Corrupted coordination of epigenetic modifications leads to diverging chromatin states and transcriptional heterogeneity in CLL.
Alessandro PastoreFederico GaitiSydney X LuRyan M BrandScott KulmRonan ChaligneHongcang GuKevin Y HuangElena K StamenovaWendy BéguelinYanwen JiangRafael C SchulmanKyu-Tae KimAlicia AlonsoJohn N AllanRichard R FurmanAndreas GnirkeCatherine J WuAri M MelnickAlexander MeissnerBradley E BernsteinOmar Abdel-WahabDan A LandauPublished in: Nature communications (2019)
Cancer evolution is fueled by epigenetic as well as genetic diversity. In chronic lymphocytic leukemia (CLL), intra-tumoral DNA methylation (DNAme) heterogeneity empowers evolution. Here, to comprehensively study the epigenetic dimension of cancer evolution, we integrate DNAme analysis with histone modification mapping and single cell analyses of RNA expression and DNAme in 22 primary CLL and 13 healthy donor B lymphocyte samples. Our data reveal corrupted coherence across different layers of the CLL epigenome. This manifests in decreased mutual information across epigenetic modifications and gene expression attributed to cell-to-cell heterogeneity. Disrupted epigenetic-transcriptional coordination in CLL is also reflected in the dysregulation of the transcriptional output as a function of the combinatorial chromatin states, including incomplete Polycomb-mediated gene silencing. Notably, we observe unexpected co-mapping of typically mutually exclusive activating and repressing histone modifications, suggestive of intra-tumoral epigenetic diversity. Thus, CLL epigenetic diversification leads to decreased coordination across layers of epigenetic information, likely reflecting an admixture of cells with diverging cellular identities.
Keyphrases
- dna methylation
- gene expression
- chronic lymphocytic leukemia
- single cell
- genome wide
- rna seq
- genetic diversity
- transcription factor
- high throughput
- papillary thyroid
- high resolution
- dna damage
- copy number
- health information
- machine learning
- poor prognosis
- squamous cell carcinoma
- electronic health record
- cell therapy
- oxidative stress
- signaling pathway
- deep learning
- squamous cell
- social media
- mass spectrometry
- cell cycle arrest