Evidence map›Paper›PMID 31496635›Full record

ArticleCancer informatics2019

Hemimethylation Patterns in Breast Cancer Cell Lines.

Shuying Sun, Yu Ri Lee, Brittany Enfield

Open access · goldAbstract read
In one paragraph

Article in Cancer informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 35% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. Article
  3. Expression and associated epigenetic mechanisms of the CaJournal of cell communication and signaling · 2022
    Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Shuying SunDepartment of Mathematics, Texas State University, San Marcos, TX, USA.ORCID https://orcid.org/0000-0003-3974-6996
Yu Ri LeeDepartment of Mathematics, Texas State University, San Marcos, TX, USA.
Brittany EnfieldGlobal Engineering Systems, Cypress Semiconductor, Austin, TX, USA.
Texas State University · USEngineering Systems (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

DNA methylation is an epigenetic event that involves adding a methyl group to the cytosine (C) site, especially the one that pairs with a guanine (G) site (ie, CG or CpG site), in a human genome. This event plays an important role in both cancerous and normal cell development. Previous studies often assume symmetric methylation on both DNA strands. However, asymmetric methylation, or hemimethylation (methylation that occurs only on 1 DNA strand), does exist and has been reported in several studies. Due to the limitation of previous DNA methylation sequencing technologies, researchers could only study hemimethylation on specific genes, but the overall genomic hemimethylation landscape remains relatively unexplored. With the development of advanced next-generation sequencing techniques, it is now possible to measure methylation levels on both forward and reverse strands at all CpG sites in an entire genome. Analyzing hemimethylation patterns may potentially reveal regions related to undergoing tumor growth. For our research, we first identify hemimethylated CpG sites in breast cancer cell lines using Wilcoxon signed rank tests. We then identify hemimethylation patterns by grouping consecutive hemimethylated CpG sites based on their methylation states, methylation "M" or unmethylation "U." These patterns include regular (or consecutive) hemimethylation clusters (eg, "MMM" on one strand and "UUU" on another strand) and polarity (or reverse) clusters (eg, "MU" on one strand and "UM" on another strand). Our results reveal that most hemimethylation clusters are the polarity type, and hemimethylation does occur across the entire genome with notably higher numbers in the breast cancer cell lines. The lengths or sizes of most hemimethylation clusters are very short, often less than 50 base pairs. After mapping hemimethylation clusters and sites to corresponding genes, we study the functions of these genes and find that several of the highly hemimethylated genes may influence tumor growth or suppression. These genes may also indicate a progressing transition to a new tumor stage.

Indexed as

bioinformaticsbreast cancerhemimethylationMethylation

Identifiers

PMID31496635
PMCPMC6716185
OpenAlexW2970646758

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.