Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Predicting aberrant CpG island methylation.

F A Feltus1, E K Lee, J F Costello

  • 1Department of Radiation Oncology and Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA 30322, USA.

Proceedings of the National Academy of Sciences of the United States of America
|October 2, 2003
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Limits on WIMP Dark Matter with NaI(Tl) Crystals in Three Years of COSINE-100 Data.

Physical review letters·2025
Same author

Integrative analysis of RNA expression signatures and recurrent genomic alterations before treatment: link to menopausal status, short-term endocrine therapy response and disease-free survival in luminal breast cancer.

ESMO open·2025
Same author

Combined Annual Modulation Dark Matter Search with COSINE-100 and ANAIS-112.

Physical review letters·2025
Same author

Improved Limit on Neutrinoless Double Beta Decay of ^{100}Mo from AMoRE-I.

Physical review letters·2025
Same author

Search for Boosted Dark Matter in COSINE-100.

Physical review letters·2023
Same author

Detection efficiency calibration for an array of fourteen HPGe detectors.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine·2023
Same journal

Chemotactic self-organization captures the dynamics of mammalian hair follicle patterning.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same journal

Tomographic imaging of superconducting order using particle-hole interference.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same journal

Inhibitory potential of autologous neutralizing antibodies sets quantitative limits on the rebound-competent HIV-1 reservoir.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same journal

Inferring epidemiological parameters under an infectious phylogeography model with visitor dynamics.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same journal

Analytical modeling for suction cup designs for skin-interfaced wearable devices.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same journal

Improving cell-free metabolism through direct integration of artificial respiratory chains.

Proceedings of the National Academy of Sciences of the United States of America·2026
See all related articles

Aberrant DNA methylation silences tumor suppressors in cancer. Researchers identified specific DNA sequence patterns that predict which CpG islands are prone to methylation, aiding cancer research.

Area of Science:

  • Genetics
  • Epigenetics
  • Cancer Biology

Background:

  • Aberrant DNA methylation of CpG islands in gene promoter regions is a key mechanism for tumor suppressor gene silencing in human cancers.
  • While certain genes are frequently methylated in specific tumor types, the reasons for this differential susceptibility remain unclear.

Purpose of the Study:

  • To investigate the intrinsic susceptibility of CpG islands to de novo methylation.
  • To identify sequence-specific features that predict methylation-prone CpG islands.

Main Methods:

  • Utilized Restriction Landmark Genome Scanning to analyze methylation susceptibility in 1,749 unselected CpG islands.
  • Overexpressed DNA cytosine-5-methyltransferase 1 (DNMT1) to induce de novo methylation.
  • Employed DNA pattern recognition and supervised learning to develop a predictive classification function.

Related Experiment Videos

Main Results:

  • Overexpression of DNMT1 increased overall CpG island methylation, but susceptibility varied significantly among loci.
  • Identified a subset of methylation-prone CpG islands (3.8%) consistently hypermethylated across DNMT1-overexpressing clones.
  • Developed a classification function based on seven novel sequence patterns, achieving 82% accuracy in distinguishing methylation-prone from methylation-resistant CpG islands.
  • No significant differences were found in size, GC content, CpG frequency, location, or promoter association between methylation-prone and resistant islands.

Conclusions:

  • CpG islands possess intrinsic differences in their susceptibility to de novo methylation.
  • The propensity of a CpG island to undergo aberrant methylation can be predicted by its DNA sequence context.