» Articles » PMID: 34006939

From Multi-omics Integration Towards Novel Genomic Interaction Networks to Identify Key Cancer Cell Line Characteristics

Overview
Journal Sci Rep
Specialty Science
Date 2021 May 19
PMID 34006939
Citations 2
Authors
Affiliations
Soon will be listed here.
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.

Citing Articles

State of the Art of Genomic Technology in Toxicology: A Review.

Recio-Vega R, Facio-Campos R, Hernandez-Gonzalez S, Olivas-Calderon E Int J Mol Sci. 2023; 24(11).

PMID: 37298568 PMC: 10253724. DOI: 10.3390/ijms24119618.


Zinc Finger Proteins in the War on Gastric Cancer: Molecular Mechanism and Clinical Potential.

Liu S, Liu X, Lin X, Chen H Cells. 2023; 12(9).

PMID: 37174714 PMC: 10177130. DOI: 10.3390/cells12091314.

References
1.
Hanahan D, Weinberg R . Hallmarks of cancer: the next generation. Cell. 2011; 144(5):646-74. DOI: 10.1016/j.cell.2011.02.013. View

2.
Schubert D, Bode C, Kenefeck R, Hou T, Wing J, Kennedy A . Autosomal dominant immune dysregulation syndrome in humans with CTLA4 mutations. Nat Med. 2014; 20(12):1410-1416. PMC: 4668597. DOI: 10.1038/nm.3746. View

3.
Chalise P, Fridley B . Integrative clustering of multi-level 'omic data based on non-negative matrix factorization algorithm. PLoS One. 2017; 12(5):e0176278. PMC: 5411077. DOI: 10.1371/journal.pone.0176278. View

4.
Laurent C, Charmpi K, Gravelle P, Tosolini M, Franchet C, Ysebaert L . Several immune escape patterns in non-Hodgkin's lymphomas. Oncoimmunology. 2015; 4(8):e1026530. PMC: 4570141. DOI: 10.1080/2162402X.2015.1026530. View

5.
Souza T, Rieswijk L, van den Beucken T, Kleinjans J, Jennen D . Persistent transcriptional responses show the involvement of feed-forward control in a repeated dose toxicity study. Toxicology. 2016; 375:58-63. DOI: 10.1016/j.tox.2016.10.009. View