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

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 m...

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Autores principales: Sun, Lillian, Namboodiri, Surya, Chen, Emily, Sun, Shuying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6778999/
https://www.ncbi.nlm.nih.gov/pubmed/31631960
http://dx.doi.org/10.1177/1176935119880516
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author Sun, Lillian
Namboodiri, Surya
Chen, Emily
Sun, Shuying
author_facet Sun, Lillian
Namboodiri, Surya
Chen, Emily
Sun, Shuying
author_sort Sun, Lillian
collection PubMed
description 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.
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spelling pubmed-67789992019-10-18 Preliminary Analysis of Within-Sample Co-methylation Patterns in Normal and Cancerous Breast Samples Sun, Lillian Namboodiri, Surya Chen, Emily Sun, Shuying Cancer Inform Translating Cancer Methylation Data Results from Bench to Bedside Using Informatics Tools 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. SAGE Publications 2019-10-05 /pmc/articles/PMC6778999/ /pubmed/31631960 http://dx.doi.org/10.1177/1176935119880516 Text en © The Author(s) 2019 http://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Translating Cancer Methylation Data Results from Bench to Bedside Using Informatics Tools
Sun, Lillian
Namboodiri, Surya
Chen, Emily
Sun, Shuying
Preliminary Analysis of Within-Sample Co-methylation Patterns in Normal and Cancerous Breast Samples
title Preliminary Analysis of Within-Sample Co-methylation Patterns in Normal and Cancerous Breast Samples
title_full Preliminary Analysis of Within-Sample Co-methylation Patterns in Normal and Cancerous Breast Samples
title_fullStr Preliminary Analysis of Within-Sample Co-methylation Patterns in Normal and Cancerous Breast Samples
title_full_unstemmed Preliminary Analysis of Within-Sample Co-methylation Patterns in Normal and Cancerous Breast Samples
title_short Preliminary Analysis of Within-Sample Co-methylation Patterns in Normal and Cancerous Breast Samples
title_sort preliminary analysis of within-sample co-methylation patterns in normal and cancerous breast samples
topic Translating Cancer Methylation Data Results from Bench to Bedside Using Informatics Tools
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6778999/
https://www.ncbi.nlm.nih.gov/pubmed/31631960
http://dx.doi.org/10.1177/1176935119880516
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