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. 2024 Jun 26;14(1):14700.
doi: 10.1038/s41598-024-65580-6.

Droplet digital PCR analysis of CDH13 methylation status in Slovak women with invasive ductal breast cancer

Ivana Baranová  1   2   3 , Marek Samec  4   5 , Dana Dvorská  1 , Igor Šťastný  1   6 , Katarína Janíková  1 , Ivana Kašubová  1 , Andrea Hornáková  1 , Eva Lukáčová  7 , Andrea Kapinová  1 , Kamil Biringer  6 , Erika Halašová  1 , Zuzana Danková  1   3
Affiliations

Droplet digital PCR analysis of CDH13 methylation status in Slovak women with invasive ductal breast cancer

Ivana Baranová et al. Sci Rep. .

Abstract

Identifying novel epigenetic biomarkers is a promising way to improve the clinical management of patients with breast cancer. Our study aimed to determine the methylation pattern of 25 tumor suppressor genes (TSG) and select the best methylation biomarker associated with clinicopathological features in the cohort of Slovak patients diagnosed with invasive ductal carcinoma (IDC). Overall, 166 formalin-fixed, paraffin-embedded (FFPE) tissues obtained from patients with IDC were included in the study. The methylation status of the promoter regions of 25 TSG was analyzed using semiquantitative methylation-specific MLPA (MS-MLPA). We identified CDH13 as the most frequently methylated gene in our cohort of patients. Further analysis by ddPCR confirmed an increased level of methylation in the promoter region of CDH13. A significant difference in CDH13 methylation levels was observed between IDC molecular subtypes LUM A versus HER2 (P = 0.0116) and HER2 versus TNBC (P = 0.0234). In addition, significantly higher methylation was detected in HER2+ versus HER2- tumors (P = 0.0004) and PR- versus PR+ tumors (P = 0.0421). Our results provide evidence that alteration in CDH13 methylation is associated with clinicopathological features in the cohort of Slovak patients with IDC. In addition, using ddPCR as a methylation-sensitive method represents a promising approach characterized by higher precision and technical simplicity to measure the methylation of target CpGs in CDH13 compared to other conventional methods such as MS-MLPA.

Keywords: CDH13; CpG methylation; Droplet digital PCR; MS-MLPA.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
The linearity of ddPCR assay for quantification of CDH13 methylation.
Figure 2
Figure 2
Heatmap visualization of methylation levels detected by MS-MLPA. The cut-off value discriminating between methylated and unmethylated status for each gene is shown at the top of the heatmap. LUM, luminal; TNBC, triple-negative breast cancer.
Figure 3
Figure 3
Representative plots of ddPCR results. Two-fold dilution series, diluted from 8000 to 62 copies per reaction, of methylated (top left) and unmethylated control DNA (top right). Two-dimensional plot corresponding to methylated sample (bottom). Blue dots represent a number of DNA copies considered methylated; green dots represent unmethylated copies of DNA. The resulting level of sample methylation is calculated as the ratio between methylated copies and all DNA copies detected by both channels. The purple lines define the threshold amplitudes.
Figure 4
Figure 4
Methylation levels detected by MS-MLPA and ddPCR in CDH13 gene.
Figure 5
Figure 5
Correlation of detected CDH13 methylation levels with clinicopathological characteristics. ER, estrogen receptor; PR, progesterone receptor; LUM, luminal; TNBC, triple-negative breast cancer.
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