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<p>Cholangiocarcinoma (CC) is a highly lethal malignancy that urgently requires reliable prognostic biomarkers. Although <i>MUC1</i> expression and promoter methylation have been implicated in CC, the clinical significance of promoter methylation pattern composition, beyond average methylation levels, remains unclear. Here, we investigated the relationship between <i>MUC1</i> promoter methylation heterogeneity, <i>MUC1</i> mRNA expression, and prognosis in CC. We analyzed bisulfite amplicon sequencing data and mRNA expression of <i>MUC1</i>, DNA methylation-related enzymes (<i>TET1</i>, <i>TET2</i>, <i>TET3</i>, <i>Dnmt1</i>, and <i>Dnmt3a</i>), and tumor microenvironment stress markers in 131 CC tissues. In the neoplastic region, high <i>MUC1</i> mRNA expression was associated with poor overall survival (HR = 0.131, 95% CI: 0.02&#xa0;to&#xa0;0.95, <i>p</i> = 0.042) and correlated with the abundance of completely unmethylated promoter patterns (r = 0.386, <i>p</i> &lt; 0.001). Among the enzymes analyzed, only <i>TET3</i> expression significantly correlated with the abundance of completely unmethylated patterns in the neoplastic region (Cohen’s f<sup>2</sup> = 0.108, <i>p</i> = 0.009), suggesting a potential region-specific regulatory association. We visualized beta-diversity in methylation pattern composition using t-SNE and classified samples into two groups based on a linear decision boundary in the t-SNE space. This classification stratified prognosis independently of clinical factors (HR = 0.291, 95% CI: 0.06&#xa0;to&#xa0;0.94, <i>p</i> = 0.037; multivariate <i>p</i> = 0.021). These findings propose a novel, composition-based epigenetic stratification framework in CC, revealing that <i>MUC1</i> promoter methylation pattern structure—rather than average methylation level—has prognostic relevance. Our results highlight the potential of pattern-resolved methylation profiling in the development of clinically applicable epigenetic biomarkers.</p>

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MUC1 promoter methylation pattern diversity and its association with TET3 expression and prognosis in cholangiocarcinoma

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月29日

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  • Seiya Yokoyama,
  • Ikumi Kitazono,
  • Michiyo Higashi,
  • Kei Matsuo,
  • Taiji Hamada,
  • Mari Kirishima,
  • Hirotsugu Noguchi,
  • Takashi Tasaki,
  • Miki Murakami,
  • Toshiaki Akahane,
  • Tatsuhiko Furukawa,
  • Takao Ohtsuka,
  • Tomoyuki Sugimoto,
  • Akihide Tanimoto

摘要

Cholangiocarcinoma (CC) is a highly lethal malignancy that urgently requires reliable prognostic biomarkers. Although MUC1 expression and promoter methylation have been implicated in CC, the clinical significance of promoter methylation pattern composition, beyond average methylation levels, remains unclear. Here, we investigated the relationship between MUC1 promoter methylation heterogeneity, MUC1 mRNA expression, and prognosis in CC. We analyzed bisulfite amplicon sequencing data and mRNA expression of MUC1, DNA methylation-related enzymes (TET1, TET2, TET3, Dnmt1, and Dnmt3a), and tumor microenvironment stress markers in 131 CC tissues. In the neoplastic region, high MUC1 mRNA expression was associated with poor overall survival (HR = 0.131, 95% CI: 0.02 to 0.95, p = 0.042) and correlated with the abundance of completely unmethylated promoter patterns (r = 0.386, p < 0.001). Among the enzymes analyzed, only TET3 expression significantly correlated with the abundance of completely unmethylated patterns in the neoplastic region (Cohen’s f2 = 0.108, p = 0.009), suggesting a potential region-specific regulatory association. We visualized beta-diversity in methylation pattern composition using t-SNE and classified samples into two groups based on a linear decision boundary in the t-SNE space. This classification stratified prognosis independently of clinical factors (HR = 0.291, 95% CI: 0.06 to 0.94, p = 0.037; multivariate p = 0.021). These findings propose a novel, composition-based epigenetic stratification framework in CC, revealing that MUC1 promoter methylation pattern structure—rather than average methylation level—has prognostic relevance. Our results highlight the potential of pattern-resolved methylation profiling in the development of clinically applicable epigenetic biomarkers.