Droplet digital PCR analysis of CDH13 methylation status in Slovak women with invasive ductal breast cancer
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...
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Veröffentlicht in: | Scientific reports 2024-06, Vol.14 (1), p.14700-10, Article 14700 |
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Sprache: | eng |
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Zusammenfassung: | 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. |
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ISSN: | 2045-2322 2045-2322 |
DOI: | 10.1038/s41598-024-65580-6 |