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Background <p>Protein EpiScores are a novel class of DNA methylation (DNAm)-based metrics proposed to measure peripheral immune system characteristics. Although Protein EpiScores have been associated with chronic disease risk, their relationship with colorectal cancer (CRC) survival has not been investigated.</p> Methods <p>We generated new genome-wide DNAm data on pre-treatment whole blood samples from a case-control sample of 136 newly diagnosed CRC patients nested in the ColoCare Study and calculated 107 Protein EpiScores using the developer’s algorithm. Over a median follow-up of 7.3 years (range: 0.3–13.8 years), 35 (26%) patients experienced disease recurrence, and 47 (35%) died. Protein EpiScore associations with disease-free and overall survival were tested using Cox regression models, adjusted for patient and clinical characteristics, and prognostic discrimination was assessed using Harrell’s C-index.</p> Results <p>In fully-adjusted models, HCII, VEGFA, CCL17, and LGALS3BP Protein EpiScores were associated with worse disease-free survival (HRs between 1.62 and 1.71, all FDR &lt; 0.05). Adding these Protein EpiScores to traditional clinical prognosis risk factors significantly improved disease-free survival prediction (C-index: 0.64 vs 0.70, P-diff= 0.03). The LGALS3BP Protein EpiScore was associated with worse overall survival (HR: 1.80, 95% CI 1.29, 2.51,<i>P</i> = 0.0005, FDR= 0.056), and improved prediction (C-index: 0.70 vs 0.75, P-diff= 0.02). Protein EpiScores for HCII, LGALS3BP, MMP12, and VEGFA showed positive association with both disease-free and overall survival (HRs &gt; 1.5).</p> Conclusions <p>Protein EpiScores are significantly associated with CRC survival. These findings highlight biological pathways underlying CRC prognosis and support the utility of Protein EpiScores for modeling survivorship.</p>

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Blood DNA methylation-predicted plasma protein levels and colorectal cancer survival

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月1日

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  • Alicia R. Richards,
  • Maria F. Gomez,
  • Bianca I. Dowling,
  • Esther Jean-Baptiste,
  • Biljana Gigic,
  • Jane C. Figueiredo,
  • Christopher I. Li,
  • David Shibata,
  • Adetunji T. Toriola,
  • Doratha A. Byrd,
  • Cornelia M. Ulrich,
  • Paul A. Stewart,
  • Erin M. Siegel,
  • Jacob K. Kresovich

摘要

Background

Protein EpiScores are a novel class of DNA methylation (DNAm)-based metrics proposed to measure peripheral immune system characteristics. Although Protein EpiScores have been associated with chronic disease risk, their relationship with colorectal cancer (CRC) survival has not been investigated.

Methods

We generated new genome-wide DNAm data on pre-treatment whole blood samples from a case-control sample of 136 newly diagnosed CRC patients nested in the ColoCare Study and calculated 107 Protein EpiScores using the developer’s algorithm. Over a median follow-up of 7.3 years (range: 0.3–13.8 years), 35 (26%) patients experienced disease recurrence, and 47 (35%) died. Protein EpiScore associations with disease-free and overall survival were tested using Cox regression models, adjusted for patient and clinical characteristics, and prognostic discrimination was assessed using Harrell’s C-index.

Results

In fully-adjusted models, HCII, VEGFA, CCL17, and LGALS3BP Protein EpiScores were associated with worse disease-free survival (HRs between 1.62 and 1.71, all FDR < 0.05). Adding these Protein EpiScores to traditional clinical prognosis risk factors significantly improved disease-free survival prediction (C-index: 0.64 vs 0.70, P-diff= 0.03). The LGALS3BP Protein EpiScore was associated with worse overall survival (HR: 1.80, 95% CI 1.29, 2.51,P = 0.0005, FDR= 0.056), and improved prediction (C-index: 0.70 vs 0.75, P-diff= 0.02). Protein EpiScores for HCII, LGALS3BP, MMP12, and VEGFA showed positive association with both disease-free and overall survival (HRs > 1.5).

Conclusions

Protein EpiScores are significantly associated with CRC survival. These findings highlight biological pathways underlying CRC prognosis and support the utility of Protein EpiScores for modeling survivorship.