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This study introduces a novel method for detecting differentially methylated regions (DMRs) in cancer by combining DNA methylation and differential variability signals. This approach enhances the identification of early epigenetic alterations crucial for cancer detection and understanding heterogeneity.

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Area of Science:

  • Epigenetics
  • Cancer Biology
  • Bioinformatics

Background:

  • DNA methylation is critical in cancer development and heterogeneity.
  • Differential variability (DV) in DNA methylation is a key indicator of early epigenetic field defects in carcinogenesis.
  • Neighboring CpG sites exhibit high correlation, influencing methylation analysis.

Purpose of the Study:

  • To develop a novel method for detecting differentially methylated regions (DMRs) by integrating differential methylation and differential variability (DV) signals.
  • To evaluate the performance of the new method against existing methods using simulation studies.
  • To apply the method to real-world cancer data for identifying novel cancer-related DMRs and epigenetic field defects.

Main Methods:

  • A new computational method was developed to detect DMRs by combining differential methylation and DV signals between sample groups.
  • The method's performance was assessed through simulation studies, comparing it with methods using only differential methylation or DV.
  • The method was applied to DNA methylation data from The Cancer Genome Atlas (TCGA) for breast invasive carcinoma (BRCA) and kidney renal clear cell carcinoma (KIRC), and from Gene Expression Omnibus (GEO) for BRCA.

Main Results:

  • The new method demonstrated superior performance in simulations compared to existing methods when true DMRs exhibit both differential methylation and DV.
  • Application to TCGA and GEO datasets identified additional cancer-related DMRs in BRCA and KIRC that were missed by single-signal methods.
  • Replication analyses confirmed the reproducibility of DMRs detected using DV in independent BRCA datasets.
  • The new method uniquely identified epigenetic field defects in BRCA, comparing tumor-adjacent normal tissues with normal tissues from cancer-free individuals, and confirmed their enrichment in breast cancer progression.

Conclusions:

  • Combining differential methylation and DV signals provides a more powerful approach for DMR detection in cancer.
  • The novel method enhances the identification of cancer-related DMRs and epigenetic field defects, offering insights into early carcinogenesis.
  • The findings highlight the importance of DV in understanding cancer heterogeneity and detecting epigenetic alterations crucial for early cancer detection and prevention strategies.