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Background <p>A blood-based approach to monitor metastasis and recurrence of esophageal squamous cell carcinoma (ESCC) remains undeveloped. This study aimed to establish a dependable model utilizing cfDNA 5-hydroxymethylcytosines (5hmC) signatures to detect these conditions in ESCC.</p> Methods <p>The 5hmC-Seal technique was employed to generate comprehensive 5hmC profiles from the plasma cell-free DNA (cfDNA) of 122 ESCC patients, classified into 72 with metastasis, 50 without metastasis, 30 with recurrence, and 92 without recurrence. Initial steps involved identifying distinct hydroxymethylation signatures linked to metastasis and recurrence. Machine learning algorithms were then utilized to construct predictive models.</p> Results <p>The study confirmed that 5hmC-based markers are predictive of metastasis and recurrence among ESCC patients. The analysis of 14 5hmC biomarkers revealed a sensitivity of 88.90% and a specificity of 84.00% (AUC = 0.922) in differentiating patients with ESCC metastasis from those without in the validation cohort. Similarly, 11 5hmC biomarkers showed a sensitivity of 93.30% and a specificity of 89.10% (AUC = 0.936) in identifying recurrent versus non-recurrent ESCC cases. Additionally, a wp-score for metastasis and recurrence, derived from the 5hmC marker, prognosticated patient outcomes.</p> Conclusions <p>The findings indicate that 5hmC markers from cfDNA serve as effective epigenetic indicators for the non-invasive detection of ESCC metastasis and recurrence.</p>

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cfDNA hydroxymethylcytosine profiling for detection metastasis and recurrence of Esophageal Squamous Cell Carcinoma

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年3月15日

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  • Subinuer Kuerban,
  • Hangyu Chen,
  • Long Chen,
  • Lei Zhang,
  • Xuehui Li,
  • Baixin Zhen,
  • Hong Xiao,
  • Yingzhu Chen,
  • Haitao Zhou,
  • Zhen Liang,
  • Guobing Xu,
  • Yicun Tao,
  • Jian Lin,
  • Xiaozheng Kang

摘要

Background

A blood-based approach to monitor metastasis and recurrence of esophageal squamous cell carcinoma (ESCC) remains undeveloped. This study aimed to establish a dependable model utilizing cfDNA 5-hydroxymethylcytosines (5hmC) signatures to detect these conditions in ESCC.

Methods

The 5hmC-Seal technique was employed to generate comprehensive 5hmC profiles from the plasma cell-free DNA (cfDNA) of 122 ESCC patients, classified into 72 with metastasis, 50 without metastasis, 30 with recurrence, and 92 without recurrence. Initial steps involved identifying distinct hydroxymethylation signatures linked to metastasis and recurrence. Machine learning algorithms were then utilized to construct predictive models.

Results

The study confirmed that 5hmC-based markers are predictive of metastasis and recurrence among ESCC patients. The analysis of 14 5hmC biomarkers revealed a sensitivity of 88.90% and a specificity of 84.00% (AUC = 0.922) in differentiating patients with ESCC metastasis from those without in the validation cohort. Similarly, 11 5hmC biomarkers showed a sensitivity of 93.30% and a specificity of 89.10% (AUC = 0.936) in identifying recurrent versus non-recurrent ESCC cases. Additionally, a wp-score for metastasis and recurrence, derived from the 5hmC marker, prognosticated patient outcomes.

Conclusions

The findings indicate that 5hmC markers from cfDNA serve as effective epigenetic indicators for the non-invasive detection of ESCC metastasis and recurrence.