bioRxivCancer BiologyPreprint
Chromatin Landscape of Cancer Cell Lines Identifies Enhancer Subtypes
Mayinuer MaitituohetiiD, Emre ArslaniD, Ayush T. RamaniD, Christopher J. TerranovaiD, Zhiyi LiuiD, Elias OroujiiD, Sanjana SrinivasaniD, Veena KochatiD, Ming TangiD, Samirkumar B. AminiD, Jonathan E. SchulziD, Neha S. SamantiD, Anand Singh, Emmanuel Martínez-LedesmaiD, Sharmistha SarkariD, Marcus Coyle, Christopher Aaron BristowiD, Faye M. JohnsoniD, Curtis R. PickeringiD, Keila E. TorresiD, Jeffery N. MyersiD, Kunal RaiiD
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Abstract
Epigenetic aberrations are a hallmark of cancer; however, systematic chromatin state maps of cancer cells are unavailable. We generated and analyzed 803 histone mark profiles in 142 cancer cell lines and 114 human tumors belonging to 9 solid tumor types. Irrespective of their cell-of-origin, cancer cells segregate from normal tissues based on their enhancer patterns, suggesting enhancer deregulation is a fundamental epigenetic feature in cancer. Enhancer based clustering defined 5 distinct subgroups of cancer cells (EpiC1-5) with unique developmental trajectories, molecular features and dependencies. Importantly, we define a set of core TFs that are critical for EpiC-specific enhancer patterns and survival. Notably, EpiC4 represented a predominantly epigenetic, pan-cancer subtype that displays poor survival, activation and dependence on a FN1-CAV1-SRC-PI3K-AKT signaling network. Together, these data uncover enhancer heterogeneity in pan-cancer systems with identification of a novel enhancer-based subtype and identify potential new therapeutic targets associated with unique epigenetic features.
- organism: human
- assay: ChIP-seq
- research focus: chromatin & epigenetic regulation
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- approach: machine learning (classical)
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