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From multi-omics integration towards novel genomic interaction networks to identify key cancer cell line characteristics
Cancer is a complex disease where cancer cells express epigenetic and transcriptomic mechanisms to promote tumor initiation, progression, and survival. To extract relevant features from the 2019 Cancer Cell Line Encyclopedia (CCLE), a multi-layer nonnegative matrix factorization approach is used. We...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8131752/ https://www.ncbi.nlm.nih.gov/pubmed/34006939 http://dx.doi.org/10.1038/s41598-021-90047-3 |
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author | Kuijpers, T. J. M. Kleinjans, J. C. S. Jennen, D. G. J. |
author_facet | Kuijpers, T. J. M. Kleinjans, J. C. S. Jennen, D. G. J. |
author_sort | Kuijpers, T. J. M. |
collection | PubMed |
description | Cancer is a complex disease where cancer cells express epigenetic and transcriptomic mechanisms to promote tumor initiation, progression, and survival. To extract relevant features from the 2019 Cancer Cell Line Encyclopedia (CCLE), a multi-layer nonnegative matrix factorization approach is used. We used relevant feature genes and DNA promoter regions to construct genomic interaction network to study gene–gene and gene—DNA promoter methylation relationships. Here, we identified a set of gene transcripts and methylated DNA promoter regions for different clusters, including one homogeneous lymphoid neoplasms cluster. In this cluster, we found different methylated transcription factors that affect transcriptional activation of EGFR and downstream interactions. Furthermore, the hippo-signaling pathway might not function properly because of DNA hypermethylation and low gene expression of both LATS2 and YAP1. Finally, we could identify a potential dysregulation of the CD28-CD86-CTLA4 axis. Characterizing the interaction of the epigenome and the transcriptome is vital for our understanding of cancer cell line behavior, not only for deepening insights into cancer-related processes but also for future disease treatment and drug development. Here we have identified potential candidates that characterize cancer cell lines, which give insight into the development and progression of cancers. |
format | Online Article Text |
id | pubmed-8131752 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-81317522021-05-25 From multi-omics integration towards novel genomic interaction networks to identify key cancer cell line characteristics Kuijpers, T. J. M. Kleinjans, J. C. S. Jennen, D. G. J. Sci Rep Article Cancer is a complex disease where cancer cells express epigenetic and transcriptomic mechanisms to promote tumor initiation, progression, and survival. To extract relevant features from the 2019 Cancer Cell Line Encyclopedia (CCLE), a multi-layer nonnegative matrix factorization approach is used. We used relevant feature genes and DNA promoter regions to construct genomic interaction network to study gene–gene and gene—DNA promoter methylation relationships. Here, we identified a set of gene transcripts and methylated DNA promoter regions for different clusters, including one homogeneous lymphoid neoplasms cluster. In this cluster, we found different methylated transcription factors that affect transcriptional activation of EGFR and downstream interactions. Furthermore, the hippo-signaling pathway might not function properly because of DNA hypermethylation and low gene expression of both LATS2 and YAP1. Finally, we could identify a potential dysregulation of the CD28-CD86-CTLA4 axis. Characterizing the interaction of the epigenome and the transcriptome is vital for our understanding of cancer cell line behavior, not only for deepening insights into cancer-related processes but also for future disease treatment and drug development. Here we have identified potential candidates that characterize cancer cell lines, which give insight into the development and progression of cancers. Nature Publishing Group UK 2021-05-18 /pmc/articles/PMC8131752/ /pubmed/34006939 http://dx.doi.org/10.1038/s41598-021-90047-3 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Kuijpers, T. J. M. Kleinjans, J. C. S. Jennen, D. G. J. From multi-omics integration towards novel genomic interaction networks to identify key cancer cell line characteristics |
title | From multi-omics integration towards novel genomic interaction networks to identify key cancer cell line characteristics |
title_full | From multi-omics integration towards novel genomic interaction networks to identify key cancer cell line characteristics |
title_fullStr | From multi-omics integration towards novel genomic interaction networks to identify key cancer cell line characteristics |
title_full_unstemmed | From multi-omics integration towards novel genomic interaction networks to identify key cancer cell line characteristics |
title_short | From multi-omics integration towards novel genomic interaction networks to identify key cancer cell line characteristics |
title_sort | from multi-omics integration towards novel genomic interaction networks to identify key cancer cell line characteristics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8131752/ https://www.ncbi.nlm.nih.gov/pubmed/34006939 http://dx.doi.org/10.1038/s41598-021-90047-3 |
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