detection requires a pretreatment to isolate or concentrate hmDNA from nonmethylated DNA. Affinity chromatography using a methyl binding domain-2 (MBD2) protein can be used, but the relatively low enrichment selectivity of MBD2 limits its clinical applicability. Here, we developed a superselective, multivalent, MBD2-coated platform to improve the selectivity of hmDNA enrichment. The multivalent platform employs control over the MBD2 surface receptor density, which is shown to strongly affect the binding of DNA with varying degrees of methylation, improving both the selectivity and the affinity of DNAs with higher numbers of methylation sites. Histidine-10-tagged MBD2 was immobilized on gold surfaces with receptor density control by tuning the amount of nickel nitrilotriacetic acid (NiNTA)-functionalized thiols in a thiol-based self-assembled monolayer. The required MBD2 surface receptor densities for DNA surface binding decreases for DNA with higher degrees of methylation. Both higher degrees of superselectivity and surface coverages were observed upon DNA binding at increasing methylation levels. Adopting the findings of this study into hmDNA enrichment of clinical samples has the potential to become more selective and sensitive than current MBD2-based methods and, therefore, to improve cancer diagnostics.

RASSF1A methylation as a biomarker for detection of colorectal cancer and hepatocellular carcinoma

BACKGROUND

Studies have validated the potential of methylated cell-free DNA as a biomarker in various tumors, and methylated DNA in plasma may be a potential biomarker for cancer.

AIM

To evaluate the diagnostic value of RASSF1A methylation in plasma for colorectal cancer (CRC) and hepatocellular carcinoma (HCC).

METHODS

A total of 92 CRC patients, 67 colorectal polyp (CRP) patients, 63 HCC patients, and 66 liver cirrhosis (LC) patients were enrolled. The plasma DNA was subjected to DNA extraction, double-strand DNA concentration determination, bisulfite conversion, purification, single-strand DNA concentration determination, and digital polymerase chain reaction (PCR) detection. The methylation rate was calculated. The diagnostic value was evaluated by the area under the curve (AUC).

RESULTS

The age and sex in the CRC and CRP groups and the HCC and LC groups were also matched. The DNA methylation rate of RASSF1A in plasma in the CRC group was 2.87 ± 1.80, and that in the CRP group was 1.50 ± 0.64. DNA methylation of RASSF1A in plasma showed a significant difference between the CRC and CRP groups. The AUC of RASSF1A methylation for discriminating the CRC and CRP groups was 0.82 (0.76-0.88). The AUCs of T1, T2, T3 and T4 CRC and CRP were 0.83 (0.72-0.95), 0.87 (0.78-0.95), 0.86 (0.77-0.95), and 0.75 (0.64-0.85), respectively. The DNA methylation rate of RASSF1A in plasma in the HCC group was 4.45 ± 2.93, and that in the LC group was 2.46 ± 2.07. DNA methylation of RASSF1A in plasma for the HCC and LC groups showed a significant difference. The AUC of RASSF1A methylation for discriminating the HCC and LC groups was 0.70 (0.60-0.79). The AUCs of T1, T2, T3 and T4 HCC and LC were 0.80 (0.61, 1.00), 0.74 (0.59-0.88), 0.60 (0.42-0.79), and 0.68 (0.53-0.82), respectively.

CONCLUSION

RASSF1A methylation in plasma detected by digital PCR may be a potential biomarker for CRC and HCC.

Quantification of Unmethylated Insulin DNA Using Methylation Sensitive Restriction Enzyme Digital Polymerase Chain Reaction

Assessment of specific β-cell death can be used to determine the quality and viability of pancreatic islets prior to transplantation and hence predict the suitability of the pancreas for isolation. Recently, several groups have demonstrated that unmethylated insulin (INS)-DNA is correlated to β-cell death in type 1 diabetes patients and during clinical islet isolation and subsequent transplantation. Here, we present a step-by-step protocol of our novel developed method for quantification of the relative amount of unmethylated INS-DNA using methylation sensitive restriction enzyme digital polymerase chain reaction This method provides a novel and sensitive way to quantify the relative amount of β-cell derived unmethylated INS-DNA in cellular lysate. We therefore suggest that this technique can be of value to reliably determine the purity of an islet preparation and may also serve as a measure of the quality of islets prior to transplantation measuring unmethylated INS-DNA as a reflection of the relative amount of lysed β-cells.

Accurate Quantification of T Cells in Copy Number Stable and Unstable DNA Samples Using Multiplex Digital PCR

An accurate T-cell quantification is prognostically and therapeutically relevant in various malignancies. We previously developed a digital PCR-based approach offering a precise T-cell enumeration in small amounts of DNA. However, it may be challenging to apply this method in malignant specimens, as copy number instability can disturb the underlying mathematical model. For example, approximately 24% of the tumors from The Cancer Genome Atlas pan-cancer data set carried a copy number alteration affecting our TRB gene T-cell marker, which would cause an underestimation or overestimation of the T-cell fraction. In this study, we introduce a multiplex digital PCR experimental setup to quantify T cells in copy number unstable DNA samples. By implementing a so-called regional corrector, genetic alterations involving the T-cell marker locus can be recognized and corrected for. This novel setup is evaluated mathematically in silico and validated in vitro by measuring T-cell presence in various samples with a known T-cell fraction. The utility of the approach is further demonstrated in copy number altered cutaneous melanomas. Our novel multiplex setup provides a simple, but accurate, DNA-based T-cell quantification in both copy number stable and unstable specimens. This approach has potential clinical and diagnostic applications, as it does not depend on availability of T-cell epitopes, has low requirements for sample quantity and quality, and can be performed in a relatively easy experiment.

Quantification of DNA methylation independent of sodium bisulfite conversion using methylation-sensitive restriction enzymes and digital PCR

Epigenetic regulation is important in human health and disease, but the exact mechanisms remain largely enigmatic. DNA methylation represents one epigenetic aspect but is challenging to quantify. In this study, we introduce a digital approach for the quantification of the amount and density of DNA methylation. We designed an experimental setup combining efficient methylation‐sensitive restriction enzymes with digital polymerase chain reaction (PCR) to quantify a targeted density of DNA methylation independent of bisulfite conversion. By using a stable reference and comparing experiments treated and untreated with these enzymes, copy number instability could be properly normalized. In silico simulations demonstrated the mathematical validity of the setup and showed that the measurement precision depends on the amount of input DNA and the fraction methylated alleles. This uncertainty could be successfully estimated by the confidence intervals. Quantification of RASSF1 promoter methylation in a variety of healthy and malignant samples and in a calibration curve confirmed the high accuracy of our approach, even in minute amounts of DNA. Overall, our results indicate the possibility of quantifying DNA methylation with digital PCR, independent of bisulfite conversion. Moreover, as the context‐density of methylation can also be determined, biological mechanisms can now be quantitatively assessed.