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Epigenetic Regulation01:37

Epigenetic Regulation

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Epigenetic changes alter the physical structure of the DNA without changing the genetic sequence and often regulate whether genes are turned on or off. This regulation ensures that each cell produces only proteins necessary for its function. For example, proteins that promote bone growth are not produced in muscle cells. Epigenetic mechanisms play an essential role in healthy development. Conversely, precisely regulated epigenetic mechanisms are disrupted in diseases like cancer.
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Stratified epithelium consists of several stacked layers of cells. They provide the durability to withstand constant physical and chemical attacks. Stratified epithelium is named after the shape of the most apical layer of cells. Stratified squamous epithelium is the most common type found in the human body. In this tissue, the apical cells are squamous, whereas the basal layer contains either columnar or cuboidal cells. The basal cells divide to form new daughter cells, which gradually become...
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The glandular epithelium is made of one or more epithelial cells modified to synthesize and secrete chemical substances. Glandular epithelia can be classified based on cell number. Unicellular glands have individual secretory cells scattered across the epithelial monolayer. In contrast, multicellular glands consist of a hollow tubular duct attached to the cluster of secretory cells located in the deep pockets.
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Related Experiment Video

Updated: Jan 13, 2026

Evaluation of Biomarkers in Glioma by Immunohistochemistry on Paraffin-Embedded 3D Glioma Neurosphere Cultures
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A cellular epigenetic classification system for glioblastoma.

Dana Silverbush1,2,3, Liv Jürgensen4,5,6,7, Nelson F Freeburg1

  • 1Department of Cancer Biology, University of Pennsylvania, -Philadelphia.

Neuro-Oncology
|January 7, 2026
PubMed
Summary

This study introduces ITHresolveGBM, a novel method to analyze glioblastoma (GBM) cell composition from DNA methylation data. It refines molecular stratification and improves diagnostics by unifying bulk and single-cell profiles.

Keywords:
DNA methylation-based classificationbioinformaticscancercellular statesglioblastomasingle-cell epigenetics

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Area of Science:

  • Oncology
  • Genomics
  • Bioinformatics

Background:

  • Glioblastoma (GBM) exhibits significant cellular heterogeneity, impacting tumor progression and treatment outcomes.
  • Single-cell profiling offers detailed insights but is not feasible for large studies or clinical use.
  • Current DNA methylation diagnostics lack cellular resolution.

Purpose of the Study:

  • To develop a computational method for deconvoluting bulk DNA methylation profiles in GBM.
  • To infer cellular composition, including microenvironment cells and malignant cell differentiation states.
  • To reconcile different GBM classification systems and enhance diagnostic accuracy.

Main Methods:

  • Utilized a hierarchical non-negative matrix factorization approach (ITHresolveGBM).
  • Applied the method to deconvolve bulk DNA methylation data.
  • Integrated multi-omic single-cell data for validation.

Main Results:

  • ITHresolveGBM identified low tumor cell content as a factor affecting methylation-based classification, particularly linking the mesenchymal subtype with high immune infiltration.
  • Epigenetic deconvolution revealed a malignant cell differentiation continuum, correlating with molecular drivers (e.g., PDGFRA, TP53, EGFR) and survival.
  • The inferred continuum aligns with existing GBM classification systems.

Conclusions:

  • The ITHresolveGBM framework successfully reconciles DNA methylation and RNA-based classification systems.
  • It provides a method to integrate bulk tumor profiles with single-cell biology insights.
  • This approach refines molecular stratification and enhances GBM diagnostics.