A Comparative Study of Methyl-BEAMing and Droplet Digital PCR for MGMT Gene Promoter Hypermethylation Detection

Abstract

Background: O-6-methylguanine-DNA methyltransferase is responsible for the direct repair of O6-methylguanine lesions induced by alkylating agents, including temozolomide. O-6-methylguanine-DNA methyltransferase promoter hypermethylation is a well-established biomarker for temozolomide response in glioblastoma patients, also correlated with therapeutic response in colorectal cancer. Objectives: The ARETHUSA clinical trial aims to stratify colorectal cancer patients based on their mismatch repair status. Mismatch repair-deficient patients are eligible for treatment with immune checkpoint inhibitors (anti-PDL-1), whereas mismatch repair-proficient samples are screened for O-6-methylguanine-DNA methyltransferase promoter methylation to identify those suitable for temozolomide treatment. Methods: In this context, a subset of ARETHUSA metastatic colorectal cancer samples was used to compare two different techniques for assessing O-6-methylguanine-DNA methyltransferase hypermethylation: Methyl-BEAMing, a highly sensitive digital PCR approach that combines emulsion PCR and flow cytometry, and droplet digital PCR, a more automated procedure that enables the rapid, operator-independent analysis of a large number of samples. Results: Our study clearly demonstrates that the results obtained using Methyl-BEAMing and droplet digital PCR are comparable, with both techniques showing similar accuracy, sensitivity, and reproducibility. Conclusions: Digital droplet PCR proved to be an efficient method for detecting gene promoter methylation. However, the Methyl-BEAMing method has proved more sensitive for detecting low quantities of DNA.

Keywords: DNAmethylation; MGMT; Methyl-BEAMing; digital PCR; metastatic colorectal cancer.

Figure 1

Representative plots of the gate strategy used for the flow cytometric analysis. (A) ARETHUSA samples analyzed through the Methyl-BEAMing technique were first grouped based on their complexity events. (B) Gate R2 (46.6%) includes unmethylated events, whereas R3 (4.1%) contains methylated ones. (C) The value of 61.7% referred to gate R3 is representative of a methylated sample. (D) Unmethylated sample control (R3 0%). (E) Methylated sample control (R3 83%). (F) The 50% control, obtained by mixing the unmethylated control with the methylated one (R3 34.1%) (G) Methylation profiling of CRC tissue samples assessed by Methyl-BEAMing.

Figure 2

Assessment of MGMT gene promoter hypermethylation using the ddPCR technique. (A) Scheme of ddPCR: DNA amplification occurs independently in thousands of drops through a water-in-oil emulsion. Droplets are classified as positive or negative based on the emitted fluorescence wavelength. (B) Linearity of quantification of ultramer oligonucleotide mixture assessed by ddPCR. (C) Methylation analysis by ddPCR using three independent bisulfite treatments in nine different mCRC samples. (D) MGMT methylation profiling of CRC tissue samples obtained by ddPCR.

Figure 3

Evaluation of the concordance between results obtained using Methyl-BEAMing and those obtained using ddPCR. (A) Contingency table was carried out to qualitatively compare the number of methylated samples evaluated by either Methyl-BEAMing or ddPCR analysis. (B) Bland–Altman plot shows the agreement between the results of both techniques used. (C) Correlation and linear regression between Methyl-BEAMing and droplet digital PCR results. (D) The table reports differences between Methyl-BEAMing and ddPCR, including the time of execution, number of amplification steps, automation grade, and sensitivity.

Figure 4

Analysis of the incidence of MGMT gene promoter methylation in a cohort of mCRC patients. (A) Clinical features collected for 148 mCRC patients. (B) This Table shows a non-statistically significant trend of increased MGMT methylation frequency in older women compared to younger ones (Fisher’s exact probability test one-tailed p-value = 0.4963).