The Limitations of Locus Specific Methylation Qualification and Quantification in Clinical Material

The terms methylation quantification and qualification seem self-explanatory however, the results of experiments aiming to quantify or qualify locus specific methylation in clinical material are often difficult to interpret. There are three main reasons for difficulties in understanding methylation status measurement. First, the complexity of locus specific methylation patterns, which oscillate between unmethylated, fully methylated, and heterogeneously methylated. Second the interpretation of methylation-screening results can frequently be problematic due to limitations of the methods used. And finally the specifications of the clinical samples used in laboratory practice frequently hamper the methylation measurement. Thus, the process of quantification and qualification of methylation has to be discussed with consideration of the specific locus analyzed, the methodology used, and the clinical material source used in each specific experiment. The question of the clinical significance of determination of different methylation levels is even more complicated, with substantial evidence for correlation between qualitative methylation changes and clinical features of the disease and at the same time no data showing that different relative levels of methylation alter the disease outcome. The limitations of methylation quantification and qualification are discussed in this mini-review

Methylation-sensitive high resolution melting (MS-HRM): a new approach for sensitive and high-throughput assessment of methylation

In this article, we show that high resolution melting analysis (HRM) is a sensitive and specific method for the detection of methylation. Methylated DNA and unmethylated DNA acquire different sequences after bisulphite treatment resulting in PCR products with markedly different melting profiles. We used PCR to amplify both methylated and unmethylated sequences and assessed HRM for the determination of the methylation status of the MGMT promoter region. Reconstruction experiments showed that MGMT methylation could be detected at levels as low as 0.1%. Moreover, MS-HRM allows for estimation of the methylation level by comparing the melting profiles of unknown PCR products to the melting profiles of PCR products derived from standards with a known unmethylated to methylated template ratio. We used MS-HRM for the analysis of eight cell lines of known methylation status and a panel of colorectal cancer specimens. The simplicity and high reproducibility of the MS-HRM protocol makes MS-HRM the method of choice for methylation assessment in many diagnostic and research applications

A new approach to primer design for the control of PCR bias in methylation studies

Primer design for PCR-based methylation analysis following bisulfite conversion of DNA is considerably more complex than primer design for regular PCR. The choice of the optimal primer set is critical to the performance and correct interpretation of the results. Most methodologies in methylation analysis utilize primers that theoretically amplify methylated and unmethylated templates at the same time. The proportional amplification of all templates is critical but difficult to achieve due to PCR bias favouring the amplification of the unmethylated template. The focus of this brief communication is to point out the important criteria needed for the successful choice of primers that will enable the control of PCR bias in bisulfite based methylation-screening protocols

Quality assessment of DNA derived from up to 30 years old formalin fixed paraffin embedded (FFPE) tissue for PCR-based methylation analysis using SMART-MSP and MS-HRM

<p>Abstract</p> <p>Background</p> <p>The High Resolution Melting (HRM) technology has recently been introduced as a rapid and robust analysis tool for the detection of DNA methylation. The methylation status of multiple tumor suppressor genes may serve as biomarkers for early cancer diagnostics, for prediction of prognosis and for prediction of response to treatment. Therefore, it is important that methodologies for detection of DNA methylation continue to evolve. Sensitive Melting Analysis after Real Time - Methylation Specific PCR (SMART-MSP) and Methylation Sensitive - High Resolution Melting (MS-HRM) are two methods for single locus DNA methylation detection based on HRM.</p> <p>Methods</p> <p>Here, we have assessed the quality of DNA extracted from up to 30 years old Formalin Fixed Paraffin Embedded (FFPE) tissue for DNA methylation analysis using SMART-MSP and MS-HRM. The quality assessment was performed on DNA extracted from 54 Non-Small Cell Lung Cancer (NSCLC) samples derived from FFPE tissue, collected over 30 years and grouped into five years intervals. For each sample, the methylation levels of the <it>CDKN2A </it>(<it>p16</it>) and <it>RARB </it>promoters were estimated using SMART-MSP and MS-HRM assays designed to assess the methylation status of the same CpG positions. This allowed for a direct comparison of the methylation levels estimated by the two methods for each sample.</p> <p>Results</p> <p><it>CDKN2A </it>promoter methylation levels were successfully determined by SMART-MSP and MS-HRM in all 54 samples. Identical methylation estimates were obtained by the two methods in 46 of the samples. The methylation levels of the <it>RARB </it>promoter were successfully determined by SMART-MSP in all samples. When using MS-HRM to assess <it>RARB </it>methylation five samples failed to amplify and 15 samples showed a melting profile characteristic for heterogeneous methylation. Twenty-seven of the remaining 34 samples, for which the methylation level could be estimated, gave the same result as observed when using SMART-MSP.</p> <p>Conclusion</p> <p>MS-HRM and SMART-MSP can be successfully used for single locus methylation studies using DNA derived from up to 30 years old FFPE tissue. Furthermore, it can be expected that MS-HRM and SMART-MSP will provide similar methylation estimates when assays are designed to analyze the same CpG positions.</p

Epigenetic activation of antiviral sensors and effectors of interferon response pathways during SARS-CoV-2 infection

Recent studies have shown that methylation changes identified in blood cells of COVID-19 patients have a po-tential to be used as biomarkers of SARS-CoV-2 infection outcomes. However, different studies have reported different subsets of epigenetic lesions that stratify patients according to the severity of infection symptoms, and more importantly, the significance of those epigenetic changes in the pathology of the infection is still not clear. We used methylomics and transcriptomics data from the largest so far cohort of COVID-19 patients from four geographically distant populations, to identify casual interactions of blood cells' methylome in pathology of the COVID-19 disease. We identified a subset of methylation changes that is uniformly present in all COVID-19 patients regardless of symptoms. Those changes are not present in patients suffering from upper respiratory tract infections with symptoms similar to COVID-19. Most importantly, the identified epigenetic changes affect the expression of genes involved in interferon response pathways and the expression of those genes differs be-tween patients admitted to intensive care units and only hospitalized. In conclusion, the DNA methylation changes involved in pathophysiology of SARS-CoV-2 infection, which are specific to COVID-19 patients, can not only be utilized as biomarkers in the disease management but also present a potential treatment target

IGHV-associated methylation signatures more accurately predict clinical outcomes of chronic lymphocytic leukemia patients than IGHV mutation load

Currently, no molecular biomarker indices are used in standard care to make treatment decisions at diagnosis of chronic lymphocytic leukemia (CLL). We used Infinium MethylationEPIC array data from diagnostic blood samples of 114 CLL patients and developed a procedure to stratify patients based on methylation signatures associated with mutation load of the IGHV gene. This procedure allowed us to predict the time to treatment with a hazard ratio (HR) of 8.34 (95% confidence interval [CI]: 4.54-15.30), as opposed to a HR of 4.35 (95% CI: 2.60-7.28) using IGHV mutation status. Detailed evaluation of 17 cases for which the two classification procedures gave discrepant results showed that these cases were incorrectly classified using IGHV status. Moreover, methylation-based classification stratified patients with different overall survival (HR=1.82; 95% CI: 1.07-3.09), which was not possible using IGHV status. Furthermore, we assessed the performance of the developed classification procedure using published HumanMethylation450 array data for 159 patients for whom information on time to treatment, overall survival and relapse was available. Despite 450K array methylation data not containing all the biomarkers used in our classification procedure, methylation signatures again stratified patients with significantly better accuracy than did IGHV mutation load regarding all available clinical outcomes. Thus, stratification using IGHV-associated methylation signatures may provide better prognostic power than IGHV mutation status