Epigenome Chaos: Stochastic and Deterministic DNA Methylation Events Drive Cancer Evolution
Abstract
:Simple Summary
Abstract
1. Introduction
2. Cancer Evolution
3. Genome Instability (Genome Chaos)
4. Epigenome Chaos
5. Mechanisms of de Novo DNA Methylation
6. New Tools for DNA Methylation Analysis
7. Epialleles-Based Analysis (EBA)
- AmpliMethProfiler, a python-based pipeline, extracts and performs statistical epihaplotype analysis of amplicons from targeted deep bisulfite sequences. This tool investigates the methylation diversity by directly extracting the methylation profiles (epihaplotypes) at a single locus in the sequence population [84,86]. Using this high-throughput approach, the epihaplotypes can be treated as haploid organisms with a specific frequency in the population (Shannon Entropy).
- MethCoresProfiler, a R-based pipeline, traces and tracks CpGs in the same phase (methylated or not methylated cores) shared by families of epialleles by calculating their frequency in the population (MethCore Index), the frequency normalized to the mean methylation (Clonality Index), and the association index between the CpGs belonging to the same core normalized to the average methylation of the population of sequences (Entanglement Index) [83]. This tool is able to recognize the original epigenetic ancestor from which the molecules of different epialleles derive, considering each addition or removal of a methyl groups as independent events. This method allows the reconstruction of the evolution of families of epialleles from a common ancestor. Note that the frequency of individual epialleles is usually not statistically significant, while the frequency of the common signature (core) is significant. This tool analyses amplicons from targeted deep bisulfite sequencing and allows the analysis of several samples longitudinally.
- Methclone extracts and performs statistical epihaplotype analysis for each locus from genome-wide DNA NGS data (RRBS and WGBS). It is based on the comparison between two samples longitudinally and identifies the epigenetic loci hosting large clonal variations. It quantifies epiallele shift(s), as the Hamming distance and the frequency of single epialleles [85].
8. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Abbreviations
APAF-1 | apoptotic protease activating factor 1 |
ASXL | additional sex combs-like |
ATM | ATM serine/threonine kinase or ataxia-telangiectasia mutated |
BRCA1 | breast cancer type 1 |
C | cytosine |
CDKN2A | Cyclin Dependent Kinase Inhibitor 2A |
CDKN2B | Cyclin Dependent Kinase Inhibitor 2B |
CDK CpG | cyclin-dependent kinase cytosine-guanine dinucleotides cluster |
DNMT1 | DNA methyl-transferase 1 |
DNMT3a | DNA methyl-transferase 3A |
DAPK | Death Associated Protein Kinase |
DMC | differentially methylated cytosines |
DMR | differentially methylated regions |
DSB | double strand break |
EBA | Epialleles-Based Analysis |
GFP | green fluorescence protein |
HR | homologous repair |
hMLH1 | MutL (E. Coli) Homolog 1 |
INK4 | INhibitors of CDK4-CDK6 |
ARF | alternate open reading frame |
KRAS | Kirsten rat sarcoma viral oncogene homolog |
LOI | loss of imprinting |
MGMT | O6-methylguanine-DNA methyltransferase |
ROS | reactive oxygen species |
RRBS | reduced representation bisulfite sequencing |
TAD | topologically associating domains |
TGF-β1 | Transforming growth factor beta1 |
TAD | topologically associating domains |
TSS | transcription start site |
TET2 | Ten-Eleven Translocation |
WGBS | whole-genome bisulfite sequencing |
WIF1 | WNT Inhibitory Factor 1 |
ZNF304 | Zinc Finger Protein 304 |
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Russo, G.; Tramontano, A.; Iodice, I.; Chiariotti, L.; Pezone, A. Epigenome Chaos: Stochastic and Deterministic DNA Methylation Events Drive Cancer Evolution. Cancers 2021, 13, 1800. https://doi.org/10.3390/cancers13081800
Russo G, Tramontano A, Iodice I, Chiariotti L, Pezone A. Epigenome Chaos: Stochastic and Deterministic DNA Methylation Events Drive Cancer Evolution. Cancers. 2021; 13(8):1800. https://doi.org/10.3390/cancers13081800
Chicago/Turabian StyleRusso, Giusi, Alfonso Tramontano, Ilaria Iodice, Lorenzo Chiariotti, and Antonio Pezone. 2021. "Epigenome Chaos: Stochastic and Deterministic DNA Methylation Events Drive Cancer Evolution" Cancers 13, no. 8: 1800. https://doi.org/10.3390/cancers13081800