From multi-omics integration towards novel genomic interaction networks to identify key cancer cell line characteristics

Abstract 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...

Full description

Bibliographic Details
Main Authors: T. J. M. Kuijpers, J. C. S. Kleinjans, D. G. J. Jennen
Format: Article
Language:English
Published: Nature Publishing Group 2021-05-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-021-90047-3
id doaj-f77ae54171204d649e417f2c0fbed7de
record_format Article
spelling doaj-f77ae54171204d649e417f2c0fbed7de2021-05-23T11:32:07ZengNature Publishing GroupScientific Reports2045-23222021-05-0111111110.1038/s41598-021-90047-3From multi-omics integration towards novel genomic interaction networks to identify key cancer cell line characteristicsT. J. M. Kuijpers0J. C. S. Kleinjans1D. G. J. Jennen2Department of Toxicogenomics, GROW School for Oncology and Developmental Biology, Maastricht UniversityDepartment of Toxicogenomics, GROW School for Oncology and Developmental Biology, Maastricht UniversityDepartment of Toxicogenomics, GROW School for Oncology and Developmental Biology, Maastricht UniversityAbstract 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.https://doi.org/10.1038/s41598-021-90047-3
collection DOAJ
language English
format Article
sources DOAJ
author T. J. M. Kuijpers
J. C. S. Kleinjans
D. G. J. Jennen
spellingShingle T. J. M. Kuijpers
J. C. S. Kleinjans
D. G. J. Jennen
From multi-omics integration towards novel genomic interaction networks to identify key cancer cell line characteristics
Scientific Reports
author_facet T. J. M. Kuijpers
J. C. S. Kleinjans
D. G. J. Jennen
author_sort T. J. M. Kuijpers
title 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_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_sort from multi-omics integration towards novel genomic interaction networks to identify key cancer cell line characteristics
publisher Nature Publishing Group
series Scientific Reports
issn 2045-2322
publishDate 2021-05-01
description Abstract 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.
url https://doi.org/10.1038/s41598-021-90047-3
work_keys_str_mv AT tjmkuijpers frommultiomicsintegrationtowardsnovelgenomicinteractionnetworkstoidentifykeycancercelllinecharacteristics
AT jcskleinjans frommultiomicsintegrationtowardsnovelgenomicinteractionnetworkstoidentifykeycancercelllinecharacteristics
AT dgjjennen frommultiomicsintegrationtowardsnovelgenomicinteractionnetworkstoidentifykeycancercelllinecharacteristics
_version_ 1721429643566776320