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An Epigenomic fingerprint of human cancers by landscape interrogation of super enhancers at the constituent level.
Liu, Xiang; Gillis, Nancy; Jiang, Chang; McCofie, Anthony; Shaw, Timothy I; Tan, Aik-Choon; Zhao, Bo; Wan, Lixin; Duckett, Derek R; Teng, Mingxiang.
Afiliação
  • Liu X; Department of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, Florida, United States of America.
  • Gillis N; Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, Florida, United States of America.
  • Jiang C; Department of Molecular Oncology, Moffitt Cancer Center, Tampa, Florida, United States of America.
  • McCofie A; Department of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, Florida, United States of America.
  • Shaw TI; Department of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, Florida, United States of America.
  • Tan AC; Department of Oncological Sciences, Huntsman Cancer Institute, The University of Utah, Salt Lake City, Utah, United States of America.
  • Zhao B; Division of Infectious Disease, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States of America.
  • Wan L; Department of Molecular Oncology, Moffitt Cancer Center, Tampa, Florida, United States of America.
  • Duckett DR; Department of Drug Discovery, Moffitt Cancer Center, Tampa, Florida, United States of America.
  • Teng M; Department of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, Florida, United States of America.
PLoS Comput Biol ; 20(2): e1011873, 2024 Feb.
Article em En | MEDLINE | ID: mdl-38335222
ABSTRACT
Super enhancers (SE), large genomic elements that activate transcription and drive cell identity, have been found with cancer-specific gene regulation in human cancers. Recent studies reported the importance of understanding the cooperation and function of SE internal components, i.e., the constituent enhancers (CE). However, there are no pan-cancer studies to identify cancer-specific SE signatures at the constituent level. Here, by revisiting pan-cancer SE activities with H3K27Ac ChIP-seq datasets, we report fingerprint SE signatures for 28 cancer types in the NCI-60 cell panel. We implement a mixture model to discriminate active CEs from inactive CEs by taking into consideration ChIP-seq variabilities between cancer samples and across CEs. We demonstrate that the model-based estimation of CE states provides improved functional interpretation of SE-associated regulation. We identify cancer-specific CEs by balancing their active prevalence with their capability of encoding cancer type identities. We further demonstrate that cancer-specific CEs have the strongest per-base enhancer activities in independent enhancer sequencing assays, suggesting their importance in understanding critical SE signatures. We summarize fingerprint SEs based on the cancer-specific statuses of their component CEs and build an easy-to-use R package to facilitate the query, exploration, and visualization of fingerprint SEs across cancers.
Assuntos

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Super Intensificadores / Neoplasias Tipo de estudo: Risk_factors_studies Limite: Humans Idioma: En Revista: PLoS Comput Biol / PloS comput. biol / PloS computational biology Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Super Intensificadores / Neoplasias Tipo de estudo: Risk_factors_studies Limite: Humans Idioma: En Revista: PLoS Comput Biol / PloS comput. biol / PloS computational biology Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos