Evidence map›Paper›PMID 31631960›Full record

ArticleCancer informatics2019

Preliminary Analysis of Within-Sample Co-methylation Patterns in Normal and Cancerous Breast Samples.

Lillian Sun, Surya Namboodiri, Emily Chen, Shuying Sun

Abstract 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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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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

4 authors.

Lillian SunStanford University, Stanford, CA, USA.
Surya NamboodiriThe University of Texas at Dallas, Richardson, TX, USA.
Emily ChenBrown University, Providence, RI, USA.
Shuying SunDepartment of Mathematics, Texas State University, San Marcos, TX, USA.ORCID https://orcid.org/0000-0003-3974-6996

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

DNA methylation plays a significant role in regulating the expression of certain genes in both cancerous and normal breast tissues. It is therefore important to study within-sample co-methylation, ie, methylation patterns between consecutive sites in a chromosome. In this article, we develop 2 new methods to compare co-methylation patterns between normal and cancerous breast samples. In particular, we investigate the co-methylation patterns of 4 different methylation states/levels separately. Using these 2 methods, we focus on addressing the following questions: How often does 1 methylation state change to other methylation states and how is this change dependent on chromosome distance? What co-methylation patterns do normal and cancerous breast samples have? Do genomic sites with different methylation states/levels have different co-methylation patterns? Our results show that cancerous and normal co-methylation patterns are significantly different. We find that this difference exists even when the physical distance of 2 sites are less than 50 bases. Breast cancer cell lines tend to remain in the same methylation state more often than normal samples, especially for the no/low or high/full methylation states. We also find that the co-methylation region lengths for various methylation states (no/low, partial, and high/full methylation states) are very different. For example, the co-methylation region lengths for partial methylation regions are shorter than the unmethylated or fully methylated regions. Our research may provide a deep understanding of co-methylation patterns. These co-methylation patterns will aid in discovering and understanding new methylation events that may be related to novel biomarkers.

Indexed as

bioinformaticsbreast cancerWithin-sample co-methylation

Identifiers

PMID31631960
PMCPMC6778999

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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.