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Using Epigenetic Data to Deconvolute Immune Cells in Cancer from Blood Samples.

Hatim Boughanem1,2, Sotiris Ouzounis3, Maurizio Callari4

  • 1Unidad de Gestión Clinica Medicina Interna, Lipids and Atherosclerosis Unit, Maimonides Institute for Biomedical Research of Cordoba (IMIBIC), Reina Sofia University Hospital, Córdoba, Spain. h.b.boughanem@gmail.com.

Methods in Molecular Biology (Clifton, N.J.)
|September 30, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces an RStudio workflow for analyzing DNA methylation data to understand immune cell dynamics in cancer. It enables estimation of immune cell proportions, aiding in biomarker discovery and treatment response insights.

Keywords:
450KBloodCancerEPICEpigeneticImmune cells

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Area of Science:

  • Epigenetics
  • Cancer Biology
  • Immunology

Background:

  • DNA methylation is key to gene regulation and cancer's epigenetic changes.
  • Immune cell dynamics influence cancer progression and treatment outcomes.
  • Profiling DNA methylation in immune cells offers insights into the tumor microenvironment.

Purpose of the Study:

  • To present a reproducible RStudio workflow for DNA methylation analysis and immune cell deconvolution.
  • To enable robust estimation of immune cell proportions from DNA methylation data.
  • To facilitate the identification of immune cell subsets as potential cancer biomarkers or therapeutic targets.

Main Methods:

  • High-throughput DNA methylation profiling.
  • Application of deconvolution algorithms to estimate immune cell proportions.
  • Functional analysis of identified immune cell subsets.
  • Development of an integrated RStudio workflow for preprocessing, analysis, and visualization.

Main Results:

  • The workflow allows for detailed analysis of DNA methylation patterns in cancer.
  • It enables accurate estimation of major immune cell type proportions.
  • Functional analysis can reveal significant immune cell subsets relevant to cancer.

Conclusions:

  • This workflow enhances reproducibility and efficiency in DNA methylation studies.
  • It provides valuable insights into immune cell dynamics and their role in cancer.
  • The approach aids in uncovering novel biomarkers and therapeutic strategies.