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The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features....
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Targeted DNA Methylation Analysis by Next-generation Sequencing
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Estimating breast tissue-specific DNA methylation age using next-generation sequencing data.

James R Castle1, Nan Lin1, Jinpeng Liu1

  • 1University of Kentucky Markey Cancer Center, 800 Rose Street, Lexington, KY, 40536, USA.

Clinical Epigenetics
|March 14, 2020
PubMed
Summary

We developed a new DNA methylation (DNAm) age model specifically for breast tissue, revealing that breast tumors show accelerated epigenetic aging compared to normal tissue. This breast tissue-specific clock offers insights into cancer-related aging effects.

Keywords:
AgingBreastDNA methylationEpigenetic ageNext-generation sequencing

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Area of Science:

  • Epigenetics
  • Genomics
  • Cancer Biology

Background:

  • DNA methylation (DNAm) age is a biomarker for biological aging.
  • Existing DNAm age clocks are poorly calibrated for breast tissue.
  • Breast tissue may exhibit faster aging than other body parts.

Purpose of the Study:

  • Develop a breast tissue-specific DNA methylation age model.
  • Investigate cancer-related aging effects in breast tumors.

Main Methods:

  • Generated genome-wide DNA methylation sequencing data from 459 normal, 107 tumor, and 45 paired adjacent-normal breast tissues.
  • Identified 286 breast tissue-specific clock CpGs using penalized linear regression.
  • Applied the novel model to estimate breast tissue-specific DNAm age.

Main Results:

  • The breast tissue-specific DNAm age model correlated highly with chronological age (r=0.88).
  • Breast tumors showed an average epigenetic age acceleration of 7 years.
  • Tumor tissues were significantly older in DNAm age than normal tissues (12-13 years older).
  • HER2+ and hormone-receptor positive subtypes exhibited significant DNAm age acceleration.
  • Epigenetic age acceleration varied with tumor grade and stage.

Conclusions:

  • The developed model provides biologically meaningful results for cancer-related aging in breast tumors.
  • Future research should explore the predictive value of breast tissue-specific epigenetic age acceleration for cancer development, treatment response, and survival.
  • The model's applicability to blood samples warrants further investigation.