Epigenomic tensor predicts disease subtypes and reveals constrained tumor evolution
Jacob R. Leistico,
Priyanka Saini,
Christopher R. Futtner,
Miroslav Hejna,
Yasuhiro Omura,
Pritin N. Soni,
Poorva Sandlesh,
Magdy Milad,
Jian-Jun Wei,
Serdar Bulun,
J. Brandon Parker,
Grant D. Barish,
Jun S. Song,
Debabrata Chakravarti
Affiliations
Jacob R. Leistico
Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL, USA; Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
Priyanka Saini
Department of Obstetrics and Gynecology, Northwestern University, Chicago, IL, USA; Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
Christopher R. Futtner
Department of Medicine, Northwestern University, Chicago, IL, USA; Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
Miroslav Hejna
Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL, USA; Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
Yasuhiro Omura
Department of Medicine, Northwestern University, Chicago, IL, USA; Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
Pritin N. Soni
Department of Obstetrics and Gynecology, Northwestern University, Chicago, IL, USA; Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
Poorva Sandlesh
Department of Obstetrics and Gynecology, Northwestern University, Chicago, IL, USA; Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
Magdy Milad
Department of Obstetrics and Gynecology, Northwestern University, Chicago, IL, USA; Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
Jian-Jun Wei
Department of Pathology, Northwestern University, Chicago, IL, USA; Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, IL, USA; Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
Serdar Bulun
Department of Obstetrics and Gynecology, Northwestern University, Chicago, IL, USA; Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
J. Brandon Parker
Department of Obstetrics and Gynecology, Northwestern University, Chicago, IL, USA; Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
Grant D. Barish
Department of Medicine, Northwestern University, Chicago, IL, USA; Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
Jun S. Song
Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL, USA; Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA; Cancer Center at Illinois, University of Illinois at Urbana-Champaign, Urbana, IL, USA; Corresponding author
Debabrata Chakravarti
Department of Obstetrics and Gynecology, Northwestern University, Chicago, IL, USA; Department of Pharmacology, Northwestern University, Chicago, IL, USA; Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, IL, USA; Corresponding author
Summary: Understanding the epigenomic evolution and specificity of disease subtypes from complex patient data remains a major biomedical problem. We here present DeCET (decomposition and classification of epigenomic tensors), an integrative computational approach for simultaneously analyzing hierarchical heterogeneous data, to identify robust epigenomic differences among tissue types, differentiation states, and disease subtypes. Applying DeCET to our own data from 21 uterine benign tumor (leiomyoma) patients identifies distinct epigenomic features discriminating normal myometrium and leiomyoma subtypes. Leiomyomas possess preponderant alterations in distal enhancers and long-range histone modifications confined to chromatin contact domains that constrain the evolution of pathological epigenomes. Moreover, we demonstrate the power and advantage of DeCET on multiple publicly available epigenomic datasets representing different cancers and cellular states. Epigenomic features extracted by DeCET can thus help improve our understanding of disease states, cellular development, and differentiation, thereby facilitating future therapeutic, diagnostic, and prognostic strategies.
