Dissecting super-enhancer heterogeneity: time to re-examine cancer subtypes?

Tan Wu; Hao Huang; Xin Wang

doi:10.1016/j.tig.2022.06.006

Dissecting super-enhancer heterogeneity: time to re-examine cancer subtypes?

Tan Wu, Hao Huang, Xin Wang^*

^*Corresponding author for this work

Jockey Club College of Veterinary Medicine and Life Sciences

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

4 Citations (Scopus)

56 Downloads (CityUHK Scholars)

Abstract

The heterogeneity of transcriptional regulations by super-enhancers (SEs) is poorly understood in human cancers. Herein, we summarize a bioinformatics workflow for genome-wide SE profiling and identification of subtype-specific SEs and regulatory networks. Dissecting SE heterogeneity provides new insights into cancer biology and alternative therapeutic strategies for cancer precision medicine.

Original language	English
Pages (from-to)	1199-1203
Number of pages	5
Journal	Trends in Genetics
Volume	38
Issue number	12
Online published	5 Jul 2022
DOIs	https://doi.org/10.1016/j.tig.2022.06.006
Publication status	Published - Dec 2022

Funding

The present work was supported by a grant from Guangdong Basic and Applied Basic Research Foundation (Project No. 2019B030302012), a grant from Shenzhen Science, Technology and Innovation Commission (Project No. 基2020N368), a start-up fund from the Chinese University of Hong Kong (Project No. 4937084), and grants from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. 11103718, 11103619, 11103921), awarded to X.W.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Research Keywords

super-enhancer
cancer subtype
heterogeneity
transcription regulation
multi-omics
regulatory network

Publisher's Copyright Statement

This full text is made available under CC-BY-NC-ND 4.0. https://creativecommons.org/licenses/by-nc-nd/4.0/

RGC Funding Information

RGC-funded

Access Output

10.1016/j.tig.2022.06.006

108597538.pdfFinal Published version, 647 KBLicence: CC BY-NC-ND

Other Access Options

Check CityUHK Library

Permanent Link

Right click to copy link

Cite this

@article{20c7886ed623498da104dc4a97d9a3ae,

title = "Dissecting super-enhancer heterogeneity: time to re-examine cancer subtypes?",

abstract = "The heterogeneity of transcriptional regulations by super-enhancers (SEs) is poorly understood in human cancers. Herein, we summarize a bioinformatics workflow for genome-wide SE profiling and identification of subtype-specific SEs and regulatory networks. Dissecting SE heterogeneity provides new insights into cancer biology and alternative therapeutic strategies for cancer precision medicine.",

keywords = "super-enhancer, cancer subtype, heterogeneity, transcription regulation, multi-omics, regulatory network",

author = "Tan Wu and Hao Huang and Xin Wang",

year = "2022",

month = dec,

doi = "10.1016/j.tig.2022.06.006",

language = "English",

volume = "38",

pages = "1199--1203",

journal = "Trends in Genetics",

issn = "0168-9525",

publisher = "Elsevier Ltd.",

number = "12",

}

TY - JOUR

T1 - Dissecting super-enhancer heterogeneity

T2 - time to re-examine cancer subtypes?

AU - Wu, Tan

AU - Huang, Hao

AU - Wang, Xin

PY - 2022/12

Y1 - 2022/12

N2 - The heterogeneity of transcriptional regulations by super-enhancers (SEs) is poorly understood in human cancers. Herein, we summarize a bioinformatics workflow for genome-wide SE profiling and identification of subtype-specific SEs and regulatory networks. Dissecting SE heterogeneity provides new insights into cancer biology and alternative therapeutic strategies for cancer precision medicine.

AB - The heterogeneity of transcriptional regulations by super-enhancers (SEs) is poorly understood in human cancers. Herein, we summarize a bioinformatics workflow for genome-wide SE profiling and identification of subtype-specific SEs and regulatory networks. Dissecting SE heterogeneity provides new insights into cancer biology and alternative therapeutic strategies for cancer precision medicine.

KW - super-enhancer

KW - cancer subtype

KW - heterogeneity

KW - transcription regulation

KW - multi-omics

KW - regulatory network

UR - http://www.scopus.com/inward/record.url?scp=85133658735&partnerID=8YFLogxK

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85133658735&origin=recordpage

U2 - 10.1016/j.tig.2022.06.006

DO - 10.1016/j.tig.2022.06.006

M3 - RGC 21 - Publication in refereed journal

SN - 0168-9525

VL - 38

SP - 1199

EP - 1203

JO - Trends in Genetics

JF - Trends in Genetics

IS - 12

ER -

Dissecting super-enhancer heterogeneity: time to re-examine cancer subtypes?

Abstract

Funding

UN SDGs

Research Keywords

Publisher's Copyright Statement

RGC Funding Information

Access Output

Other Access Options

Permanent Link

Other Files and Links

Fingerprint

GRF: Overcoming the Intratumor Heterogeneity By Multi-Scale Spatial Characterizations of Tumor Microenvironment for Integrative Colorectal Cancer Classification

GRF: Dissecting Age-dependent Molecular Heterogeneity of Colorectal Cancer and Establishing a Probabilistic Model for Robust Prediction of High-risk Young-onset Colorectal Cancer Patients

GRF: Multi-omic Molecular Subtyping of Ovarian High-grade Serous Carcinoma and Multidimensional Network Inference for Dissecting the Mesenchymal Subtype Specific Regulatory Mechanisms

Cite this

Dissecting super-enhancer heterogeneity: time to re-examine cancer subtypes?

Abstract

Funding

UN SDGs

Research Keywords

Publisher's Copyright Statement

RGC Funding Information

Access Output

Other Access Options

Permanent Link

Other Files and Links

Fingerprint

Projects

GRF: Overcoming the Intratumor Heterogeneity By Multi-Scale Spatial Characterizations of Tumor Microenvironment for Integrative Colorectal Cancer Classification

GRF: Dissecting Age-dependent Molecular Heterogeneity of Colorectal Cancer and Establishing a Probabilistic Model for Robust Prediction of High-risk Young-onset Colorectal Cancer Patients

GRF: Multi-omic Molecular Subtyping of Ovarian High-grade Serous Carcinoma and Multidimensional Network Inference for Dissecting the Mesenchymal Subtype Specific Regulatory Mechanisms

Cite this